Metallo-β-lactamases (MBLs) producing bacteria especially the ones with New Delhi metallo-beta-lactamase-1 (NDM-1) and its variants can potentially hydrolyse all the major β-lactam antibiotics, ultimately escalating anti-microbial resistance world-wide. There is a dearth of approved inhibitors to combat NDM and other MBLs producing bacteria. Hence we focussed to find novel inhibitor(s) in-silico which can potentially suppress the activity of NDM/MBLs. A total of 2400 compounds were virtually screened to identify a promising carboxylic acid-containing compound (CID-53986787) analogous to NDM antagonist Captopril. Our lead compound can bind adjacent to the active site zinc ions (Zn1 and Zn2) in all highly resistant NDM variants. CID-53986787 possesses ~ 5–8% higher binding affinity than Captopril, exhibiting molecular interactions with crucial residues that can destabilize the hydrolytic activity of NDM. CID-53986787 was virtually evaluated to ascertain its safe pharmacological/toxicity profile. Molecular dynamics simulation studies further elucidated its stable interaction with the target protein (NDM-1).
Metallo-β-lactamases (MBLs) producing bacteria especially the ones with New Delhi metallo-beta-lactamase-1 (NDM-1) and its variants can potentially hydrolyse all the major β-lactam antibiotics, ultimately escalating anti-microbial resistance world-wide. There is a dearth of approved inhibitors to combat NDM and other MBLs producing bacteria. Hence we focussed to find novel inhibitor(s) in-silico which can potentially suppress the activity of NDM/ MBLs. 2400 compounds were virtually screened to identify a promising carboxylic acid-containing compound (CID-53986787) analogous to NDM antagonist Captopril. Our lead compound can bind adjacent to the active site zinc ions (Zn1 and Zn2) in all highly resistant NDM variants. CID-53986787 possesses ~5-8% higher binding affinity than Captopril, exhibiting molecular interactions with crucial residues that can destabilize the hydrolytic activity of NDM. CID-53986787 was virtually evaluated to ascertain its safe pharmacological/ toxicity profile. Molecular dynamics simulation studies elucidated its stable interaction with the target protein (NDM-1).
Findings reveal that central residues play a significant role in determining the functional properties of proteins. These results have implications in predicting binding/active site residues, specifically in the context of drug designing, if additional information concerning ligand binding is exploited.
Proteins are biochemical compounds made up of one or more polypeptides in a specific order, typically folded into a functionally active form. Proteins are categorized into four different structural classes according to the topology of αhelices and β-strands. In this study, we modeled these four structural classes as an undirected network depicting amino acids as nodes and interaction between them as edges. Results infer that basic protein classes can be easily recognized as well as distinguished by utilizing protein contact maps (PCM). Toward studying the globin-like fold, the helix-loop-helix region contacts were seen to be of a unique pattern, and these remained in all the folds. Further, the averaged diagonal contacts were analyzed and identified those contacts in α/β proteins were higher in comparison with the other class. Interesting, we noticed that anti-parallel beta sheets were dominant in all-β and α + β classes that lead to similar diagonal patterns. Network properties of all four basic classes were analyzed and found to possess small-world property. Findings infer that PCM may assist classify protein structure classes and it also helps in evaluating the predicted protein structures.
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