Related Experiment Video
Updated: May 26, 2025
11:44
Synthesis and Structure Determination of µ-Conotoxin PIIIA Isomers with Different Disulfide Connectivities
Published on: October 2, 2018
12.5K
ConoGPT: Fine-Tuning a Protein Language Model by Incorporating Disulfide Bond Information for Conotoxin Sequence
Guohui Zhao1, Cheng Ge2, Wenzheng Han1
1College of Computer Science and Technology, Ocean University of China, Songling Road, Qingdao 266100, China.
Toxins
|February 25, 2025
Summary
ConoGPT, a novel AI model, generates conotoxin sequences with disulfide bond information, overcoming limitations of traditional methods. This approach accelerates the discovery of new drug candidates targeting nicotinic acetylcholine receptors.
Area of Science:
- Biochemistry
- Computational Biology
- Drug Discovery
Background:
- Conotoxins are valuable peptides from Conus snails with therapeutic potential.
- Traditional conotoxin production is costly, time-consuming, and limits sequence diversity.
Purpose of the Study:
- To develop an AI model (ConoGPT) for efficient and diverse conotoxin sequence generation.
- To incorporate disulfide bond information into AI models for improved conotoxin design.
Main Methods:
- Fine-tuning the ProtGPT2 model with disulfide bond data to create ConoGPT.
- Utilizing molecular docking and dynamics simulations to assess generated sequences.
- Evaluating physicochemical properties and structural integrity of novel conotoxin candidates.
Main Results:
- ConoGPT generates conotoxin sequences with authentic physicochemical properties.
- ConoGPT outperforms models lacking disulfide bond information in generating ordered structures.
- Generated sequences show high binding affinity to nicotinic acetylcholine receptors (nAChR).
- Molecular dynamics confirm the stability of designed conotoxins.
Conclusions:
- ConoGPT offers a novel computational approach for conotoxin design and discovery.
- The model facilitates the generation of functional peptides with therapeutic potential.
- This strategy enhances the exploration of conotoxin sequence space for drug development.
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