Virtual Ligand Screening Research Articles

Identification of a pyrimidinetrione derivative as the potent DprE1 inhibitor by structure-based virtual ligand screening

Despite the increasing need of new antituberculosis drugs, the number of agents approved for the market has fallen to an all-time low. In response to the emerging drug resistance followed, structurally unique chemical entities will be highlighted. decaprenylphosphoryl-β-d-ribose oxidase (DprE1) participating in the biosynthesis of mycobacterium cell wall is a highly vulnerable and validated antituberculosis target. On the basis of it, a systematic strategy was applied to identify a high-quality lead compound (compound 50) that inhibits the essential enzyme DprE1, thus blocking the synthesis of the mycobacterial cell wall to kill M. tuberculosis in vitro and in vivo. Correspondingly, the rational design and synthetic strategy for compound 50 was reported. Notably, the compound 50 has been confirmed to be no toxicity. Altogether, our data suggest the compound 50 targeting DprE1 is a promising candidate for the tuberculosis (TB) therapy.

Functional Annotation of Bacterial Signal Transduction Systems: Progress and Challenges.

Bacteria possess a large number of signal transduction systems that sense and respond to different environmental cues. Most frequently these are transcriptional regulators, two-component systems and chemosensory pathways. A major bottleneck in the field of signal transduction is the lack of information on signal molecules that modulate the activity of the large majority of these systems. We review here the progress made in the functional annotation of sensor proteins using high-throughput ligand screening approaches of purified sensor proteins or individual ligand binding domains. In these assays, the alteration in protein thermal stability following ligand binding is monitored using Differential Scanning Fluorimetry. We illustrate on several examples how the identification of the sensor protein ligand has facilitated the elucidation of the molecular mechanism of the regulatory process. We will also discuss the use of virtual ligand screening approaches to identify sensor protein ligands. Both approaches have been successfully applied to functionally annotate a significant number of bacterial sensor proteins but can also be used to study proteins from other kingdoms. The major challenge consists in the study of sensor proteins that do not recognize signal molecules directly, but that are activated by signal molecule-loaded binding proteins.

FINDSITEcomb2.0: A New Approach for Virtual Ligand Screening of Proteins and Virtual Target Screening of Biomolecules.

Computational approaches for predicting protein-ligand interactions can facilitate drug lead discovery and drug target determination. We have previously developed a threading/structural-based approach, FINDSITEcomb, for the virtual ligand screening of proteins that has been extensively experimentally validated. Even when low resolution predicted protein structures are employed, FINDSITEcomb has the advantage of being faster and more accurate than traditional high-resolution structure-based docking methods. It also overcomes the limitations of traditional QSAR methods that require a known set of seed ligands that bind to the given protein target. Here, we further improve FINDSITEcomb by enhancing its template ligand selection from the PDB/DrugBank/ChEMBL libraries of known protein-ligand interactions by (1) parsing the template proteins and their corresponding binding ligands in the DrugBank and ChEMBL libraries into domains so that the ligands with falsely matched domains to the targets will not be selected as template ligands; (2) applying various thresholds to filter out falsely matched template structures in the structure comparison process and thus their corresponding ligands for template ligand selection. With a sequence identity cutoff of 30% of target to templates and modeled target structures, FINDSITEcomb2.0 is shown to significantly improve upon FINDSITEcomb on the DUD-E benchmark set by increasing the 1% enrichment factor from 16.7 to 22.1, with a p-value of 4.3 × 10-3 by the Student t-test. With an 80% sequence identity cutoff of target to templates for the DUD-E set and modeled target structures, FINDSITEcomb2.0, having a 1% ROC enrichment factor of 52.39, also outperforms state-of-the-art methods that employ machine learning such as a deep convolutional neural network, CNN, with an enrichment of 29.65. Thus, FINDSITEcomb2.0 represents a significant improvement in the state-of-the-art. The FINDSITEcomb2.0 web service is freely available for academic users at http://pwp.gatech.edu/cssb/FINDSITE-COMB-2 .

A benchmarking study on virtual ligand screening against homology models of human GPCRs.

G-protein-coupled receptor (GPCR) is an important target class of proteins for drug discovery, with over 27% of FDA-approved drugs targeting GPCRs. However, being a membrane protein, it is difficult to obtain the 3D crystal structures of GPCRs for virtual screening of ligands by molecular docking. Thus, we evaluated the virtual screening performance of homology models of human GPCRs with respect to the corresponding crystal structures. Among the 19 GPCRs involved in this study, we observed that 10 GPCRs have homology models that have better or comparable performance with respect to the corresponding X-ray structures, making homology models a viable choice for virtual screening. For a small subset of GPCRs, we also explored how certain methods like consensus enrichment and sidechain perturbation affect the utility of homology models in virtual screening, as well as the selectivity between agonists and antagonists. Most notably, consensus enrichment across multiple homology models often yields results comparable to the best performing model, suggesting that ligand candidates predicted with consensus scores from multiple models can be the optimal option in practical applications where the performance of each model cannot be estimated.

Novel 3D Structure Based Model for Activity Prediction and Design of Antimicrobial Peptides

The emergence and worldwide spread of multi-drug resistant bacteria makes an urgent challenge for the development of novel antibacterial agents. A perspective weapon to fight against severe infections caused by drug-resistant microorganisms is antimicrobial peptides (AMPs). AMPs are a diverse class of naturally occurring molecules that are produced as a first line of defense by all multi-cellular organisms. Limited by the number of experimental determinate 3D structure, most of the prediction or classification methods of AMPs were based on 2D descriptors, including sequence, amino acid composition, peptide net charge, hydrophobicity, amphiphilic, etc. Due to the rapid development of structural simulation methods, predicted models of proteins (or peptides) have been successfully applied in structure based drug design, for example as targets of virtual ligand screening. Here, we establish the activity prediction model based on the predicted 3D structure of AMPs molecule. To our knowledge, it is the first report of prediction method based on 3D descriptors of AMPs. Novel AMPs were designed by using the model, and their antibacterial effect was measured by in vitro experiments.

Activation Dynamics of the Neurotensin G Protein-Coupled Receptor 1

A replica-exchange protocol remarkably enhances the sampling of the activation dynamics of the neurotensin receptor type 1, a G protein-coupled receptor (GPCR) and important drug target. Our work highlights the dynamic communication between conformational changes of the agonist and the G protein-binding site, via contraction-oscillation of the orthosteric pocket. It also gives insights into the mechanism by which certain mutations diminish or stimulate activation. The replica-exchange protocol effectively enhances barrier crossing where standard brute-force molecular dynamics simulations fail. It is readily applicable to other GPCRs and represents a promising approach for virtual ligand screening, using the typical features of receptor activation as a benchmark.

Steroids from Ganoderma sinense as new natural inhibitors of cancer-associated mutant IDH1

Isocitrate dehydrogenase (IDH) is one of the key enzymes in the tricarboxylic acid cycle, and IDH mutations have been associated with many cancers, including glioblastoma, sarcoma, acute myeloid leukemia, etc. Three natural steroids 1–3 from Ganoderma sinense, a unique and rare edible-medicinal fungi in China, were found as potential IDH1 inhibitors by virtual ligand screening method. Among the three compounds, 3 showed the highest binding affinity to IDH1 with significant calculated binding free energy. Enzymatic kinetics demonstrated that 3 inhibited mutant enzyme in a noncompetitive manner. The half effective concentration of 3 for reducing the concentration of D-2HG in HT1080 cells was 35.97 μM. The levels of histone H3K9me3 methylation in HT1080 cells were reduced by treating with 3. Furthermore, knockdown of mutant IDH1 in HT1080 cells decreased the anti-proliferative sensitivity to 3. In short, our findings highlight that compound 3 may have clinical potential in tumor therapies as an effective inhibitor of mutant IDH1.

A Thieno[2,3- d]pyrimidine Scaffold Is a Novel Negative Allosteric Modulator of the Dopamine D2 Receptor.

Recently, a novel negative allosteric modulator (NAM) of the D2-like dopamine receptors 1 was identified through virtual ligand screening. This ligand comprises a thieno[2,3- d]pyrimidine scaffold that does not feature in known dopaminergic ligands. Herein, we provide pharmacological validation of an allosteric mode of action for 1, revealing that it is a NAM of dopamine efficacy and identify the structural determinants of this allostery. We find that key structural moieties are important for functional affinity and negative cooperativity, while functionalization of the thienopyrimidine at the 5- and 6-positions results in analogues with divergent cooperativity profiles. Successive compound iterations have yielded analogues exhibiting a 10-fold improvement in functional affinity, as well as enhanced negative cooperativity with dopamine affinity and efficacy. Furthermore, our study reveals a fragment-like core that maintains low μM affinity and robust negative cooperativity with markedly improved ligand efficiency.

8-Chrysoeriol, as a potential BCL-2 inhibitor triggers apoptosis of SW1990 pancreatic cancer cells

8-Chrysoeriol, a bioactive flavanoid, was firstly identified to bind directly to BCL-2 as BH3 mimetics by structure-based virtual ligand screening. And 3D docking model revealed the molecular basis of 8-Chrysoeriol targeting to BCL-2. The interaction between 8-Chrysoeriol and BCL-2 was further confirmed using Microscale Thermophoresis (MST) technique. Meanwhile, high expression level of antiapoptotic protein BCL-2 was detected in SW1990 pancreatic cancer cells and 8-Chrysoeriol showed obvious proapoptosis effect against SW1990 in vitro. Collectively, the results showed that 8-Chrysoeriol as a natural dietary product potentially targeting to BCL-2 could serve as a lead compound for SW1990 pancreatic cancer therapy.

Repurposed FDA-approved drugs targeting genes influencing aging can extend lifespan and healthspan in rotifers

Pharmaceutical interventions can slow aging in animals, and have advantages because their dose can be tightly regulated and the timing of the intervention can be closely controlled. They also may complement environmental interventions like caloric restriction by acting additively. A fertile source for therapies slowing aging is FDA approved drugs whose safety has been investigated. Because drugs bind to several protein targets, they cause multiple effects, many of which have not been characterized. It is possible that some of the side effects of drugs prescribed for one therapy may have benefits in retarding aging. We used computationally guided drug screening for prioritizing drug targets to produce a short list of candidate compounds for in vivo testing. We applied the virtual ligand screening approach FINDSITEcomb for screening potential anti-aging protein targets against FDA approved drugs listed in DrugBank. A short list of 31 promising compounds was screened using a multi-tiered approach with rotifers as an animal model of aging. Primary and secondary survival screens and cohort life table experiments identified four drugs capable of extending rotifer lifespan by 8–42%. Exposures to 1 µM erythromycin, 5 µM carglumic acid, 3 µM capecitabine, and 1 µM ivermectin, extended rotifer lifespan without significant effect on reproduction. Some drugs also extended healthspan, as estimated by mitochondria activity and mobility (swimming speed). Our most promising result is that rotifer lifespan was extended by 7–8.9% even when treatment was started in middle age.

Study of adenylyl cyclase-GαS interactions and identification of novel AC ligands.

Adenylyl cyclases (ACs) are membrane bound enzymes that catalyze the production of cAMP from ATP in response to the activation by G-protein Gαs. Different isoforms of ACs are ubiquitously expressed in different tissues involved in regulatory mechanisms in response to specific stimulants. There are 9 AC isoforms present in humans, with AC5 and AC6 proposed to play a vital role in cardiac functions. The activity of AC6 is sensitive to nitric oxide, such that nitrosylation of the protein might regulate its function. However, the information on structural determinants of nitrosylation in ACs and how they interact with Gαs is limited. Here we used homology modeling to build a molecular model of human AC6 bound to Gαs. Based on this 3D model, we predict the nitrosylation amenable cysteines, and identify potential novel ligands of AC6 using virtual ligand screening. Our model suggests Cys1004 in AC6 (subunit C2) and Cys174 in Gαs present at the AC-Gαs interface as the possible residues that might undergo reversible nitrosylation. Docking analysis predicted novel ligands of AC6 that include forskolin-based compounds and its derivatives. Further work involving site-directed mutagenesis of the predicted residues will allow manipulation of AC activity using novel ligands, and crucial insights on the role of nitrosylation of these proteins in pathophysiological conditions.

New natural inhibitors of hexokinase 2 (HK2): Steroids from Ganoderma sinense

Hexokinase 2 (HK2), a rate-limiting enzyme in the first step of glycolysis pathway, expresses at high level in cancer cells compared with normal cells. HK2 provides a new target for cancer therapy due to its pivotal role in tumor tumourigenic and metastatic process. The structure-based virtual ligand screening in a small in-house database of natural products predicted that a new steroid, (22E,24R)-6β-methoxyergosta-7,9(11),22-triene-3β,5α-diol (2) from Ganoderma sinense has high binding affinity to HK2 with significant calculated binding free energy. Based on this prediction, compound 2, together with the other 12 steroid analogues (1, 3–13) from this plant were selected for further in vitro microscale thermophoresis (MST), enzyme inhibition, and cell-based assays based on the HK2 target. And compound 2 was finally identified as an HK2 inhibitor. As the first natural HK2 inhibitor, compound 2 can be considered as a potential drug candidate targeting at HK2 for cancer therapy.

Discovery of Spiro Oxazolidinediones as Selective, Orally Bioavailable Inhibitors of p300/CBP Histone Acetyltransferases.

p300 and its paralog CBP can acetylate histones and other proteins and have been implicated in a number of diseases characterized by aberrant gene activation, such as cancer. A novel, highly selective, orally bioavailable histone acetyltransferase (HAT) domain inhibitor has been identified through virtual ligand screening and subsequent optimization of a unique hydantoin screening hit. Conformational restraint in the form of a spirocyclization followed by substitution with a urea led to a significant improvement in potency. Replacement of the hydantoin moiety with an oxazolidinedione followed by fluoro substitution led to A-485, which exhibits potent cell activity, low clearance, and high oral bioavailability.

Molecular Dynamics as a Tool for Virtual Ligand Screening.

Rational drug design is essential for new drugs to emerge, especially when the structure of a target protein or catalytic enzyme is known experimentally. To that purpose, high-throughput virtual ligand screening campaigns aim at discovering computationally new binding molecules or fragments to inhibit a particular protein interaction or biological activity. The virtual ligand screening process often relies on docking methods which allow predicting the binding of a molecule into a biological target structure with a correct conformation and the best possible affinity. The docking method itself is not sufficient as it suffers from several and crucial limitations (lack of protein flexibility information, no solvation effects, poor scoring functions, and unreliable molecular affinity estimation).At the interface of computer techniques and drug discovery, molecular dynamics (MD) allows introducing protein flexibility before or after a docking protocol, refining the structure of protein-drug complexes in the presence of water, ions and even in membrane-like environments, and ranking complexes with more accurate binding energy calculations. In this chapter we describe the up-to-date MD protocols that are mandatory supporting tools in the virtual ligand screening (VS) process.Using docking in combination with MD is one of the best computer-aided drug design protocols nowadays. It has proved its efficiency through many examples, described below.

Strategies for Designing Novel Anti-Tubercular Drugs with Special Reference to Mycobacterial MelF (Rv1936) as a Drug Target

Tuberculosis (TB) is a major public health problem throughout the world. There is an immediate need to device novel anti-tubercular drugs (ATDs). Whole cell screening (WCS) and target based screening (TBS) approaches are widely used to devise new ATDs. WCS is considered relatively a favourable strategy but it lacks in the precise target knowledge, whereas the target based hit compounds may not ensure the drugability. In this manuscript, we have discussed the potent inhibitors designed against the mycobacterial MelF (Rv1936) by using the TBS as well as virtual ligand screening, which also revealed synergistic effect with the first-line bactericidal drugs, i.e., isoniazid and rifampicin.

A natural inhibitor of kidney-type glutaminase: a withanolide from Physalis pubescens with potent anti-tumor activity.

Kidney-type glutaminase (KGA), a mitochondrial enzyme converting glutamine to glutamate for energy supply, was over-expressed in many cancers and had been regarded as a promising therapeutic target in recent years. Structure-based virtual ligand screening predicted physapubescin K, a new withanolide from Physalis pubescens, to be potential KGA inhibitor. Enzyme activity inhibition assays and microscale thermophoresis experiments had demonstrated the efficiency and specificity of physapubescin K targeting KGA. Additionally, physapubescin K exhibited potent proliferation inhibitory effects on a panel of human cancer cell lines, such as SW1990 and HCC827-ER. It blocked glutamine metabolism in SW1990 with increasing intracellular level of glutamine and decreasing glutamate and its downstream metabolites. Physapubescin K also significantly inhibited the tumor growth in a SW1990 xenograft mouse model. Interestingly, physapubescin K could reverse the resistance of HCC827-ER cells to erlotinib and synergize with the hexokinase 2 inhibitor to markedly enhance the inhibition of SW1990 cell proliferation.

Identification of insulin-sensitizing molecules acting by disrupting the interaction between the Insulin Receptor and Grb14

Metabolic diseases are characterized by a decreased action of insulin. During the course of the disease, usual treatments frequently fail and patients are finally submitted to insulinotherapy. There is thus a need for innovative therapeutic strategies to improve insulin action. Growth factor receptor-bound protein 14 (Grb14) is a molecular adapter that specifically binds to the activated insulin receptor (IR) and inhibits its tyrosine kinase activity. Molecules disrupting Grb14-IR binding are therefore potential insulin-sensitizing agents. We used Structure-Based Virtual Ligand Screening to generate a list of 1000 molecules predicted to hinder Grb14-IR binding. Using an acellular bioluminescence resonance energy transfer (BRET) assay, we identified, out of these 1000 molecules, 3 compounds that inhibited Grb14-IR interaction. Their inhibitory effect on insulin-induced Grb14-IR interaction was confirmed in co-immunoprecipitation experiments. The more efficient molecule (C8) was further characterized. C8 increased downstream Ras-Raf and PI3-kinase insulin signaling, as shown by BRET experiments in living cells. Moreover, C8 regulated the expression of insulin target genes in mouse primary hepatocytes. These results indicate that C8, by reducing Grb14-IR interaction, increases insulin signalling. The use of C8 as a lead compound should allow for the development of new molecules of potential therapeutic interest for the treatment of diabetes.

Farnesyl phenolic enantiomers as natural MTH1 inhibitors from Ganoderma sinense.

Cancer cells are more addictive to MTH1 than normal cells because of their dysfunctional redox regulations. MTH1 plays an important role to maintain tumor cell survival, while it is not indispensable for the growth of normal cells. Farnesyl phenols having a coumaroyl substitution are rather uncommon in nature. Eight farnesyl phenolic compounds with such substituent moiety (1–8), including six new ones, ganosinensols E–J (1–6) were isolated from the 95% EtOH extract of the fruiting bodies of Ganoderma sinense. Four pairs of enantiomers 1/2, 3/4, 5/6 and 7/8 were resolved by HPLC using a Daicel Chiralpak IE column. Their structures were elucidated from extensive spectroscopic analyses and comparison with literature data. The absolute configurations of C-1′ in 1–6 were assigned by ECD spectra. These compounds were predicted to have high binding affinity to MTH1 through virtual ligand screening. The enzyme inhibition experiments and cell-based assays confirmed their inhibitory effects on MTH1. Furthermore, siRNA knockdown experiments and the cellular thermal shift assay (CETSA) confirmed that the farnesyl phenolic enantiomers specifically bound with MTH1 in intact cells. Meanwhile, the low cytotoxicity of 1–8 on normal human cells further verified their good selectivity and specificity to MTH1. These active structures are expected to be potential anti-cancer lead compounds.

Rational design of drug-like compounds targeting Mycobacterium marinum MelF protein.

The mycobacterial mel2 locus (mycobacterial enhanced infection locus, Rv1936-1941) is Mycobacterium marinum and M. tuberculosis specific, which can withstand reactive oxygen species (ROS) and reactive nitrogen species (RNS) induced stress. A library of over a million compounds was screened using in silico virtual ligand screening (VLS) to identify inhibitors against the modeled structure of MelF protein expressed by melF of mel2 locus so that M. marinum’s ability to withstand ROS/RNS stress could be reduced. The top ranked 1000 compounds were further screened to identify 178 compounds to maximize the scaffold diversity by manually evaluating the interaction of each compound with the target site. M. marinum melF was cloned, expressed and purified as maltose binding protein (MBP)-tagged recombinant protein in Escherichia coli. After establishing the flavin dependent oxidoreductase activity of MelF (~ 84 kDa), the inhibitors were screened for the inhibition of enzyme activity of whole cell lysate (WCL) and the purified MelF. Amongst these, 16 compounds could significantly inhibit the enzyme activity of purified MelF. For the six best inhibitory compounds, the minimal inhibitory concentration (MIC) was determined to be 3.4–19.4 μM and 13.5–38.8 μM for M. marinum and M. tuberculosis, respectively. Similarly, the minimal bactericidal concentration (MBC) was determined to be 6.8–38.8 μM and 27–38.8 μM against M. marinum and M. tuberculosis, respectively. One compound each in combination with isoniazid (INH) also showed synergistic inhibitory effect against M. marinum and M. tuberculosis with no cytotoxicity in HeLa cells. Interestingly, these inhibitors did not display any non-specific protein-structure destabilizing effect. Such inhibitors targeting the anti-ROS/RNS machinery may facilitate the efficient killing of replicating and nonreplicating mycobacteria inside the host cells.

Pocket detection and interaction-weighted ligand-similarity search yields novel high-affinity binders for Myocilin-OLF, a protein implicated in glaucoma

Traditional structure and ligand based virtual screening approaches rely on the availability of structural and ligand binding information. To overcome this limitation, hybrid approaches were developed that relied on extraction of ligand binding information from proteins sharing similar folds and hence, evolutionarily relationship. However, they cannot target a chosen pocket in a protein. To address this, a pocket centric virtual ligand screening approach is required. Here, we employ a new, iterative implementation of a pocket and ligand-similarity based approach to virtual ligand screening to predict small molecule binders for the olfactomedin domain of human myocilin implicated in glaucoma. Small-molecule binders of the protein might prevent the aggregation of the protein, commonly seen during glaucoma. First round experimental assessment of the predictions using differential scanning fluorimetry with myoc-OLF yielded 7 hits with a success rate of 12.7%; the best hit had an apparent dissociation constant of 99nM. By matching to the key functional groups of the best ligand that were likely involved in binding, the affinity of the best hit was improved by almost 10,000 fold from the high nanomolar to the low picomolar range. Thus, this study provides preliminary validation of the methodology on a medically important glaucoma associated protein.