Software

Central Limit Free Energy Perturbation

Nowadays, binding free energy calculations are essential for the study of chemical and biological systems. However, accurate methodologies in the field are often computationally demanding, which limits their applicability. As an alternative, we introduced the Central Limit Free Energy Perturbation (CL-FEP) approach. Without computing intermediate points of a system transformation (e.g. stratified coupling and decoupling of a ligand), CL-FEP can deliver accurate free energy change values. In CL-FEP, the exponential average estimator is evaluated upon transforming the energy output of molecular dynamics simulations by applying the Central Limit theorem. Importantly, energies from explicit solvent simulations can be used to evaluate the estimator and no fitted parameters are introduced by our implementation.

CL-FEP is freely available at https://clfep.zmb.uni-due.de/index.php

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Machine Learning Models

Machine learning methods allow exploiting the information content in protein datasets. We introduced a procedure for the general-purpose numerical codification of polypeptides. With this, we developed a support vector machine model (PPI-Detect), which allows predicting whether two proteins will interact or not. PPI-Detect outperforms state of the art sequence-based predictors of PPI. Using PPI-Detect, we designed a peptide which biological activity was then experimentally established.

PPI-Detect is freely available at https://ppi-detect.zmb.uni-due.de

Logo ProtDCal-Suite

ProtDCal-Suite

We also introduced ProtDCal-Suite, a web server comprising a set of tools for studying proteins. The main module is a software named ProtDCal, which encodes the structural information of proteins in machine-learning-friendly vectors. Secondary modules are protein analysis tools developed with ProtDCal’s descriptors: PPI-Detect, for predicting the interaction likelihood of protein-protein and protein-peptide pairs; Enzyme Identifier, for identifying enzymes from amino acid sequences or 3D structures and Pred-Nglyco, for predicting N-glycosylation sites.

ProtDCal-Suite is freely available at https://protdcal.zmb.uni-due.de.