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Special Issue Vol. 16, pp. 173–175 (2019) “Progress of Theoretical and Computational Biophysics” doi: 10.2142/biophysico.16.0_173 Biophysics and Physicobiology https://www.jstage.jst.go.jp/browse/biophysico/ Preface Forewords to the special issue “Progress of theoretical and computational biophysics—in honor of Professor Nobuhiro Go’s outstanding contribution on the occasion of his 80th birthday” Mikio Kataoka1*, Akio Kitao2* and Hidetoshi Kono3* 1Nara Institute of Science and Technology, Ikoma, Nara 630-0192, Japan 2Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan 3National Institutes for Quantum and Radiological Science and Technology, Kizugawa, Kyoto 619-0215, Japan It is our great honor and pleasure to organize this special Another reason is that Professor Nobuhiro Go turned 80 issue in Biophysics and Physicobiology, “Progress of theo- years old on February 14th this year. Needles to say, Professor retical and computational biophysics—in honor of Professor Go is one of the leading theoretical biophysicists. Not only Nobuhiro Go’s outstanding contribution on the occasion of he carried out significant theoretical studies in protein sci- his 80th birthday”. We have two main reasons to plan this ence, but also he recognized the importance of big data in special issue. One reason is the recent development of data- biophysics in late 1990’s. He is one of the pioneers of bioin- driven science, AI and deep-learning. Omics studies were formatics. Here, let us look back on his achievements in the one of the emerging fields in biology in 2000’s. Because of field of theoretical and computational biophysics with his big data of genome and protein structures, biology has an brief carrier. aspect of information science. AI, deep-learning and data- Nobuhiro Go was born on February 14, 1939. He gradu- driven science will change theoretical and computational ated from Physics Department, the University of Tokyo in biophysics drastically. These new methodologies will reveal 1961. At the Graduate School of Science, the University of new empirical rules to control biological system, which are Tokyo, he first studied theoretical elementary particle physics never clarified with the old-fashioned biological studies. On in his master’s study and then moved to Biophysics at the the other hand, we are concerned that these new methodolo- Ph.D. course. He joined a faculty member of Physics Depart- gies do not necessarily clarify the molecular bases of life. It ment as an assistant (Joshu) in 1964. After he received the would be meaningful to overview the present status of theo- doctoral degree, he joined in Harold Scheraga lab in Cornell retical and computational biophysics at the timing of new University as a postdoctoral fellow. He promoted to associ- era “Reiwa” started. ate professor in Department of Physics, Faculty of Science, Kyushu University in 1971 and then promoted to Professor of Department of Chemistry, Faculty of Science, Kyoto * Editor-in-Charge of this special issue University in 1987. He was also appointed to a guest pro- Corresponding author: Mikio Kataoka, Nara Institute of Science and Technology, Ikoma, Nara 630-0192, Japan. fessor in Graduate School of Information Science, Nara e-mail: [email protected] Institute of Science and Technology as well as an excellent investigator in Japan Atomic Energy Research Institute, after he retired from Kyoto University. He also served as a president of the Biophysical Society of Japan, a vice president of the International Union of Pure and Applied Biophysics, a chairman of International Union of Pure and Applied Physics and a member of Science Council of Japan. ©2019 THE BIOPHYSICAL SOCIETY OF JAPAN 174 Biophysics and Physicobiology Vol. 16 Professor Go has been contributing to the construction of mal modes” [6]. The Go’s normal mode picture is now a the theoretical basis for the understanding of the principle standard concept to study protein function from protein of protein architecture. In the process of deciphering the structures. He also developed a method utilizing protein nor- principle, he has solved various problems from the protein mal modes to derive the dynamical properties from X-ray structure formation (protein folding) to the emergence of diffraction experiment [7]. Further, Prof. Go extended his protein function (protein dynamics). normal mode method to anharmonic protein dynamics. He He has established the principle of protein folding appli- succeeded in unifying the harmonic and the anharmonic cable to any kind of protein structures, originally devising a aspects of protein dynamics by “Jumping-Among Mimima simple lattice protein [1–3]. His lattice protein actually (JAM) model” [8]. behaved like a real protein, implicating that the simple model As the case of the consistency principle of protein folding, successfully captured the very vital point of protein folding. the experimental works have been quite limited in the field Based on the studies, he proposed the consistency principle of protein dynamics. One of a few exceptions was neutron [1–3]. This principle reads “both local and non-local inter- inelastic scattering. There was a discrepancy between the actions in a native protein structure work consistently to density of state at lower energy side obtained by neutron favor or stabilize the unique three-dimensional structure scattering and that obtained by a conventional normal mode appearing in the native condition”. This principle was embod- analysis. Theorists considered that discrepancy came from ied in an ideal model of protein folding, which is now widely an insufficient approximation of potential functions which acknowledged and called as “Go model”. The model con- were used in the calculation. However, Prof. Go clearly siders only the interactions between the atom pairs making proved that the discrepancy came from the friction effect of contacts in the native structure, and ignores all non-native hydration water, and the low-energy protein dynamics can interactions. Go model is now considered as the most funda- be correctly described by the normal mode analysis [9,10]. mental model in protein folding like the ideal gas model in Since then, the role of hydration water became an important physics. He summarized these pioneering achievements in subject in the field of biophysics. His theory has attracted the pivotal review article in 1983 [3]. many experimentalists. Although the consistency principle or the Go model is Besides these contributions to the theories of protein sci- now widely accepted as the standard model to study protein ence, he also developed the epoch-making important method stability and folding mechanism, it had been neglected for a to solve the solution structure of a protein by NMR. When long time. We think that there are two major reasons: First, Prof. Go was staying in Wüthrich lab, he noticed that the the experimental techniques were undeveloped at that time NMR distance data contain sufficient information to con- to substantiate the importance of his novel idea; Secondly, struct complicated protein three-dimensional structure, when Prof. Go proposed the consistency principle, people although the distances determined by NMR (NOE signals) believed that a real protein was much more complicated than are limited by quantity and by quality, that is, the distance the Go model. However, the situation was dramatically can be determined simply as being less than 5 Å or more changed from late 80’s. The accumulation of quantitative than 5 Å [11]. He developed the computational method and sophisticated experimental works revealed that real pro- called distance geometry to solve protein structures at atomic teins behaved really like the Go model. The turning point resolution from the loosely determined distance data came when Peter Wolynes published a paper reevaluating obtained by NMR [11,12]. The method first applied to the the consistency principle in 1987 [4]. In the paper, Wolynes protein by Kurt Wüthrich [13,14], which led Wüthrich to the employed a modern theory of complex disordered systems 2002 Nobel Prize in Chemistry. NMR with the distance to reach the same conclusion. The consistency principle is geometry is now one of the fundamental methods in struc- now the leading principle in protein science, and the Go tural biology. Prof. Go opened the way for this field. He also model is the standard model for the simulations of protein contributed to the development of a new method for the folding. In the 1983 review, Prof. Go concluded that the evo- structure analysis of a single protein molecule using diffrac- lution of proteins was the process of the natural selection of tion images obtained by intense coherent X-ray from free polypeptide chains satisfying the physico-chemical law, or electron laser [15]. the consistency principle [3]. This paper actually experi- As mentioned above, he recognized the significance of enced several upsurges of citation decades after publication, big data in biology. When he organized a grant-in-aid for which is completely different from usual papers whose num- scientific research in priority areas “Principle of Protein ber of citations drops off after 5–10 years. Architecture” since 1995 till 1999, he included the subject of Professor Go also contributed to the understanding of pro- bioinformatics in the group. After he retired from Kyoto tein dynamics and the relation with biological functions. He University, he started new laboratories of bioinformatics developed a unique and novel method of normal mode and data-driven science in Nara Institute of Science and analysis of a protein [5,6]. Utilizing the normal mode mod- Technology and in Japan Atomic Energy Research Institute. els, he advocated a picture of protein function, “biological Obviously, Professor Go’s contribution to theoretical and function occurred mostly in the low-energy collective nor- computational biophysics is outstanding. We would like to Kataoka et al.: Forewords to the special issue 175 dedicate the special issue for Professor Go for celebrating 517 (1998).