Computation of 3D queries for ROCS based virtual screens

Discovery of novel PRMT5 inhibitors bearing a methylpiperazinyl moiety

Background: PRMT5 is an epigenetics-related enzyme, which plays a critical role in cancer development. Hence PRMT5 inhibition has been validated as a promising therapeutic strategy. Methods & Results: We synthesized a series of methylpiperazinyl derivatives as novel PRMT5 inhibitors that were achieved by scaffold-hopping from EPZ015666 by virtual screening followed by rational drug design. Among all compounds 43g, bearing a thiourea linker, showed antitumor activity across multiple cancer cell lines and reduced the level of symmetric arginine dimethylation of SmD3 dose-dependently. Moreover, 43g selectively inhibited PRMT5 among protein arginine methyltransferase isoforms. Further proteomics analysis revealed that 43g remarkably reduced the global arginine dimethylation level in a cellular context. Conclusion: This work provides new chemical templates for future structural optimization of PRMT5-related cancer treatments.

BCL::MolAlign: Three-Dimensional Small Molecule Alignment for Pharmacophore Mapping

Small molecule flexible alignment is a critical component of both ligand- and structure-based methods in computer-aided drug discovery. Despite its importance, the availability of high-quality flexible alignment software packages is limited. Here, we present BCL::MolAlign, a freely available property-based molecular alignment program. BCL::MolAlign accommodates ligand flexibility through a combination of pregenerated conformers and on-the-fly bond rotation. BCL::MolAlign converges on alignment poses by sampling the relative orientations of mutually matching atom pairs between molecules through Monte Carlo Metropolis sampling. Across six diverse ligand data sets, BCL::MolAlign flexible alignment outperforms MOE, ROCS, and FLEXS in recovering native ligand binding poses. Moreover, the BCL::MolAlign alignment score is more predictive of ligand activity than maximum common substructure similarity across 10 data sets. Finally, on a recently published benchmark set of 20 high quality congeneric ligand-protein complexes, BCL::MolAlign is able to recover a larger fraction of native binding poses than maximum common substructure-based alignment and RosettaLigand. BCL::MolAlign can be obtained as part of the Biology and Chemistry Library (BCL) software package freely with an academic license or can be accessed via Web server at http://meilerlab.org/index.php/servers/molalign .

Methods for Virtual Screening of GPCR Targets: Approaches and Challenges

Virtual screening (VS) has become an integral part of the drug discovery process and is a valuable tool for finding novel chemical starting points for GPCR targets. Ligand-based VS makes use of biochemical data for known, active compounds and has been applied successfully to many diverse GPCRs. Recent progress in GPCR X-ray crystallography has made it possible to incorporate detailed structural information into the VS process. This chapter outlines the latest VS techniques along with examples that highlight successful applications of these methods. Best practices for increasing the likelihood of VS success, as well as ongoing challenges, are also discussed.

Discovery, design and synthesis of 6H-anthra[1,9-cd]isoxazol-6-one scaffold as G9a inhibitor through a combination of shape-based virtual screening and structure-based molecular modification

Protein lysine methyltransferase G9a is widely considered as an appealing antineoplastic target. Herein we present an integrated workflow combining shape-based virtual screening and structure-based molecular modification for the identification of novel G9a inhibitors. The shape-based similarity screening through ROCS overlay on the basis of the structure of UNC0638 was performed to identify CPUY074001 contained a 6H-anthra[1,9-cd]isoxazol-6-one scaffold as a hit. Analysis of the binding mode of CPUY074001 with G9a and 3D-QSAR results, two series compounds were designed and synthesized. The derivatives were confirmed to be active by in vitro assay and the SAR was explored by docking stimulations. Besides, several analogues showed acceptable anti-proliferative effects against several cancer cell lines. Among them, CPUY074020 displayed potent dual G9a inhibitory activity and anti-proliferative activity. Furthermore, CPUY074020 induced cell apoptosis in a dose-dependent manner and displayed a significant decrease in dimethylation of H3K9. Simultaneously, CPUY074020 showed reasonable in vivo PK properties. Altogether, our workflow supplied a high efficient strategy in the identification of novel G9a inhibitors. Compounds reported here can serve as promising leads for further study.

Identification of novel JMJD2A inhibitor scaffold using shape and electrostatic similarity search combined with docking method and MM-GBSA approach

We present a hierarchical workflow combining shape- and electrostatic-based virtual screening for the identification of novel Jumonji domain-containing protein 2A (JMJD2A) inhibitors.

Improving the use of ranking in virtual screening against HIV-1 integrase with triangular numbers and including ligand profiling with antitargets

A delicate balance exists between a drug molecule's toxicity and its activity. Indeed, efficacy, toxicity, and side effect problems are a common cause for the termination of drug candidate compounds and development projects. To address this, an antitarget interaction profile is built and combined with virtual screening and cross docking for new inhibitors of HIV-1 integrase, in order to consider possible off-target interactions as early as possible in a drug or hit discovery program. New ranking techniques using triangular numbers improve ranking information on the compounds and recovery of known inhibitors into the top compounds using different docking programs. This improved ranking arises from using consensus of ranks between docking programs and ligand efficiencies to derive a new rank, instead of using absolute score values, or average of ranks. The triangular number rerank also allowed the objective combination of results from several protein targets or screen conditions and several programs. Triangular number reranking conserves more information than other reranking methods such as average of scores or averages of ranks. In addition, the use of triangular numbers for reranking makes possible the use of thresholds with a justified leeway based on the number of available known inhibitors, so that the majority of the compounds above the threshold in ranks compare to the compounds that have known experimentally determined biological activity. The battery of anti- or off-targets can be tailored to specific molecular or drug design challenges. In silico filters can thus be deployed in successive stages, for prefiltering, activity profiling, and for further analysis and triaging of libraries of compounds.

Focused chemical libraries--design and enrichment: an example of protein-protein interaction chemical space

One of the many obstacles in the development of new drugs lies in the limited number of therapeutic targets and in the quality of screening collections of compounds. In this review, we present general strategies for building target-focused chemical libraries with a particular emphasis on protein-protein interactions (PPIs). We describe the chemical spaces spanned by nine commercially available PPI-focused libraries and compare them to our 2P2I3D academic library, dedicated to orthosteric PPI modulators. We show that although PPI-focused libraries have been designed using different strategies, they share common subspaces. PPI inhibitors are larger and more hydrophobic than standard drugs; however, an effort has been made to improve the drug-likeness of focused chemical libraries dedicated to this challenging class of targets.

Identification of 1,2,5-oxadiazoles as a new class of SENP2 inhibitors using structure based virtual screening

Small ubiquitin like modifier (SUMO) specific proteases (SENPs) are cysteine proteases that carry out the proteolytic processing of SUMO from its pro form as well as the deconjugation of SUMO from substrate proteins. SENPs are attractive targets for drug discovery due to their crucial role in the development of various diseases. However, the SENPs inhibitor discovery efforts were limited, and only a few inhibitors or activity based probes have been identified until now. Here, we report a new class of SENP2 inhibitors identified by a combination of structure based virtual screening and quantitative FRET based assay. Our virtual screening protocol initially involves the identification of small molecules that have similar shape and electrostatic properties with the conjugate of SUMO1 C-terminal residues and substrate lysine. Molecular docking was then used to prioritize these small molecules for a FRET based assay that quantifies their SENP2 endopeptidase activity. The initial round of virtual screening followed by FRET based assay has enabled the identification of eight compounds with >40% SENP2 inhibition at 30 μM compound concentration. Five of these compounds belong to two scaffolds containing a 1,2,5-oxadiazole core that represent a novel class of SENP2 inhibitors. To improve the inhibitory potency and explore the structure-activity relationship of these two 1,2,5-oxadiazole scaffolds, structurally related compounds were identified in another round of virtual screening. The biological assay results confirmed SENP2 inhibitory activity of these two scaffolds. The most potent compound of each scaffold showed an IC50 of 5.9 and 3.7 μM. Most of the compounds also inhibited closely related isoform SENP1, while no detectable inhibition on other proteases, such as papain and trypsin, was observed. Our study suggests that 1,2,5-oxadiazoles could be used as a starting point for the development of novel therapeutic agents against various diseases targeting SENPs.

Discovery and design of tricyclic scaffolds as protein kinase CK2 (CK2) inhibitors through a combination of shape-based virtual screening and structure-based molecular modification

Protein kinase CK2 (CK2), a ubiquitous serine/threonine protein kinase for hundreds of endogenous substrates, serves as an attractive anticancer target. One of its most potent inhibitors, CX-4945, has entered a phase I clinical trial. Herein we present an integrated workflow combining shape-based virtual screening for the identification of novel CK2 inhibitors. A shape-based model derived from CX-4945 was built, and the subsequent virtual screening led to the identification of several novel scaffolds with high shape similarity to that of CX-4945. Among them two tricyclic scaffolds named [1,2,4]triazolo[4,3-c]quinazolin and [1,2,4]triazolo[4,3-a]quinoxalin attracted us the most. Combining strictly chemical similarity analysis, a second-round shape-based screening was performed based on the two tricyclic scaffolds, leading to 28 derivatives. These compounds not only targeted CK2 with potent and dose-dependent activities but also showed acceptable antiproliferative effects against a series of cancer cell lines. Our workflow supplies a high efficient strategy in the identification of novel CK2 inhibitors. Compounds reported here can serve as ideal leads for further modifications.

Integrating ligand-based and protein-centric virtual screening of kinase inhibitors using ensembles of multiple protein kinase genes and conformations

The rapidly growing wealth of structural and functional information about kinase genes and kinase inhibitors that is fueled by a significant therapeutic role of this protein family provides a significant impetus for development of targeted computational screening approaches. In this work, we explore an ensemble-based, protein-centric approach that allows for simultaneous virtual ligand screening against multiple kinase genes and multiple kinase receptor conformations. We systematically analyze and compare the results of ligand-based and protein-centric screening approaches using both single-receptor and ensemble-based docking protocols. A panel of protein kinase targets that includes ABL, EGFR, P38, CDK2, TK, and VEGFR2 kinases is used in this comparative analysis. By applying various performance metrics we have shown that ligand-centric shape matching can provide an effective enrichment of active compounds outperforming single-receptor docking screening. However, ligand-based approaches can be highly sensitive to the choice of inhibitor queries. Employment of multiple inhibitor queries combined with parallel selection ranking criteria can improve the performance and efficiency of ligand-based virtual screening. We also demonstrated that replica-exchange Monte Carlo docking with kinome-based ensembles of multiple crystal structures can provide a superior early enrichment on the kinase targets. The central finding of this study is that incorporation of the template-based structural information about kinase inhibitors and protein kinase structures in diverse functional states can significantly enhance the overall performance and robustness of both ligand and protein-centric screening strategies. The results of this study may be useful in virtual screening of kinase inhibitors potentially offering a beneficial spectrum of therapeutic activities across multiple disease states.

Exploring polypharmacology using a ROCS-based target fishing approach

Polypharmacology has emerged as a new theme in drug discovery. In this paper, we studied polypharmacology using a ligand-based target fishing (LBTF) protocol. To implement the protocol, we first generated a chemogenomic database that links individual protein targets with a specified set of drugs or target representatives. Target profiles were then generated for a given query molecule by computing maximal shape/chemistry overlap between the query molecule and the drug sets assigned to each protein target. The overlap was computed using the program ROCS (Rapid Overlay of Chemical Structures). We validated this approach using the Directory of Useful Decoys (DUD). DUD contains 2950 active compounds, each with 36 property-matched decoys, against 40 protein targets. We chose a set of known drugs to represent each DUD target, and we carried out ligand-based virtual screens using data sets of DUD actives seeded into DUD decoys for each target. We computed Receiver Operator Characteristic (ROC) curves and associated area under the curve (AUC) values. For the majority of targets studied, the AUC values were significantly better than for the case of a random selection of compounds. In a second test, the method successfully identified off-targets for drugs such as rimantadine, propranolol, and domperidone that were consistent with those identified by recent experiments. The results from our ROCS-based target fishing approach are promising and have potential application in drug repurposing for single and multiple targets, identifying targets for orphan compounds, and adverse effect prediction.

Comprehensive structural and functional characterization of the human kinome by protein structure modeling and ligand virtual screening

The growing interest in the identification of kinase inhibitors, promising therapeutics in the treatment of many diseases, has created a demand for the structural characterization of the entire human kinome. At the outset of the drug development process, the lead-finding stage, approaches that enrich the screening library with bioactive compounds are needed. Here, protein structure based methods can play an important role, but despite structural genomics efforts, it is unlikely that the three-dimensional structures of the entire kinome will be available soon. Therefore, at the proteome level, structure-based approaches must rely on predicted models, with a key issue being their utility in virtual ligand screening. In this study, we employ the recently developed FINDSITE/Q-Dock ligand homology modeling approach, which is well-suited for proteome-scale applications using predicted structures, to provide extensive structural and functional characterization of the human kinome. Specifically, we construct structure models for the human kinome; these are subsequently subject to virtual screening against a library of more than 2 million compounds. To rank the compounds, we employ a hierarchical approach that combines ligand- and structure-based filters. Modeling accuracy is carefully validated using available experimental data with particularly encouraging results found for the ability to identify, without prior knowledge, specific kinase inhibitors. More generally, the modeling procedure results in a large number of predicted molecular interactions between kinases and small ligands that should be of practical use in the development of novel inhibitors. The data set is freely available to the academic community via a user-friendly Web interface at http://cssb.biology.gatech.edu/kinomelhm/ as well as at the ZINC Web site ( http://zinc.docking.org/applications/2010Apr/Brylinski-2010.tar.gz ).

Cis-isomerism and other chemical requirements of steroidal agonists and partial agonists acting at TRPM3 channels

BACKGROUND AND PURPOSE

The transient receptor potential melastatin-3 (TRPM3) channel forms calcium-permeable, non-selective, cationic channels that are stimulated by pregnenolone sulphate (PregS). Here, we aimed to define chemical requirements of this acute steroid action and potentially reveal novel stimulators with physiological relevance.

EXPERIMENTAL APPROACH

We used TRPM3 channels over-expressed in HEK 293 cells, with intracellular calcium measurement and whole-cell patch-clamp recording techniques.

KEY RESULTS

The stimulation of TRPM3 channels was confined to PregS and closely related steroids and not mimicked by other major classes of steroids, including progesterone. Relatively potent stimulation of TRPM3-dependent calcium entry was observed. A sulphate group positioned at ring A was important for strong stimulation but more striking was the requirement for a cis (beta) configuration of the side group, revealing previously unrecognized stereo-selectivity and supporting existence of a specific binding site. A cis-oriented side group on ring A was not the only feature necessary for high activity because loss of the double bond in ring B reduced potency and loss of the acetyl group at ring D reduced efficacy and potency. Weak steroid stimulators of TRPM3 channels inhibited effects of PregS, suggesting partial agonism. In silico screening of chemical libraries for non-steroid modulators of TRPM3 channels revealed the importance of the steroid backbone for stimulatory effects.

CONCLUSIONS AND IMPLICATIONS

Our data defined some of the chemical requirements for acute stimulation of TRPM3 channels by steroids, supporting the existence of a specific and unique steroid binding site. Epipregnanolone sulphate was identified as a novel TRPM3 channel stimulator.

Application of QSAR and shape pharmacophore modeling approaches for targeted chemical library design

Optimization of chemical library composition affords more efficient identification of hits from biological screening experiments. The optimization could be achieved through rational selection of reagents used in combinatorial library synthesis. However, with a rapid advent of parallel synthesis methods and availability of millions of compounds synthesized by many vendors, it may be more efficient to design targeted libraries by means of virtual screening of commercial compound collections. This chapter reviews the application of advanced cheminformatics approaches such as quantitative structure-activity relationships (QSAR) and pharmacophore modeling (both ligand and structure based) for virtual screening. Both approaches rely on empirical SAR data to build models; thus, the emphasis is placed on achieving models of the highest rigor and external predictive power. We present several examples of successful applications of both approaches for virtual screening to illustrate their utility. We suggest that the expert use of both QSAR and pharmacophore models, either independently or in combination, enables users to achieve targeted libraries enriched with experimentally confirmed hit compounds.