Conformational Ensemble Generation

Conformation Clustering

• protein-cluster-conformers: used to cluster a parsed set of monomeric protein chains via a global conformational change metric based on CA distances.
  

MD

• MDSubSampler: a posteriori sampling of important protein conformations from biomolecular simulations (standalone)
  
• SubPEx: Worth the Weight: Sub-Pocket EXplorer (SubPEx), a Weighted Ensemble Method to Enhance Binding-Pocket Conformational Sampling
  

ML

• AF2-Rave: AF2-Rave combines AlphaFold2 with enhanced sampling to predict a range of conformations for a given protein sequence, aiming to generate Boltzmann-ranked conformations
  
• AF-cluster: This method predicts multiple protein conformations using sequence clustering and AlphaFold2, aiming to capture the diversity of protein structures.
  
• AFsample2: a method employing random MSA column masking to reduce the influence of co-evolutionary signals to enhance the structural diversity of models generated by the AF2 neural network
  
• AlphaFlow: AlphaFold Meets Flow Matching for Generating Protein Ensembles. (Note: There is a preprint challenging the claims in the AF-Cluster paper. You can read it here.)
  
• DeepConformer: diffusion generative model for sampling protein conformation distributions from a given amino acid sequence
  
• EGDiff: ExEnDiff: An Experiment-guided Diffusion model for protein conformational Ensemble generation
  
• ICoN: Sampling Conformational Ensembles of Highly Dynamic Proteins via Generative Deep Learning
  
• Str2Str: Str2Str is a score-based framework for zero-shot protein conformation sampling, drawing inspiration from traditional methods to sample conformations guided by a neural score network trained on the PDB database.
  

Other

• AlphTraj: AlphaTraj is software designed for analyzing pocket dynamics.
  
• DANCE: DANCE is designed to process a set of input protein 3D structures provided in Crystallographic Information File (CIF) format and output protein or protein family-specific conformational collections in CIF or PDB format.
  
• EnGens: a computational framework for generation andanalysis of representative protein conformationalensembles (online)
  
• GMdSilva: Predicting Relative Populations of Protein Conformations without a Physics Engine Using AlphaFold2
  
• ICoN: Sampling Conformational Ensembles of Highly Dynamic Proteins via Generative Deep Learning
  
• SMA-MD: Generation of conformational ensembles of small molecules via surrogate model-assisted molecular dynamics