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Predicting cryptic ligand binding sites based on normal modes guided conformational sampling
  • Wenjun Zheng
Wenjun Zheng
University at Buffalo

Corresponding Author:[email protected]

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To greatly expand the druggable genome, fast and accurate predictions of cryptic sites for small molecules binding in target proteins are in high demand. In this study, we have developed a fast and simple conformational sampling scheme guided by normal modes solved from the coarse-grained elastic models followed by atomistic backbone refinement and sidechain repacking. Despite the observations of complex and diverse conformational changes associated with ligand binding, we found that simply sampling along each of the lowest 30 modes is near optimal for adequately restructuring cryptic sites so they can be detected by existing pocket finding programs like fpocket and concavity. We further trained machine-learning protocols to optimize the combination of the sampling-enhanced pocket scores with other dynamic and conservation scores, which only slightly improved the performance. As assessed based on a training set of 84 known cryptic sites and a test set of 14 proteins, our method achieved high accuracy of prediction (with area under the receiver operating characteristic curve > 0.8) comparable to the CryptoSite server. Compared with CryptoSite and other methods based on extensive molecular dynamics simulation, our method is much faster (1-2 hours for an average-size protein) and simpler (using only pocket scores), so it is suitable for high-throughput processing of large datasets of protein structures at the genome scale.
28 Jun 2020Submitted to PROTEINS: Structure, Function, and Bioinformatics
29 Jun 2020Submission Checks Completed
29 Jun 2020Assigned to Editor
23 Jul 2020Reviewer(s) Assigned
09 Aug 2020Review(s) Completed, Editorial Evaluation Pending
26 Aug 2020Editorial Decision: Revise Minor
27 Sep 20201st Revision Received
28 Sep 2020Submission Checks Completed
28 Sep 2020Assigned to Editor
28 Sep 2020Reviewer(s) Assigned
03 Nov 2020Review(s) Completed, Editorial Evaluation Pending
21 Nov 2020Editorial Decision: Accept
Apr 2021Published in Proteins: Structure, Function, and Bioinformatics volume 89 issue 4 on pages 416-426. 10.1002/prot.26027