UMMBAS — Molecular Modelling for Bio-Chemical Applications
2023–2025 Computational Chemistry Machine Learning VR
UMMBAS — Utilisation of Molecular Modelling for Bio-Chemical Application Scenarios
Bio-chemical research increasingly depends on accurate computational modelling. UMMBAS pools expertise across H-BRS in method development, visualisation, and computational analysis to tackle material science and biochemical questions — centred on a novel collaborative immersive VR environment for data analysis.
Approach
The workflow combines:
- (a) Force field generation — reliably computing atomistic potential energy landscapes for halogenated ligand-protein systems
- (b) Structural dynamics — investigating dynamics and structure of biologically active pharmaceutical systems
- (c) Statistical analysis and 3D visualisation — interactive VR-based data exploration
Traditional and novel optimisation methods are combined with machine learning and visual computing to create a standardised toolset for biologically motivated problems.
My role
I contributed to ML-accelerated force field parameterisation and surrogate-assisted optimisation methods — building on my work in CytoTransport and AErOmAt.
Partners
Prof. Matthias Preller (lead), Prof. Wolfgang Heiden, Dr. Karl Kirschner, Prof. Dirk Reith — H-BRS. Funded by the Ministry of Culture and Science of NRW (LMKW).