Understanding the resistance mechanism of penicillin binding protein 1a mutant against cefotaxime using molecular dynamic simulation

<p>Antibiotic resistance is a threatening challenge for global health, as the expansion of resistance to current antibiotics has made serious therapeutic problems. Genome mutations are key evolutionary mechanisms conferring antibiotic resistance in bacterial pathogens. For example, penicillin and cephalosporins resistance is mostly mediated by mutations in penicillin binding proteins to change the affinity of the drug. Accordingly, threonine point mutations were reported to develop antibiotic resistance in various bacterial infections including pneumococcal infections. In this study, conventional molecular dynamics simulations, umbrella sampling simulations and MM/GBSA free energy calculations were applied to figure out how the Threonine to Alanine mutation (T to A) at STMK motif affects the binding of cefotaxime to Penicillin Binding Protein 1a and to reveal the resistance mechanism induced by the T to A mutation. The results obtained from the computational methods demonstrate that the T to A mutation increases the flexibility of the binding pocket and changes its conformation, which leads to increased conformational entropy change (−<i>T</i>Δ<i>S</i>) and attenuates the bonds between the ligand and the receptor. In brief, our findings indicate that both of the alterations of the conformational enthalpy and entropy contribute to the T to A-induced resistance in the binding of cefotaxime into penicillin binding protein 1a.</p

Identification of novel metallo-β-lactamases inhibitors using ligand-based pharmacophore modelling and structure-based virtual screening

Metallo-β-lactamases (MBLs) are a group of enzymes that hydrolyze the most commonly used β-lactam-based antibiotics, leading to the development of multi-drug resistance. The three main clinically relevant groups of these enzymes are IMP, VIM, and NDM. This study aims to introduce potent novel overlapped candidates from a ZINC database retrieved from the 200,583-member natural library against the active sites of IMP-1, VIM-2, and NDM-1 through a straightforward computational workflow using virtual screening approaches. The screening pipeline started by assessing Lipinski’s rule of five (RO5), drug-likeness, and pan-assay interference compounds (PAINS) which were used to generate a pharmacophore model using D-captopril as a standard inhibitor. The process was followed by the consensus docking protocol and molecular dynamic (MD) simulation combined with the molecular mechanics Poisson-Boltzmann Surface Area (MM-PBSA) method to compute the total binding free energy and evaluate the binding characteristics. The absorption, distribution, metabolism, elimination, and toxicity (ADMET) profiles of the compounds were also analyzed, and the search space decreased to the final two inhibitory candidates for B1 subclass MBLs, which fulfilled all criteria for further experimental evaluation. Communicated by Ramaswamy H. Sarma</p

Final selected CTL, HTL and LBL epitopes for multi-epitope vaccines construction.

Final selected CTL, HTL and LBL epitopes for multi-epitope vaccines construction.</p

S1 Fig -

Prediction of the secondary structure of the construct 1 (A) and construct 2 (B) vaccines. The predicted results showed that among 686 amino acids in the construct 1, 268 (39.07%), 135 (19.68%), 66 (9.62%) and 217 (31.63%) amino acids are involved in α-helix, extended strand, beta turn, and random coil, respectively. Our predicted outputs revealed that among 607 amino acids in the construct 2, 205 (33.77%), 132 (21.75%), 63 (10.38%) and 207 (34.10%) amino acids are involved in α-helix, extended strand, beta turn, and random coil, respectively. (DOCX)</p

Multiple alignment of the P7 protein sequences in HCV strains.

(PDF)</p

Cytotoxic T Lymphocyte (CTL) epitopes of the P7protein.

(DOCX)</p

S2 Fig -

Linear (A and C) and Discontinuous (B and D) B-cell epitopes of the construct 1 (A and B) and construct 2 (C and D) vaccines (colored spheres). (DOCX)</p

Helper T Lymphocyte (HTL) epitopes of the NS3 protein.

(DOCX)</p

Multiple alignment of the NS3 protein sequences in HCV strains.

(PDF)</p

The 3D view of the final system conformations.

The interface residues between two proteins TLRs (orange cartoon) and vaccines (magenta cartoon) residues (orange and magenta sticks) are labeled. Hydrogen bonds and hydrophobic contacts are presented as green dashed line and arc with spokes radiating, respectively. A and B indicate TLR4-construct 1 and TLR3-construct 2 complexes, respectively.</p