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arxiv:2502.00508

PyMOLfold: Interactive Protein and Ligand Structure Prediction in PyMOL

Published on Feb 1
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Abstract

PyMOLfold integrates AI-based protein structure prediction and visualization within PyMOL, allowing direct prediction of protein structures from amino acid sequences and ligand placement using models like ESM3, Boltz-1, and Chai-1.

AI-generated summary

PyMOLfold is a flexible and open-source plugin designed to seamlessly integrate AI-based protein structure prediction and visualization within the widely used PyMOL molecular graphics system. By leveraging state-of-the-art protein folding models such as ESM3, Boltz-1, and Chai-1, PyMOLfold allows researchers to directly predict protein tertiary structures from amino acid sequences without requiring external tools or complex workflows. Furthermore, with certain models, users can provide a SMILES string of a ligand and have the small molecule placed in the protein structure. This unique capability bridges the gap between computational folding and structural visualization, enabling users to input a primary sequence, perform a folding prediction, and immediately explore the resulting 3D structure within the same intuitive platform.

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