scholarly journals Pharmacoinformatics-based identification of transmembrane protease serine-2 inhibitors from Morus Alba as SARS-CoV-2 cell entry inhibitors

2021 ◽  
Author(s):  
Anshul Shakya ◽  
Rupesh V. Chikhale ◽  
Hans Raj Bhat ◽  
Fatmah Ali Alasmary ◽  
Tahani Mazyad Almutairi ◽  
...  
Keyword(s):  
Md Simulation ◽  
Hydrophobic Interactions ◽  
Binding Free Energy ◽  
Surface Protein ◽  
Morus Alba ◽  
Bioactive Molecules ◽  
Chemical Components ◽  
Pharmacokinetic Parameters ◽  
The Stability ◽  
Novel Coronavirus

Abstract Transmembrane protease serine-2 (TMPRSS2) is a cell-surface protein expressed by epithelial cells of specific tissues including those in the aerodigestive tract. It helps the entry of novel coronavirus (n-CoV) or Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in the host cell. Successful inhibition of the TMPRSS2 can be one of the crucial strategies to stop the SARS-CoV-2 infection. In the present study, a set of bioactive molecules from Morus alba Linn. were screened against the TMPRSS2 through two widely used molecular docking engines such as Autodock vina and Glide. Molecules having a higher binding affinity toward the TMPRSS2 compared to Camostat and Ambroxol were considered for in-silico pharmacokinetic analyses. Based on acceptable pharmacokinetic parameters and drug-likeness, finally, five molecules were found to be important for the TMPRSS2 inhibition. A number of bonding interactions in terms of hydrogen bond and hydrophobic interactions were observed between the proposed molecules and ligand-interacting amino acids of the TMPRSS2. The dynamic behavior and stability of best-docked complex between TRMPRSS2 and proposed molecules were assessed through molecular dynamics (MD) simulation. Several parameters from MD simulation have suggested the stability between the protein and ligands. Binding free energy of each molecule calculated through MM-GBSA approach from the MD simulation trajectory suggested strong affection toward the TMPRSS2. Hence, proposed molecules might be crucial chemical components for the TMPRSS2 inhibition. Graphic abstract

Design of potential IKK-β inhibitors using molecular docking and molecular dynamics techniques for their anti-cancer potential

2020 ◽  
Vol 16 ◽  
Author(s):  
Salam Pradeep Singh ◽  
Iftikar Hussain ◽  
Bolin Kumar Konwar ◽  
Ramesh Chandra Deka ◽  
Chingakham Brajakishor Singh
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Md Simulation ◽  
Inflammatory Diseases ◽  
Binding Free Energy ◽  
Anti Cancer ◽  
Dietary Phytochemicals ◽  
Toxicity Analysis ◽  
The Stability ◽  
Stable Trajectory

Aim and Objective: To evaluate a set of seventy phytochemicals for their potential ability to bind the inhibitor of nuclear factor kappaB kinase beta (IKK-β) which is a prime target for cancer and inflammatory diseases. Materials and Methods: Seventy phytochemicals were screened against IKK-β enzyme using DFT-based molecular docking technique and the top docking hits were carried forward for molecular dynamics (MD) simulation protocols. The adme-toxicity analysis was also carried out for the top docking hits. Results: Sesamin, matairesinol and resveratrol were found to be the top docking hits with a total score of -413 kJ/mol, -398.11 kJ/mol and 266.73 kJ/mol respectively. Glu100 and Gly102 were found to be the most common interacting residues. The result from MD simulation observed a stable trajectory with a binding free energy of -107.62 kJ/mol for matairesinol, -120.37 kJ/mol for sesamin and -40.56 kJ/mol for resveratrol. The DFT calculation revealed the stability of the compounds. The ADME-Toxicity prediction observed that these compounds fall within the permissible area of Boiled-Egg and it does not violate any rule for pharmacological criteria, drug-likeness etc. Conclusion: The study interprets that dietary phytochemicals are potent inhibitors of IKK-β enzyme with favourable binding affinity and less toxic effects. In fact, there is a gradual rise in the use of plant-derived molecules because of its lesser side effects compared to chemotherapy. The study has also provided an insight by which the phytochemicals inhibited the IKK-β enzyme. The investigation would also provide in understanding the inhibitory mode of certain dietary phytochemicals in treating cancer.

scholarly journals Conjugated β-Cyclodextrin Enhances the Affinity of Folic Acid towards FRα: Molecular Dynamics Study

Molecules ◽  
2021 ◽  
Vol 26 (17) ◽  
pp. 5304
Author(s):  
Mohammad G. Al-Thiabat ◽  
Amirah Mohd Gazzali ◽  
Noratiqah Mohtar ◽  
Vikneswaran Murugaiyah ◽  
Ezatul Ezleen Kamarulzaman ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Folic Acid ◽  
Root Mean Square ◽  
Active Site ◽  
Md Simulation ◽  
Binding Free Energy ◽  
Cancer Drug ◽  
Radius Of Gyration ◽  
Mean Square ◽  
The Stability

Drug targeting is a progressive area of research with folate receptor alpha (FRα) receiving significant attention as a biological marker in cancer drug delivery. The binding affinity of folic acid (FA) to the FRα active site provides a basis for recognition of FRα. In this study, FA was conjugated to beta-cyclodextrin (βCD) and subjected to in silico analysis (molecular docking and molecular dynamics (MD) simulation (100 ns)) to investigate the affinity and stability for the conjugated system compared to unconjugated and apo systems (ligand free). Docking studies revealed that the conjugated FA bound into the active site of FRα with a docking score (free binding energy < −15 kcal/mol), with a similar binding pose to that of unconjugated FA. Subsequent analyses from molecular dynamics (MD) simulations, root mean square deviation (RMSD), root mean square fluctuation (RMSF), and radius of gyration (Rg) demonstrated that FA and FA–βCDs created more dynamically stable systems with FRα than the apo-FRα system. All systems reached equilibrium with stable RMSD values ranging from 1.9–2.4 Å and the average residual fluctuation values of the FRα backbone atoms for all residues (except for terminal residues ARG8, THR9, THR214, and LEU215) were less than 2.1 Å with a consistent Rg value of around 16.8 Å throughout the MD simulation time (0–100 ns). The conjugation with βCD improved the stability and decreased the mobility of all the residues (except residues 149–151) compared to FA–FRα and apo-FRα systems. Further analysis of H-bonds, binding free energy (MM-PBSA), and per residue decomposition energy revealed that besides APS81, residues HIS20, TRP102, HIS135, TRP138, TRP140, and TRP171 were shown to have more favourable energy contributions in the holo systems than in the apo-FRα system, and these residues might have a direct role in increasing the stability of holo systems.

scholarly journals Drug Repurposing Approach against Novel Coronavirus Disease (COVID-19) through Virtual Screening Targeting SARS-CoV-2 Main Protease

Biology ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 2
Author(s):  
Kamrul Hasan Chowdhury ◽  
Md. Riad Chowdhury ◽  
Shafi Mahmud ◽  
Abu Montakim Tareq ◽  
Nujhat Binte Hanif ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Virtual Screening ◽  
Hydrophobic Interactions ◽  
Binding Free Energy ◽  
Specific Treatment ◽  
Dynamics Simulation ◽  
Experimental Drugs ◽  
Main Protease ◽  
Novel Coronavirus

Novel coronavirus disease (COVID-19) was identified from China in December 2019 and spread rapidly through human-to-human transmission, affecting so many people worldwide. Until now, there has been no specific treatment against the disease and repurposing of the drug. Our investigation aimed to screen potential inhibitors against coronavirus for the repurposing of drugs. Our study analyzed sequence comparison among SARS-CoV, SARS-CoV-2, and MERS-CoV to determine the identity matrix using discovery studio. SARS-CoV-2 Mpro was targeted to generate an E-pharmacophore hypothesis to screen drugs from the DrugBank database having similar features. Promising drugs were used for docking-based virtual screening at several precisions. Best hits from virtual screening were subjected to MM/GBSA analysis to evaluate binding free energy, followed by the analysis of binding interactions. Furthermore, the molecular dynamics simulation approaches were carried out to assess the docked complex’s conformational stability. A total of 33 drug classes were found from virtual screening based on their docking scores. Among them, seven potential drugs with several anticancer, antibiotic, and immunometabolic categories were screened and showed promising MM/GBSA scores. During interaction analysis, these drugs exhibited different types of hydrogen and hydrophobic interactions with amino acid residue. Besides, 17 experimental drugs selected from virtual screening might be crucial for drug discovery against COVID-19. The RMSD, RMSF, SASA, Rg, and MM/PBSA descriptors from molecular dynamics simulation confirmed the complex’s firm nature. Seven promising drugs for repurposing against SARS-CoV-2 main protease (Mpro), namely sapanisertib, ornidazole, napabucasin, lenalidomide, daniquidone, indoximod, and salicylamide, could be vital for the treatment of COVID-19. However, extensive in vivo and in vitro studies are required to evaluate the mentioned drug’s activity.

In silico identification of new anti-SARS-CoV-2 agents from bioactive phytocompounds targeting the viral spike glycoprotein and human TLR4

2021 ◽  
Vol 18 ◽  
Author(s):  
Nabarun Chandra Das ◽  
Rajendra Kumar Labala ◽  
Ritwik Patra ◽  
Asamanja Chattoraj ◽  
Suprabhat Mukherjee
Keyword(s):  
In Silico ◽  
Md Simulation ◽  
Docking Study ◽  
Spike Glycoprotein ◽  
Molecular Docking Study ◽  
S Protein ◽  
Proinflammatory Responses ◽  
Experimental Validations ◽  
The Stability ◽  
Novel Coronavirus

Background: The recent outbreak of novel coronavirus disease (COVID-19) pandemic caused by SARS-CoV-2 has posed a tremendous threat to mankind. The unavailability of a specific drug or vaccine has been the major concern to date. Spike (S) glycoprotein of SARS-CoV-2 plays the most crucial role in the viral infection and immunopathogenesis, and hence this protein appears to be an efficacious target for drug discovery. Objective: Identifying potent bioactive phytocompound that can target viral spike (S) glycoprotein and human TLR4 to reduce immunopathological manifestations of COVID-19. Method: A series of thirty (30) bioactive phytocompounds, previously documented for antiviral activity, were theoretically screened for their binding efficacy against key proteins related to pathogenesis of SARSCoV-2 namely viral spike (S) glycoprotein and human TLR4. MD simulation was employed to verify the postulations of molecular docking study and further ADME analysis was performed to predict the most effective one. Results: Studies hypothesized that two new phytochemicals viz. cajaninstilbene acid (-8.83 kcal/mol) and papaverine (-5.81 kcal/mol) might be the potent inhibitors of spike glycoprotein with stout binding affinity and favourable ADME attributes. MD simulation further ratified the stability of the docked complexes between the phytochemicals and S protein through strong hydrogen bonding. Our in silico data also indicated that cajaninstilbene acid and papaverine might block human TLR4 which could be useful to mitigate SARS-CoV-2-induced lethal proinflammatory responses. Conclusion: Experimental data collectively predict cajaninstilbene acid as the potential blocker of S protein which may be used as anti-viral against COVID-19 in the future. However, further experimental validations alongside toxicological detailing are needed for claiming the candidature of these molecules as future anti-corona therapeutics.

scholarly journals Screening of β1- and β2-Adrenergic Receptor Modulators through Advanced Pharmacoinformatics and Machine Learning Approaches

2021 ◽  
Vol 22 (20) ◽  
pp. 11191
Author(s):  
Md Ataul Islam ◽  
V. P. Subramanyam Rallabandi ◽  
Sameer Mohammed ◽  
Sridhar Srinivasan ◽  
Sathishkumar Natarajan ◽  
...  
Keyword(s):  
Machine Learning ◽  
Md Simulation ◽  
Hydrophobic Interactions ◽  
Learning Approaches ◽  
Ligand Complex ◽  
Pubchem Database ◽  
Pharmacokinetic Assessment ◽  
Β2 Adrenergic Receptor ◽  
The Stability ◽  
Β Adrenergic Receptors

Cardiovascular diseases (CDs) are a major concern in the human race and one of the leading causes of death worldwide. β-Adrenergic receptors (β1-AR and β2-AR) play a crucial role in the overall regulation of cardiac function. In the present study, structure-based virtual screening, machine learning (ML), and a ligand-based similarity search were conducted for the PubChem database against both β1- and β2-AR. Initially, all docked molecules were screened using the threshold binding energy value. Molecules with a better binding affinity were further used for segregation as active and inactive through ML. The pharmacokinetic assessment was carried out on molecules retained in the above step. Further, similarity searching of the ChEMBL and DrugBank databases was performed. From detailed analysis of the above data, four compounds for each of β1- and β2-AR were found to be promising in nature. A number of critical ligand-binding amino acids formed potential hydrogen bonds and hydrophobic interactions. Finally, a molecular dynamics (MD) simulation study of each molecule bound with the respective target was performed. A number of parameters obtained from the MD simulation trajectories were calculated and substantiated the stability between the protein-ligand complex. Hence, it can be postulated that the final molecules might be crucial for CDs subjected to experimental validation.

A comprehensive in silico study towards understanding the inhibitory mechanism of Lactoperoxidase by Dapsone and Propofol

2020 ◽  
Vol 16 ◽  
Author(s):  
Rameez Jabeer Khan ◽  
Rajat Kumar Jha ◽  
Gizachew Muluneh Amera ◽  
Jayaraman Muthukumaran ◽  
Rashmi Prabha Singh ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Md Simulation ◽  
Binding Free Energy ◽  
Protoporphyrin Ix ◽  
Md Simulations ◽  
Prosthetic Group ◽  
Drug Molecules ◽  
Group A ◽  
Complex Forms ◽  
Covalently Linked

Introduction: Lactoperoxidase (LPO) is a member of mammalian heme peroxidase family and is an enzyme of innate immune system. It possesses a covalently linked heme prosthetic group (a derivative of protoporphyrin IX) in its active site. LPO catalyzes the oxidation of halides and pseudohalides in the presence of hydrogen peroxide (H2O2) and shows a broad range of antimicrobial activity. Methods: In this study, we have used two pharmaceutically important drug molecules, namely dapsone and propofol, which are earlier reported as potent inhibitors of LPO. Whereas the stereochemistry and mode of binding of dapsone and propofol to LPO is still not known because of the lack of the crystal structure of LPO with these two drugs. In order to fill this gap, we utilized molecular docking and molecular dynamics (MD) simulation studies of LPO in native and complex forms with dapsone and propofol. Results: From the docking results, the estimated binding free energy (ΔG) of -9.25 kcal/mol (Ki = 0.16 μM) and -7.05 kcal/mol (Ki = 6.79 μM) was observed for dapsone, and propofol, respectively. The standard error of Auto Dock program is 2.5 kcal/mol; therefore, molecular docking results alone were inconclusive. Conclusion: To further validate the docking results, we performed MD simulation on unbound, and two drugs bounded LPO structures. Interestingly, MD simulations results explained that the structural stability of LPO-Propofol complex was higher than LPO-Dapsone complex. The results obtained from this study establish the mode of binding and interaction pattern of the dapsone and propofol to LPO as inhibitors.

scholarly journals High-throughput screening of natural compounds and inhibition of a major therapeutic target HsGSK-3β for Alzheimer’s disease using computational approaches

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Rohit Shukla ◽  
Tiratha Raj Singh
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
High Throughput Screening ◽  
Complex Disease ◽  
Glycogen Synthase ◽  
Binding Free Energy ◽  
Drug Candidate ◽  
Pharmacokinetic Analysis ◽  
Pharmacokinetic Parameters ◽  
Computational Approaches

Abstract Background Alzheimer’s disease is a leading neurodegenerative disease worldwide and is the 6th leading cause of death in the USA. AD is a very complex disease and the drugs available in the market cannot fully cure it. The glycogen synthase kinase 3 beta plays a major role in the hyperphosphorylation of tau protein which forms the neurofibrillary tangles which is a major hallmark of AD. In this study, we have used a series of computational approaches to find novel inhibitors against GSK-3β to reduce the TAU hyperphosphorylation. Results We have retrieved a set of compounds (n=167,741) and screened against GSK-3β in four sequential steps. The resulting analysis of virtual screening suggested that 404 compounds show good binding affinity and can be employed for pharmacokinetic analysis. From here, we have selected 20 compounds those were good in terms of pharmacokinetic parameters. All these compounds were re-docked by using Autodock Vina followed by Autodock. Four best compounds were employed for MDS and here predicted RMSD, RMSF, Rg, hydrogen bonds, SASA, PCA, and binding-free energy. From all these analyses, we have concluded that out of 167,741 compounds, the ZINC15968620, ZINC15968622, and ZINC70707119 can act as lead compounds against HsGSK-3β to reduce the hyperphosphorylation. Conclusion The study suggested three compounds (ZINC15968620, ZINC15968622, and ZINC70707119) have great potential to be a drug candidate and can be tested using in vitro and in vivo experiments for further characterization and applications.

scholarly journals On the optimal control of coronavirus (2019-nCov) mathematical model; a numerical approach

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
N. H. Sweilam ◽  
S. M. Al-Mekhlafi ◽  
A. O. Albalawi ◽  
D. Baleanu
Keyword(s):  
Mathematical Model ◽  
Optimal Control ◽  
Weighted Average ◽  
Necessary Optimality Conditions ◽  
Numerical Approach ◽  
Population Number ◽  
Infected People ◽  
The Stability ◽  
Novel Coronavirus ◽  
Theoretical Results

Abstract In this paper, a novel coronavirus (2019-nCov) mathematical model with modified parameters is presented. This model consists of six nonlinear fractional order differential equations. Optimal control of the suggested model is the main objective of this work. Two control variables are presented in this model to minimize the population number of infected and asymptotically infected people. Necessary optimality conditions are derived. The Grünwald–Letnikov nonstandard weighted average finite difference method is constructed for simulating the proposed optimal control system. The stability of the proposed method is proved. In order to validate the theoretical results, numerical simulations and comparative studies are given.

Docking, Binding Free Energy Estimation, and MD Simulation of Newly Designed CQ and HCQ Analogues Against the Spike-ACE2 Complex of SARS-CoV-2

2021 ◽  
Vol 6 (4) ◽  
pp. 77-89
Author(s):  
Anjoomaara H. Patel ◽  
Riya B. Patel ◽  
MahammadHussain J. Memon ◽  
Samiya S. Patel ◽  
Sharav A. Desai ◽  
...  
Keyword(s):  
Free Energy ◽  
Md Simulation ◽  
Binding Free Energy ◽  
Docking Studies ◽  
Radius Of Gyration ◽  
Ligand Interaction ◽  
Energy Estimation ◽  
Efficacious Treatment ◽  
Protein Ligand Interaction ◽  
Derivatives Of

The coronavirus disease 2019 (COVID-19) virus has been spreading rapidly, and scientists are endeavouring to discover drugs for its efficacious treatment. Chloroquine phosphate, an old drug for treatment of malaria, has shown to have apparent efficacy and acceptable safety against COVID-19. As a part of Drug Discovery Hackathon-2020, in this study, the authors have tried making the derivatives of CQ and HCQ using MarvinSketch by ChemAxon. Molecular docking studies of these ligands were performed using Glide by Schrodinger, and ADME profiles were obtained by using QikProp. The obtained results after data analysis demonstrated that ligands HCQ_imidazoll, choloroquine_3c, HCQ_pyrrolC had good binding affinity and complied with all the ADME parameters. The molecular dynamic simulation of these ligands in complex with the 2019-nCoV RBD/ACE-2-B0AT1 complex PDB ID: 6M17 were carried out, and the parameters like RMSD, RMSF, and radius of gyration were observed to understand the fluctuations and protein-ligand interaction.

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