Metallo-enzymes are a large class of biomolecules promoting specialized chemical reactions. Quantum-classical quantum mechanics/molecular mechanics molecular dynamics, describing the metal site at quantum mechanics level, while accounting for the rest of system at molecular mechanics level, has an accessible time-scale limited by its computational cost. Hence, it must be integrated with classical molecular dynamics and enhanced sampling simulations to disentangle the functions of metallo-enzymes. In this review, we provide an overview of these computational methods and their capabilities. In particular, we will focus on some systems such as CYP19A1 a Fe-dependent enzyme involved in estrogen biosynthesis, and on Mg2+-dependent DNA/RNA processing enzymes/ribozymes and the spliceosome, a protein-directed ribozyme. This information may guide the discovery of drug-like molecules and genetic manipulation tools.
Can multiscale simulations unravel the function of metallo-enzymes to improve knowledge-based drug discovery? / Sgrignani, J.; Casalino, L.; Doro, F.; Spinello, A.; Magistrato, A.. - In: FUTURE MEDICINAL CHEMISTRY. - ISSN 1756-8919. - 11:7(2019), pp. 771-791.
|Titolo:||Can multiscale simulations unravel the function of metallo-enzymes to improve knowledge-based drug discovery?|
|Autori:||Sgrignani, J.; Casalino, L.; Doro, F.; Spinello, A.; Magistrato, A.|
|Data di pubblicazione:||2019|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.4155/fmc-2018-0495|
|Appare nelle tipologie:||1.2 Review in journal|