Vědecký pracovník
doc. RNDr. Jan Řezáč, Ph.D.
Kontakty
Profil
I am computational chemist interested mainly in non-covalent interactions. More details about my work can be found at my personal website.
Další zdroje
Vybrané publikace
S66: A Well-balanced Database of Benchmark Interaction Energies Relevant to Biomolecular Structures
Journal of Chemical Theory and Computation 7 (8): 2427-2438 (2011).
With numerous new quantum chemistry methods being developed in recent years and the promise of even more new methods to be developed in the near future, it is clearly critical that highly accurate, well-balanced, reference data for many different atomic and molecular properties be available for the parametrization and validation of these methods. One area of research that is of particular importance in many areas of chemistry, biology, and material science is the study of noncovalent interactions. Because these interactions are often strongly influenced by correlation effects, it is necessary to use computationally expensive high-order wave function methods to describe them accurately. Here, we present a large new database of interaction energies calculated using an accurate CCSD(T)/CBS scheme. Data are presented for 66 molecular complexes, at their reference equilibrium geometries and at 8 points systematically exploring their dissociation curves; in total, the database contains 594 points: 66 at equilibrium geometries, and 528 in dissociation curves. The data set is designed to cover the most common types of noncovalent interactions in biomolecules, while keeping a balanced representation of dispersion and electrostatic contributions. The data set is therefore well suited for testing and development of methods applicable to bioorganic systems. In addition to the benchmark CCSD(T) results, we also provide decompositions of the interaction energies by means of DFT-SAPT calculations. The data set was used to test several correlated QM methods, including those parametrized specifically for noncovalent interactions. Among these, the SCS-MI-CCSD method outperforms all other tested methods, with a root-mean-square error of 0.08 kcal/mol for the S66 data set.
Nedávné publikace
Benchmarking of Semiempirical Quantum-Mechanical Methods on Systems Relevant to Computer-Aided Drug Design
Journal of Chemical Information and Modeling 60 (3): 1453-1460 (2020).
DFTB+, a software package for efficient approximate density functional theory based atomistic simulations
Journal of Chemical Physics 152 (12): 124101 (2020).
Non-Covalent Interactions Atlas Benchmark Data Sets: Hydrogen Bonding
Journal of Chemical Theory and Computation 16 (4): 2355-2368 (2020).
Impressive Enrichment of Semiempirical Quantum Mechanics-Based Scoring Function: HSP90 Protein with 4541 Inhibitors and Decoys
ChemPhysChem 20 (21): 2759-2766 (2019).