Integrating medicinal chemistry, organic/combinatorial chemistry, and computational chemistry for the discovery of selective estrogen receptor modulators with Forecaster, a novel platform for drug discovery

Target-specific novel molecules with their recipe: Incorporating synthesizability in the design process

Application of Artificial intelligence (AI) in drug discovery has led to several success stories in recent times. While traditional methods mostly relied upon screening large chemical libraries for early-stage drug-design, de novo design can help identify novel target-specific molecules by sampling from a much larger chemical space. Although this has increased the possibility of finding diverse and novel molecules from previously unexplored chemical space, this has also posed a great challenge for medicinal chemists to synthesize at least some of the de novo designed novel molecules for experimental validation. To address this challenge, in this work, we propose a novel forward synthesis-based generative AI method, which is used to explore the synthesizable chemical space. The method uses a structure-based drug design framework, where the target protein structure and a target-specific seed fragment from co-crystal structures can be the initial inputs. A random fragment from a purchasable fragment library can also be the input if a target-specific fragment is unavailable. Then a template-based forward synthesis route prediction and molecule generation is performed in parallel using the Monte Carlo Tree Search (MCTS) method where, the subsequent fragments for molecule growth can again be obtained from a purchasable fragment library. The rewards for each iteration of MCTS are computed using a drug-target affinity (DTA) model based on the docking pose of the generated reaction intermediates at the binding site of the target protein of interest. With the help of the proposed method, it is now possible to overcome one of the major obstacles posed to the AI-based drug design approaches through the ability of the method to design novel target-specific synthesizable molecules.

SARS-CoV-2 external structures interacting with nanospheres using docking and molecular dynamics

Coronavirus is caused by the SARS-CoV-2 virus has shown rapid proliferation and scarcity of treatments with proven effectiveness. In this way, we simulated the hospitalization of carbon nanospheres, with external active sites of the SARS-CoV-2 virus (M-Pro, S-Gly and E-Pro), which can be adsorbed or inactivated when interacting with the nanospheres. The computational procedures performed in this work were developed with the SwissDock server for molecular docking and the GROMACS software for molecular dynamics, making it possible to extract relevant data on affinity energy, distance between molecules, free Gibbs energy and mean square deviation of atomic positions, surface area accessible to solvents. Molecular docking indicates that all ligands have an affinity for the receptor's active sites. The nanospheres interact favorably with all proteins, showing promising results, especially C60, which presented the best affinity energy and RMSD values ​​for all protein macromolecules investigated. The C60 with E-Pro exhibited the highest affinity energy of -9.361 kcal/mol, demonstrating stability in both molecular docking and molecular dynamics simulations. Our RMSD calculations indicated that the nanospheres remained predominantly stable, fluctuating within a range of 2 to 3 Å. Additionally, the analysis of other structures yielded promising results that hold potential for application in other proteases.Communicated by Ramaswamy H. Sarma.

Computational and biophysical methods for the discovery and optimization of covalent drugs

Drugs that act by covalently attaching to their targets have been used to treat human diseases for over a hundred years. However, the deliberate design of covalent drugs was discouraged due to concerns of toxicity and off-target effects. Recent successes in covalent drug discovery have sparked fresh interest in this field. New screening and testing methods aimed at covalent inhibitors can play pivotal roles in facilitating the discovery process. This feature article focuses on computational and biophysical advances originating from our labs over the past decade and how these approaches have contributed to the design of prolyl oligopeptidase (POP) and SARS-CoV-2 3CLpro covalent inhibitors.

Elucidation of the binding mode of organic polysulfides on the human TRPA1 receptor

Introduction: Previous studies have established that endogenous inorganic polysulfides have significant biological actions activating the Transient Receptor Potential Ankyrin 1 (TRPA1) receptor. Organic polysulfides exert similar effects, but they are much more stable molecules, therefore these compounds are more suitable as drugs. In this study, we aimed to better understand the mechanism of action of organic polysulfides by identification of their binding site on the TRPA1 receptor. Methods: Polysulfides can readily interact with the thiol side chain of the cysteine residues of the protein. To investigate their role in the TRPA1 activation, we replaced several cysteine residues by alanine via site-directed mutagenesis. We searched for TRPA1 mutant variants with decreased or lost activating effect of the polysulfides, but with other functions remaining intact (such as the effects of non-electrophilic agonists and antagonists). The binding properties of the mutant receptors were analyzed by in silico molecular docking. Functional changes were tested by in vitro methods: calcium sensitive fluorescent flow cytometry, whole-cell patch-clamp and radioactive calcium-45 liquid scintillation counting. Results: The cysteines forming the conventional binding site of electrophilic agonists, namely C621, C641 and C665 also bind the organic polysulfides, with the key role of C621. However, only their combined mutation abolished completely the organic polysulfide-induced activation of the receptor. Discussion: Since previous papers provided evidence that organic polysulfides exert analgesic and anti-inflammatory actions in different in vivo animal models, we anticipate that the development of TRPA1-targeted, organic polysulfide-based drugs will be promoted by this identification of the binding site.

Novel inhibitors and activity-based probes targeting serine proteases

Serine proteases play varied and manifold roles in important biological, physiological, and pathological processes. These include viral, bacterial, and parasitic infection, allergic sensitization, tumor invasion, and metastasis. The use of activity-based profiling has been foundational in pinpointing the precise roles of serine proteases across this myriad of processes. A broad range of serine protease-targeted activity-based probe (ABP) chemotypes have been developed and we have recently introduced biotinylated and "clickable" peptides containing P1 N-alkyl glycine arginine N-hydroxy succinimidyl (NHS) carbamates as ABPs for detection/profiling of trypsin-like serine proteases. This present study provides synthetic details for the preparation of additional examples of this ABP chemotype, which function as potent irreversible inhibitors of their respective target serine protease. We describe their use for the activity-based profiling of a broad range of serine proteases including trypsin, the trypsin-like protease plasmin, chymotrypsin, cathepsin G, and neutrophil elastase (NE), including the profiling of the latter protease in clinical samples obtained from patients with cystic fibrosis.

Novel Aurora A and Protein Kinase C (α, β1, β2, and θ) Multitarget Inhibitors: Impact of Selenium Atoms on the Potency and Selectivity

Aurora kinases and protein kinase C (PKC) have been shown to be involved in different aspects of cancer progression. To date, no dual Aurora/PKC inhibitor with clinical efficacy and low toxicity is available. Here, we report the identification of compound 2e as a potent small molecule capable of selectively inhibiting Aurora A kinase and PKC isoforms α, β1, β2 and θ. Compound 2e demonstrated significant inhibition of the colony forming ability of metastatic breast cancer cells in vitro and metastasis development in vivo. In vitro kinase screening and molecular modeling studies revealed the critical role of the selenium-containing side chains within 2e, where selenium atoms were shown to significantly improve its selectivity and potency by forming additional interactions and modulating the protein dynamics. In comparison to other H-bonding heteroatoms such as sulfur, our studies suggested that these selenium atoms also confer more favorable PK properties.

Prerequisite Binding Modes Determine the Dynamics of Action of Covalent Agonists of Ion Channel TRPA1

Transient receptor potential ankyrin 1 (TRPA1) is a transmembrane protein channeling the influx of calcium ions. As a polymodal nocisensor, TRPA1 can be activated by thermal, mechanical stimuli and a wide range of chemically damaging molecules including small volatile environmental toxicants and endogenous algogenic lipids. After activation by such compounds, the ion channel opens up, its central pore widens allowing calcium influx into the cytosol inducing signal transduction pathways. Afterwards, the calcium influx desensitizes irritant evoked responses and results in an inactive state of the ion channel. Recent experimental determination of structures of apo and holo forms of TRPA1 opened the way towards the design of new agonists, which can activate the ion channel. The present study is aimed at the elucidation of binding dynamics of agonists using experimental structures of TRPA1-agonist complexes at the atomic level applying molecular docking and dynamics methods accounting for covalent and non-covalent interactions. Following a test of docking methods focused on the final, holo structures, prerequisite binding modes were detected involving the apo forms. It was shown how reversible interactions with prerequisite binding sites contribute to structural changes of TRPA1 leading to covalent bonding of agonists. The proposed dynamics of action allowed a mechanism-based forecast of new, druggable binding sites of potent agonists.

Biocatalytic synthesis of planar chiral macrocycles

Macrocycles can restrict the rotation of substituents through steric repulsions, locking in conformations that provide or enhance the activities of pharmaceuticals, agrochemicals, aroma chemicals, and materials. In many cases, the arrangement of substituents in the macrocycle imparts an element of planar chirality. The difficulty in predicting when planar chirality will arise, as well as the limited number of synthetic methods to impart selectivity, have led to planar chirality being regarded as an irritant. We report a strategy for enantio- and atroposelective biocatalytic synthesis of planar chiral macrocycles. The macrocycles can be formed with high enantioselectivity from simple building blocks and are decorated with functionality that allows one to further modify the macrocycles with diverse structural features.

Structural Basis for Achieving GSK-3β Inhibition with High Potency, Selectivity, and Brain Exposure for Positron Emission Tomography Imaging and Drug Discovery

Using structure-guided design, several cell based assays, and microdosed positron emission tomography (PET) imaging, we identified a series of highly potent, selective, and brain-penetrant oxazole-4-carboxamide-based inhibitors of glycogen synthase kinase-3 (GSK-3). An isotopologue of our first-generation lead, [3H]PF-367, demonstrates selective and specific target engagement in vitro, irrespective of the activation state. We discovered substantial ubiquitous GSK-3-specific radioligand binding in Tg2576 Alzheimer's disease (AD), suggesting application for these compounds in AD diagnosis and identified [11C]OCM-44 as our lead GSK-3 radiotracer, with optimized brain uptake by PET imaging in nonhuman primates. GSK-3β-isozyme selectivity was assessed to reveal OCM-51, the most potent (IC50 = 0.030 nM) and selective (>10-fold GSK-3β/GSK-3α) GSK-3β inhibitor known to date. Inhibition of CRMP2T514 and tau phosphorylation, as well as favorable therapeutic window against WNT/β-catenin signaling activation, was observed in cells.

Evaluation of α-hydroxycinnamic acids as pyruvate carboxylase inhibitors

Through a structure-based drug design project (SBDD), potent small molecule inhibitors of pyruvate carboxylase (PC) have been discovered. A series of α-keto acids (7) and α-hydroxycinnamic acids (8) were prepared and evaluated for inhibition of PC in two assays. The two most potent inhibitors were 3,3'-(1,4-phenylene)bis[2-hydroxy-2-propenoic acid] (8u) and 2-hydroxy-3-(quinoline-2-yl)propenoic acid (8v) with IC₅₀ values of 3.0 ± 1.0 μM and 4.3 ± 1.5 μM respectively. Compound 8v is a competitive inhibitor with respect to pyruvate (K_i = 0.74 μM) and a mixed-type inhibitor with respect to ATP, indicating that it targets the unique carboxyltransferase (CT) domain of PC. Furthermore, compound 8v does not significantly inhibit human carbonic anhydrase II, matrix metalloproteinase-2, malate dehydrogenase or lactate dehydrogenase.

Predicting Positions of Bridging Water Molecules in Nucleic Acid-Ligand Complexes

Over the past two decades, interests in DNA and RNA as drug targets have been growing rapidly. Following the trends observed with protein drug targets, computational approaches for drug design have been developed for this new class of molecules. Our efforts toward the development of a universal docking program, Fitted, led us to focus on nucleic acids. Throughout the development of this docking program, efforts were directed toward displaceable water molecules which must be accurately located for optimal docking-based drug discovery. However, although there is a plethora of methods to place water molecules in and around protein structures, there is, to the best of our knowledge, no such fully automated method for nucleic acids, which are significantly more polar and solvated than proteins. We report herein a new method, Splash'Em (Solvation Potential Laid around Statistical Hydration on Entire Macromolecules) developed to place water molecules within the binding cavity of nucleic acids. This fast method was shown to have high agreement with water positions in crystal structures and will therefore provide essential information to medicinal chemists.

Customizable de novo design strategies for DOCK: Application to HIVgp41 and other therapeutic targets

De novo design can be used to explore vast areas of chemical space in computational lead discovery. As a complement to virtual screening, from-scratch construction of molecules is not limited to compounds in pre-existing vendor catalogs. Here, we present an iterative fragment growth method, integrated into the program DOCK, in which new molecules are built using rules for allowable connections based on known molecules. The method leverages DOCK's advanced scoring and pruning approaches and users can define very specific criteria in terms of properties or features to customize growth toward a particular region of chemical space. The code was validated using three increasingly difficult classes of calculations: (1) Rebuilding known X-ray ligands taken from 663 complexes using only their component parts (focused libraries), (2) construction of new ligands in 57 drug target sites using a library derived from ∼13M drug-like compounds (generic libraries), and (3) application to a challenging protein-protein interface on the viral drug target HIVgp41. The computational testing confirms that the de novo DOCK routines are robust and working as envisioned, and the compelling results highlight the potential utility for designing new molecules against a wide variety of important protein targets. © 2017 Wiley Periodicals, Inc.

Medicinal Chemistry Projects Requiring Imaginative Structure-Based Drug Design Methods

Computational methods for docking small molecules to proteins are prominent in drug discovery. There are hundreds, if not thousands, of documented examples-and several pertinent cases within our research program. Fifteen years ago, our first docking-guided drug design project yielded nanomolar metalloproteinase inhibitors and illustrated the potential of structure-based drug design. Subsequent applications of docking programs to the design of integrin antagonists, BACE-1 inhibitors, and aminoglycosides binding to bacterial RNA demonstrated that available docking programs needed significant improvement. At that time, docking programs primarily considered flexible ligands and rigid proteins. We demonstrated that accounting for protein flexibility, employing displaceable water molecules, and using ligand-based pharmacophores improved the docking accuracy of existing methods-enabling the design of bioactive molecules. The success prompted the development of our own program, Fitted, implementing all of these aspects. The primary motivation has always been to respond to the needs of drug design studies; the majority of the concepts behind the evolution of Fitted are rooted in medicinal chemistry projects and collaborations. Several examples follow: (1) Searching for HDAC inhibitors led us to develop methods considering drug-zinc coordination and its effect on the pKa of surrounding residues. (2) Targeting covalent prolyl oligopeptidase (POP) inhibitors prompted an update to Fitted to identify reactive groups and form bonds with a given residue (e.g., a catalytic residue) when the geometry allows it. Fitted-the first fully automated covalent docking program-was successfully applied to the discovery of four new classes of covalent POP inhibitors. As a result, efficient stereoselective syntheses of a few screening hits were prioritized rather than synthesizing large chemical libraries-yielding nanomolar inhibitors. (3) In order to study the metabolism of POP inhibitors by cytochrome P450 enzymes (CYPs)-for toxicology studies-the program Impacts was derived from Fitted and helped us to reveal a complex metabolism with unforeseen stereocenter isomerizations. These efforts, combined with those of other docking software developers, have strengthened our understanding of the complex drug-protein binding process while providing the medicinal chemistry community with useful tools that have led to drug discoveries. In this Account, we describe our contributions over the past 15 years-within their historical context-to the design of drug candidates, including BACE-1 inhibitors, POP covalent inhibitors, G-quadruplex binders, and aminoglycosides binding to nucleic acids. We also remark the necessary developments of docking programs, specifically Fitted, that enabled structure-based design to flourish and yielded multiple fruitful, rational medicinal chemistry campaigns.

Identification of estrogen receptor α ligands with virtual screening techniques

Utilization of computer-aided molecular discovery methods in virtual screening (VS) is a cost-effective approach to identify novel bioactive small molecules. Unfortunately, no universal VS strategy can guarantee high hit rates for all biological targets, but each target requires distinct, fine-tuned solutions. Here, we have studied in retrospective manner the effectiveness and usefulness of common pharmacophore hypothesis, molecular docking and negative image-based screening as potential VS tools for a widely applied drug discovery target, estrogen receptor α (ERα). The comparison of the methods helps to demonstrate the differences in their ability to identify active molecules. For example, structure-based methods identified an already known active ligand from the widely-used bechmarking decoy molecule set. Although prospective VS against one commercially available database with around 100,000 drug-like molecules did not retrieve many testworthy hits, one novel hit molecule with pIC50 value of 6.6, was identified. Furthermore, our small in-house compound collection of easy-to-synthesize molecules was virtually screened against ERα, yielding to five hit candidates, which were found to be active in vitro having pIC50 values from 5.5 to 6.5.

Single-Point Mutation with a Rotamer Library Toolkit: Toward Protein Engineering

Protein engineers have long been hard at work to harness biocatalysts as a natural source of regio-, stereo-, and chemoselectivity in order to carry out chemistry (reactions and/or substrates) not previously achieved with these enzymes. The extreme labor demands and exponential number of mutation combinations have induced computational advances in this domain. The first step in our virtual approach is to predict the correct conformations upon mutation of residues (i.e., rebuilding side chains). For this purpose, we opted for a combination of molecular mechanics and statistical data. In this work, we have developed automated computational tools to extract protein structural information and created conformational libraries for each amino acid dependent on a variable number of parameters (e.g., resolution, flexibility, secondary structure). We have also developed the necessary tool to apply the mutation and optimize the conformation accordingly. For side-chain conformation prediction, we obtained overall average root-mean-square deviations (RMSDs) of 0.91 and 1.01 Å for the 18 flexible natural amino acids within two distinct sets of over 3000 and 1500 side-chain residues, respectively. The commonly used dihedral angle differences were also evaluated and performed worse than the state of the art. These two metrics are also compared. Furthermore, we generated a family-specific library for kinases that produced an average 2% lower RMSD upon side-chain reconstruction and a residue-specific library that yielded a 17% improvement. Ultimately, since our protein engineering outlook involves using our docking software, Fitted/Impacts, we applied our mutation protocol to a benchmarked data set for self- and cross-docking. Our side-chain reconstruction does not hinder our docking software, demonstrating differences in pose prediction accuracy of approximately 2% (RMSD cutoff metric) for a set of over 200 protein/ligand structures. Similarly, when docking to a set of over 100 kinases, side-chain reconstruction (using both general and biased conformation libraries) had minimal detriment to the docking accuracy.

Discovery of novel small-molecule antagonists for GluK2

KA receptors have shown to be potential therapeutic targets in CNS diseases such as schizophrenia, depression, neuropathic pain and epilepsy. Through the use of our docking tool Fitted, we investigated the relationship between ligand activity towards GluK2 and the conformational state induced at the receptor level. By focusing our rational design on the interaction between the ligand and a tyrosine residue in the binding site, we synthesized a series of molecules based on a glutamate scaffold, and carried out electrophysiological recordings. The observed ability of some of these molecules to inhibit receptor activation shows the potential of our design for the development of effective antagonists with a molecular size comparable to that of the endogenous neurotransmitter L-glutamate.

Metabolic Instability of Cyanothiazolidine-Based Prolyl Oligopeptidase Inhibitors: a Structural Assignment Challenge and Potential Medicinal Chemistry Implications

As part of the development of cyanothiazolidine-based prolyl oligopeptidase inhibitors, initial metabolism studies suggested multiple sites of oxidation by P450 enzymes. Surprisingly, in-depth investigations revealed that epimerization at multiple stereogenic centers was responsible for the conversion of the single primary metabolite into a panel of secondary metabolites. The rapid isomerization of all seven detected molecules precluded the use of NMR spectroscopy or X-ray crystallography for complete structural determination, presenting an interesting structure elucidation challenge. Through a combination of LC-MS analysis, synthetic work, deuterium exchange studies, and computational predictions, we were able to characterize all metabolites and to elucidate their dynamic behavior in solution. In the context of drug development, this study reveals that cyanothiazolidine moieties are problematic due to their rapid P450-mediated oxidation and the unpredictable stability of the corresponding metabolites.

Improvements, trends, and new ideas in molecular docking: 2012-2013 in review

Molecular docking is a computational method for predicting the placement of ligands in the binding sites of their receptor(s). In this review, we discuss the methodological developments that occurred in the docking field in 2012 and 2013, with a particular focus on the more difficult aspects of this computational discipline. The main challenges and therefore focal points for developments in docking, covered in this review, are receptor flexibility, solvation, scoring, and virtual screening. We specifically deal with such aspects of molecular docking and its applications as selection criteria for constructing receptor ensembles, target dependence of scoring functions, integration of higher-level theory into scoring, implicit and explicit handling of solvation in the binding process, and comparison and evaluation of docking and scoring methods.

Syntheses and evaluation of carbon-11- and fluorine-18-radiolabeled pan-tropomyosin receptor kinase (Trk) inhibitors: exploration of the 4-aza-2-oxindole scaffold as Trk PET imaging agents

Tropomyosin receptor kinases (TrkA/B/C) are critically involved in the development of the nervous system, in neurological disorders as well as in multiple neoplasms of both neural and non-neural origins. The development of Trk radiopharmaceuticals would offer unique opportunities toward a more complete understanding of this emerging therapeutic target. To that end, we first developed [(11)C]GW441756 ([(11)C]9), a high affinity photoisomerizable pan-Trk inhibitor, as a lead radiotracer for our positron emission tomography (PET) program. Efficient carbon-11 radiolabeling afforded [(11)C]9 in high radiochemical yields (isolated RCY, 25.9% ± 5.7%). In vitro autoradiographic studies in rat brain and TrkB-expressing human neuroblastoma cryosections confirmed that [(11)C]9 specifically binds to Trk receptors in vitro. MicroPET studies revealed that binding of [(11)C]9 in the rodent brain was mostly nonspecific despite initial high brain uptake (SUVmax = 2.0). Modeling studies of the 4-aza-2-oxindole scaffold led to the successful identification of a small series of high affinity fluorinated and methoxy derivatized pan-Trk inhibitors based on our lead compound 9. Out of this series, the fluorinated compound 10 was selected for initial evaluation and radiolabeled with fluorine-18 (isolated RCY, 2.5% ± 0.6%). Compound [(18)F]10 demonstrated excellent Trk selectivity in a panel of cancer relevant kinase targets and a promising in vitro profile in tumors and brain sections but high oxidative metabolic susceptibility leading to nonspecific brain distribution in vivo. The information gained in this study will guide further exploration of the 4-aza-2-oxindole scaffold as a lead for Trk PET ligand development.

istar: a web platform for large-scale protein-ligand docking

Protein-ligand docking is a key computational method in the design of starting points for the drug discovery process. We are motivated by the desire to automate large-scale docking using our popular docking engine idock and thus have developed a publicly-accessible web platform called istar. Without tedious software installation, users can submit jobs using our website. Our istar website supports 1) filtering ligands by desired molecular properties and previewing the number of ligands to dock, 2) monitoring job progress in real time, and 3) visualizing ligand conformations and outputting free energy and ligand efficiency predicted by idock, binding affinity predicted by RF-Score, putative hydrogen bonds, and supplier information for easy purchase, three useful features commonly lacked on other online docking platforms like DOCK Blaster or iScreen. We have collected 17,224,424 ligands from the All Clean subset of the ZINC database, and revamped our docking engine idock to version 2.0, further improving docking speed and accuracy, and integrating RF-Score as an alternative rescoring function. To compare idock 2.0 with the state-of-the-art AutoDock Vina 1.1.2, we have carried out a rescoring benchmark and a redocking benchmark on the 2,897 and 343 protein-ligand complexes of PDBbind v2012 refined set and CSAR NRC HiQ Set 24Sept2010 respectively, and an execution time benchmark on 12 diverse proteins and 3,000 ligands of different molecular weight. Results show that, under various scenarios, idock achieves comparable success rates while outperforming AutoDock Vina in terms of docking speed by at least 8.69 times and at most 37.51 times. When evaluated on the PDBbind v2012 core set, our istar platform combining with RF-Score manages to reproduce Pearson's correlation coefficient and Spearman's correlation coefficient of as high as 0.855 and 0.859 respectively between the experimental binding affinity and the predicted binding affinity of the docked conformation. istar is freely available at http://istar.cse.cuhk.edu.hk/idock.

A platinum(II) phenylphenanthroimidazole with an extended side-chain exhibits slow dissociation from a c-Kit G-quadruplex motif

A series of three platinum(II) phenanthroimidazoles each containing a protonable side-chain appended from the phenyl moiety through copper(I)-catalyzed azide-alkyne cycloaddition (CuAAC) were evaluated for their capacities to bind to human telomere, c-Myc, and c-Kit derived G-quadruplexes. The side-chain has been optimized to enable a multivalent binding mode to G-quadruplex motifs, which would potentially result in selective targeting. Molecular modeling, high-throughput fluorescence intercalator displacement (HT-FID) assays, and surface plasmon resonance (SPR) studies demonstrate that complex 2 exhibits significantly slower dissociation rates compared to platinum phenanthroimidazoles without side-chains and other reported G-quadruplex binders. Complex 2 showed little cytotoxicity in HeLa and A172 cancer cell lines, consistent with the fact that it does not follow a telomere-targeting pathway. Preliminary mRNA analysis shows that 2 specifically interacts with the ckit promoter region. Overall, this study validates 2 as a useful molecular probe for c-Kit related cancer pathways.

Development of a computational tool to rival experts in the prediction of sites of metabolism of xenobiotics by p450s

The metabolism of xenobiotics--and more specifically drugs--in the liver is a critical process controlling their half-life. Although there exist experimental methods, which measure the metabolic stability of xenobiotics and identify their metabolites, developing higher throughput predictive methods is an avenue of research. It is expected that predicting the chemical nature of the metabolites would be an asset for designing safer drugs and/or drugs with modulated half-lives. We have developed IMPACTS (In-silico Metabolism Prediction by Activated Cytochromes and Transition States), a computational tool combining docking to metabolic enzymes, transition state modeling, and rule-based substrate reactivity prediction to predict the site of metabolism (SoM) of xenobiotics. Its application to sets of CYP1A2, CYP2C9, CYP2D6, and CYP3A4 substrates and comparison to experts' predictions demonstrates its accuracy and significance. IMPACTS identified an experimentally observed SoM in the top 2 predicted sites for 77% of the substrates, while the accuracy of biotransformation experts' prediction was 65%. Application of IMPACTS to external sets and comparison of its accuracy to those of eleven other methods further validated the method implemented in IMPACTS.

Virtual screening and computational optimization for the discovery of covalent prolyl oligopeptidase inhibitors with activity in human cells

Our docking program, Fitted, implemented in our computational platform, Forecaster, has been modified to carry out automated virtual screening of covalent inhibitors. With this modified version of the program, virtual screening and further docking-based optimization of a selected hit led to the identification of potential covalent reversible inhibitors of prolyl oligopeptidase activity. After visual inspection, a virtual hit molecule together with four analogues were selected for synthesis and made in one-five chemical steps. Biological evaluations on recombinant POP and FAPα enzymes, cell extracts, and living cells demonstrated high potency and selectivity for POP over FAPα and DPPIV. Three compounds even exhibited high nanomolar inhibitory activities in intact living human cells and acceptable metabolic stability. This small set of molecules also demonstrated that covalent binding and/or geometrical constraints to the ligand/protein complex may lead to an increase in bioactivity.