Biomedical subjects

Yoshiharu Hayashi

Publications and source records attributed to Yoshiharu Hayashi.

5 recordsLinked to original sources

PubMed2005

1-((S)-gamma-substituted prolyl)-(S)-2-cyanopyrrolidine as a novel series of highly potent DPP-IV inhibitors.

1-(Gamma-substituted prolyl)-(S)-2-cyanopyrrolidines were designed based on the predicted binding mode of the known DPP-IV inhibitor NVP-DPP728 and evaluated for their inhibitory activity. In structure-activity relationship study at the gamma-position of proline, it became clear that compounds bearing (S)-stereochemistry were 20-fold more potent than the antipode. Of these compounds, the (3,4-dicyanophenyl)amino- and (3-chloro-4-cyanophenyl)amino-derivatives showed the highest inhibitory activity.

Dipeptidyl Peptidase 4↗

PubMed2004

Protein classification using comparative molecular interaction profile analysis system.

We recently introduced a new molecular description factor, interaction profile Factor (IPF) that is useful for evaluating molecular interactions. IPF is a data set of interaction energies calculated by the Comparative Molecular Interaction Profile Analysis system (CoMIPA). CoMIPA utilizes AutoDock 3.0 docking program, and the system has shown to be a powerful tool in clustering the interacting properties between small molecules and proteins. In this report, we describe the application of CoMIPA for protein clustering. A sample set of 15 proteins that share less than 20% homology and have no common functional motifs in primary structure were chosen. Using CoMIPA, we were able to cluster proteins that bound to the same small molecule. Other structural homology-based clustering programs such as PSI-BLAST or PFAM were unable to achieve the same classification. The results are striking because it is difficult to find any common features in the active sites of these proteins that share the same ligand. CoMIPA adds new dimensions for protein classification and has the potential to be a helpful tool in predicting and analyzing molecular interactions.

Algorithms↗

PubMed2003

Sterol ferulates, sterols, and 5-alk(en)ylresorcinols from wheat, rye, and corn bran oils and their inhibitory effects on Epstein-Barr virus activation.

Sterol ferulate, free sterol, and 5-alk(en)ylresorcinol constituents of wheat, rye, and corn bran oils were studied. Among the sterol ferulates, one novel compound, 24-methylenecholestanol ferulate (7), along with six known compounds, namely, 24-methylcholestanol ferulate (1), 24-methylcholesterol ferulate (2), 2-methyllathosterol ferulate (3), stigmastanol ferulate (4), sitosterol ferulate (5), and schottenol ferulate (6), were isolated and characterized. Five known free sterols, namely, 24-methylcholesterol (8), stigmastanol (9), sitosterol (10), schottenol (11), and stigmasterol (12), were isolated and identified. 5-Alk(en)ylresorcinols were found in wheat and rye bran oils but not in corn bran oil. Of these, one new compound, 5-n-(2'-oxo-14'-Z-heneicosenyl) resorcinol (19), and seven known compounds, namely, 5-n-heptadecyl- (13), 5-n-nonadecyl- (14), 5-n-heneicosyl- (15), 5-n-tricosyl- (16), 5-n-pentacosyl- (17), 5-n-(14'-Z-nonadecenyl)- (18), and 5-n-(2'-oxoheneicosyl)resorcinols (20), were isolated and characterized. These compounds were evaluated with respect to their inhibitory effects on the induction of Epstein-Barr virus early antigen (EBV-EA) by 12-O-tetradecanoylphorbol-13-acetate (TPA) in Raji cells, which is known to be a primary screening test for antitumor promoters. Four compounds, 1, 2, 4, and 11, showed potent inhibitory effects on EBV-EA induction.

Coumaric Acids↗

PubMed2003

Molecular evaluation using in silico protein interaction profiles.

MOTIVATION: To find a correlation between the activities and structures of molecules is one of the most important subjects for molecular evaluation study. Traditional quantitative structure-activity relationship (QSAR) methodologies represent those attempts using physicochemical descriptors. Creating a new molecular description factor based on the results of a computational docking study will add new dimensions to molecular evaluation. RESULTS: We propose a new molecular description factor analysis system called the Comparative Molecular Interaction Profile Analysis (CoMIPA) system in which the AutoDock program is used for docking evaluation of small molecule compound-protein complexes. Interaction energies are calculated, and the data sets obtained are called interaction profiles (IPFs). Using the IPF as a scoring indicator, the system could be a powerful tool to cluster the interacting properties between small molecules and bio macromolecules such as ligand-receptor bindings. Further development of the system will enable us to predict the adverse effects of a drug candidate.

Algorithms↗

PubMed2003

RNA aptamer evaluation using comparative molecular interaction profile analysis system.

In this paper, we introduce a system named Comparative Molecular Interaction Profile Analysis system (CoMIPA) that utilizes virtual docking study for comprehensive analysis of molecular interactions. Research of RNA aptamer is very useful to creation of functional molecules, because RNA aptamer is excellent in binding selectivity and the stability of structure. By using 3-bases RNA fragment, the system can use computational molecular docking results to help for RNA aptamer screening. We believe that the system has the potential to be a useful for RNA aptamer design.

Binding Sites↗