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Updated: Jan 26, 2026

Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes
Published on: December 13, 2016
Can multiscale simulations unravel the function of metallo-enzymes to improve knowledge-based drug discovery?
Jacopo Sgrignani1, Lorenzo Casalino2, Fabio Doro3
1Institute for Research in Biomedicine (IRB), Università della Svizzera Italiana (USI), CH-6500, Bellinzona, Switzerland.
Abstract:
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.
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