Predicting the effect of mutations on protein stability and protein binding affinity using pretrained neural networks and a ranking objective function.

Predicting the effect of mutations on protein stability using a simple orientational potential.

Some notes (cookbook) for pyMol. Protein Crystallography course.

Prediction of protein thermodynamic stability changes upon mutations through a Gaussian Network Model simulating protein unfolding behavior

Predicting the effect of mutations on protein stability and protein-protein interaction affinity.

A workflow to get rid of redundant mutations

Snakemake pipeline for Rosetta 'cartesian-ddg' protocol for protein stability prediction upon mutations.

Implementation of Abyssal, a deep neural network trained with a new "mega" dataset to predict the impact of an amino acid variant on protein stability.

Reimplementation of RaSP, a deep neural network for rapid protein stability prediction, in PyTorch.

https://biohackathon.biolib.com/event/2021-protein-edition/ - team "house-of-mutants" - task "Predicting multi-mutant protein stability"

R shiny app to analyse circular dichroism data

Two R shiny apps developed for analyzing differential scanning fluorimetry (DSF) data. One for binding, and one for stability

Large data set of thermal stabilities for mutants of BglB, and associated publication

Identify the thermostable mutations in enzymes

Official repository for the paper "Few-shot Prediction of the experimental functional measurements for proteins with single point mutations".

calculating ddg of point-mutation using contact potentials