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Computational discovery of potent and bioselective protoporphyrinogen IX oxidase inhibitor via fragment deconstruction analysis Ge-Fei Hao, Yang Zuo, Sheng-Gang Yang, Qian Chen, Yue Zhang, Chun-Yan Yin, Cong-Wei Niu, Zhen Xi, and Guang-Fu Yang J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.7b01557 • Publication Date (Web): 27 Jun 2017 Downloaded from http://pubs.acs.org on July 3, 2017

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Journal of Agricultural and Food Chemistry

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Computational discovery of potent and bioselective protoporphyrinogen IX

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oxidase inhibitor via fragment deconstruction analysis

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Ge-Fei Hao,a,† Yang Zuo,a,† Sheng-Gang Yang,a,† Qian Chen,a Yue Zhang,a Chun-Yan Yin,a Cong-Wei Niu,b

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Zhen Xi,b,c* and Guang-Fu Yang,a,c*

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a

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University, Wuhan 430079, P.R.China; bState Key Laboratory of Elemento-Organic Chemistry Nankai University Tianjin

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300071, P. R. China; cCollaborative Innovation Center of Chemical Science and Engineering, Tianjing 300072, P.R.China;

Key Laboratory of Pesticide & Chemical Biology, Ministry of Education, College of Chemistry, Central China Normal

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Correspondence:

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Guang-Fu Yang, Ph.D. & Professor

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College of Chemistry

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Central China Normal University

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152 Luoyu Road, 430079

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Wuhan, Hubei, P. R. China

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TEL: 86-27-67867800

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FAX: 86-27-67867141

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E-mail: [email protected]

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—————————

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†

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*To whom correspondence should be addressed. E-mail: [email protected]; [email protected]

Co-first authors.

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ACS Paragon Plus Environment


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ABSTRACT

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Tuning the binding selectivity through appropriate ways is a primary goal in the design and

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optimization of a lead toward discovering agrochemical. However, how to rational design of

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selectivity is still a big challenge. Herein, we developed novel computational fragment

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generation & coupling (CFGC) strategy and led to a series of highly potent and bioselective

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inhibitors targeting protoporphyrinogen IX oxidase, which play vital roles in haem and

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chlorophyll biosynthesis, which has been proved to be associated with many drugs and

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agrochemicals. However, the existing agrochemical are non-bioselective, resulting in a great

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threat to non-targeting organisms. To the best of our knowledge, this is the first time to

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discover bioselective inhibitor targeting tetrapyrrole biosynthesis pathway so far. In addition,

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the candidate showed excellent in vivo bioactivity and much better safety towards human.

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KEYWORDS: fragment; PPO; enzyme inhibitors; herbicides; bioselectivity

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Introduction

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Agrochemicals are powerful reagents with increasing impacts on drug discovery.

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However, agrochemicals of poor selectivity always generate misleading results. Hence, tuning

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of bioselectivity, which means to produce selectivity between target and nontarget organisms,

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is a primary aim on the path of agrochemical discovery. Traditionally, discovering compounds

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tightly binding to a target of interest is a primary aim in molecular design.1 Until recently,

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medicinal chemist has made considerable effort to improve selectivity for fear of adverse side

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effects, which is regarded to be more challenging in the process of design.2 Actually, obtaining

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selectivity is importantly more complex than obtaining affinity with two reasons: firstly,

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multiple factors should be taken into account in this task, secondly, considering different

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binding modes with adequate accuracy is inherently difficult.3 So far rational design of

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bioselectivity is challenging, because it is essential to assess energy differences for each ligand

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binding to a group of targets and off-targets rather than to a single objective target. Rational

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design of selectivity requires decreasing the false-negative rate, but without improving the

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false-positive one. Therefore, it is widely believed that rational design of both bioselectivity

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and potency are highly desirable.

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Protoporphyrinogen oxidase (PPO) is a key enzyme in the early step of tetrapyrrole

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biosynthesis, which plays pivotal roles in the electron-transfer related energy-generating

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processes.4 It can catalyze protogen to proto through six-electron oxidation.5 The inhibition of

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PPO will result in self-oxidation of protogen and the accumulation of proto, which can induce

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the formation of singlet oxygen for cell death.6 Due to its crucial role, interest in PPO arises

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from both its medical and agricultural significance.7-9 For example, an inherited disease called

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variegated porphyria (VP), which is characterized by cutaneous photosensitivity and the

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propensity to develop acute neurovisceral crisis, is caused by partial PPO deficiency.10 PPO

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inhibitors has been used in photodynamic therapy (PDT) for the treatment of cancer.11 Besides,

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another potent application of PPO inhibitors is to control the broadleaf weeds in agriculture.12

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However, the existing PPO-inhibiting herbicides are less bioselective especially for

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mammalian PPO,13 resulting in a series of neurological and dermatological problems and an

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increased incidence of liver cancer induced by phototoxicity.14 As a result, the development of

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potent and bioselective PPO inhibitors is in high demand.

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In the present study, we aimed to discover potent and bioselective PPO inhibitor and

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obtained a detailed understanding of the molecular mechanism of bioselective PPO inhibitor. In

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order to prove potency and bioselectivity, we performed inhibition kinetic assay, In vivo

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bioactivity assay, and photodynamic study. As a starting point for bioselective inhibitor

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discovery, we report a novel strategy and the identification of a potent and bioselective

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inhibitor of Nicotiana tabacum PPO (ntPPO) (Ki = 22 nM, 2749-fold selectivity) over human

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PPO (hPPO). Because the method relies on fragment deconstruction, the relative contributions

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to the potency and selectivity of each fragment were readily determined, which shows

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important insight into the molecular mechanism of bioselectivity. To the best of our knowledge,

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this is the first potent and bioselective PPO inhibitor described so far. This compound

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represents promising new herbicidal agent that target the essential PPO of the weeds with high

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safety toward the non-target organisms.

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Experimental Procedures

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Fragment deconstruction analysis

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The fragment deconstruction analysis was performed with a three-step computational

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protocol by using Amber 9 package shown in Figure S2: (1) A minimization procedure was

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performed on the docking conformation of protein-inhibitor complex. (2) Ligand structure

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binding in the pocket is deconstructed into fragments according to the binding with the

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sub-pocket. (3) The binding free energies (∆G) are calculated for each protein-fragment

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complexes. The ranking of fragments is sorted according to fragment efficiency (FE) defined as

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∆G divided by the non hydrogen atom count (HAC), FE = -∆Gcal/HAC.

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Virtual screening in ntPPO and hPPO

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The virtual library was prepared and minimized using SYBYL 7.0 (Tripos Inc., USA)

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with a combination of the steepest descent and conjugated gradient algorithm. A convergence

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criterion of 0.05 kcal mol-1 Å-1 was used. The crystal structures of ntPPO and hPPO were used

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for docking calculation. The addition of polar hydrogens to the crystal structure were done by

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using the Autodock Tools Package.15 Docking calculation was performed by Autodock

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(version 4.0).16 Totally, 256 runs were launched for each inhibitor. The default parameter

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values were set for the docking calculation. The compounds with a high score for ntPPO but a

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low score for hPPO were further evaluated for their synthetic feasibility.

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Binding free energy calculations

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The binding conformations were determined by docking calculations.16 Then, the complex

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structure

from

docking

study

was

further

refined

before

the

molecular

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mechanics/Poisson-Boltzmann surface area (MM/PBSA) calculation (see details in Table S1

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and Figure S3).17 In the energy minimization, the receptor was fixed at the beginning; then

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only the backbone of the receptor was fixed; finally the whole system was fully refined to a

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convergence of 0.01 kcal/(mol·Å).

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Synthetic chemistry

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Standard methods were used to treat chemical reagents before use. Solvents were dried

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and redistilled before use. A VARIAN Mercury-Plus 600 or 400 spectrometer was used to

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record 1H NMR spectra in CDCl3 or DMSO-d6 with TMS as the internal reference. A

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FINNIGAN Mass platform TRACEMS 2000 was used to obtain mass spectral data by

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electrospray ionization (ESI-MS). A Vario EL III instrument was used for elemental analysis.

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Melting points were obtained from a Buchi B-545 melting point apparatus.

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Enzyme Expression, Purification and Inhibition Kinetic Analysis

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The expression of ntPPO and hPPO enzymes were similar with the reported methods.5,18,19

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Because the product proto has a maximum excitation wavelength at 410 nm and a maximum

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emission wavelength at 630 nm, the PPO activity can be estimated by fluorescence.20 In

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inhibition kinetic assays, dimethyl sulfoxide (DMSO) was used to dissolve the inhibitor. The

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final concentration ranged from 0.005 µM to 250 µM. The enzymatic reaction rate was tested

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in 100 mM potassium phosphate (pH = 7.5), 5 mM DTT, 1 mM EDTA, Tween 80 (0.03%, v/v),

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200 mM imidazole, 5 µM FAD, and approximately 0-40 µg of protein.

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Plants materials and growth conditions

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In herbicidal activity assay, Arabidopsis thaliana ecotype Columbia-0 (Col-0) were grown

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on half-strength MS (Murashige and Skoog) solid media, which contains 1% sucrose. A

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chamber was set at 22 °C with a photosynthetically active radiation of 75 µmol/m2/s1 and a

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day/night cycle of 16-h light/8-h dark.

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In vivo bioactivities

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The herbicidal bioactivities against monocotyledon weeds, such as D. sanguinalis, E.

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crus-galli, and S. faberii, and dicotyledon weeds, such as A. theophrasti, A. retroflexus, and

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E. prostrate, were evaluated according to the previous method.20 With DMSO as solvent and

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Tween-80 as emulsification reagent, all test compounds were formulated as 100 g/L emulsified

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concentrates. Water was used to dilute the formulae to the required concentration, which was

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applied to pot-grown plants in a green-house. A clay soil was used with pH 6.5%, 1.6% organic

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matter, 37.3% clay particles, and CEC 12.1 mol/kg. Herbicidal activity was estimated visually

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at 15 days post treatment.

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Cell Culture

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Human Embryonic Kidney (HEK293 cells) were cultivated in culture medium DMEM

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(Gibco) with 10% (V/V) fetal bovine serum, 1% (V/V) penicillin and streptomycin. We grew

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cells as monolayers on 96-well plates, at 37℃ and 5% CO2 overnight.

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Photodynamic Study

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96-well plate was used to seed cell at a density of approximately 5 × 104 cells per well.

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After incubation for 48 h, we washed the cells with PBS. 0.1 mL of solutions with the

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appropriate drug were added to the wells for an incubation of 4 h. The plates were then

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irradiated by an LED lamp, which can emit a field of red light (peak output centered on 630

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nm) over an area of 11 cm × 5 cm at a fluence of 0.073 J/cm2 for 22 min. After the irradiation,

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the cells were incubated in a replaced medium for a further 24 h. The MTT assay was used for

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cytotoxicity determination. The medium containing 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl

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tetra-zolium bromide (MTT) (1 mg/mL dissolved in full RPMI-1640 medium) was used to

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incubate the cell for 3 h. The formazan derivatives was dissolved in DMSO (0.1 mL) after

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remove of the medium. UV absorption was quantified at 570 nm by a 96-well plate reader (MR

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700 Dynatech, Dynex, Worthing, UK). The mean survival rate was calculated at every

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concentration for testing prodrugs. Dark toxicity was determined by testing the survival rate

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after incubation with drugs but without exposure to irradiation.

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Results

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Structural Basis for Bioselectivity

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The active site of PPO may be considered as having two sub-sites geared for different

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types of interactions. The two sites are: the hydrophobic region for substrate binding (referred

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as Site I), and the hydrophilic region for substrate binding (referred to as Site II).21,22 A

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schematic representation of the active site is shown in Figure 1A and 1B. The site I was

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formed by a number of non-polar amino acids, such as Met368 and Gly169 in hPPO and

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Met368 and Gly175 in ntPPO. The volume of site I in ntPPO (122 Å3) is similar with hPPO

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(155 Å3) (shown in Figure S1). The site II was formed by a number of non-polar and polar

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amino acids, such as Phe331 and Arg97 in hPPO and Phe353 and Arg98 in ntPPO, which are

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two highly conserved residues in site II over all eukaryotic PPOs.

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Analysis revealed that the rim dimensions of the active site are different in two PPOs.

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Figure 1A and 1B shows four regions, which represents boundaries of the rim. Region A

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corresponds to Leu356 and Gly175 in ntPPO and Leu334 and Gly169 in hPPO; region B

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corresponds to FAD and Phe392 in ntPPO and FAD and Met368 in hPPO; region C

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corresponds to Leu372 and Phe353 in ntPPO and Val347 and Phe331 in hPPO; region D

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corresponds to Arg98 in ntPPO and Arg97 in hPPO. There is small difference between ntPPO

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and hPPO in A and B region. However, the conformational difference of phenylalanine at the C

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region results in a significant diversity. The conformation of Phe331 is “down” in hPPO, which

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is totally different from the “up” conformation of Phe353 in ntPPO. Therefore, the volume of

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site II in ntPPO (425 Å3) is larger than in hPPO (288 Å3, shown in Figure S1). The structural

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variation can also be shown by measuring the A-C distance in the crystal structure, which is 8.7

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Å in hPPO and 12.4 Å in ntPPO. Hence, if we can design compounds targeting the structural

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diversity in C region, for example a fragment more fit to ntPPO but clash with hPPO, this steric

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effect will give more opportunity for achieving selectivity.

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Fragment Deconstruction Analysis

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Herbicides of the N-phenylnitrogen heterocycle-type and pyrimidinedione-type inhibitors

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have become very aggressive in recent years. The substitution patterns of the phenyl moiety of

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the pioneering compound chlorphthalim have been extensively studied, which leads to

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flumioxazin with benzoxazinone as its core substructure.23 The structurally novel

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pyrimidinedione herbicide saflufenacil is developed recently by BASF with good biological

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performance.24 Understanding the binding mechanism of these highly potent inhibitors can help

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us to uncover the binding “hot spots” and identify regions contributing to bioselectivity. Hence,

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computational study of the binding structures of ntPPO and hPPO with flumioxazin and

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saflufenacil were performed. They were recognized as having common structural moieties

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which is 2,4,5-trisubstituted phenyl group and suitable nitrogen heterocycle connected by a

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C–N bond. As shown in Figure 1C and 1D, flumioxazin and saflufenacil have very similar

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binding modes and conformations. The phthalimide and pyrimidinedione rings are sandwiched

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by Phe392 and Gly175 in ntPPO and by Met368 and Gly169 in hPPO. Meanwhile, the

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N-phenyl rings are sandwiched by Val347 and Leu334 in hPPO and by Leu372 and Leu356 in

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ntPPO. In addition, hydrogen-bond interactions are formed with Arg98 in ntPPO and Arg97 in

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hPPO. Except for these common interaction patterns, the N-benzyl moiety is involved in an

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additional T-π stacking with hydrophobic residues of Phe331 in hPPO, whereas this interaction

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disappeared in ntPPO because of the different conformation of Phe353.

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These two potent PPO inhibitors contain a pre-organized scaffold, which directs two

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vectors towards the proximal site I and site II as recognition “hot spots”. They share similar

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binding modes addressing site I and site II, but different fragments were employed with the

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rigid link, which prompts us to investigate the fitness of fragment in each sub-pocket by an

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inverse fragment deconstruction analysis based on fragment efficiency (FE) defined as the

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binding free energy (∆G) divided by the non-hydrogen atom count (HAC), FE = -∆Gcal/HAC.

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Analysis based on ∆FE (FE(ntPPO)-FE(hPPO)) rather than potency alone could be useful in the

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selection of fragments potential for selectivity. The results from site I-directed deconstruction

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(Figure 2: boxes 1 and 2) is that phthalimide 1d displays a ∆G value of -14.61 kcal/mol for

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ntPPO and -12.87 kcal/mol for hPPO, this small site I fragment with 11 heavy atoms shows a

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∆FE of 0.16. However, deconstructing the reference saflufenacil (Figure 2, boxes 1 and 2)

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results in the site I fragment pyrimidinedione 2d with a ∆G value of -17.16 kcal/mol for ntPPO,

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-8.81 kcal/mol for hPPO, and an improved ∆FE of 0.64, which qualifies it for selectivity

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improvement in site I pocket (Figure 2, box 2).

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Besides, another result from site II-directed deconstruction of saflufenacil (Figure 2: box

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2) is that all fragments (2a–c) display no significant difference between ntPPO and hPPO (with

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-32.23 < ∆G < -8.74 kcal/mol to ntPPO and -29.52 < ∆G < -7.09 kcal/mol to hPPO), hence the

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∆FE is only between 0.14 and 0.18. No favorable effect for selectivity of this fragment is

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observed despite the presence of both H bond acceptors and donors in the sulfonamide.

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Interestingly, deconstructing the reference inhibitor flumioxazin (Figure 2, box 1) results in the

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site I benzoxazinone 1b with a ∆G value of -24.24 kcal/mol for ntPPO, -19.89 kcal/mol for

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hPPO, and a ∆FE of 0.36. This fragment is less active but has a higher ∆FE and a smaller size

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than 2a derived from saflufenacil. This improvement in ∆FE of benzoxazinone could partially

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be attributed to favourable hydrophobic interactions with ntPPO surface, whereas steric clash

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with hPPO surface.

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The fragment deconstruction analysis provides insights into the contributions of each

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fragment on potency and bioselectivity, which led us to examine the recombination of

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fragments based on energy deconstruction and fragment efficiency (FE) as a way to enhance

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PPO-inhibiting activity and bioselectivity simultaneously. Figure 2 summarizes our strategy of

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deconstruction and recombination to arrive at a new scaffold benzoxazinone-substituted

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pyrimidinedione. These designed compounds were successfully synthesized and structurally

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characterized (shown in Scheme S1). The optimal substituent of benzoxazinone moiety is the

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fluorine at the 7-position.25 In addition, the structural combination of the C-2 and N-4 of the

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oxazine ring has attracted the intense attention of many researchers.23

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Identification of Bioselectivity Inhibitors

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To improve PPO-inhibiting potency, we envisioned that hydrogen-bond donors at the N-4

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position of the benzoxazinone ring would interact with a nearby arginine. Stronger hydrogen

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bonds can be used as a proper way to improve the potency of PPO inhibitors. Hence, a virtual

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screening was conducted to identify optimum substituents. The virtual library was enumerated

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by decorating the core scaffold with different carboxylic ester groups at position R1, and was

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screened with both enzymes to obtain highly potent and bioselective PPO inhibitors (for details,

248

see the Supporting Information). The docking scores of each inhibitor for ntPPO and hPPO

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were compared. Inhibitor with high score for ntPPO, but low score for hPPO would be an idea

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candidate for subsequent synthesis (Table 1). The Ki values against ntPPO and hPPO of the

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compounds were evaluated using fluorometric assays as described previously.26 As shown in

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Table 1, most of compounds 3-9 displayed similar ntPPO and hPPO-inhibiting activity

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compared with reference compounds. They displayed low selectivity for ntPPO except for

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compound

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benzoxazinone-substituted pyrimidinedione may be a new scaffold to achieve bioselectivity.

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For commercial PPO-inhibiting herbicide sulfentrazone (SUT), flumioxazin (FLX), and

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saflufenacil (SAF), we determined its Ki values of 0.03, 0.0072, and 0.014 µM for ntPPO and

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0.98, 0.0399, and 1.1945 µM for hPPO (32.67, 5.54, and 85.32-folds bioselectivity).

3,

which

shows

a

810-fold

selectivity.

This

demonstrated

that

259

To further improve bioselectivity of these inhibitors, we focused on structure-guided

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modification at R2 position. Since the volume difference of site II between ntPPO and hPPO is

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a unique feature, the introduction of larger moiety at position R2 (Figure 2) were expected to

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fit well with ntPPO but clash with hPPO surface, which may further improve the bioselectivity

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for ntPPO over hPPO. So, compounds 10-16 were further synthesized and found to display

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much higher selectivity for ntPPO (Table 1). As expected on the basis of docking results, a

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simple modification at R2 led to a general increase in selectivity for ntPPO. The expected clash

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with hPPO surface resulted in a dozens-fold decrease in hPPO inhibition, but did not lead to a

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loss of activity towards ntPPO. Compared with SUT, FLX, and SAF, most of the target

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compounds display much higher selectivity. The most promising compound is 10 with Ki =

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0.022 µM for ntPPO and Ki = 60.49 µM for hPPO. This result indicates that compound 10

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shows ~2749 times bioselectivity. As shown in Scheme S1, the target compounds 3-16 were

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smoothly prepared by a multiple step synthetic route using 2,4-disubstituted anilines as starting

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materials. The structures of all intermediates and title compounds were confirmed by elemental

273

analyses, 1H NMR and ESI-MS spectral data (shown in the Supporting Information).

274 275

Molecular Basis of Bioselective Inhibitors

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To investigate the molecular mechanism of bioselectivity at the atomic level, the docking

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derived binding modes were further optimized and the molecular mechanic/Poisson-Boltzmann

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surface area (MM/PBSA) calculations were carried out. As shown in Table S1, the binding

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free energies (∆Gbind) calculated for all ligands binding with the ntPPO range from -45.07 to

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-42.91 kcal/mol. Compound 6 and 12 have the lowest ∆Gbind value, and 16 has the highest

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∆Gbind value. However, the calculated ∆Gbind values for hPPO range from -41.19 to -34.76

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kcal/mol, with the lowest ∆Gbind value corresponding to 5 and the highest ∆Gbind value

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corresponding to 14. Further, we also estimated the corresponding experimental binding free

284

energies of 3-16 based on ∆Gbind(expt.) = -RTlnKi. Obviously, the absolute binding affinities

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285

were most likely overestimated by the MM/PBSA calculations (Table S1). However, the

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relative binding free energy shifts (∆∆Gbind) from ntPPO to hPPO can be used to quantitatively

287

correlate with the selectivity levels for the inhibitors. There is a good linear correlation (r2 =

288

0.97) between the ∆∆Gbind (calc.) values from calculation and the ∆∆Gbind (expt.) values derived

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from the experimental data (Figure S1), suggesting that the optimized binding modes were

290

reasonable.

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The ntPPO:10 complex structure suggests that 10 binds in a mode similar to saflufenacil,

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with the pyrimidinedione ring π-stacks with Phe392 in ntPPO and sandwiches by Met368 and

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Gly169 in hPPO (Figure 3). The benzoxazinone ring occupies site II of hPPO, results in an

294

extra T-stacking with Phe331, which is similar to the binding modes of flumioxazin and

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saflufenacil in hPPO. However, this T-stacking interaction results in a limit for the adjustment

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of the benzoxazinone ring, hence the R2-methyl substituent could lead to a clash with the hPPO

297

surface. The situation is different in site II of ntPPO, in order to avoid the clash of the

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R2-methyl substituent with the ntPPO surface, the benzoxazinone ring is slightly twisted.

299

Surprisingly, the carbonyl group of ethyl acetate substituent at position R1 has a stronger

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hydrogen bond interaction with Arg98 in ntPPO than Arg97 in hPPO, which might be caused

301

by the different binding pattern of the benzoxazinone ring in site II. Hence, significant gain in

302

selectivity of compound 10 can be observed.

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In Vivo Herbicidal Activity

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Based on the above results, compound 10 shows excellent potency and high bioselectivity

306

towards ntPPO. Then, the controlling efficacy of compound 10 against weeds was further

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tested in greenhouse. Consistent with the enzyme inhibition result, compound 10 can decrease

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the survival of Arabidopsis thaliana, as expected based on the activity of sulfentrazone (Figure

309

4). The treatment with compound 10 induces primary symptom with commercial PPO

310

herbicide such as bleaching the plant foliage. These results clearly show that compound 10

311

could be used as an effective PPO-inhibiting herbicide during the vegetative growth stage.

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To determine whether compound 10 has in vivo bioactivity in a wide spectrum, the

313

post-emergence herbicidal activities of compound 10 against monocotyledon weeds, such as D.

314

sanguinalis, E. crus-galli, and S. faberii, and dicotyledon weeds, such as A. theophrasti, A.

315

retroflexus, and E. prostrate, were tested in the green house at the concentrations of 37.5, 75,

316

and 150 g.ai/ha. Due to the worldwide application, sulfentrazone was selected as a reference.

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As shown in Table 2, both compound 10 and sulfentrazone were found to display promising

318

herbicidal activities on dicotyledon weeds at 75 and 150 g.ai/ha. Even at the concentration of

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37.5 g ai/ha, compound 10 still exhibited total control against A. theophrasti, A. retroflexus,

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and E. prostrate, showing much higher activity than sulfentrazone. These results indicated that

321

the herbicidal activity of compound 10 is promising.

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Phototoxicity

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The human disease variegate porphyria (VP), associated with a partial deficiency of PPO

325

activity, can induce a skin phototoxic response, which resembles an exaggerated sunburn.27 In

326

addition, it may result in an group of dermatological and neurological problems28 and an

327

improved incidence of liver cancer.29 Non-selective PPO inhibitors can induce the high level of

328

porphyrin in feces and blood, in addition, the carboxylated porphyrins in liver of rats and mice,

15



Page 16 of 33

329

which is the same as occurs in variegate porphyria in humans.30,31 The green PPO-inhibiting

330

herbicide should avoid the phototoxic effect for human. Hence, the phototoxic effect was tested

331

for compound 10 by using Human Embryonic Kidney 293 cells (HEK293).

332

In mammalian cells, 5-aminolaevulinic acid (5-ALA) is metabolized to protoporphyrin IX

333

(PpIX), which is a potent photosensitizer. Hence, 5-ALA can induce excellent phototoxic

334

effect.32 The phototoxicities of PPO inhibitor that can also give rise to the most important

335

enhancements of PpIX accumulation were evaluated in HEK293 cells. As shown in Figure 5,

336

the cells were irradiated with blue light (0.073 J/cm2) after 4h of incubation with four doses of

337

the selected compound 10, as well as 5-ALA for comparison. In agreement with the data from

338

binding potency experiments, compound 10 that exhibited a low potency for hPPO also

339

exhibited lower phototoxicity. At 0.01 mM, there are almost no phototoxicity for both

340

compound 10 and 5-ALA. However, after exposure to 5-ALA at 0.1 mM, the cell survival rate

341

was 68%, while compound 10 was as similar as at 0.01 mM, retaining the cell viability around

342

90%. Furthermore, when the cells were exposed to 0.5 and 1 mM of 5-ALA, the cell viability

343

was decreased to under 20%, but compounds 10 still retained low phototoxicity. It is important

344

that the compound 10 displayed very low phototoxicity under the conditions adopted in all

345

these experiments.

346 347

Discussion

348

Improving drug selectivity for its target has far proved to be tremendous challenge of drug

349

discovery in the post-genomic era because a multitude of functional proteins have been

350

characterized and the active pockets of a target protein family are often quite similar.

16


Page 17 of 33


351

Compared with drug selectivity, however, it is more challenging to rationally improve

352

agrochemical selectivity, because of the highly conserved enzyme in different species. In many

353

cases, this aim is attained through trial and error, rational approaches for the tuning of

354

selectivity are still limited. Hence, it is in high priority to develop novel and creative strategies

355

to guide the tuning of ligand selectivity.33

356

Fragment-based de novo design has emerged as an effective approach for the

357

identification of lead compounds with novel scaffold in drug discovery. Available

358

fragment-based approaches, however, are only able to discover and characterize fragment on

359

the target protein. An important challenge for fragment-based de novo design is how to design

360

compounds to modulate a specific target while leaving related proteins unaffected. Because

361

most fragments have limited interactions with the target, the identification of specific

362

fragments is still quite intractable problems in most cases.

363

Upon this challenge, computational fragment generation & coupling (CFGC) was

364

developed and proved to be an effective strategy to guide the tuning of selectivity. We have

365

presented a comparative investigation on the binding pockets of hPPO and ntPPO, and defined

366

two sub-pockets in the view of ligand-protein interaction. The further application of CFGC

367

allowed us to estimate the FE of various fragment and arrived at a new bioselective scaffold of

368

benzoxazinone-substituted pyrimidinedione. By integrating CFGC, organic synthesis, and

369

computational simulations together, we have rationally designed and synthesized a series of

370

highly potent and bioselective ntPPO inhibitors. The computational simulations revealed that

371

the C-2-methyl substituted pyrimidinedione moiety fitted well with site II of ntPPO but clashed

17



Page 18 of 33

372

with hPPO, which accounted for the molecular mechanism of bioselectivity. These results

373

demonstrated that the CFGC is a useful strategy for bioselective lead discovery.

374

It should be noted that the CFGC strategy also have limitations. Clearly, this strategy is

375

based on the assumption that the binding mode of each fragment in the original molecule is

376

similar to that in the new scaffold. If the new scaffold changes to a new binding mode, it will

377

lead to significantly underestimate of the binding free-energy, which can result in a

378

false-positive or false-negative prediction. Therefore, further improvement should be done to

379

make this stragety suitable for broader application.

380

To our knowledge, compound 10 discovered by structure-based design displayed good

381

binding potency (Ki = 22 nM) for ntPPO and the highest bioselectivity up to now (2749-folds

382

over hPPO). In addition, compound 10 showed excellent herbicidal activity even at the low

383

concentration of 37.5 g.ai/ha, showing its potential as a much safer lead for further herbicide

384

development. The above results may open up new opportunities for the study of PPO and its

385

involvement in the establishment of much safer agrochemical for human.

386 387

Abbreviations used

388

PPO, Protoporphyrinogen oxidase; CFGC, Computational fragment generation & coupling;

389

PDT,

390

mechanics/Poisson-Boltzmann surface area; FE, fragment efficiency; HAC, heavy atom count;

391

SUT, sulfentrazone; FLX, flumioxazin; SAF, saflufenacil; 5-ALA, 5-aminolaevulinic acid

photodynamic

therapy;

VP,

variegate

porphyria;

MM/PBSA,

molecular

392 393

18


Page 19 of 33


394

Acknowledgments

395

We thank Prof. Jie Chen at ZheJiang Research Institute of Chemical Industry for help with

396

herbicidal activity assay. This research was supported by the National Key Technologies R&D

397

Program (2014BAD20B01) and the National Natural Science Foundation of China (No.

398

21332004 and 21402059).

399 400

Supporting Information Available: The Supporting Information is available free of charge

401

online at http://pubs.acs.org.

402 403 404 405 406 407

References: (1) Gleeson, M. P.; Hersey, A.; Montanari, D.; Overington, J. Probing the links between in vitro potency, ADMET and physicochemical parameters, Nat. Rev. Drug Discov. 2011, 10, 197-208. (2) Huggins, D. J.; Sherman, W.; Tidor, B. Rational Approaches to Improving Selectivity in Drug Design, J. Med. Chem. 2012, 55, 1424-1444.

408

(3) Yang, C.; Pflugrath, J. W.; Camper, D. L.; Foster, M. L.; Pernich, D. J.; Walsh, T. A. Structural basis

409

for herbicidal inhibitor selectivity revealed by comparison of crystal structures of plant and mammalian

410

4-hydroxyphenylpyruvate dioxygenases, Biochemistry 2004, 43, 10414-10423.

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(4) Mobius, K.; Arias-Cartin, R.; Breckau, D.; Hannig, A. L.; Riedmann, K.; Biedendieck, R.; Schroder, S.;

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Becher, D.; Magalon, A.; Moser, J.; Jahn, M.; Jahn, D. Heme biosynthesis is coupled to electron transport chains

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for energy generation, Proc. Natl. Acad. Sci. U. S. A. 2010, 107, 10436-10441.

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(5) Heinemann, I. U.; Diekmann, N.; Masoumi, A.; Koch, M.; Messerschmidt, A.; Jahn, M.; Jahn, D.

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Functional definition of the tobacco protoporphyrinogen IX oxidase substrate-binding site, Biochem. J. 2007, 402,

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575-580.

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(6) Arnould, S.; Camadro, J. M. The domain structure of protoporphyrinogen oxidase, the molecular target of diphenyl ether-type herbicides, Proc. Natl. Acad. Sci. U. S. A. 1998, 95, 10553-10558.

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(7) Qin, X.; Sun, L.; Wen, X.; Yang, X.; Tan, Y.; Jin, H.; Cao, Q.; Zhou, W.; Xi, Z.; Shen, Y. Structural

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insight into unique properties of protoporphyrinogen oxidase from Bacillus subtilis, J. Struct. Biol. 2010, 170,

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76-82.

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(8) Wang, B. F.; Wen, X.; Qin, X. H.; Wang, Z. F.; Tan, Y.; Shen, Y. Q.; Xi, Z. Quantitative Structural Insight into Human Variegate Porphyria Disease, J. Biol. Chem. 2013, 288, 11731-11740. (9) Patzoldt, W. L.; Hager, A. G.; McCormick, J. S.; Tranel, P. J. A codon deletion confers resistance to herbicides inhibiting protoporphyrinogen oxidase, Proc. Natl. Acad. Sci. U. S. A. 2006, 103, 12329-12334. (10) Brenner, D. A.; Bloomer, J. R. The enzymatic defect in variegate prophyria. Studies with human cultured skin fibroblasts, N. Engl. J. Med. 1980, 302, 765-769. (11) Fingar, V. H.; Wieman, T. J.; McMahon, K. S.; Haydon, P. S.; Halling, B. P.; Yuhas, D. A.; Winkelman, J. W. Photodynamic therapy using a protoporphyrinogen oxidase inhibitor, Cancer Res. 1997, 57, 4551-4556. (12) Hao, G. F.; Zuo, Y.; Yang, S. G.; Yang, G. F. Protoporphyrinogen Oxidase Inhibitor: An Ideal Target for Herbicide Discovery, Chimia 2011, 65, 961-969.

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(13) Hao, G.-F.; Tan, Y.; Xu, W.-F.; Cao, R.-J.; Xi, Z.; Yang, G.-F. Understanding Resistance Mechanism of

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Protoporphyrinogen Oxidase-Inhibiting Herbicides: Insights from Computational Mutation Scanning and

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Site-Directed Mutagenesis, J. Agric. Food Chem. 2014, 62, 7209-7215.

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(14) Eales, L.; Day, R. S.; Blekkenhorst, G. H. The clinical and biochemical features of variegate porphyria: an analysis of 300 cases studied at Groote Schuur Hospital, Cape Town, Int. J. Biochem. 1980, 12, 837-853. (15) Sanner, M. F. A component-based software environment for visualizing large macromolecular assemblies, Structure 2005, 13, 447-462. (16) Huey, R.; Morris, G. M.; Olson, A. J.; Goodsell, D. S. A semiempirical free energy force field with charge-based desolvation, J. Comput. Chem. 2007, 28, 1145-1152.

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(17) Kollman, P. A.; Massova, I.; Reyes, C.; Kuhn, B.; Huo, S.; Chong, L.; Lee, M.; Lee, T.; Duan, Y.;

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Wang, W.; Donini, O.; Cieplak, P.; Srinivasan, J.; Case, D. A.; Cheatham, T. E. Calculating structures and free

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energies of complex molecules: combining molecular mechanics and continuum models, Acc. Chem. Res. 2000,

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33, 889-897.

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(18) Corrigall, A. V.; Siziba, K. B.; Maneli, M. H.; Shephard, E. G.; Ziman, M.; Dailey, T. A.; Dailey, H. A.;

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Kirsch, R. E.; Meissner, P. N. Purification of and kinetic studies on a cloned protoporphyrinogen oxidase from the

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aerobic bacterium Bacillus subtilis, Arch. Biochem. Biophys. 1998, 358, 251-256.

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(19) Qin, X.; Tan, Y.; Wang, L.; Wang, Z.; Wang, B.; Wen, X.; Yang, G.; Xi, Z.; Shen, Y. Structural insight into human variegate porphyria disease, FASEB J. 2010, 25, 653-664. (20) Jiang, L. L.; Zuo, Y.; Wang, Z. F.; Tan, Y.; Wu, Q. Y.; Xi, Z.; Yang, G. F. Design and syntheses of

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novel

N-(benzothiazol-5-yl)-4,5,6,7-tetrahydro-1H-isoindole-1,3(2H)-dione

and

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N-(benzothiazol-5-yl)isoindoline-1,3-dione as potent protoporphyrinogen oxidase inhibitors, J. Agric. Food Chem.

453

2011, 59, 6172-6179.

454

(21) Koch, M.; Breithaupt, C.; Kiefersauer, R.; Freigang, J.; Huber, R.; Messerschmidt, A. Crystal structure

455

of protoporphyrinogen IX oxidase: a key enzyme in haem and chlorophyll biosynthesis, EMBO J. 2004, 23,

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1720-1728.

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(22) Qin, X.; Tan, Y.; Wang, L.; Wang, Z.; Wang, B.; Wen, X.; Yang, G.; Xi, Z.; Shen, Y. Structural insight into human variegate porphyria disease, FASEB J. 2011, 25, 653-664.

459

(23) Huang, M. Z.; Luo, F. X.; Mo, H. B.; Ren, Y. G.; Wang, X. G.; Ou, X. M.; Lei, M. X.; Liu, A. P.;

460

Huang, L.; Xu, M. C. Synthesis and Herbicidal Activity of Isoindoline-1,3-dione Substituted Benzoxazinone

461

Derivatives Containing a Carboxylic Ester Group, J. Agric. Food Chem. 2009, 57, 9585-9592.

462 463

(24) Sikkema, P. H.; Shropshire, C.; Soltani, N. Tolerance of spring barley (Hordeum vulgare L.), oats (Avena sativa L.) and wheat (Triticum aestivum L.) to saflufenacil, Crop Prot. 2008, 27, 1495-1497.

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(25) Macias, F. A.; De Siqueira, J. M.; Chinchilla, N.; Marin, D.; Varela, R. M.; Molinillo, J. M. G. New

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Herbicide Models from Benzoxazinones: Aromatic Ring Functionalization Effects, J. Agric. Food Chem. 2006, 54,

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9843-9851.

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(26) Tan, Y.; Sun, L.; Xi, Z.; Yang, G. F.; Jiang, D. Q.; Yan, X. P.; Yang, X.; Li, H. Y. A capillary

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electrophoresis assay for recombinant Bacillus subtilis protoporphyrinogen oxidase, Anal. Biochem. 2008, 383,

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200-204.

470

(27) Deybach, J.-C.; Puy, H.; Robreau, A.-M.; Lamoril, J.; Da Silva, V.; Grandchamp, B.; Nordmann, Y.

471

Mutations in the Protoporphyrinogen Oxidase Gene in Patients with Variegate Porphyria, Hum. Mol. Genet. 1996,

472

5, 407-410.

473 474 475 476 477 478

(28) Eales, L.; Day, R. S.; Blekkenhorst, G. H. The clinical and biochemical features of variegate porphyria: an analysis of 300 cases studied at Groote Schuur Hospital, Cape Town, Int. J. Biochem. 1980, 12, 837-853. (29) Kauppinen, R.; Mustajoki, P. Acute hepatic porphyria and hepatocellular carcinoma, Br. J. Cancer 1988, 57, 117-120. (30) Krijt, J.; Pleskot, R.; Sanitrak, J.; Janousek, V. Experimental hepatic porphyria induced by oxadiazon in male mice and rats, Pestic. Biochem. Physiol. 1992, 42, 180-187.

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479

(31) Krijt, J.; Vokurka, M.; Sanitrak, J.; Janousek, V.; van Holsteijn, I.; Blaauboer, B. J. Effect of the

480

protoporphyrinogen oxidase-inhibiting herbicide fomesafen on liver uroporphyrin and heptacarboxylic porphyrin

481

in two mouse strains, Food Chem. Toxicol. 1994, 32, 641-650.

482

(32) Carre, J.; Eleouet, S.; Rousset, N.; Vonarx, V.; Heyman, D.; Lajat, Y.; Patrice, T. Protoporphyrin IX

483

fluorescence kinetics in C6 glioblastoma cells after delta-aminolevulinic acid incubation: effect of a

484

protoporphyrinogen oxidase inhibitor, Cell. Mol. Biol. (Noisy-le-Grand) 1999, 45, 433-444.

485 486

(33) Huggins, D. J.; Sherman, W.; Tidor, B. Rational approaches to improving selectivity in drug design, J. Med. Chem. 2012, 55, 1424-1444.

487 488 489 490 491 492 493 494 495 496 497 498 499 500

23



Page 24 of 33

501

Figure Legends

502

Figure 1. A Sectional view of the hydrophobic site I and the site II of hPPO. B Sectional view of the

503

hydrophobic site I and the site II of ntPPO. Distances between boundaries of A and C region are shown with

504

black arrows. Letters A-D denote four boundary areas surrounding the pocket rim. C Side view of the

505

simulated binding modes of flumioxazin and saflufenacil in hPPO. The phthalimide and pyrimidinedione

506

moieties are sandwiched by Met368 and Gly169, whereas N-phenyl and benzoxazinone moieties stack with

507

Val347 and Leu334. The orientation of Phe331 is in “down” state, which results in a smaller site II pocket.

508

To avoid clashes with the surface of site II pocket, the smaller N-phenyl moiety can easily adjust its position,

509

which is hard for the larger benzoxazinone moiety to adapt to the substituent change. D Side view of the

510

simulated binding modes of flumioxazin and saflufenacil in ntPPO. The phthalimide and pyrimidinedione

511

moieties interact with Phe392 and Gly175 by stacking, whereas N-phenyl and benzoxazinone moieties are

512

sandwiched by Leu372 and Leu356. The orientation of Phe353 is in “up” state, which results in a larger site

513

II pocket. Both the N-phenyl and benzoxazinone moieties can easily adjust its position to adapt to the

514

substituent change.

515 516

Figure 2. Fragment deconstruction process (∆G values are given in kcal/mol, FE defined as ∆G divided by

517

the heavy atom count (HAC), FE = -∆Gcal/HAC, ∆FE = FE(ntPPO)-FE(hPPO)).

518 519

Figure 3. A Computational binding modes of 10:ntPPO. The benz-oxazinone moiety is located in site II of

520

ntPPO and sandwiched by Leu372 and Leu356. The blue dashed line indicates the surface of the sub-pocket

521

and the black dashed arrows indicate interactions between the ligand and the enzyme. Due to the “up”

522

conformation of Phe353, a larger space results in a steric fit for C-2-methyl substituent benzoxazinone. The

24


Page 25 of 33


523

carbonyl oxygen of carboxylic ester group can form two stronger hydrogen bonds with Arg98. B

524

Computational binding modes of 10:hPPO. Due to the “down” conformation of Phe331, an extra T-stacking

525

interaction is observed between the benzoxazinone moiety and Phe331. In this smaller site II, the C-2-methyl

526

substituent benzoxazinone cannot adjust its position and clashes with the surface, which leads to the lost of

527

the expected hydrogen-bond interactions between the carbonyl oxygen of carboxylic ester group and Arg97,

528

but with the hydrogen bonding interaction to the carbonyl oxygen of benzoxazinone instead.

529 530

Figure 4. Compound 10 treatment reduced survival of rate of 3-week-old Arabidopsis thaliana in herbicidal

531

activity assay. (A) The working concentration was 25 µM for compound 10 and sulfentrazone (SUT). 0.1%

532

DMSO is used as control. The survival rate is determined as % of initial fresh weight. Error bars represent

533

standard error values. (B) Wild-type (Col-0) plants are grown under condition described in Materials and

534

Methods for three weeks. Then plants are sprayed with compound 10 or sulfentrazone (SUT) solutions.

535

Photographs were imaged before chemical treatment (top panel) and six-days after treatment (bottom panel).

536

And survival rates were calculated six-days after treatment. Values are the mean survival rates from three

537

independent assays (12 seedlings per assay). Error bars indicate SD.

538 539

Figure 5. Phototoxicity after incubation with 0.01 mM (white), 0.1 mM (light-gray), 0.5 mM (gray), and 1

540

mM (black) of compound 10 and 5-ALA in HEK293 cell line. Incubation time was 4 h. Irradiation was

541

performed with blue light (0.073 J/cm2). Cell viability was assessed by MTT assay (see Experimental

542

Section for details).

543 544

25



545

Page 26 of 33

Table 1 In vitro activity of inhibitors 3-16 to hPPO and ntPPO. hPPO ntPPO No.

R1

R2

SF[a] Ki[µM] Ki[µM]

SUT[b]

—

—

0.98

0.03

32.67

FLX

—

—

0.0399

0.0072

5.54

SAF

—

—

1.1945

0.014

85.32

3

CH2COOC2H5

H

11.34

0.014

810.07

4

CH2CH2COOC2H5

H

1.19

0.048

24.75

5

CH2COOCH2CH2CH3

H

0.28

0.035

7.94

6

CH2COOCH(CH3)2

H

1.69

0.020

84.50

7

CH2COOCH3

H

7.56

0.095

79.58

8

CH(CH3)COOC2H5

H

0.51

0.056

9.11

9

CH(CH3)COOCH3

H

5.10

0.100

51.00

10

CH2COOC2H5

CH3

60.49

0.022

2749.00

11

CH2CH2COOC2H5

CH3

18.31

0.025

732.00

CH2COOCH2CH2CH3 CH3

4.15

0.012

345.50

44.41

0.038

1169.00

CH3 159.97

0.091

1758.00

12 13

CH2COOCH(CH3)2

CH3

14

CH2COOCH3

15

CH(CH3)COOC2H5

CH3

31.53

0.048

657.00

16

CH(CH3)COOCH3

CH3

75.65

0.107

707.00

546

[a] The Selectivity Factor(SF) = Ki (hPPO)/Ki (ntPPO). [b] Sulfentrazone (SUT), Flumioxazin

547

(FLX), Saflufenacil (SAF)

26


Page 27 of 33

548


Table 2 Herbicidal activities of the highest bioselective ntPPO inhibitor. Dosage ATa

DS

AR

EC

EP

SF

37.5

++++b

―

++++

―

++++

+

75

++++

―

++++

+

++++

+

150

++++

―

++++

+++

++++

+++

37.5

+++

―

+++

+++

+++

++

75

++++

+

++++ ++++ ++++

+++

150

++++

++ ++++ ++++ ++++ ++++

Compound (g.ai/ha)

10

SUT

549

[a] AT for Abutilon theophrasti, DS for Digitaria sanguinalis, AR for Amaranthus retroflexus,

550

EC for Echinochloa crus-galli, EP for Eclipta prostrate, and SF for Setaria faberii. [b] Rating

551

system for the growth inhibition percentage: ++++, ≥ 90%; +++, 80-89%; ++, 60-79%; +,

552

50-59%; ―, < 50%.

553 554 555 556 557 558 559 560 561

27



562

Page 28 of 33

Figure 1

563 564 565 566 567 568 569 570 571 572 573 574 575 576

28


Page 29 of 33

577


Figure 2

578 579 580 581 582 583 584 585 586

29



587

Page 30 of 33

Figure 3

588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 30


Page 31 of 33

605


Figure 4

606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 31



622

Page 32 of 33

Figure 5

623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 32


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TOC Graphic

639 640

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