Combining molecular dynamics and docking simulations of the cytidine deaminase from Mycobacterium tuberculosis H37Rv

Abstract

Cytidine Deaminase (CD) is an evolutionarily conserved enzyme that participates in the pyrimidine salvage pathway recycling cytidine and deoxycytidine into uridine and deoxyuridine, respectively. Here, our goal is to apply computational techniques in the pursuit of potential inhibitors of Mycobacterium tuberculosis CD (MtCDA) enzyme activity. Molecular docking simulation was applied to find the possible hit compounds. Molecular dynamics simulations were also carried out to investigate the physically relevant motions involved in the protein-ligand recognition process, aiming at providing estimates for free energy of binding. The proposed approach was capable of identifying a potential inhibitor, which was experimentally confirmed by IC(50) evaluation. Our findings open up the possibility to extend this protocol to different databases in order to find new potential inhibitors for promising targets based on a rational drug design process.

Characterization of a chitinase from the cellulolytic actinomycete Thermobifida fusca

“…Coordinates for chitohexaose were extracted from the PDB (2PI8; [15]) and the ligand was subjected to the default energy minimization function in YASARA employing the AMBER99 force field. Docking was done using AutoDock Vina via the PyRx interface [16,17]. A structure-based multiple sequence alignment was generated using PROMALS3D [18].…”

Fusing a Carbohydrate-Binding Module into the Aspergillus usamii β-Mannanase to Improve Its Thermostability and Cellulose-Binding Capacity by In Silico Design

“…Then, the interaction between the candidate CBM and cellobiose was predicted by molecular docking (MD) simulation. The binding free energy of the CBM with cellobiose, contrary to their affinity [13], was calculated using the AutoDock 4.2 program (http://autodock.scripps.edu), which combines a rapid binding free energy evaluation through precalculated grids of affinity potentials with a variety of search algorithms to find the most suitable binding position for a ligand on a given macromolecule [14]. Finally, a CBM having the lowest binding free energy was selected, and fused into the AuMan5A forming an AuMan5A-CBM.…”

Fusion of a family 20 carbohydrate‐binding module (CBM20) with cyclodextrin glycosyltransferase of Geobacillus sp. CHB1 improves catalytic efficiency

“…The interaction between the candidate fusion enzymes and maltohexaose was predicted by molecular docking (MD) simulation and the MOE software. The binding free energy of the fusion enzymes with maltohexaose, opposite to their affinity , was calculated using the MOE software (http://www.chemcomp.com) and the AutoDock 4.2 program (http://autodock.scripps.edu), which combines a rapid binding free energy evaluation through precalculated grids of affinity potentials with all kinds of search algorithms to find the most suitable binding place for a ligand on a given giant molecule . Finally, from the in silico designed fusion CGTases, a candidate fusion enzyme CGTΔE‐CBM having the lowest binding free energy was selected, cloned into expression vector and expressed in E coli BL21 (DE3) strain.…”