@article { ISI:000357458400018, title = {In silico ligand binding studies of cyanogenic beta-glucosidase, dhurrinase-2 from Sorghum bicolor}, journal = {Journal of Molecular Modeling}, volume = {21}, number = {7}, year = {2015}, month = {JUL}, pages = {184}, publisher = {SPRINGER}, address = {233 SPRING ST, NEW YORK, NY 10013 USA}, abstract = {

Dhurrinase, a cyanogenic beta-glucosidase from Sorghum bicolor is the key enzyme responsible for the hydrolysis of dhurrin to produce toxic hydrogen cyanide, as a part of plant defence mechanism. Dhurrinase 1 (SbDhr1) and dhurrinase 2 (SbDhr2), two isozymes have been isolated and characterized from S. bicolor. However, there is no information in the literature about the three dimensional (3D) structure of SbDhr2 and molecular interactions involved between the protein and ligand. In this study, the three dimensional structure of SbDhr2 was built based on homology modeling by using the X-ray crystallographic structure of its close homologue SbDhr1 as the template. The generated 3D model was energy minimized and the quality was validated by Ramachndran plot, various bioinformatic tools and their relevant parameters. Stability, folding-unfolding and flexibility of the modeled SbDhr2 was evaluated on the basis of RMSD, radius of gyration (R-g) and RMSF values respectively, obtained through molecular dynamic (MD) simulation. Further, molecular docking was performed with its natural substrate dhurrin, one substrate analogue, three un-natural substrates, and one inhibitor. Analysis of molecular interactions in the SbDhr2-ligand complexes revealed the key amino acid residues responsible to stabilize the ligands within the binding pocket through non-bonded interactions and some of them were found to be conserved (Glu239, Tyr381, Trp426, Glu454, Trp511). Reasonably broader substrate specificity of SbDhr2 was explained through the wider entrance passage observed in comparison to SbDhr1.

}, keywords = {beta-Glucosidase, Dhurrinase, Molecular docking, Molecular dynamic simulation, Sorghum bicolor}, issn = {1610-2940}, doi = {10.1007/s00894-015-2730-1}, author = {Mahajan, Chavi and Patel, Krunal and Khan, Bashir Mohammad and Rawal, Shuban S.} } @article {45648, title = {Effect of the amino acid L-histidine on methane hydrate growth kinetics}, journal = {Journal of Natural Gas Science and Engineering}, volume = {35}, year = {2016}, month = {SEP}, pages = {1453-1462}, type = {Article}, abstract = {

In the present study, the effect of a polar amino acid, L-histidine on methane hydrate growth kinetics has been investigated. Methane hydrate formation experiments were carried out in a stirred tank reactor setup at pressure and temperature conditions of 274.15 K and 5.0 MPa respectively. Two different concentrations (0.1 and 1 wt \%) of L-histidine were studied. Hydrate growth through molecular dynamic (MD) simulation was also studied; pressure and temperature conditions for the simulations were set at 10.0 MPa and 270.0 K, while the concentration of L-histidine was kept fixed at 0.94 wt \%. Hydrate formation runs using MD simulation were carried out with optimal concentration of methane in water. The presence of L-histidine in the system was found to significantly enhance methane hydrate growth kinetics as compared to pure water for both experimental and MD simulation runs. Final gas consumption with 1 wt \% L-histidine was found to be comparable to that with 1 wt \% SDS, the most commonly used additive for hydrate promotion studies. L-histidine is a benign additive which offers considerable enhancement in methane hydrate formation kinetics and can be utilized for various hydrate based technologies such as methane storage and transport. (C) 2016 Elsevier B.V. All rights reserved.

}, keywords = {Amino acid, Crystal growth, Gas hydrate, kinetics, Molecular dynamic simulation}, issn = {1875-5100}, doi = {10.1016/j.jngse.2016.05.052}, author = {Bhattacharjee, Gaurav and Choudhary, Nilesh and Kumar, Asheesh and Chakrabarty, Suman and Kumar, Rajnish} } @article {47391, title = {Molecular phylogeny, structure modeling and in silico screening of putative inhibitors of aerolysin of Aeromonas hydrophila EUS112}, journal = {Journal of Biomolecular Structure \& Dynamics}, volume = {40}, year = {2022}, month = {JUN}, type = {Article}, abstract = {

Aeromonas hydrophila, a Gram-negative bacterium, causes diseases in fish, resulting in excessive loss to the aquaculture industry. Aeromonas is a highly heterogeneous group of bacteria, and the heterogeneity of the genus is attributed to variation and diversity in the virulence factors and toxins among various Aeromonas strains. One of the major toxins aerolysin, secreted by the bacterium, causes hemorrhagic-septicemia and diarrhea and can serve as a drug target. Here, we describe characterization, molecular phylogeny, and homology modeling of the aerolysin of A. hydrophila strain EUS112 (Ah(EUS112)) cloned in our lab. The encoded aerolysin is 485 amino acids long with an N-terminal signal sequence of 23 amino acids. Phylogenetic analysis of the aerolysin of Ah(EUS112) revealed that it belongs to a diverse group of toxins, showing maximum similarity with aerolysins of other Aeromonas strains followed by Vibrio toxin. The homology model of the mature aerolysin of Ah(EUS112) was generated using the crystal structure of a mutant aerolysin (PDB\#3g4n) as the template, which showed that the encoded aerolysin exists as a channel protein. Validation of the generated model using bioinformatics tool confirmed it to be a good quality model that can be used for drug design. Molecular dock analysis revealed that drugs, aralia-saponin I, cyclamin, ardisiacrispin B, and aralia-saponin II bind to aerolysin with a higher affinity as compared to other drugs and at functionally important amino acids of aerolysin. Hence, these molecules can act as an effective therapeutics for inhibiting the aerolysin pore formation and curtail the severity of Aeromonas infection. Communicated by Ramaswamy H. Sarma

}, keywords = {Aerolysin, homology modeling, Molecular docking, Molecular dynamic simulation, phylogenetic tree}, issn = {0739-1102}, doi = {10.1080/07391102.2021.1918254, Early Access Date = APR 2021}, author = {Yadav, Sunita Kumari and Panwar, Deepak and Singh, Ankita and Tellis, Meenakshi B. and Joshi, Rakesh Shamsunder and Dixit, Aparna} }