Preliminary Exploring The Evaluation Of Drug Activity In Early Stage Of Drug Research And Development With Chemical Genomics

Characteristics of innovative drug research and development (drug R & D) are high investment, high risks and long cycle. Drug R & D currently are confronting some difficulties such as failures of many clinical trials and the decrement of new drugs passed by FDA. In order to improve the success rate of new drug R & D, shorten the cycle of drug R & D, and reduce drug R & D costs, our initial exploration was to use chemical genomics evaluating drug activity in the early stage of drug R & D.In first, we established a chemical genomics database on the basis of gene expression profiles data in our laboratory and public gene expression profiles data coming from network. Secondly, we compared results of PPAR agonist activity evaluated by Pearson correlation coefficient and Spearman correlation coefficient. Pearson correlation coefficient was selected as analysis method of chemical genomics for the connective of gene and drug. Finally, chemical genomics was used to assess the activity of new synthetic PPAR agonist and HDAC inhibitors. The briefly steps were described in the following:1. Establishment of chemical genomics database: First of all, we have tested gene expression profiles of A549 and HepG2 cells treated by 35 compounds. Secondly, we have collected over 500 Multi-chip data about more than 160 compounds in PC3, MCF7 and HL60 cells from network resources. These data were used to build a chemical genomics database.2. Establishment of analysis methods for chemical genomics data: According to chemical genomics data in PC3 cells, rosiglitazone, a PPAR agonist, was selected as a reference drug. Chemical structure-related genes, gene function and target-related genes were selected as a signature. The parameters Pearson correlation coefficient and non-parameter Spearman correlation coefficient were used to evaluate the compounds in PC3 cells. Results showed that Pearson correlation coefficient were better than Spearman correlation coefficient in the evaluation of drug activity.3. Evaluation of new PPAR agonists: According to chemical genomics data in HepG2 cells, we selected respectively PPAR agonist WY14643, rosiglitazone and chiglitazar as reference drug. Then we selected chemical structure-related genes as a signature. Activities of PPARα, PPARγand PPARα/γwere evaluated by Pearson correlation coefficient. The results showed that CS38 was PPARγ/αdouble-agonist as a biased towards PPARγactivity. CS98 showed strong PPARαactivity while it is similar to CS38 in chemical structure. CS204 was PPARγ/αdouble-agonist. CS88 had no obvious PPARγand PPARαactivity while it was similar to CS204 in chemical structure. CS307 showed PPARα/γdouble-agonist activity. But CS207 only showed strong PPARγactivity while it was similar to CS307 in chemical structure.4. Evaluation of new HDAC inhibitor: According to chemical genomics data in HepG2 and A549 cells, HDAC inhibitor MS-275 in A549 was selected as a reference drug. We selected chemical structure-related genes as a signature. We used Pearson correlation coefficient evaluating HDAC inhibition activity of compounds. The results showed that CS55 was similar to MS-275 in HDAC inhibition activity.In sum, we used chemical genomics on the basis of gene expression profiles data evaluating activities of new synthetic PPAR agonist and HDAC inhibitor in vitro. We established the technology platform of drug activity's evaluation in the early stage of drug R & D on the basis of chemical genomics. The platform was also significance for lead optimization and selection of candidate drug with other therapeutic effect. Chemical genomics could be used to connect genes and drugs, evaluate the activity of new drug in the cell level in the early stage of drug R & D, provide guidance for the pre-clinical and clinical trials, effectively reduce the risk of new drug R & D, and help to improve drug R & D success rate.