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Biofragments: An Approach towards Predicting Protein Function Using Biologically Related Fragments and its Application to Mycobacterium tuberculosis CYP126
Author(s) -
Hudson Sean A.,
Mashalidis Ellene H.,
Bender Andreas,
McLean Kirsty J.,
Munro Andrew W.,
Abell Chris
Publication year - 2014
Publication title -
chembiochem
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.05
H-Index - 126
eISSN - 1439-7633
pISSN - 1439-4227
DOI - 10.1002/cbic.201300697
Subject(s) - mycobacterium tuberculosis , computational biology , function (biology) , drug discovery , ligand (biochemistry) , chemical library , virtual screening , substrate (aquarium) , combinatorial chemistry , ligand efficiency , chemistry , stereochemistry , cytochrome p450 , biochemistry , biology , small molecule , enzyme , genetics , tuberculosis , medicine , ecology , receptor , pathology
We present a novel fragment‐based approach that tackles some of the challenges for chemical biology of predicting protein function. The general approach, which we have termed biofragments, comprises two key stages. First, a biologically relevant fragment library (biofragment library) can be designed and constructed from known sets of substrate‐like ligands for a protein class of interest. Second, the library can be screened for binding to a novel putative ligand‐binding protein from the same or similar class, and the characterization of hits provides insight into the basis of ligand recognition, selectivity, and function at the substrate level. As a proof‐of‐concept, we applied the biofragments approach to the functionally uncharacterized Mycobacterium tuberculosis ( Mtb ) cytochrome P450 isoform, CYP126. This led to the development of a tailored CYP biofragment library with notable 3D characteristics and a significantly higher screening hit rate (14 %) than standard drug‐like fragment libraries screened previously against Mtb CYP121 and 125 (4 % and 1 %, respectively). Biofragment hits were identified that make both substrate‐like type‐I and inhibitor‐like type‐II interactions with CYP126. A chemical‐fingerprint‐based substrate model was built from the hits and used to search a virtual TB metabolome, which led to the discovery that CYP126 has a strong preference for the recognition of aromatics and substrate‐like type‐I binding of chlorophenol moieties within the active site near the heme. Future catalytic analyses will be focused on assessing CYP126 for potential substrate oxidative dehalogenation.