Biomedical subjects

Daisuke Takaya

Publications and source records attributed to Daisuke Takaya.

6 recordsLinked to original sources

PubMed2006

FAMS complex: a fully automated homology modeling system for protein complex structures.

The formation of a protein-protein complex is responsible for many biological functions; therefore, three-dimensional structures of protein complexes are essential for deeper understandings of protein functions and the mechanisms of diseases at the atomic level. However, compared with individual proteins, complex structures are difficult to solve experimentally because of technical limitations. Thus a method that can predict protein complex structures would be invaluable. In this study, we developed new software, FAMS Complex; a fully automated homology modeling system for protein complex structures consisting of two or more molecules. FAMS Complex requires only sequences and alignments of the target protein as input and constructs all molecules simultaneously and automatically. FAMS Complex is likely to become an essential tool for structure-based drug design, such as in silico screening to accelerate drug discovery before an experimental structure is solved. Moreover, in this post-genomic era when huge amounts of protein sequence information are available, a major goal is the determination of protein-protein interaction networks on a genomic scale. FAMS Complex will contribute to this goal, because its procedure is fully automated and so is suited for large-scale genome wide modeling.

Automation↗

PubMed2005

Searching for protein-protein interaction sites and docking by the methods of molecular dynamics, grid scoring, and the pairwise interaction potential of amino acid residues.

In CAPRI Rounds 1 and 2, we assumed that because there are many ionic charges that weaken electrostatic interaction forces in living cells, the hydrophobic interaction force might be important entropically. As a result of Rounds 1 and 2, the predictions for binding sites and geometric centers were acceptable, but those of the binding axes were poor, because only the largest benzene cluster was used for generating the initial docking structures. These were generated by fitting of benzene clusters formed on the surface of receptor and ligand. In CAPRI Rounds 3-5, the grid-scoring sum on the protein-protein interaction surface and the pairwise potential of the amino acid residues, which were indicated as coming easily into the protein-protein interaction regions, were used as the calculation methods, along with the smaller benzene clusters that participated in benzene cluster fitting. Good predicted models were obtained for Targets 11 and 12. When the modeled receptor proteins were superimposed on the experimental structures, the smallest ligand root-mean-square deviation (RMSD) values corresponding to the RMSD between the model and experimental structures were 6.2 A and 7.3 A, respectively.

Algorithms↗

PubMed2005

Protein structure prediction in CASP6 using CHIMERA and FAMS.

In CASP6, the CHIMERA-group predicted full-atom models of all targets using SKE-CHIMERA, a Web-user interface system for protein structure prediction that allows human intervention at necessary stages; we used a lot of information from our own data and from publicly available data. Using SKE-CHIMERA, we iterated manual step (template selection and alignment by the in-house program CHIMERA) and automatic step (three-dimensional model building by the in-house program FAMS). The official CASP6 assessment showed that CHIMERA-group was one of the most successful predictors in homology modeling, especially for FR/H (Fold Recognition/Homologous). In this article, we introduce the method of CHIMERA-group and discuss its successes and failures in CASP6.

Algorithms↗

PubMed2004

Remarkably different structures and reaction mechanisms of ketoreductases for the opposite stereochemical control in the biosynthesis of BIQ antibiotics.

Two ketoreductases, RED1 and RED2, are involved in the biosynthesis of actinorhodin in Streptomyces coelicolor A3(2) and dihydrogranaticin in S. violaceoruber Tu22, respectively. They are responsible for the stereospecific reductions of the bicyclic intermediate to give (S)- or (R)-DNPA, although there is no similarity between their amino acid sequences. Biotransformation using synthetic analogous substrates revealed that the substrate specificities are quite different. Homology modelling studies and site directed mutagenesis showed remarkable differences in three-dimensional structures and catalytic mechanisms between RED1 and RED2.

Alcohol Oxidoreductases↗

PubMed2004

Evaluation of homology modeling of the severe acute respiratory syndrome (SARS) coronavirus main protease for structure based drug design.

To accelerate the development of drugs against severe acute respiratory syndrome (SARS), we constructed a homology model of the SARS coronavirus main protease using our modeling software, FAMS Ligand&Complex, and released it before the X-ray structure was solved. The X-ray structure showed our model as accurately predicted and useful for structure based drug design.

Antiviral Agents↗

PubMed2004

Protein structure prediction in structure based drug design.

The human genome and other genome sequencing projects have generated huge amounts of protein sequence information. Recently, a structural genomics project that aims to determine at least one representative three-dimensional structure from every protein family experimentally has been started. Homology modeling will play an essential role in structure based drug design such as in silico screening; because based on these representative structures the three-dimensional structures of the remaining proteins encoded in the various genomes can be predicted by homology modeling. The results of the last Critical Assessment of Techniques for Protein Structure Prediction (CASP5) demonstrated that the quality of homology modeling prediction has improved; reaching a level of reliability that biologists can now confidently use homology modeling. With improvements in modeling software and the growing number of known protein structures, homology modeling is becoming a more and more powerful and reliable tool. The present paper discusses the features and roles of homology modeling in structure based drug design, and describes the CHIMERA and FAMS modeling systems as examples. For a sample application, homology modeling of non-structural proteins of the severe acute respiratory syndrome (SARS) coronavirus is discussed. Many biological functions involve formation of protein-protein complexes; in which the protein molecules behave dynamically in the course of binding. Therefore, an understanding of protein-protein interaction will be very important for structure based drug design. To this end, normal mode analysis is useful. The present paper discusses the prediction of protein-protein interaction using normal mode analysis and examples of applications are given.

Amino Acid Sequence↗