LDeng0205/confidence-bootstrapping
Implementation of the Confidence Bootstrapping procedure for protein-ligand docking.
This project offers a method to refine protein-ligand docking predictions. By taking existing protein structure and ligand data, it improves the accuracy of how small molecules might bind to proteins. Researchers in drug discovery or biochemistry would use this to better understand molecular interactions.
No commits in the last 6 months.
Use this if you need to improve the precision of protein-ligand docking simulations, especially for novel or less-studied protein binding sites.
Not ideal if you are looking for a simple, out-of-the-box docking solution without the need for finetuning or if you lack computational resources for training.
Stars
27
Forks
3
Language
Python
License
MIT
Category
Last pushed
Feb 29, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/LDeng0205/confidence-bootstrapping"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
pritampanda15/PandaDock
PandaDock: Physics based Molecular Docking with GNN Scoring
kexinhuang12345/DeepPurpose
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
BioinfoMachineLearning/PoseBench
Comprehensive benchmarking of protein-ligand structure prediction methods. (Nature Machine Intelligence)
maranasgroup/CatPred
Machine Learning models for in vitro enzyme kinetic parameter prediction
kamerlinlab/KIF
KIF - Key Interactions Finder. A python package to identify the key molecular interactions that...