Development and applications of multiscale methods in molecular modeling and bioinformatics
Group members
prof. dr hab. Bogdan Lesyng
dr Krystiana A. Krzyśko
dr Joanna Panecka-Hofman
National collaboration
prof. dr hab. Jacek Waluk, IChF PAN
dr Franciszek Rakowski, ICM UW
dr Edyta Dyguda-Kazimierowicz, Wrocław University of Technology
dr hab. Joanna Kowalska, Division of Biophysics FUW
dr Marcin Warmiński, Division of Biophysics FUW
International collaboration
prof. dr hab. Waldemar Priebe, MD Anderson Cancer Center, Houston, USA
prof. Rebecca C. Wade, Heidelberg Institute for Theoretical Studies, Heidelberg University
dr Ina Poehner, School of Pharmacy, University of Eastern Finland
Keywords
multiscale modeling
bioinformatics
molecular dynamics
quantum dynamics
structure
function
causality analysis
The group was estabilished by Prof. Bogdan Lesyng as the Laboratory of Molecular Design and Bioinformatics, using funds from the BioExploratorium Center of Excellence. We collaborate with Center for Machine Learning (Center4ML) led by Prof. dr hab. Bogdan Lesyng.
Research topics
The description of mechanisms governing the functioning of complex (bio)molecular systems, as well as methods for molecular design of systems with desired structural and functional properties, requires the use of advanced, multiscale mathematical and computational modeling methods. Our research includes, among others:
- proton and electron dynamics in realistic molecular environments,
- simulations of catalytic processes, including mechanisms of enzyme activation, inhibition, and regulation, with particular emphasis on complex protease systems and the role of specific structural domains in molecular recognition processes,
- conversion of (bio)chemical energy into mechanical energy,
- design of next-generation drugs, including covalent inhibitors,
- analysis of molecular consequences of point mutations, including assessment of structural, energetic, and electrostatic changes and their correlation with clinical phenotype,
- studies of biological nanomachines,
- as well as, for example, fundamental research related to the detection and analysis of causal relationships between events in structural transformations,
- fundamental research related to the detection and analysis of causal relationships between events in structural transformations.
For example, methods of microscopic quantum and quantum–classical molecular dynamics (QM and QM/MM MD) are used to simulate proton and electron transfer (hopping) in (bio)molecular systems, to analyze elementary stages of catalytic processes, and to generate microscopic electrostatic fields. These approaches also enable studies of enzyme activation, inhibition, and regulation mechanisms, including modeling of covalent docking processes and chemical bond formation within active sites.
On the other hand, methods of classical mesoscale molecular dynamics are applied in simulations of spontaneous structural self-organization processes, complex stability, and the impact of point mutations on protein architecture and their energetic properties. Multistep symplectic integration algorithms allow stable simulations over long timescales.
Methods based on the Poisson–Boltzmann equation are also applied and further developed, enabling determination of mesoscale electrostatic fields that strongly govern molecular recognition processes (molecular recognition), interaction selectivity, and electrostatic environment reorganization induced by structural changes.
Within the above research areas, the group also employs machine learning (ML) methods to support analysis of simulation data, prediction of mutation effects, and optimization of molecular design processes.