RMSF Analysis Research Articles

Soyasapogenol-B as a Potential Multitarget Therapeutic Agent for Neurodegenerative Disorders: Molecular Docking and Dynamics Study.

Neurodegenerative disorders involve various pathophysiological pathways, and finding a solution for these issues is still an uphill task for the scientific community. In the present study, a combination of molecular docking and dynamics approaches was applied to target different pathways leading to neurodegenerative disorders such as Alzheimer’s disease. Initially, abrineurin natural inducers were screened using physicochemical properties and toxicity assessment. Out of five screened compounds, a pentacyclic triterpenoid, i.e., Soyasapogenol B appeared to be the most promising after molecular docking and simulation analysis. Soyasapogenol B showed low TPSA (60.69), high absorption (82.6%), no Lipinski rule violation, and no toxicity. Docking interaction analysis revealed that Soyasapogenol B bound effectively to all of the targeted proteins (AChE, BuChE MAO-A, MAO-B, GSK3β, and NMDA), in contrast to other screened abrineurin natural inducers and inhibitors. Importantly, Soyasapogenol B bound to active site residues of the targeted proteins in a similar pattern to the native ligand inhibitor. Further, 100 ns molecular dynamics simulations analysis showed that Soyasapogenol B formed stable complexes against all of the targeted proteins. RMSD analysis showed that the Soyasapogenol B–protein complex exhibited average RMSD values of 1.94 Å, 2.11 Å, 5.07 Å, 2.56 Å, 3.83 Å and 4.07 Å. Furthermore, the RMSF analysis and secondary structure analysis also indicated the stability of the Soyasapogenol B–protein complexes.

Evaluation of Cyc1 protein stability in Acidithiobacillus ferrooxidans bacterium after E121D mutation by molecular dynamics simulation to improve electron transfer.

Cyc1 (Cytochrome c552) is a protein in the electron transport chain of the Acidithiobacillus ferrooxidans (Af) bacteria which obtain their energy from oxidation Fe2+ to Fe3+. The electrons are directed through Cyc2, RCY (rusticyanin), Cyc1 and Cox aa3 proteins to O2. Cyc1 protein consists of two chains, A and B. In the present study, a novel mutation (E121D) in the A chain of Cyc1 protein was selected due to electron receiving from Histidine 143 of RCY. Then, the changes performed in the E121D mutant were evaluated by MD simulations analyzes. Cyc1 and RCY proteins were docked by a Patchdock server. By E121D mutation, the connection between Zn 1388 of chain B and aspartate 121 of chain A weaken. Asp 121 gets farther from Zn 1388. Therefore, the aspartate gets closer to Cu 1156 of the RCY leading to the higher stability of the RCY/Cyc1 complex. Further, an acidic residue (Glu121) becomes a more acidic residue (Asp121) and improves the electron transfer to Cyc1 protein. The results of RMSF analysis showed further ligand flexibility in mutation. This leads to fluctuation of the active site and increases redox potential at the mutation point and the speed of electron transfer. This study also predicts that in all respiratory chain proteins, electrons probably enter the first active site via glutamate and exit histidine in the second active site of each respiratory chain protein.

Inhibitory effect of compounds extracted from Monochoria hastata (L.) Solms on SARS-CoV-2 main protease: An insight from molecular docking and MD-simulation studies

Using molecular docking and other studies, 20 compounds extracted from Monochoria hastata (L.) Solms were screened, and their inhibitory efficiency examined against main protease (3CLpro) of SARS CoV-2. All the compounds were found to binding with 3CLpro through van der Waals and electrostatic forces of attractions. Among them, Azelaic dihydrazide (ADZ) was found to have the highest docking score. 3CLpro-ADZ complex was studied by MD simulation. ADZ was found to disrupt the structure of 3CLpro after 2 ns. RMSD and RMSF analysis along with sequence and binding energy analysis suggest that ADZ can be a potential drug against SARS CoV-2.

Computational Simulations Highlight the IL2Rα Binding Potential of Polyphenol Stilbenes from Fenugreek.

Widely used in global households, fenugreek is well known for its culinary and medicinal uses. The various reported medicinal properties of fenugreek are by virtue of the different natural phytochemicals present in it. Regarded as a promising target, interleukin 2 receptor subunit alpha (IL2Rα) has been shown to influence immune responses. In the present research, using in silico techniques, we have demonstrated the potential IL2Rα binding properties of three polyphenol stilbenes (desoxyrhaponticin, rhaponticin, rhapontigenin) from fenugreek. As the first step, molecular docking was performed to assess the binding potential of the fenugreek phytochemicals with IL2Rα. All three phytochemicals demonstrated interactions with active site residues. To confirm the reliability of our molecular docking results, 100 ns molecular dynamics simulations studies were undertaken. As discerned by the RMSD and RMSF analyses, IL2Rα in complex with the desoxyrhaponticin, rhaponticin, and rhapontigenin indicated stability. The RMSD analysis of the phytochemicals alone also demonstrated no significant structural changes. Based on the stable molecular interactions and comparatively slightly better MM/PBSA binding free energy, rhaponticin seems promising. Additionally, ADMET analysis performed for the stilbenes indicated that all of them obey the ADMET rules. Our computational study thus supports further in vitro IL2Rα binding studies on these stilbenes, especially rhaponticin.

Unraveling the possible inhibitors for Chorismate synthase to combat tuberculosis using in silico approach

Tuberculosis antibiotic resistance is a huge concern to the global population. The goal of this study was to find new and effective compounds to treat multidrug-resistant tuberculosis by targeting Chorismate synthase (CS), a crucial enzyme for Mycobacterium tuberculosis survival (MbT). The potential of a library of compounds as selective anti - tuberculosis drugs was investigated. Docking was first conducted using MoE to determine the effectiveness of the compounds. Molecular docking studies followed by MD simulation studies (total of 500 ns) in combination with free energy calculations grade the ligands in terms of their binding affinities. In the ligand bound state of the CS, MD simulations revealed a change from stretched to bended motional shift in loop L19. The RMSF analysis also revealed this flexibility, which was confirmed by visual inspection of L19 at various time intervals during the experiment. It appears that ZF1(-25.43Kcal/mol) and ZF2 (-22.04Kcal/mol) form hbonds and have a high binding energy in the active region of protein. Residues wise distribution of binding energy reveals that Arg144, Trp4, Thr6, and L19 amino acid residues are engaged in binding of CS with inhibitors. In summary, the findings suggest that compounds ZF1 and ZF2 may be more effective and selective anti-TB agents than currently available drugs. Also the role of L19, mediated by αH9 and αH5 in the retention of ligand inside the active pocket, through the formation of lid was also revealed. This knowledge will aid in the discovery of drugs that are potent CS inhibitors. More experimental research and a better understanding of the structure-activity relationship could aid in the development of possible candidates with better CS inhibition. Communicated by Ramaswamy H. Sarma

In Silico Drug Repurposing Approach: Investigation of Mycobacterium tuberculosis FadD32 Targeted by FDA-Approved Drugs.

Background: Despite the enormous efforts made towards combating tuberculosis (TB), the disease remains a major global threat. Hence, new drugs with novel mechanisms against TB are urgently needed. Fatty acid degradation protein D32 (FadD32) has been identified as a promising drug target against TB, the protein is required for the biosynthesis of mycolic acids, hence, essential for the growth and multiplication of the mycobacterium. However, the FadD32 mechanism upon the binding of FDA-approved drugs is not well established. Herein, we applied virtual screening (VS), molecular docking, and molecular dynamic (MD) simulation to identify potential FDA-approved drugs against FadD32. Methodology/Results: VS technique was found promising to identify four FDA-approved drugs (accolate, sorafenib, mefloquine, and loperamide) with higher molecular docking scores, ranging from −8.0 to −10.0 kcal/mol. Post-MD analysis showed that the accolate hit displayed the highest total binding energy of −45.13 kcal/mol. Results also showed that the accolate hit formed more interactions with FadD32 active site residues and all active site residues displayed an increase in total binding contribution. RMSD, RMSF, Rg, and DCCM analysis further supported that the presence of accolate exhibited more structural stability, lower bimolecular flexibility, and more compactness into the FadD32 protein. Conclusions: Our study revealed accolate as the best potential drug against FadD32, hence a prospective anti-TB drug in TB therapy. In addition, we believe that the approach presented in the current study will serve as a cornerstone to identifying new potential inhibitors against a wide range of biological targets.

Consensus scoring-based virtual screening and molecular dynamics simulation of some TNF-alpha inhibitors

Inhibition of Tumor Necrosis Factor-alpha (TNF-alpha) represents a therapeutic approach towards the management or treatment of various inflammatory diseases like rheumatoid arthritis and cancer, but the current treatment regimen against this target in these diseases is the use of antibodies which may trigger an autoimmune response. This suggests a search for small-molecule inhibitors that could selectively inhibit the protein target. In the present study, fifty-five bioactive compounds of plant origin with already reported anti-inflammatory activities were screened for their affinity for TNF-alpha using a molecular docking strategy. We combined results from three different software packages (iGEMDOCK, MOE, & SAMSON) to come up with the best binders of the target. In addition, the resulting binders were subjected to in silico ADMET (Absorption, distribution, metabolism, excretion, and toxicity) and 100 ns molecular dynamics simulation to determine their drug-like properties and atomistic binding mechanisms respectively. Of the fifty-five evaluated bioactive compounds, Rutin, Schisantherin A, and Hesperidin performed well in the three software packages, with considerable ranking therewith. Interestingly, these compounds did not only interact with hotspot residues on TNF-alpha but also apparently balanced well on the knife-edge of pharmacokinetics and toxicity. More importantly, from the RMSD, RMSF, ROG, SASA, and hydrogen bond analysis, it was seen that Rutin, Schisantherin A, & Hesperidin exhibited stability in the active pocket of the protein. These results portend the three compounds as potent inhibitors of TNF-alpha that should be considered for further evaluation and drug development.

Identifying the analogues of berberine as promising antitubercular drugs targeting Mtb-FtsZ polymerisation through ligand-based virtual screening and molecular dynamics simulations.

Berberine, an active compound in the extract of golden seal (an age-long remedy for many infections) has been confirmed to be responsible for the extract's activity against multi-drug resistant strain of Mycobacterium tuberculosis. There is no available study that shows the exact target of berberine in M tuberculosis, although it is confirmed that berberine inhibits the polymerisation of filamentous temperature-sensitive mutant Z (FtsZ), an important bacteria cytokinesis protein, in Escherichia coli, suggesting that FtsZ could as well be the target of berberine in M tuberculosis. In this study, we carried out ligand-based virtual screening to identify analogues of berberine followed by molecular dynamics (MD) simulations of the complexes of Mtb-FtsZ with berberine (berb1) and the five selected analogues (berb9 [ZINC1709414], berb37 [ZINC238749993], berb38 [ZINC13509022], berb43 [ZINC14765594], and berb48 [ZINC238758595]). Post-MD analyses such as binding free energy, RMSD, RMSF, RoG and hydrogen bond lifetime analysis were used to understand the interactions between these ligands and the receptor. The results suggested that Mtb-FtsZ could likely be the target of berberine in M tuberculosis as it forms a stable complex coupled with a significantly high binding energy. The study also identified other potential inhibitors of MTB-FtsZ polymerisation. Berb38 specifically showed greater interaction with the residues at the binding site of the protein, forming a far more stable complex with the receptor than any of the other compounds under investigation, including berberine itself. ADME properties calculations also predicted all the ligands to be bioactive as orally administered drugs.

Conformational exploration of RbgA using molecular dynamics: Possible implications in ribosome maturation and GTPase activity in different nucleotide bound states

Ribosome biogenesis GTPase A (RbgA) is involved in the late steps of the 50S ribosomal subunit maturation by binding into the 45S pre-ribosomal subunit. The association of RbgA to the 45S intermediate subunit depends on its bound nucleotide (GTP/GDP), probably because of the conformational shifts that occur between the GTP and GDP bound states. However, the available crystal structures of Staphylococcus aureus RbgA (SaRbgA) do not show any significant variations between different nucleotide bound states. Therefore, conformational exploration of SaRbgA in different nucleotide bound states was carried out using all-atom molecular dynamics (MD) simulations. Exploration of conformational distribution using cluster analysis and principal component analysis (PCA) revealed that GDP and pppGpp bound systems exhibit a larger distribution. This is majorly due to the fluctuations of the C-terminal tail (C-tail) as a result of the unwinding of α-helical secondary conformations into loop conformations which are observed from RMSF and DSSP analyses. Further investigation of the network of interactions revealed that the GTP and GMPPNP bound systems hold the C-tail in an α-helical form through stronger interactions between the active-site and C-tail. We also find that the presence of Mg2+ positions Sw-I loop away from the bound nucleotide and stabilizes the active-site water molecules. This seems to assist SaRbgA GTPase activity. In addition, mutations at the C-terminal and Sw-II conserved residues exhibit a larger conformational distribution majorly due to the C-tail fluctuations suggesting that the C-tail of SaRbgA probably interacts with the rRNA or rprotein in the process of ribosome biogenesis.

Molecular docking, DFT analysis, and dynamics simulation of natural bioactive compounds targeting ACE2 and TMPRSS2 dual binding sites of spike protein of SARS CoV-2

The scientific community is continuously working to discover drug candidates against potential targets of SARS-CoV-2, but effective treatment has not been discovered yet. The virus enters the host cell through molecular interaction with its enzymatic receptors i.e., ACE2 and TMPRSS2, which, if, synergistically blocked can lead to the development of novel drug candidates. In this study, 1503 natural bioactive compounds were screened by HTVS, followed by SP and XP docking using Schrodinger Maestro software. Bio-0357 (protozide) and Bio-597 (chrysin) were selected for dynamics simulation based on synergistic binding affinity on S1 (docking score −9.642 and −8.78 kcal/mol) and S2 domains (-5.83 and −5.3 kcal/mol), and the RMSD, RMSF and Rg analyses showed stable interaction. The DFT analysis showed that the adsorption of protozide/chrysin, the band gap of protozide/chrysin-F/G reduced significantly. From SERS, results, it can be concluded that QDs nanocluster will act as a sensor for the detection of drugs. The docking study showed Bio-0357 and Bio-0597 bind to both S1 and S2 domains through stable molecular interactions, which can lead to the discovery of new drug candidates to prevent the entry of SARS-CoV-2. This in-silico study may be helpful to researchers for further in vitro experimental validation and development of new therapy for COVID-19.

Modeling the structural and reactivity properties of hydrazono methyl-4H-chromen-4-one derivatives—wavefunction-dependent properties, molecular docking, and dynamics simulation studies

This study explains the vibration and interaction of three pharmaceutically active hydrazine derivatives, (E)-3-((2-(2,5-difluorophenyl)hydrazono)methyl)-4H-chromen-4-one (DFH), (E)-3-((2-(4-(trifluoromethyl)phenyl)hydrazono)methyl)-4H-chromen-4-one (TMH), and (E)-3-((2-(3,5-bis(trifluoromethyl)phenyl)hydrazono)methyl)-4H-chromen-4-one (BPH) using theoretical approach. The trend in chemical reactivity and stability of the studied compounds was observed to show increasing stability and decreasing reactivity and this was obtained from orbital energies. The effect of bromine and chlorine atoms, instead of fluorine atoms, is also noted. Surface analysis on the covalent bond was attained by ELF and LOL analysis. Biological activities were predicted using molecular docking studies. Docking results were analyzed with standard drugs, 5-fluorouracil/piperine. Antitumor activity of hydrazine derivatives was found to be higher than reference ones. Molecular dynamics (MD) simulation was performed for 100ns to validate the stability behavior of hydrazine derivatives with the dual specificity threonine tyrosine kinase (TTK) protein. RMSD, RMSF, Rg, SASA, and intermolecular analysis of DFH, TMH, and BPH with threonine tyrosine kinase forms stable ligand-protein interactions. The molecular and predictive biological properties of three pharmaceutically active hydrazine derivatives which can be helpful to researchers in future experimental validation through in vitro and in vivo studies.

DFT, docking, MD simulation, and vibrational spectra with SERS analysis of a benzoxazole derivative: an anti-cancerous drug

Spectroscopic, DFT, and SERS studies of antimicrobial bioactive 2-(p-bromophenyl)-5-(2-(4-(p-chlorophenyl)piperazine-1-yl)acetamido)benzoxazole (BCAB) have been reported. Very large changes are seen wavenumbers in Raman and SERS. Variations in modes may be due to surface π-electron interactions and means, the BACB is inclined with respect to the metal surface. Theoretical molecular geometry optimization parameters, wavenumbers, frontier molecular orbitals, and molecular electrostatic potential surface have been calculated using density functional theory. The docked ligand forms a stable complex with SOCS-2 and can be BCAB may be an anti-cancerous drug. According to RMSD, RMSF, and Rg analysis, BACB and SOCS-2 protein form a stable and stable interaction.

The binding mechanism of ivermectin and levosalbutamol with spike protein of SARS-CoV-2.

In this study, we have investigated the binding mechanism of two FDA-approved drugs (ivermectin and levosalbutamol) with the spike protein of SARs-CoV-2 using three different computational modeling techniques. Molecular docking results predict that ivermectin shows a large binding affinity for spike protein (− 9.0 kcal/mol) compared to levosalbutamol (− 4.1 kcal/mol). Ivermectin binds with LEU492, GLN493, GLY496, and TRY505 residues in the spike protein through hydrogen bonds and levosalbutamol binds with TYR453 and TYR505 residues. Using density functional theory (DFT) studies, we have calculated the binding energies between ivermectin and levosalbutamol with residues in spike protein which favor their binding are − 22.4 kcal/mol and − 21.08 kcal/mol, respectively. The natural bond orbital (NBO) charge analysis has been performed to estimate the amount of charge transfer that occurred by two drugs during interaction with residues. Molecular dynamics (MD) study confirms the stability of spike protein bound with ivermectin through RMSD and RMSF analyses. Three different computer modeling techniques reveal that ivermectin is more stable than levosalbutamol in the active site of spike protein where hACE2 binds. Therefore, ivermectin can be a suitable inhibitor for SARS-CoV-2 to enter into the human cell through hACE2.

The identification of novel inhibitors of human angiotensin-converting enzyme 2 and main protease of Sars-Cov-2: A combination of in silico methods for treatment of COVID-19

The angiotensin-converting enzyme 2 (ACE2) and main protease (MPro), are the putative drug candidates for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we performed 3D-QSAR pharmacophore modeling and screened 1,264,479 ligands gathered from Pubchem and Zinc databases. Following the calculation of the ADMET properties, molecular docking was carried out. Moreover, the de novo ligand design was performed. MD simulation was then applied to survey the behavior of the ligand-protein complexes. Furthermore, MMPBSA has utilized to re-estimate the binding affinities. Then, a free energy landscape was used to find the most stable conformation of the complexes. Finally, the hybrid QM-MM method was carried out for the precise calculation of the energies.The Hypo1 pharmacophore model was selected as the best model. Our docking results indicate that the compounds ZINC12562757 and 112,260,215 were the best potential inhibitors of the ACE2 and MPro, respectively. Furthermore, the Evo_1 compound enjoys the highest docking energy among the designed de novo ligands. Results of RMSD, RMSF, H-bond, and DSSP analyses have demonstrated that the lead compounds preserve the stability of the complexes’ conformation during the MD simulation. MMPBSA data confirmed the molecular docking results. The results of QM-MM showed that Evo_1 has a stronger potential for specific inhibition of MPro, as compared to the 112,260,215 compound.

Theoretical investigation on the reactive and interaction properties of sorafenib – DFT, AIM, spectroscopic and Hirshfeld analysis, docking and dynamics simulation

Hepatocellular carcinoma is one of the severe types of malignancy characterized by rapid tumor growth and is mostly found in the last stage of very advanced tumor formation. In this manuscript, we present the gross structural features of sorafenib and its reactivity and wavefunction properties using computational simulations. Density functional theory was used to optimize the ground state geometry and docking was used to predict biological activity. Various intermolecular interactions are analyzed and reaction sites for attacking electrophiles and nucleophiles identified. The calculated values of electron density, Laplacian and ellipticity for all bonds designated the formation of an ionic or covalent bond. Regions between carbon and nitrogen have high LOL values showing covalent bond nature. Molecular docking and dynamics simulations studies show that from the binding energy, RMSD, RMSF and Rg analysis of sorafenib and multidrug resistance-associated protein 1 forms a stable and stable interaction.

Investigation of Cyc1 protein structure stability after H53I mutation using computational approaches to improve redox potential

Acidithiobacillus ferrooxidans (Af) is an acidophilic bacterium that grows in rigid surroundings and gets its own energy from the oxidation of Fe2+ to Fe3+. These bacteria are involved in the bioleaching process. Cyc1 is a periplasmic protein with a crucial role in electron transportation in the respiratory chain. His53 of the Cyc1 protein, involved in electron transfer to CoxB, was selected for mutation and bioinformatics studies. His53 was substituted by Ile using PyMol software. Molecular dynamics simulations were performed for wild and mutant types of Cyc1 protein. The conformational changes of mutated protein were studied by analyzing RMSD, RMSF, SASA, Rg, H Bond, and DSSP. The results of the RMSF analysis indicated an increase in the flexibility of the ligand in the mutant. Finally, active site instability leads to an increase in the value of E0 at the mutation point and improving electron transfer. On the other, His53 in Cyc1 is interconnected to Glu126 in CoxB through the water molecule (W76) and hydrogen bonding. In the H53I mutation, there was a decrease in the distance between H2O 2030, 2033, and isoleucine 53, and subsequently, the distance to the water molecule 76 between the two proteins was reduced and strengthens the hydrogen bond between Cyc1 and CoxB, finally improves electron transfer and the bioleaching process.

Computational identification of potential lead molecules targeting rho receptor of Neisseria gonorrhoeae

Gonorrhea, one of the sexually transmitted disease caused by a gram negative diplococcus bacteria Neisseria gonorrhoeae. Rho protein is indispensable for bacterial viability due to its versatile functions in physiology apart from RNA dependent transcription termination. Based on conserved function and wider role in several cellular processes, inhibitors specifically targeting Rho proteins are largely in use these days to treat various bacterial infections. In this study, three dimensional structure of Rho protein was modeled using the template protein from E. coli and further the optimized model was simulated for 100 ns to understand the structural stability and compactness. Owing to the therapeutic potential of Rho, traditional structure-based virtual screening was applied to identify potential inhibitors for the selected target. Based on empirical glide scoring functions two potent lead molecules (ChemBridge_6121956 and ChemBridge_5232688) were selected from ChemBridge database. The pharmacokinetic properties of these lead molecules are within the permissible range. DFT descriptor revealed that the lead molecules are more reactive, which also supports the molecular docking studies. The stability of Rho and Rho-inhibitor complexes was studied using molecular dynamics simulation. Parameters include binding free energy calculation, RMSD, RMSF and hydrogen bond analysis depicts the stability of Rho and Rho-inhibitors throughout the simulation. Altogether, the identified lead molecules require further optimization towards the design and development of new antibiotics against N. gonorrhoeae. Communicated by Ramaswamy H. Sarma

Molecular modelling of quinoline derivatives as telomerase inhibitors through 3D-QSAR, molecular dynamics simulation, and molecular docking techniques

Rising mortality due to cancer has led to the development and identification of newer targets and molecules to cure the disease. Telomerase is one of the attractive targets for design of many chemotherapeutic drugs. This research highlights the designing of novel telomerase inhibitors using ligand-based (3D-QSAR) and structure-based (molecular docking and molecular dynamics simulation) approaches. For the development of the 3D-QSAR model, 37 synthetic molecules reported earlier as telomerase inhibitors were selected from diversified literature. Three different alignment methods were explored; among them, distill alignment was found to be the best method with good statistical results and was used for the generation of QSAR model. Statistically significant CoMSIA model with a correlation coefficient (r2ncv) value of 0.974, leave one out (q2) value of 0.662 and predicted correlation coefficient (r2pred) value of 0.560 was used for the analysis of QSAR. For the MDS study, A-chain of telomerase was stabilised for 50 ns with respect to 1-atm pressure, with an average temperature of 299.98 k and with potential energy of 1,145,336 kJ/m converged in 997 steps. Furthermore, the behaviour study of variants towards the target revealed that active variable gave better affinity without affecting amino acid sequences and dimensions of protein which was accomplished through RMSD, RMSF and Rg analysis. Results of molecular docking study supported the outcomes of QSAR contour maps as ligand showed similar interactions with surrounded amino acids which were identified in contour map analysis. The results of the comprehensive study might be proved valuable for the development of potent telomerase inhibitors.

Computational prediction of nimbanal as potential antagonist of respiratory syndrome coronavirus.

The high pathogenic nature of the Middle East Respiratory coronavirus (MER) and the associated high fatality rate demands an urgent attention from researchers. Because there is currently no approved drug for the management of the disease, research efforts have been intensified towards the discovery of a potent drug for the treatment of the disease. Papain Like protease (PLpro) is one of the key proteins involved in the viral replication. We therefore docked forty-six compounds already characterized from Azadirachta indica, Xylopia aethipica and Allium cepa against MERS-CoV-PLpro.The molecular docking analysis was performed with AutoDock 1.5.6 and compounds which exhibit more negative free energy of binding, and low inhibition constant (Ki) with the protein (MERS-CoV-PLpro) were considered potent. The physicochemical and pharmacokinetic properties of the compounds were predicted using the Swissadme web server.Twenty-two of the compounds showed inhibition potential similar to dexamethasone and remdesvir, which had binding affinity of −6.8 and −6.3 kcal/mol respectively. The binding affinity of the compounds ranged between −3.4 kcal/mol and −7.7 kcal/mol whereas; hydroxychloroquine had a binding affinity of −4.5 kcal/mol. Among all the compounds, nimbanal and verbenone showed drug likeliness, they did not violate the Lipinski rule neither were they inhibitors of drug-metabolizing enzymes. Both nimbanal and verbenone were further post-scored with MM/GBSA and the binding free energy of nimbanal (−25.51 kcal/mol) was comparable to that of dexamethasone (−25.46 kcal/mol). The RMSD, RMSF, torsional angle, and other analysis following simulation further substantiate the efficacy of nimbanal as an effective drug candidate. In conclusion, our study showed that nimbanal is a more promising therapeutic agent and could be a lead for the discovery of a new drug that may be useful in the management of severe respiratory coronavirus syndrome.

Effect of nelfinavir stereoisomers on coronavirus main protease: Molecular docking, molecular dynamics simulation and MM/GBSA study

In this study, the binding strength of 32 diastereomers of nelfinavir, a proposed drug for the treatment of COVID-19, was considered against main protease. Molecular docking was used to determine the most potent diastereomers. The top three diastereomers along with apo form of protein were then considered via molecular dynamics simulation and MM-GBSA method. During the simulation, the structural consideration of four proteins considered was carried out using RMSD, RMSF, Rg and hydrogen bond analysis tools. Our data demonstrated that the effect of nelfinavir RSRSR stereoisomer on protein stability and compactness is higher than the other. We also found from the hydrogen bond analysis that this important diastereomer form three hydrogen bonds with the residues of Glu166, Gly143 and Hie41. MM/GBSA analysis showed that the binding strength of RSRSR is more than other stereoisomers and that the main contributions to binding energy are vdW and electronic terms. The nelfinavir RSRSR stereoisomer introduced in this study may be effective in the treatment of COVID-19.