1
|
Wang JM, Cui RK, Qian ZK, Yang ZZ, Li Y. Mining channel-regulated peptides from animal venom by integrating sequence semantics and structural information. Comput Biol Chem 2024; 109:108027. [PMID: 38340414 DOI: 10.1016/j.compbiolchem.2024.108027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 01/24/2024] [Accepted: 02/04/2024] [Indexed: 02/12/2024]
Abstract
Channel-regulated peptides (CRPs) derived from animal venom hold great promise as potential drug candidates for numerous diseases associated with channel proteins. However, discovering and identifying CRPs using traditional bio-experimental methods is a time-consuming and laborious process. While there were a few computational studies on CRPs, they were limited to specific channel proteins, relied heavily on complex feature engineering, and lacked the incorporation of multi-source information. To address these problems, we proposed a novel deep learning model, called DeepCRPs, based on graph neural networks for systematically mining CRPs from animal venom. By combining the sequence semantic and structural information, the classification performance of four CRPs was significantly enhanced, reaching an accuracy of 0.92. This performance surpassed baseline models with accuracies ranging from 0.77 to 0.89. Furthermore, we employed advanced interpretable techniques to explore sequence and structural determinants relevant to the classification of CRPs, yielding potentially valuable bio-function interpretations. Comprehensive experimental results demonstrated the precision and interpretive capability of DeepCRPs, making it an accurate and bio-explainable suit for the identification and categorization of CRPs. Our research will contribute to the discovery and development of toxin peptides targeting channel proteins. The source data and code are freely available at https://github.com/liyigerry/DeepCRPs.
Collapse
Affiliation(s)
- Jian-Ming Wang
- College of Mathematics and Computer Science, Dali University, Dali, China
| | - Rong-Kai Cui
- College of Mathematics and Computer Science, Dali University, Dali, China
| | - Zheng-Kun Qian
- College of Mathematics and Computer Science, Dali University, Dali, China
| | - Zi-Zhong Yang
- Yunnan Provincial Key Laboratory of Entomological Biopharmaceutical R&D, College of Pharmacy, Dali University, Dali, China
| | - Yi Li
- College of Mathematics and Computer Science, Dali University, Dali, China.
| |
Collapse
|
2
|
Ngo K, Lopez Mateos D, Han Y, Rouen KC, Ahn SH, Wulff H, Clancy CE, Yarov-Yarovoy V, Vorobyov I. Elucidating molecular mechanisms of protoxin-II state-specific binding to the human NaV1.7 channel. J Gen Physiol 2024; 156:e202313368. [PMID: 38127314 PMCID: PMC10737443 DOI: 10.1085/jgp.202313368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 09/08/2023] [Accepted: 12/04/2023] [Indexed: 12/23/2023] Open
Abstract
Human voltage-gated sodium (hNaV) channels are responsible for initiating and propagating action potentials in excitable cells, and mutations have been associated with numerous cardiac and neurological disorders. hNaV1.7 channels are expressed in peripheral neurons and are promising targets for pain therapy. The tarantula venom peptide protoxin-II (PTx2) has high selectivity for hNaV1.7 and is a valuable scaffold for designing novel therapeutics to treat pain. Here, we used computational modeling to study the molecular mechanisms of the state-dependent binding of PTx2 to hNaV1.7 voltage-sensing domains (VSDs). Using Rosetta structural modeling methods, we constructed atomistic models of the hNaV1.7 VSD II and IV in the activated and deactivated states with docked PTx2. We then performed microsecond-long all-atom molecular dynamics (MD) simulations of the systems in hydrated lipid bilayers. Our simulations revealed that PTx2 binds most favorably to the deactivated VSD II and activated VSD IV. These state-specific interactions are mediated primarily by PTx2's residues R22, K26, K27, K28, and W30 with VSD and the surrounding membrane lipids. Our work revealed important protein-protein and protein-lipid contacts that contribute to high-affinity state-dependent toxin interaction with the channel. The workflow presented will prove useful for designing novel peptides with improved selectivity and potency for more effective and safe treatment of pain.
Collapse
Affiliation(s)
- Khoa Ngo
- Biophysics Graduate Group, University of California, Davis, Davis, CA, USA
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, USA
| | - Diego Lopez Mateos
- Biophysics Graduate Group, University of California, Davis, Davis, CA, USA
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, USA
| | - Yanxiao Han
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, USA
| | - Kyle C. Rouen
- Biophysics Graduate Group, University of California, Davis, Davis, CA, USA
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, USA
| | - Surl-Hee Ahn
- Department of Chemical Engineering, University of California, Davis, Davis, CA, USA
| | - Heike Wulff
- Department of Pharmacology, University of California, Davis, Davis, CA, USA
| | - Colleen E. Clancy
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, USA
- Department of Pharmacology, University of California, Davis, Davis, CA, USA
- Center for Precision Medicine and Data Science, University of California, Davis, Davis, CA, USA
| | - Vladimir Yarov-Yarovoy
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, USA
- Department of Anesthesiology and Pain Medicine, University of California, Davis, Davis, CA, USA
| | - Igor Vorobyov
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA, USA
- Department of Pharmacology, University of California, Davis, Davis, CA, USA
| |
Collapse
|