Odseki

Raziskovalna dejavnost Teoretičnega odseka je usmerjena v razumevanje kompleksnih kemijskih, fizikalnih in bioloških procesov skozi prizmo naprednih teoretičnih in računskih pristopov. Štirje laboratoriji združujejo računsko kemijo in umetno inteligenco z eksperimentalni tehnikami za reševanje sodobnih izzivov na področju ved o življenju ter znanosti o materialih.

Razvijamo in uporabljamo širok nabor računskih metod, ki segajo od kvantnokemijskih pristopov in simulacije molekulske dinamike do večskalnega modeliranja, virtualnega rešetanja, Bayesove kvantifikacije negotovosti ter sodobnih orodij strojnega učenja in umetne inteligence. Ti napredni pristopi omogočajo natančno preučevanje dinamike in funkcije kompleksnih (bio)molekularnih sistemov, načrtovanje in optimizacijo biološko aktivnih molekul, potencialnih zdravilnih učinkovin ter načrtovanje naprednih materialov. 

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2. STEVANOVIĆ, Kristina, HERLAH, Barbara, PAVLIN, Matic, PERDIH, Andrej. Asymmetric T-segment binding and gate dynamics govern the final stages of the type IIA topoisomerase catalytic cycle. International journal of biological macromolecules. 2025, 327, 1, 1-17. https://www.sciencedirect.com/science/article/pii/S0141813025077736

3. KOLARIČ, Anja, GERME, Thomas, HRAST RAMBAHER, Martina, STEVENSON, Clare E. M., LAWSON, David M., BURTON, Nicolas P., VÖRÖS, Judit, MAXWELL, Anthony, MINOVSKI, Nikola, ANDERLUH, Marko. Potent DNA gyrase inhibitors bind asymmetrically to their target using symmetrical bifurcated halogen bonds. Nature communications. 2021, 12150-1-150-13. https://www.nature.com/articles/s41467-020-20405-8
    
4. BORIŠEK, Jure, AUPIČ, Jana, MAGISTRATO, Alessandra. Third metal ion dictates the catalytic activity of the two-metal-ion pre-ribosomal RNA-processing machinery. Angewandte Chemie : international edition. 2024, 63, 44, 1-8. https://onlinelibrary.wiley.com/doi/10.1002/anie.202405819
    
5. PRAŠNIKAR, Eva, LJUBIČ, Martin, PERDIH, Andrej, BORIŠEK, Jure. Machine learning heralding a new development phase in molecular dynamics simulations. Artificial intelligence review. 2024, 57, 4, 1-36. https://link.springer.com/article/10.1007/s10462-024-10731-4
    

6. OGRIS, Iza, ZUPANČIČ, Barbara, SOSIČ, Izidor, MERZEL, Franci, GOLIČ GRDADOLNIK, Simona. Mechanistic insight into the dynamics of Mur ligase through a comprehensive timescale-specific approach. Communications chemistry. 2025, 8, 285. https://www.nature.com/articles/s42004-025-01675-z

7. HUBMAN, Anže, MERZEL, Franci. Determination of thermal conductivities in liquids by identifying heat transport in nonequilibrium MD simulations. Journal of molecular liquids. 2023, 370, 1-7. https://www.sciencedirect.com/science/article/pii/S0167732222024552 

8. NTARAKAS Nikolaos, LAH, Maša, SVENŠEK, Daniel, POTISK Tilen, PRAPROTNIK, Matej. Dissipative particle dynamics models of encapsulated microbubbles and nanoscale gas vesicles for biomedical ultrasound simulations. ACS Applied Nano Materials.2025, 8, 32, 16053-16070. https://pubs.acs.org/doi/10.1021/acsanm.5c02783
    

9. JUG, Matevž, SVENŠEK, Daniel, POTISK, Tilen, PRAPROTNIK, Matej. Learning macroscopic equations of motion from dissipative particle dynamics simulations of fluids. Computer Methods in Applied Mecahnics and Engineering. 2024, 432, 117379. https://www.sciencedirect.com/science/article/pii/S0045782524006340?via%3Dihub

10. COSTE, Amaury, SLEJKO, Ema, ZAVADLAV, Julija, PRAPROTNIK, Matej. Developing and implicit solvation machine learning model for molecular simulations of ionic media. Journal of Chemical Theory and Computation. 2024, 20, 411–420. https://pubs.acs.org/doi/10.1021/acs.jctc.3c00984