scholarly journals In Silico Identification of Possible Inhibitors for Protein Kinase B (PknB) of Mycobacterium tuberculosis

Molecules ◽  
2021 ◽  
Vol 26 (20) ◽  
pp. 6162
Author(s):  
Tatiana F. Vieira ◽  
Fábio G. Martins ◽  
Joel P. Moreira ◽  
Tiago Barbosa ◽  
Sérgio F. Sousa
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Protein Kinases ◽  
In Silico ◽  
Structural Information ◽  
Experimental Testing ◽  
Binding Pocket ◽  
Free Energy Calculations ◽  
Ligand Docking ◽  
Active Site Residues ◽  
Dynamics Simulations

With tuberculosis still being one of leading causes of death in the world and the emergence of drug-resistant strains of Mycobacterium tuberculosis (Mtb), researchers have been seeking to find further therapeutic strategies or more specific molecular targets. PknB is one of the 11 Ser/Thr protein kinases of Mtb and is responsible for phosphorylation-mediated signaling, mainly involved in cell wall synthesis, cell division and metabolism. With the amount of structural information available and the great interest in protein kinases, PknB has become an attractive target for drug development. This work describes the optimization and application of an in silico computational protocol to find new PknB inhibitors. This multi-level computational approach combines protein–ligand docking, structure-based virtual screening, molecular dynamics simulations and free energy calculations. The optimized protocol was applied to screen a large dataset containing 129,650 molecules, obtained from the ZINC/FDA-Approved database, Mu.Ta.Lig Virtual Chemotheca and Chimiothèque Nationale. It was observed that the most promising compounds selected occupy the adenine-binding pocket in PknB, and the main interacting residues are Leu17, Val26, Tyr94 and Met155. Only one of the compounds was able to move the active site residues into an open conformation. It was also observed that the P-loop and magnesium position loops change according to the characteristics of the ligand. This protocol led to the identification of six compounds for further experimental testing while also providing additional structural information for the design of more specific and more effective derivatives.

scholarly journals Identification of New Potential Inhibitors of Quorum Sensing through a Specialized Multi-Level Computational Approach

Molecules ◽  
2021 ◽  
Vol 26 (9) ◽  
pp. 2600
Author(s):  
Fábio G. Martins ◽  
André Melo ◽  
Sérgio F. Sousa
Keyword(s):  
Virtual Screening ◽  
Quorum Sensing ◽  
In Silico ◽  
Bacterial Infections ◽  
Extracellular Polymeric Substances ◽  
Free Energy Calculations ◽  
Ligand Docking ◽  
Screening Tests ◽  
Scoring Functions ◽  
Potential Inhibitors

Biofilms are aggregates of microorganisms anchored to a surface and embedded in a self-produced matrix of extracellular polymeric substances and have been associated with 80% of all bacterial infections in humans. Because bacteria in biofilms are less amenable to antibiotic treatment, biofilms have been associated with developing antibiotic resistance, a problem that urges developing new therapeutic options and approaches. Interfering with quorum-sensing (QS), an important process of cell-to-cell communication by bacteria in biofilms is a promising strategy to inhibit biofilm formation and development. Here we describe and apply an in silico computational protocol for identifying novel potential inhibitors of quorum-sensing, using CviR—the quorum-sensing receptor from Chromobacterium violaceum—as a model target. This in silico approach combines protein-ligand docking (with 7 different docking programs/scoring functions), receptor-based virtual screening, molecular dynamic simulations, and free energy calculations. Particular emphasis was dedicated to optimizing the discrimination ability between active/inactive molecules in virtual screening tests using a target-specific training set. Overall, the optimized protocol was used to evaluate 66,461 molecules, including those on the ZINC/FDA-Approved database and to the Mu.Ta.Lig Virtual Chemotheca. Multiple promising compounds were identified, yielding good prospects for future experimental validation and for drug repurposing towards QS inhibition.

scholarly journals Crystal Structures of Two Coronavirus ADP-Ribose-1″-Monophosphatases and Their Complexes with ADP-Ribose: a Systematic Structural Analysis of the Viral ADRP Domain

2008 ◽  
Vol 83 (2) ◽  
pp. 1083-1092 ◽  
Author(s):  
Yuanyuan Xu ◽  
Le Cong ◽  
Cheng Chen ◽  
Lei Wei ◽  
Qi Zhao ◽  
...  
Keyword(s):  
Structural Analysis ◽  
Crystal Structures ◽  
Structural Information ◽  
Large Family ◽  
Binding Pocket ◽  
Structural Basis ◽  
Active Site Residues ◽  
Replication Process ◽  
Functional Studies ◽  
Group I

ABSTRACT The coronaviruses are a large family of plus-strand RNA viruses that cause a wide variety of diseases both in humans and in other organisms. The coronaviruses are composed of three main lineages and have a complex organization of nonstructural proteins (nsp's). In the coronavirus, nsp3 resides a domain with the macroH2A-like fold and ADP-ribose-1"-monophosphatase (ADRP) activity, which is proposed to play a regulatory role in the replication process. However, the significance of this domain for the coronaviruses is still poorly understood due to the lack of structural information from different lineages. We have determined the crystal structures of two viral ADRP domains, from the group I human coronavirus 229E and the group III avian infectious bronchitis virus, as well as their respective complexes with ADP-ribose. The structures were individually solved to elucidate the structural similarities and differences of the ADRP domains among various coronavirus species. The active-site residues responsible for mediating ADRP activity were found to be highly conserved in terms of both sequence alignment and structural superposition, whereas the substrate binding pocket exhibited variations in structure but not in sequence. Together with data from a previous analysis of the ADRP domain from the group II severe acute respiratory syndrome coronavirus and from other related functional studies of ADRP domains, a systematic structural analysis of the coronavirus ADRP domains was realized for the first time to provide a structural basis for the function of this domain in the coronavirus replication process.

scholarly journals In silico screening of W. salutaris bioactive constituents reveal betulinic acid, ursolic acid acetate and eucosterol as potential M. tuberculosis antagonists targeting FabF

2021 ◽  
Author(s):  
Nokukhanya Gumede ◽  
Kgothatso E. Machaba ◽  
Umar Ndagi ◽  
Hezekiel M. Kumalo ◽  
Ndumiso N. Mhlongo
Keyword(s):  
Ursolic Acid ◽  
Betulinic Acid ◽  
In Silico ◽  
Fatty Acid Biosynthesis ◽  
Binding Energies ◽  
Active Site Residues ◽  
Bioactive Constituents ◽  
Inhibitory Potential ◽  
Dynamics Simulations ◽  
Potential Inhibitors

Abstract Tuberculosis (TB) remains a long-standing burdening disease to control worldwide. The lengthy current TB treatment, which boasts with unbearable adverse effects, and frequent emergence of drug resistant strains of M. tuberculosis lays an increasing burden. This behests urgent discovery and development of alternative novel medicine to alleviate TB. In this report, in silico methods were applied to examine the propensity of W. salutaris active compounds as potential inhibitors of M. tuberculosis fatty acid biosynthesis protein (FabF). Thirteen compounds were virtually screened against FabF and subjected to molecular dynamics simulations and post-dynamics analyses to examine their inhibitory potential. Betulinic acid, ursolic acid and ursolic acid acetate had the best binding energies and hence the best inhibitory potential against FabF and desirable cytotoxicity profile. These compounds bind and interact with FabF active site residues to exert their inhibitory potential. Findings in this preliminary report warrant further experimental validation towards the development of these compounds as potential drugs targeting FabF in the treatment of tuberculosis.

scholarly journals Computational Studies to Identify Potential Main Protease Inhibitors for SARS-CoV-2

2020 ◽  
Author(s):  
M. Elizabeth Sobhia ◽  
Ketan Ghosh ◽  
Srikanth Sivangula ◽  
Harmanpreet Singh ◽  
Siva Kumar
Keyword(s):  
In Silico ◽  
Experimental Studies ◽  
Binding Pocket ◽  
Vital Role ◽  
Active Site Residues ◽  
X Ray Diffraction ◽  
Main Protease ◽  
Docking Protocol ◽  
In Silico Studies

The Coronavirus pandemic has put the entire humanity in total shock and has forced the world to go under total lockdown. It is time for the entire scientific community across the globe to find a solution for this deadly and unseen enemy. In silico studies play a vital role in situations like this, as experimental studies are not feasible by all researchers particularly with relevance to BSL4 procedures. In this study, using the high resolution crystal structure of SARS-CoV-2 main protease (PDB: 5R82), we have identified molecules which can potentially inhibit the main protease (Mpro). We used a three-tier docking protocol making use of three different databases. We analysed the residues which are lying near the ligand binding pocket of the main protease structure and it shows a wide cavity, which can accommodate chemically diverse ligands, occupying different sub-pockets. Using the small fragment bound in the 5R82, we have identified several larger molecules whose functional groups make interactions with the active site residues covering. This study also presumably steers the structure determination of many ligand-main protease complexes using x- ray diffraction methods. These molecules can be used as ‘in silico leads’ and further be explored in the development of SARS-CoV-2 drugs.

scholarly journals In silico homology modelling and identification of Tousled-like kinase 1 inhibitors for glioblastoma therapy via high throughput virtual screening protein-ligand docking

2015 ◽  
Author(s):  
Kamariah Ibrahim ◽  
Abubakar Danjuma ◽  
Chyan Leong Ng ◽  
Nor Azian Abdul Murad ◽  
Roslan Harun ◽  
...  
Keyword(s):  
Virtual Screening ◽  
High Throughput ◽  
Energy Minimization ◽  
In Silico ◽  
Structural Information ◽  
Homology Modelling ◽  
Ligand Docking ◽  
Nmr Studies ◽  
Homology Models ◽  
High Throughput Virtual Screening

Background: Glioblastoma multiforme (GBM) is a grade IV brain tumor that arises from star-shaped glial cells supporting neural cells called astrocytes. The survival of GBM patients remains poor despite many specific molecular targets have been developed. Tousled-like kinase 1 (TLK1), a serine-threonine kinase, was identified to be overexpressed in cancer such as GBM. TLK1 plays an important role in controlling chromosomal aggregation, cell survival and proliferation. In vitro studies suggested that TLK1 is a potential target for some cancers. Hence, identification of suitable molecular inhibitors for TLK1 is warranted as new therapeutic agents in GBM. To date, there is no direct structural information available from X-ray crystallography and NMR studies for TLK1. In this study, we aimed to create a homology model of TLK1 and to identify suitable molecular inhibitors or compounds that are likely to bind and inhibit TLK1 activity via in silico high-throughput virtual screening (HTVS) protein-ligand docking. Methods: 3D homology models of TLK1 were derived from various servers including HOmology ModellER, i-Tasser, Psipred and Swiss Model. All models were evaluated using Swiss-Model Q-Mean server. Only one model was selected for further analysis. Further validation was performed using PDBsum, 3d2go, ProSA, Procheck analysis and ERRAT. Energy minimization was performed using YASARA energy minimization server. Subsequently, HTVS was performed using Molegro Virtual Docker 6.0 and candidate ligands from ligand.info database. Ligand-docking procedures were analyzed at the catalytic site of TLK1. Drug-like molecules were filtered using FAFDrugs3 ADME-Tox filter. Results and conclusion: High quality homology models were obtained from the 4B8M Aurora B kinase derived from Xenopus levias structure that share 33% sequence identity to TLK1. From the HTVS ligand-docking, two compounds were identified to be the potential inhibitors as it did not violate the Lipinski rule of five and CNS-based filter as a potential drug-like molecule for GBM.

scholarly journals Computational Studies to Identify Potential Main Protease Inhibitors for SARS-CoV-2

2020 ◽  
Author(s):  
M. Elizabeth Sobhia ◽  
Ketan Ghosh ◽  
Srikanth Sivangula ◽  
Harmanpreet Singh ◽  
Siva Kumar
Keyword(s):  
In Silico ◽  
Experimental Studies ◽  
Binding Pocket ◽  
Vital Role ◽  
Active Site Residues ◽  
X Ray Diffraction ◽  
Main Protease ◽  
Docking Protocol ◽  
In Silico Studies

The Coronavirus pandemic has put the entire humanity in total shock and has forced the world to go under total lockdown. It is time for the entire scientific community across the globe to find a solution for this deadly and unseen enemy. In silico studies play a vital role in situations like this, as experimental studies are not feasible by all researchers particularly with relevance to BSL4 procedures. In this study, using the high resolution crystal structure of SARS-CoV-2 main protease (PDB: 5R82), we have identified molecules which can potentially inhibit the main protease (Mpro). We used a three-tier docking protocol making use of three different databases. We analysed the residues which are lying near the ligand binding pocket of the main protease structure and it shows a wide cavity, which can accommodate chemically diverse ligands, occupying different sub-pockets. Using the small fragment bound in the 5R82, we have identified several larger molecules whose functional groups make interactions with the active site residues covering. This study also presumably steers the structure determination of many ligand-main protease complexes using x- ray diffraction methods. These molecules can be used as ‘in silico leads’ and further be explored in the development of SARS-CoV-2 drugs.

Determinants of the species selectivity of oxazolidinone antibiotics targeting the large ribosomal subunit

2013 ◽  
Vol 394 (11) ◽  
pp. 1529-1541 ◽  
Author(s):  
Jagmohan S. Saini ◽  
Nadine Homeyer ◽  
Simone Fulle ◽  
Holger Gohlke
Keyword(s):  
Free Energy ◽  
Deinococcus Radiodurans ◽  
Structural Information ◽  
Current Knowledge ◽  
Binding Free Energy ◽  
Ribosomal Subunit ◽  
Free Energy Calculations ◽  
Haloarcula Marismortui ◽  
Species Selectivity ◽  
Dynamics Simulations

Abstract Oxazolidinone antibiotics bind to the highly conserved peptidyl transferase center in the ribosome. For developing selective antibiotics, a profound understanding of the selectivity determinants is required. We have performed for the first time technically challenging molecular dynamics simulations in combination with molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) free energy calculations of the oxazolidinones linezolid and radezolid bound to the large ribosomal subunits of the eubacterium Deinococcus radiodurans and the archaeon Haloarcula marismortui. A remarkably good agreement of the computed relative binding free energy with selectivity data available from experiment for linezolid is found. On an atomic level, the analyses reveal an intricate interplay of structural, energetic, and dynamic determinants of the species selectivity of oxazolidinone antibiotics: A structural decomposition of free energy components identifies influences that originate from first and second shell nucleotides of the binding sites and lead to (opposing) contributions from interaction energies, solvation, and entropic factors. These findings add another layer of complexity to the current knowledge on structure-activity relationships of oxazolidinones binding to the ribosome and suggest that selectivity analyses solely based on structural information and qualitative arguments on interactions may not reach far enough. The computational analyses presented here should be of sufficient accuracy to fill this gap.

scholarly journals Genome Mining, Phylogenetic and Structural Analysis of Bacterial Nitrilases for the Biodegradation of Nitrile Compounds

2021 ◽  
Author(s):  
Richa Salwan ◽  
Vivek Sharma ◽  
Surajit Das
Keyword(s):  
Structural Analysis ◽  
Substrate Specificity ◽  
Active Site ◽  
Structural Information ◽  
Genome Mining ◽  
Binding Pocket ◽  
Catalytic Triad ◽  
Vital Role ◽  
Active Site Residues ◽  
Motif Analysis

Abstract Microbial nitrilases play vital role in biodegradation of nitrile-containing contaminants in pollutant and effluents treatments in chemical and textile industries as well as the biosynthesis of IAA from tryptophan in plants. However, the lack of structural information hinders the correlation of its activity and substrate specificity. Here, we have identified bacterial genomes for nitrilases bearing unassigned functions including hypothetical, uncharacterized, or putative role. The genomic annotations revealed four predicted nitrilases encoding genes as uncharacterized subgroup of the nitrilase superfamily. Further, the annotation of these nitrilases revealed relatedness with nitrilase hydratases and cyanoalanine hydratases. The characterization of motif analysis of these protein sequences, predicted a single motif of 20-28 aa, and glutamate (E), lysine (K) and cysteine (C) residues as a part of catalytic triad along with several active site residues. The structural analysis of the modeled nitrilases revealed geometrical and close conformation of α-helices and β-sheets arranged in a sandwich structure. The catalytic residues constituted the substrate binding pocket and exhibited the wide nitrile substrate spectra for both aromatic and aliphatic nitriles containing compounds. The aromatic amino acid residues Y159 in active site were predicted to show importance for substrate specificity. The substitution of non-aromatic alanine residue in place of Y159 completely disrupted the catalytic activity for indole-3-acetonitrile. The present study reports several uncharacterized nitrilases which have not been reported so far for their role in the biodegradation of pollutants, xenobiotics which could find applications in industries.

scholarly journals Atomic-scale characterization of mature HIV-1 capsid stabilization by inositol hexakisphosphate (IP6)

2020 ◽  
Vol 6 (38) ◽  
pp. eabc6465 ◽  
Author(s):  
Alvin Yu ◽  
Elizabeth M. Y. Lee ◽  
Jaehyeok Jin ◽  
Gregory A. Voth
Keyword(s):  
Kinetic Studies ◽  
Binding Pocket ◽  
Free Energy Calculations ◽  
Atomic Scale ◽  
Binding Modes ◽  
Ligand Density ◽  
Scale Characterization ◽  
Dynamics Simulations

Inositol hexakisphosphates (IP6) are cellular cofactors that promote the assembly of mature capsids of HIV. These negatively charged molecules coordinate an electropositive ring of arginines at the center of pores distributed throughout the capsid surface. Kinetic studies indicate that the binding of IP6 increases the stable lifetimes of the capsid by several orders of magnitude from minutes to hours. Using all-atom molecular dynamics simulations, we uncover the mechanisms that underlie the unusually high stability of mature capsids in complex with IP6. We find that capsid hexamers and pentamers have differential binding modes for IP6. Ligand density calculations show three sites of interaction with IP6 including at a known capsid inhibitor binding pocket. Free energy calculations demonstrate that IP6 preferentially stabilizes pentamers over hexamers to enhance fullerene modes of assembly. These results elucidate the molecular role of IP6 in stabilizing and assembling the retroviral capsid.

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