Laboratory of Informatics of Molecular Functions(AIST) Recruiting students for the academic year 2018


Associate Professor Kentaro TOMII
E-mail: k-tomii{at}
Lab HP


【Key Words】Protein structure prediction, Structure comparison, Protein function prediction, Drug discovery, Sequence analysis

Rapid accumulation of sequence and structure data of biological macromolecules has increased the need for rapid computational analysis of those data. Our laboratory develops new methods used for analysis of those data to acquire new biological knowledge. Most of our work is related to computational structural biology and protein bioinformatics, but we also cross into a wide range of academic fields.

Protein structure prediction

Our lab has developed and released FORTE ( 1)[1], which implements a profile-profile comparison method that is applicable to predict protein structures. We have applied this method in elucidating the TOM complex [2], and also in CASP and CAPRI, a community-wide experiment for predicting protein structure and protein complex [3].

Protein ligand-binding site comparison

We have developed a method for performing an exhaustive pairwise comparison of known and putative ligand-binding sites in PDB. We have created a database, called PoSSuM ( to compile comparison results [4]. We have also developed an effective method for ligand-binding site comparison based on a reduced vector representation derived from multidimensional scaling of generalized description of binding sites [5].

Protein evolution and design

Learning about the mechanisms behind protein structure formation is one way to deepen our understanding of proteins. We have devised an efficient amino acid substitution matrix, called MIQS, based on a set of typical existing matrices[6]. We have also succeeded in comparing protein profiles related to sequence (evolution) and structure to discover common sequential and conformal characteristics between unrelated proteins [7].

Research at our lab

Our lab is in Artificial Intelligent Research Center (AIRC) at the AIST Tokyo Waterfront Research Center in Odaiba, Tokyo.


  1. K. Tomii et a;., FORTE: a profile-profile comparison tool for protein fold recognition. Bioinformatics (2004).
  2. T. Shiota et al., Molecular architecture of the active mitochondrial protein gate. Science (2015).
  3. M. Lensink et al., Prediction of homo-and hetero- protein complexes by protein docking and template-based modeling:a CASP-CAPRI experiment. Proteins (2016).
  4. J. Ito et al., PoSSuM v.2.0: data update and a new function for investigating ligand analogs and target pro- teinsofsmall-moleculedrugs. NAR (2015).
  5. T. Nakamura et al., Protein ligand-binding sitecompari- son by a reduced vector representation derived from multidimensional scaling of generalized description of binding sites. Methods (2016).
  6. K. Yamada et al., Revisiting amino acid substitution matrices for identifying distantly related proteins. Bioinformatics (2014).
  7. K. Tomii et al., Convergent evolution in structural ele- ments of proteins investigated using cross profile analysis. BMC Bioinformatics (2012).

Fig. 1: Protein structure prediction using FORTE


The University of Tokyo
Graduate School of Frontier Sciences, The University of Tokyo

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