Improving Drug Design: An Update on Recent Applications of

Review pubs.acs.org/crt

Improving Drug Design: An Update on Recent Applications of Efficiency Metrics, Strategies for Replacing Problematic Elements, and Compounds in Nontraditional Drug Space Nicholas A. Meanwell* Department of Discovery Chemistry, Bristol-Myers Squibb Research & Development, Wallingford, Connecticut 06492, United States ABSTRACT: Drug discovery and development is a complex and lengthy enterprise that suffers from high rates of candidate attrition at all stages of the process. The physical, biological, and toxicological properties of a drug candidate are inextricably linked to its structure, and once a molecule has been synthesized, all subsequent studies along the development path are focused only on assessing and understanding its properties in greater detail. Unfortunately, a full prediction of the biological properties of a molecule from an analysis of its 2or 3-dimensional structure is currently beyond our expertise. This backdrop mandates that considerable care be taken at the design stage if a molecule is to be successful in testing a mechanistic concept underlying a disease process and to progress into late stage clinical trials and, ultimately, marketing approval. While there are multiple potential causes of candidate attrition, an introspective analysis of drug design practices over the past decade has focused attention on the perception that contemporary molecules are unnecessarily obese, burdened by high molecular weight and excessive lipophilicity. This practice is believed to have its roots in the singular pursuit of enhancing potency during lead optimization rather than adopting a more holistic approach to drug design that gives broader consideration to how structural features affect developability properties. In an effort to provide the medicinal chemistry community with practical guideposts to enhancing compound quality in the drug design phase and which can readily be applied, a series of efficiency indices have been proposed that attempt to define aspects of compound quality in the context of a series of physicochemical parameters. Of these metrics, lipophilic ligand efficiency (LLE or LipE), which provides an index of the dependence of the potency of a molecule on its intrinsic lipophilicity, has been characterized as the most robust metric that has potential for broad-based application. In this review, after describing the background literature behind the derivation of efficiency metrics and approaches to assessing compound aesthetics, synopses of some recent practical application in lead optimization campaigns are presented. However, molecules that fall into space beyond that associated with traditional drug-like properties are an important part of the current and future landscape, exemplified by the summary of direct acting hepatitis C virus NS3 and NS5A inhibitors that have transformed clinical therapy for this chronic disease. While drug development in nontraditional drug-like space is more challenging and the rules for compound quality will be different with much still to be understood, careful and disciplined drug design practices will be an essential element of success.

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CONTENTS

1. Introduction 2. Emergence of Efficiency Metrics 2.1. Analyses of Marketed Drug Properties 2.2. Drug−Target Binding Kinetics and Ligand Efficiency (LE), Size-Independent Ligand Efficiency (SILE), and Group Efficiency (GE) 2.3. Synopsis of Some of the Effects of Lipophilicity 2.4. Lipophilic Ligand Efficiency (LLE or LipE), LLEAT, and Lipophilicity-Corrected Ligand Efficiency (LELP) 2.5. Central Nervous System Drug Space 2.6. “Rule of 5” Metric and Other Prognosticators of Bioavailability

© 2016 American Chemical Society

3. Understanding the Sources of Problematic Lipophilicity 3.1. Fraction of sp3 Carbon Atoms 3.2. Aromatic Ring Count and Compound Properties 3.3. Solubility Forecast Index (SFI) and Property Forecast Index (PFI) 3.4. Pedigree of Aromatic Heterocycles in Drug Discovery

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Special Issue: Toxicology Strategies for Drug Discovery - Present and Future

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Received: February 3, 2016 Published: March 14, 2016 564

DOI: 10.1021/acs.chemrestox.6b00043 Chem. Res. Toxicol. 2016, 29, 564−616

Chemical Research in Toxicology 3.5. Estimating Drug Quality: The Quantitative Estimate of Drug-Likeness (QED) Metric 4. Some Recent Examples of the Application of Lipophilic Efficiency Indices in Drug Design 4.1. Validity of the Lipophilic Ligand Efficiency (LLE or LipE) Metric and Its Correlation with Binding Enthalpy 4.2. Discovery of Maraviroc 4.3. Controlling cLog P for Ligands Targeting Lipophilic Binding Sites: Cannabinoid CB2 Agonists 4.4. Controlling cLog P for Ligands Targeting Lipophilic Binding Sites: Cholesteryl Ester Transfer Protein (CETP) Inhibitors 4.5. LLE (LipE) and Inhibitors of Acetyl-CoA Carboxylases (ACCs) 4.6. Monitoring LLE (LipE) while Optimizing HIV1 NNRTIs 4.7. Monitoring LLE (LipE) while Optimizing Epidermal Growth Factor Receptor (EGFR) Inhibitors 4.8. Monitoring LLE (LipE) While Optimizing Selective Androgen Receptor Modulators (SARMs) 4.9. Monitoring LLE (LipE) while Optimizing Protein Arginine Methyltransferase 5 (PRMT5) Inhibitors 4.10. Lowering the Log D of HCV NS5B Inhibitors to Reduce Promiscuity 4.11. Application CNS MPO Scores in the Optimization of γ-Secretase Inhibitors and Modulators: The Use of Lipophilic Metabolism Efficiency (LipMetE) 4.12. Monitoring LLE (LipE) and CNS MPO Scores while Optimizing for Brain Penetrant Leucine Rich Repeat Kinase 2 (LRRK2) Inhibitors 4.13. Monitoring LELP during Lead Optimization of Malaria N-Myristoyltransferase Inhibitors 5. Approaches to Increasing FSP3 in Drug Design 5.1. Bicyclo[1.1.1]pentane as a Phenyl Isostere in γ-Secretase Inhibitors 5.2. Probing Phenyl Isosteres in the ABL1 Kinase Inhibitor Imatinib 5.3. Utility of a Cyclopropyl Ring as a Phenyl Replacement in Factor Xa Inhibitors 5.4. Phenyl Mimics in Oxytocin Antagonists 5.6. Replacing a Problematic Diaminopyridine Toxicophore in Bradykinin BK1 Antagonists 5.6. Reducing sp2 Carbon Atom Count in RORγ Inhibitors 5.7. Modulating Fsp3 Count and Monitoring Efficiency Metrics in Inhibitors of Diacylglycerol Acyltransferase 2 5.8. Increasing Fsp 3 Count in ATR Kinase Inhibitors 6. Compounds That Explore Chemical Space beyond the “Rule of 5” Criteria 6.1. Orally Bioavailable Bcl-2-Bak Protein−Protein Interaction Inhibitors 6.2. Orally Bioavailable Taxane Derivatives 6.3. HCV NS5A Inhibitors 6.4. HCV NS3 Protease Inhibitors

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7. Concluding Remarks Author Information Corresponding Author Notes Biography Abbreviations References

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1. INTRODUCTION The practice of the discovery and development of drug candidates designed to address unmet medical need has evolved considerably over the last century as our knowledge and understanding of disease biology and compound design has deepened and become more sophisticated.1 The clinical application of small molecule therapeutics has had a profound impact on human longevity and well-being, with recent notable successes including the control of human immunodeficiency virus 1 (HIV-1) replication using combination regimens and the drug cocktails that have been developed to increase cure rates in hepatitis C virus (HCV) infection to well over 90%.2−8 However, the drug discovery and development enterprise is complex and arduous, and the attrition rate for drug candidates throughout the continuum of this process has remained stubbornly high, despite significant advances in preclinical profiling that have improved predictions of absorption, distribution, metabolism and excretion (ADME), and several aspects of off-target toxicology.7−10 In 1991, the major causes of drug failure were poor pharmacokinetic (PK) properties (40%), lack of efficacy (30%), and toxicological issues (21%); by 2000, the complexion had changed considerably, with toxicity (32%) and efficacy issues (26%) being the major contributors, while PK issues accounted for just 8% of the failures (Table 1).9 The

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Table 1. Sources of Drug Candidate Attrition year toxicity lack of efficacy PK/bioavailability CMC issues commercial cost of goods

586 588 589 589

1991 21% 30% 40% 0% 5% 0%

2000 32% 26% 8% 4% 20% 8%

2011−2012 28% 56% not reported not reported 17%

590

combination of CMC issues, commercial reasons, and cost of goods together amounted to 5% of the failures in 1991, but by 2000, these factors accounted for 32%, with commercial reasons the major contributor at 20%, reflecting an escalation in the competitive nature of the pharmaceutical business environment. By 2012, this scenario appeared to be little changed with Phase I and II failures due to a lack of efficacy estimated at 56%, toxicity accounting for 28%, while strategic and business reasons amounted to 17% of the attrition.11 In what is probably the most contemporary survey, the fates of 812 orally administered drug candidates nominated for clinical evaluation at four major pharmaceutical houses between 2000 and 2010, inclusive, were studied, revealing a somewhat different picture within this microcosm of the pharmaceutical industry.12 Of the 812 compounds surveyed, the fates of 808 were known with 605 (74%) terminated, 365 (45%) before reaching clinical studies, while 193 (23%) were still in development at the time of article submission.12 Nonclinical toxicology was determined to be the major cause of candidate failure (240, 40%), with

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Table 2. Changes in Physicochemical Parameters Associated with Oral Drugs over Timea

number of compounds MW cLog P % PSA ΣOH + NH (HBDs) ΣO+N ΣHBAs number of rotatable bonds (RB) number of rings a

oral drugs pre-1983

oral drugs 1983−2002

difference in mean values between pre-1983 and 1983−2002 periods

properties for oral drugs launched between 1993 and 2002

864

329

331 2.27 21.1 1.81 5.14 2.95 4.97

377 2.50 21.0 1.77 6.33 3.74 6.42

14% 10% 0% −2% 23% 27% 29%

382 2.61 21.2 1.80 6.32 3.82 6.58

2.56

2.88

13%

3.02

154

All data are mean values.

highly complex nature of drug discovery means that simple solutions are unlikely.10,31,32 While a deeper understanding of the science underlying disease processes may help with target selection and the problem of poor efficacy, the issue of toxicity for small molecule drugs will always be challenging given the limited mechanistic insights that are typically gleaned from compound failures.10

clinical toxicology accounting for an additional 68 (11%) of the compounds. Inadequate PK or poor formulation properties were responsible for the termination of 38 (6%) of the candidates, 55 (9%) failed because of a lack of clinical efficacy, and scientific reasons accounted for an additional 33 compounds (5%). Portfolio rationalization and commercial reasons represented a major contribution to candidate attrition, combining to account for a total of 164 compounds, 28% of the cohort. The majority of the portfolio rationalization casualties occurred during the 2006−2010 time period, reflecting an increase in the competitive nature of the business environment and the associated turbulence within an industry responding to significant change, restructuring, and mergers and acquisitions. In a separate and more broadly encompassing study, a large scale analysis of the clinical success rates for 835 biotechnology, specialty, and large pharmaceutical firms who collectively advanced 4,451 drugs between 2003 and 2011 was conducted.13 This analysis indicated that efficacy issues were the major cause of attrition both for Phase 3 (40%) compounds and of NDA/BLA submissions (48%).13 Safety problems accounted for 9% of failures in Phase III and 31% of the NDA/BLAs, while commercial reasons were a significant factor at both stages of development, accounting for 18% of Phase 3 drugs and 8% of NDA/BLA candidates, with the remainder failing for reasons unknown. The compiled statistics indicated that 64.5% of compounds successfully navigated Phase I clinical studies, while 32.4% passed Phase II criteria for advancement, and 60.1% of this cohort (19% of the total) were successful in completing Phase III trials. The probability of FDA approval after NDA/BLA submission was 83.2%; however, overall only 10.4% of compounds entering clinical trials achieved this milestone. An alternative view has estimated overall success rates of just 4.1%; however, a specific focus on the attrition associated with HCV drug development revealed that while a cohort of 712 drug candidates were advanced between 1995 and 2014, only 12 small molecules and biologic drugs (2%) had been approved in a major worldwide market by early 2015, although recent FDA decisions have significantly increased this number.14 Not surprisingly, these statistics have been viewed as an industry in crisis and the subject of extensive discourse. Commentators have offered several potential approaches to addressing the underlying issues and have focused on all aspects of the process, ranging from target selection to organizational and operational performance.15−30 Although the number of FDA drug approvals in 2014 was viewed as an improvement over previous years and that tally was surpassed in 2015, the

2. EMERGENCE OF EFFICIENCY METRICS 2.1. Analyses of Marketed Drug Properties. As part of the response to the observations made on the decline in drug approvals that occurred in the latter part of the 1990s, a school of thought began to develop in the medicinal chemistry community that was based on an introspective scrutiny of evolving drug design practices. This initiative had its roots in a detailed analysis of the physicochemical properties of marketed, orally administered drugs that were developed over the course of the 20th century.33−38 Data on molecular weight (MW), lipophilicity (cLog P), percentage of polar surface area (PSA), the number of H-bond donors and acceptors (HBDs and HBAs), the number of O and N atoms, the number of rotatable bonds (RBs), and ring count were compiled and analyzed for changes over time.33−38 A comparison of these properties for drugs marketed before 1983 with those marketed in the 1983− 2002 time period revealed trends in which all properties with the exception of %PSA and the number of HBDs had increased, although the percent increase in cLog P was less than that for the other properties (Table 2).36 By adopting a closer focus, much of the increase in the mean values of these properties between 1983 and 2002 was attributable to the latter decade of the study period; data are also captured in Table 2. Notably, the absence of a significant change in %PSA and the number of HBDs over the study period was viewed as the result of a natural filter for orally absorbed drugs since these are key factors in membrane permeability. Recognizing that compounds marketed in the 1993−2002 time frame had their design origins 10−15 years earlier, recent analyses have attempted to glean a more contemporary view of drug design practices by evaluating the structural matter in patent applications filed between 2000 and 2010.38−40 An analysis of the patent estate originating with the four major drug developers GlaxoSmithKline, Pfizer, Astra-Zeneca, and Merck revealed that median cLog P (4.1) and MW (450 Da) values for all of the compounds emanating from these companies were higher than those for drugs launched in the 1990−2006 period where the median cLog P and MW values were 3.1 and 432 Da, respectively.38 In a broader study that 566



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Since the dominant force associated with the binding energy of hydrophobic groups is a favorable desolvation entropy arising from the release of ordered H2O molecules, it is much easier to optimize this parameter since it has been estimated that burying a carbon atom from solvent contributes approximately 25 cal/ mol/Ǻ 2 to binding affinity. In the absence of isothermal titration calorimetry (ITC) data to finesse the underlying thermodynamic signature of a drug−target interaction, it can be challenging to understand the effect of changes to a structure on the fundamental energetics of the process. Increasing the lipophilic burden of a molecule will often lead to enhanced affinity, and such compounds may appear to represent an advance in a lead optimization campaign based on the assumption that increased potency will equate with improved selectivity, higher cell penetration, and a lower dose.41 However, this approach often results in large hydrophobic drug candidates with less than ideal developability properties, a phenomenon that has most likely been encouraged by the observation that membrane permeability for larger molecules is facilitated by higher lipophilicity.42,43,46,47 Some targets, particularly protein−protein interactions, require large ligands that explore nontraditional drug space in order to demonstrate a therapeutic effect, and identifying molecules of this type for development will demand some refinement of the rules associated with oral drug design.48−55 Nature may provide some insight and guidance into how to design molecules within this class that demonstrate acceptable membrane permeability and PK properties based on the observation that the 11 residue cyclic peptide cyclosporine A and its analogues are orally bioavailable.48−55

analyzed compounds claimed in patent applications from 18 large pharmaceutical houses published between 2000 and 2010, mean cLog P values ranged from 3.51 to 4.48, while the mean MW ranged from 427 to 494 Da, confirming a trend toward higher values than the drugs launched in the 1990−2006 interval.39 These studies also highlighted significant differences in drug design practices between companies, with patented compounds from Pfizer and Astra-Zeneca, two organizations that have emphasized an appreciation of physicochemical properties in the drug design phase, falling close to or at the lower end of the mean values of both parameters. The phenomenon of corporate design practices was investigated more closely by comparing and contrasting the calculated properties of molecules addressing shared targets, where cultural differences in design practices were anticipated to be more apparent, with those that addressed nonbiased targets. No substantial difference was observed between the mean values of a range of physical property measurements for target-biased and target-unbiased patent compounds within these organizations, with the exception of aromatic carbon atom count. These observations suggested that target selection was not the principle underlying the interorganization variance in calculated physical properties but rather institutional practices in drug design. 2.2. Drug−Target Binding Kinetics and Ligand Efficiency (LE), Size-Independent Ligand Efficiency (SILE), and Group Efficiency (GE). The scenario that has been sketched is one in which medicinal chemists exhibit a propensity to focus primarily on enhancing potency during lead optimization without fully understanding the underlying source of the observed changes while affording only a limited consideration to other aspects of compound devlopability.38,39,41−43 The binding affinity of a ligand for its target is a function of enthalpic and entropic contributions, defined by the Gibbs free energy change described in eq 1.42,43 This can be parsed into individual contributions in which affinity is governed mostly by intermolecular van der Waals attractive forces, H-bonding interactions, and repulsive forces like the hydrophobic effect that drive a ligand out of water and into the hydrophobic cavity of a protein (eq 2). High affinity binding requires positive contributions from both enthalpy and entropy, but the simultaneous optimization of these two aspects of drug association is challenging and perplexing because enthalpic optimization can frequently be offset by a loss in entropy.44,45 The difficulty in maximizing the enthalpic contribution is a consequence of the favorable formation of H-bond and van der Waals contacts being opposed by the cost of desolvation of incorrectly positioned polar moieties within a molecule. HBonding interactions are highly sensitive to both distance and angle, and a suboptimal interaction between a ligand and its target can lead to a negative effect on potency. This is because the gross change in enthalpy depends on the difference in Hbond strength between the ligand and its target and the ligand and bulk H2O. The desolvation energy of a polar moiety at 25 °C is commonly considered to approximate 8 kcal/mol, 10-fold higher than that associated with the energy of desolvation of a nonpolar group. Similarly, van der Waals interactions are maximized by a perfect geometric fit.42,43 There are two major contributing components to the entropy of binding: a positive entropic effect due to the release of ordered H2O molecules and a conformational effect, which is typically negative since the association of a ligand with its target usually results in the loss of conformational freedom for one or both of the molecules.

ΔG binding = ΔH − T ΔS = −RT ln Keq

(1)

ΔG binding = ΔG hydrogen bonds + ΔGelectrostatic + ΔG hydrophobic + ΔGvdw

(2)

The tendency to selectively focus on enhancing potency during lead optimization campaigns rather than adopting a more holistic perspective of drug design has been proposed as an important phenomenon underlying the propensity to produce large, lipophilic drug candidates that have been characterized as molecularly obese.41 As part of an effort to provide guidance on drug design parameters to the medicinal chemistry community, several efficiency metrics have been proposed that are designed to assess aspects of compound quality and which are readily calculated by the practioner.56−60 Ligand efficiency (LE), defined as the Gibbs free energy of binding (ΔGbinding) divided by heavy atom count (HAC, kcal/ mol per non-hydrogen atom (eq 3), is the original index that evaluates the free energy of binding per heavy atom.61 This metric has been proposed as a measure of the efficiency with which atoms in a ligand are deployed. The LE equation is preferably calculated using the logarithm of the inhibition constant (pKi or pKD) with correction by the relationship ΔGbinding = ∼1.37 kcal/mol for a 10-fold change in potency, but the logarithm of the IC50 value (pIC50) has also been used. GE =

−ΔG binding

HAC pK i , pKD , PIC50 = kcal/mol per non‐H‐atom HAC × 0.74

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(3)



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to a fundamental invalidity underlying its mathematical derivation.65,67 These criticisms have stimulated considerable discussion and provoked discourse that attempts to moderate the perspective and provide guidance on how to use LE and GE as rule-of-thumb metrics in lead optimization.68−70 Other scaled metrics that have been proposed attempt to equate potency with molecular weight (binding efficiency index, BEI, eq 6) or polar surface area (surface binding efficiency index, SEI, eq 7) that, like LE, have considerable uncertainty associated with some of the underlying fundamental assumptions but have nevertheless found application in several lead optimization campaigns based on both prospective and retrospective analyses.56−60,69,71−73

The original analysis surveyed data on a large number of high affinity protein−ligand interactions for which the free energy of binding was found to increase linearly with the number of nonH atoms, with an initial slope of 1.5 kcal/mol.61 However, the free energy of binding was found to increase little as the MW extended beyond 15 heavy atoms, an observation that prompted the development of size-independent ligand efficiency (SILE) which provides a better fit to the observed curve and is defined in eq 4.62−65 The origin of this phenomenon was probed by evaluating the thermodynamic parameters for 102 ligand−protein complexes in the BindingDB database.44,45 A plot of entropy versus enthalpy exhibited a strong negative correlation, confirming the tendency of these two components to align in opposite directions and reflecting the difficulty of simultaneously optimizing these parameters. Plots of enthalpy and entropy versus free energy showed no correlation, suggesting that in this data set neither entropy nor enthalpy were suitable surrogates for the change in free energy. Plots of enthalpy and entropy versus molecular size showed weak trends, but a plot of enthalpy efficiency, defined as ΔH/HAC, versus molecular size, revealed an erosion in enthalpic efficiency with increasing HAC, a pattern similar to that observed for the LE versus HAC plot. In contrast, entropic efficiency, defined as ΔS/HAC, showed no significant dependence on HAC.44,45

SILE =

BEI =

SEI =

(4)

An extension of the ligand efficiency concept is group efficiency (GE), which is defined in eq 5 and assesses the effect of the incremental change in binding energetics in response to the addition of an atom or functional group to a molecule.66 This concept provides a metric with which to assess the inherent quality of added functionality during lead optimization by allowing a relatively straightforward understanding of the effects of changes in heavy atom count on potency. Thus, GE provides simple guidelines with respect to the gain in potency one should expect as a function of the size of an added group, a metric that is easily implemented. This relationship indicates that if the addition of a benzene, pyridine, or cyclohexane ring to a molecule increases potency by 10-fold, then GE = 0.21, while a 20-fold change in potency would reflect a GE value of 0.29. Clearly, if the starting point is a molecule with a typical LE value of 0.3, the introduction of a benzene, pyridine, or cyclohexane ring requires an improvement in potency of at least 20-fold if LE is to be merely maintained, while the addition of an indole, benzimidazole, or benzofuran heterocycle would require a potency enhancement of 100-fold in order to fully preserve the binding efficiency quality of the lead molecule.66 GE = =

−ΔΔG binding ΔHAC ΔpIC50 HAC × 0.74

kcal/mol per non H‐atom

MW(kDa)

(6)

pK i , pKD , pIC50 PSA/100Å2

(7)

2.3. Synopsis of Some of the Effects of Lipophilicity. While the facility with which the entropic contribution to binding affinity can be optimized by increasing lipophilic burden rather than balancing entropic and enthalpic parameters appears to be a source of molecularly obese compounds, lipophilicity is a critical determinant of many of the factors that are associated with drug properties and developability.41,74−78 Excess lipophilicity is almost invariably deleterious in its effects on developability parameters with the exception of membrane permeability, where in vitro studies have indicated that as molecular weight increases, the lipophilicity of a molecule needs to increase in order to maintain a high probability of being permeable across a Caco-2 membrane.46 This phenomenon may underlie the preponderance of molecularly obese compounds in the contemporary primary and patent medicinal chemistry literature. Perhaps the most overt problem associated with increased lipophilicity is the negative effect on aqueous solubility, an important determinant of oral bioavailability and a fundamental element of the biopharmaceutics classification of drugs.77−84 The advancement of poorly soluble drug candidates is the basis for an increasing contemporary reliance on enabled formulations that are employed to overcome problems associated with dissolution- and solubility-limited oral bioavailability.81−84 The general solubility equation (GSE, eq 8) is an empirically derived relationship that, in its most fundamental form, equates the dependence of compound solubility on melting point and lipophilicity.85−88 It has been shown that melting point can be replaced by total polar surface area (TPSA) to afford a similar level of predictive quality (eq 9), while including both terms (eq 10) has been found to further improve the reliability.88 In these equations, melting point is the “brick dust” factor, while Log P refers to the so-called “grease ball” component, both of which contribute to compound solvation and dissolution.88−91 Highly lipophilic compounds typically exhibit solvation-limited solubility, while solid state-limited solubility is associated with high melting compounds.89−91 For a drug candidate with a Log P value of 2.3, the mean for a set of marketed drugs, that has a melting point of 150 °C, the GSE predicts the solubility to be 900 μM.92−95 If the Log P value is increased to 3.3 without a change in the melting point, the predicted solubility falls to 100 μM, almost an order of magnitude lower.92−95 However, an experimental measurement of the kinetic solubility of 711

affinity HAC0.3

pK i , pKD , pIC50

(5)

The appeal of LE and GE is in the convenience and rapidity with which these factors can be assessed during lead optimization, but the simplistic nature of these metrics requires an understanding of, and appreciation for, their inherent limitations when interpreting data.67−70 The relevance of LE as a metric has been challenged based on the lack of direct proportionality to molecular size and an inconsistency of the magnitude of effect between homologous series, both attributed 568



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of 75 Å, while the presence of a single of these risk factors was associated with lower odds of exhibiting good selectivity.111 This observation extended to in vivo toleration studies where applying the same parameter thresholds indicated that compounds in the high lipophilicity/low TPSA quadrant were 6-fold more likely to fail than those in the low cLog P/high TPSA quadrant, independent of the free fraction of drug in plasma.111 The propensity for the induction of phospholipidosis or inhibition of the human ether à go-go related gene (hERG) K+ ion channel (KCNH2) has been associated with similar physical properties, with manifestation of both dependent on lipophilicity and the presence of a basic amine.112 Phospholipidosis relates to drug-induced accumulation of phospholipids in cells, and the majority of models suggest that the combination of a measure of basicity (pKa) and Log P can predict the potential for occurrence, although use of the amphiphilic moment rather than cLog P has been suggested to offer improved predictive value.113−122 The potential to encounter inhibition of the hERG cardiac ion channel, a highly promiscuous protein, as an off-target liability is related to compound lipophilicity and is exacerbated with compounds containing a basic amine element.123−125 A quantitative analysis of hERG liability based on inhibitory data derived from an in vitro electrophysiology assay indicated that for neutral and basic compounds, increasing lipophilicity was associated with a greater potential to interfere with this channel.123 For the neutral compounds studied, there was only a 30% chance of avoiding significant hERG inhibition at a concentration of 10 μM if the Log D was >3.3, while for basic compounds, the requirement was far more stringent with a Log D of 4,400 preclinical compounds, an analysis of 232 drugs for which human PK data was available revealed a higher bioavailability for those compounds with a Log D value of between 2 and 3.97,98 A weak but significant relationship between cLog P and clearance in the rat was noted, with more lipophilic compounds cleared more rapidly, although there was some dependence on ion state in this cohort.97 This may reflect, in part, the increased metabolic rate typically observed for more lipophilic compounds in liver microsomes and cytochrome P450 (P450) enzyme preparations, although many other factors are involved in clearance mechanisms.99−103 A weak trend toward clearance increasing with lipophilicity in humans has also been noted for 670 intravenously administered drugs and clinical candidates.104 An increase in lipophilicity was associated with increased inhibition of the P450 enzymes 2C9, 2C19, 2D6, and 3A4, although hydrophobicity exerted only a limited influence on the inhibition of P450 1A2.97,105 However, although compounds with a Log P value of 10 μM), the correlation between lipophilicity and P450 inhibition is somewhat weak.74,105,106 There were some unique dependencies of inhibition on compound ionization state across these isozymes, while inhibition showed a correlation with increased molecular weight only for P450 3A4 inhibition, with P450 1A2 inhibition inversely related to MW, attributed to the small size of the active site of this enzyme.97,105,106 Increased lipophilicity has also been correlated with a higher risk for off-target effects beyond P450 inhibition that can manifest as toxicity.74−76,107,108 There is an increased propensity for promiscuity for componds with a higher calculated Log P, as measured by inhibitory effects toward biochemical profiling assays in vitro.109,110 In one study of a cohort of compounds expressing modest inhibitory activity in selecetivity profiling assays (≤30% inhibition at 10 μM), those with a cLog P value of 3 and a TPSA of 0.35, indicating a low dependence of binding efficiency on lipophilicity and HAC that suggested the importance of additional factors. A focus on the source of lipophilicity suggested that factoring in consideration of a combination of Log D and aromatic atom count (#Ar) provided a more selective discrimination, with just 4.5% of compounds meeting the refined criteria that, notably, included six of the nine clinical compounds.134 LLE HAC × 0.74 (pK i , pKD , PIC50 − cLogP) = + 0.11 HAC × 0.74

LLEAT =

kcal/mol per non H‐atom

(12)

Lipophilicity-corrected ligand efficiency (LELP) is defined as the ratio of Log P and LE and has been proposed to be a useful metric to consider during lead optimization (eq 13).131 Although the full value range of LELP is −10 to +10, a typical lead molecule with a LE value of >0.4 and a cLog P between 0 and 3 would express a LELP value of between 0 and 7.5, and a target value of ≤10 has been suggested as a useful guidepost in the lead optimization phase. The mean LELP value calculated for 210 Phase II compounds (8.5) and 302 orally administered marketed drugs (6.4) was lower than that for successful leads (8.8) and HTS leads (11.8), indicative of refinement in the later stages of optimization.

(11)

A caveat with LE and GE is that all atoms are treated with equivalence regardless of their polarity or ion status. Thus, these indices do not effectively discriminate between sulfonic acid (SO3H), trifluoromethyl (CF3), dimethylaminomethyl (CH2N(CH3)2), and trimethylsilyl (Si(CH3)3) substituents, all of which are viewed as identical by LE and GE and yet clearly have very different physicochemical properties and metabolic liabilities. Similarly, LE and GE do not adequately differentiate a carboxylic acid (CO2H) from a carboxamide (CONH2) or a phenyl ring from a pyridyl ring. In an attempt to address this deficiency, indices have been devised that combine elements of LE and LLE.130−133 LLEAT is defined by eq 12 and was conceived to allow a determination of the suitable potency and Log P for a fragment by hybridizing LLE and LE.130 The constant is added because a typical molecule with a potency of 10 nM, an HAC of 36, and a Log P of 3 would have an LLEAT value of ∼0.19; thus, adding 0.11 was designed to harmonize the value with the more conventional LE metric. LLEAT attempts to provide a measure of the quality of an added fragment in the context of both size and intrinsic lipophilicity, and this metric suggests that when an LE value is significantly greater than LLEAT, drug−target binding is dominated by lipophilicity. In contrast to GE where the addition of a phenyl group to a molecule with an LE of 0.3 requires an ∼20-fold increase in potency to maintain heavy atom efficiency, taking lipophilicity into account in the context of LLEAT demands a 460-fold potency enhancement.130,133 In contrast, adding a pyridine ring incurs a much lower penalty, requiring only a 30fold increase in biological activity in order to maintain compound quality. While LLEAT was introduced for fragment-based drug design (FBDD), a retrospective analysis of the physical properties of orally bioavailable factor Xa inhibitors that attempted to differentiate clinically successful compounds from those that failed, noted that the most prominent clinically

LELP =

Log P LE

(13)

2.5. Central Nervous System Drug Space. The central nervous system (CNS) drug space has more restrictive physicochemical criteria attributed to the specific demands of the blood−brain barrier (BBB) that are dependent on the lipophilicity and H-bonding properties of a molecule, as well as the activity of the transporters P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP).135−145 After analyzing the physicochemical and in vitro ADME attributes associated with 119 successfully marketed CNS drugs and 108 Pfizer clinical candidates with a view to understanding factors associated with success, a multiparametric relationship between the physicochemical descriptors cLog P, cLog D, MW, PSA, HBD, and pKa and the ADME properties of membrane permeability, human liver microsome (HLM) clearance, P-gp substrate potential, hERG inhibition, and cytotoxicity was developed.139,140 This analysis facilitated the development of a straightforward scoring system of compound quality that focused on aligning desirable attributes in a CNS multiparameter optimization (MPO) score (Table 3).140 Compounds with properties within the preferred range were assigned a score of 1 for each function, while those Table 3. Physicochemical Parameters That Constitute the CNS MPO Score for CNS Active Compounds140

570

property

cLog P

cLog D

MW

desirable range

≤3

≤2

≤360

undesirable range

>5

>4

>500

% PSA >40 and ≤90 ≤20 and >120

# HBDs

pKa

≤0.5

≤8

>3.5

>10



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calculated physical properties of a molecule to predict the potential for oral absorption was based on an analysis of 2,245 compounds from the World Drug Index conducted by Lipinksi, who discerned the parameters known as the “rule of 5”.148,149 This mnemonic reflects the observation that molecules were more likely to be orally absorbed if they conformed to a MW of ≤500, a Log P < 5, and possessed ≤10 HBAs and ≤5 HBDs. Consistent with this observation, a plot of cLogP against MW for 617 approved oral drugs defined a centroid occurring at a MW of 316 and a cLog P of 2.3, with preferred molecules possessing 4 HBAs and 2 HBDs.92 However, natural products and compounds subject to active transport were recognized for their potential to be exceptions, and it was subsequently noted that only 51% of all FDA-approved drugs that are used orally comply with the “rule of 5”, while 20% fail at least one parameter.150,151 In its most basic form, the “rule of 5” scores compounds in a binary fashion, with a pass or fail designation based on a hard cutoff, and each parameter is given an equal weighting. In an effort to provide a more nuanced scoring system, a proposal has been made to soften the hard cutoffs by scoring the properties on a slope that extends to either side of the parameter target number and which can further be refined by adjusting the weightings of each parameter.149 The “rule of 5” observations were rapidly embraced by the drug discovery community, and this guideline was frequently referenced and invoked as a justification of compound quality, sometimes with a zealousness that accorded it the aura of a law for some practitioners who attempted to apply the defined values of these rules in decision making. Nevertheless, the Lipinksi article was seminal in stimulating interest in attempting to further quantify drug likeness by readily calculated physicochemical terms and in identifying additional factors involved in drug disposition and toxicity that might be used in a prospective fashion. While several of those have been described above, the complexity of drug disposition and toxicity is dependent on a multitude of factors that are difficult, if not impossible, to distill into a simple series of physicochemicalbased metrics. Nevertheless, several of these factors have predictive value but context and their inherent limitations need to be given full consideration in their prospective application. Some of the more important factors are summarized in the next section. The number of RBs was identified as a prognosticator of an oral bioavailability (F) value of >20% in rats that was independent of MW, with 65% of compounds with ≤7 RBs having an oral F of ≥20%.152 By way of contrast, 75% of compounds with ≥10 RBs had an oral F of ≤20%, results that correlated with a reduced rate of permeation through an artificial membrane as RB count increased. Upon closer inspection of the data, it was noted that for compounds with a MW of 5 were classified as having a high free fraction in the mouse brain, considered as a remarkable result given the inherent complexity of the factors influencing the disposition of the compounds in vivo. None of the individual parameters exhibited a correlation, with the notable exception that 86% of the compounds with a cLog D of >5 fell into the low free fraction group. More recently, the CNS MPO scoring tool has been demonstrated to be useful in the assessment of brain bioavailability of inhibitors of leucine-rich repeat kinase 2 (LRRK2), an enzyme linked both functionally and genetically to neurodegeneration in Parkinson’s disease.146

Recognizing that the CNS MPO score is inherently heavily biased toward lipophilicity parameters, a probabilistic MPO scoring function, designated pMPO, has been developed that is based on defining the physiochemical properties associated with 299 brain penetrant drugs that were compared and contrasted with those of 366 drugs that were considered to be not brain penetrant.147 Although 14 descriptors were evaluated, 5 were selected for relevance based on an analysis of distributions that appeared to differentiate CNS-penetrant from nonpenetrant drugs. The descriptors and the weightings assigned were as follows: TPSA (0.33), number of HBDs (0.27), MW (0.16), cLog D (0.13), and the value of most basic pKa (0.12). The pMPO descriptors selected reflect the importance of the polarity of a molecule in determining CNS penetration, and the pMPOCNS score is calculated by summing the individual weightings and probability distribution of the desired molecules. While there was reasonable overall agreement between this methodology and the original CNS MPO scoring function, there were several notable differences that appeared to have roots in the heavier reliance of the earlier scoring paradigm on lipophilicity parameters.147 2.6. “Rule of 5” Metric and Other Prognosticators of Bioavailability. The original description of the importance of 571



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centers.161 This was suggestive of a process of natural attrition of compounds with low stereochemical complexity during the development process, and a subsequent study linked a high Fsp3 value with a reduced potential for promiscuity and P450 inhibition.162 The latter observation correlates with analyses of compounds of natural origin, which are more steroechemically complex than molecules typically prepared in drug discovery campaigns and occupy quite different physicochemical space.163−168 These properties have been shown to be associated with a higher degree of discrimination toward interaction with a range of proteins as well as the ability to address different protein targets. 3.2. Aromatic Ring Count and Compound Properties. The observation of the attrition of drug candidates with low Fsp3 values in development is supported by studies of the GlaxoSmithKline pipeline that analyzed compounds from the perspective of evaluating the correlation between the number of aromatic rings in a molecule and its potential to progress from discovery through the development pipeline to enter proof-ofconcept clinical trials.169,170 Although the number of compounds at each stage of development that were analyzed in this study was relatively small, as compounds progressed through the stages of development, there was a noticeable decline in mean aromatic ring count, as summarized in Table 5. In an

stability in liver microsomes (LM), the observation with this cohort of compounds may not be a general phenomeon.153 The upper limit of 10 RBs proposed as a predictor of good oral bioavailability in preclinical species may be too stringent since a study of 434 compounds culled from several therapeutic areas at Upjohn found that for some projects, compounds possessing 15−20 RBs were associated with acceptable oral exposure.154 This provides a cautionary note on the generality of applying this property as a cutoff, particularly since an analysis of 1,014 marketed oral drugs for which human PK data was available indicated an upper limit of 13 RBs to predict an oral bioavailability of ≥20%.155 Several molecular topology descriptors that encompass the molecular framework (the number of heavy atoms in the framework of a molecule divided by the total HAC), the number of ring systems, and the number of side chain atoms and the fraction of sp3 atoms (Fsp3 = # of sp3 hybridized C atoms/total C atom count) have also been shown to contribute to ADME disposition independent of other physicochemical measurements, adding further to the complexity of correlating molecular properties with drug disposition and quality.156−160

3. UNDERSTANDING THE SOURCES OF PROBLEMATIC LIPOPHILICITY 3.1. Fraction of sp3 Carbon Atoms. The three dimensionality of compounds in the GVK BIO database of drugs and candidates was analyzed by assessing the MW, the degree of saturation as defined by Fsp3, and the number of stereocenters at each stage of development.161 The thesis probed with this study sought to understand if increasing saturation correlated with the potential of a molecule to progress toward becoming a marketed drug and what correlation, if any, there was with physicochemical properties. The analysis revealed that the mean MW of a compound decreased with progression, while the mean Fsp3 count increased as a compound progressed through the five stages of development, rising by 31% from discovery compounds to marketed drugs, data that are summarized in Table 4.

Table 5. Mean Aromatic Ring Count for Compounds in the GlaxoSmithKline Pipeline by Development Stage number of compounds mean aromatic ring count

discovery

number of compounds MW Fsp3 fraction of compounds with ≥1 stereocenter

2,200,000 449 0.36 0.53 0.46a

phase 1 phase 2 phase 3 376 436 0.38 0.52 0.49a

591 429 0.43 0.60 0.52a

188 417 0.45 0.63 0.62a

FIH

P1

P2

PoC

50 3.3

68 2.9

35 2.5

53 2.7

96 2.3

effort to illuminate some of the underlying factors, the effect of aromatic ring count on several important developability properties was assessed, data that are compiled in Table 6. Table 6. Effects of Aromatic Ring Count on Key Developability Parameters

Table 4. MW, Fsp3, and the Number of Compounds with ≥1 Stereocenter in Small Molecules by Phase of Development phase

preclinical

drugs 1179 350 0.47 0.64 0.61a

# of aromatic rings

1

2

3

4

5

cLog P value CHI Log DpH7.4 value % HSA binding aqueous solubility (μg/mL) P450 3A4 inhibition (pIC50) hERG inhibition (pIC50)

1.9 1.3 78 100 4.7 5.2

2.9 2.1 88 79 4.9 5.6

3.7 2.4 93 57 5.2 5.7

4.4 2.7 96 36 5.4 5.7

5.1 2.9 96 28 5.7 5.5

These data indicate that as aromatic ring count increases, cLog P, Log D, human serum albumin (HAS) binding, P450 3A4 inhibition, and hERG inhibition all increase in parallel while solubility declines, precipitating the conclusion that as aromatic ring count increases, key parameters associated with developability are adversely affected.169 A more detailed probe sought to understand if the problems were associated with specific ring types, with data parsed by analyzing by aromatic, heteroaromatic, carboaliphatic, and heteroaliphatic ring content, which were assessed for effects on chromatographic hydrophobicity index Log DpH7.4, (CHI Log DpH7.4) solubility, protein binding (HSA and alpha-1 acid glycoprotein (AGP)), hERG inhibition, and inhibition of five key P450 enzymes.170 The analysis identified carboaromatic rings as being associated with more developability problems than the other three ring types. More specifically, carboaromatic rings were associated with

After the removal of compounds that failed any “rule of 5” parameter or had >10 RBs.

a

Moreover, the mean number of compounds with one or more stereocenters was found to increase with compound progression, amounting to a 33% increase between discovery compounds and marketed drugs after removing all compounds that violated one of the “rule of 5” parameters or had >10 RBs. In the analysis of physical properties, a higher Fsp3 value was associated with a lower melting point and increased aqueous solubility based on data from cohorts of 4,432 and 1,202 compounds, respectively. Thus, the implication is that more highly saturated compounds have a greater chance of succeeding as drugs, with compounds that successfully navigate to the later stages of development containing more stereo572



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3.3. Solubility Forecast Index (SFI) and Property Forecast Index (PFI). A subsequent study analyzed the relationship between calculated and measured hydrophobicity and the kinetic solubility of ∼100,000 compounds that had been measured using a high throughput chemiluminescent nitrogen detection method that had a dynamic range of 1−500 μM.93 The ACD cLog DpH7.4 gave a useful but somewhat crude indication of the solubility classification for a molecule with low solubility, which was defined as 200 μM. However, solubility was also shown to be related to the # of aromatic rings (#Ar) contained within a molecule, and a pie chart matrix plot of cLog DpH7.4 and #Ar showed a more pronounced differentiation than that using either parameter alone. The percentage of poorly soluble compounds was found to increase in concert with ACD cLog DpH7.4 and #Ar, with a split noted at a value of cLogDpH7.4 + #Ar = 5. This was codified as the solubility forecast index (SFI), defined in eq 14, that can be used as a simple guide to predict the aqueous solubility, with a compound more likely to be soluble if the SFI value is 700 μM, a bioavailability of 83% in the rat after PO dosing at 10 mg/kg body weight, and a half-life measured as 8 h. This study demonstrates that even when the point of departure is a molecule with good drug-like properties, further gains are possible if lipophilicity is deployed in a judicious fashion, most effectively monitored by paying close attention to the LLE (LipE) values of analogues. 4.9. Monitoring LLE (LipE) while Optimizing Protein Arginine Methyltransferase 5 (PRMT5) Inhibitors. Protein arginine methyltransferase 5 (PRMT5), also known as histone methyltransferase, is an epigenetic target for which optimization of the screening lead 59 was pursued in an effort to identify a tool molecule with a PK profile suitable for in vivo studies designed to probe the pharmacology of inhibiton.247 From Xray cocrystal structures, it was apparent that the tetrahydroquinoline heterocycle of 59 made a π-cation interaction with the S-adenosyl methionine cofactor, so this element was preserved. However, optimization of the left side of the molecule using insights gleaned from the cocrystal structure data allowed the introduction of rational structural modifications which afforded the pyrimidine derivative 60 as a compound with enhanced potency, lower cLog P and cLog D, and LELP values and a higher LLE (LipE) (Table 15). However, this compound exhibited only modest effects in cellbased methylation and proliferation assays, while the more lipophilic pyridine-based cyclobutyl homologue 61 was considerably more potent in cells. The enhanced potency associated with 61 appears to be driven by lipophilicity since the efficiency metrics calculated based on the enzyme inhibitory activity reveal lower LLE (LipE) and higher LELP values.247 These observations appear to be reflected in the lower stability of 61 compared to 60 in HLM and mouse liver microsomes, with the latter selected as the tool compound for in vivo studies, while the former was reserved for use as an in vitro standard (Table 15). In PK studies conducted in mice, a dose of 100 mg/kg body weight of 60 afforded unbound plasma concentrations (mouse protein binding = ∼30%) at or above the cell-based Z-138 ICW IC90 value for 12 h, suggesting that BID dosing would provide effective inhibition of PRMT5 in vivo.248 4.10. Lowering the Log D of HCV NS5B Inhibitors to Reduce Promiscuity. The indole derivative 62 is a potent inhibitor of the HCV NS5B polymerase enzyme in which the 2-

Figure 7. Structures and biological and physicochemical property data for the EGFR inhibitors 54−56.

Although these compounds exhibited moderate to high clearance in rats, the diol 56 was more stable than 55 in human hepatocytes. Because of the absence of metabolism due to the demethylation observed with methyl ethers, 56 was selected for further study in xenograft models where it was evaluated as a mixture of disasteroemers since the individual isomers offered essentially identical in vitro profiles. This compound suppressed the EGFR phosphorylation in a TMLR mutant-driven H1975 xenograft mouse model following oral administration once a day for 3 days.129 Although not identified as a drug candidate, the optimization toward 56 provides an example of contemporary drug design taking advantage of compound quality indices as an aid to the interpretation of structure−activity relationships (SARs).245 4.8. Monitoring LLE (LipE) While Optimizing Selective Androgen Receptor Modulators (SARMs). In a study of selective androgen receptor modulators (SARMs), the identification of compounds with high potency in a functional assay, high LE values, and good PK and aqueous solubility were set as the objective.246 The lead molecule 57 had the targeted potency and was structurally more compact than earlier compounds, with a low MW that translated into a high LE value. Further optimization monitored LLE (LipE) to guide analogue exploration toward compounds with lower cLog P values. Replacing the Me substituent of 57 with a series of heterocycles arrived at the oxazole 58 which distinguished itself from other heterocycles by the low cLog P and high LLE (LipE) values while fully preserving the potency of the 584



Review

inhibited hERG channel activity with IC50 values of 2.1 and 1.4 μM, respectively, and 64 prolonged the action potential duration (APD) by 20% in a guinea pig papillary muscle assay at a concentration of 30 μM, raising concern for the potential of QT prolongation at the predicted therapeutic plasma concentrations. The high lipophilicity of these compounds compared to earlier leads was recognized as a potential distinguishing element, and a matrix of compounds was prepared that explored cLog DpH7.4 values ranging from 2.2 to >6.6. Twelve of the compounds were evaluated in eight offtarget assays, and a plot of cLog DpH7.4 against the frequency of observing >50% inhibition at 10 μM revealed a positive correlation, R2 = 0.67 and p = < 0.002. Using potency criteria that specified EC50 values of 8.7, while for 65 it is moderated to 7.5, closer to the value of ≤7 that has been proposed as a predictor of improved solubility and lower promiscuity, driven in this case by a focus on lowering cLog D rather than #Ar, an additional avenue that may have led to further improvement.93,94 4.11. Application CNS MPO Scores in the Optimization of γ-Secretase Inhibitors and Modulators: The Use of Lipophilic Metabolism Efficiency (LipMetE). The relationship between metabolic stability and lipophilicity has been explored in the context of the metric lipophilic metabolism efficiency (LipMetE) which relates the unbound clearance of a drug in vitro (Clint,u) to LLE (LipE), as defined by

Table 15. Biological and Physicochemical Property Data for the Protein Arginine Methyltransferase 5 Inhibitors 59−61

59 PRMT5 IC50 (nM) Z-138 ICW IC50 (nM) Z-138 proliferation IC50 (nM) cLog P cLog D LE LLE (cLog P/cLog D) LELP (cLog P/cLog D)

326 nM ND ND 3.9 0.7 0.32 2.6/5.8 12.2/2.2

HLM-scaled CL (mL/min/kg) mouse liver microsome-scaled CL (mL/min/kg)

13 50

60 22 9 351 0.6 −0.1 0.38 7.1/7.8 1.57/− 0.26 1067 (0/163) >1928 (0/178) >3200 (2/449) (4/188) (1/178)

cLog P 1.9 2.1 2.8 2.7 3.0 2.8

CNS MPO score 5.4 5.1 4.5 5.0 4.5

LE

LLE

LELP

0.46 0.42 0.41 0.47 0.54 0.41

6.6 6.6 6.2 5.3 6.2 5.9

4.2 5.0 6.8 5.7 5.6 6.8

much improved blood−brain barrier penetration, but neither of these compounds promoted LRRK2 dephosphorylation in the CNS, hypothesized to be the result of nonspecific binding with TAE-684 (77), attributed to its high lipophilicity, with speculation extended to include GSK2578215A (78), which has a similarly high cLog P value.146,253 The pyrimidine derivative 79 was characterized as a potent LRRK2 inhibitor that demonstrated excellent kinase selectivity, attributed to the ortho-MeO substituent which had been introduced into a predecessor molecule after examination of a homology model of LRRK2 that was based on JAK2 and which indicated that the MeO would not be tolerated by the active site of the latter kinase (Table 18).254−257 Although 79 demonstrated modest potency in a cell-based assay, it did inhibit LRRK2-mediated autophosphorylation in the mouse brain in vivo and compounds with enhanced potency in the cellular assay were sought as part of the optimization process. The SARs that had been developed to this point suggested that analogues with improved cell-based activity were those with more lipophilic substituents at C-5 of the pyrimidine ring, moieties capable of interacting more effectively with the Met1947 gatekeeper residue of the kinase. The optimal combination of pyrimidine substituents was achieved with the

threonine kinase that is widely expressed throughout the body, although higher levels are found in the brain, kidney, heart, and B-lymphocytes.146 Although an understanding of the endogenous role of LRRK2 and its substrates is incomplete due to the complexity of its interactions, it has been shown to be responsible for PARK8-induced neurodegeneration, and 40 genetic variants have been identified, of which six have been confirmed to contribute to the pathogenesis of Parkinson’s disease. Consequently, inhibitors of the kinase function of LRRK2 have been sought as a potential approach to the treatment of Parkinson’s disease, and since CNS penetration is required for in vivo efficacy, monitoring efficiency indices have featured prominently during lead optimization as part of the effort to identify compounds with targeted profiles.146,253 Screening strategies to find lead inhibitors were implemented that used either inhibition of phosphorylation of a surrogate substrate or inhibition of the binding of the protein to a matrixbound active site ligand, with LRRK2-IN-1 (75) and CZC25146 (76) the first potent and selective inhibitors to be characterized. However, neither of these compounds demonstrated appreciable brain penetration, attributed, in part, to the modest or poor CNS MPO scores (Table 17). TAE-684 (77) and GSK2578215A (78) are potent LRRK2 inhibitors with 587



Review

due to nuclear receptor activation and directly and reversibly inhibited P450 1A2. Nevertheless, this compound was advanced as an additional tool molecule useful for in vivo studies along with GNE-9605 (84), the result of further optimization. In GNE-9605 (85), the oxetane ring and the equatorially disposed fluorine atom are designed to modulate the basicity of the piperidine N atom as a means of modulating P-gp efflux and improving brain penetration, further assisted by reversion to the slightly more lipophilic Cl substituent on the pyrazole ring.254−256 In an alternative series, efficiency indices and CNS MPO scores were monitored during optimization of the screen hit 85, a modestly potent LRRK2 inhibitor that was selective over 39 other kinases and possessed a high CNS MPO score, with LE and LLE (LipE) values considered attractive in a lead with just 17 heavy atoms (Table 19).258 A virtual screen exercise

CF3 derivative 80 which profiled similarly to 79 with respect to its CNS MPO, LE, LLE (LipE), and LELP scores but demonstrated a 3-fold higher unbound brain/plasma ratio and a higher CSF/unbound plasma ratio in rats (0.48 for 80 compared to 0.29 for 79). This profile is reflected in a reduced in vitro MDR efflux ratio of 1.2 for 80 compared to 2.8 for 79. The single crystal X-ray structure of 80 was informative, indicating the presence of a H-bond between the aniline NH and ortho-MeO and an interaction between one of the fluorine atoms of the CF3 substituent with the adjacent NH, both of which were considered to be factors contributing to the increased brain penetration of the compound. These properties made 80 a useful tool compound that inhibited LRRK2mediated autophosphorylation of Ser1292 in the brains of mice at brain levels of ∼100 nM and plasma levels of ∼150 nM. Kinase profiling with 80 revealed good selectivity with only 1 of 189 kinases significantly affected at 0.1 μM. However, the kinase that was susceptible to 80 was TTK (MPS1), which was inhibited by 55% at 0.1 μM and 98% at 1 μM, and considered to be a possible source of the genotoxicity seen with this compound in a human peripheral blood lymphocyte assay. The next round of optimization addressed this problem by comparing the homology model of LRRK2 with the X-ray of TTK, which suggested that selectivity may be gained by further substitution of the aniline ring. While a Cl or MeO substituent at C-5′ enhanced selectivity, these compounds suffered from either poorer CNS penetration or higher metabolism in human hepatocytes.254−256 A careful analysis of the physical properties of the series indicated that compounds with a cLog D of between 1.8 and 3.3 were more likely to be metabolically stable in human hepatocytes, while those with a cLog D of 90 Å2 were subject to P-gp efflux. These parameters were used to guide further design which focused on exploring subtle structural changes in an effort to remain within targeted property space. GNE-7915 (81) was the result of that exercise, characterized as a potent and selective LRRK2 inhibitor exhibiting good PK properties that reduced the levels of phosphorylated LRRK2 in the mouse brain after oral or IP doses ranging from 10 to 50 mg/kg body weight (Table 18). GNE-7915 (81) did not demonstrate evidence of genotoxicity in vitro and was evaluated in a series advanced toxicity studies in rats and cynomolgus monkeys that revealed a profile suitable for a preclinical prototype with which to further explore LRRK2 pharmacology. However, two potential liabilities with GNE-7915 (80) were its poor aqueous solubility (10,000 337.4 25 5 7 0 7 65.3 4.24 4.24 0.36 2.26 0.23 11.8 0.28 12 3 7.24

170 6.8 1840 351.4 26 5 7 0 7 65.3 4.66 4.66 0.37 2.14 0.22 12.6 0.32 11 3 7.66

114 6.9 127 365.4 27 5 7 0 7 65.3 5.07 5.07 0.36 1.83 0.20 14.1 0.35 10 3 8.07

9.5 8.0 1120 419.8 29 7 8 0 8 74.5 4.37 4.37 0.39 3.63 0.28 11.2 0.32 11 3 7.37 59

a

All physicochemical data values are abstracted from SciFinder and calculated using Advanced Chemical Development (ADC)/Laboratories) software v11.02. Efficiency indices were calculated based on cLog DpH7.

Figure 12. Design concept for evolving the bradykinin BK1 antagonist 114 to cyclopropyl glycine derivative 115.

the core N atom. In order to improve the overall profile of 122, attention was focused on increasing the three-dimensionality of

the 2-substituent in an effort to sterically interfere with glucuronidation while reducing promiscuity. This approach 593



Review

Table 26. Structures, Biological Data, Calculated Physicochemical Properties, Efficiency Indices, and PK Profiles Associated with the Bradykinin B1 Antagonists 114 and 115a compd #

114

11.8 human BK B1 Ki (nM) pKi 7.93 MW 443.4 RB 7 HBA 6 HBD 2 ΣHBA + HBD 8 PSA (Å2) 80.3 cLog P 3.94 cLog DpH7 3.93 LE 0.35 LLE 4.0 LLEAT 0.28 LELP 11.3 Fsp3 0.17 cLog DpH7 + #Ar 6.93 Rat PK Parameters Following Oral Administration %F 9 t1/2 (h) 0.15 CL (mL/min/kg) 35

Table 27. Structures, Biological Data, Calculated Physicochemical Properties, and Efficiency Indices Associated with the TGR5 Antagonists 116 and 117a

115 63 7.20 434.4 8 6 2 8 84.5 2.86 2.86 0.33 4.34 0.30 8.7 0.32 4.86 26 9.5 9.3

a


compd #

116

117

EC50 (nM) pIC50 MW RB HBA HBD ΣHBA + HBD PSA (Å2) cLog P Log DpH7 LLE LE LLEAT LELP Fsp3 Log DpH7.4 + #Ar

6.1 8.2 414.3 3 5 1 6 45.7 6.18 6.18 2.02 0.41 0.21 15.1 0.14 9.18

5.1 8.3 404.3 3 5 1 6 52.7 3.63 3.62 4.68 0.43 0.34 8.4 0.33 5.62

a

All physicochemical data values are abstracted from SciFinder and calculated using Advanced Chemical Development (ADC)/Laboratories) software v11.02. Efficiency indices calculated based on cLog DpH7.

based on its selectivity for DGAT2 over other acyl transferases other than monoacylglycerol O-acyltransferase 2 (MGAT2), which was inhibited with similar potency.279 In addition to enhancing target selectivity, optimization focused on improving the physical properties of 124 as an approach to addressing the negligible oral bioavailability in mice and reducing the high clearance in vivo observed with this prototype. Throughout this process, physicochemical properties including LLE (LipE), LE, and PSA were monitored to guide structural modifications toward productive chemical space. Preliminary SAR studies indicated that the amide and methoxyphenyl moieties were important since their absence resulted in inactive compounds. Modifications to the urea element led to 125, a compound with potency and LE similar to those of 124 but with much lower lipophilicity, which translated into improved LLE(LipE), Fsp3, and cLog P + #Ar values along with a 5-fold enhancement in selectivity over MGAT2. Since the isoquinoline ring of 124 and 125 was tolerant of manipulation, partial saturation and functionalization of the N atom gave 126 as a refined and potent DGAT2 inhibitor with >1,000-fold selectivity over MGAT2 and 23% oral bioavailability in mice.279 A 30 mg/kg body weight subcutaneous dose of 126 administered to mice pretreated with a lipase inhibitor resulted in a 40% lowering of plasma triglyceride levels. More detailed studies in mice characterized the metabolic fingerprint of the 126 as a compound that reduces newly synthesized triglycerides while redistributing linoleic acid toward newly synthesized phosphatidylcholine and cholesteryl ester. Careful attention was paid to monitoring LLE (LipE) values during the optimization of the MGAT3 inhibitor screening hit 127 to afford 128 (Figure 17), a tool compound with selectivity and PK properties that allowed the role of this enzyme in lipid

Figure 13. Metabolic activation pathways for bradykinin BK1 antagonist 114.

was successful, identifying PF-06424439 (123) as a molecule with the highest LLE (LipE) of the analogues synthesized in this phase of the survey. This compound presented acceptable metabolic stability in HLM, was not subject to glucuronidation in human hepatocytes, and was the first DGAT2 inhibitor to demonstrate favorable effects on hepatic and circulating lipid levels in rats following oral administration. After extensive preclinical profiling, PF-06424439 (123) was selected as a clinical candidate. In an alternative series of DGAT2 inhibitors, the urea 124 (Figure 16) was selected as a lead from a screening campaign 594



Review

Figure 14. Structures, biological and profiling data, calculated physicochemical properties, and efficiency indices associated with the RORγ inhibitors 118−120.

Figure 15. Structures, biological and profiling data, calculated physicochemical properties, and efficiency indices associated with the diacylglycerol acyltransferase 2 (DGAT) inhibitors 121−123.

This compound was characterized as a potent ATR inhibitor, IC50 = 26 nM, with a LLE (LipE) value of 4.6 based on this assay but was a more potent inhibitor of PI3Kα, IC50 = 9 nM.281 A 7-azaindole heterocycle was found to be an excellent replacement for the electron-rich dimethoxyphenyl ring of 129, with 130 demonstrating 50-fold enhanced potency and improved LLE (LipE). However, compound 130 was poorly soluble, requiring further refinement. A dimethylsulfonamide was found to be a good substitute for the primary amide moiety of 130 that divested of two HBDs and improved solubility in the context of 131, in which the core heterocycle was further modified to help improve physical properties. A further gain in solubility was obtained by the addition of the CH3 substituent to the heterocyclic core, proposed based on modeling studies, which afforded 132. While the sulfonamide of 132 could be successfully replaced with a methyl sulfone, this modification was accompanied by problematic hERG inhibition. Consequently, additional increases in solubility were sought by adding further to the sp3 carbon atom count of the molecule, approached by replacing the phenyl ring with a piperazine heterocycle to give 134. While the potency of 134 is 3-fold less than 133, leading to some loss of LLE (LipE), the Fsp3 count is doubled, and this modification resulted in mitigation of the hERG inhibitory activity, while solubility was increased 8-fold. The final structural adjustment implemented was the addition of a 6-Cl substituent designed to address an efflux issue in Caco-2 cells that led to 135. This compound combined good potency in the cellular assay, where Chk1 phosphorylation was inhibited with an EC50 of 37 nM, representing a 4-fold improvement over 134, with acceptable solubility. Although not considered suitable for development, 135 was characterized as a good tool molecule with which to explore the pharmacological ramifications of ATR inhibition in vivo.281,282

Figure 16. Structures, biological and profiling data, calculated physicochemical properties, and efficiency indices associated with the diacylglycerol acyltransferase 2 (DGAT) inhibitors 124−126.

homeostasis to be explored in vivo.280 The result of this approach was an optimized compound with increased potency and selectivity, reduced cLog P, and an increased Fsp3 count, properties that translated into a significantly improved LLE (LipE) value. 5.8. Increasing Fsp3 Count in ATR Kinase Inhibitors. A lead inhibitor of the DNA damage response kinase ATR was sought using a cell-based assay that evaluated compound effects based on the inhibition of pChk1 phosphorylation on Ser345, a substrate of ATR, a screen that identified the imidazopyridazine 129 as a molecule with the targeted effect (Figure 18).281,282 595



Review

Figure 17. Structures, biological and profiling data, calculated physicochemical properties, and efficiency indices associated with the MGAT3 inhibitors 127 and 128.

Figure 18. Structures, biological and profiling data, calculated physicochemical properties, and efficiency indices associated with the ATR inhibitors 129−135.

discovered using an SAR by NMR screening protocol.283−286 Many of the structural elements in 136 are preserved in the clinical candidate ABT-263 (navitoclax, 137), which, remarkably for a molecule with a MW = 974.6, a PSA of 170 Å2, and cLog P and cLog DPh7 values of 9.7 and 7.15, respectively, and which exhibits modest aqueous solubility, is orally bioavailable, with lymphatic uptake and an apparent contributing pathway.287 An X-ray cocrystal structure of 136 with Bcl-2 revealed that the thiophenyl ring folds back on the molecule in a fashion that allows it to engage in π−π stacking interactions with the nitroaryl ring. In an effort to move away from the dependence on these aromatic rings, rigid tricyclic moieties were postulated as potential mimics with reduced lipophilicity and rotatable bond count, a concept that anticipated a potential thermodynamic advantage based on structural preorganization and increased ligand complementarity.288 The CH2−adamantyl moiety in 138 provided a useful and lower MW surrogate that inhibited Bcl-2-BAK association with an IC50 value 30-fold higher than that of the prototype 136 (Table 28). An X-ray cocrystal of 138 with Bcl-2 confirmed the proposed binding mode of the bicyclic element; however, it was noted that the sulfone moiety had moved to an extent that it was not able to fully engage the backbone H-bond donor from Gly104,

6. COMPOUNDS THAT EXPLORE CHEMICAL SPACE BEYOND THE “RULE OF 5” CRITERIA While contemporary drug design practices appear to be leading to many molecules that fall outside of the “rule of 5” parameters that are predictive of a higher potential for oral absorption, there are many examples where successful drugs have emerged from this region of chemical space. While finding molecules in this arena that combine acceptable physicochemical, PK, and toxicological properties may be more challenging, the select vignettes below describe some of the recent successful endeavors. While some targets can only be satisfied with ligands that fall outside of the “rule of 5” parameters, it has been advocated that drug design when working within this chemical space should still focus on minimizing lipophilicity while optimizing potency. The vignettes described below provide some contemporary and illustrative examples of successful drug discovery campaigns and include some of the interesting approaches and observations.38,39,48−51,133 6.1. Orally Bioavailable Bcl-2-Bak Protein−Protein Interaction Inhibitors. ABT-737 (136) is a potent inhibitor of the Bcl-2-Bak protein−protein interaction that was assembled and optimized by structurally hybridizing fragments that bound weakly to hot spots in the BCl-2 protein that were 596



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Table 28. Biological Data, Calculated Physicochemical Properties, and Efficiency Indices Associated with the Bcl-2-Bak Inhibitors 136 and 138−140a

compd #

136

138

139

140

Bcl-2-BAK IC50 (nM) pEC50 cLog P cLog DpH7 MW RB HBA HBD ΣHBA + HBD PSA (Å2) LE LLE LLEAT LELP Fsp3 cLog DpH7+ Ar#

20 7.7 8.5 5.88 813.4 15 11 2 13 164 0.19 1.82 0.15 30.9 0.26 10.88

670 6.17 7.2 5.22 618.2 7 6 1 7 78 0.2 0.95 0.14 26.1 0.46 8.22

310 6.51 5.3 3.21 747.4 11 9 1 10 100 0.18 3.30 0.20 17.8 0.54 6.21

120 6.92 7.7 5.75 632.6 7 6 1 7 78 0.22 1.17 0.15 28.8 0.47 13.0

a


efficiency metrics were only marginally improved despite reductions in cLog P and cLog DpH7 when comparisons are made using the relevant matched pairs (Table 28). 6.2. Orally Bioavailable Taxane Derivatives. Paclitaxel (141) and docetaxel (142) are the most prominent taxanes, and both are administered by IV infusion since they exhibit poor oral bioavailability in humans, attributed to issues associated with poor solubility and/or P-gp transport. For 141, solubility appears to be more of a problem than P-gp transport, while the oral bioavailability of 142 is increased 10fold from 8% to 88% when dosed in conjunction with the P-gp inhibitor cyclosporine.289 However, the four paclitaxel analogues 143−146 demonstrate significant oral bioavailability, and their physicochemical properties are compiled in Table 29 along with comparable data for 141 and 142.290−308 A plot of cLog P and MW for the oral taxanes 143−146 is depicted in

explaining the reduced intrinsic potency. The absence of the dimethylamine element of 136 was also noted and addressed by the introduction of polarity to the adamantane ring, a modification that improved potency 2- to 3-fold depending on the nature of the substituent, with the morpholinoethyl ether 139 representative. Although not probed further, expansion of the adamantine ring by a single CH2 gave 140, which increased potency by 5-fold, suggesting opportunity for further refinement in this direction. The oral bioavailability of 138 in rats was 66%, with low clearance (6 mL/min/kg) despite a cLog P value that remained high at 9.5. The alcohol precursor to 139 was similarly potent, IC50 = 300 nM, with a much reduced cLog P of 6.4 and oral bioavailability in rats of 100%.288 While the tricyclic moieties of 138−140 offer an interesting and innovative approach to replacing two aromatic rings while doubling the Fsp3 count, many of the other 597



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Table 29. Biological Data, Calculated Physicochemical Properties, and Efficiency Indices Associated with the Taxanes 141− 146a

compd # 141 142 143 144 145 146

C47H51NO14 C43H53NO14 C43H59NO16 C44H57NO17 C41H57NO14 C46H60FN3O13

MW

RB

HBA

HBD

ΣHBA + HBD

cLog P

cLog DpH7

PSA (Å2)

Fsp3

#Ar

cLog DpH7 + #Ar

853.9 807.9 845.9 871.9 829.9 882.0

17 17 19 18 21 17

15 15 17 18 15 16

4 5 4 3 5 3

19 20 21 21 20 19

3.95 2.46 3.49 2.92 2.96 4.51

3.95 2.46 3.49 2.92 2.94 3.32

221 224 240 246 224 202

0.45 0.56 0.67 0.66 0.63 0.66

3 2 1 1 1 2

6.95 4.46 4.49 3.92 3.94 5.32

a

All physicochemical data values are abstracted from SciFinder and calculated using Advanced Chemical Development (ADC)/Laboratories) software v11.02.

BMS-275183 (143) was identified as an orally active taxane following an empirical strategy that focused on identifying compounds with improved aqueous solubility.290−295 A C-4 methyl carbonate was associated with increased solubility (∼40fold) and oral exposure (50-fold) compared to those of 141, with modification of the C-3′ phenyl moiety to a tert-butyl explored based on the precedent that this enhanced aqueous solubility, anticipated to augment the solubilizing effect of the C-4 methyl carbonate, and reduced P-gp recognition. Although

Figure 19 where the centroid for marketed oral drugs is marked in green.92 It is clear from this plot that these compounds fall far from the drug-like space based on MW, although the cLog P values comply with the “rule of 5” criterion. There are no obvious physicochemical parameters that differentiate the orally bioavailable compounds from the two IV-infused drugs other than the fact that oral compounds all have higher Fsp3 counts and all but tesetaxel (146) have fewer aromatic rings than 141 and 142. 598



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Figure 19. Plot of cLog P versus MW for oral taxanes compiled in Table 29. The centroid value (MW = 316 and cLog P = 2.3) determined for 617 FDA-approved oral drugs is marked in green.

levels comparable between IV and PO drug administration.299−303 Tesetaxel (146) exhibits higher cytotoxicity than 141 and 142 toward tumor cell lines, particularly those expressing P-gp, and shows higher intracellular accumulation.163 Compound 146 exhibited antitumor effects in mice subcutaneously implanted with B16 melanoma BL6 cells with results that were similar whether the drug was administered by the IV or PO route, while 142 was inactive in this model when given PO at a dose of 600 mg/kg body weight.304−309 In vivo antitumor activity after oral dosing of 146 extended to two Pg-pexpressing human solid tumor xenografts implanted in mice under circumstances where 141 and 142 were in ineffective. In detailed PK studies, 146 was rapidly absorbed in mice, dogs, and monkeys following oral administration, with plasma elimination biphasic in nature and dependent on species.305 In dogs, the elimination half-life was longer than that in mice or monkeys, and in the mouse, radioactivity was widely distributed to all tissues with the exception of the CNS. The oral bioavailability of 146 was 107%, 47%, and 63% in mice, dogs, and monkeys, respectively.305 In a Phase I clinical trial, 146 was administered orally once every 21 days to patients with advanced solid tumors in combination with the 5-fluorouracil prodrug capecitibine with dose escalation from 18 to 35 mg/m2 determining that the maximum tolerated dose was 27 mg/ m2.307,308 However, while 146 was advanced into Phase II trials for the treatment of malignant melanoma, advanced gastric cancer, breast cancer, prostate cancer, nonsmall cell lung cancer, and advanced bladder cancer, development appears to have been halted in 2012 as the result of a business decision.308 6.3. HCV NS5A Inhibitors. Hepatitis C virus (HCV) NS5A inhibitors are exceptionally potent antiviral agents in cell culture with EC50 values of optimized compounds typically in the 5−50 pM range.310 This class of HCV inhibitor appears to have a dual effect on both the virus replication machinery and virion assembly, the latter accounting for the rapid fall in viremia following oral dosing to HCV-infected subjects. These compounds typically comprise dipeptide elements deployed at each end of a biphenyl or biphenyl-like scaffold as exemplified by daclatasvir (147), the prototype of the class.311 The physicochemical properties of the 10 most prominent clinically evaluated NS5A inhibitors 147−156 are compiled in Table 30 where they are listed by increasing MW.312 These compounds

this modification led to a 2-fold reduction in oral exposure in mice compared to the phenyl prototype, 143 was orally bioavailable in three species, with P-gp playing a role in its disposition in mice where the plasma AUC0−6h was 1.5-fold higher in Mdr1a/1b−/− mice.290 The compound was active in a M109 murine lung tumor model following oral dosing, with efficacy comparable to that of the IV administered 141 and was as cytotoxic toward an A2780 human ovarian carcinoma cell line in vitro while retaining activity toward cell lines resistant to 141. In vivo, 143 was active in five tumor models following oral administration, and the compound was advanced into clinical development where a preliminary study indicated that the drug was rapidly absorbed with plasma exposure increasing with dose, although not proportionally up to 160 mg/m2, while the mean plasma half-life was 22 h.292−295 However, in a follow-on efficacy study conducted in patients with solid tumors, clinical benefit was limited, and there was no clear correlation between dose and exposure, with substantial interpatient variability observed, while high exposures were associated with neutropenic sepsis.295 IDN-5109 (144) shows low cross-resistance with 141 in tumor cell lines expressing P-gp, and the compound is a poor substrate for this transporter.296−303 In nude mice, 144 was rapidly absorbed, with the drug disappearing from the plasma in a biphasic manner that recapitulated the IV kinetic profile and oral bioavailability determined to be 48%. Oral administration of doses of 60, 90, and 120 mg/kg body weight of 144 were associated with antitumor activity in 1A9 ovarian carcinoma xenograft models, with efficacy dependent on the dose.296−298 The more heavily modified seco-taxane 145 was rapidly absorbed in mice after oral dosing with bioavailability determined to be 43%, while metabolite excretion was more rapid after oral dosing, suggestive of first pass metabolism, and the AUC after 2 weeks of dosing was 2-fold lower than that on day one.299−303 In a small study conducted in dogs, 145 was orally bioavailable after administration of doses of 20, 40, and 80 mg/kg body weight, with dose-related but not doseproportional exposure. In a human breast carcinoma mouse xenograft model, 145 reduced tumor growth after daily oral doses of 90 mg/kg body weight for 4 days, with efficacy comparable to the IV administered drug. In contrast, 141 was inactive when given orally in this model, while 145 was active in several other tumor models, with efficacy at equivalent dosing 599



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Table 30. Physicochemical Properties and Efficiency Metrics Associated with the HCV NS5A Inhibitors 147−156a

147 148 149 150 151 152 153 154 155 156

mol formula

MW

RB

HBA

HBD

ΣHBA + HBD

cLog P

cLog DpH7

PSA (Å2)

Fsp3

Ar#

cLog DpH7 + Ar#

C40H50N8O6 C42H50N8O6 C42H52N8O8 C49H55N9O7 C49H54N8O8 C47H48N8O6S2 C49H54F2N8O6 C50H67N7O8 C60H72N8O6 C57H65F5N10O8

739 763 797 882 883 885 889 894 1001 1113

13 12 13 13 13 13 12 16 12 17

14 14 16 16 16 14 14 15 14 18

4 4 4 4 4 4 4 4 4 4

18 18 20 20 20 18 18 19 18 22

2.51 4.81 3.46 5.48 4.78 5.29 4.54 6.63 11.55 5.81

2.43 4.73 3.38 5.35 4.73 5.21 4.52 6.63

175 175 193 189 193 231 175 179 175 200

0.45 0.43 0.48 0.39 0.39 0.32 0.47 0.52 0.50 0.47

4 5 4 5 6 7 5 3 6 6

6.43 9.73 7.38 10.35 10.73 12.21 9.52 9.63 17.55 11.73

5.73

a

All physicochemical data values are abstracted from SciFinder and calculated using Advanced Chemical Development (ADC)/Laboratories) software v11.02. 600



Review

Figure 20. Plot of cLog P versus MW for the HCV NS5A inhibitors compiled in Table 30. The centroid value (MW = 316 and cLog P = 2.3) determined for 617 FDA-approved oral drugs is marked in green.

inhibitors show dose-related, although not always doseproportional, increases in exposure in humans following oral administration of doses ranging from 1 to 500 mg and typically exhibit long half-lives in vivo, ranging from 7.4 (149) to 55.73 (153) hours.312 As a class, these molecules are very effective antiviral agents in vivo, and this class of HCV inhibitor has emerged as the backbone of clinically effective therapeutic regimens. These drugs have transformed HCV clinical therapy from a combination of PEG-IFN-α and ribavirin taken for 48 weeks with cure rates of 40−50% and a significant incidence of adverse events to convenient, orally administered drug combinations taken for 6−12 weeks, with cure rates in excess of 90% and relatively benign side effect profiles.

exhibit a wide range of physical properties, many of which extend beyond traditional drug-like space. The MW range varies from 739 (147) to 1113 (156), while cLog P values (collated from SciFinder) range from 2.51 (147) to 11.55 (155); data that are plotted in Figure 20 which displays in green the centroid of MW (316) and cLog P (2.3) values determined for 617 FDA-approved oral drugs. As with the orally bioavailable taxanes 143−146, the values of these two developability parameters for HCV NS5A inhibitors are far removed from the centroid value of oral drugs. In addition, the number of RBs ranges from 12 to 17, well above that determined to be optimal in preclinical studies and significantly higher than the average value of approved oral drugs (Table 2). While HBA counts are high across these molecules (14−18), the number of HBDs is uniform at four, reflective of these as critical elements of the pharmacophore but compliant with the “rule of 5” criterion. Although the carbamate NH elements are not required for potent antiviral activity, they do appear to play a role in membrane permeability, exemplified by studies with the phenylglycine derivative 157 which expresses antiviral potency comparable to that of 147 but is considerably less membrane permeable despite fewer RBs, HBDs, and HBAs and a lower PSA.313,314 Modeling studies have suggested that in environments of low polarity, the carbamate-based compounds like 147 may form an intramolecular H-bond between the imidazole/benzimidazole NH and the carbonyl of the carbamate moiety, structural elements that are a component of all of the compounds compiled in Table 30. Recalculating the effective 3D-PSA of 147 taking the intramolecular H-bond into account reduces the value to ∼120 Å2, closer to the 105 Å2 calculated for 157. Two of the most recently disclosed NS5A inhibitors, 155 and 156, present some of the most extreme physicochemical values within the class, with both having MW values beyond 1000 Da, while the cLog P value calculated for 155 is >11, parameters that classify both compounds as molecularly obese. Indeed, with the exception of 147 and 149, all of the NS5A inhibitors fall into the large and greasy category when using values of cLog P = 4 and MW = 400 (Gleeson’s 4/ 400 ADME rule) as the discriminators, while relaxing those cutoffs to the Lipinski criteria of 5/500 moves an additional three of the compounds in Table 30 into the large and not greasy quadrant.95,97 Nevertheless, the majority of NS5A

6.4. HCV NS3 Protease Inhibitors. HCV NS3 PIs are typically based on tripeptidic structures with the pioneering molecules telaprevir (158) and boceprevir (159) relying upon an electrophilic carbonyl to interact with the active site serine of the enzyme.315 In contrast, the more recent second generation inhibitors incorporate an acidic C-terminus motif, most commonly a cyclopropyl acylsulfonamide, that takes advantage of the observation of product-based inhibition.315 While 158 and 159 were administered on TID schedules, the more recent second generation PIs have improved PK profiles that allow BID or QD dosing. Within this class, both 158 and 159 have been withdrawn from marketing by their sponsors, a consequence of problematic side effect profiles and dosing schedules that have been superseded by the second generation entrants in the field. Interestingly, 158 and 159 offer the lowest MW, PSA, and aromatic ring counts and the highest Fsp3 counts of the class; data are summarized in Table 31. An analysis of the physical properties of the estate from which 159 was selected indicates that this molecule was firmly in the leading echelon, with just 1% of compounds having better combined LE and LLE (LipE) values.133 In contrast, 38% of the analogues of 158 were of higher quality based on the combination of the values of these efficiency metrics. All of 601



Review

Table 31. Calculated Physicochemical Properties Associated with the HCV NS3 Protease Inhibitors 158−171a

compd #

molecular Formula

MW

RB

158 159

C35H51N7O6 C27H45N5O5

680 520

14 10

160 161 162 163 164 165 166 167 168 169 170 171

C35H46ClN5O9S C40H50N6O8S C40H49BrN6O9S C38H50N6O9S C38H55N5O9S C43H53N5O8S C45H56F2N6O8S2 C38H47N5O7S2 C35H46FN5O9S C40H43N7O7S C38H46F4N6O9S C45H60ClN7O9S

748 775 870 767 758 800 911 750 732 766 839 910.5

13 9 14 7 6 13 9 7 7 6 6 17

HBA

HBD

ΣHBA + HDD

cLog P

cLog DpH7

First Generation HCV NS3 Protease Inhibitors 13 4 17 4.36 4.36 10 5 15 2.84 2.84 Second Generation HCV NS3 Protease Inhibitors 14 3 17 4.25 2.36 14 4 18 5.85 2.44 15 4 19 5.37 3.06 15 3 18 4.37 2.49 14 3 17 3.9 2.03 13 2 15 4.15 2.25 14 2 16 6.3 4.41 12 2 14 6.1 4.24 14 3 17 3.17 1.27 14 3 17 5.13 3.22 15 3 18 1.19 −0.7 16 4 20 5.58 3.65

PSA (Å2)

Fsp3

Ar#

cLog DpH7 + Ar#

180 151

0.71 0.81

1 0

5.36 2.84

191 210 227 204 189 173 214 194 189 198 204 222

0.57 0.55 0.52 0.63 0.71 0.51 0.58 0.55 0.63 0.42 0.63 0.64

2 3 3 2 1 3 3 3 1 4 2 3

4.36 5.44 6.06 4.49 3.03 5.25 7.41 7.24 2.27 7.22 1.3 6.65

a

All physicochemical data values are abstracted from SciFinder and calculated using Advanced Chemical Development (ADC)/Laboratories) software v11.02. 602



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Figure 21. Plot of cLog P versus MW for HCV NS3 protease inhibitors compiled in Table 31. The centroid value (MW = 316 and cLog P = 2.3) determined for 617 FDA-approved oral drugs is marked in green.

Table 32. Biological Activity, PK Properties, and Calculated Physicochemical Properties Associated with HCV NS3 Protease Inhibitors 172−175a

*: rat/15 mg/kg body weight ID/PEG/Tween 90:1/data 0−4 h. All physicochemical data values are abstracted from SciFinder and calculated using Advanced Chemical Development (ADC)/Laboratories) software v11.02. a

the compounds conform to the “rule of 5” guideline for HBD count, while the number of RBs is generally relatively well controlled for such large molecules.319,320 This is largely a function of the prevalence of macrocycles within the tripeptide acid/acylsulfonamide class that connects either P1 and P3 or P4

the second generation PIs are high MW compounds (Figure 21), but the acidic nature of the carboxy terminus moderates the cLog DpH7 values and likely confers transporter recognition, which contributes to their oral disposition.316−318 Nevertheless, these tripetidic molecules are membrane permeable, and all of 603



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Table 33. Biological Activity and PK Properties Associated with HCV NS3 Protease Inhibitors 176−178a

a

compd #

GT 1b Ki (nM)

GT 1b replicon EC50 (nM)

rat Cmax (nM)

rat plasma AU0−4 h (μM·h)

4 h liver concentration (μM)

176 177 178

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