scholarly journals In silico identification of novel chemical compounds with anti-TB potential for the inhibition of InhA and EthR from Mycobacterium tuberculosis

2020 ◽  
Author(s):  
Sajal Kumar Halder ◽  
Fatiha Elma
Keyword(s):  
Molecular Dynamics ◽  
Mycobacterium Tuberculosis ◽  
Molecular Docking ◽  
Molecular Dynamics Simulation ◽  
Chemical Compounds ◽  
Dynamics Simulation ◽  
Health Concern ◽  
Radius Of Gyration

ABSTRACTTuberculosis (TB) continuously pose a major public health concern around the globe, with a mounting death toll of approximately 1.4 million in 2019. The reduced bioavailability, increased toxicity and resistance of several first-line and second-line anti-TB drugs such as isoniazid, ethionamide have necessitated the search for new medications. In this research, we have identified several novel chemical compounds with anti-TB properties using various computational tools like molecular docking analysis, drug-likeness evaluation, ADMET profiling, P450 site of metabolism prediction and molecular dynamics simulation study. This study involves fifty drug-like compounds with antibacterial activity that inhibit InhA and EthR involved in the synthesis of one of the major lipid components, mycolic acid, which is crucial for the viability of Mycobacterium tuberculosis. Among these fifty compounds, 3-[3-(4-Fluorophenyl)-1,2,4-oxadiazol-5-yl]-N-(2-methylphenyl) piperidine-1-carboxamide (C22) and 5-(4-Ethyl-phenyl)-2-(1H-tetrazol-5-ylmethyl)-2H-tetrazole (C29) were found to pass the two-step molecular docking, P450 site of metabolism prediction and pharmacokinetics filtering analysis successfully. Their binding stability for target proteins have been evaluated through RMSD, RMSF, Radius of gyration analysis from 10 ns Molecular Dynamics Simulation (MDS) run. Our identified drugs could be a capable therapeutic for Tuberculosis drug discovery, having said that more in vitro and in vivo testing is required to justify their potential as novel drug and mode of action.

scholarly journals An Analysis Based on Molecular Docking and Molecular Dynamics Simulation Study of Bromelain as Anti-SARS-CoV-2 Variants

2021 ◽  
Vol 12 ◽  
Author(s):  
Trina Ekawati Tallei ◽  
Fatimawali ◽  
Afriza Yelnetty ◽  
Rinaldi Idroes ◽  
Diah Kusumawaty ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulation ◽  
Three Dimensional ◽  
Md Simulations ◽  
Inhibitory Effect ◽  
Dynamics Simulation ◽  
Novel Coronavirus

The rapid spread of a novel coronavirus known as SARS-CoV-2 has compelled the entire world to seek ways to weaken this virus, prevent its spread and also eliminate it. However, no drug has been approved to treat COVID-19. Furthermore, the receptor-binding domain (RBD) on this viral spike protein, as well as several other important parts of this virus, have recently undergone mutations, resulting in new virus variants. While no treatment is currently available, a naturally derived molecule with known antiviral properties could be used as a potential treatment. Bromelain is an enzyme found in the fruit and stem of pineapples. This substance has been shown to have a broad antiviral activity. In this article, we analyse the ability of bromelain to counteract various variants of the SARS-CoV-2 by targeting bromelain binding on the side of this viral interaction with human angiotensin-converting enzyme 2 (hACE2) using molecular docking and molecular dynamics simulation approaches. We have succeeded in making three-dimensional configurations of various RBD variants using protein modelling. Bromelain exhibited good binding affinity toward various variants of RBDs and binds right at the binding site between RBDs and hACE2. This result is also presented in the modelling between Bromelain, RBD, and hACE2. The molecular dynamics (MD) simulations study revealed significant stability of the bromelain and RBD proteins separately up to 100 ns with an RMSD value of 2 Å. Furthermore, despite increases in RMSD and changes in Rog values of complexes, which are likely due to some destabilized interactions between bromelain and RBD proteins, two proteins in each complex remained bonded, and the site where the two proteins bind remained unchanged. This finding indicated that bromelain could have an inhibitory effect on different SARS-CoV-2 variants, paving the way for a new SARS-CoV-2 inhibitor drug. However, more in vitro and in vivo research on this potential mechanism of action is required.

Binding of biguanides to β-lactoglobulin: molecular-docking and molecular dynamics simulation studies

2014 ◽  
Vol 68 (11) ◽  
Author(s):  
Mehdi Sahihi ◽  
Yousef Ghayeb
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulation ◽  
Hydrophobic Interactions ◽  
Mean Value ◽  
Transport Protein ◽  
Dynamics Simulation ◽  
Radius Of Gyration ◽  
Accessible Surface ◽  
Β Lactoglobulin

AbstractBiguanides are a class of drugs derived from biguanide and they are the most widely used drugs for diabetes mellitus or pre-diabetes treatment. An investigation of their interaction and a transport protein such as β-lactoglobulin (BLG) at atomic level could be a valuable factor in controlling their transport to biological sites. Molecular-docking and molecular dynamics simulation methods were used to study the interaction of metformin, phenformin and buformin as biguanides and BLG as transport protein. The molecular-docking results revealed that these biguanides bind to BLG and that the BLG affinity for binding the biguanides decreases in the following order: phenformin — buformin — metformin. The docking results also show the hydrophobic interactions to have a significant role in the BLG-biguanides complex stability. Analysis of molecular dynamic simulation trajectories shows that the root mean square deviation of various systems attained equilibrium and fluctuated around the mean value at various times. The time evolution of the radius of gyration and the total solvent-accessible surface of the protein showed that BLG and BLG-biguanide complexes became stable at approximately 2500 ps and that there was not any conformational change in the BLG-biguanide complexes. In addition, the profiles of atomic fluctuations show the rigidity of the ligand-binding site during the simulation.

scholarly journals Phytochemicals from Leucas zeylanica Targeting Main Protease of SARS-CoV-2: Chemical Profiles, Molecular Docking, and Molecular Dynamics Simulations

Biology ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 789
Author(s):  
Mycal Dutta ◽  
Abu Montakim Tareq ◽  
Ahmed Rakib ◽  
Shafi Mahmud ◽  
Saad Ahmed Sami ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulation ◽  
Surface Area ◽  
Dynamics Simulation ◽  
Solvent Accessible Surface Area ◽  
Gas Chromatography Mass Spectrometry ◽  
Radius Of Gyration ◽  
Hydrogen Bond Formation ◽  
Main Protease

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a contemporary coronavirus, has impacted global economic activity and has a high transmission rate. As a result of the virus’s severe medical effects, developing effective vaccinations is vital. Plant-derived metabolites have been discovered as potential SARS-CoV-2 inhibitors. The SARS-CoV-2 main protease (Mpro) is a target for therapeutic research because of its highly conserved protein sequence. Gas chromatography–mass spectrometry (GC-MS) and molecular docking were used to screen 34 compounds identified from Leucas zeylanica for potential inhibitory activity against the SARS-CoV-2 Mpro. In addition, prime molecular mechanics–generalized Born surface area (MM-GBSA) was used to screen the compound dataset using a molecular dynamics simulation. From molecular docking analysis, 26 compounds were capable of interaction with the SARS-CoV-2 Mpro, while three compounds, namely 11-oxa-dispiro[4.0.4.1]undecan-1-ol (−5.755 kcal/mol), azetidin-2-one 3,3-dimethyl-4-(1-aminoethyl) (−5.39 kcal/mol), and lorazepam, 2TMS derivative (−5.246 kcal/mol), exhibited the highest docking scores. These three ligands were assessed by MM-GBSA, which revealed that they bind with the necessary Mpro amino acids in the catalytic groove to cause protein inhibition, including Ser144, Cys145, and His41. The molecular dynamics simulation confirmed the complex rigidity and stability of the docked ligand–Mpro complexes based on the analysis of mean radical variations, root-mean-square fluctuations, solvent-accessible surface area, radius of gyration, and hydrogen bond formation. The study of the postmolecular dynamics confirmation also confirmed that lorazepam, 11-oxa-dispiro[4.0.4.1]undecan-1-ol, and azetidin-2-one-3, 3-dimethyl-4-(1-aminoethyl) interact with similar Mpro binding pockets. The results of our computerized drug design approach may assist in the fight against SARS-CoV-2.

Heparin-reduced graphene oxide nanocomposites for curcumin delivery: in vitro, in vivo and molecular dynamics simulation study

2019 ◽  
Vol 7 (3) ◽  
pp. 1011-1027 ◽  
Author(s):  
Xiaoqun Shi ◽  
Yang Wang ◽  
Haiyan Sun ◽  
Yujuan Chen ◽  
Xingzhen Zhang ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Graphene Oxide ◽  
Molecular Dynamics Simulation ◽  
Reduced Graphene Oxide ◽  
Simulation Study ◽  
Dynamics Simulation ◽  
Reduced Graphene

We fabricated novel rGO-based nanocomposites and analyzed their interaction with drug and proteins via a molecular dynamics study.

scholarly journals An immunoinformatics study: designing multivalent T-cell epitope vaccine against canine circovirus

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Pankaj Jain ◽  
Amit Joshi ◽  
Nahid Akhtar ◽  
Sunil Krishnan ◽  
Vikas Kaushik
Keyword(s):  
Molecular Dynamics ◽  
Amino Acids ◽  
Molecular Docking ◽  
In Silico ◽  
Cell Epitope ◽  
Cost Effective ◽  
Dynamics Simulation ◽  
Cloning And Expression

Abstract Background Canine circovirus is a deadly pathogen of dogs and causes vasculitis and hemorrhagic enteritis. It causes lethal gastroenteritis in pigs, fox, and dogs. Canine circovirus genome contains two main (and opposite) transcription units which encode two open reading frames (ORFs), a replicase-associated protein (Rep) and the capsid (Cap) protein. The replicase protein and capsid protein consist of 303 amino acids and 270 amino acids respectively. Several immuno-informatics methods such as epitope screening, molecular docking, and molecular-dynamics simulations were used to craft peptide-based vaccine construct against canine circovirus. Results The vaccine construct was designed by joining the selected epitopes with adjuvants by suitable linker. The cloning and expression of the vaccine construct was also performed using in silico methods. Screening of epitopes was conducted by NetMHC server that uses ANN (Artificial neural networking) algorithm. These methods are fast and cost-effective for screening epitopes that can interact with dog leukocyte antigens (DLA) and initiate an immune response. Overall, 5 epitopes, YQHLPPFRF, YIRAKWINW, ALYRRLTLI, HLQGFVNLK, and GTMNFVARR, were selected and used to design a vaccine construct. The molecular docking and molecular dynamics simulation studies show that these epitopes can bind with DLA molecules with stability. The codon adaptation and in silico cloning studies show that the vaccine can be expressed by Escherichia coli K12 strain. Conclusion The results suggest that the vaccine construct can be useful in preventing the dogs from canine circovirus infections. However, the results need further validation by performing other in vitro and in vivo experiments.

scholarly journals Molecular dynamics simulation-guided drug sensitivity prediction for lung cancer with rareEGFRmutations

2019 ◽  
Vol 116 (20) ◽  
pp. 10025-10030 ◽  
Author(s):  
Shinnosuke Ikemura ◽  
Hiroyuki Yasuda ◽  
Shingo Matsumoto ◽  
Mayumi Kamada ◽  
Junko Hamamoto ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Kinase Inhibitors ◽  
Dynamics Simulation ◽  
Cell Lung Carcinoma ◽  
Variants Of Unknown Significance ◽  
Mutational Hotspots

Next generation sequencing (NGS)-based tumor profiling identified an overwhelming number of uncharacterized somatic mutations, also known as variants of unknown significance (VUS). The therapeutic significance ofEGFRmutations outside mutational hotspots, consisting of >50 types, in nonsmall cell lung carcinoma (NSCLC) is largely unknown. In fact, our pan-nation screening of NSCLC without hotspotEGFRmutations (n= 3,779) revealed that the majority (>90%) of cases with rareEGFRmutations, accounting for 5.5% of the cohort subjects, did not receive EGFR-tyrosine kinase inhibitors (TKIs) as a first-line treatment. To tackle this problem, we applied a molecular dynamics simulation-based model to predict the sensitivity of rare EGFR mutants to EGFR-TKIs. The model successfully predicted the diverse in vitro and in vivo sensitivities of exon 20 insertion mutants, including a singleton, to osimertinib, a third-generation EGFR-TKI (R2= 0.72,P= 0.0037). Additionally, our model showed a higher consistency with experimentally obtained sensitivity data than other prediction approaches, indicating its robustness in analyzing complex cancer mutations. Thus, the in silico prediction model will be a powerful tool in precision medicine for NSCLC patients carrying rareEGFRmutations in the clinical setting. Here, we propose an insight to overcome mutation diversity in lung cancer.

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