Exploring Binding Pockets in the Conformational States of the SARS-CoV-2 Spike Trimers for the Screening of Allosteric Inhibitors Using Molecular Simulations and Ensemble-Based Ligand Docking.

Understanding mechanisms of allosteric regulation remains elusive for the SARS-CoV-2 spike protein, despite the increasing interest and effort in discovering allosteric inhibitors of the viral activity and interactions with the host receptor ACE2. The challenges of discovering allosteric modulators of the SARS-CoV-2 spike proteins are associated with the diversity of cryptic allosteric sites and complex molecular mechanisms that can be employed by allosteric ligands, including the alteration of the conformational equilibrium of spike protein and preferential stabilization of specific functional states. In the current study, we combine conformational dynamics analysis of distinct forms of the full-length spike protein trimers and machine-learning-based binding pocket detection with the ensemble-based ligand docking and binding free energy analysis to characterize the potential allosteric binding sites and determine structural and energetic determinants of allosteric inhibition for a series of experimentally validated allosteric molecules. The results demonstrate a good agreement between computational and experimental binding affinities, providing support to the predicted binding modes and suggesting key interactions formed by the allosteric ligands to elicit the experimentally observed inhibition. We establish structural and energetic determinants of allosteric binding for the experimentally known allosteric molecules, indicating a potential mechanism of allosteric modulation by targeting the hinges of the inter-protomer movements and blocking conformational changes between the closed and open spike trimer forms. The results of this study demonstrate that combining ensemble-based ligand docking with conformational states of spike protein and rigorous binding energy analysis enables robust characterization of the ligand binding modes, the identification of allosteric binding hotspots, and the prediction of binding affinities for validated allosteric modulators, which is consistent with the experimental data. This study suggested that the conformational adaptability of the protein allosteric sites and the diversity of ligand bound conformations are both in play to enable efficient targeting of allosteric binding sites and interfere with the conformational changes.

Inhibition of Neutral Sphingomyelinase 2 by Novel Small Molecule Inhibitors Results in Decreased Release of Extracellular Vesicles by Vascular Smooth Muscle Cells and Attenuated Calcification.

Vascular calcification (VC) is an important contributor and prognostic factor in the pathogenesis of cardiovascular diseases. VC is an active process mediated by the release of extracellular vesicles by vascular smooth muscle cells (VSMCs), and the enzyme neutral sphingomyelinase 2 (nSMase2 or SMPD3) plays a key role. Upon activation, the enzyme catalyzes the hydrolysis of sphingomyelin, thereby generating ceramide and phosphocholine. This conversion mediates the release of exosomes, a type of extracellular vesicles (EVs), which ultimately forms the nidus for VC. nSMase2 therefore represents a drug target, the inhibition of which is thought to prevent or halt VC progression. In search of novel druglike small molecule inhibitors of nSMase2, we have used virtual ligand screening to identify potential ligands. From an in-silico collection of 48,6844 small druglike molecules, we selected 996 compounds after application of an in-house multi-step procedure combining different filtering and docking procedures. Selected compounds were functionally tested in vitro; from this, we identified 52 individual hit molecules that inhibited nSMase2 activity by more than 20% at a concentration of 150 µM. Further analysis showed that five compounds presented with IC50s lower than 2 µM. Of these, compounds ID 5728450 and ID 4011505 decreased human primary VSMC EV release and calcification in vitro. The hit molecules identified here represent new classes of nSMase2 inhibitors that may be developed into lead molecules for the therapeutic or prophylactic treatment of VC.

Identification of antiparasitic drug targets using a multi-omics workflow in the acanthocephalan model.

BACKGROUND: With the expansion of animal production, parasitic helminths are gaining increasing economic importance. However, application of several established deworming agents can harm treated hosts and environment due to their low specificity. Furthermore, the number of parasite strains showing resistance is growing, while hardly any new anthelminthics are being developed. Here, we present a bioinformatics workflow designed to reduce the time and cost in the development of new strategies against parasites. The workflow includes quantitative transcriptomics and proteomics, 3D structure modeling, binding site prediction, and virtual ligand screening. Its use is demonstrated for Acanthocephala (thorny-headed worms) which are an emerging pest in fish aquaculture. We included three acanthocephalans (Pomphorhynchus laevis, Neoechinorhynchus agilis, Neoechinorhynchus buttnerae) from four fish species (common barbel, European eel, thinlip mullet, tambaqui). RESULTS: The workflow led to eleven highly specific candidate targets in acanthocephalans. The candidate targets showed constant and elevated transcript abundances across definitive and accidental hosts, suggestive of constitutive expression and functional importance. Hence, the impairment of the corresponding proteins should enable specific and effective killing of acanthocephalans. Candidate targets were also highly abundant in the acanthocephalan body wall, through which these gutless parasites take up nutrients. Thus, the candidate targets are likely to be accessible to compounds that are orally administered to fish. Virtual ligand screening led to ten compounds, of which five appeared to be especially promising according to ADMET, GHS, and RO5 criteria: tadalafil, pranazepide, piketoprofen, heliomycin, and the nematicide derquantel. CONCLUSIONS: The combination of genomics, transcriptomics, and proteomics led to a broadly applicable procedure for the cost- and time-saving identification of candidate target proteins in parasites. The ligands predicted to bind can now be further evaluated for their suitability in the control of acanthocephalans. The workflow has been deposited at the Galaxy workflow server under the URL tinyurl.com/yx72rda7 .

Structural Characterization of KOR Inactive and Active States for 3D Pharmacology and Drug Discovery.

The structure of the human kappa opioid receptor (KOR) in complex with the long-acting antagonist JDTic was solved crystallographically in 2012 and, along with structures of other opioid receptors, revolutionized our understanding of opioid system function and pharmacology. More recently, active state KOR structure was also determined, giving important insights into activation mechanisms of the receptor. In this review, we will discuss how the understanding of atomistic structures of KOR established a key platform for deciphering details of subtype and functional selectivity of KOR-targeting ligands and for discovery of new chemical probes with potentially beneficial pharmacological profiles.

Machine Learning Assisted Approach for Finding Novel High Activity Agonists of Human Ectopic Olfactory Receptors.

Olfactory receptors (ORs) constitute the largest superfamily of G protein-coupled receptors (GPCRs). ORs are involved in sensing odorants as well as in other ectopic roles in non-nasal tissues. Matching of an enormous number of the olfactory stimulation repertoire to its counterpart OR through machine learning (ML) will enable understanding of olfactory system, receptor characterization, and exploitation of their therapeutic potential. In the current study, we have selected two broadly tuned ectopic human OR proteins, OR1A1 and OR2W1, for expanding their known chemical space by using molecular descriptors. We present a scheme for selecting the optimal features required to train an ML-based model, based on which we selected the random forest (RF) as the best performer. High activity agonist prediction involved screening five databases comprising ~23 M compounds, using the trained RF classifier. To evaluate the effectiveness of the machine learning based virtual screening and check receptor binding site compatibility, we used docking of the top target ligands to carefully develop receptor model structures. Finally, experimental validation of selected compounds with significant docking scores through in vitro assays revealed two high activity novel agonists for OR1A1 and one for OR2W1.

Structure based discovery of novel hexokinase 2 inhibitors.

Hexokinase 2 (HK2) is over-expressed in most of human cancers and has been proved to be a promising target for cancer therapy. In this study, based on the structure of HK2, we screened over 6 millions of compounds to obtain the lead. A total of 26 (E)-N'-(2,3,4-trihydroxybenzylidene) arylhydrazide derivatives were then designed, synthesized, and evaluated for their HK2 enzyme activity and IC50 values against two cancer cell lines. Most of the 26 target compounds showed excellently in vitro activity. Among them, compound 3j showed the strongest inhibitory effects on HK2 enzyme activity with an IC50 of 0.53 ± 0.13 µM and exhibited the most potent growth inhibition against SW480 cells with an IC50 of 7.13 ± 1.12 µM, which deserves further studies.

Chemical space of Escherichia coli dihydrofolate reductase inhibitors: New approaches for discovering novel drugs for old bugs.

Escherichia coli Dihydrofolate reductase is an important enzyme that is essential for the survival of the Gram-negative microorganism. Inhibitors designed against this enzyme have demonstrated application as antibiotics. However, either because of poor bioavailability of the small-molecules resulting from their inability to cross the double membrane in Gram-negative bacteria or because the microorganism develops resistance to the antibiotics by mutating the DHFR target, discovery of new antibiotics against the enzyme is mandatory to overcome drug-resistance. This review summarizes the field of DHFR inhibition with special focus on recent efforts to effectively interface computational and experimental efforts to discover novel classes of inhibitors that target allosteric and active-sites in drug-resistant variants of EcDHFR.

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-ß-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.

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.

[In silico Search for Tubulin Polymerization Inhibitors].

Cytostatic colchicine is widely used in the treatment of Familial Mediterranean fever, but it has several side effects. For finding new, more effective drugs with higher affinity and diminishside effects we carried out virtual screening of potential inhibitors of the main target of colchicine, the polymerization of tubulin by evaluating affinity 25745 compounds, structurally related to the colchicine. We have identified 11 commercially available compounds with higher affinity to tubulin. Compounds with highest binding scores include trimethoxybenzene and its derivatives; these compounds bind to the same site in similar orientation. Information provided can form the basis for design of new cytostatics.

Physapubescin, a natural withanolide as a kidney-type glutaminase (KGA) inhibitor.

Kidney-type glutaminase (KGA) is over expressed in many kinds of cancers that converts glutamine to glutamate for supplying energy, and has become an object for targeted cancer therapy. The structure-based virtual ligand screening identified physapubescin, a withanolide purified from Physalis pubescens L., as a possible inhibitor of KGA with low binding energy. Enzyme inhibition experiments and cell-based assays further confirmed its inhibitory effects on KGA activity, suggesting potential applications of physapubescin and its derivatives as KGA inhibitors.

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.

A bitter pill for type 2 diabetes? The activation of bitter taste receptor TAS2R38 can stimulate GLP-1 release from enteroendocrine L-cells.

The bitter taste receptor TAS2R38 is a G protein coupled receptor (GPCR) that has been found in many extra-oral locations like the gastrointestinal (GI) system, respiratory system, and brain, though its function at these locations is only beginning to be understood. To probe the receptor's potential metabolic role, immunohistochemistry of human ileum tissues was performed, which showed that the receptor was co-localized with glucagon-like peptide 1 (GLP-1) in L-cells. In a previous study, we had modeled the structure of this receptor for its many taste-variant haplotypes (Tan et al. 2011), including the taster haplotype PAV. The structure of this haplotype was then used in a virtual ligand screening pipeline using a collection of ∼2.5 million purchasable molecules from the ZINC database. Three compounds (Z7, Z3, Z1) were purchased from the top hits and tested along with PTU (known TAS2R38 agonist) in in vitro and in vivo assays. The dose-response study of the effect of PTU and Z7 on GLP-1 release using wild-type and TAS2R38 knockout HuTu-80 cells showed that the receptor TAS2R38 plays a major role in GLP-1 release due to these molecules. In vivo studies of PTU and the three compounds showed that they each increase GLP-1 release. PTU was also chemical linked to cellulose to slow its absorption and when tested in vivo, it showed an enhanced and prolonged GLP-1 release. These results suggest that the GI lumen location of TAS2R38 on the L-cell makes it a relatively safe drug target as systemic absorption is not needed for a TAS2R38 agonist drug to effect GLP-1 release.

Novel small molecule binders of human N-glycanase 1, a key player in the endoplasmic reticulum associated degradation pathway.

Peptide:N-glycanase (NGLY1) is an enzyme responsible for cleaving oligosaccharide moieties from misfolded glycoproteins to enable their proper degradation. Deletion and truncation mutations in this gene are responsible for an inherited disorder of the endoplasmic reticulum-associated degradation pathway. However, the literature is unclear whether the disorder is a result of mutations leading to loss-of-function, loss of substrate specificity, loss of protein stability or a combination of these factors. In this communication, without burdening ourselves with the mechanistic underpinning of disease causation because of mutations on the NGLY1 protein, we demonstrate the successful application of virtual ligand screening (VLS) combined with experimental high-throughput validation to the discovery of novel small-molecules that show binding to the transglutaminase domain of NGLY1. Attempts at recombinant expression and purification of six different constructs led to successful expression of five, with three constructs purified to homogeneity. Most mutant variants failed to purify possibly because of misfolding and the resultant exposure of surface hydrophobicity that led to protein aggregation. For the purified constructs, our threading/structure-based VLS algorithm, FINDSITE(comb), was employed to predict ligands that may bind to the protein. Then, the predictions were assessed by high-throughput differential scanning fluorimetry. This led to the identification of nine different ligands that bind to the protein of interest and provide clues to the nature of pharmacophore that facilitates binding. This is the first study that has identified novel ligands that bind to the NGLY1 protein as a possible starting point in the discovery of ligands with potential therapeutic applications in the treatment of the disorder caused by NGLY1 mutants.

Implications of the small number of distinct ligand binding pockets in proteins for drug discovery, evolution and biochemical function.

Coincidence of the properties of ligand binding pockets in native proteins with those in proteins generated by computer simulations without selection for function shows that pockets are a generic protein feature and the number of distinct pockets is small. Similar pockets occur in unrelated protein structures, an observation successfully employed in pocket-based virtual ligand screening. The small number of pockets suggests that off-target interactions among diverse proteins are inherent; kinases, proteases and phosphatases show this prototypical behavior. The ability to repurpose FDA approved drugs is general, and minor side effects cannot be avoided. Finally, the implications to drug discovery are explored.

FRAGSITE2: A structure and fragment-based approach for virtual ligand screening.

Protein function annotation and drug discovery often involve finding small molecule binders. In the early stages of drug discovery, virtual ligand screening (VLS) is frequently applied to identify possible hits before experimental testing. While our recent ligand homology modeling (LHM)-machine learning VLS method FRAGSITE outperformed approaches that combined traditional docking to generate protein-ligand poses and deep learning scoring functions to rank ligands, a more robust approach that could identify a more diverse set of binding ligands is needed. Here, we describe FRAGSITE2 that shows significant improvement on protein targets lacking known small molecule binders and no confident LHM identified template ligands when benchmarked on two commonly used VLS datasets: For both the DUD-E set and DEKOIS2.0 set and ligands having a Tanimoto coefficient (TC) < 0.7 to the template ligands, the 1% enrichment factor (EF1% ) of FRAGSITE2 is significantly better than those for FINDSITEcomb2.0 , an earlier LHM algorithm. For the DUD-E set, FRAGSITE2 also shows better ROC enrichment factor and AUPR (area under the precision-recall curve) than the deep learning DenseFS scoring function. Comparison with the RF-score-VS on the 76 target subset of DEKOIS2.0 and a TC < 0.99 to training DUD-E ligands, FRAGSITE2 has double the EF1% . Its boosted tree regression method provides for more robust performance than a deep learning multiple layer perceptron method. When compared with the pretrained language model for protein target features, FRAGSITE2 also shows much better performance. Thus, FRAGSITE2 is a promising approach that can discover novel hits for protein targets. FRAGSITE2's web service is freely available to academic users at http://sites.gatech.edu/cssb/FRAGSITE2.

Structure-based discovery of a novel small-molecule inhibitor of TEAD palmitoylation with anticancer activity.

The paralogous oncogenic transcriptional coactivators YAP and TAZ are the distal effectors of the Hippo signaling pathway, which plays a critical role in cell proliferation, survival and cell fate specification. They are frequently deregulated in most human cancers, where they contribute to multiple aspects of tumorigenesis including growth, metabolism, metastasis and chemo/immunotherapy resistance. Thus, they provide a critical point for therapeutic intervention. However, due to their intrinsically disordered structure, they are challenging to target directly. Since YAP/TAZ exerts oncogenic activity by associating with the TEAD1-4 transcription factors, to regulate target gene expression, YAP activity can be controlled indirectly by regulating TEAD1-4. Interestingly, TEADs undergo autopalmitoylation, which is essential for their stability and function, and small-molecule inhibitors that prevent this posttranslational modification can render them unstable. In this article we report discovery of a novel small molecule inhibitor of YAP activity. We combined structure-based virtual ligand screening with biochemical and cell biological studies and identified JM7, which inhibits YAP transcriptional reporter activity with an IC50 of 972 nMoles/Ltr. Further, it inhibits YAP target gene expression, without affecting YAP/TEAD localization. Mechanistically, JM7 inhibits TEAD palmitoylation and renders them unstable. Cellular thermal shift assay revealed that JM7 directly binds to TEAD1-4 in cells. Consistent with the inhibitory effect of JM7 on YAP activity, it significantly impairs proliferation, colony-formation and migration of mesothelioma (NCI-H226), breast (MDA-MB-231) and ovarian (OVCAR-8) cancer cells that exhibit increased YAP activity. Collectively, these results establish JM7 as a novel lead compound for development of more potent inhibitors of TEAD palmitoylation for treating cancer.

Phytochemical Profile, In Vitro Bioactivity Evaluation, In Silico Molecular Docking and ADMET Study of Essential Oils of Three Vitex Species Grown in Tarai Region of Uttarakhand.

A comparative study of volatiles, antioxidant activity, phytotoxic activity, as well as in silico molecular docking and ADMET study, was conducted for essential oils from three Vitex species, viz., V. agnus-castus, V. negundo, and V. trifolia. Essential oils (OEs) extracted by hydrodistillation were subjected to compositional analysis using GC-MS. A total number of 37, 45, and 43 components were identified in V. agnus-castus, V. negundo, and V. trifolia, respectively. The antioxidant activity of EOs, assessed using different radical-scavenging (DPPH, H2O2 and NO), reducing power, and metal chelating assays, were found to be significant as compared with those of the standards. The phytotoxic potential of the EOs was performed in the receptor species Raphanusraphanistrum (wild radish) and the EOs showed different levels of intensity of seed germination inhibition and root and shoot length inhibition. The molecular docking study was conducted to screen the antioxidant and phytotoxic activity of the major and potent compounds against human protein target, peroxiredoxin 5, and 4-hydroxyphenylpyruvate dioxygenase protein (HPPD). Results showed good binding affinities and attributed the strongest inhibitory activity to 13-epi-manoyl oxide for both the target proteins.

Structure-Based Virtual Screening of Ultra-Large Library Yields Potent Antagonists for a Lipid GPCR.

Cysteinyl leukotriene G protein-coupled receptors, CysLT1R and CysLT2R, regulate bronchoconstrictive and pro-inflammatory effects and play a key role in allergic disorders, cardiovascular diseases, and cancer. CysLT1R antagonists have been widely used to treat asthma disorders, while CysLT2R is a potential target against uveal melanoma. However, very few selective antagonist chemotypes for CysLT receptors are available, and the design of such ligands has proved to be challenging. To overcome this obstacle, we took advantage of recently solved crystal structures of CysLT receptors and an ultra-large Enamine REAL library, representing a chemical space of 680 M readily available compounds. Virtual ligand screening employed 4D docking models comprising crystal structures of CysLT1R and CysLT2R and their corresponding ligand-optimized models. Functional assessment of the candidate hits yielded discovery of five novel antagonist chemotypes with sub-micromolar potencies and the best Ki = 220 nM at CysLT1R. One of the hits showed inverse agonism at the L129Q constitutively active mutant of CysLT2R, with potential utility against uveal melanoma.

Structure-based discovery of potent and selective melatonin receptor agonists.

Melatonin receptors MT1 and MT2 are involved in synchronizing circadian rhythms and are important targets for treating sleep and mood disorders, type-2 diabetes and cancer. Here, we performed large scale structure-based virtual screening for new ligand chemotypes using recently solved high-resolution 3D crystal structures of agonist-bound MT receptors. Experimental testing of 62 screening candidates yielded the discovery of 10 new agonist chemotypes with sub-micromolar potency at MT receptors, with compound 21 reaching EC50 of 0.36 nM. Six of these molecules displayed selectivity for MT2 over MT1. Moreover, two most potent agonists, including 21 and a close derivative of melatonin, 28, had dramatically reduced arrestin recruitment at MT2, while compound 37 was devoid of Gi signaling at MT1, implying biased signaling. This study validates the suitability of the agonist-bound orthosteric pocket in the MT receptor structures for the structure-based discovery of selective agonists.