©2021-2032 All Rights Reserved. Online Journal of Bioinformatics. You may not store these pages in any form except for your own personal use. All other usage or distribution is illegal under international copyright treaties. Permission to use any of these pages in any other way besides the before mentioned must be gained in writing from the publisher. This article is exclusively copyrighted in its entirety to email@example.com publications. This article may be copied once but may not be, reproduced or re-transmitted without the express permission of the editors. Linking: To link to this page or any pages linking to this page you must link directly to this page only here rather than put up your own page.
Online Journal of Bioinformatics©
Volume 22 (3): 153-168, 2021.
Homology docking SHV β-lactamases for drug resistance.
Mohd Hassan Baig, Shazi Shakil and Asad U Khan.
Interdisciplinary Biotechnology Unit, Aligarh Muslim University, Aligarh, India
Baig MH, Shakil S, Khan AU., Homology docking SHV β-lactamases for drug resistance, Onl J Bioinform., 22 (3): 153-168, 2021. Extended-spectrum-β-lactamases (ESBLs) in bacteria impart resistance to cephalosporins. SHV enzymes in ESBLs and binding of SHV-48, SHV-61, SHV-89, SHV-95 or SHV-105 to β-lactamase inhibitors has not been reported. We generated homology 3D model structure of SHV enzymes validated for stereo chemical properties. We targeted active site amino acid residues of SHV enzyme model to predict binding of inhibitors by energy docking. All SHV variants except SHV-61 interacted with clavulanic acid through S70, S130, K234 and A237, as residues. Of 20 docking interactions S70 and A237 were crucial for correct positioning of inhibitors on binding sites in 12 and 14 instances, respectively. By energy and Ki calculations, Penem1 was most efficient inhibitor against all bacterial enzymes, excluding SHV-105, where LN1-255 was most efficient.
Key Words: SHV β-lactamases, Homology, Docking, 3D model, Drug resistance.