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67 lines
2.3 KiB
Python
67 lines
2.3 KiB
Python
PREDICT_TARGET_STRUCTURE_TOOL = {
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"type": "function",
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"function": {
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"name": "predict_target_structure_alphafold2",
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"description": "Predicts the 3D structure of the target protein sequence using AlphaFold2.",
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"parameters": {
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"type": "object",
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"properties": {
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"sequence": {"type": "string", "description": "Amino acid sequence of the target protein."},
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},
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"required": ["sequence"]
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}
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}
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}
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DESIGN_BINDER_BACKBONE_TOOL = {
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"type": "function",
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"function": {
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"name": "design_binder_backbone_rfdiffusion",
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"description": "Generates a novel protein binder backbone using RFDiffusion, conditioned on the target protein structure.",
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"parameters": {
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"type": "object",
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"properties": {
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"contigs": {"type": "string", "description": "RFDiffusion contigs (e.g., 'A1-100/0 50-70')."},
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"hotspot_residues": {"type": "array", "items": {"type": "string"}, "description": "Optional hotspot residues (e.g., ['A50', 'A52'])."},
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},
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"required": ["contigs"]
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}
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}
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}
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DESIGN_BINDER_SEQUENCE_TOOL = {
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"type": "function",
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"function": {
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"name": "design_binder_sequence_proteinmpnn",
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"description": "Designs an amino acid sequence for the generated binder backbone.",
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"parameters": {
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"type": "object",
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"properties": {
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"sampling_temp": {"type": "array", "items": {"type": "number"}, "description": "Sampling temperatures (e.g., [0.1, 0.2]). Default [0.1]."}
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},
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"required": []
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}
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}
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}
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EVALUATE_COMPLEX_TOOL = {
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"type": "function",
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"function": {
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"name": "evaluate_binder_complex_alphafold2_multimer",
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"description": "Predicts the complex structure of target and designed binder, providing quality scores.",
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"parameters": {
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"type": "object",
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"properties": {
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"relax_prediction": {"type": "boolean", "description": "Whether to relax the prediction. Default True."}
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},
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"required": []
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}
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}
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}
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ALL_TOOLS_LIST = [
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PREDICT_TARGET_STRUCTURE_TOOL,
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DESIGN_BINDER_BACKBONE_TOOL,
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DESIGN_BINDER_SEQUENCE_TOOL,
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EVALUATE_COMPLEX_TOOL
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]
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