Faculty of Physics University of Warsaw > Events > Seminars > Biological Physics and Bioinformatics Seminar

Biological Physics and Bioinformatics Seminar

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Dr Kamila Maliszewska-Olejniczak (Katedra Fizyki i Biofizyki, Instytut Biologii, SZKOŁA GŁÓWNA GOSPODARSTWA WIEJSKIEGO W WARSZAWIE)

The evaluation of DNA damage and repair induced by different genotoxic agents

https://zoom.us/j/91976153012?pwd=azNiMWE4UnhPN3lRQlY2UHZHOXVkQT09
Meeting ID: 919 7615 3012
Passcode: 747922
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Bogdan Lesyng (UW)
Anna Niedźwiecka (IF PAN)
Piotr Zielenkiewicz (IBB)

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Dr hab. Anna Synak (Zakład Biomateriałów i Fizyki Medycznej, Instytut Fizyki Doświadczalnej, Wydział Matematyki, Fizyki i Informatyki, Uniwersytet Gdański)

Analysis of electronic excitation energy transfer in selected fluorescent systems

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Dr hab. Piotr Bednarczyk, prof. SGGW (Katedra Fizyki i Biofizyki, Instytut Biologii, Szkoła Główna Gospodarstwa Wiejskiego w Warszawie)

Exploring the impact of particulate matters on cellular damage: investigaton the role of mitochondrial potassium channels

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Dr hab. Anna Wiśniewska-Becker, prof. UJ (Zakład Biofizyki, Wydział Biochemii, Biofizyki i Biotechnologii, Uniwersytet Jagielloński)

Structural effects and photoreactivity of curcumin in model systems and in vitro

join us at 00:00

RNDr. Martin Pospíšek, Ph.D. (Department of Genetics & Microbiology, Faculty of Science, Charles University in Prague)

Polysome profiling and analysis of translatome from a limited amount of cells

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Prof. Bożena Kamińska (Nencki Institute of Experimental Biology, Warsaw)

Visualization of transcription in a single cell and space of the brain tumors

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Dr inż. Edyta Dyguda-Kazimierowicz (Advanced Materials Engineering and Modelling Group, Faculty of Chemistry, Wrocław University of Technology)

MED interaction energy model: nonempirical assessment of enzyme inhibition and activity

Abstract
Estimating the inhibitory potency of ligands and catalytic activity of enzyme mutants remains challenging as commonly employed empirical scoring functions still lack sufficient performance and routine in silico screening of mutant libraries with quantum chemical approaches is too computationally extensive. We propose a ligand scoring model MED [1] based on first principles and accounting for two long-range interaction energy components: multipole electrostatic and approximate dispersion terms. By merging computational efficiency with the lack of arbitrary parameterization, it functions as a robust tool for predicting the relative binding energy within enzyme binding and/or active sites. Herein, the predictive capabilities of the MED model will be compared with those of empirical scoring methods. The recent developments in MED-guided determination of mutant catalytic activity will also be presented, along with emerging principles to be followed in computational de novo enzyme design.
Acknowledgements: Support from NCN PRELUDIUM 2016/21/N/ST4/00516 grant is acknowledged. Calculations were performed at the Wroclaw Centrefor Networking and Supercomputing.
[1] W. Jedwabny, E. Dyguda-Kazimierowicz, K. Pernal, K. Szalewicz, K. Patkowski, J. Phys. Chem. A 125, 1787 (2021)

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Jan Wróblewski (Institute of Informatics, Faculty of Mathematics, Informatics and Mechanics, University of Warsaw)

Quantitative comparison of reaction-diffusion cellular automata with partial differential equations

Abstract
Cellular automata (CA) are used to simulate physical processes with various degrees of precision, but vast majority of CA has not been theoretically proven to converge to their well-established PDE model counterparts. We present a stochastic reaction-diffusion CA with a parameter that can increase its precision by increasing the number of molecules within. We show how its solutions converge to the PDE model as parameters improve. These theoretical results give confidence in the accuracy of the CA model itself, but the error bounds are small enough only for impractically computationally intensive precision parameters. Therefore, we experimentally show that, even for small precision parameters, we obtain good quantitative and qualitative similarity between CA and PDE simulations. We discuss the methods and challenges of quantitatively comparing these models as well as discuss a few interesting findings about the specific reaction-diffusion modeled by them.

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prof. W. Andrzej Sokalski (Department of Chemistry, Wrocław University of Science & Technology, Wyb. Wyspiańskiego 27, 50-370 Wrocław)

Analysis of the physical nature of catalytic effects: Development and applications of bottom-up methods for ab initio catalyst inverse design via catalytic fields

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prof. Vito Foderà (Department of Pharmacy, University of Copenhagen, Denmark)

Morphological Heterogeneity in Protein Amyloid-like Aggregation

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prof. dr hab. inż. Łukasz Berlicki (Wydział Chemiczny, Politechnika Wrocławska, Wrocław)

Design and engineering of functional miniproteins

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Dr hab. Bartosz Różycki, prof IF PAN (Instytut Fizyki Polskiej Akademii Nauk, Warszawa)

Conformational ensemble of the SARS-COV-2 nucleocapsid protein based on molecular simulations and SAXS data

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Prof. Matthias Bochtler (International Institute of Molecular and Cell Biology & Institute of Biochemistry and Biophysics, Warsaw, Poland)

X-rays, electrons, and neutrons as probes of atomic matter

At Matthias' request, before the lecture, we are attaching a version of the manuscript on which the lecture is based in case someone in the audience would like to have a look before. Matthias would like to get the most rigorous possible check of his conclusions, in case anyone would find errors in the manuscript that could still be corrected before the manuscript is (hopefully) accepted.

STRUCTURE-D-22-00198_R3-2.pdf

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Prof. Yuji Sugita (Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan)

Multi-scale molecular dynamics simulations of protein functions in the cellular environments

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Dawid Woś (Wydział Fizyki Uniwersytetu Warszawskiego)

Microbial influence on the growth of manganese mineral dendrites

Abstract:
Mineral dendrites are an example of a pattern that forms in rocks when theyare infiltrated by Mn-rich hydrothermal fluids. These fluids interact with oxygenated fluids within the rock matrix, leading to the formation of manganese oxide, which subsequently precipitates and forms intricate patterns. Bacteria can catalyze manganese oxidation reaction by at least 2-3 orders of magnitude and hence their presence can play a significant role in the formation and growth of manganese precipitates. We hypothesize that presence of Mn-oxidizing bacteria can also trigger band formation in the growing dendrites, which is observed in some natural structures.
We investigate this process using numerical simulations and analyze dependence of dendrite morphology on various physical parameters such as initial concentrations of manganese ions and oxygen molecules, reaction rates, nucleation thresholds, and surface energy. We have compared numerical results with experimental data on 3D dendrites in zeolites obtained using X-ray microtomography, which has revealed the presence of a banded pattern. Simulation results and experimental data agreement allows us to infer the presence of microorganisms during formation. We have compared numerical results to morphologies of the real systems with the aim of reconstructing hydrochemical conditions prevailing during their growth.

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Prof. Michał Dadlez (Instytut Biochemii i Biofizyki Polskiej Akademii Nauk)

Various manifestations of protein structural dynamics revealed by monitoring hydrogen-deuterium exchange

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Prof. Cecilia Clementi (Einstein Professor - Freie Universität Berlin, Department of Physics, Berlin, Germany and Rice University, Department of Physics, Houston, USA)

Machine learning coarse-grained potentials of protein thermodynamics

AbstractMolecular Dynamic simulations are becoming a standard tool to characterizeprotein dynamics. Despite the significant progress and impressive resultsobtained utilizing atomic-level force fields, simulations longer thanmilliseconds are still unfeasible for large protein systems. We presentrecent results on the developments of protein models at reduced resolutionthat can still well reproduce a protein configurational landscape but at asmall fraction of the cost. We discuss the method development and theresults, and we present a quantitative comparison of the thermodynamic anddynamic properties of different macromolecular systems at differentresolutions.