Discovery of human coronaviruses pan-papain-like protease inhibitors using computational approaches

The papain-like protease (PLpro) is vital for the replication of coronaviruses (CoVs), as well as for escaping innate-immune responses of the host. Hence, it has emerged as an attractive antiviral drug-target. In this study, computational approaches were employed, mainly the structure-based virtual screening coupled with all-atom molecular dynamics (MD) simulations to computationally identify specific inhibitors of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) PLpro, which can be further developed as potential pan-PLpro based broad-spectrum antiviral drugs. The sequence, structure, and functional conserveness of most deadly human CoVs PLpro were explored, and it was revealed that functionally important catalytic triad residues are well conserved among SARS-CoV, SARS-CoV-2, and middle east respiratory syndrome coronavirus (MERS-CoV). The subsequent screening of a focused protease inhibitors database composed of ∼7,000 compounds resulted in the identification of three candidate compounds, ADM_13083841, LMG_15521745, and SYN_15517940. These three compounds established conserved interactions which were further explored through MD simulations, free energy calculations, and residual energy contribution estimated by MM-PB(GB)SA method. All these compounds showed stable conformation and interacted well with the active residues of SARS-CoV-2 PLpro, and showed consistent interaction profile with SARS-CoV PLpro and MERS-CoV PLpro as well. Conclusively, the reported SARS-CoV-2 PLpro specific compounds could serve as seeds for developing potent pan-PLpro based broad-spectrum antiviral drugs against deadly human coronaviruses. Moreover, the presented information related to binding site residual energy contribution could lead to further optimization of these compounds.

An online repository of solvation thermodynamic and structural maps of SARS-CoV-2 targets

SARS-CoV-2 recently jumped species and rapidly spread via human-to-human transmission to cause a global outbreak of COVID-19. The lack of effective vaccine combined with the severity of the disease necessitates attempts to develop small molecule drugs to combat the virus. COVID19_GIST_HSA is a freely available online repository to provide solvation thermodynamic maps of COVID-19-related protein small molecule drug targets. Grid inhomogeneous solvation theory maps were generated using AmberTools cpptraj-GIST, 3D reference interaction site model maps were created with AmberTools rism3d.snglpnt and hydration site analysis maps were created using SSTMap code. The resultant data can be applied to drug design efforts: scoring solvent displacement for docking, rational lead modification, prioritization of ligand- and protein- based pharmacophore elements, and creation of water-based pharmacophores. Herein, we demonstrate the use of the solvation thermodynamic mapping data. It is hoped that this freely provided data will aid in small molecule drug discovery efforts to defeat SARS-CoV-2.

Drug repurposing using computational methods to identify therapeutic options for COVID-19

PURPOSE

Recently, the world has been dealing with a new type of coronavirus called COVID-19 that in terms of symptoms is similar to the SARS coronavirus. Unfortunately, researchers could not find a registered therapy to treat the infection related to the virus yet. Regarding the fact that drug repurposing is a good strategy for epidemic viral infection, we applied the drug repurposing strategy using virtual screening to identify therapeutic options for COVID-19. For this purpose, five proteins of COVID-19 (3-chymotrypsin-like protease (3CLpro), Papain-Like protease (PLpro), cleavage site, HR1 and RBD in Spike protein) were selected as target proteins for drug repositioning.

METHODS

First, five proteins of COVID-19 were built by homology modeling. Then FDA-approved drugs (2471 drugs) were screened against cleavage site and RBD in Spike protein via virtual screening. One hundred and twenty-eight FDA-approved drugs with the most favorable free-binding energy were attached to the cleavage site and RBD in Spike protein. Of these 128 drugs, 18 drugs have either been used currently as antiviral or have been reported to possess antiviral effects. Virtual screening was then performed for the 18 selected drugs with ACE2, 3CLpro and PLpro and HR1 and TMPRSS2.

RESULTS

According to the results, glecaprevir, paritaprevir, simeprevir, ledipasvir, glycyrrhizic acid, TMC-310911, and hesperidin showed highly favorably free binding energies with all tested target proteins.

CONCLUSION

The above-mentioned drugs can be regarded as candidates to treat COVID-19 infections, but further study on the efficiency of these drugs is also necessary.

Identification of potential inhibitors of Zika virus NS5 RNA-dependent RNA polymerase through virtual screening and molecular dynamic simulations

Zika virus (ZIKV) is one of the mosquito borne flavivirus with several outbreaks in past few years in tropical and subtropical regions. The non-structural proteins of flaviviruses are suitable active targets for inhibitory drugs due to their role in pathogenicity. In ZIKV, the non-structural protein 5 (NS5) RNA-Dependent RNA polymerase replicates its genome. Here we have performed virtual screening to identify suitable ligands that can potentially halt the ZIKV NS5 RNA dependent RNA polymerase (RdRp). During this process, we searched and screened a library of ligands against ZIKV NS5 RdRp. The selected ligands with significant binding energy and ligand-receptor interactions were further processed. Among the selected docked conformations, top five was further optimized at atomic level using molecular dynamic simulations followed by binding free energy calculations. The interactions of ligands with the target structure of ZIKV RdRp revealed that they form strong bonds within the active sites of the receptor molecule. The efficacy of these drugs against ZIKV can be further analyzed through in-vitro and in-vivo studies.

Repurposing FDA-approved phytomedicines, natural products, antivirals and cell protectives against SARS-CoV-2 (COVID-19) RNA-dependent RNA polymerase

Following the recent emergence of SARS-CoV-2 or coronavirus disease 2019 (COVID-19), drug discovery and vaccine design to combat this fatal infection are critical. In this study, an essential enzyme in the SARS-CoV-2 replication machinery, RNA-dependent RNA polymerase (RDRP), is targeted in a virtual screening assay using a set of 1,664 FDA-approved drugs, including sets of botanical and synthetic derivatives. A set of 22 drugs showed a high docking score of >-7. Notably, approximately one-third of the top hits were either from natural products or biological molecules. The FDA-approved phytochemicals were sennosides, digoxin, asiaticoside, glycyrrhizin, neohesperidin, taxifolin, quercetin and aloin. These approved natural products and phytochemicals are used as general tonics, antioxidants, cell protectives, and immune stimulants (nadid, thymopentin, asiaticoside, glycyrrhizin) and in other miscellaneous systemic or topical applications. A comprehensive analysis was conducted on standard precision and extra precision docking, two-step molecular dynamics simulations, binding energy calculations and a post dynamics analysis. The results reveal that two drugs, docetaxel and neohesperidin, showed strong binding profiles with SARS CoV-2 RdRP. These results can be used as a primer for further drug discovery studies in the treatment of COVID-19. This initiative repurposes safe FDA-approved drugs against COVID-19 RdRP, providing a rapid channel for the discovery and application of new anti-CoV therapeutics.

KLF7: a new candidate biomarker and therapeutic target for high-grade serous ovarian cancer

BACKGROUND

In spite of great progress in the surgical and clinical management, until now no significant improvement in overall survival of High-Grade Serous Ovarian Cancer (HGSOC) patients has been achieved. Important aspects for disease control remain unresolved, including unclear pathogenesis, high heterogeneity and relapse resistance after chemotherapy. Therefore, further research on molecular mechanisms involved in cancer progression are needed to find new targets for disease management. The Krüppel-like factors (KLFs) are a family of transcriptional regulators controlling several basic cellular processes, including proliferation, differentiation and migration. They have been shown to play a role in various cancer-relevant processes, in a context-dependent way.

METHODS

To investigate a possible role of KLF family members as prognostic biomarkers, we carried out a bioinformatic meta-analysis of ovarian transcriptome datasets in different cohorts of late-stage HGSOC patients. In vitro cellular models of HGSOC were used for functional studies exploring the role of KLF7 in disease development and progression. Finally, molecular modelling and virtual screening were performed to identify putative KLF7 inhibitors.

RESULTS

Bioinformatic analysis highlighted KLF7 as the most significant prognostic gene, among the 17 family members. Univariate and multivariate analyses identified KLF7 as an unfavourable prognostic marker for overall survival in late-stage TCGA-OV and GSE26712 HGSOC cohorts. Functional in vitro studies demonstrated that KLF7 can play a role as oncogene, driving tumour growth and dissemination. Mechanistic targets of KLF7 included genes involved in epithelial to mesenchymal transition, and in maintaining pluripotency and self-renewal characteristics of cancer stem cells. Finally, in silico analysis provided reliable information for drug-target interaction prediction.

CONCLUSIONS

Results from the present study provide the first evidence for an oncogenic role of KLF7 in HGSOC, suggesting it as a promising prognostic marker and therapeutic target.

Design a synthetic glucose receptor using computational intelligence approach

The synthetic glucose receptors help to develop glucose sensors and alternative insulin therapies. Designing a glucose recognition molecule in an aqueous system remains a considerable challenge. Therefore, In-silico molecular screening hypothesis is proposed to overcome the difficulties found during the modeling of a molecule. The small organic compounds from compound databases are screened for glucose receptor modeling. Thereafter, the different computational models are designed that mimic natural glucose receptors based on screened compounds. The orientation and binding of glucose molecules within the developed receptor are predicted through the molecular interaction approach. The modeled receptors and receptor-glucose complex structures are used for geometry optimization and molecular dynamics computation. The docking results reveal that ZINC82047919, ZINC238094340, and ZINC238519600 compounds-based models provide better interactions with glucose and its orientation within the receptor cavity. The molecular dynamics simulation results showed that the receptor designed using compound ZINC238094340 is unable to hold the glucose and undergo significant conformation changes during simulation process. The receptor designed from ZINC238094340 and ZINC238519600 compounds is utilized as a reference glucose binding receptor in this study. The proposed computational approach is able to develop a novel glucose receptor and other glucose relative sugar molecules.

Improvement of the Structure Generator DAECS with Respect to Structural Diversity

The development of novel organic compounds with desired properties is time consuming and costly. Thus, the quantitative structure-property relationship (QSPR) model is used widely for efficiently discovering compounds with the desired properties. Novel structures can be generated from a variety of input structures in silico by structure generators. We previously developed the structure generator DAECS to yield highly active drug-like structures. However, the structural diversity of the structures generated by DAECS was still small for practical applications such as drug discovery. In this paper, we present structure modification rules and the algorithm to output more diverse structures through the DAECS workflow. Two new types of structural modification rules, bond contraction and ring mergence, were added. The new algorithm, which restricts the search area and subsequently clusters structures on a two-dimensional map generated by generative topographic mapping, was implemented for the repetitive selection of seed structures. A case study was conducted to evaluate our method using ligand structures for the histamine H1 receptor. The results showed improved structural diversity than the previous method.

Targeting SARS-CoV-2 main protease: structure based virtual screening, in silico ADMET studies and molecular dynamics simulation for identification of potential inhibitors

COVID-19 pandemic has created a healthcare crisis across the world and has put human life under life-threatening circumstances. The recent discovery of the crystallized structure of the main protease (M_pro) from SARS-CoV-2 has provided an opportunity for utilizing computational tools as an effective method for drug discovery. Targeting viral replication has remained an effective strategy for drug development. M_pro of SARS-COV-2 is the key protein in viral replication as it is involved in the processing of polyproteins to various structural and nonstructural proteins. Thus, M_pro represents a key target for the inhibition of viral replication specifically for SARS-CoV-2. We have used a virtual screening strategy by targeting M_pro against a library of commercially available compounds to identify potential inhibitors. After initial identification of hits by molecular docking-based virtual screening further MM/GBSA, predictive ADME analysis, and molecular dynamics simulation were performed. The virtual screening resulted in the identification of twenty-five top scoring structurally diverse hits that have free energy of binding (ΔG) values in the range of −26-06 (for compound AO-854/10413043) to −59.81 Kcal/mol (for compound 329/06315047). Moreover, the top-scoring hits have favorable AMDE properties as calculated using in silico algorithms. Additionally, the molecular dynamics simulation revealed the stable nature of protein-ligand interaction and provided information about the amino acid residues involved in binding. Overall, this study led to the identification of potential SARS-CoV-2 M_pro hit compounds with favorable pharmacokinetic properties. We believe that the outcome of this study can help to develop novel M_pro inhibitors to tackle this pandemic.

Communicated by Ramaswamy H. Sarma

Identification of novel inhibitors of the ABC transporter BmrA

The resistance of microbes to commonly used antibiotics has become a worldwide health problem. A major underlying mechanism of microbial antibiotic resistance is the export of drugs from bacterial cells. Drug efflux is mediated through the action of multidrug resistance efflux pumps located in the bacterial cell membranes. The critical role of bacterial efflux pumps in antibiotic resistance has directed research efforts to the identification of novel efflux pump inhibitors that can be used alongside antibiotics in clinical settings. Here, we aimed to find potential inhibitors of the archetypical ATP-binding cassette (ABC) efflux pump BmrA of Bacillus subtilis via virtual screening of the Mu.Ta.Lig. Chemotheca small molecule library. Molecular docking calculations targeting the nucleotide-binding domain of BmrA were performed using AutoDock Vina. Following a further drug-likeness filtering step based on Lipinski's Rule of Five, top 25 scorers were identified. These ligands were then clustered into separate groups based on their contact patterns with the BmrA nucleotide-binding domain. Six ligands with distinct contact patterns were used for further in vitro inhibition assays based on intracellular ethidium bromide accumulation. Using this methodology, we identified two novel inhibitors of BmrA from the Chemotheca small molecule library.

Comparison of Binding Site of Remdesivir and Its Metabolites with NSP12-NSP7-NSP8, and NSP3 of SARS CoV-2 Virus and Alternative Potential Drugs for COVID-19 Treatment

Remdesivir was approved by the U.S.A. Food and Drug administration for emergency use to interfere with the replication of SARS CoV-2 virus (the agent that causes COVID-19) in adults and children hospitalized with severe disease. The crystal structure of the metabolite of remdesivir (Monophosphate of GS-441524) and NSP12-NSP8-NSP7 of SARS CoV-2 virus was recently reported. The crystal structures of ADP-Ribose or AMP and NSP3 of SARS CoV-2 virus were also released, recently. This study compared their binding sites and suggests the crystal structure of NSP3 of SARS CoV-2 virus as an alternative binding site of AMP or ADP-ribose to treat COVID-19. We virtually screened 682 FDA-approved compounds, and the top 10 compounds were selected by analysis of docking scores, (G-score, D-score, and Chemscore) and visual analysis using a structure-based docking approach of NSP3 of SARS CoV-2 virus. All immunization approaches are based on the SARS-CoV-2 virus spike protein. A recent study reported that the D614G mutation in the SARS-CoV-2 virus spike protein reduces S1 shedding and increases infectivity of SARS COV-2 virus. Therefore, if there is a severe change in the spike protein of a modified Coronavirus, all developed vaccines can lose their efficacy, necessitating the need for an alternative treatment method. The top 10 compounds (FDA-approved) in this study are selected based on NSP 3 binding site, and therefore are a potential viable treatment because they will show potential activity for all mutations in the SARS-CoV-2 virus spike protein.

Virtual screening and network pharmacology-based synergistic mechanism identification of multiple components contained in Guanxin V against coronary artery disease

BACKGROUND

Guanxin V (GXV), a traditional Chinese medicine (TCM), has been widely used to treat coronary artery disease (CAD) in clinical practice in China. However, research on the active components and underlying mechanisms of GXV in CAD is still scarce.

METHODS

A virtual screening and network pharmacological approach was utilized for predicting the pharmacological mechanisms of GXV in CAD. The active compounds of GXV based on various TCM-related databases were selected and then the potential targets of these compounds were identified. Then, after the CAD targets were built through nine databases, a PPI network was constructed based on the matching GXV and CAD potential targets, and the hub targets were screened by MCODE. Moreover, Metascape was applied to GO and KEGG functional enrichment. Finally, HPLC fingerprints of GXV were established.

RESULTS

A total of 119 active components and 121 potential targets shared between CAD and GXV were obtained. The results of functional enrichment indicated that several GO biological processes and KEGG pathways of GXV mostly participated in the therapeutic mechanisms. Furthermore, 7 hub MCODEs of GXV were collected as potential targets, implying the complex effects of GXV-mediated protection against CAD. Six specific chemicals were identified.

CONCLUSION

GXV could be employed for CAD through molecular mechanisms, involving complex interactions between multiple compounds and targets, as predicted by virtual screening and network pharmacology. Our study provides a new TCM for the treatment of CAD and deepens the understanding of the molecular mechanisms of GXV against CAD.

Ligand and Structure-based Virtual Screening of Lamiaceae Diterpenes with Potential Activity against a Novel Coronavirus (2019-nCoV)

BACKGROUND

The emergence of a new coronavirus (CoV), named 2019-nCoV, as an outbreak originated in the city of Wuhan, China, has resulted in the death of more than 3,400 people this year alone and has caused worldwide an alarming situation, particularly following previous CoV epidemics, including the Severe Acute Respiratory Syndrome (SARS) in 2003 and the Middle East Respiratory Syndrome (MERS) in 2012. Currently, no exists for infections caused by CoVs; however, some natural products may represent potential treatment resources, such as those that contain diterpenes.

OBJECTIVE

This study aimed to use computational methods to perform a virtual screening (VS) of candidate diterpenes with the potential to act as CoV inhibitors.

METHODS

1,955 diterpenes, derived from the Nepetoideae subfamily (Lamiaceae), were selected using the SistematX tool (https://sistematx.ufpb.br), which were used to make predictions. From the ChEMBL database, 3 sets of chemical structures were selected for the construction of predictive models.

RESULTS

The chemical structures of molecules with known activity against SARS CoV, two of which were tested for activity against specific viral proteins and one of which was tested for activity against the virus itself, were classified according to their pIC50 values [-log IC50 (mol/l)].

CONCLUSION

In the consensus analysis approach, combining both ligand- and structure-based VSs, 19 compounds were selected as potential CoV inhibitors, including isotanshinone IIA (01), tanshinlactone (02), isocryptotanshinone (03), and tanshinketolactone (04), which did not present toxicity within the evaluated parameters.

LigGrep: a tool for filtering docked poses to improve virtual-screening hit rates

Structure-based virtual screening (VS) uses computer docking to prioritize candidate small-molecule ligands for subsequent experimental testing. Docking programs evaluate molecular binding in part by predicting the geometry with which a given compound might bind a target receptor (e.g., the docked "pose" relative to a protein target). Candidate ligands predicted to participate in the same intermolecular interactions typical of known ligands (or ligands that bind related proteins) are arguably more likely to be true binders. Some docking programs allow users to apply constraints during the docking process with the goal of prioritizing these critical interactions. But these programs often have restrictive and/or expensive licenses, and many popular open-source docking programs (e.g., AutoDock Vina) lack this important functionality. We present LigGrep, a free, open-source program that addresses this limitation. As input, LigGrep accepts a protein receptor file, a directory containing many docked-compound files, and a list of user-specified filters describing critical receptor/ligand interactions. LigGrep evaluates each docked pose and outputs the names of the compounds with poses that pass all filters. To demonstrate utility, we show that LigGrep can improve the hit rates of test VS targeting H. sapiens poly(ADPribose) polymerase 1 (HsPARP1), H. sapiens peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 (HsPin1p), and S. cerevisiae hexokinase-2 (ScHxk2p). We hope that LigGrep will be a useful tool for the computational biology community. A copy is available free of charge at http://durrantlab.com/liggrep/ .

Discovery of novel modulators targeting human TRPC5: Docking-based virtual screening, molecular dynamics simulation and binding affinity predication

Canonical transient receptor potential channel 5 (TRPC5) plays a key role in the regulation of central nervous system, cardiovascular system, kidney disease, cancer, and could be also involved in liver function, arthritis, diabetes-associated complications and so on. However, evidence of TRPC5 function on cellular or organismic levels is sparse. There is still a need for identifying novel and efficient TRPC5 channel modulators to study TRPC5 function. In this study, based on the hTRPC5 structure obtained by homology modeling and the predicted binding site, we have performed virtual screening of 212,736 compounds from the specs database（http://www.specs.net) to find potential hTRPC5 modulators. Lipinski and Veber rules, ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity) and PAINS (Pan Assay Interference structures) filters were used to screen the large database. Further, multi-software combination docking, cluster analysis and interaction analysis were used to select 20 potential active candidates with novel skeleton. 4 Hits, bearing appreciable binding affinity with hTRPC5 were selected for 40ns all-atom molecular dynamics (MD) simulations under explicit water conditions. The MD simulation results suggested that the 4 Hits binding induces a slight structural change and stabilizes the hTRPC5 structure. In addition, decomposition free energy demonstrated that residues TRP434, LEU437, MET438, ALA441, ILE484, ILE487, LEU488, LEU491, LEU515, ILE517, LEU518, LEU521, PHE531, THR607, VAL610, ILE611, VAL615 played the critical role on system stability. 4 Hits, as potential modulators of hTRPC5, may be potential leads to develop effective therapeutics hTRPC5-associated diseases.

In silico and in vitro screening for potential anticancer candidates targeting GPR120

The G-protein coupled receptor - GPR120 has recently been implicated as a novel target for colorectal cancer (CRC) and other cancer managements. In this study, a homology model of GPR120S (short isoform) was generated to identify potential anti-cancer compounds targeting the GPR120 receptor using a combined in silico docking-based virtual screening (DBVS), structure-activity relationships (SAR) and in vitro screening approach. SPECS database of synthetic chemical compounds (~350,000) was screened using the developed GPR120S model to identify molecules binding to the orthosteric binding pocket followed by an AutoDock SMINA rigid-flexible docking protocol. The best 13 hit molecules were then tested in vitro to evaluate their cytotoxic activity against SW480 - human CRC cell line expressing GPR120. The test compound 1 (3-​(4-​methylphenyl)​-​2-​[(2-​oxo-​2-​phenylethyl)​sulfanyl]​-​5,6-​dihydrospiro(benzo[h]​quinazoline-​5,1'-​cyclopentane)​-​4(3H)​-​one) showed ~ 90% inhibitory effects on cell growth with micromolar affinities (IC₅₀ = 23.21-26.69 µM). Finally, SAR analysis of compound 1 led to the identification of a more active compound from the SPECS database showing better efficacy during cell-based cytotoxicity assay -5 (IC₅₀ = 5.89-6.715 µM), while a significant reduction in cytotoxic effects of 5 was observed in GPR120-siRNA pre-treated SW480 cells. The GPR120S homology model generated, and SAR analysis conducted by this work discovered a potential chemical scaffold, dihydrospiro(benzo[h]quinazoline-5,1'-cyclopentane)-4(3H)-one, which will aid future research on anti-cancer drug development for CRC management.

Synthesis and bio-evaluation of a novel selective butyrylcholinesterase inhibitor discovered through structure-based virtual screening

In recent years, butyrylcholinesterase (BChE) has gradually gained worldwide interests as a novel target for treating Alzheimer's disease (AD). Here, two pharmacophore models were generated using Schrödinger suite and used to virtually screen ChemDiv database, from which three hits were obtained. Among them, 2513-4169 displayed the highest inhibitory activity and selectivity against BChE (eeAChE IC₅₀ > 10 μM, eqBChE IC₅₀ = 3.73 ± 1.90 μM). Molecular dynamic (MD) simulation validated the binding pattern of 2513-4169 in BChE, and it could form a various of receptor-ligand interactions with adjacent residues. In vitro cytotoxicity assay proved the safety of 2513-4169 on diverse neural cell lines. Moreover, the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium (MTT) assay performed on SH-SY5Y cells proved the neuroprotective effect of 2513-4169 against toxic Aβ_1-42. In vivo behavioral study further confirmed the great efficacy of 2513-4169 on reversing Aβ_1-42-induced cognitive impairment of mice and clearing the toxic Aβ_1-42 in brains. Moreover, 2513-4169 was proved to be able to cross blood-brain barrier (BBB) through a parallel artificial membrane permeation assay of BBB (PAMPA-BBB). Taken together, 2513-4169 is a promising lead compound for future optimization to discover anti-AD treating agents.

Mitoxantrone, pixantrone and mitoxantrone (2-hydroxyethyl)piperazine are toll-like receptor 4 antagonists, inhibit NF-κB activation, and decrease TNF-alpha secretion in primary microglia

Toll-like receptor 4 (TLR4) recognizes various endogenous and microbial ligands and is an essential part in the innate immune system. TLR4 signaling initiates transcription factor NF-κB and production of proinflammatory cytokines. TLR4 contributes to the development or progression of various diseases including stroke, neuropathic pain, multiple sclerosis, rheumatoid arthritis and cancer, and better therapeutics are currently sought for these conditions. In this study, a library of 140 000 compounds was virtually screened and a resulting hit-list of 1000 compounds was tested using a cellular reporter system. The topoisomerase II inhibitor mitoxantrone and its analogues pixantrone and mitoxantrone (2-hydroxyethyl)piperazine were identified as inhibitors of TLR4 and NF-κB activation. Mitoxantrone was shown to bind directly to the TLR4, and pixantrone and mitoxantrone (2-hydroxyethyl)piperazine were shown to inhibit the production of proinflammatory cytokines such as tumor necrosis factor alpha (TNFα) in primary microglia. The inhibitory effect on NF-κB activation or on TNFα production was not mediated through cytotoxity at ≤ 1 µM concentration for pixantrone and mitoxantrone (2-hydroxyethyl)piperazine treated cells, as assessed by ATP counts. This study thus identifies a new mechanism of action for mitoxantrone, pixantrone, and mitoxantrone (2-hydroxyethyl)piperazine through the TLR4.

In silico assessment of natural products and approved drugs as potential inhibitory scaffolds targeting aminoacyl-tRNA synthetases from Plasmodium

Malaria remains the leading cause of deaths globally, despite significant advancement towards understanding its epidemiology and availability of multiple therapeutic interventions. Poor efficacy of the approved vaccine, and the rapid emergence of antimalarial drug resistance, warrants an urgent need to expedite the process of development of new lead molecules targeting malaria. Aminoacyl-tRNA synthetases (aaRSs) are essential enzymes crucial for ribosomal protein synthesis and are valid antimalarial targets. This study explores the prospects of (re-)positioning the repertoire of approved drugs and natural products as potential malarial aaRS inhibitors. Molecular docking of these two sets of small-molecules to lysyl-, prolyl-, and tyrosyl- synthetases from Plasmodium followed by a comparison of the top-ranking docked compounds against human homologs facilitated identification of promising molecular scaffolds. Raltitrexed and Cefprozil, an anticancer drug and an antibiotic, respectively, showed stronger binding to Plasmodium aaRSs compared to human homologs with > 4 kcal/mol difference in the docking scores. Similarly, a difference of ~ 3 kcal/mol in Glide scores was observed for docked Calcipotriol, a drug used for psoriasis treatment, against the two lysyl-tRNA synthetases. Natural products such as Dihydroxanthohumol and Betmidin, having aromatic rings as a substructure, showed preferential docking to the purine binding pocket in Plasmodium tyrosyl-tRNA synthetase as evident from the calculated change in binding free energies. We present detailed analyses of the calculated intermolecular interaction for all top-scoring docked poses. Overall, this study provides a compelling foundation to design and develop specific antimalarials.

In silico identification of strong binders of the SARS-CoV-2 receptor-binding domain

The world is currently witnessing the spread of the deadly severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes the coronavirus disease 2019 (COVID-19). In less than three months since the first cases were reported, the World Health Organization declared it a pandemic disease. Although several treatment and prevention strategies are currently under investigation, a continuous effort to investigate and develop effective cures is urgently needed. Thus, we performed molecular docking and structure-based virtual screening of libraries of approved drugs, antivirals, inhibitors of protein-protein interactions, and one million other small molecules to identify strong binders of the SARS-CoV-2 receptor-binding domain (RBD) that might interfere with the receptor recognition process, so as to inhibit the viral cellular entry. According to our screening and selection criteria, three approved antivirals (elbasvir, grazoprevir, and sovaprevir) and 4 other drugs (hesperidin, pamaqueside, diosmin, and sitogluside) were identified as potent binders of the RBD. The binding of these molecules involved several RBD residues required for the interaction of the virus with its cellular receptor. Furthermore, this study also discussed the pharmacological action of the 4 non-antiviral drugs on hematological and neurological disorders that, in addition to inhibiting the viral entry, could be beneficial against the neurological disorders identified in COVID-19 patients. Besides, six other small-molecules were identified, with no pharmacological description so far, exhibiting strong binding affinities to the RBD that we believe worth being investigated as inhibitors of the SARS-CoV-2-receptor interaction.

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We aimed to identify strong binders of the SARS-CoV-2 RBD to be used as inhibitors of virus-receptor interaction.

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Accordingly, 3 antivirals, 4 other approved drugs and 6 small-molecules have been identified as potential ligands of the RBD.

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The binding of these selected compounds involves several RBD residues crucial for the virus-receptor interaction.

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Besides RBD-binding, we discussed the possible effects of the selected drugs on the COVID-19- related neurological disorders.

Identification of novel αβ-tubulin modulators with antiproliferative activity directed to cancer therapy using ligand and structure-based virtual screening

Among several strategies related to cancer therapy targeting the modulation of αβ-tubulin has shown encouraging findings, more specifically when this is achieved by inhibitors located at the colchicine binding site. In this work, we aim to fish new αβ-tubulin modulators through a diverse and rational VS study, and thus, exhibiting the development of two VS pipelines. This allowed us to identify two compounds 5 and 9 that showed IC₅₀ values of 19.69 and 21.97 μM, respectively, towards possible modulation of αβ-tubulin, such as assessed by in vitro assays in C6 glioma and HEPG2 cell lines. We also evaluated possible mechanisms of action of obtained hits towards the colchicine binding site of αβ-tubulin by using docking approaches. In addition, assessment of the stability of the active (5 and 9) and inactive compounds (3 and 13) within the colchicine binding site was carried out by molecular dynamics (MD) simulations, highlighting the solvent effect and revealing the compound 5 as the most stable in the complex. At last, deep analysis of these results provided some valuable insights on the importance of using mixed ligand- and structure-based strategies in VS campaigns, in order to achieve higher chemical diversity and biological effect as well.

Discovery of small molecule PLpro inhibitor against COVID-19 using structure-based virtual screening, molecular dynamics simulation, and molecular mechanics/Generalized Born surface area (MM/GBSA) calculation

COVID-19 is spreading in a global pandemic that is endangering human life and health. Therefore, there is an urgent need to target COVID-19 to find effective treatments for this emerging acute respiratory infection. Viral Papain-Like cysteine protease (PLpro), similar to papain and the cysteine deubiquitinase enzyme, has been a popular target for coronavirus inhibitors, as an indispensable enzyme in the process of coronavirus replication and infection of the host. Combined structure-based virtual screening, molecular dynamics (MD) simulation, and molecular mechanics/Generalized Born surface area (MM/GBSA) free energy calculation approaches were utilized for identification of PLpro inhibitors. Four compounds (F403_0159, F112_0109, G805_0497, D754_0006) with diverse chemical scaffolds were retrieved as hits based on docking score and clustering analysis. Molecular dynamics simulations indicated that the contribution of van der Waals interaction dominated the binding free energies of these compounds, which may be attributed to the hydrophobicity of active site of PLpro from COVID-19. Moreover, all four compounds formed conservative hydrogen bonds with the residues Asp164, Gln269, and Tyr273. We hoped that these four compounds might represent the promising chemical scaffolds for further development of novel PLpro inhibitors against COVID-19.

In silico identification of drug candidates against COVID-19

The COVID-19 pandemic has caused unprecedented health and economic crisis throughout the world. However, there is no effective medication or therapeutic strategy for treatment of this disease currently. Here, to elucidate the inhibitory effects, we first tested binding affinities of 11 HIV-1 protease inhibitors or their pharmacoenhancers docked onto SARS-CoV-2 main protease (M pro ), and 12 nucleotide-analog inhibitors docked onto RNA dependent RNA polymerase (RdRp). To further obtain the effective drug candidates, we screened 728 approved drugs via virtual screening on SARS-CoV-2 M pro . Our results demonstrate that remdesivir shows the best binding energy on RdRp and saquinvir is the best inhibitor of M pro . Based on the binding energies, we also list 10 top-ranked approved drugs which can be potential inhibitors for M pro . Overall, our results do not only propose drug candidates for further experiments and clinical trials but also pave the way for future lead optimization and drug design.

Application of target repositioning and in silico screening to exploit fatty acid binding proteins (FABPs) from Echinococcus multilocularis as possible drug targets

Fatty acid binding proteins (FABPs) are small intracellular proteins that reversibly bind fatty acids and other hydrophobic ligands. In cestodes, due to their inability to synthesise fatty acids and cholesterol de novo, FABPs, together with other lipid binding proteins, have been proposed as essential, involved in the trafficking and delivery of such lipophilic metabolites. Pharmacological agents that modify specific parasite FABP function may provide control of lipid signalling pathways, inflammatory responses and metabolic regulation that could be of crucial importance for the parasite development and survival. Echinococcus multilocularis and Echinococcus granulosus are, respectively, the causative agents of alveolar and cystic echinococcosis (or hydatidosis). These diseases are included in the World Health Organization's list of priority neglected tropical diseases. Here, we explore the potential of FABPs from cestodes as drug targets. To this end, we have applied a target repurposing approach to identify novel inhibitors of Echinococcus spp. FABPs. An ensemble of computational models was developed and applied in a virtual screening campaign of DrugBank library. 21 hits belonging to the applicability domain of the ensemble models were identified, and 3 of the hits were assayed against purified E. multilocularis FABP, experimentally confirming the model's predictions. Noteworthy, this is to our best knowledge the first report on isolation and purification of such four FABP, for which initial structural and functional characterization is reported here.

Identification of potential drug target in malarial disease using molecular docking analysis

Malaria caused by genus Plasmodium, is a parasite which is the main health issue for humans and about half of the population were suffered. An every year, approximately 1.2–2.7 million people died due to malaria globally. Therefore to prevent the spreading of malaria from the glob novel active drugs with specific activities are necessary. The present study aimed to identify novel drug molecule together with the bioinformatic tools for the development of active malarial drugs. As the search for latest anti malarial compound was developed, this work determined six active blends from various drug databases which possess drug-like characteristics and presents a significant anti malarial actions in in-silico level. Compound ID 300238, 889, 76569, 87324, 45678, and Z185397112are a few of the ligands were got from the Toss lab, Maybridge, Cambridge, Life chem, Bitter, and Examine drug databases and docked against hexokinase 1 protein (PDB: 1CZA) with high throughput practical screening (HTVS) using Glide v6.6. Amid the 6 compounds, compound no: 300238 from Toss lab has the greatest docking score of −9.889 kcal/mol targeting 1CZA protein. The active sites of Hexokinase I of protein were determine by using superimposition of the destination and template structure showed similar structural folds and active sites which were decidedly conserved. The quality of hexokinase I protein was considered to be sterically stable where the protein was prepared by utilizing the software protein preparation execute in the Schrodinger suite. Prepared proteins were evaluated using SAVES and the studies of molecular dynamics of the hexokinase, and the GROMACS were performed for protein–ligand complex. The low HOMO-LUMO energy gaps of the compound verified the greater stability of the molecule. Here, the tested drug candidates have good absorption, distribution, metabolism, and excretion (ADME) properties which were established by using QikProp, version 3.4 of Schrodinger.