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”

It is our great honor and pleasure to organize this special issue in Biophysics and Physicobiology, “Progress of theoretical and computational biophysics—in honor of Professor Nobuhiro Go’s outstanding contribution on the occasion of his 80th birthday”. We have two main reasons to plan this special issue. One reason is the recent development of data-driven science, AI and deep-learning. Omics studies were one of the emerging fields in biology in 2000’s. Because of big data of genome and protein structures, biology has an aspect of information science. AI, deep-learning and data-driven science will change theoretical and computational biophysics drastically. These new methodologies will reveal new empirical rules to control biological system, which are never clarified with the old-fashioned biological studies. On the other hand, we are concerned that these new methodologies do not necessarily clarify the molecular bases of life. It would be meaningful to overview the present status of theoretical and computational biophysics at the timing of new era “Reiwa” started.

Another reason is that Professor Nobuhiro Go turned 80 years old on February 14th this year. Needles to say, Professor Go is one of the leading theoretical biophysicists. Not only he carried out significant theoretical studies in protein science, but also he recognized the importance of big data in biophysics in late 1990’s. He is one of the pioneers of bioinformatics. Here, let us look back on his achievements in the field of theoretical and computational biophysics with his brief carrier.

Nobuhiro Go was born on February 14, 1939. He graduated from Physics Department, the University of Tokyo in 1961. At the Graduate School of Science, the University of Tokyo, he first studied theoretical elementary particle physics in his master’s study and then moved to Biophysics at the Ph.D. course. He joined a faculty member of Physics Department as an assistant (Joshu) in 1964. After he received the doctoral degree, he joined in Harold Scheraga lab in Cornell University as a postdoctoral fellow. He promoted to associate 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 University in 1987. He was also appointed to a guest professor in Graduate School of Information Science, Nara 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.

Professor Go has been contributing to the construction of the theoretical basis for the understanding of the principle of protein architecture. In the process of deciphering the principle, he has solved various problems from the protein structure formation (protein folding) to the emergence of protein function (protein dynamics).

He has established the principle of protein folding applicable to any kind of protein structures, originally devising a simple lattice protein [1–3]. His lattice protein actually behaved like a real protein, implicating that the simple model successfully captured the very vital point of protein folding. Based on the studies, he proposed the consistency principle [1–3]. This principle reads “both local and non-local interactions in a native protein structure work consistently to favor or stabilize the unique three-dimensional structure appearing in the native condition”. This principle was embodied in an ideal model of protein folding, which is now widely acknowledged and called as “Go model”. The model considers only the interactions between the atom pairs making contacts in the native structure, and ignores all non-native interactions. Go model is now considered as the most fundamental model in protein folding like the ideal gas model in physics. He summarized these pioneering achievements in the pivotal review article in 1983 [3].

Although the consistency principle or the Go model is now widely accepted as the standard model to study protein stability and folding mechanism, it had been neglected for a long time. We think that there are two major reasons: First, the experimental techniques were undeveloped at that time to substantiate the importance of his novel idea; Secondly, when Prof. Go proposed the consistency principle, people believed that a real protein was much more complicated than the Go model. However, the situation was dramatically changed from late 80’s. The accumulation of quantitative and sophisticated experimental works revealed that real proteins behaved really like the Go model. The turning point came when Peter Wolynes published a paper reevaluating the consistency principle in 1987 [4]. In the paper, Wolynes employed a modern theory of complex disordered systems to reach the same conclusion. The consistency principle is now the leading principle in protein science, and the Go model is the standard model for the simulations of protein folding. In the 1983 review, Prof. Go concluded that the evolution of proteins was the process of the natural selection of polypeptide chains satisfying the physico-chemical law, or the consistency principle [3]. This paper actually experienced several upsurges of citation decades after publication, which is completely different from usual papers whose number of citations drops off after 5–10 years.

Professor Go also contributed to the understanding of protein dynamics and the relation with biological functions. He developed a unique and novel method of normal mode analysis of a protein [5,6]. Utilizing the normal mode models, he advocated a picture of protein function, “biological function occurred mostly in the low-energy collective normal modes” [6]. The Go’s normal mode picture is now a standard concept to study protein function from protein structures. He also developed a method utilizing protein normal modes to derive the dynamical properties from X-ray diffraction experiment [7]. Further, Prof. Go extended his normal mode method to anharmonic protein dynamics. He succeeded in unifying the harmonic and the anharmonic aspects of protein dynamics by “Jumping-Among Mimima (JAM) model” [8].

As the case of the consistency principle of protein folding, the experimental works have been quite limited in the field of protein dynamics. One of a few exceptions was neutron inelastic scattering. There was a discrepancy between the density of state at lower energy side obtained by neutron scattering and that obtained by a conventional normal mode analysis. Theorists considered that discrepancy came from an insufficient approximation of potential functions which were used in the calculation. However, Prof. Go clearly proved that the discrepancy came from the friction effect of hydration water, and the low-energy protein dynamics can be correctly described by the normal mode analysis [9,10]. Since then, the role of hydration water became an important subject in the field of biophysics. His theory has attracted many experimentalists.

Besides these contributions to the theories of protein science, he also developed the epoch-making important method to solve the solution structure of a protein by NMR. When Prof. Go was staying in Wüthrich lab, he noticed that the NMR distance data contain sufficient information to construct complicated protein three-dimensional structure, although the distances determined by NMR (NOE signals) are limited by quantity and by quality, that is, the distance can be determined simply as being less than 5 Å or more than 5 Å [11]. He developed the computational method called distance geometry to solve protein structures at atomic resolution from the loosely determined distance data obtained by NMR [11,12]. The method first applied to the protein by Kurt Wüthrich [13,14], which led Wüthrich to the 2002 Nobel Prize in Chemistry. NMR with the distance geometry is now one of the fundamental methods in structural biology. Prof. Go opened the way for this field. He also contributed to the development of a new method for the structure analysis of a single protein molecule using diffraction images obtained by intense coherent X-ray from free electron laser [15].

As mentioned above, he recognized the significance of big data in biology. When he organized a grant-in-aid for scientific research in priority areas “Principle of Protein Architecture” since 1995 till 1999, he included the subject of bioinformatics in the group. After he retired from Kyoto University, he started new laboratories of bioinformatics and data-driven science in Nara Institute of Science and Technology and in Japan Atomic Energy Research Institute.

Obviously, Professor Go’s contribution to theoretical and computational biophysics is outstanding. We would like to dedicate the special issue for Professor Go for celebrating his 80th birthday. We have 31 contributions in this special issue including 4 contributions from abroad as well as Prof. Go’s recent original work. This special issue covers wide area of theoretical and computational biophysics reflecting Prof. Go’s research fields, and will be a good reference to overlook the present situation of theoretical and computational biophysics.