Computational investigation of drug bank compounds against 3C-like protease (3CLpro) of SARS-CoV-2 using deep learning and molecular dynamics simulation.

Blocking the main replicating enzyme, 3 Chymotrypsin-like protease (3CLpro) is the most promising drug development strategy against the SARS-CoV-2 virus, responsible for the current COVID-19 pandemic. In the present work, 9101 drugs obtained from the drug bank database were screened against SARS-CoV-2 3CLpro prosing deep learning, molecular docking, and molecular dynamics simulation techniques. In the initial stage, 500 drug-screened by deep learning regression model and subjected to molecular docking that resulted in 10 screened compounds with strong binding affinity. Further, five compounds were checked for their binding potential by analyzing molecular dynamics simulation for 100 ns at 300 K. In the final stage, two compounds {4-[(2s,4e)-2-(1,3-Benzothiazol-2-Yl)-2-(1h-1,2,3-Benzotriazol-1-Yl)-5-Phenylpent-4-Enyl]Phenyl}(Difluoro)Methylphosphonic Acid and 1-(3-(2,4-dimethylthiazol-5-yl)-4-oxo-2,4-dihydroindeno[1,2-c]pyrazol-5-yl)-3-(4-methylpiperazin-1-yl)urea were screened as potential hits by analyzing several parameters like RMSD, Rg, RMSF, MMPBSA, and SASA. Thus, our study suggests two potential drugs that can be tested in the experimental conditions to evaluate the efficacy against SARS-CoV-2. Further, such drugs could be modified to develop more potent drugs against COVID-19.

Interdomain linkers tailor the stability of immunoglobulin repeats in polyproteins.

Linkers in polyproteins are considered as mere spacers between two adjacent domains. However, a series of studies using single-molecule force spectroscopy have recently reported distinct thermodynamic stability of I27 in polyproteins with varying linkers and indicated the vital role of linkers in domain stability. A flexible glycine rich linker (-(GGG)n, n ≥ 3) featured unfolding at lower forces than the regularly used arg-ser (RS) based linker. Interdomain interactions among I27 domains in Gly-rich linkers were suggested to lead to reduced domain stability. However, the negative impact of inter domain interactions on domain stability is thermodynamically counter-intuitive and demanded thorough investigations. Here, using an array of ensemble equilibrium experiments and in-silico measurements with I27 singlet and doublets with two aforementioned linkers, we delineate that the inter-domain interactions in fact raise the stability of the polyprotein with RS linker. More surprisingly, a highly flexible Gly-rich linker has no interference on the stability of polyprotein. Overall, we conclude that flexible linkers are preferred in a polyprotein for maintaining domain's independence.

Structure-based screening of novel lichen compounds against SARS Coronavirus main protease (Mpro) as potentials inhibitors of COVID-19.

The outbreak of SARS-CoV-2 and deaths caused by it all over the world have imposed great concern on the scientific community to develop potential drugs to combat Coronavirus disease-19 (COVID-19). In this regard, lichen metabolites may offer a vast reservoir for the discovery of antiviral drug candidates. Therefore, to find novel compounds against COVID-19, we created a library of 412 lichen compounds and subjected to virtual screening against the SARS-CoV-2 Main protease (Mpro). All the ligands were virtually screened, and 27 compounds were found to have high affinity with Mpro. These compounds were assessed for drug-likeness analysis where two compounds were found to fit well for redocking studies. Molecular docking, drug-likeness, X-Score, and toxicity analysis resulting in two lichen compounds, Calycin and Rhizocarpic acid with Mpro-inhibiting activity. These compounds were finally subjected to molecular dynamics simulation to compare the dynamics behavior and stability of the Mpro after ligand binding. The binding energy was calculated by MM-PBSA method to determine the intermolecular protein-ligand interactions. Our results showed that two compounds; Calycin and Rhizocarpic acid had the binding free energy of - 42.42 kJ mol/1 and - 57.85 kJ mol/1 respectively as compared to reference X77 (- 91.78 kJ mol/1). We concluded that Calycin and Rhizocarpic acid show considerable structural and pharmacological properties and they can be used as hit compounds to develop potential antiviral agents against SARS-CoV-2. These lichen compounds may be a suitable candidate for further experimental analysis.

Using Chou's 5-steps rule to study pharmacophore-based virtual screening of SARS-CoV-2 Mpro inhibitors.

Recently emerged SARS-CoV-2 is the cause of the ongoing outbreak of COVID-19. It is responsible for the deaths of millions of people and has caused global economic and social disruption. The numbers of COVID-19 cases are increasing exponentially across the world. Control of this pandemic disease is challenging because there is no effective drug or vaccine available against this virus and this situation demands an urgent need for the development of anti-SARS-CoV-2 potential medicines. In this regard, the main protease (Mpro) has emerged as an essential drug target as it plays a vital role in virus replication and transcription. In this research, we have identified two novel potent inhibitors of the Mpro (PubChem3408741 and PubChem4167619) from PubChem database by pharmacophore-based high-throughput virtual screening. The molecular docking, toxicity, and pharmacophore analysis indicate that these compounds may act as potential anti-viral candidates. The molecular dynamic simulation along with the binding free energy calculation by MMPBSA showed that these compounds bind to Mpro enzyme with high stability over 50 ns. Our results showed that two compounds: PubChem3408741 and PubChem4167619 had the binding free energy of - 94.02 kJ mol-1 and - 122.75 kJ mol-1, respectively, as compared to reference X77 (- 76.48 kJ mol-1). Based on our work's findings, we propose that these compounds can be considered as lead molecules for targeting Mpro enzyme and they can be potential SARS-CoV-2 inhibitors. These inhibitors could be tested in vitro and explored for effective drug development against COVID-19.

Evaluation of the inhibitory potential of Valproic acid against histone deacetylase of Leishmania donovani and computational studies of Valproic acid derivatives.

Valproic acid (VA) is a proven inhibitor of human histone deacetylases (HDACs). The homogenous HDAC has been associated with all major human parasitic pathogens and hence, it has been considered an attractive drug target for anti-leishmanial therapy. To assist in drug design endeavors for HDACs, an in-vitro study has been presented to investigate the VA inhibition on Leishmania donovani HDAC (LdHDAC). The regression analysis of VA by 24 hrs viability assay confirmed its activity against LdHDAC. Moreover, the toxicity of VA is also well documented. Thus, the in-silico experiments were also conducted to screen the non-toxic VA derivatives as anti-leishmanial drug candidates having potential as inhibitors of LdHDAC. For in-silico study, the 3D structure of target LdHDAC was developed by homology modeling. Based on their in-silico activity, we shortlisted 13 VA derivatives having maximum affinity for LdHDAC and identified four potential derivatives that can specifically bind to this protein. After that, these ligands were subjected to molecular dynamics simulation. These derivatives may be effective against L. donovani promastigotes since they followed Lipinski's RO5 and were non-toxic. Thus, screened derivatives can be considered as lead ligands for targeting LdHDAC and may be used as possible drug candidates to treat leishmaniasis and overcome the limitation of anti-leishmanial drugs. This is the first report of antileishmanial potential of VA and its derivatives targeting LdHDAC. Hence, the current investigation presents a search for novel target specific drugs to aid the anti-leishmanial drug development.Communicated by Ramaswamy H. Sarma.

In silico screening of natural compounds to inhibit interaction of human ACE2 receptor and spike protein of SARS-CoV-2 for the prevention of COVID-19.

A computational investigation was carried out to find out potential phytochemicals that could inhibit the binding of human angiotensin-converting enzyme-2 (ACE2) receptors to spike protein of SARS-CoV-2 which is an essential step to gain entry inside human cells and onset of viral infection known as Coronavirus disease (COVID-19). A library of phytochemicals was screened by virtual screening against ACE2 receptors resulting in twenty phytochemicals out of 686 which had binding energy (-11.8 to -6.9 kcal/mol). Drug-likeness gave five hits, but ADMET analysis yielded 4 nontoxic hit phytochemicals. Molecular dynamics simulation of four-hit compounds resulted in acceptable stability and good dynamics behavior. These phytochemicals are Hinokinin, Gmelanone, Isocolumbin, and Tinocordioside, from Vitis vinifera, Gmelina arborea, and Tinospora cordifolia. The above-mentioned phytochemicals may be promising ACE2 inhibitors and can prevent infection of SARS-CoV-2 by inhibiting the entry of the virus into host cells.Communicated by Ramaswamy H. Sarma.

Identification of essential oil phytocompounds as natural inhibitors of Odorant-binding protein to prevent malaria through in silico approach.

Malaria predominantly affects millions annually in the African and Asian tropical and subtropical countries. With no effective vaccine, malaria prevention is exclusively dependent on preventing human-vector interaction. Anopheles gambiae, the main vector of the malaria parasite Plasmodium falciparum contains Odorant Binding proteins (OBPs) which are considered an attractive drug target for anti-malarial therapy. To identify a potential anti-malarial compound, we performed a structure-based screening of 876 phytocompounds derived from essential oils against the OBP4 by molecular docking. The compounds having better docking scores were assessed for drug-likeness, toxicity, and molecular interaction analysis. As per the results, strong affinities and high stability were demonstrated by two phytocompounds viz. Alpha-cyperone (-8.1 kcal mol-1) and Humulene oxide (-8.1 kcal mol-1) with OBP4. The hydrophobic interactions involve Phe123, Ala106, Thr57, Ala52, Thr69, and Ile64 within the binding cavities, which may block the OBP4 receptor resulting in disorientation. After that, the potential compounds were subjected to molecular dynamics (MD) simulation to evaluate their structural stability and dynamics at the active site of OBP4. The MM-PBSA result revealed that Alpha-cyperone and Humulene oxide had binding free energy of -92.44 kJ mol-1 and -113.25 kJ mol-1, respectively. Simulation outcomes demonstrate that these phytocompounds displayed considerable significant structural and pharmacological properties. The LD50 value of Alpha-cyperone and Humulene oxide also suggested that both are safe and suitable for use in natural repellent development. We suggest that the use of these compounds can minimize the treatment period and the various side effects associated with the currently available anti-malarial drugs.Communicated by Ramaswamy H. Sarma.

Deep-learning based repurposing of FDA-approved drugs against Candida albicans dihydrofolate reductase and molecular dynamics study.

Candida albicans causes the fatal fungal bloodstream infection in humans called Candidiasis. Most of the Candida species are resistant to the antifungals used to treat them. Drug-resistant C. albicans poses very serious public health issues. To overcome this, the development of effective drugs with novel mechanism(s) of action is requisite. Drug repurposing is considered a viable alternative approach to overcome the above issue. In the present study, we have attempted to identify drugs that could target the essential enzyme, dihydrofolate reductase of C. albicans (CaDHFR) to find out potent and selective antifungal antifolates. FDA-approved-drug-library from the Selleck database containing 1930 drugs was screened against CaDHFR using deep-learning, molecular docking, X-score and similarity search methods. The screened compounds showing better binding with CaDHFR were subjected to molecular dynamics simulation (MDS). The results of post-MDS analysis like RMSD, RMSF, RG, SASA, the number of hydrogen bonds and PCA suggest that Paritaprevir, Lumacaftor and Rifampin can make good interaction with CaDHFR. Furthermore, analysis of binding free energy corroborated the stability of interactions as they had binding energy of -114.91 kJ mol-1, -79.22 kJ mol-1 and -78.52 kJ mol-1 for Paritaprevir, Lumacaftor and Rifampin respectively as compared to the reference (-63.10 kJ mol-1). From the results, we conclude that these drugs have great potential to inhibit CaDHFR and would add to the drug discovery against candidiasis, and hence these drugs for repurposing should be explored further.

Molecular basis for the repurposing of histamine H2-receptor antagonist to treat COVID-19.

With the world threatened by a second surge in the number of Coronavirus cases, there is an urgent need for the development of effective treatment for the novel coronavirus (COVID-19). Recently, global attention has turned to preliminary reports on the promising anti-COVID-19 effect of histamine H2-receptor antagonists (H2RAs), most especially Famotidine. Therefore, this study was designed to exploit a possible molecular basis for the efficacy of H2RAs against coronavirus. Molecular docking was performed between four H2RAs, Cimetidine, Famotidine, Nizatidine, Ranitidine, and three non-structural proteins viz. NSP3, NSP7/8 complex, and NSP9. Thereafter, a 100 ns molecular dynamics simulation was carried out with the most outstanding ligands to determine the stability. Thereafter, Famotidine and Cimetidine were subjected to gene target prediction analysis using HitPickV2 and eXpression2Kinases server to determine the possible network of genes associated with their anti-COVID activities. Results obtained from molecular docking showed the superiority of Famotidine and Cimetidine compared to other H2RAs with a higher binding affinity to all selected targets. Molecular dynamic simulation and MMPBSA results revealed that Famotidine as well as Cimetidine bind to non-structural proteins more efficiently with high stability over 100 ns. Results obtained suggest that Famotidine and Cimetidine could be a viable option to treat COVID-19 with a mechanism of action that involves the inhibition of viral replication through the inhibition of non-structural proteins. Therefore, Famotidineand Cimetidine qualify for further study as a potential treatment for COVID-19.

Repurposing of FDA approved drugs against Salmonella enteric serovar Typhi by targeting dihydrofolate reductase: an in silico study.

Drug-resistant Salmonella enteric serovar Typhi (S. Typhi) poses a vital public health issue. To overcome drug resistance issues, the development of effective drugs with novel mechanism(s) of action is required. In this regard, drug repurposing is a viable alternative approach to find novel drugs to overcome drug resistance. Therefore, a FDA-approved-drug-library containing 1930 drugs was analyzed against the dihydrofolate reductase (DHFR) of S. Typhi using deep learning regression algorithms. Initially, a total of 500 compounds were screened, followed by rescreening by molecular docking. Further, from screened compounds by molecular docking, the top eight compounds were subjected to molecular dynamics (MD) simulation. Analysis of MD simulation resulted in four potential compounds, namely; Duvelisib, Amenamevir, Lifitegrast and Nilotinib against the DHFR enzyme. During the MD simulation, these four drugs achieved good stability during the 100 ns trajectory period at 300 K. Further to know the insights of the complex's stability, we calculated RMSF, RG, SASA and interaction energy for the last 60 ns trajectory period because all complexes showed the stability after 40 ns trajectory period. MM-PBSA analysis of the last 10 ns of MD trajectories showed the stability of the complexes. From our results, we conclude that these drugs can also be useful for treating typhoid fever and can inhibit S. Typhi by interfering with the function of the DHFR enzyme. Communicated by Ramaswamy H. Sarma.

Identification of natural inhibitors against Mpro of SARS-CoV-2 by molecular docking, molecular dynamics simulation, and MM/PBSA methods.

The recent outbreak of SARS-CoV-2 disease, also known as COVID-19, has emerged as a pandemic. The unavailability of specific therapeutic drugs and vaccines urgently demands sincere efforts for drug discovery against COVID-19. The main protease (Mpro) of SARS-CoV-2 is a critical drug target as it plays an essential role in virus replication. Therefore for the identification of potential inhibitors of SARS-CoV-2 Mpro, we applied a structure-based virtual screening approach followed by molecular dynamics (MD) study. A library of 686 phytochemicals was subjected to virtual screening which resulted in 28 phytochemicals based on binding energy. These phytochemicals were further subjected to drug-likeness and toxicity analysis, which resulted in seven drug-like hits. Out of seven, five phytochemicals viz., Mpro-Dehydrtectol (-10.3 kcal/mol), Epsilon-viniferin (-8.6 kcal/mol), Peimisine (-8.6 kcal/mol), Gmelanone (-8.4 kcal/mol), and Isocolumbin (-8.4 kcal/mol) were non-toxic. Consequently, these phytochemicals are subjected to MD, post MD analysis, and MM/PBSA calculations. The results of 100 ns MD simulation, RMSF, SASA, Rg, and MM/PBSA show that Epsilon-viniferin (-29.240 kJ/mol), Mpro-Peimisine (-43.031 kJ/mol) and Gmelanone (-13.093 kJ/mol) form a stable complex with Mpro and could be used as potential inhibitors of SARS-CoV-2 Mpro. However, further investigation of these inhibitors against Mpro receptor of COVID-19 is needed to validate their candidacy for clinical trials. Communicated by Ramaswamy H. Sarma.

A dynamic simulation study of FDA drug from zinc database against COVID-19 main protease receptor.

The sudden outbreak of COVID-19 has been responsible for several deaths across the globe. Due to its high contagious nature, it spreads from one human to another very quickly. Now it becomes a global public health threat with no approved treatments. In silico techniques can accelerate the drug development process. Our research aimed to identify the novel drugs for inhibition of Main protease (Mpro) enzyme of COVID-19 by performing in silico approach. In this context, a library consisting of 3180 FDA-approved drugs from 'the ZINC database' was used to identify novel drug candidates against 'the Mpro' of SARS-CoV-2. Initially, the top 10 drugs out of 3180 drugs were selected by molecular docking according to their binding score. Among 10 selected drugs; seven drugs that showed binding with Mpro enzyme residue Glu166 were subjected to100 ns Molecular dynamics (MD) simulation. Out of seven compounds, four namely, ZINC03831201, ZINC08101052, ZINC01482077, and ZINC03830817 were found significant based on MD simulation results. Furthermore, RMSD, RMSF, RG, SASA, PCA, MMPBSA (for last 40 ns) were calculated for the 100 ns trajectory period. Currently, the world needs potent drugs in a short period and this work suggests that these four drugs could be used as novel drugs against COVID-19 and it also provides new lead compounds for further in vitro, in vivo, and ongoing clinical studies against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Identification of SARS-CoV-2 RNA dependent RNA polymerase inhibitors using pharmacophore modelling, molecular docking and molecular dynamics simulation approaches.

The RNA-dependent RNA polymerase (RdRp) is one of the crucial enzymes in severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2) catalysing the replication of RNA, therefore acts as a potential target for antiviral drug design. The fixation of a ligand in the active site of RdRp may alter the SARS-CoV-2 life cycle. Present work aimed at identifying novel inhibitors of the SARS-CoV-2 RdRp enzyme by performing pharmacophore-based virtual screening, molecular docking and molecular dynamics simulation (MDS). Initially, the pharmacophore model of SARS-CoV-2 RdRp was constructed and the resulting model was used to screen compounds from ChEMBL, ZINC and PubChem databases. During the investigation, 180 compounds were screened using the above model and subjected to molecular docking with RdRp. Two compounds viz. ChEMBL1276156 and PubChem135548348 showed a strong binding affinity with RdRp than its standard inhibitor, Remdesivir. Toxicity prediction of these two compounds reveals their non-toxic nature. These compounds were further subjected to MDS for 100 ns to check their stability after binding with RdRp. The MDS of RdRp-ChEMBL1276156 and RdRp-PubChem135548348 complexes show enhanced stability in comparison to the RdRp-Remdesivir complex. The average interaction energy calculated after 100 ns of MDS was -146.56 and -172.68 KJ mol-1 for RdRp-CHEMBL1276156 complex and RdRp-PubChem135548348 complex, respectively, while -59.90 KJ mol-1 for RdRp-Remdesivir complex. The current investigation reveals that these two compounds are potent inhibitors of SARS-CoV-2 RdRp and they could be tested in the experimental condition to evaluate their efficacy against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Screening of potential bio-molecules from Moringa olifera against SARS-CoV-2 main protease using computational approaches.

COVID-19 caused by SARS-CoV-2 is responsible for the deaths of millions of people worldwide. It is having devastating effects on the people of all countries. In this regard, the phytochemicals of medicinal plants could be explored to prevent this disease. M. oleifera is a miracle plant with antibacterial, antiviral, and antioxidant properties because of its high content of flavonoids, glucosides and glucosinolates. Therefore, we constructed a library of 294 phytochemicals of M. oleifera and filtered it through the FAF-Drugs4. Further, molecular docking studies of filtered phytochemicals were performed with Mpro enzyme to investigate the binding interactions. Drug likeness properties, ADMET prediction were analyzed to determine the therapeutic aspect of these compounds. Based on the binding energy score of the top 4 compounds, the results indicate that Vicenin-2 has the highest binding affinity (-8.6 kcal mol-1) as compared to the reference molecule (-8.4 kcal mol-1). ADMET result reveals that all top four compounds have minimal toxic effects and good absorption. Further, 500 ns molecular dynamics simulation of the top four compounds showed that Kaempferol-3-O-rutinoside and Vitexin have good stability with Mpro. These two compounds were then subjected for MMPBSA (last 50 ns) calculation to analyze the protein-ligand stability and dynamic behavior. Kaempferol-3-O-rutinoside and Vitexin showed very good binding free energy i.e. -40.136 kJ mol-1 and -26.784 kJ mol-1, respectively. Promising outcomes from MD simulations evidence the worth of these compounds for future drug development to combat coronavirus disease.Communicated by Ramaswamy H. Sarma.

Identification of Berbamine, Oxyacanthine and Rutin from Berberis asiatica as anti-SARS-CoV-2 compounds: An in silico study.

Owing to the shortage of specific medicines, the global pandemic of COVID-19 caused by SARS-CoV-2 has been the greatest challenge for the science community. Researchers from all over the world developed some drugs which failed to completely suppress the contiguous disease. SARS-CoV-2 main protease (Mpro), an important component in viral pathogenesis, is considered as a prospective drug target to stop SARS-CoV-2 infection. Since identification of phytochemicals with anti-Mpro activity has been carried out to develop the potential drugs against SARS-CoV-2. Therefore, the present study was conducted to screen phytochemicals of Berberis asiatica for anti-SARS-CoV-2 activity. Through text mining, thirty phytochemicals were reported from B. asiatica, of which, three phytochemicals (Berbamine, Oxyacanthine, and Rutin) show high affinity with the SARS-CoV-2 Mpro and exhibited favorable intermolecular interactions with the catalytic residues (His41 and Cys145) and other essential residues. The molecular dynamics simulation showed that Mpro-phytochemical complexes are more stable, less fluctuating, more compact, and moderately extended than the Mpro-X77 (Reference) complex. The number of H-bonds and MMPBSA results also demonstrates that Berbamine, Oxyacanthine, and Rutin are potent Mpro inhibitors having free energy of -20.79, -33.35, and -31.12 kcal mol-1 respectively. The toxicity risk prediction supports all phytochemicals for drug-like and non-toxic nature. From the result, we propose that binding of these phytochemicals could hamper the function of Mpro. This work suggests that selected phytochemicals could be used as novel anti-COVID-19 drug candidates, and might act as novel compounds for in vitro and in vivo study.

Molecular docking and molecular dynamics simulation approach to screen natural compounds for inhibition of Xanthomonas oryzae pv. Oryzae by targeting peptide deformylase.

Xanthomonas oryzae pv. Oryzae (Xoo) causes bacterial leaf blight (BLB) of rice which results in a huge loss in production. Many chemicals are used to control BLB disease. However, these chemicals are toxic to the environments, animals and human beings. Thus, there is a demand to discover potential and safe natural pesticides to manage BLB disease successfully. Therefore, we screened a library of phytochemicals of different plants having antibacterial activity by targeting Peptide Deformylase (PDF) of Xoo using in silico techniques. A library of 318 phytochemicals was prepared and subjected to rigid and flexible molecular docking against PDF followed by molecular dynamics simulation and free energy analysis of protein-ligand complexes. The results of virtual screening showed that 14 compounds from different plants have good binding energy as compare to reference molecule (3 R)-2,3-dihydro[1,3] thiazolo [3,2 a]benzimidazol-3-ol) (-7.7 kcal mol-1). Out of 14 hit compounds, eight compounds that were selected based on binding energy were analyzed by Molecular dynamic (MD) simulation. Analysis of MD simulation revealed that eight compounds namely; Bisdemethoxycurcumin, Rosmarinic acid, Piperanine, Dihydropiperlonguminine, Piperdardine, Dihydrocurcumin and Lonhumosides B achieved good stability during the 80 ns MD simulation at 300 K in term of the RMSD. Further, we calculated RMSF, RG, SASA, and interaction energy after 40 ns due to showing the stability of complexes. From our results, we conclude that these natural compounds could inhibit Xoo by targeting PDF receptor and can be used as potential bactericidal candidates against BLB disease of rice against Xoo and other bacteria. Communicated by Ramaswamy H. Sarma.

QSAR modeling and pharmacoinformatics of SARS coronavirus 3C-like protease inhibitors.

The search for effective treatment against novel coronavirus (COVID-19) remains a global challenge due to controversies on available vaccines. In this study, data of SARS coronavirus 3C-like protease (3CLpro) inhibitors; a key drug target in the coronavirus genome was retrieved from CHEMBL database. Quantitative Structure-Activity Relationship (QSAR) studies, Molecular docking, Absorption-Distribution-Metabolism-Excretion-Toxicity (ADMET) and molecular dynamics simulation (MDS) were carried out using these 3CLpro inhibitors. QSAR model constructed using the data had correlation coefficient R2 value of 0.907; cross-validated correlation coefficient Q2 value of 0.866 and test set predicted correlation coefficient R2pred value of 0.517. Variance inflation factor (VIF) values for descriptors contained in the model ranged from 1.352 to 1.68, hence, these descriptors were orthogonal to one another. Therefore, the model was statistically significant and can be used to screen and design new molecules for their inhibitory activity against 3CLpro. Molecular docking showed that seven of the compounds (inhibitors) used in the study had a remarkable binding affinity (-9.2 to -10.3 kcal/mol) for 3CLpro. ADMET study revealed that five (CHEMBL Accession IDs 19438, 196635, 377150, 208763, and 210097) of the seven compounds with good binding ability obeyed Lipinski's rule of five. Hence, they were compounds with drug-like properties. MDS analysis revealed that 3CLpro-compound 21, 3CLpro-compound 22, 3CLpro-compound 40 complexes are very stable as compared to the reference 3CLpro-X77 complex. Therefore, this study identified three potent inhibitors of 3CLpro viz. CHEMBL194398, CHEMBL196635, and CHEMBL210097 that can be further explored for the treatment of COVID-19.

In silico identification of natural fungicide from Melia azedarach against isocitrate lyase of Fusarium graminearum.

Isocitrate Lyase (ICL) is a crucial enzyme involved in the Glyoxylate pathway, essential for the virulence of several fungal pathogens including Fusarium graminearum. ICL is a novel target for the discovery of antifungal compounds and F. graminearum ICL inhibitors can be used to control the growth of this fungus. Although, several inhibitors of ICL have been identified, however, most of these inhibitors are not environment-friendly. Hence there is still a need to discover natural inhibitors of ICL that can be more effective. To identify a potential antifungal compound, we performed a structure-based screening of phytochemicals of Melia azedarach against the FgICL structure by molecular docking and 104 ligands were found to have a better docking score as compared to the reference molecule. These compounds were assessed for drug-likeness and ADMET prediction. After molecular docking, drug-likeness and toxicity analysis, six potential compounds (Melianoninol (-6.6 kcal/mol), Nimbinene (-7.7 kcal/mol), Vilasinin (-8.1 kcal/mol), Fraxinellone (-6.7 kcal/mol), Gedunin (-7.8 kcal/mol), and Meldenin (-7.8 kcal/mol)) were subjected for rescoring by X-Score. The structural stability and dynamics of screened compounds at the active site of FgICL were examined using MD simulation and MM-PBSA analysis. The result of MM-PBSA revealed that four phytochemicals viz. Melianoninol, Nimbinene, Vilasinin, and Fraxinellone had binding free energy of -17.25 kcal/mol, -59.35 kcal/mol, -64.79 kcal/mol, and -29.86 kcal/mol, respectively. Molecular dynamics simulation and MM-PBSA demonstrated that these four phytochemicals displayed considerable significant structural and pharmacological properties and could be probable antifungal drug candidates against F. graminearum. These phyotchemicals of M. azedarach may be suitable candidates for further experimental analysis. [Formula: see text]Communicated by Ramaswamy H. Sarma.

Molecular dynamics simulation for screening phytochemicals as α-amylase inhibitors from medicinal plants.

Diabetes mellitus (DM) is a complicated metabolic disorder with several enzymes, including α-amylase and α-glycosidase. The α-amylase is responsible for postprandial glucose levels; therefore, inhibiting its activity is helpful in diabetes management. Hence, to find natural inhibitors of α-amylase, we have prepared a 257 phytochemical library from selected medicinal plants with antidiabetic activity and conducted a virtual screening and molecular dynamics study. Seventy-nine phytochemicals were screened out of 257 phytochemicals based on binding energy, ranged from -10.1 kcal mol-1 to -7.6 kcal mol-1. The binding energies of screened compounds were lower or equal to the reference molecule (-7.6 kcal mol-1). The binding affinity of six screened phytochemicals was re-scored by X-SCORE. These phytochemicals were subjected to ADMET and Drug-likeness analysis. After screening docking and drug-likeness analysis, six phytochemicals viz., Shahidine, Epicatechin, Quercetin, Isocolumbin, Ellagic acid, Luteolin and a reference molecule (Acarbose) were subjected to Molecular dynamics (MD) simulation to analyze the stability of the docked protein-ligand complex. The values of root mean square deviation, RMSF, RG, SASA, H-Bond, the interaction energy of all protein-ligand complexes were calculated after 30 ns of MD simulation. The results of screened complexes revealed good stability as compared to reference Acarbose. Pharmacophore features of the screened phytochemicals and α-amylase inhibitors showed many common pharmacophore features. Based on finding the screened phytochemicals, e.g. Shahidine, Epicatechin, Quercetin, Isocolumbin, Ellagic acid, and Luteolin, may be used as a potential inhibitors against α-amylase. These phytochemicals could be optimized and synthesized to develop potential drugs to manage and treat diabetes, targeting α-amylase.Communicated by Ramaswamy H. Sarma.

Predictive modeling by deep learning, virtual screening and molecular dynamics study of natural compounds against SARS-CoV-2 main protease.

The whole world is facing a great challenging time due to Coronavirus disease (COVID-19) caused by SARS-CoV-2. Globally, more than 14.6 M people have been diagnosed and more than 595 K deaths are reported. Currently, no effective vaccine or drugs are available to combat COVID-19. Therefore, the whole world is looking for new drug candidates that can treat the COVID-19. In this study, we conducted a virtual screening of natural compounds using a deep-learning method. A deep-learning algorithm was used for the predictive modeling of a CHEMBL3927 dataset of inhibitors of Main protease (Mpro). Several predictive models were developed and evaluated based on R2, MAE MSE, RMSE, and Loss. The best model with R2=0.83, MAE = 1.06, MSE = 1.5, RMSE = 1.2, and loss = 1.5 was deployed on the Selleck database containing 1611 natural compounds for virtual screening. The model predicted 500 hits showing the value score between 6.9 and 3.8. The screened compounds were further enriched by molecular docking resulting in 39 compounds based on comparison with the reference (X77). Out of them, only four compounds were found to be drug-like and three were non-toxic. The complexes of compounds and Mpro were finally subjected to Molecular dynamic (MD) simulation for 100 ns. The MMPBSA result showed that two compounds Palmatine and Sauchinone formed very stable complex with Mpro and had free energy of -71.47 kJ mol-1 and -71.68 kJ mol-1 respectively as compared to X77 (-69.58 kJ mol-1). From this study, we can suggest that the identified natural compounds may be considered for therapeutic development against the SARS-CoV-2.Communicated by Ramaswamy H. Sarma.