Theoretical and experimental biology in one<br>—A symposium in honour of Professor Kuo-Chen Chou’s 50th anniversary and Professor Richard Giegé’s 40th anniversary of their scientific careers

Abstract

It has been a dream that theoretical biology can be extensively applied in experimental biology to accelerate the understanding of the sophiscated movements in living organisms. A brave assay and an excellent example were represented by enzymology, in which the well-established physico-chemistry is used to describe, to fit, to predict and to improve enzyme reactions. Before the modern bioinformatics, the developments of the combination of theoretical biology and experimental biology have been mainly limited to various classic formulations. The systematic use of graphic rules by Prof. Kuo-Chen Chou and his coworkers has significantly facilitated to deal with complicated enzyme systems. With the recent fast progress of bioinformatics, prediction of protein structures and various protein attributes have been well established by Chou and co-workers, stimulating the experimental biology. For example, their recent method for predicting protein subcellular localization (one of the important attributes of proteins) has been extensively applied by scientific colleagues, yielding many new results with thousands of citations. The research by Prof. Chou is characterized by introducing novel physical concepts as well as powerful and elegant mathematical methods into important biomedical problems, a focus throughout his career, even when facing enormous difficulties. His efforts in 50 years have greatly helped us to realize the dream to make "theoretical and experimental biology in one". Prof. Richard Giege is well known for his multidisciplinary research combining physics, chemistry, enzymology and molecular biology. His major focus of study is on the identity of tRNAs and their interactions with aminoacyl-tRNA synthetases (aaRS), which are of critical importance to the fidelity of protein biosynthesis. He and his colleagues have carried out the first crystallization of a tRNA/aaRS complex, that between tRNA Asp and AspRS from yeast. The determination of the complex structure contributed significantly to understand the interaction of protein and RNA. From his fine research, they have also found other biological function of these small RNAs. He has developed in parallel appropriate methods for his research, of which the protein crystallogenesis, a name he has coined, is an excellent example. Now macromolecular crystallogenesis has become a developed science. In fact, such contribution has accelerated the development of protein crystallography, stimulating the study of macromolecular structure and function.

Gram-positive and Gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into Chou׳s general PseAAC

“…Since user-friendly and publicly accessible web-servers represent the future direction for developing practically more useful models, simulated methods, or predictors (Chou and Shen, 2009;Lin and Lapointe, 2013), we shall make efforts in our future work to provide a web-server for the method presented in this paper. Table 5 Comparison of our achieved results (%) with the similar studies found in the literature.…”

Modelling the molecular mechanism of protein–protein interactions and their inhibition: CypD–p53 case study

“…Many marvellous biological functions in proteins and DNA and their profound dynamic mechanisms, such as switch between active and inactive states [46], cooperative effects [47], allosteric transition [48,49], intercalation of drugs into DNA [50] and assembly of microtubules [51], can be revealed by studying their internal motions, as elaborated in a comprehensive review and summarized in a recent paper [52,53] as well as a Wikipedia article at http://en.wikipedia.org/wiki/Low-frequency_collective_ motion_in_proteins_and_DNA. Likewise, to really understand the action mechanism of receptor-ligand or proteinprotein binding, we should consider not only the static structures concerned but also the dynamical information obtained by simulating their internal motions or dynamic process.…”

A two-layer classification framework for protein fold recognition

“…Since user-friendly and publicly accessible web-servers represent the future direction for developing practically more useful prediction methods or models Lin and Lapointe, 2013), we plan to provide a web-server for our method as done in (Liu et al, 2014;Qiu et al, 2014;Guo et al, 2014;Ding et al, 2014;Xu et al, 2014) in our future work. Table 6 Comparison between TLCF n with other related papers in terms of prediction accuracy.…”