Identification of Protein Cryptic Sites via Conformational Dynamics Capturing and Water-Based Pocket Characterization in Molecular Dynamics Simulations
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| Titel: | Identification of Protein Cryptic Sites via Conformational Dynamics Capturing and Water-Based Pocket Characterization in Molecular Dynamics Simulations |
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| Autoren: | Tianming Qu, Steven L. Austin, Lianqing Zheng, James Zhang, Wei Yang |
| Publikationsjahr: | 2025 |
| Bestand: | Bath Spa University: Figshare |
| Schlagwörter: | Biophysics, Biochemistry, Medicine, Hematology, Computational Biology, Biological Sciences not elsewhere classified, Mathematical Sciences not elsewhere classified, Chemical Sciences not elsewhere classified, Physical Sciences not elsewhere classified, Information Systems not elsewhere classified, one specific challenge, extensive human input, demo data sets, attracted increasing interest, cryptic site region, 93 cryptic pockets, studied cryptic sites, cryptic sites studies, cryptosite data set, 84 protein systems, procedure dynamically identifies, two cryptic sites, https :// github, dynamic pocket transitions, conformational dynamics capturing, based pocket characterization, wbc method outperforms, md simulation results, cryptic sites, two well |
| Beschreibung: | 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 |
| Publikationsart: | article in journal/newspaper |
| Sprache: | unknown |
| DOI: | 10.1021/acs.jctc.5c01019.s001 |
| Verfügbarkeit: | https://doi.org/10.1021/acs.jctc.5c01019.s001 https://figshare.com/articles/journal_contribution/Identification_of_Protein_Cryptic_Sites_via_Conformational_Dynamics_Capturing_and_Water-Based_Pocket_Characterization_in_Molecular_Dynamics_Simulations/30005528 |
| Rights: | CC BY-NC 4.0 |
| Dokumentencode: | edsbas.AAA876BB |
| Datenbank: | BASE |
Nájsť tento článok vo Web of Science | 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 |
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| DOI: | 10.1021/acs.jctc.5c01019.s001 |