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This repository presents an approach for ligand discovery for protein bindign pockets, by combining Monte Carlo (MC) simulations with the model Chai-1 (Chai-1 github, Chai-1 technical report). There are two types of simulations presented here: - The basic simulation explores chemical space by…
The main features of jakobagamia/ai-mclig are: Structure Prediction Models.
Open-source alternatives to jakobagamia/ai-mclig include: jwohlwend/boltz — Boltz is a deep learning molecular modeler and biomolecular structure prediction system. It uses neural network… google-deepmind/alphafold3 — AlphaFold3 is a biomolecular structure prediction model and bioinformatics structural analysis tool. It uses a deep… google-deepmind/alphafold — AlphaFold is a deep learning biology tool and structural bioinformatic pipeline designed to predict the… rosettacommons/deepab — Official repository for DeepAb: Antibody structure prediction using interpretable deep learning. The code, data, and… rosettacommons/fvhallucinator — The code for FvHallucinator is made available under the Rosetta-DL license as part of the Rosetta-DL bundle. tencentai4s/tfold — English | 简体中文.
AlphaFold3 is a biomolecular structure prediction model and bioinformatics structural analysis tool. It uses a deep learning system to predict the three-dimensional shapes of proteins, DNA, RNA, and ligands. The system functions as a diffusion-based protein folding model that predicts the spatial coordinates of biomolecular atoms and interactions. It utilizes a GPU-accelerated inference pipeline to process genetic sequences and structural templates for molecular modeling. The project covers structural bioinformatics analysis and protein interaction modeling to determine the physical arrangem
Boltz is a deep learning molecular modeler and biomolecular structure prediction system. It uses neural network architectures to simulate the physical folding and docking of biomolecules, specifically predicting the three-dimensional shapes of protein and ligand complexes. The project functions as a protein-ligand complex predictor and binding affinity predictor, estimating the strength and probability of molecular interactions between ligands and targets. These capabilities are applied to computer aided drug design, including ligand binding affinity prediction and protein-ligand interaction
AlphaFold is a deep learning biology tool and structural bioinformatic pipeline designed to predict the three-dimensional shapes of proteins from their amino acid sequences. It functions as a machine learning system capable of generating 3D molecular models for both monomeric proteins and multimeric protein complexes, including homomers and heteromers. The system incorporates evolutionary information through multiple sequence alignment to identify physical proximity between residues. It utilizes a neural network architecture featuring spatial attention mechanisms and iterative refinement to d
Structure prediction and design of proteins with noncanonical amino acids.