title: Development of a human dihydroorotate dehydrogenase (hDHODH) pharma-similarity index approach with scaffold-hopping strategy for the design of novel potential inhibitors.
abstract: Human dihydroorotate dehydrogenase (hDHODH) is a class-2 dihydroorotate dehydrogenase. Because it is extensively used by proliferating cells, its inhibition in autoimmune and inflammatory diseases, cancers, and multiple sclerosis is of substantial clinical importance. In this study, we had two aims. The first was to develop an hDHODH pharma-similarity index approach (PhSIA) using integrated molecular dynamics calculations, pharmacophore hypothesis, and comparative molecular similarity index analysis (CoMSIA) contour information techniques. The approach, for the discovery and design of novel inhibitors, was based on 25 diverse known hDHODH inhibitors. Three statistical methods were used to verify the performance of hDHODH PhSIA. Fischer's cross-validation test provided a 98% confidence level and the goodness of hit (GH) test score was 0.61. The q(2), r(2), and predictive r(2) values were 0.55, 0.97, and 0.92, respectively, for a partial least squares validation method. In our approach, each diverse inhibitor structure could easily be aligned with contour information, and common substructures were unnecessary. For our second aim, we used the proposed approach to design 13 novel hDHODH inhibitors using a scaffold-hopping strategy. Chemical features of the approach were divided into two groups, and the Vitas-M Laboratory fragment was used to create de novo inhibitors. This approach provides a useful tool for the discovery and design of potential inhibitors of hDHODH, and does not require docking analysis; thus, our method can assist medicinal chemists in their efforts to identify novel inhibitors.
authors: Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan.
authors: Kuei-Chung
authors: KC
authors: Shih
authors: Bioinformatics Center, Chang Gung University, Taoyuan, Taiwan.
authors: Chi-Ching
authors: CC
authors: Lee
authors: Graduate Institute of Chang-Gung Medical Science, Chang-Gung University, Taoyuan, Taiwan.
authors: Chi-Neu
authors: CN
authors: Tsai
authors: Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan.
authors: Yu-Shan
authors: YS
authors: Lin
authors: Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan ; Department of Computer Science and Information Engineering, Providence University, Taichung, Taiwan.
authors: Chuan-Yi
authors: CY
authors: Tang
mesh_terms: D000090722:Dihydroorotate Dehydrogenase; D015195:Drug Design; D004791:Enzyme Inhibitors / Q000737:chemistry* / Q000378:metabolism / Q000494:pharmacology; D006801:Humans; D006860:Hydrogen Bonding; D020128:Inhibitory Concentration 50; D008958:Models, Molecular; D015394:Molecular Structure; D044925:Oxidoreductases Acting on CH-CH Group Donors / Q000037:antagonists & inhibitors / Q000737:chemistry* / Q000378:metabolism; D015203:Reproducibility of Results
chemical_list: D000090722:Dihydroorotate Dehydrogenase; D004791:Enzyme Inhibitors; D044925:Oxidoreductases Acting on CH-CH Group Donors