Bringing HDX-MS to the companyConnecting experimental data with simulations and predictionsCytokine, antibody and small molecule drug discoveryManaging collaborations with external partnersDeveloping ML predictors for IDP drug discovery

Molecular dynamics simulations, force field development, free energy calculations and Machine Learning for accelerated drug design

Development and implementation of a Monte Carlo program for the prediction of polymer degradation.Chemical structure prediction of biodegradable polymers with Machine Learning approaches (mainly virtual autoencoder) using Tensorflow.

MD simulations of proteins with GROMACS. Free energy calculations with pmxConfigurational entropy calculations based on different approaches (quasi-harmonical approximation, counting the dihedral angle phase space). -> Complete picture of the thermostability of T4 LysozymeDevelopment of a new method to calculate backbone and sidechain NMR order parameter from MD simulations which increases the accuracy by a factor 2 in comparison to established methods. Reparametrization of the methyl group dihedral angles in the AMBER force fields by CCSD(T) coupled cluster calculations which increases the accuracy with respect to experiment by a factor of 2.3 for fast dynamics.Markov State model of the protein backbone dihedral angles which identifies unknown protein jumps.

Analysis of relaxation rates from NMR experiments.Combination of order parameter from MD simulations and NMR relaxation experiments.Identification of experimental artefacts.

Protein structure prediction with Monte Carlo simulations using GMIN.Implementation of chemical shift (CS) predictor CAMSHIFT in GMIN.Performing and improvement of CS restrained PSP with the basin-hopping MC approach.Protein folding with neural network based secondary structure predictor.-> Method predicts proteins up to 60 residues as accurate as established techniques in less than half of the time.Development of knowledge-based Monte Carlo moves based on the protein structure.

MD simulations of polymer brushes with nanoparticles using LAMMPS.Development and implementation of a grand canonical ensemble in LAMMPS using JAVA.Development of a theoretical model to describe the nanoparticle (NP) distribution in absorbing polymer brushes with different brush surface densities, NP sizes and attractive energies.

Development, implementation and test of a program to analyze images of superconducting vortices using Pascal/Delphi. Presentation of the result in Spanish.

Graphical analysis of cell images.Writing the official script of the lecture ”Theoretical Biophysics” using LaTeX.