Target-based Virtual Screening Research Articles

Network pharmacology speaking to ethnopharmacology: new data on an ancient remedy

Network pharmacology as a “green approach”, predicting metabolite behaviours chemically and biologically and guid¬ing biological experimental design, is a new strategy aiming to uncover the mechanism of action of natural products as drug candidates. It provides a powerful way to identify novel mechanisms of natural products with potential thera¬peutic effects. This approach has emerged as a powerful tool to overcome the limitations of traditional methods, such as the ability to predict the adverse effects of a drug and the likelihood of failure during clinical trials, by applying systems biology principles to the field of pharmacology. This method combines the multi-omics dataset, computer modeling, and chemical biology so as to reveal pharmaceutical actions and guide drug discovery. Therefore, computer-aided drug design combined with network pharmacology can be viewed as a novel in silico screening ap¬proach to drug discovery, by utilising chemoinformatics, bioinformatics, structure biology, and chemical biology. This strategy includes target-based virtual screening - molecular docking, ligand similarity-based virtual screening, and inverse screening (Inver-dock), providing a powerful tool for target identification of drug candidates, multitarget dis¬covery, and natural bioactive product profiling. It can also be used for selectivity profiling of drugs, drug repositioning, safety profiling, and metabolism profiling prediction (ADMET).

Liensinine, a Novel and Food-Derived Compound, Exerts Potent Antihepatoma Efficacy via Inhibiting the Kv10.1 Channel.

Plant metabolites from natural product extracts offer unique advantages against carcinogenesis in the development of drugs. The target-based virtual screening from food-derived compounds represents a promising approach for tumor therapy. In this study, we performed virtual screening to target the presumed inhibitor-binding pocket and identified a highly potent Kv10.1 inhibitor, liensinine (Lien), which can inhibit the channel in a dose-dependent way with an IC50 of 0.24 ± 0.07 μM. Combining molecular dynamics simulations with mutagenesis experiments, our data show that Lien interacts with Kv10.1 by binding with Y539, T543, D551, E553, and H601 in the C-linker domain of Kv10.1. In addition, the interaction of sequence alignment and 3D structural modeling revealed differences between the C-linker domain of the Kv10.1 channel and the Kv11.1 channel. Furthermore, antitumor experiments revealed that Lien suppresses the proliferation and migration of HCC both in vitro and in vivo. In summary, the food-derived compound, Lien, may serve as a lead compound for antihepatoma therapeutic drugs targeting Kv10.1.

Virtual screening of flavonoids as potential RIPK1 inhibitors for neurodegeneration therapy.

Global prevalence of neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease is increasing gradually, whereas approvals of successful therapeutics for central nervous system disorders are inadequate. Accumulating evidence suggests pivotal roles of the receptor-interacting serine/threonine-protein kinase 1 (RIPK1) in modulating neuroinflammation and necroptosis. Discoveries of potent small molecule inhibitors for RIPK1 with favorable pharmacokinetic properties could thus address the unmet medical needs in treating neurodegeneration. In a structure-based virtual screening, we performed site-specific molecular docking of 4,858 flavonoids against the kinase domain of RIPK1 using AutoDock Vina. We predicted physicochemical descriptors of the top ligands using the SwissADME webserver. Binding interactions of the best ligands and the reference ligand L8D were validated using replicated 500-ns Gromacs molecular dynamics simulations and free energy calculations. From Vina docking, we shortlisted the top 20 flavonoids with the highest binding affinities, ranging from -11.7 to -10.6 kcal/mol. Pharmacokinetic profiling narrowed down the list to three orally bioavailable and blood-brain-barrier penetrant flavonoids: Nitiducarpin, Pinocembrin 7-O-benzoate, and Paratocarpin J. Next, trajectories of molecular dynamics simulations of the top protein-ligand complexes were analyzed for binding interactions. The root-mean-square deviation (RMSD) was 1.191 Å (±0.498 Å), 1.725 Å (±0.828 Å), 1.923 Å (±0.942 Å), 0.972 Å (±0.155 Å) for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D, respectively. The radius of gyration (Rg) was 2.034 nm (±0.015 nm), 2.0.39 nm (± 0.025 nm), 2.053 nm (±0.021 nm), 2.037 nm (±0.016 nm) for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D, respectively. The solvent accessible surface area (SASA) was 159.477 nm2 (±3.021 nm2), 159.661 nm2 (± 3.707 nm2), 160.755 nm2 (±4.252 nm2), 156.630 nm2 (±3.521 nm2), for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D complexes, respectively. Therefore, lower RMSD, Rg, and SASA values demonstrated that Nitiducarpin formed the most stable complex with the target protein among the best three ligands. Finally, 2D protein-ligand interaction analysis revealed persistent hydrophobic interactions of Nitiducarpin with the critical residues of RIPK1, including the catalytic triads and the activation loop residues, implicated in the kinase activity and ligand binding. Our target-based virtual screening identified three flavonoids as strong RIPK1 inhibitors, with Nitiducarpin exhibiting the most potent inhibitory potential. Future in vitro and in vivo studies with these ligands could offer new hope for developing effective therapeutics and improving the quality of life for individuals affected by neurodegeneration.

Synergistic inhibition of glioblastoma multiforme through an in-silico analysis of luteolin and ferulic acid derived from Angelica sinensis and Cannabis sativa: Advancements in computational therapeutics.

The primary objective of this study is to uncover novel therapeutic agents for the treatment of Glioblastoma Multiforme (GBM), a highly aggressive form of brain cancer, and Alzheimer's Disease (AD). Given the complexity and resistance associated with both conditions, the study underscores the imperative need for therapeutic alternatives that can traverse the biological intricacies inherent in both neuro-oncological and neurodegenerative disorders. To achieve this, a meticulous, target-based virtual screening was employed on an ensemble of 50 flavonoids and polyphenol derivatives primarily derived from plant sources. The screening focused predominantly on molecular targets pertinent to GBM but also evaluated the potential overlap with neural pathways involved in AD. The study utilized molecular docking and Molecular Dynamic (MD) simulation techniques to analyze the interaction of these compounds with a key biological target, protein tyrosine phosphatase receptor-type Z (PTPRZ). Out of the 50 compounds examined, 10 met our stringent criteria for binding affinity and specificity. Subsequently, the highest value of binding energy was observed for the synergistic binding of luteolin and ferulic acid with the value of -10.5 kcal/mol. Both compounds exhibited inherent neuroprotective properties and demonstrated significant potential as pathway inhibitors in GBM as well as molecular modulators in AD. Drawing upon advanced in-silico cytotoxicity predictions and sophisticated molecular modeling techniques, this study casts a spotlight on the therapeutic capabilities of polyphenols against GBM. Furthermore, our findings suggest that leveraging these compounds could catalyze a much-needed paradigm shift towards more integrative therapeutic approaches that span the breadth of both neuro-oncology and neurodegenerative diseases. The identification of cross-therapeutic potential in flavonoids and polyphenols could drastically broaden the scope of treatment modalities against both fatal diseases.

Autochthonous Peruvian Natural Plants as Potential SARS-CoV-2 Mpro Main Protease Inhibitors.

Over 750 million cases of COVID-19, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), have been reported since the onset of the global outbreak. The need for effective treatments has spurred intensive research for therapeutic agents based on pharmaceutical repositioning or natural products. In light of prior studies asserting the bioactivity of natural compounds of the autochthonous Peruvian flora, the present study focuses on the identification SARS-CoV-2 Mpro main protease dimer inhibitors. To this end, a target-based virtual screening was performed over a representative set of Peruvian flora-derived natural compounds. The best poses obtained from the ensemble molecular docking process were selected. These structures were subjected to extensive molecular dynamics steps for the computation of binding free energies along the trajectory and evaluation of the stability of the complexes. The compounds exhibiting the best free energy behaviors were selected for in vitro testing, confirming the inhibitory activity of Hyperoside against Mpro, with a Ki value lower than 20 µM, presumably through allosteric modulation.

A combined ligand and target-based virtual screening strategy to repurpose drugs as putrescine uptake inhibitors with trypanocidal activity.

Chagas disease, also known as American trypanosomiasis, is a neglected tropical disease caused by the protozoa Trypanosoma cruzi, affecting nearly 7million people only in the Americas. Polyamines are essential compounds for parasite growth, survival, and differentiation. However, because trypanosomatids are auxotrophic for polyamines, they must be obtained from the host by specific transporters. In this investigation, an ensemble of QSAR classifiers able to identify polyamine analogs with trypanocidal activity was developed. Then, a multi-template homology model of the dimeric polyamine transporter of T. cruzi, TcPAT12, was created with Rosetta, and then refined by enhanced sampling molecular dynamics simulations. Using representative snapshots extracted from the trajectory, a docking model able to discriminate between active and inactive compounds was developed and validated. Both models were applied in a parallel virtual screening campaign to repurpose known drugs as anti-trypanosomal compounds inhibiting polyamine transport in T. cruzi. Montelukast, Quinestrol, Danazol, and Dutasteride were selected for in vitro testing, and all of them inhibited putrescine uptake in biochemical assays, confirming the predictive ability of the computational models. Furthermore, all the confirmed hits proved to inhibit epimastigote proliferation, and Quinestrol and Danazol were able to inhibit, in the low micromolar range, the viability of trypomastigotes and the intracellular growth of amastigotes.

Target-Based Virtual and Biochemical Screening Against HMG-CoA Reductase Reveals Allium sativum-Derived Organosulfur Compound N-Acetyl Cysteine as a Cardioprotective Agent

Target-Based Virtual and Biochemical Screening Against HMG-CoA Reductase Reveals Allium sativum-Derived Organosulfur Compound N-Acetyl Cysteine as a Cardioprotective Agent

Discovery of New Zika Protease and Polymerase Inhibitors through the Open Science Collaboration Project OpenZika.

The Zika virus (ZIKV) is a neurotropic arbovirus considered a global threat to public health. Although there have been several efforts in drug discovery projects for ZIKV in recent years, there are still no antiviral drugs approved to date. Here, we describe the results of a global collaborative crowdsourced open science project, the OpenZika project, from IBM's World Community Grid (WCG), which integrates different computational and experimental strategies for advancing a drug candidate for ZIKV. Initially, molecular docking protocols were developed to identify potential inhibitors of ZIKV NS5 RNA-dependent RNA polymerase (NS5 RdRp), NS3 protease (NS2B-NS3pro), and NS3 helicase (NS3hel). Then, a machine learning (ML) model was built to distinguish active vs inactive compounds for the cytoprotective effect against ZIKV infection. We performed three independent target-based virtual screening campaigns (NS5 RdRp, NS2B-NS3pro, and NS3hel), followed by predictions by the ML model and other filters, and prioritized a total of 61 compounds for further testing in enzymatic and phenotypic assays. This yielded five non-nucleoside compounds which showed inhibitory activity against ZIKV NS5 RdRp in enzymatic assays (IC50 range from 0.61 to 17 μM). Two compounds thermally destabilized NS3hel and showed binding affinity in the micromolar range (Kd range from 9 to 35 μM). Moreover, the compounds LabMol-301 inhibited both NS5 RdRp and NS2B-NS3pro (IC50 of 0.8 and 7.4 μM, respectively) and LabMol-212 thermally destabilized the ZIKV NS3hel (Kd of 35 μM). Both also protected cells from death induced by ZIKV infection in in vitro cell-based assays. However, while eight compounds (including LabMol-301 and LabMol-212) showed a cytoprotective effect and prevented ZIKV-induced cell death, agreeing with our ML model for prediction of this cytoprotective effect, no compound showed a direct antiviral effect against ZIKV. Thus, the new scaffolds discovered here are promising hits for future structural optimization and for advancing the discovery of further drug candidates for ZIKV. Furthermore, this work has demonstrated the importance of the integration of computational and experimental approaches, as well as the potential of large-scale collaborative networks to advance drug discovery projects for neglected diseases and emerging viruses, despite the lack of available direct antiviral activity and cytoprotective effect data, that reflects on the assertiveness of the computational predictions. The importance of these efforts rests with the need to be prepared for future viral epidemic and pandemic outbreaks.

Target-based virtual screening and molecular interaction studies for lead identification of natural olive compounds against glioblastoma multiforme.

Glioblastoma multiforme, a rare traumatic brain disorder, is at the research climax for its uncontrolled growth leading to a catastrophic outcome. Throwing light on the target-based virtual screening of drugs using natural phytocompounds is a striking cornerstone in glioblastoma-based drug discovery, accelerating with leaps and bounds. This project aims to develop promising lead compounds against glioblastoma brain cancer using OliveNet™, an open-source database. In this pursuit, our rationale for selecting molecules was based on their capability to pass through the blood-brain barrier. Out of 51 derivative molecules from flavonoids and polyphenols, 17 molecules were screened out bearing the best ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties, alongside fulfilling our rationale of lead selection. Two polyphenols, 3,4,5-trimethoxybenzoic acid and 4-ethyl guaiacol, have binding affinity for the antioxidant flavonoid luteolin of -5.1 and -4.3 kcal/mol, respectively. According to docking studies, the residues ASN1960, ASN1966, ASN1960, PHE1984, TYR1896, VAL1911, and LYS1966 make both polar and nonpolar interactions with 3,4,5-trimethoxybenzoic acid and 4-ethylguanidine, respectively. LD50 values of toxicity screening using TOX Pro brought to limelight the excellent safety profile of polyphenols and flavonoids. Furthermore, studies using in silico cytotoxicity prediction and molecular modelling have decisively shown that these polyphenols are likely to be effective brain cancer inhibitors and promising future lead candidates against glioblastoma multiforme.

Uncovering Streptomyces-Derived Compounds as Cosmeceuticals for the Development of Improved Skin Photoprotection Products: An In Silico Approach to Explore Multi-Targeted Agents

The search for novel photoprotective substances has become a challenge in cosmeceutical research. Streptomyces-derived compounds can serve as a promising source of photoprotective agents to formulate skin photoprotection products, such as sunscreens. This study aimed to identify specialized metabolites with the potential to modulate UV-induced cellular damage in the skin by identifying potential multi-target-directed ligands. Using a combination of ligand- and target-based virtual screening approaches, a public compound library comprising 6524 Streptomyces-derived specialized metabolites was studied for their photoprotective capability. The compounds were initially filtered by safety features and then examined for their ability to interact with key targets in the photodamage pathway by molecular docking. A set of 50 commercially available UV filters was used as the benchmark. The protein–ligand stability of selected Streptomyces-derived compounds was also studied by molecular dynamics (MD) simulations. From the compound library, 1981 compounds were found to meet the safety criteria for topically applied products, such as low skin permeability and low or non-toxicity-alerting substructures. A total of 34 compounds had promising binding scores against crucial targets involved in UV-induced photodamage, such as serotonin-receptor subtype 5-HT2A, platelet-activating factor receptor, IL-1 receptor type 1, epidermal growth factor receptor, and cyclooxygenase-2. Among these compounds, aspergilazine A and phaeochromycin F showed the highest ranked interactions with four of the five targets and triggered complex stabilization over time. Additionally, the predicted UV-absorbing profiles also suggest a UV-filtering effect. Streptomyces is an encouraging biological source of compounds for developing topical products. After in silico protein–ligand interactions, binding mode and stabilization of aspergilazine A and phaeochromycin F led to the discovery of potential candidates as photodamage multi-target inhibitors. Therefore, they can be further explored for the formulation of skin photoprotection products.

Target-based virtual screening, computational multiscoring docking and molecular dynamics simulation of small molecules as promising drug candidate affecting kinesin-like protein KIFC1.

The kinesin family member C1 (KIFC1) is an essential protein that facilitates the bipolar division of neoplastic cells. Inhibiting KIFC1 by small molecules is a lucrative strategy to impede bipolar mitosis leading to the apoptosis of cancerous cells. The research aims to envisage small-molecule inhibitors targeting KIFC1. The Mcule database, a comprehensive online digital platform containing more than five million chemical compounds, was used for structure-based virtual screening (SBVS). Druglikeness filtration sifted 2,293,282 chemical hits that further narrowed down to 49 molecules after toxicity profiling. Finally, 39 compounds that comply with the BOILED-Egg permeation predictive model of the ADME rules were carried forward for multiscoring docking using the AutoDock Vina inbuilt to Mcule drug discovery platform, DockThorand SwissDock tools. The mean of ΔG terms produced by docking tools was computed to find consensus top ligand hits. AZ82 exhibited stronger binding (Consensus ΔG: -7.99 kcal mol-1 ) with KIFC1 among reference inhibitors, for example, CW069 (-7.57 kcal mol-1 ) andSR31527 (-7.01 kcal mol-1 ). Ten ligand hits namely, Mcule-4895338547 (Consensus ΔG: -8.69 kcal mol-1 ), Mcule-7035674888 (-8.42 kcal mol-1 ), Mcule-5531166845 (-8.53 kcal mol-1 ), Mcule-3248415882 (-8.55 kcal mol-1 ), Mcule-291881733 (-8.41 kcal mol-1 ), Mcule-5918624394 (-8.44), Mcule-3470115427 (-8.47), Mcule-3686193135 (-8.18 kcal mol-1 ), Mcule-3955355291 (8.09 kcal mol-1 )and Mcule-9534899193 (-8.01 kcal mol-1 ) depicted strong binding interactions with KIFC1 in comparison to potential reference inhibitor AZ82. The top four ligands and AZ82 were considered for molecular dynamics simulation of 50 ns duration. Toxicity profiling, physicochemical properties, lipophilicity, solubility, pharmacokinetics, druglikeness, medicinal chemistry attributes, average potential energy, RMSD, RMSF, SASA, ΔGsolvand Rg analyses forecast the ligand mcule-4895338547 as a promising inhibitor of KIFC1.

Lead Identification against 3C-like Protease of SARS-CoV-2 Via Target-based Virtual Screening and Molecular Dynamics Simulation

Published on:June 2022 Journal of Young Pharmacists, 2022; 14(2):179-186 Original Article | doi:10.5530/jyp.2022.14.34 Authors: Afaf S Alwabli Department of Biological Sciences, Rabigh College of Science and Arts, King Abdulaziz University, Jeddah, SAUDI ARABIA. Abstract: Background: The COVID-19 pandemic has prompted the human population’s emotional, social, and financial loss worldwide and presents an unprecedented challenge to health, food, and working styles. However, the exceptional implication of vaccinations at every nook and corner of the world has been breaking the rate of infection and mortality to a greater extent; in the case of potential oral drugs, we still need to decipher more palliative and therapeutic measures to develop effective antiviral drug candidates. Materials and Methods: The study exploits the structurebased virtual screening (SBVS) approach to identify small molecule inhibitors against 3C-like protease (3CLPRO) of SARS-CoV-2 from more than five million compounds of the MCULE database. Results: Four basic properties viz., molecular weight (≤ 500 g/m), hydrogen bond donor (≤ 5), hydrogen bond acceptor (≤ 10), and logP (≤ 5) as an initial filter were employed in SBVS workflow that extracted 2,235,82 compounds that were subsequently reduced to 22 ligands showing lesser ΔG values than reference drug nirmatrelvir (-7.9 kcal/mol). Upon toxicity check, 10 ligands were obtained that further curtailed to 9 molecules when passed through the BOILED-Egg model of the ADME. Upon compliance of druglikeness other than Lipinski viz., Ghose, Veber, Egan, Muegge, and bioavailability score 7 molecules were shortlisted in which 5 molecules exhibited zero PAINS and Brenk alert. Conclusion: At last, only 1 ligand hit (Mcule-3133395989) was identified that obeyed hydrogen bond selection criterion (ligand-3CLPRO complex ≥ 3 HBs). RMSD, RMSF, SASA, ΔGsolv, Rg, and HBs parameters of MD simulations predict Mcule-3133395989 more stable and promising antiviral agent compared to nirmatrelvir.Key words: 3CLPRO, SARS-CoV-2, SBVS, Nirmatrelvir, MD simulation.

Target-Based Virtual Screening of Natural Compounds Identifies a Potent Antimalarial With Selective Falcipain-2 Inhibitory Activity.

We employed a comprehensive approach of target-based virtual high-throughput screening to find potential hits from the ZINC database of natural compounds against cysteine proteases falcipain-2 and falcipain-3 (FP2 and FP3). Molecular docking studies showed the initial hits showing high binding affinity and specificity toward FP2 were selected. Furthermore, the enzyme inhibition and surface plasmon resonance assays were performed which resulted in a compound ZINC12900664 (ST72) with potent inhibitory effects on purified FP2. ST72 exhibited strong growth inhibition of chloroquine-sensitive (3D7; EC50 = 2.8 µM) and chloroquine-resistant (RKL-9; EC50 = 6.7 µM) strains of Plasmodium falciparum. Stage-specific inhibition assays revealed a delayed and growth defect during parasite growth and development in parasites treated with ST72. Furthermore, ST72 significantly reduced parasite load and increased host survival in a murine model infected with Plasmodium berghei ANKA. No Evans blue staining in ST72 treatment indicated that ST72 mediated protection of blood–brain barrier integrity in mice infected with P. berghei. ST72 did not show any significant hemolysis or cytotoxicity against human HepG2 cells suggesting a good safety profile. Importantly, ST72 with CQ resulted in improved growth inhibitory activity than individual drugs in both in vitro and in vivo studies.

Multitarget-Based Virtual Screening for Identification of Herbal Substances toward Potential Osteoclastic Targets

Osteoporosis is a complex bone disease indicating porous bone with low bone mass density and fragility. Cathepsin K, V-ATPase, and αVβ3 integrin are exhibited as novel targets for osteoporosis treatment. Our preliminary study uses a state-of-the-art method, including target-based virtual screening and clustering methods to determine promising candidates with multitarget properties. Phytochemicals with osteoprotective properties from the literature are used to elucidate the molecular interactions toward three targets. The binding scores of compounds are normalized and rescored. The K-means and hierarchical clustering methods are applied to filter and define the promising compounds, and the silhouette analysis is supposed to validate the clustering method. We explore 108 herbal compounds by virtual screening and the cluster approach, and find that rutin, sagittatoside A, icariin, and kaempferitrin showed strong binding affinities against Cathepsin K, V-ATPase, and αVβ3 integrin. Dockings of candidates toward three targets also provide the protein-ligand interactions and crucial amino acids for binding. Our study provides a straightforward and less time-consuming approach to exploring the new multitarget candidates for further investigations, using a combination of in silico methods.

Target-Based Virtual Screening and LC/MS-Guided Isolation Procedure for Identifying Phloroglucinol-Terpenoid Inhibitors of SARS-CoV-2.

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to more than 5 million deaths worldwide to date. Due to the limited therapeutic options so far available, target-based virtual screening with LC/MS support was applied to identify the novel and high-content compounds 1–4 with inhibitory effects on SARS-CoV-2 in Vero E6 cells from the plant Dryopteris wallichiana. These compounds were also evaluated against SARS-CoV-2 in Calu-3 cells and showed unambiguous inhibitory activity. The inhibition assay of targets showed that compounds 3 and 4 mainly inhibited SARS-CoV-2 3CLpro, with effective Kd values. Through docking and molecular dynamics modeling, the binding site is described, providing a comprehensive understanding of 3CLpro and interactions for 3, including hydrogen bonds, hydrophobic bonds, and the spatial occupation of the B ring. Compounds 3 and 4 represent new, potential lead compounds for the development of anti-SARS-CoV-2 drugs. This study has led to the development of a target-based virtual screening method for exploring the potency of natural products and for identifying natural bioactive compounds for possible COVID-19 treatment.

Identification of potent food constituents as SARS-CoV-2 papain-like protease modulators through advanced pharmacoinformatics approaches

The current ongoing pandemic of COVID-19 urges immediate treatment measures for controlling the highly contagious SARS-CoV-2 infections. The papain-like protease (PLpro), which is released from nsp3, is presently being evaluated as a significant anti-viral drug target for COVID-19 therapy development. Particularly, PLpro is implicated in the cleavage of viral polyproteins and antagonizes the host innate immune response through its deubiquitinating and deISGylating actions, thus making it a high-profile antiviral therapeutic target. The present study reports a few specific food compounds that can bind tightly with the SARS-CoV-2 PLpro protein identified through extensive computational screening techniques. Precisely, extensive advanced computational approaches combining target-based virtual screening, particularly employing sub-structure based similarity search, molecular docking, molecular dynamics (MD) simulations, and MM-GBSA based binding free energy calculations have been employed for the identification of the most promising food compounds with substantial functional implications as SARS-CoV-2 PLpro protein inhibitors/modulators. Observations from the present research investigation also provide a deeper understanding of the binding modes of the proposed four food compounds with SARS-CoV-2 PLpro protein. In docking analyses, all compounds have established essential inter-molecular interaction profiles at the active site cavity of the SARS-CoV-2 PLpro protein. Similarly, the long-range 100 ns conventional MD simulation studies also provided an in-depth understanding of probable interactions and dynamic behaviour of the SARS-CoV-2 PLpro protein-food compound complexes. Binding free energies of all molecular systems revealed a strong interaction affinity of food compounds towards the SARS-CoV-2 PLpro protein. Moreover, clear-cut comparative analyses against the known standard inhibitor also suggest that proposed food compounds may act as potential active chemical entities for modulating the action of the SARS-CoV-2 PLpro protein.

Binary-QSAR guided virtual screening of FDA approved drugs and compounds in clinical investigation against SARS-CoV-2 main protease.

With the emergence of the new SARS-CoV-2 virus, drug repurposing studies have gained substantial importance. Combined with the efficacy of recent improvements in ligand- and target-based virtual screening approaches, virtual screening has become faster and more productive than ever. In the current study, an FDA library of approved drugs and compounds under clinical investigation were screened for their antiviral activity using the antiviral therapeutic activity binary QSAR model of the MetaCore/MetaDrug platform. Among 6733-compound collection, we found 370 compounds with a normalized therapeutic activity value greater than a cutoff of 0.75. Only these selected compounds were used for molecular docking studies against the SARS-CoV-2 main protease (Mpro). After initial short (10 ns) molecular dynamics (MD) simulations with the top-50 docking scored compounds and following molecular mechanics generalized born surface area (MM/GBSA) calculations, top-10 compounds were subjected to longer (100 ns) MD simulations and end-point MM/GBSA estimations. Our virtual screening protocol yielded Cefuroxime pivoxetil, an ester prodrug of second-generation cephalosporin antibiotic Cefuroxime, as being a considerable molecule for drug repurposing against the SARS-CoV-2 Mpro.

Analysis of SARS-CoV-2 RNA-dependent RNA polymerase as a potential therapeutic drug target using a computational approach

BackgroundThe Severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) outbreak originating in Wuhan, China, has raised global health concerns and the pandemic has now been reported on all inhabited continents. Hitherto, no antiviral drug is available to combat this viral outbreak.MethodsKeeping in mind the urgency of the situation, the current study was designed to devise new strategies for drug discovery and/or repositioning against SARS-CoV-2. In the current study, RNA-dependent RNA polymerase (RdRp), which regulates viral replication, is proposed as a potential therapeutic target to inhibit viral infection.ResultsEvolutionary studies of whole-genome sequences of SARS-CoV-2 represent high similarity (> 90%) with other SARS viruses. Targeting the RdRp active sites, ASP760 and ASP761, by antiviral drugs could be a potential therapeutic option for inhibition of coronavirus RdRp, and thus viral replication. Target-based virtual screening and molecular docking results show that the antiviral Galidesivir and its structurally similar compounds have shown promise against SARS-CoV-2.ConclusionsThe anti-polymerase drugs predicted here—CID123624208 and CID11687749—may be considered for in vitro and in vivo clinical trials.

Design, synthesis, molecular docking and anticonvulsant evaluation of 6-methyl-2-arylaminopyrimidin-4(3H)-one

The aim. Synthesis of 2-aminoaryl derivatives of 6-methyl-pyrimidin-4(3H)-one, target-based virtual screening followed by the study of anticonvulsant activity and the establishment of structure-activity patterns.Materials and methods. The standard methods of organic synthesis were used, synthesized compounds structure was proved with elemental analysis, 1H NMR spectroscopy, chromatography-mass spectrometry. Molecular docking was performed using AutoDockTools-1.5.6 and AutoDock Vina. Anticonvulsant activity was studied in а model of pentylenetetrazole seizures in rats.Results. Methylation of 6-methyl-2-thiopyrimidin-4 (3H)-one with dimethyl sulfate or methyl iodide gave a 2-thiomethyl derivative. By heating the latter with aromatic amines at 140 ºC, the target 2-aminoaryl derivatives of 6-methyl-pyrimidin-4 (3H)-one were obtained. The prospect of screening the synthesized compounds on the pentylenetetrazole model by seizure and the selection of the objects was performed by the results of binding energy and conformation evaluation at the active sites of GABA receptor and GABA-AT. The test substances did not show anticonvulsant activity: only 2 compounds tended to exhibit activity according to the criterion of integral protective index - a decrease in mortality compared to control, preventing mortality in 100 and 80 % of animals, respectively. Comparison with previous activity results of 2-thioacetanilide derivatives allowed to prove the positive role of thioacetamide and phenyl fragments, as well as 4-Br, 4-MeO radicals in the manifestation of anticonvulsant activity and increase of lethality in the presence of Cl atoms.Conclusions. The synthesis was performed and construction of the 2-aminoaryl derivatives of 6-methyl-pyrimidin-4(3H)-one was proved. PTZ seizures model in rats did not show anticonvulsant activity. However, the obtained results allowed us to identify a number of structural fragments that influence anticonvulsant activity. A positive correlation between in vivo studies on PTZ seizures model and docking results in active sites of GABAA and GABAAT enzyme was determined

Analysis of therapeutic targets for SARS-CoV-2 and discovery of potential drugs by computational methods

SARS-CoV-2 has caused tens of thousands of infections and more than one thousand deaths. There are currently no registered therapies for treating coronavirus infections. Because of time consuming process of new drug development, drug repositioning may be the only solution to the epidemic of sudden infectious diseases. We systematically analyzed all the proteins encoded by SARS-CoV-2 genes, compared them with proteins from other coronaviruses, predicted their structures, and built 19 structures that could be done by homology modeling. By performing target-based virtual ligand screening, a total of 21 targets (including two human targets) were screened against compound libraries including ZINC drug database and our own database of natural products. Structure and screening results of important targets such as 3-chymotrypsin-like protease (3CLpro), Spike, RNA-dependent RNA polymerase (RdRp), and papain like protease (PLpro) were discussed in detail. In addition, a database of 78 commonly used anti-viral drugs including those currently on the market and undergoing clinical trials for SARS-CoV-2 was constructed. Possible targets of these compounds and potential drugs acting on a certain target were predicted. This study will provide new lead compounds and targets for further in vitro and in vivo studies of SARS-CoV-2, new insights for those drugs currently ongoing clinical studies, and also possible new strategies for drug repositioning to treat SARS-CoV-2 infections.