With the unprecedented processing capacity available, computational studies are making remarkable contributions in the field of enzymatic biocatalysis. Work in this field has focused on screening and identifying enzyme-candidates that show superior performance and stability than those currently in use. Large-scale simulations of increasingly realistic biological systems allow us to investigate enzyme function and molecular recognition in atomic detail, and they play a pivotal role in computational enzyme redesign protocols. The aim of my project is to develop robust protocols and algorithms for efficient optimization of catalytic properties using ab initio molecular dynamics and machine learning.
Computational proteomics, computer aided drug design (CADD) through machine learning methods, molecular dynamics simulations for drug discovery
MSc in Bioinformatics (Johns Hopkins University, Baltimore)
Prof Carmen Domene
Dr Georgios Exarchakis
