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Structure-based library design and fragment screening for the identification of reversible complement Factor D protease inhibitors Anna Vulpetti, Stefan Randl, Simon Rüdisser, Nils Ostermann, Paulus Erbel, Aengus MacSweeney, Thomas Zoller, Bahaa Salem, Bernd Gerhartz, Frederic Cumin, Ulrich Hommel, Claudio Dalvit, Edwige Lorthiois, and Jürgen Maibaum J. Med. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jmedchem.6b01684 • Publication Date (Web): 03 Feb 2017 Downloaded from http://pubs.acs.org on February 6, 2017

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Journal of Medicinal Chemistry

Structure-based library design and fragment screening for the identification of reversible complement Factor D protease inhibitors

Anna Vulpetti,a* Stefan Randl,a†, Simon Rüdisser,a Nils Ostermann,a Paulus Erbel,a Aengus Mac Sweeney,a†† Thomas Zoller,a Bahaa Salem,a Bernd Gerhartz,a Frederic Cumin,a Ulrich Hommel,a Claudio Dalvit,a Edwige Lorthiois,a Jürgen Maibauma a

Novartis Pharma AG, Novartis Institutes for BioMedical Research, Novartis Campus, CH-4056 Basel, Switzerland

KEYWORDS: Alternative complement pathway, Factor D inhibitors, fragment-based screening, structure-based drug design, WaterLOGSY, ligand-observed 19F NMR screening

ABSTRACT: Chronic dysregulation of alternative complement pathway activation has been associated with diverse clinical disorders including age-related macular degeneration and paroxysmal nocturnal hemoglobinurea. Factor D is a trypsin-like serine protease with a narrow specificity for arginine in the P1 position, which catalyses the first enzymatic reaction of the amplification loop of the alternative pathway. In this paper, we describe two hit finding 1 ACS Paragon Plus Environment


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approaches leading to the discovery of new chemical matter for this pivotal protease of the complement system: in silico active site mapping for hot spots identification to guide rational structure-based design and NMR screening of focussed and diverse fragment libraries. The wealth of information gathered by these complementary approaches enabled the identification of ligands binding to different sub-pockets of the latent Factor D conformation and was instrumental for understanding the binding requirements for the generation of the first known potent non-covalent reversible Factor D inhibitors.

INTRODUCTION Factor D (FD) is the rate-limiting enzyme of the alternative complement pathway. It is a trypsinlike serine protease which circulates in blood as a mature, but proteolytically inactive, enzyme and which requires a highly specific mechanism for activation. There are no endogenous inhibitors known for FD and activation occurs upon binding to its only known natural substrate Factor B (FB) in complex with complement C3b. This induces a reversible conformational change of FD with subsequent cleavage of a single peptide bond of FB in the C3b:FB complex to form the products Ba and C3b:Bb. The surface-bound and proteolytically active C3b:Bb, also known as the C3 convertase, then cleaves C3 to form C3a and C3b, resulting in the amplification of the alternative complement pathway. Furthermore, generation of C5 convertase by additional recruitment of C3b and ultimately the downstream formation of membrane attack complex (MAC) lead to cell membrane disruption and lysis.1-5 Various human genetic polymorphisms of alternative pathway components, as well as other mechanisms responsible for over-activation of this pathway, have been linked to the predisposition and development of age-related macular

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degeneration (AMD), characterized by a slow progression in loss of central vision, as well as other rare diseases such as paroxysmal nocturnal haemoglobinuria (PNH).6 In the quest for noncovalent inhibitors of FD suitable for oral administration, which were unprecedented at the outset of our work, we have embarked on an extensive hit finding campaign by using multiple approaches in parallel.7 In a more detailed account, we describe herein how structure-based drug design (SBDD) was a valuable strategy to identify selective non-covalent inhibitors of the latent form of FD. This approach was of particular importance as high-throughput screening (HTS) of the large Novartis compound collection failed to deliver any validated hits by using two different assay formats.7 The SBDD approach was complemented by fragment-based screening (FBS) campaigns which, despite providing only a few validated hits, had a key impact on lead optimization. In particular, NMR screening of two fragment libraries will be discussed: the WaterLOGSY8 screening of a designed focussed target-based library of fragments and the

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F

NMR screening of the diverse Novartis library of fluorinated fragments known as LEF (Local Environment of Fluorine).9 RESULTS AND DISCUSSION Latent FD is unique among S1 serine proteases. The comparison of latent FD protein crystal structures1 with those of other serine proteases of the S1 family revealed three unique structural features: i) an atypical conformation of the catalytic triad (Asp102, His57 and Ser195; in cyan color in Figure 1a and Figure S1) in which the catalytic His57 is pointing away from Ser195 and is involved in H-bond interactions with the backbone carbonyl of Thr98 and the side chain of Glu60 (Figure 1a); ii) the presence of a distinctive self-inhibitory loop (amino acid residues 214 to 218; Figure 1a, shown in orange color); iii) a unique salt bridge between Asp189 and Arg218 at the bottom of the S1 pocket. Although the interaction of the Asp carboxylate with the Arg



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guanidinium is off from an ideal co-planar salt bridge, this twisted salt bridge is observed in many FD crystal structures (Figure S2a). As a consequence, latent FD has very low proteolytic activity towards arginine P1-containing peptide-substrate analogs.1 Gros et al. have shed further light on the substrate-dependent FD activation mechanism by elegant X-ray crystallography studies using the catalytically inactive S195A FD mutant.5 Accordingly, latent FD is activated by its substrate C3b:FB through allosteric interactions outside the active site (also known as exosite region) that trigger conformational changes at the catalytic site of FD. The crystal structure of the ternary complex C3b:FB:FDS195A (PDB code: 2xwb,5 3.5 Å resolution), not available at the time of our work, shows the catalytic site of FD in an enzymatically active conformation induced by the substrate binding at the exosite region, and a rearranged self-inhibitory loop conformation with the Arg218 side chain pointing out of the S1 pocket.

Figure 1. Crystal structure of FD (PDB code 1dic; the covalently bound ligand is omitted for clarity). a) Ribbon diagram showing the self-inhibitory loop in orange color and the catalytic


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triad highlighted in cyan. b) The binding site ‘site1’ generated by SiteMap is shown as grey translucent surface. The ‘site points’ (shown in white) cover a large region comprising the S1, S1β, S1´ and S2´ sub-pockets. The hydrophobic, H-bond donor and acceptor maps are shown in yellow (-0.5 kcal/mol iso-contour), blue (-10 kcal/mol) and red color (-10 kcal/mol), respectively.

Hot spot analysis via in silico active site mapping. Ligand-binding site prediction and characterization is an active field of research, and several different approaches are currently under development.10,

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The FD structure (PDB code 1dic,12 1.8 Å resolution) was used to

investigate the presence of hot spots for ligand binding by using the site analysis tools available in the Schrödinger13 commercial package. Hot spots are defined as those regions of the active site that contribute to a large fraction of the binding free energy. The Schrödinger SiteMap tool14 provides a wealth of information in the form of computed properties (see Table S1, Supporting Information) and graphical contour maps distinguishing regions in a binding pocket that are favourable for occupancy by hydrophobic, H-bond donor or H-bond acceptor ligand groups. The hydrophobic (depicted in yellow), donor (blue), and acceptor (red) maps for the PDB 1dic ‘site1’ (see Table S1) are shown in Figure 1b and are subsequently discussed in more detail. Access to the non-prime site is restricted in the latent FD conformation due to the presence of the selfinhibitory loop. Moreover, the reported observation that short peptide sequences spanning the prime and non-prime sites adjacent to the putative scissile bond are not recognized as substrates by latent FD4 suggested to us that the prime-site pockets are not readily accessible for the design of potent small-molecule inhibitors, but rather would require significant conformational movements. This part of the active site was therefore not considered attractive for drug design.



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The S1 sub-pocket has a mixed hydrophilic and hydrophobic character. Arg218 (explicitly depicted in Figure 1a) renders the bottom of the S1 pocket to be hydrophilic, while the peptide backbone between Cys191-Lys192 makes the ‘upper’ portion of the S1 site susceptible for hydrophobic/stacking interactions (yellow map in Figure 1b). The S1ʹ sub-pocket shows a red Hbond acceptor map in the vicinity of the Gly193 backbone NH (also known as the oxyanion hole), and a yellow hydrophobic map on top of the Cys42-Cys58 disulfide bridge. The OH group of Ser215 and the backbone NH of Gly216 offer opportunities for interactions with ligand Hbond acceptors (red map in Figure 1b). It is noteworthy, that in another publicly available crystal structure of FD covalently bound to isatoic anhydride (PDB code 1bio,2 1.5 Å resolution), the Ser215-Gly216 dipeptide portion adopts a flipped conformation in which the carbonyl of Ser215, instead of the NH of Gly216 as in the PDB 1dic structure, points into the cavity, thereby changing the H-bond binding opportunities in this portion of the binding site (Figure S2b). The region located on top of the Cys191-Cys220 disulfide bridge, also known as S1β pocket,15 has a predominantly hydrophobic character, with the potential for an additional H-bond interaction with the backbone NH of Cys220, as indicated by the small red spot in Figure 1b. A literature survey of known inhibitors of S1 proteases indicated that binding contacts in this region may contribute to improve ligand binding affinity.15 The S2ʹ sub-pocket offers opportunities for ligand H-bond donor (blue maps) as well as hydrophobic contacts (yellow maps, Figure 1b). The carbonyl of Leu41 located at the interface between the S1ʹ and S2ʹ sites is a potential partner for an interaction with a ligand H-bond donor feature. The backbone carbonyl of His40 is also pointing into the S2ʹ sub-pocket, but with a higher solvent accessibility. The hydrophobic hot spot constituted by Gly142 and the aliphatic side chain carbon atoms of Ile143 and Arg151 attracted our interest. The Arg151 side chain is 6 ACS Paragon Plus Environment

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flexible (Figure S2b) and projects the guanidinium terminal group into various different locations. However, the aliphatic portion of the Arg151 residue favorably contributes to the S2ʹ hydrophobic hot spot. In close proximity, the carbonyl of Trp141 is predicted to provide a potential opportunity for H-bond interaction with suitable ligands (Figure 1a). It is important to stress that these computational maps do not aim at providing a detailed description of all types of contacts that a ligand can make with various portions of the protein. The view is simplistic in terms of just hydrophobic, H-bond donor or acceptor maps, but nevertheless is useful to quickly get a good sense of key binding interaction opportunities within the predicted binding pocket of the target of interest. Not all potential interactions are well described by currently existing computational tools. For example, the H-bond donor blue map facing a protein carbonyl can also be considered as an opportunity for the formation of a halogen bond.16 The SiteMap tool14 as well as other computational algorithms for pocket characterization10 can inspire structure-based design. Retrospectively, we performed an independent hot spot analysis using the crystal structure of FD (PDB code: 1dic) with the publicly available FTMap software. Briefly, the FTMap approach17 samples the surface of a target protein by using 16 small organic molecules as probes and finds favorable positions using empirical free energy functions. For each probe type, the individual probe conformations are clustered and the clusters are ranked on the basis of average free energy. The regions that bind several probe clusters (consensus cluster) predict the binding hot spots. The consensus clusters are ranked on the basis of the total number of non-bonded interactions between the protein and all the probes in the cluster. The amino acid residues in contact with the probes of each defined cluster constitute the predicted ligand binding site (called FTSite). This information is accessible by using the FTSite algorithm,18 a publicly 7 ACS Paragon Plus Environment


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available method for binding site identification. Figure 2a highlights the FTMap consensus clusters for latent FD, and Figure 2b shows the three top-ranked predicted FTSite binding sites. Nearby consensus clusters can be fused together and the FTSite 1 corresponds to the consensus clusters CS001 in conjunction with CS002 (i.e., S1 and S1´ sub-pockets). The FTSite 2 corresponds to CS000 (i.e. the S2´ sub-pocket) and the FTSite 3 covers the non-prime site (CS004). The FTMap and SiteMap analyses gave consistent results, thereby clearly indicating the importance of the S1, S1β, S1ʹ and S2ʹ sites for ligand binding. Ranking among the different subpockets is possible in FTMap by calculating the consensus cluster strength S, which is defined as the number of probe clusters within the consensus cluster. A consensus cluster strength S>16 indicates a druggable pocket, while S30 µM) against human FD in a thioesterolysis assay,7,

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docking studies of a truncated (S)-proline-based analog indeed confirmed the S1´ proline binding pose to be compatible with the active site architecture of latent FD (R1=R2=Me, schematically depicted in Figure 5a). In this binding mode, the proline central scaffold is positioned in the FD S1ʹ sub-pocket with the carbonyl of the urea linker forming a H-bond with the NH of Gly193 in the oxyanion hole, and with the NH of the amide spacer forming a H-bond with the carbonyl of Leu41 (both in green in Figure 5b). These two H-bond interactions are important to anchor the proline core in the S1ʹ site and to provide suitable vectors for extensions towards both the S1 and the S2’ sub-pockets.


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Figure 5. Structure-based library design based on a proline scaffold: a) The central (S)configured proline scaffold (in green in panel b) forms two H-bond interactions with the NH of Gly193 and the carbonyl of Leu41, as indicated by the dashed lines. The two substituents, R1 and R2, point into the S1 and S2ʹ sub-pockets, respectively. b) The hydrophobic S1 and S2ʹ hot spots (in yellow color), the guanidinium NH of Arg218 (in blue color), the carbonyl of Leu41 and the NH of Gly193 (both in green color), the carbonyl of His40 and Trp141 (in red color), which all were targeted by the proline library design, are highlighted on the FD surface of the PDB code 1dic crystal structure. c) The torsion angles (TOR1) around the benzylic and the anilinic R1 groups are depicted in green and purple, respectively (see main text for discussion). d) 3D overlay of the docking poses of two library representatives: compounds 1 (green) and 2 (purple) of Chart 1.

Based on these findings, a small FD-focused (S)-proline-based library was designed by choosing R1 and R2 substituents able to target the most buried hot spots of the S1 and S2ʹ sub-pockets (Figure 5b) identified from the binding site analysis (vide supra). A combinatorial docking approach, using the crystal structure PDB code 1dic, was used to select the optimal R1 and R2 substituents from 3286 commercially available primary amines with a MW≤350. Instead of enumerating the entire virtual proline library which would have generated >9 million possible compounds, two independent docking calculations were carried out by keeping either R1 or R2 fixed to methyl, and by varying either the R2 or R1 residue, respectively. It was reasonable to assume that the effect of the two substituents would be additive, as the proline scaffold is well anchored and almost perfectly overlapped in the two docking runs. The docking was performed with Glide23, 24 requiring the presence of at least one of the two H-bonds formed by the urea and



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carboxamide linkers to the NH of Gly193 and/or the carbonyl of Leu41 as a constraint (Figure 5b). The final small selection of analogs proposed for synthesis was performed by visual inspection of the top scoring poses: twelve amines targeting the S1 pocket and four amines addressing the S2ʹ pocket. Two types of R1 residues were included in the selection: substituted benzyl and aryl moieties, as shown in Figure 5c. With respect to the benzylic R1 substitution, modelling suggested that a suitable H-bond acceptor in the ortho position could form a H-bond with the Arg218 side chain. A di-substitution pattern was proposed for aryl R1 moieties bearing a H-bond acceptor at the meta position, that could interact with the Arg218 side chain and, in addition, a group at the ortho position that would favor a properly distorted geometry to direct the aromatic portion into the narrow S1 pocket (Figure 5b). Figure 5d shows the overlay of the docked conformations of two representative target molecules, 1 and 2 (Chart 1). The carboxylic ester groups of 1 and 2 were predicted to occupy the same spatial position. The overlay highlights that the torsion angle (TOR1 in Figure 5c, d) around the anilinic phenyl and the urea functionality should be out of plane by ca. -60˚. Thus, we thought that replacing the NH spacer group with a CH2 could favor the required non-planar conformation. This was confirmed by the analysis of the conformational preference in small molecules of the Crystallographic Structural Database.25 Figure S3 (Supporting Information) summarizes the full torsional analysis by using various queries for the different S1-S1ʹ linkers under discussion. Exploration of the structure-activity relationship of the respective amide S1-S1ʹ linkers, however, was not primarily the focus of the initial prototype library design and will be discussed elsewhere. For the initial library, we limited the number of prime-site R2 moieties to four. Among them, the meta-trifluoromethoxy phenyl group was


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predicted to optimally fill the S2ʹ hydrophobic hot spot (see Figure 1b and Figure 5b) due to the characteristic perpendicular conformation of the CF3O group relative to the phenyl ring.26 In total, twenty (S)-proline-based analogs were prepared by parallel synthesis in three steps as illustrated for the representative analogs 2 and 3 in Scheme S1 (Supplementary Information). We were very gratified that several compounds, when tested in the enzymatic thioesterolysis assay, showed inhibitory activities with IC50 values of 30 µM) in the thioesterolysis assay. This is attributed to the planar conformation of the aryl OCH3 residue, which positions the smaller CH3 to a different area of the pocket thereby reducing the hydrophobic binding contacts.


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Compound 1 showed a IC50 value of 9 µM against KLK7 and selectivity against a panel of 10 human S1 proteases including kallikrein 5, chymotrypsin, trypsin, coagulation factor Xa, thrombin and neutrophil elastase (all IC50 values >30 µM). The overall binding of compound 1 matches remarkably well the hot spots derived from SiteMap and FTMap, and the shape of the pocket calculated by FTSite (Figure S5). The structural information of FD in complex with compound 1, in combination with results from structureguided fragment screening (described in the next paragraph), has provided a validated entry point for subsequent iterative lead optimization, eventually leading to highly potent, selective and orally efficacious inhibitors of human FD.7



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Figure 6. Soaked structure of 1 (cyan) in complex with FD (PDB code 5fbe7). The key intermolecular hydrogen bonds between the ligand and the protein are indicated by the red dashed lines. See Figure S4c for the electron density map of the bound ligand.

b) In silico FD focused fragment library for WaterLOGSY NMR screening. In parallel to the library design around the proline core, we also performed in silico fragments docking. A large set of ca. 50,000 fragments, physically available as powders in the Novartis compound archive, was collected based on well-defined selection criteria (see Experimental Section for more detail) and then docked into two structures of FD with very distinct characteristics for the S1 pocket: 1) the previously used published crystal structure PDB 1dic, in which Asp189 is engaged in a salt-bridge interaction with the Arg218; and 2) a manually modelled FD active site structure with an S1 ‘open conformation’ in which the Arg218 side chain has been displaced from its crystallographic location by disrupting the salt bridge. Such a conformation would in principle enable the carboxylic acid of Asp189 to make direct contacts with a given S1-binding fragment. The assumption for the existence of such an ‘open conformation’ of FD (later on confirmed by the X-ray crystallography work described by Gros et al.5) was corroborated by the fact that FD binds the C3b:FB substrate and cleaves FB between Lys234 and Arg235, unequivocally demonstrating arginine specificity at the S1 pocket. We also reasoned that the irreversible

covalent

FD

inhibitor,

2-carbamimidoylbenzo[b]thiophen-6-yl

thiophene-2-

carboxylate (BCX-1470),27 bearing a classical basic benzamidine motif, is very likely recognized by an ‘open S1 conformation’ of FD via a charged interaction with the Asp189 carboxylate prior to covalent bond formation with the catalytic Ser195.


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All top-scored poses of fragments docked into the two protein conformations covered the S1 subpocket with or without filling in addition the S1ʹ pocket. To readily organize, analyze, and visualize the vast amount of information generated by the two docking studies, the docked protein−ligand complexes were grouped into four subsets depending if neutral or charged groups of the ligand were putatively forming H-bonds with either Arg218 or Asp189. The underlying idea was to diversify the selection of S1-binding motifs with different characteristics by visualizing and selecting ligands from each of the four categories and not just simply relying on scoring values, which would have biased the selection towards ionic interactions. A set of finally selected 192 fragments was screened in mixtures of eight compounds by using the ligand-observed WaterLOGSY8 NMR technique. Deconvolution performed on the active mixture identified compound 4 (Figure 7) as a binder (Figure S6, Supporting Information). Due to its low solubility (~30 µM), protein-based 2D 1H15N HSQC28 NMR measurements did not provide any evidence of binding. X-ray structure analysis using the soaking and cocrystallization methods also failed, most likely due to the limited solubility and low affinity of the compound. We therefore reasoned that optimization of the neutral fragment 4 for water solubility could provide a valid strategy in order to gain structural insight into its target binding interactions. Identifying unique poses by docking fragments can be a challenge. A single binding mode could not be proposed for 4 with high confidence. However, the docking poses generated on both ‘open and close’ S1 conformations suggested that the 2-carboxamide indole scaffold is binding deep into the S1 cavity and that the tethered phenyl ring is exposed to the solvent. Based on this notion, a more soluble derivative of 4, compound 5 (Figure 7) bearing a solubilizing carboxylic acid moiety at the putative solvent exposed meta-phenyl position, was synthesized and 19 ACS Paragon Plus Environment


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subsequently confirmed as a binder by WaterLOGSY. In addition, the higher solubility of 5 (~2 mM) allowed confirmation of its binding to FD by protein-observed 2D 1H15N HSQC NMR and determination of its binding constant (Kd = 1600 µM).7

Figure 7. Co-crystal structure of 5 (cyan) bound to FD (PDB code 5fbi7). Key intermolecular hydrogen bonds between the ligand and the protein are indicated by red dashed lines.

In line with the improved solubility of 5, its crystal structure in complex with FD could be solved by co-crystallization at 1.46 Å resolution (Figure 7). The analysis of the data revealed electron density for the indole-carboxamide moiety of 5 in the S1 pocket, while the benzyl ether moiety lacked electron density and appeared to be disordered as it is pointing towards the solvent, as predicted (Figure S7 shows the partially visible electron density of the bound ligand). The indole


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ring is sandwiched between Ser217 of the self-inhibitory loop and the Lys192 side chain. The self-inhibitory loop adopts a conformation similar to that observed in the FD crystal complex with inhibitor 1. The salt bridge between Arg218 and Asp189 at the bottom of S1 is still formed. The NH2 and carbonyl oxygen of the amide group form H-bond interactions to the backbone carbonyl of Thr214 and to the Arg218 side chain of the self-inhibitory loop, respectively. The nitrogen atom of the indole ring is at H-bond distance to the backbone carbonyl group of Arg218. The crystal structure of fragment 5 in complex with FD highlighted for the first time the type of H-bond interactions that can be formed between a neutral ligand and the S1 sub-pocket. These intriguing findings were instrumental for our subsequent SAR optimization work and enabled us to efficiently improve the inhibitory potency of the proline-based inhibitor 1 against FD by using a ligand merging strategy.7 Furthermore, the indole-carboxamide scaffold of 5 was considered as an attractive S1 starting point for growing towards identified hot spots for ligand binding, which will be reported elsewhere in due course. c) Screening of diverse Novartis corporate fragment libraries. In addition to the targetbased focused set of fragments (vide supra), and in the course of our continued research efforts on developing FD inhibitors, we screened two diverse corporate fragment libraries, each constituted of ca. 1400 small molecules: the LEF library9 which is a library of fluorinated fragments bearing CF3, CF2 and CF groups designed for ligand-observed 19F NMR screening29 in mixtures of 15 or 30 fragments, and a library of fragments suitable for various biophysical and biochemical screening techniques, called the CORE library. While screening of our CORE library against human FD by protein-observed NMR (2D 1H15N HSQC) was unsuccessful in delivering any validated hits, five weak-affinity hits were identified from the LEF library (0.35% hit rate). Previous screening of the LEF library against several other protease targets had resulted



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in all cases in significantly higher hit rates. As an example, LEF screening by 19F NMR against bovine trypsin had provided 31 hits, corresponding to a 2.15% hit rate with a 40% success rate in crystal structure determination.30 Interestingly, all the five low-affinity FD hits are bearing a CF moiety. As previously discussed,31 the CF moiety is more sensitive to protein binding than the CF3 by using the NMR detection method due to the larger difference in

19

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F

F chemical shifts between the free and

bound state of a CF containing molecule versus that of a CF3. The two structurally most dissimilar LEF hits, compounds 6 and 7, are shown in Chart 2. The screening results for the active mixture of the LEF library containing compound 7 against FD are shown in Figure S8 (Supporting Information).

LEF Hits by 19F NMR screening

SAR by Archive

Fragment Hopping

Chart 2. Elaboration of initial fragments hits (compounds 6 and 7) derived from the

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F NMR

screening of the LEF library. The mixture of racemic trans:cis (85:15) diasteroisomers 8 and compound 9 were identified as hits by a 19F NMR reporter assay and subsequently validated by 22 ACS Paragon Plus Environment

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protein-observed NMR (2D 1H15N HSQC). Compound 8 was derived from a structure-activity relationship (SAR) by archive effort and compound 9 from a subsequent ‘fragment hopping’ selection.

No evidence for binding could be observed in protein-observed NMR (2D 1H15N HSQC) experiments, nor could crystal structures be obtained for any of the five LEF hits, which we attributed to the very low affinity of these fragments to FD. As no in silico binding mode could be proposed with high confidence, we performed an SAR by archive search (docking, 2Dsimilarity, sub-structure searches) for related analogs in the Novartis compound collection. About 50 close analogs were selected with the aim of finding compounds with improved potency and good solubility, to enhance the probability for successful protein–ligand crystal structure determination. As these compounds were screened in a

19

F NMR reporter assay,32 the presence

of a ligand fluorine atom in the tested molecules was not required. Compound 8, a racemic (85:15)-mixture of trans:cis diasteroisomers (Chart 2), was the only one for which a crystal structure could be solved (Figure 7a). Compound 8 showed a Kd of ~500 µM (based on the

19

F

NMR reporter assay), which was also confirmed by protein-observed NMR (2D 1H15N HSQC). Only the trans-configured stereoisomer (1S,2S)-8 was observed to be bound in the enzyme active site. Intriguingly, the indole portion binds in S1ʹ with the carboxylic acid interacting with the NH of Gly193 and the side chain hydroxyl of Ser195 (modelled in two conformations in the electron density map, see Figure S9a, Supporting Information). The self-inhibitory loop was also observed to adopt two conformations (Figure S9a). The catalytic His57 is again in an outward conformation. The NH of the indole is involved in a H-bond with the backbone carbonyl of Ser215 of the self-inhibitory loop while the fluoro-phenyl portion of the indole makes no



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interaction with FD. The carboxamide NH forms a H-bond with the backbone carbonyl of Leu41, while the trans-configured cyclopropyl extended linker places the terminal phenyl deep into the S2ʹ hydrophobic hot spot at the same position occupied by the CF3O motif of compound 1 in its complex to FD (Figure S10a). Interestingly, the guanididium group of the Arg151 side chain forms a π-cation interaction33, 34 with the terminal phenyl ring, thereby shielding the S2ʹ sub-pocket from solvent. The (1S,2S)-2-phenylcyclopropanyl pharmacophore has been subsequently merged with the S1-S1' scaffold derived from inhibitor 1 leading to potent FD inhibitors,35 which will be reported elsewhere in due course. The binding interactions of S1 protease inhibitors bearing a free carboxylic acid to the oxyanion hole have been previously reported.36-38 However, the position of a COOH group in close proximity to the oxyanion hole, as observed for (S,S)-8 in the crystal complex structure with a His57 flipped-out conformation, is to the best of our knowledge unprecedented. A follow-up ‘fragment hopping’ was then carried out on compound 8 by performing a molecular-fields ligand-based 3D similarity search39 against the Novartis compound collection as a de novo design fragment approach. Five chemical 2D-dissimilar fragments were selected by visual inspection, and one fragment, compound 9 (Chart 2) was found to have a similar binding affinity to FD with a Kd value of ~500 µM (determined by the

19

F NMR reporter assay). The

predicted binding mode of 9 based on molecular-fields alignment (Figure 8b) was confirmed by X-ray crystallography (Figure 8a). Compound 9 binds in a similar way compared to 8, by forming H-bonds with the side chain of Ser195 and with the NH of Gly193. Both urea NH groups of 9 are close to the backbone carbonyl of Leu41, with the distal NH on the S2ʹ side forming a H-bond interaction (with a distance dN-O=2.8 Å, Figure S9b, Supporting Information). Both crystal structures of FD in complex with 8 and 9 show Arg218 and Asp189 involved in a 24 ACS Paragon Plus Environment

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salt bridge at the bottom of the S1 pocket, as observed in the crystal structures of FD in complex with 1 and 5 (Figure S10b). The carboxylic acids of 8 and 9 mimic the interaction of the carbonyl urea of 1 with the NH of Gly193 (Figure S10b). It is worth noting the success of the applied fragment hopping approach in providing an additional starting point for further inhibitor optimization with a limited screening effort. The careful selection of bioisosteric molecules proved to be a valuable approach to identify a different chemical series with similar binding properties. This is a nice example showing how to capitalize on the knowledge of the binding information of the identified hits.

Figure 8. a) Overlay of FD crystal structures in complex with 8 (yellow, PDB code 5mt0, only the ligand is shown) and 9 (cyan, PDB code 5mt4, the protein is shown in grey color); b) Overlay of compounds 8 (yellow) and 9 (cyan) based on XED (eXended Electron Distribution)



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field points. The cyan color of the points corresponds to areas of high electron density, where the electrostatic negative field is important; sand color corresponds to areas of hydrophobicity; shape/van der Waals descriptors are in yellow color and areas with low electron density corresponding to positive electrostatic fields are shown in brown color.

d) Experimental vs. in silico SiteMap and FTMap druggability scores. The above described fragment-based screening campaigns revealed FD to be a challenging target with a low experimental ligandability score, applying the scoring system40 utilized at Astra Zeneca. This scoring system takes into account the fragment screening hit rates, the hits affinity range and their diversity.41 Researchers at Abbott42 also proposed fragment screening outcomes to be a useful approach for ligandability assessment of novel targets. In this context, we have also 19

proposed ligand-based

F NMR-based screening as a convenient experimental approach for

ligandability assessment43 of novel targets, as it can be performed with limited amount of protein and resources early in the drug discovery process. An example of

19

F NMR-based fragment

screening as quick and efficient means of assessing target ligandability has also been reported by researchers at Amgen.44 The in silico assessment of ligandability still remains challenging. SiteMap, in addition to identifying and characterizing binding sites, also provides a druggability score (Dscore) associated to them. A Dscore value of 0.99 was calculated for the large FD active site depicted in Figure 1b,

which

corresponds

to

a site classified

as

borderline between

being

‘difficult/druggable’.45 This might be ascribed to the spread of the hot spots over a large binding area (size=132; see Table S1, Supporting Information, for all the SiteMap descriptors) thus


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resulting in an intrinsic difficulty in identifying highly efficient small fragments. The calculated Dscore for trypsin is lower (DScore=0.87, PDB code 2zft) than that of FD, but calculated on a smaller pocket (size=73, at the S1 site). This might explain the higher FBS hit rate obtained for trypsin vs. FD (using the same 19F NMR method and library). However, it is worth pointing out that SiteMap aims at predicting druggability and not ligandability. Druggability is defined as the probability of success in developing an orally bioavailable, pharmaceutically useful drug candidate whereas a protein is ligandable if potent small-molecule ligands can be found for it. Thus, the lower Dscore for trypsin can be most likely ascribed to its charged S1 pocket characteristics. A charged (or a very hydrophilic) ligand can bind tightly, but it could be more challenging to convert it into a drug with good pharmacokinetic properties. The druggability assessment of FTMap is also in line with the low experimental FBS and HTS hit rate for FD, as all the three top ranked consensus clusters have consensus clusters strength S≤14. However, in silico assessment of ligandability still needs to be taken with caution in decision-making processes, while an estimate of ligandability by experimental FBS can be more informative. In situations of experimental low ligandability, approaches other than HTS, such as the structure-based / knowledge-based approaches and sensitive screening biophysical assays described here can be very valuable.

CONCLUSIONS Several SBDD and FBS approaches were applied successfully for identifying structurally distinct validated hits as non-covalent ligands weakly binding to complement FD, a serine protease of the S1 family involved in the activation loop of the alternative complement pathway. Both



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approaches represented a valuable strategy to tackle the atypical active site architecture of FD in its latent conformation, for which HTS of large compound collections in our hands did not deliver any useful chemical starting points. The hypothesis that a center N-acylated (S)-prolinecarboxamide core could serve as a well-anchored S1’ scaffold, as observed in the case of the S1 protease KLK7, provided the rational for designing a FD-tailored library. Compound 1 was rapidly identified as FD inhibitor with micromolar IC50 in a thioesterolysis assay by incorporating substituents able to target the hot spot regions in the S1 and S2’ sub-pockets as derived by the in silico mapping of the putative binding site. The predicted binding pose of 1 to the latent active site conformation was confirmed by its high-resolution X-ray crystal structure in complex with FD. In parallel, a small focused set of fragments, selected by high-throughput docking of a large fragment library and screened by WaterLOGSY, led to the identification of the non-canonical S1 binding fragment 4 and its more soluble analog 5, which was demonstrated by X-ray crystallography to bind deeply into the unique S1 pocket of latent FD in its closed conformation. Moreover, the 19F NMR screening of the LEF library of fluorinated fragments followed by SAR by archive and 3D similarity searches provided complementary structural information by identifying fragments 8 and 9, both binding to the S1ʹ and S2ʹ pockets and interacting with their free carboxyl acid moiety to the oxyanion hole of the enzyme in an unprecedented His57 flippedout conformation. In summary, an early, effective and integrated implementation of computational approaches, parallel chemistry, NMR screening and X-Ray crystallography has identified the first reversible inhibitors of FD, for which at the time of this research effort, only covalent FD inhibitors were known. Subsequent optimization by merging the key binding elements of these low affinity


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molecules interacting at different sub-pockets, as elucidated by crystal structures, has resulted in the generation of potent FD inhibitors.7

EXPERIMENTAL SECTION General computational information. All proteins used in this study were prepared in Maestro46 Protein Preparation Wizard. Water molecules were removed. Protonation states were set at pH 7.4 using Epik.47 The catalytic His57 residue was manually protonated. The docking of the proline library and of the Novartis fragment set was performed with Glide23, 24 into an adapted PDB crystal structure 1dic of human FD (with a torsional angle for N-Cα-Cβ-OG of the Ser195 side-chain set to Χ1 = 170˚, as observed in the KLK7 crystal complex, to allow for direct H-bond interaction of the urea carbonyl of the proline ligand with the NH of Gly193). The fragment set consisting of 51,746 fragments was collected from the Novartis database according to the following criteria (calculated with Pipeline Pilot48): available amount >20 mg; 150 ≤ MW ≤ 300; number of H-bond acceptors + number of H-bond donors ≥3; exclusion of noorganic atoms; Atomic logP49 (AlogP) ≤3; number of rotatable bonds ≤4; 1 ≤ number of rings ≤ 4; number of atoms with unknown stereochemistry/isomerism = 0; undesirable chemical functionalities were filtered out. In order to find all possible protein binding sites of FD, SiteMap14 was used with all default parameters. For each input protein, a list of up to five potential binding sites was saved. The PDB protein structure 1dic was also submitted to the FTMap and FTSite servers (http://ftmap.bu.edu and http://ftsite.bu.edu/, respectively). The FTMap and FTSite algorithms are described in detail in the literature.17,18 Molecular shapes and the XED (eXended Electron Distribution) field



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similarities were calculated by using the Blaze program (previously known as FieldScreen) from Cresset.39 Chemistry. Unless otherwise specified, all solvents and reagents were obtained from commercial suppliers and were used without further drying or purification. Normal phase flash chromatography was performed using Merck silica gel 60 (230-400 mesh), Darmstadt, Germany. Rf values for thin layer chromatography (TLC) were determined using 5 x 10 cm TLC plates, silica gel F254, Merck, Darmstadt, Germany. 1H NMR spectra were recorded on a Bruker Avance DPX 400 BBO spectrometer. The analyses were performed by using electrospray ionization in positive ion modus after separation by liquid chromatography (Nexera from Shimadzu). The elemental composition was derived from the mass spectra acquired at the high resolution of about 30’000 on an LTQ Orbitrap XL mass spectrometer (Thermo Scientific). The high mass accuracy below 1 ppm was obtained by using a lock mass. Mass-spectra and LC/MS were determined using an Agilent 1100 series instrument. Purity was determined by analytical HPLC using an Agilent 1100 or 1200 series instrument, by integration of the area under the UV absorption curve at λ =254 nm or 214 nm, tR refers to retention time. The following conditions were used for analytical (a to c) or preparative (d) HPLC. Conditions a: Waters Symmetry C18, particle size 3.5 µm, column size 2.1 x 50 mm, eluent/gradient 20-95% CH3CN/H2O/3.5 min, 95% CH3CN/2 min (CH3CN and H2O containing 0.1% TFA), flow rate 0.6 mL/min, column temperature 25 °C. Conditions b: Waters X-Bridge C18, particle size 2.5 µm, column size 3 x 50 mm, eluent/gradient 10-98% CH3CN/H2O/8.6 min, 98% CH3CN/1.4 min (CH3CN and H2O containing 0.1% TFA), flow rate 1.4 mL/min, column temperature 40 °C. Conditions c. Waters Sunfire C18, particle size 2.5 µm, column size 3.0 x 30 mm, eluent/gradient 10-98% CH3CN/H2O/2.5 min (CH3CN and H2O containing 0.1% TFA), flow rate 30 ACS Paragon Plus Environment

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1.4 mL/min, column temperature 25 °C. Conditions d: Waters Sunfire C18-ODB, particle size 5 µm, column size 30 x 100 mm, eluent/gradient 20-100% CH3CN/H2O/20 min, 100% CH3CN/3 min (CH3CN and H2O containing 0.1% TFA), flow rate 40 mL/min. All final compounds had a purity of ≥95%. Methyl (S)-2-((2-((3-(trifluoromethoxy)phenyl)carbamoyl)pyrrolidine-1carboxamido)methyl)benzoate (1) and 3-(((2-carbamoyl-1H-indol-5-yl)oxy)methyl)benzoic acid (5). The synthesis of these two compounds is described in the preceeding article.7 (S)-Methyl 4-methyl-3-(2-((3-(trifluoromethoxy)phenyl)carbamoyl) pyrrolidine-1-carboxamido) benzoate (2). The compound as a slightly colored solid (51.7 mg, 46%) was prepared from methyl 3-amino-4-methylbenzoate according to the procedure described for the preparation of 3. tR (HPLC conditions a) 3.55 min, purity 96.7%; LC/MS: 464.0 [M-H]-, 466.1 [M-H]-; 1H NMR (400 MHz, CDCl3): δ (ppm) 10.0 (s, 1H), 8.32 (m, 1H), 7.79 (dd, J = 7.9, 1.6 Hz, 1H), 7.68 (s, 1H), 7.36 (m, 1H), 7.29 (m, 2H), 6.92 (m, 1H), 6.21 (s, 1H), 4.78 (d, J = 7.6 Hz, 1H), 3.91 (s, 3H), 3.60 (td, J = 8.1, 1.3 Hz, 1H), 3.45 (m, 1H), 2.70 (dd, J = 12.5, 6.2 Hz, 1H), 2.33 (s, 3H), 2.28 (m, 1H), 2.18 (m, 1H), 1.93 (m, 1H). (S)-Methyl

3-(2-((3-(trifluoromethoxy)phenyl)carbamoyl)pyrrolidine-1-carboxamido)-

benzoate (3). (S)-2-(3-trifluoromethoxy-phenylcarbamoyl)-pyrrolidine-1-carboxylic acid tertbutyl ester: To a mixture of N-Boc-L-proline (5.00 g, 23.2 mmol), 3-(trifluoromethoxy)aniline (3.73 mL, 27.9 mmol) and HBTU (13.2 g, 34.8 mmol) in DMF (60 mL) was added diisopropylethylamine (7.95 mL, 46.5 mmol) and the resulting yellow solution was stirred at room temperature under a nitrogen atmosphere for 16 h. The solvent was then concentrated under vacuum and the residue was dissolved in EtOAc and washed with an aqueous 1N HCl solution. The combined organics were neutralized by addition of a saturated aqueous NaHCO3 31 ACS Paragon Plus Environment


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solution. The layers were separated and the water phase was back-extracted twice with CH2Cl2. The combined organic extracts were dried (Na2SO4), filtered and concentrated. The crude residue was purified by flash column chromatography on silica gel (c-hexane/EtOAc 3:1 to 2:1) to afford (S)-2-(3-trifluoromethoxy-phenylcarbamoyl)-pyrrolidine-1-carboxylic acid tert-butyl ester as an orange solid (8.52 g, 98%). TLC, Rf (c-hexane/EtOAc 1:1) 0.6; MS (LC/MS): 397.1 [M+Na]+, 275.2 [MH-Boc]+, 373.3 [M-H]-; tR (HPLC conditions a) 3.81 min; 1H NMR (400 MHz, CDCl3): δ (ppm) 9.80 (br, s, 1H), 7.59 (s, 1H), 7.28 (m, 2H), 6.89 (m, 1H), 4.47 (m, 1H), 3.42 (m, 2H), 2.26 (m, 1H), 1.94 (m, 3H), 1.50 (s, 9H). (S)-pyrrolidine-2-carboxylic acid (3-trifluoromethoxy-phenyl)-amide as the trifluoroacetate salt: To a solution of (S)-2-(3-trifluoromethoxy-phenylcarbamoyl)-pyrrolidine-1-carboxylic acid tertbutyl ester (5.91 g, 15.8 mmol) in CH2Cl2 (10 mL) was added TFA (4.48 mL, 63.1 mmol) and the solution was stirred at room temperature for 24 h. The crude reaction mixture was concentrated under vacuum, Et2O was added and the white precipitate was filtered off to give (S)-pyrrolidine-2-carboxylic acid (3-trifluoromethoxy-phenyl)-amide as the trifluoroacetate salt as a slightly brown solid (5.04 g, 82%). MS (LC/MS): 275.2 [M+H]+, 273.3 [M-H]-; tR (HPLC, conditions a) 2.47 min; 1H NMR (400 MHz, DMSO-d6): δ (ppm) 10.8 (s, 1H), 9.27 (br, s, 1H), 8.73 (br, s, 1H), 7.79 (s, 1H), 7.50 (m, 2H), 7.13 (d, J = 6.8 Hz, 1H), 4.34 (m, 1H), 3.30 (m, 2H), 2.36 (m, 1H), 2.02 (m, 1H), 1.94 (m, 2H). (S)-Methyl

3-(2-((3-(trifluoromethoxy)phenyl)carbamoyl)pyrrolidine-1-carboxamido)benzoate

(3): To a solution of methyl 3-aminobenzoate (50.0 mg, 0.32 mmol) and triethylamine (81 mL, 0.58 mmol) in toluene (5 mL) was added phosgene (20% in toluene; 345 mL, 3.27 mmol) and the reaction mixture was stirred at 100 °C for 2 h. After cooling to room temperature, nitrogen was bubbled through the solution for 5 min. The solvent was evaporated, THF (5 mL) was added


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to the residue followed by triethylamine (95 mL, 0.68 mmol) and (S)-pyrrolidine-2-carboxylic acid (3-trifluoromethoxy-phenyl)-amide (138 mg, 0.360 mmol). The reaction mixture was stirred at room temperature until completion of the reaction and was then concentrated under vacuum. The crude residue was dissolved in EtOAc, a 1N HCL solution was added and the organic phase was separated. The aqueous layer was extracted twice with AcOEt and the combined organics were dried (Na2SO4), filtered and evaporated to dryness. The crude residue was purified by preparative HPLC to afford 3 as a slightly yellow solid (60 mg, 41%). tR (HPLC, conditions b) 4.56 min, purity 100%; LC/MS: 450.1 [M-H]-, 452.0 [M-H]-; 1H NMR (400 MHz, CDCl3) δ (ppm): 9.92 (s, 1H), 7.96 (t, J = 1.9 Hz, 1H), 7.79 (m, 2H), 7.68 (s, 1H), 7.43 (t, J = 8 Hz, 1H), 7.34 (m, 1H), 7.28 (t, J = 8.1 Hz, 1H), 6.92 (d, J = 7.8 Hz, 1H), 6.48 (s, 1H), 4.76 (d, J = 7.6 Hz, 1H), 3.92 (s, 3H), 3.59 (m, , 1H), 3.45 (m, 1H), 2.66 (dd, J = 12.4, 6.1 Hz, 1H), 2.26 (m, 1H), 2.18 (m, 1H), 1.93 (m, 1H); HRMS: 452.14273 [M+H]+ (calcd 452.14278 for C21H21O5N3F3). Compounds 6-9 are commercially available: 6 (CAS Registry Number: 1512-99-8); 7 (CAS Registry Number: 370846-48-3); 8 (CAS Registry Number: 890093-48-8); 9 (CAS Registry Number: 728911-05-5). Preparation of human FD catalytic domains. Human CFD (UniProt P00746) catalytic domain (G24-A253) was amplified by PCR using an in-house cDNA collection. The PCR products were cloned into pET24 (Novagen) and expressed in Escherichia coli (Rosetta) in form of inclusion bodies. Inclusion bodies were solubilized in 6 M guadinium HCl containing 100 mM DTT to reach a protein concentration of approximately 5 to 10 mg/mL. Pro-FD refolding was obtained by rapid dilution of solubilized inclusion bodies at 10 °C with 50 mM Tris/HCl (pH 8.5) containing 0.8 M arginine, 10 mM CaCl2, 1 mM EDTA, 1 mM GSH, and 0.5 mM GSSG, leading to a final protein concentration of 50 µg/mL. After gentle agitation at 10 °C for one day,



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the protein was concentrated and purified by size-exclusion chromatography (SEC). The FD catalytic domain was formed by removal of the pro-peptide sequence in the presence of trypsincoated beads for 6 h at 8 °C. For the analogous preparation of uniformly human FD, a M9 minimal medium with

15

15

N-isotope labeled

NH4Cl as the sole nitrogen source was used.

Complement FD thioesterolysis assay. The FD thioesterolysis assay was performed according to published procedures.7, 22 A typical dose response curve for compound 1 is reported in Figure S11. NMR spectroscopy. WaterLOGSY,8 2D 1H-15N HSQC28 and

19

F T2 filter29 experiments were

performed on Bruker AvanceII 500 and 600 MHz spectrometers and/or on an AvanceIII HD 800 MHz spectrometer equipped with a cryogenically cooled probe-head. Screening of the target-based focused set of fragments against the human FD was performed by WaterLOGSY at 10 µM protein concentration and nominal 100 µM compound concentrations. Spectra were recorded with 256 scans and 1.6 s mixing time at 296K, and by using excitation sculpting for water suppression.50 Compounds were screened in mixtures of eight. A binding hit was defined by a change of sign of the WaterLOGSY signal relative to the unbound compound. Two dimensional 1H15N HSQC experiments were recorded at 310K using flip-back pulses51 and a Watergate52,

53

sequence for water suppression. The NMR samples contained 100 µM

uniformly 15N labeled FD, 50 mM Tris-D11 (Cambridge Isotope Laboratories (CIL), 98% DLM1814-5), 100 mM NaCl (Fluka Catalogue Nr. 71376), and 10% D2O (CIL DLM-2259-1). Dissociation constants were calculated by assuming the formation of a 1:1 complex and by fitting the data according to the published protocol.54 The molecules of the LEF library9 were tested in mixtures containing either 15 or 30 compounds. The concentration of the CF- and CF3-containing molecules was 35 µM and 18 µM, respectively.


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The NMR samples were in 50 mM Tris, 100 mM NaCl, pH 8.0, and contained 9% D2O for the lock signal. All the 19F NMR experiments were recorded at 297K. The T2 filter experiments were recorded with the Carr-Purcell-Meiboom-Gill scheme55 with a time interval of 40 ms between the 180º pulses and with different total lengths. The spectra were acquired with proton decoupling using the WALTZ-16 composite pulse sequence during the acquisition time. The free induction decays were multiplied with an exponential multiplication window function with a linewidth of 1 Hz before Fourier transformation. SAR by archive was followed by NMR using the FAXS method (Fluorine chemical shift Anisotropy and eXchange for Screening).32 Compound 1 was used as a spy (reporter) molecule and its displacement was monitored. The NMR sample contains 6 µM FD protein, 25 µM compound 1 and up to 1000 µM of the tested fragment analogs. Compounds showing competition were confirmed for binding by two dimensional 1H15N HSQC experiments. FD crystallography. Human FD was crystallized by the hanging drop vapour diffusion method. A 1 µL FD solution (18 mg/mL FD, 10 mM Tris pH 7.0, 100 mM NaCl) was mixed with 1 µL reservoir solution (25% PEG3350, 100 mM BIS-TRIS pH 6.5 for 8, or 26% PEGME2000, 100mM Bis-Tris pH 6.5 for 9) and was equilibrated against 1 mL reservoir solution. Glutaraldehyde cross-linked crystals were soaked overnight with 25 mM compound 8 and flashfrozen in liquid nitrogen. Compound 9 was soaked into crystals by the addition of 10 mM compound to the crystal containing drop and incubation overnight was followed by direct flash freezing. X-ray diffraction data were collected from single crystals at the Swiss Light Source, beamline X10SA, equipped with a PILATUS pixel detector. The diffraction data were processed and scaled with XDS and XSCALE,56 respectively. The structures were solved by molecular replacement using the program MOLREP and the coordinates of PDB code 1bio as search



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model. Structures were built using the program COOT57 and were refined using the programs Refmac.58 Images were generated using the program PyMOL.59

ASSOCIATED CONTENT Supporting Information. Overlay of multiple FD PDB crystal structures; Crystallographic Structural Database (CSD) analysis of benzylic and anilinic proline-ureas torsion angles; WaterLOGSY spectrum recordered for compound 4 in the presence of FD;

19

F NMR spectra recordered for the mixture containing

compound 7 in the absence and in the presence of FD; all computed properties calculated with SiteMap; overlay of FD crystal structures bound to compounds 1, 5, 8 and 9; electron density of the bound ligand 1 and 5; overlay of FD crystal structures bound to compound 1 with the consensus clusters and the binding sites predicted by FTMap and FTSite; synthetic scheme for the preparation of 2 and 3; FD crystal structures in complex with compound 8 and 9; 2D depiction of the small molecules in the complex with PDB code 2zft and 5fah of Figure 4b; dose reponse curve for inhibition of FD activity for 1 (PDF). Molecular formula strings and the associated biochemical data (CSV). This material is available free of charge via the Internet at http://pubs.acs.org.” Accession Codes The atomic coordinates of FD complexed with compounds 8 and 9 have been deposited in the Protein Data Bank with accession codes 5mt0 and 5mt4, respectively. Authors will release the atomic coordinates and experimental data upon article publication.


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AUTHOR INFORMATION Corresponding Author *Corresponding author: To whom correspondence should be addressed. Tel: +41-61-3241016. Email: [email protected]. Present Addresses † Stefan Randl: Evonik Japan Co., Ltd., Shinjuku Monolith 12F, 2-3-1, Nishi-Shinjuku, Shinjuku-ku, 163-0938 Tokyo. ††Aengus Mac Sweeney: Drug Discovery Department, Actelion Pharmaceuticals Ltd., CH-4123 Allschwil, Switzerland. Notes The authors declare competing financial interest.

ACKNOWLEDGMENT We thank Allan D'Arcy, Frederic Villard and Florence Zinc for their assistance in preparing FD – fragments complex crystals.

REFERENCES 1.

Volanakis, J. E.; Narayana, S. V. Complement factor D, a novel serine protease. Protein

Sci. 1996, 5, 553-564. 2.

Jing, H.; Babu, Y. S.; Moore, D.; Kilpatrick, J. M.; Liu, X. Y.; Volanakis, J. E.;

Narayana, S. V. Structures of native and complexed complement factor D: implications of the 37 ACS Paragon Plus Environment


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atypical His57 conformation and self-inhibitory loop in the regulation of specific serine protease activity. J. Mol. Biol. 1998, 282, 1061-1081. 3.

Jing, H.; Macon, K. J.; Moore, D.; DeLucas, L. J.; Volanakis, J. E.; Narayana, S. V.

Structural basis of profactor D activation: from a highly flexible zymogen to a novel selfinhibited serine protease, complement factor D. EMBO J. 1999, 18, 804-814. 4.

Taylor, F. R.; Bixler, S. A.; Budman, J. I.; Wen, D. Y.; Karpusas, M.; Ryan, S. T.;

Jaworski, G. J.; Safari-Fard, A.; Pollard, S.; Whitty, A. Induced fit activation mechanism of the exceptionally specific serine protease, complement Factor D. Biochemistry 1999, 38, 2849-2859. 5.

Forneris, F.; Ricklin, D.; Wu, J.; Tzekou, A.; Wallace, R. S.; Lambris, J. D.; Gros, P.

Structures of C3b in Complex with Factors B and D Give Insight into Complement Convertase Formation. Science 2010, 330, 1816-1820. 6.

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