Softwares & Webservers in the Gohlke group

The group of Prof. Gohlke has published several algorithms and softwares based on computational biophysics and data sciences to model and simulate biomolecules and their interactions. Novel machine learning based methods in the fields of protein structure and properties prediction are also developed.

Constraint Network Analysis (CNA)

A Software Package for Efficiently Linking Biomacromolecular Structure, Flexibility, Stability, and Function

RCNMA/NMSim

A normal mode-based geometric simulation approach for exploring biologically relevant conformational transitions in proteins

DrugScore

Scoring functions to predict protein-ligand, RNA-ligand, and protein-protein interactions

PACKMOL-memgen

A generalized workflow for automated building of membrane-protein–lipid-bilayer systems

Free Energy Workflow (FEW)

An automated workflow for protein-ligand binding free energy calculations

Vasor

Vasor provides predictions on the pathogenicity of specific amino acid substitutions in the Multidrug Resistance protein 3 (MDR3)

TopScore

Using Deep Neural Networks and Large Diverse Data Sets for Accurate Protein Model Quality Assessment

TopModel

Template-Based Protein Structure Prediction at Low Sequence Identity Using Top-Down Consensus and Deep Neural Networks

TopDomain

Exhaustive Protein Domain Boundary Metaprediction Combining Multisource Information and Deep Learning

TopProperty

Robust Metaprediction of Transmembrane and Globular Protein Features Using Deep Neural Networks

TopEnzyme

Classification framework mapping enzyme topologies to enzyme commission and structures

PocketAnalyzerPCA

A program to characterize and visualize of pocket conformational distributions in protein conformational ensembles

VisualCNA

A PyMOL plug-in for interactive constraint network analysis and protein engineering for improving thermostability