Molecular dynamics & enhanced sampling methods development to determine microscopic transition mechanisms, free energies and kinetics
Molecular dynamics & enhanced sampling methods development to determine microscopic transition mechanisms, free energies and kinetics
Z F. Brotzakis, V. Limongelli, and M. Parrinello. Accelerating the Calculation of Protein-Ligand Binding Free Energy and Residence Times using Dynamically Optimized Collective Variables. J. Chem. Theory Comput., 15(1):743–750, 2019
Z. F. Brotzakis, P.G. Bolhuis. Unbiased Atomistic Insight in the Mechanisms and Solvent Role for Globular Protein Dimer Dissociation J. Phys. Chem. B 123 (9), 1883-1895, 2019
Z.F. Brotzakis, P.G. Bolhuis.Approximating Committor and Free Energy Landscapes in standard Transition Path Sampling using Virtual Interface Exchange, J. Chem. Phys. 151 (17), 174111, 2019
MhD, H. Murtada, Z. F. Brotzakis, M. Vendruscolo. Language Models for Molecular Dynamics (2024) bioRxiv, 2024.11. 25.625337
Protein Dynamics Landscape Design: Designing protein sequences for tuned kinetics and thermodynamics
Z. F. Brotzakis, M. Vendruscolo,G. Skretas (2025). Design of Protein Sequences with Precisely Tuned Kinetic Properties. bioRxiv https://doi.org//doi.org/10.1101/2025.02.13.638027
Determining accurate structural ensembles by developing integrative structural biology methods
Z. F. Brotzakis, M. Vendruscolo, and P. G Bolhuis. A method of incorporating rate constants as kinetic constraints in molecular dynamics simulations. Proc. Natl. Acad. Sci. U.S.A., 118(2):e2012423118, 2021
Z.F. Brotzakis, T Löhr, S Truong, S Hoff, M Bonomi, M Vendruscolo. Determination of the Structure and Dynamics of the Fuzzy Coat of an Amyloid Fibril of IAPP Using Cryo-Electron Microscopy.Biochemistry 62 (16), 2407–2416,2023.
Z.F. Brotzakis, S. Zhang, MhD. H. Murtada, M. Vendruscolo . AlphaFold prediction of structural ensembles of disordered proteins. Nat Commun 16, 1632, 2025.
Computer Aided Drug Discovery
S. Chia , Z.F. Brotzakis, A. Possenti, B. Mannini,R. Cataldi,M.Nowinska, R. Staats,S. Linse, T. Knowles, J. Habchi. & M. Vendruscolo. Structure-based discovery of small molecule inhibitors of the autocatalytic proliferation of α-synuclein aggregates. Mol. Pharmaceutics, 20, 1, 183–193 2022
R.I. Horne, H.M. Murtada, H. Donghui, Z.F. Brotzakis,R.C. Gregory. et al. Exploration and Exploitation Approaches Based on Generative Machine Learning to Identify Potent Small Molecule Inhibitors of α-Synuclein Secondary Nucleation. J. Chem. Theory. Comput. 19, 14, 4701–4710, 2023.
R. I. Horne, E. A. Andrzejewska, P. Alam*, Z. F. Brotzakis*. et al. Discovery of potent inhibitors of α-synuclein aggregation using structure-based iterative learning. Nat Chem Biol 20, 634–645, 2024.
Z F. Brotzakis, V. Limongelli, and M. Parrinello. Accelerating the Calculation of Protein-Ligand Binding Free Energy and Residence Times using Dynamically Optimized Collective Variables. J. Chem. Theory Comput., 15(1):743–750, 2019
Applications in Protein Dynamics
Z F. Brotzakis, Philip R Lindstedt, Ross J Taylor, Dillon J Rinauro, Nicholas C T Gallagher et al. A Structural Ensemble of a Tau-Microtubule Complex Reveals Regulatory Tau Phosphorylation and Acetylation Mechanisms. ACS Central Science, 7(12):1986–1995, 2021.
Z. F. Brotzakis, T. Lohr, and M. Vendruscolo. Determination of intermediate state structures in the opening pathway of SARS-CoV-2 spike using cryo-electron microscopy. Chem. Sci., 12(26):9168–9175, 2021
H. Mikolajek*, M. Weckener*, Z. F. Brotzakis*, J Huo, E.V. Dalietou, et. al. Correlation between binding affinity and the conformational entropy of nanobodies targeting the SARS-CoV-2 spike protein. PNAS, 119 (31):e2205412119, 2022
Forcefield Optimization
P.G. Bolhuis, Z.F. Brotzakis, B. Keller. Optimizing molecular potential models by imposing kinetic constraints with path reweighting J. Chem. Phys.159, 074102, 2023
R. Dutta, Z.F. Brotzakis, A. Mira A. Bayesian Calibration of Force-fields from Experimental Data: TIP4P Water. J. Chem. Phys. 149: 154110 ,2018