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ConoGPT: Fine-Tuning a Protein Language Model by Incorporating Disulfide Bond Information for Conotoxin Sequence Generation
by
Liu, Hao
, Ge, Cheng
, Han, Wenzheng
, Zhao, Guohui
, Yu, Rilei
in
Acetylcholine receptors (nicotinic)
/ activity prediction
/ Amino Acid Sequence
/ Amino acids
/ Analysis
/ Animals
/ Biological activity
/ Chemical bonds
/ Chemical properties
/ Chemical synthesis
/ Conotoxins
/ Conotoxins - chemistry
/ Conotoxins - metabolism
/ Conus Snail
/ Diffusion models
/ Disulfides - chemistry
/ DNA sequencing
/ Drug development
/ Dynamic stability
/ Entropy
/ Enzymes
/ In vivo methods and tests
/ Language
/ Marine mollusks
/ Marine toxins
/ Molecular docking
/ Molecular Docking Simulation
/ Molecular dynamics
/ Molecular Dynamics Simulation
/ Mollusks
/ Nucleotide sequencing
/ peptide generation
/ Peptides
/ Physicochemical properties
/ protein language model
/ Proteins
/ receptors
/ Receptors, Nicotinic - metabolism
/ Shellfish
/ Toxins
2025
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ConoGPT: Fine-Tuning a Protein Language Model by Incorporating Disulfide Bond Information for Conotoxin Sequence Generation
by
Liu, Hao
, Ge, Cheng
, Han, Wenzheng
, Zhao, Guohui
, Yu, Rilei
in
Acetylcholine receptors (nicotinic)
/ activity prediction
/ Amino Acid Sequence
/ Amino acids
/ Analysis
/ Animals
/ Biological activity
/ Chemical bonds
/ Chemical properties
/ Chemical synthesis
/ Conotoxins
/ Conotoxins - chemistry
/ Conotoxins - metabolism
/ Conus Snail
/ Diffusion models
/ Disulfides - chemistry
/ DNA sequencing
/ Drug development
/ Dynamic stability
/ Entropy
/ Enzymes
/ In vivo methods and tests
/ Language
/ Marine mollusks
/ Marine toxins
/ Molecular docking
/ Molecular Docking Simulation
/ Molecular dynamics
/ Molecular Dynamics Simulation
/ Mollusks
/ Nucleotide sequencing
/ peptide generation
/ Peptides
/ Physicochemical properties
/ protein language model
/ Proteins
/ receptors
/ Receptors, Nicotinic - metabolism
/ Shellfish
/ Toxins
2025
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ConoGPT: Fine-Tuning a Protein Language Model by Incorporating Disulfide Bond Information for Conotoxin Sequence Generation
by
Liu, Hao
, Ge, Cheng
, Han, Wenzheng
, Zhao, Guohui
, Yu, Rilei
in
Acetylcholine receptors (nicotinic)
/ activity prediction
/ Amino Acid Sequence
/ Amino acids
/ Analysis
/ Animals
/ Biological activity
/ Chemical bonds
/ Chemical properties
/ Chemical synthesis
/ Conotoxins
/ Conotoxins - chemistry
/ Conotoxins - metabolism
/ Conus Snail
/ Diffusion models
/ Disulfides - chemistry
/ DNA sequencing
/ Drug development
/ Dynamic stability
/ Entropy
/ Enzymes
/ In vivo methods and tests
/ Language
/ Marine mollusks
/ Marine toxins
/ Molecular docking
/ Molecular Docking Simulation
/ Molecular dynamics
/ Molecular Dynamics Simulation
/ Mollusks
/ Nucleotide sequencing
/ peptide generation
/ Peptides
/ Physicochemical properties
/ protein language model
/ Proteins
/ receptors
/ Receptors, Nicotinic - metabolism
/ Shellfish
/ Toxins
2025
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ConoGPT: Fine-Tuning a Protein Language Model by Incorporating Disulfide Bond Information for Conotoxin Sequence Generation
Journal Article
ConoGPT: Fine-Tuning a Protein Language Model by Incorporating Disulfide Bond Information for Conotoxin Sequence Generation
2025
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Overview
Conotoxins are a class of peptide toxins secreted by marine mollusks of the Conus genus, characterized by their unique mechanism of action and significant biological activity, making them highly valuable for drug development. However, traditional methods of acquiring conotoxins, such as in vivo extraction or chemical synthesis, face challenges of high costs, long cycles, and limited exploration of sequence diversity. To address these issues, we propose the ConoGPT model, a conotoxin sequence generation model that fine-tunes the ProtGPT2 model by incorporating disulfide bond information. Experimental results demonstrate that sequences generated by ConoGPT exhibit high consistency with authentic conotoxins in physicochemical properties and show considerable potential for generating novel conotoxins. Furthermore, compared to models without disulfide bond information, ConoGPT outperforms in terms of generating sequences with ordered structures. The majority of the filtered sequences were shown to possess significant binding affinities to nicotinic acetylcholine receptor (nAChR) targets based on molecular docking. Molecular dynamics simulations of the selected sequences further confirmed the dynamic stability of the generated sequences in complex with their respective targets. This study not only provides a new technological approach for conotoxin design but also offers a novel strategy for generating functional peptides.
Publisher
MDPI AG,MDPI
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