Identification of Protein Cryptic Sites via Conformational Dynamics Capturing and Water-Based Pocket Characterization in Molecular Dynamics Simulations

Employing molecular dynamics (MD) simulation to study the formation of novel protein cryptic sites has attracted increasing interest in the field of drug discovery. One specific challenge in this area is finding a viable method to accurately identify and characterize cryptic site transitions from MD simulation results while minimizing the need for extensive human input. Since the formation of cryptic sites often involves significant conformational changes in the protein structure, a method capable of capturing and describing these dynamic pocket transitions with precision is essential. In this paper, we present a new procedure, Conformational Dynamics Capturing and Water-Based Characterization (CDC-WBC). This procedure dynamically identifies the cryptic site region by tracking protein conformational changes observed during molecular dynamics (MD) simulations. The procedure also incorporates water density information to enhance the characterization of cryptic sites across frames. We evaluate the CDC-WBC procedure by applying it to characterize the opening process of the two well-studied cryptic sites in TEM1 β-lactamase. The results demonstrate that the CDC-WBC method accurately captures the open-closed transitions of the two cryptic sites. For comparison, three commonly used protein cavity detection methods in cryptic sites studies, POVME2, Epock, and MDpocket, are applied to identify the "CBT" cryptic site in TEM1 β-lactamase. The results show that the CDC-WBC method outperforms these methods in characterizing the transitions of the "CBT" cryptic site. Additionally, using a benchmark set of 84 protein systems (93 cryptic pockets) from the CryptoSite data set, CDC-WBC consistently shows better performance in distinguishing between the open and closed states of cryptic sites, further highlighting its capability for precise characterization of dynamic cryptic site transitions. The detailed implementation of the CDC-WBC procedure and demo data sets are uploaded to GitHub: https://github.com/TianmingQu/CDC-WBC.git.

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Publication Details

Journal
Journal of Chemical Theory and Computation
Published
2025-08-28
DOI
https://doi.org/10.1021/acs.jctc.5c01019
Primary Topic
Protein Structure and Dynamics
Type
article
Field-Weighted Citation Impact
0.00

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article

Identification of Protein Cryptic Sites via Conformational Dynamics Capturing and Water-Based Pocket Characterization in Molecular Dynamics Simulations

Wei Yang, Tianming Qu, Steven L. Austin, Lianqing Zheng et al.
Journal of Chemical Theory and Computation
Protein Structure and Dynamics
article

Identification of Protein Cryptic Sites via Conformational Dynamics Capturing and Water-Based Pocket Characterization in Molecular Dynamics Simulations

Wei Yang, Tianming Qu, Steven L. Austin, Lianqing Zheng, J. Zhang
article en

Abstract

Employing molecular dynamics (MD) simulation to study the formation of novel protein cryptic sites has attracted increasing interest in the field of drug discovery. One specific challenge in this area is finding a viable method to accurately identify and characterize cryptic site transitions from MD simulation results while minimizing the need for extensive human input. Since the formation of cryptic sites often involves significant conformational changes in the protein structure, a method capable of capturing and describing these dynamic pocket transitions with precision is essential. In this paper, we present a new procedure, Conformational Dynamics Capturing and Water-Based Characterization (CDC-WBC). This procedure dynamically identifies the cryptic site region by tracking protein conformational changes observed during molecular dynamics (MD) simulations. The procedure also incorporates water density information to enhance the characterization of cryptic sites across frames. We evaluate the CDC-WBC procedure by applying it to characterize the opening process of the two well-studied cryptic sites in TEM1 β-lactamase. The results demonstrate that the CDC-WBC method accurately captures the open-closed transitions of the two cryptic sites. For comparison, three commonly used protein cavity detection methods in cryptic sites studies, POVME2, Epock, and MDpocket, are applied to identify the "CBT" cryptic site in TEM1 β-lactamase. The results show that the CDC-WBC method outperforms these methods in characterizing the transitions of the "CBT" cryptic site. Additionally, using a benchmark set of 84 protein systems (93 cryptic pockets) from the CryptoSite data set, CDC-WBC consistently shows better performance in distinguishing between the open and closed states of cryptic sites, further highlighting its capability for precise characterization of dynamic cryptic site transitions. The detailed implementation of the CDC-WBC procedure and demo data sets are uploaded to GitHub: https://github.com/TianmingQu/CDC-WBC.git.

Journal of Chemical Theory and ComputationVol. 21(17)
Florida State University (US)
National Institute of General Medical Sciences
Clean water and sanitation
Openalex Percentile: Top 80%
Protein Structure and Dynamics
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