Computational Analysis and Binding Site Identification of Type III Secretion System ATPase from Pseudomonas aeruginosa

• Published in: Interdisciplinary sciences : computational life sciences 2016-12, Vol.8 (4), p.403-411
• Main Authors: Dash, Raju, Hosen, S. M. Zahid, Sultana, Tasniha, Junaid, Md, Majumder, Mohuya, Ishat, Ismat Ara, Uddin, Mir Muhammad Nasir
• Format: Article
• Language: English
• Subjects: Adenosine triphosphatase; Adenosine Triphosphatases - chemistry; Adenosine Triphosphatases - metabolism; Amino acid sequence; Bacteria; Bacterial Proteins - chemistry; Bacterial Proteins - metabolism; Binding sites; Biomedical and Life Sciences; Chemical compounds; Computation; Computational Biology - methods; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Appl. in Life Sciences; Computer applications; Computer simulation; Drug development; Enzymes; Gram-negative bacteria; Health Sciences; Homology; Life Sciences; Mathematical and Computational Physics; Medicine; Molecular docking; Molecular Docking Simulation; Original Research Article; Pharmacology; Phylogeny; Pseudomonas aeruginosa; Pseudomonas aeruginosa - enzymology; Residues; Secretion; Secretions; Statistics for Life Sciences; Target recognition; Theoretical; Theoretical and Computational Chemistry; Type III Secretion Systems - metabolism; Virulence; Virulence factors
• ISSN: 1913-2751; 1867-1462
• DOI: 10.1007/s12539-015-0121-z

In many gram-negative bacteria, the type III secretion system (T3SS), as a virulence factor, is an attractive target for developing novel antibacterial. Regarding this, in our study, we aimed to identify the putative drug target for Pseudomonas aeruginosa , considering ATPase enzyme involved in the type III secretion system. Selective protein sequence of P. aeruginosa involved in the T3SS was retrieved from NCBI databases, and its homologues were subjected to phylogenetic analysis. Its association in T3SS was analyzed via STRING, and the 3D structure was determined by means of homology modeling followed by intensive optimization and validation. The binding site was predicted by 3DLigandSite and examined through molecular docking simulation by Autodock Vina with salicylidene acylhydrazide class of virulence-blocking compounds. PROCHECK analysis showed that 96.7 % of the residues were in the most favored regions, 1.9 % were in the additional allowed region, and 1.4 % were in the generously allowed region of the Ramachandran plot. The refined model yielded ERRAT scores of 88.124 and Verify3D value of 0.2, which indicates that the environmental profile of the model is good. The best binding affinity was observed by ME0055 compound, and ALA160, ALA161, GlY162, GLY163, GLY164, GLY165, SER166, THR167, TYR338, and PRO339 residues were found to be having complementary in the ligand-binding site. However, these findings should be further confirmed by wet lab studies for design a targeted therapeutic agent.