kamerlinlab/KIF
KIF - Key Interactions Finder. A python package to identify the key molecular interactions that regulate any conformational change.
KIF helps molecular scientists understand how proteins and other biomolecules change shape by identifying the key non-covalent interactions that drive these conformational changes. You feed it molecular dynamics simulation data (trajectories), along with a description of the change you're interested in, and it tells you which specific interactions are most important. The output helps you visualize these critical interactions directly on 3D molecular structures.
Available on PyPI.
Use this if you run molecular dynamics simulations and need to pinpoint the exact molecular interactions responsible for a protein's conformational change, enzyme catalysis, or other dynamic processes.
Not ideal if you are looking to run new molecular dynamics simulations, as this tool analyzes pre-existing trajectory data.
Stars
34
Forks
4
Language
Python
License
GPL-2.0
Category
Last pushed
Jan 06, 2026
Commits (30d)
0
Dependencies
11
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/kamerlinlab/KIF"
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
BioinfoMachineLearning/FlowDock
A geometric flow matching model for generative protein-ligand docking and affinity prediction....