Inference code for scalable emulation of protein equilibrium ensembles with generative deep learning

Making Protein folding accessible to all!

A differentiable implementation of kernel density estimation in PyTorch.

HyperMPNN ‒ A general strategy to design thermostable proteins learned from hyperthermophiles

In silico directed evolution of peptide binders with AlphaFold

[AAAI 2025] Dynamic Protein Data Bank

List of papers about Proteins Design using Deep Learning

A Euclidean diffusion model for structure-based drug design.

AlphaFold Meets Flow Matching for Generating Protein Ensembles

aimmd (AI for Molecular Mechanism Discovery) autonomously steers (a large number of) molecular dynamics simulations to efficiently sample and understand rare transition events.

EigenFold: Generative Protein Structure Prediction with Diffusion Models

LAST: Latent Space Assisted Adaptive Sampling for Protein Trajectories

Code for the ProteinMPNN paper

Ankh: Optimized Protein Language Model

Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation

Evolutionary Scale Modeling (esm): Pretrained language models for proteins

PyTorch based Probabilistic Time Series forecasting framework based on GluonTS backend

Database of Interacting Protein Structures (DIPS)

Statistical inference of Generalized Langevin Equation using Expectation-Maximization algorithm

Statistical models for biomolecular dynamics

Langevin equation optimization via Likelihood maximization