We apply and develop techniques grounded in bioinformatics, computational biophysics, and computational pharmaceutical chemistry such as docking, molecular dynamics simulations, free energy estimations, and methods to characterize the flexibility of protein and RNA structures. The following web server are provided by the Gohlke group:
DrugscorePPI is a knowledge-based scoring function for computational alanine-scanning in protein-protein interfaces [64,50]. The PDB-derived statistical potentials have been fine-tuned by an atomtype-based QSAR approach with respect to experimental binding free energy differences between wildtype proteins and ALA mutants for protein-protein complex formation. DrugScorePPI is therefore dedicated to successfully identify hot spots in protein-protein interfaces.
NMSim is a normal mode-based geometric simulation approach for exploring biologically relevant conformational transitions in proteins . The approach has been shown to reproduce experimentally observed conformational variabilities in the case of domain and loop motions and is able to generate meaningful pathways of conformational transitions. The generated structures are of good stereochemical quality. Thus, they can serve as input to docking approaches or as starting points for more sophisticated sampling techniques.
Constraint Network Analysis (CNAnalysis) is a graph theory-based rigidity analysis approach that analyzes global and local flexibility and rigidity characteristics of proteins by carrying out thermal unfolding simulations. The approach has been used to predict the thermostability of proteins and to identify structural weak spots, i.e., residues that upon mutation would improve a protein's thermostability. Furthermore, the approach can also be applied in other areas of computational biomolecular research, e.g., for linking biomolecular flexibility and function and for investigating changes of biomolecular flexibility due to complex formation.
TopSuite is a deep-learning based web server for protein model quality assessment (TopScore) and template-based protein structure prediction (TopModel). TopScore provides meta-predictions for global and residue-wise model quality estimation using deep neural networks. TopModel predicts protein structures using a top-down consensus approach to aid the template selection and subsequently uses TopScore to refine and assess the predicted structures.