Showing 3 open source projects for "structural frame 3d"

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  • 1
    Protenix

    Protenix

    A trainable PyTorch reproduction of AlphaFold 3

    Protenix is an open-source, trainable PyTorch reimplementation of AlphaFold 3, developed by ByteDance with the goal of democratizing high-accuracy protein structure prediction for computational biology and drug-discovery research. Protenix provides a complete pipeline for turning protein sequences (with optional MSA / sequence alignment) or structural inputs (e.g. PDB/CIF) into full 3D atomic-level structure predictions. It supports both “full” models and lightweight variants such as “Protenix-Mini,” offering a trade-off between speed/compute cost and predictive accuracy — making structure prediction accessible even in resource-constrained environments. The project also includes support for constraints (e.g., specifying residue- or atom-level contact constraints, or pocket constraints) to guide predictions toward biologically or experimentally relevant conformations, which enhances its utility for tasks like modeling complexes, ligands, or antibody–antigen interactions.
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  • 2

    xPyder PyMOL Plugin

    Analyze and visualize coupled residues and their networks in proteins

    xPyder is a PyMOL plugin to analyze and visualize on the 3D structure dynamical cross-correlation matrices (DCCM), linear mutual information (LMI), communication propensities (CP), intra- and inter-molecular interactions (e.g. PSN), and more, to produce highly customizable publication-quality images. xPyder identifies networks (using concepts from graph theory, such as hubs and shortest path searching), compares matrices and focuses the analysis on relevant information by filtering the data using a modular, user-expandable plugin system that takes advantage of structural and dynamical information, contributing to bridge the gap between dynamical and mechanical properties at the molecular level.
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  • 3
    SureFit generates 3D mesh surfaces (in VTK and Caret formats) from 3D structural MRI volumes (in formats such as Analyze, AFNI, raw).
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