New molecular scaffolds for the design of Mycobacterium tuberculosis type II dehydroquinase inhibitors identified using ligand and receptor based virtual screening

Using ligand and receptor based virtual screening approaches we have identified potential virtual screening hits targeting type II dehydroquinase from Mycobacterium tuberculosis, an effective and validated anti-mycobacterial target. Initially, we applied a virtual screening workflow based on a combination of 2D structural fingerprints, 3D pharmacophore and molecular docking to identify compounds that rigidly match specific aspects of ligand bioactive conformation. Subsequently, the resulting compounds were ranked and prioritized using receptor interaction fingerprint based scoring and quantitative structure activity relationship model developed using already known actives. The virtual screening hits prioritized belong to several classes of molecular scaffolds with several available substitution positions that could allow chemical modification to enhance binding affinity. Finally, identified hits may be useful to a medicinal chemist or combinatorial chemist to pick up the new molecular starting points for medicinal chemistry optimization for the design of novel type II dehydroquinase inhibitors.     

Efficient hit-finding approaches for histone methyltransferases: the key parameters

For many novel epigenetics targets the chemical ligand space and structural information were limited until recently and are still largely unknown for some targets. Hit-finding campaigns are therefore dependent on large and chemically diverse libraries. In the specific case of the histone methyltransferase G9a, the authors have been able to apply an efficient process of intelligent selection of compounds for primary screening, rather than screening the full diverse deck of 900 000 compounds to identify hit compounds. A number of different virtual screening methods have been applied for the compound selection, and the results have been analyzed in the context of their individual success rates. For the primary screening of 2112 compounds, a FlashPlate assay format and full-length histone H3.1 substrate were employed. Validation of hit compounds was performed using the orthogonal fluorescence lifetime technology. Rated by purity and IC(50) value, 18 compounds (0.9% of compound screening deck) were finally considered validated primary G9a hits. The hit-finding approach has led to novel chemotypes being identified, which can facilitate hit-to-lead projects. This study demonstrates the power of virtual screening technologies for novel, therapeutically relevant epigenetics protein targets.     

Ligand based virtual screening and biological evaluation of inhibitors of chorismate mutase (Rv1885c) from Mycobacterium tuberculosis H37Rv

We have identified new lead candidates that possess inhibitory activity against Mycobacterium tuberculosis H37Rv chorismate mutase by a ligand-based virtual screening optimized for lead evaluation in combination with in vitro enzymatic assay. The initial virtual screening using a ligand-based pharmacophore model identified 95 compounds from an in-house small molecule database of 15,452 compounds. The obtained hits were further evaluated by molecular docking and 15 compounds were short listed based on docking scores and the other scoring functions and subjected to biological assay. Chorismate mutase activity assays identified four compounds as inhibitors of M. tuberculosis chorismate mutase (MtCM) with low K(i) values. The structural models for these ligands in the chorismate mutase binding site will facilitate medicinal chemistry efforts for lead optimization against this protein.     

Pharmacophore modeling and structure-based virtual screening to identify potent inhibitors targeting LuxP of Vibrio harveyi

The main aim of the study is to identify molecules that can disrupt quorum sensing (QS) system of Vibrio harveyi and therefore perhaps the production of toxins. Recently, a novel class of dioxazaborocane derivatives has been found to block AI-2 QS by targeting LuxPQ, but the mechanism of protein inhibition is still unclear. In order to investigate the possible binding modes, all the derivatives were docked into the binding site of LuxP using induced fit docking (IFD). The computed binding affinity is in good agreement with the experimental data. Resultant protein–ligand complexes were simulated using Desmond module and the result revealed better binding of ligands in the binding site of LuxP. Both pharmacophore- and structure-based virtual screening was performed to identify novel hits against LuxP. A filtering protocol, including lipinski filters, number of rotatable bonds and three levels of docking precisions were used for the selection of hits with specific properties. The virtual screening results were then combined and analyzed, which retrieved six hits with significant Glide score, binding affinity toward LuxP. The pharmacokinetic properties of the retrieved hits are in the acceptable range. Enrichment calculation was performed to validate the final hits, to discriminate the active compounds from the inactive compounds. The identified hits could serve as a base for further drug development against LuxP of Vibrio harveyi.     

Identification of plasmepsin inhibitors as selective anti-malarial agents using ligand based drug design

We describe the application of ligand based virtual screening technologies towards the discovery of novel plasmepsin (PM) inhibitors, a family of malarial parasitic aspartyl proteases. Pharmacophore queries were used to screen vendor libraries in search of active and selective compounds. The virtual hits were biologically assessed for activity and selectivity using whole cell Plasmodium falciparum parasites and on target in PM II, PM IV and the closely related human homologue, Cathepsin D assays. Here we report the virtual screening highlights, structures of the hits and their demonstrated biological activity.     

Pharmmaker: Pharmacophore modeling and hit identification based on druggability simulations

Recent years have seen progress in druggability simulations, that is, molecular dynamics simulations of target proteins in solutions containing drug‐like probe molecules to characterize their drug‐binding abilities, if any. An important consecutive step is to analyze the trajectories to construct pharmacophore models (PMs) to use for virtual screening of libraries of small molecules. While considerable success has been observed in this type of computer‐aided drug discovery, a systematic tool encompassing multiple steps from druggability simulations to pharmacophore modeling, to identifying hits by virtual screening of libraries of compounds, has been lacking. We address this need here by developing a new tool, Pharmmaker, building on the DruGUI module of our ProDy application programming interface. Pharmmaker is composed of a suite of steps: (Step 1) identification of high affinity residues for each probe molecule type; (Step 2) selecting high affinity residues and hot spots in the vicinity of sites identified by DruGUI; (Step 3) ranking of the interactions between high affinity residues and specific probes; (Step 4) obtaining probe binding poses and corresponding protein conformations by collecting top‐ranked snapshots; and (Step 5) using those snapshots for constructing PMs. The PMs are then used as filters for identifying hits in structure‐based virtual screening. Pharmmaker, accessible online at http://prody.csb.pitt.edu/pharmmaker , can be used in conjunction with other tools available in ProDy.     

Evaluation of the amino acid binding site of Mycobacterium tuberculosis glutamine synthetase for drug discovery

A combination of a literature survey, structure-based virtual screening and synthesis of a small library was performed to identify hits to the potential antimycobacterial drug target, glutamine synthetase. The best inhibitor identified from the literature survey was (2S,5R)-2,6-diamino-5-hydroxyhexanoic acid (4, IC(50) of 610+/-15microM). In the virtual screening 46,400 compounds were docked and subjected to a pharmacophore search. Of these compounds, 29 were purchased and tested in a biological assay, allowing three novel inhibitors containing an aromatic scaffold to be identified. Based on one of the hits from the virtual screening a small library of 15 analogues was synthesized producing four compounds that inhibited glutamine synthetase.     

Pharmacophore and structure-based drug design,molecular dynamics and admet/tox studies to design novel potential pad4 inhibitors

We have used docking (GLIDE), pharmacophore modeling (Discovery Studio), long trajectory molecular dynamics (Discovery Studio) and ADMET/Tox (QikProp and DEREK) to investigate PAD4 in order to determine potential novel inhibitors and hits. We have carried out virtual screening in the ZINC natural compounds database. Pharmacokinetics and Toxicity of the best hits were assessed using databases implemented in softwares that create models based on chemical structures taking into account consideration about the toxicophoric groups. A wide variety of pharmaceutical relevant properties are determined in order to make decisions about molecular suitability. After screening and analysis, the 6 most promising PAD4 inhibitors are suggested, with strong interactions (pi-stacking, hydrogen bonds, hydrophobic contacts) and suitable pharmacotherapeutic profile as well.     

Discovery of hit molecules targeting allosteric site of hepatitis C virus NS5B polymerase

Abstract

Nonstructural protein 5B (NS5B), the RNA-dependent RNA polymerase of Hepatitis C Virus (HCV), plays a key role in viral amplification and is an attractive and most explored target for discovery of new therapeutic agents for Hepatitis C. Though safe and effective, NS5B inhibitors were launched in 2013 (Sovaldi) and 2014 (Harvoni, Viekira Pak), the high price tags of these medications limit their use among poor people in developing countries. Hence, still there exists a need for cost-effective and short duration anti-HCV agents especially those targeting niche patient population who were non-respondent to earlier therapies or with comorbid conditions. The present study describes the discovery of novel non-nucleoside (NNI) inhibitors of NS5B using a series of rational drug design techniques such as virtual screening, scaffold matching and molecular docking. 2D and 3D structure based virtual screening technique identified 300 hit compounds. Top 20 hits were screened out from identified hits using molecular docking technique. Four molecules, that are representative of 20 hits were evaluated for binding affinity under in vitro conditions using surface plasmon resonance-based assay and the results emphasized that compound with CoCoCo ID: 412075 could exhibit good binding response toward NS5B and could be a potential candidate as NS5B inhibitor.

Communicated by Ramaswamy H. Sarma     

3D pharmacophore based virtual screening of T-type calcium channel blockers

Virtual screening of the commercial databases was done by using a three dimensional pharmacophore previously developed for T-type calcium channel blockers using CATALYSTtrade mark program. Biological evaluation of 25 selected virtual hits resulted in the discovery of a highly potent compound VH04 with IC(50) value of 0.10 microM, eight times as potent as the known selective T-type calcium channel blocker, mibefradil. Search for similar compounds yielded several hits with micro-molar IC(50) values and high T-type calcium channel selectivity. Based on the structure of the virtual hits, small molecule libraries with novel scaffolds were designed, synthesis and biological evaluation of which are currently in progress. This result shows a successful example of ligand based drug discovery of potent T-type calcium channel blockers.     

Identification of novel serotonin 2C receptor ligands by sequential virtual screening

Pharmacophore modelling, docking and virtual screening have become important tool in drug discovery process. Serotonin 2C (5-HT_2C) receptor ligands have got major attention for their therapeutic uses as antidepressant and anorectic agents. Two step pharmacophore and docking based virtual screening was done using 5-HT_2C agonists. Two common feature pharmacophore directed virtual hits had submicromolar activity. Refined pharmacophore with excluded volumes was constructed and combined with homology model based docking. Best hit from this virtual screening showed IC₅₀ of 20.1 nM. Similarity search of this hit compound resulted more active ligand with 7.8 nM activity.     

Probing voltage sensing domain of KCNQ2 channel as a potential target to combat epilepsy: a comparative study

Multidrug resistance along with side-effects of available anti-epileptic drugs and unavailability of potent and effective agents in submicromolar quantities presents the biggest therapeutic challenges in anti-epileptic drug discovery. The molecular modeling techniques allow us to identify agents with novel structures to match the continuous urge for its discovery. KCNQ2 channel represents one of the validated targets for its therapy. The present study involves identification of newer anti-epileptic agents by means of a computer-aided drug design adaptive protocol involving both structure-based virtual screening of Asinex library using homology model of KCNQ2 and 3D-QSAR based virtual screening with docking analysis, followed by dG bind and ligand efficiency calculations with ADMET studies, of which 20 hits qualified all the criterions. The best ligands of both screenings with least potential for toxicity predicted computationally were then taken for molecular dynamic simulations. All the crucial amino acid interactions were observed in hits of both screenings such as Glu130, Arg207, Arg210 and Phe137. Robustness of docking protocol was analyzed through Receiver operating characteristic (ROC) curve values 0.88 (Area under curve AUC?=?0.87) in Standard Precision and 0.84 (AUC?=?0.82) in Extra Precision modes. Novelty analysis indicates that these compounds have not been reported previously as anti-epileptic agents.     

Synthesis and biological testing of novel pyridoisothiazolones as histone acetyltransferase inhibitors

We present a combination of database screening, synthesis and in vitro testing to identify novel histone acetyltransferase (HAT) inhibitors. The National Cancer Institute compound collection (NCI) and several commercial databases were filtered by similarity-based virtual screening to find new HAT inhibitors. Employing the recombinant HAT p300/CBP-associated factor (PCAF) and two different histone substrates for screening, pyridoisothiazolones were identified as inhibitors of human PCAF. Due to the limited solubility of the initial hits, we synthesized and tested them on PCAF. The compounds inhibit the proliferation of cancer cells. In summary, valuable chemical tools and potential lead candidates for new anticancer agents directed against HATs as new targets have been identified.     

Computational approach to the identification of novel Aurora-A inhibitors

Aurora kinase A has been emerging as a key therapeutic target for the design of anticancer drugs. For the purpose of finding biologically active and novel compounds and providing new ideas for drug-design, we performed virtual screening using commercially available databases. A three-dimensional common feature pharmacophore model was developed with the HipHop program provided in the Catalyst software package, and this model was used as a query for screening the databases. A recursive partitioning (RP) model was developed as a filtering system, which was able to classify active and inactive compounds. Eventually, a step-wise virtual screening procedure was conducted by applying the common feature pharmacophore and the RP model in succession to discover novel potent Aurora-A inhibitors. A total of 68 compounds were selected for testing of their in vitro anticancer activities against various human cancer cell lines. Based on the activity data, we have identified fifteen compounds that warrant further investigation. Several compounds have a high inhibition rate (above 80% at 10 ??M) and a GI₅₀ lower than 5 ??M for the cell lines DU145 and HT29. Enzyme assay for these compounds identified hits with micro molar activity. Compound C11 has the highest activity (IC₅₀ = 5.09 ??M). The hits obtained from this screening scheme could be potential drug candidates after further optimization.     

IKKβ inhibitors identification part I: Homology model assisted structure based virtual screening

Control of NF-κB release through the inhibition of IKKβ has been identified as a potential target for the treatment of inflammatory and autoimmune diseases. We have employed structure based virtual screening scheme to identify lead like molecule from ChemDiv database. Homology models of IKKβ enzyme were developed based on the crystal structures of four kinases. The efficiency of the homology model has been validated at different levels. Docking of known inhibitors library revealed the possible binding mode of inhibitors. Besides, the docking sequence analyses results indicate the responsibility of Glu172 in selectivity. Structure based virtual screening of ChemDiv database has yielded 277 hits. Top scoring 75 compounds were selected and purchased for the IKKβ enzyme inhibition test. From the combined approach of virtual screening followed by biological screening, we have identified six novel compounds that can work against IKKβ, in which 1 compound had highest inhibition rate 82.09% at 10 μM and IC₅₀ 1.76 μM and 5 compounds had 25.35–48.80% inhibition.     

A new strategy for improved secondary screening and lead optimization using high-resolution SPR characterization of compound-target interactions

Biophysical label-free assays such as those based on SPR are essential tools in generating high-quality data on affinity, kinetic, mechanistic and thermodynamic aspects of interactions between target proteins and potential drug candidates. Here we show examples of the integration of SPR with bioinformatic approaches and mutation studies in the early drug discovery process. We call this combination 'structure-based biophysical analysis'. Binding sites are identified on target proteins using information that is either extracted from three-dimensional structural analysis (X-ray crystallography or NMR), or derived from a pharmacore model based on known binders. The binding site information is used for in silico screening of a large substance library (e.g. available chemical directory), providing virtual hits. The three-dimensional structure is also used for the design of mutants where the binding site has been impaired. The wild-type target and the impaired mutant are then immobilized on different spots of the sensor chip and the interactions of compounds with the wild-type and mutant are compared in order to identify selective binders for the binding site of the target protein. This method can be used as a cost-effective alternative to high-throughput screening methods in cases when detailed binding site information is available. Here, we present three examples of how this technique can be applied to provide invaluable data during different phases of the drug discovery process.     

Discovery of LRRK2 inhibitors by using an ensemble of virtual screening methods

In this paper, we present the results of a ligand- and structure-based virtual screen targeting LRRK2, a kinase that has been implicated in Parkinson’s disease. For the ligand-based virtual screen, the structures of 12 competitor compounds were used as queries for a variety of 2D and 3D searches. The structure-based virtual screen relied on homology models of LRRK2, as no X-ray structure is currently available in the public domain. From the virtual screening, 662 compounds were purchased, of which 35 showed IC₅₀ values below 10 μM in wild-type and/or mutant LRRK2 (a hit rate of 5.3%). Of these 35 hits, four were deemed to have potential for medicinal chemistry follow-up.     

Ligand- and structure-based in silico studies to identify kinesin spindle protein (KSP) inhibitors as potential anticancer agents

Kinesin spindle protein (KSP) belongs to the kinesin superfamily of microtubule-based motor proteins. KSP is responsible for the establishment of the bipolar mitotic spindle which mediates cell division. Inhibition of KSP expedites the blockade of the normal cell cycle during mitosis through the generation of monoastral MT arrays that finally cause apoptotic cell death. As KSP is highly expressed in proliferating/cancer cells, it has gained considerable attention as a potential drug target for cancer chemotherapy. Therefore, this study envisaged to design novel KSP inhibitors by employing computational techniques/tools such as pharmacophore modelling, virtual database screening, molecular docking and molecular dynamics. Initially, the pharmacophore models were generated from the data-set of highly potent KSP inhibitors and the pharmacophore models were validated against in house test set ligands. The validated pharmacophore model was then taken for database screening (Maybridge and ChemBridge) to yield hits, which were further filtered for their drug-likeliness. The potential hits retrieved from virtual database screening were docked using CDOCKER to identify the ligand binding landscape. The top-ranked hits obtained from molecular docking were progressed to molecular dynamics (AMBER) simulations to deduce the ligand binding affinity. This study identified MB-41570 and CB-10358 as potential hits and evaluated these experimentally using in vitro KSP ATPase inhibition assays.