Abstracts Keynote & Plenary

The results demonstrate that our method achieves good performances on predicting transcriptional
regulations.
Keywords: regulatory networks, ChIP-chip, TF knock-out and expression data
PO-038
The development
of SNP prediction algorithm for CYtochrome P450
Li Li and Dongqing Wei
Department of Bioinformatics
and Biostatistics, College of Life Sciences and Biotechnology, Shanghai
Jiaotong University, 800 Dongchuan Road, Minhang District Shanghai, 200240, China
Cytochrome P450 (also called CYPs, P450s and CYP450s), a member of hemoproteins
superfamily[1-3], has been identified from variety of species. The P450s are the most important
enzymes responsible for drug metabolism. They participate in many kinds of catalyze reactions refer to
both exogenous and endogenous compounds. Single nucleotide polymorphisms (SNPs) are the most
frequently occurring genetic variation in the human CYPs, considered as a decisive factor for the
disease susceptibility and drug response. Consequently, SNPs have become one of the most significant
research areas in current human genomic studies.
In the post-genome era, the rapid accumulation of SNP data provides an opportunity to find out SNPs
using computational methods. However, the majority of current predict methods are unsatisfactory due
to the lower prediction accuracy (just about 40%-50%).
In order to solve this problem, we build a support vector machine (SVM) model based on the protein
coded by the gene around CYP450 SNP site and the physical and chemical properties of the
amino acids. By using a wide range of data, we demonstrate the accuracy of this method achieves
65%, which is about 15% higher Compared with the existing machine learning method (including
the random forest method and K-neighbor method) and pattern discovery algorithm. However, the
accuracy of this algorithm is still quite low. Currently, we are making efforts to integrate more
information for further optimization.
References
1.Jing-Fang Wang
and Dong-Qing, Wei*, “Role of Structural Bioinformatics and TCM databases in
Pharmacogenomics”, Pharmacogenomics, 10, Issue 10 (2009).
2.Jing-Fang Wang, Cheng-Cheng Zhang, , Jing-Yi Yan, Kuo-Chen Chou, Dong-Qing Wei* ,
“Structure of cytochrome P450s and personalized drug”, Current Medicinal Chem, 16, 232-244(2009).
3. Jing-Fang Wang , Dong-Qing Wei*, Kuo-Chen Chou, “Pharmacogenomics and Personalized Use of
Drugs”, Current Topics in Medicinal Chemistry, 8, 1573-1579(2008).
Conventional and solvent free syntheses of 1N-3-{(4-substituted
aryl-3-chloro-2-oxo-azetidine)-imido}-propyl-1,2,3 -benzotriazole derivatives: Antimicrobial
activity
Ritu Sharma
and S.D. Srivastava*
Synthesis organic laboratory, Department
of Chemistry,
Dr. H.S. Gour University(A Central University), Sagar- 470003,
India
Email: ritusharmaic@rediffmail.com
Heterocycles bearing nitrogen moieties constitute the core structure of numbers of pharmacologically
and biologically active interesting compounds. The efficiency of azoles as chemotherapeutic agent is
well established. Various derivatives of 1,2,3-benzo-triazole and 2-oxoazetidines exhibit interesting
pharmacological properties including antimicrobial, antifungal, anticancer, analgesic anticonvulsant,
antiinflamma-tory, and CNS depressant. In this work, we focus interest on incorporating azetidinone