scholarly journals Molecular docking between the RNA polymerase of the Moniliophthora perniciosa mitochondrial plasmid and Rifampicin produces a highly stable complex

2013 ◽  
Vol 10 (1) ◽  
Author(s):  
Bruno Andrade ◽  
Catiane Souza ◽  
Aristóteles Góes-Neto
Keyword(s):  
Molecular Docking ◽  
Rna Polymerase ◽  
Stable Complex ◽  
Mitochondrial Plasmid ◽  
Moniliophthora Perniciosa

scholarly journals The application of in silico experimental model in the assessment of ciprofloxacin and levofloxacin interaction with main SARS-CoV-2 targets: S-, E- and TMPRSS2 proteins, RNA-dependent RNA polymerase and papain-like protease (PLpro)—preliminary molecular docking analysis

2021 ◽  
Author(s):  
Krzysztof Marciniec ◽  
Artur Beberok ◽  
Stanisław Boryczka ◽  
Dorota Wrześniok
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Rna Polymerase ◽  
Stable Complex ◽  
E Proteins ◽  
Rna Dependent Rna Polymerase ◽  
Docking Analysis ◽  
Molecular Studies ◽  
Molecular Docking Analysis ◽  
Positive Controls

Abstract Background The new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was identified at the end of 2019. Despite growing understanding of SARS-CoV-2 in virology as well as many molecular studies, except remdesivir, no specific anti-SARS-CoV-2 drug has been officially approved. Methods In the present study molecular docking technique was applied to test binding affinity of ciprofloxacin and levofloxacin—two commercially available fluoroquinolones, to SARS-CoV-2 S-, E- and TMPRSS2 proteins, RNA-dependent RNA polymerase and papain-like protease (PLPRO). Chloroquine and dexamethasone were used as reference positive controls. Results When analyzing the molecular docking data it was noticed that ciprofloxacin and levofloxacin possess lower binding energy with S protein as compared to the references. In the case of TMPRSS2 protein and PLPRO protease the best docked ligand was levofloxacin and in the case of E proteins and RNA-dependent RNA polymerase the best docked ligands were levofloxacin and dexamethasone. Moreover, a molecular dynamics study also reveals that ciprofloxacin and levofloxacin form a stable complex with E- and TMPRSS2 proteins, RNA polymerase and papain-like protease (PLPRO). Conclusions The revealed data indicate that ciprofloxacin and levofloxacin could interact and potentially inhibit crucial SARS-CoV-2 proteins.

scholarly journals In Silico Molecular Docking and Interaction Analysis of Traditional Chinese Medicines Against SARS-CoV-2 Receptor

2021 ◽  
Vol 16 (5) ◽  
pp. 1934578X2110150
Author(s):  
Gang Li ◽  
Wei Zhou ◽  
Xiurong Zhao ◽  
Ying Xie
Keyword(s):  
Molecular Docking ◽  
In Silico ◽  
Interaction Analysis ◽  
Herbal Remedies ◽  
Receptor Protein ◽  
Stable Complex ◽  
Traditional Chinese Medicines ◽  
Ligand Interaction ◽  
Chinese Medicines ◽  
In Silico Molecular Docking

The novel coronavirus, 2019-nCoV, has led to a major pandemic in 2020 and is responsible for more than 2.9 million officially recorded deaths worldwide. As well as synthetic anti-viral drugs, there is also a need to explore natural herbal remedies. The Traditional Chinese Medicines (TCMs) system has been used for thousands of years for the prevention, diagnosis, and treatment of several chronic diseases. In this paper, we performed an in silico molecular docking and interaction analysis of TCMs against SARS-CoV-2 receptor RNA-dependent RNA polymerase (RdRp). We obtained the 5 most effective plant compounds which had a better binding affinity towards the target receptor protein. These compounds areforsythoside A, rutin, ginkgolide C, icariside II, and nolinospiroside E. The top-ranked compound, based on docking score, was nolinospiroside, a glycoside found in Ophiopogon japonicas that has antioxidant properties. Protein-ligand interaction analysis discerned that nolinospiroside formed a strong bond between ARG 349 of the protein receptor and the carboxylate group of the ligand, forming a stable complex. Hence, nolinospiroside could be deployed as a lead compound against SARS-CoV-2 infection that can be further investigated for its potential benefits in curbing the viral infection.

scholarly journals Rationale design and synthesis of some novel imidazole linked thiazolidinone hybrid molecules as DNA minor groove binders

2020 ◽  
Vol 11 (2) ◽  
pp. 120-132
Author(s):  
Javeed Ahmad War ◽  
Santosh Kumar Srivastava
Keyword(s):  
Molecular Docking ◽  
Binding Affinity ◽  
Specific Binding ◽  
Minor Groove ◽  
Stable Complex ◽  
Binding Studies ◽  
In Vitro Susceptibility ◽  
Reference Drug ◽  
Hybrid Molecules

A new series of imidazole linked thiazolidinone hybrid molecules was designed and subsequently synthesized through a feasible, three step reaction protocol. The structures of these molecules were established using FT-IR, 1H NMR, 13C NMR and HRMS techniques. In vitro susceptibility tests against some Gram positive (Staphylococcus aureus and Bacillus subtilis) and Gram negative bacteria (Escherichia coli and Pseudomonas aeruginosa) exhibited broad spectrum potency of the molecules. The most potent molecule (S2A7) amongst the screened molecules, showed minimum inhibitory concentration (MIC) value not less than 2.0 µg/mL which was at par with the reference drug Streptomycin. Structure activity relationships revealed nitro and chloro groups being crucial for bioactivity when present at meta position of arylidene ring in 3-(3-(imidazol-1-yl)propyl)-5-(benzylidene)-2-(phenylimino)thiazolidin-4-one. Deoxyribonucleic acid (DNA)and bovine serum albumin (BSA) binding studies for S2A7 under simulated physiological pH were probed using UV-Visible, fluorescence quenching, gel electrophoresis and molecular docking techniques. These studies established that S2A7 has strong binding affinity towards DNA and binds at the minor groove of DNA with binding constant (Kb) of 0.1287×102 L/mol. Molecular docking simulations of S2A7 with DNA and BSA predicted binding affinity of -9.2 and -7.2 kcal/mol, respectively. Van der Waals forces and hydrogen bonding interactions were predicted as the main forces of interaction. With DNA, S2A7 exhibited specific binding affinity towards adenine-thiamine base pairs. The compound S2A7 forms a stable complex with BSA by binding at subdomain IIIA implying high bio-distribution of the compound.

scholarly journals Molecular Docking Analysis of the T450A Mutation of the Gene rpoB Mycobacterium leprae from Leprosy Patients in Papua, West Papua and North Maluku, Indonesia

2021 ◽  
pp. 3578-3584
Author(s):  
Yustinus Maladan ◽  
Hana Krismawati ◽  
Tri Wahyuni ◽  
Hotma Martogi Lorensi Hutapea ◽  
Muhammad Fajri Rokhmad ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Rna Polymerase ◽  
Binding Affinity ◽  
Rpob Gene ◽  
Ramachandran Plot ◽  
Docking Analysis ◽  
West Papua ◽  
Leprosy Patients ◽  
Subunit B ◽  
Molecular Docking Analysis

Leprosy persists to be a health problem in Indonesia, especially in the provinces of North Maluku, West Papua and Papua. Early diagnosis and complete treatment with multidrug therapy (MDT) remain the key strategy for reducing the disease burden. One of the major components of MDT is rifampicin which in certain cases in several countries, M. leprae resistance to this drug issue has been reported albeit only a few. This research aimed to detect and analyze polymorphism in M. leprae rpoB gene that was isolated from leprosy patients in three provinces: North Maluku Province, West Papua Province and Papua Province, Indonesia. The identification of mutations in the M. leprae rpoB gene was carried out by aligning the results of DNA sequencing with the reference strain. The 3D structure of rpoB was derived using the Swiss Model. The T450A, S456L, and H451Y variants of RNA Polymerase B subunits were constructed using FoldX based on the wild-type structure. The structures were repaired, and protein stability was evaluated using foldX under the Yasara viewer. The QC of the rpoB M. leprae homology models was conducted with Ramachandran Plot modeling using PROCHECK. The difference in binding affinity between native protein and T450A, S456L, and H45I variants were analyzed using molecular docking. rpoB gene of M. leprae contains a mutation found in nucleotide of 1348 bp. The mutation triggered the conversion of the amino acid Threonine to Alanine in the amino acid to 450 rpoB subunit B. The structure of 3D RNA Polymerase Subunit B was constructed using rpoB Mycobacterium tuberculosis with PDB code 5UH5 as template. According to Ramachandran Plot, the percentage of residues in the most favored regions are 91.9%, and there was no significant number of residues in the disallowed regions. The results of molecular docking showed that the T450A variant had the same binding affinity with the native protein which was -8.9 kcal. Binding affinity on the S456L and H451Y variants increased by -7.3 kcal and -8.2 kcal, respectively. According to Molecular Docking analysis, T450A variant did not affect the energy binding between RNA polymerase and rifampicin.

scholarly journals Inhibitory Effects of Cortex Dictamni Aqueous Extract on Dipeptidyl Peptidase I and Chymase Activities and the Screening of Active Ingredients in Cortex Dictamni Based on Molecular Docking Technique

2020 ◽  
Vol 12 (1) ◽  
pp. 19
Author(s):  
Qi Wang ◽  
Tao Wei ◽  
Xiaoying Zhou
Keyword(s):  
Molecular Docking ◽  
Aqueous Extract ◽  
Hydrophobic Interactions ◽  
Cell Model ◽  
Docking Simulation ◽  
Dipeptidyl Peptidase ◽  
Stable Complex ◽  
Molecular Docking Study ◽  
Natural Inhibitor ◽  
Anti Inflammatory

Dipeptidyl peptidase I (DPPI) and chymase, the granulo-proteases produced and released by mast cells, are important targets of anti-inflammatory drug research and development. Cortex Dictamni is a definite nature drug with anti-inflammatory activity, but the mechanism is unclear and effects of Cortex Dictamni on DPPI and chymase are unknown. This study focuses on effects of Cortex Dictamni aqueous extract (CDAE) on DPPI and chymase activities using cell model, bio-molecular interactions and the Molecular docking study by Discovery Studio (DS) analysis. The results showed that CDAE could significantly inhibit DPPI and chymase activities in vitro and in living rat spleen lymphocytes. Molecular docking simulation demonstrated that Troxerutin, the one of the active compounds of Cortex Dictamni, formed a hydrogen bond with amino acid ILE429 and a strong hydrophobic interaction with TYR64 CYS234 PRO279 ALA382 of DPPI. These interactions allow Troxerutin to form a stable complex with the DPPI, implicating that Troxerutin might be a potential natural inhibitor of DPPI. Dictamnoside M, another active compound of Cortex Dictamni formed hydrogen bonds and hydrophobic interactions within the binding pocket of chymase domain and form a stable complex with the chymase. Dictamnoside M maybe a potential natural inhibitor of chymase. This study suggested a new nature inhibitor Cortex Dictamni and its active components with the anti-inflammatory effects.

Protein-Ligand Docking Methodologies and Its Application in Drug Discovery

2016 ◽  
pp. 196-219
Author(s):  
Sanchaita Rajkhowa ◽  
Ramesh C. Deka
Keyword(s):  
Molecular Docking ◽  
Drug Discovery ◽  
Drug Design ◽  
High Throughput Screening ◽  
Docking Studies ◽  
Stable Complex ◽  
Scoring Functions ◽  
Binding Modes ◽  
Structure Based Drug Design ◽  
Modern Drug

Molecular docking is a key tool in structural biology and computer-assisted drug design. Molecular docking is a method which predicts the preferred orientation of a ligand when bound in an active site to form a stable complex. It is the most common method used as a structure-based drug design. Here, the authors intend to discuss the various types of docking methods and their development and applications in modern drug discovery. The important basic theories such as sampling algorithm and scoring functions have been discussed briefly. The performances of the different available docking software have also been discussed. This chapter also includes some application examples of docking studies in modern drug discovery such as targeted drug delivery using carbon nanotubes, docking of nucleic acids to find the binding modes and a comparative study between high-throughput screening and structure-based virtual screening.

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