Applications of different computational approaches to study proteins in biological systems will be discussed in this talk. We will first show how molecular dynamic (MD) simulations with QM/MM potentials can be applied to understand the catalytic mechanisms of individual enzymes or enzyme complexes as well as their specificity. It is demonstrated that such computational approaches can serve as powerful tools for understanding details of enzyme catalysis and predict substrate specificity. As we know, determination of complete genomes from a number of organisms have offered an unprecedented opportunity for biological research and transformed biology into a discipline that depends significantly on how to interpret large-scale data sets. By selecting representative proteomes from three domains of life, two giant DNA viruses, and collective gene sets from viruses and organelles including mitochondria, chloroplast and plasmids, we will demonstrate that systematical analyses of the interplay between protein length (L, the amino acid sequence length) and protein disorder (D, the percentage of residues in a so-called intrinsically disordered state) may allow us to construct two-dimensional LD-space maps for describing the proteomes or gene sets. It is found that the gene distributions in this LD-space may serve as architectural “fingerprints” shaped by the evolutionary processes.
Hong Guo obtained his Ph.D. degree at Harvard University in 1991 under the supervision of Prof. Martin Karplus (Nobel Prize Winer). From 1991--1993, he was an International NSERC postdoctoral fellow at University of Waterloo, and from 1993--1997, he was a postdoctoral fellow/research associate at University of Montreal and CERCA. He moved back to Harvard to work with Prof. Karplus as well as Prof. William Lipscomb (also a Nobel Prize Winer) as a scientist in 1998 and started at the University of Tennessee Knoxville (UTK) in 2002 where he is currently a professor at Department of Biochemistry & Cellular and Molecular Biology. He is also a senior member at Center for Molecular Biophysics, UTK/Oak Ridge National Lab. His research interests include the study of enzymes and enzyme’s specificity based on QM/MM MD simulations and protein structure prediction and application and development of computational approaches for big data analysis.