Novel Soybean Variety Lacking Raffinose Synthase 2 Activity.

Variation in the raffinose family oligosaccharide (RFO) content in soybean is advantageous for livestock farming and health science. In this study, a soybean variety (GmJMC172) with a significantly low stachyose content in its seeds was identified in the NARO Genebank core collection. The results of the single-nucleotide polymorphism (SNP) analysis suggested that this phenomenon was related to a single-base deletion, inducing a frameshift mutation in raffinose synthase 2 (RS2), rather than the polymorphisms in the RS3, RS4, and stachyose synthase (STS) sequences. Differences in the enzymatic properties between the native RS2 and truncated RS2 were examined by using a three-dimensional model predicted using Alphafold2. In addition to revealing the missing active pocket in truncated RS2, the modeled structure explained the catalytic role of W331* and suggested a sufficient space to bind both sucrose and raffinose in the ligand-binding pocket. The soybean line, with seeds available from the NARO Genebank, could serve as breeding materials for manipulating the RFO content.

Chemical curation to improve data accuracy: recent development of the 3DMET database.

We have developed a three-dimensional structure database of natural metabolites (3DMET). Early development of the 3DMET database relied on content auto-generated from 2D-structures of other chemical databases. From 2009, we began manual curation, obtaining new compounds from published works. In the process of curation, problems of digitizing 3D-structures from structure drawings of documents were accumulated. As the same as auto-generation, structure drawings should be also payed attention about stereochemistry. Our experiences in manual curation of 3DMET, as described herein, may be useful to others in this field of research and for the development of supporting systems of a chemical structure database. Manual curation is still necessary for proper database entry of the 3D-configurations of chiral atoms, a problem encountered frequently among natural products.

Current Challenges in Development of a Database of Three-Dimensional Chemical Structures.

We are developing a database named 3DMET, a three-dimensional structure database of natural metabolites. There are two major impediments to the creation of 3D chemical structures from a set of planar structure drawings: the limited accuracy of computer programs and insufficient human resources for manual curation. We have tested some 2D-3D converters to convert 2D structure files from external databases. These automatic conversion processes yielded an excessive number of improper conversions. To ascertain the quality of the conversions, we compared IUPAC Chemical Identifier and canonical SMILES notations before and after conversion. Structures whose notations correspond to each other were regarded as a correct conversion in our present work. We found that chiral inversion is the most serious factor during the improper conversion. In the current stage of our database construction, published books or articles have been resources for additions to our database. Chemicals are usually drawn as pictures on the paper. To save human resources, an optical structure reader was introduced. The program was quite useful but some particular errors were observed during our operation. We hope our trials for producing correct 3D structures will help other developers of chemical programs and curators of chemical databases.

Three-dimensional structure database of natural metabolites (3DMET): a novel database of curated 3D structures.

A database of 3D structures of natural metabolites has been developed called 3DMET. During the process of structure conversion from 2D to 3D, we found many structures were misconverted at chiral atoms and bonds. Several popular converters were tested in regard to their conversion accuracy. For verification, three canonical strings were also tested. No procedure could satisfactorily cover all the structures of the natural products. The misconverted structures had to be corrected manually. However, a nonnegligible number of mistakes were also observed even after manual curation, so a self-checking system was developed and introduced to our work flow. Thus, the 3D structures in our 3DMET database were evaluated in two steps: automatically and manually. The current version includes most of the natural products of the KEGG COMPOUND collection [ http://www.genome.jp/kegg/compound/ ] and is searchable by string, value range, and substructure. 3DMET can be accessed via http://www.3dmet.dna.affrc.go.jp/ , which also has detailed manuals.

Development of new indices to evaluate protein-protein interfaces: assembling space volume, assembling space distance, and global shape descriptor.

Protein-protein interaction is fundamental to initiate the cellular functions of proteins, and thus structural analyses of protein interfaces are the first step to understand their functions at the molecular level. Although shape complementarities have been used to evaluate the fitness of interfaces, the conventional method did not distinguish between two main components of complementarity, the well-fitting of the surface shapes and the size of the gap regions between the pair of molecules, and could not evaluate the global shape of the interfaces. Therefore, we now propose three new indices to describe protein interfaces: assembling space volume (ASV), assembling space distance (AS-distance), and global shape descriptor (GS). The ASV is calculated using Delaunay tessellation, and the AS-distance is calculated as the ratio of ASV to delta-ASA (accessible surface area). The GS is calculated as the ratio of the volume of Delaunay tetrahedra with a long edge to that of all tetrahedra in the assembling space. To evaluate the feasibility of the three indices, we applied our method to homo-dimer proteins, and performed systematic comparisons with SURFNET by Laskowski and shape complementarity by Lawrence and Colman. As a result, our indices behave differently from the existing ones, and shed light on new features of protein-protein interfaces, as general trends of AS-distances for all protein interfaces.