Multi target drug design for gastrointestinal cancer

医学 自动停靠 药品 对接(动物) 癌症 靶向治疗 药理学 计算生物学 癌症研究 生物信息学 内科学 生物 生物化学 生物信息学 护理部 基因
作者
Varun Jaiswal
出处
期刊:Annals of Oncology [Elsevier BV]
卷期号:28: iii18-iii19 被引量:4
标识
DOI:10.1093/annonc/mdx261.020
摘要

Introduction: Gastrointestinal cancer is one of the most diagnosed cancer after lung and breast cancer world wide. Gastrointestinal cancer is complex disease and conventional methods used to design drug which is targeting one drug target have limited success in cancer treatment till now. The compensatory mechanism and pathways which limits the effectiveness of single target based drugs. Researcher have suggested multi target therapy may be able to treat complex disease such as cancer as well as overcome drug resistance (Giordano and Petrelli 2008; Li, Schurig-Briccio et al. 2014). Development of drug for multiple target same time is challenging task and limited studies have been done so far. Current work is an attempt to design inhibitors for two drug target important in gastrointestinal cancer simultaneously. Methods: Crystal structure of two important drug targets in gastrointestinal cancer insulin-like growth factor receptor (IGF-1R) (PDBID: 4U0I) and receptor tyrosine kinase (KIT) (PDBID: 2ZM3) were taken from protein data bank. Diverse set of molecules of NCI diversity 3 were taken from ZINC database. Ligand preparation was carried out with the help of babel and AutoDock tool kit. In both selected drug target literature reported binding cavity were used for docking study. Co-crystal ligands were removed from crystal structure of both the drug target and binding site defined with the help of auto-dock tool kit. AutoDock 4.2 was used for docking studies to calculate estimated free binding energy (FBE) of all molecules from NCI diversity set 3. Finally ranking of all ligands in both drug target was prepared and common inhibitors were identified with the help of self-developed PERL scripts. similarity analysis was carried out using ChemMine on common inhibitor to verified the uniqueness of identified common inhibitors. Finally interaction of selected ligands in docking complex was studied through ligplot and manual visualization using UCSF chimera. Results: All molecules used for docking were ranked according to FBE for both the drug target separately. In case of KIT FBE ranges from -3.8 to -12.2 and for IGF-1R FBE ranges from -2.98 to -11.24. Six ligands had FBE < =10.5 in KIT and IGF-1R were selected as a common inhibitor for the both selected drug targets. Clustering of six selected common ligands resulted in four cluster. Further interactions of these ligands in docking complexes were studied and common interaction pattern were observed in both the drug targets. Conclusion: Virtual screening of diverse set of molecule were carried out successfully on two important drug targets reported in gastrointestinal cancer. Six compounds were identified which had high FBE in both targets which indicate them as multi-target drug for gastrointestinal cancer. These compounds can be verified in further experimentation and may provide new starting point for the treatment of gastrointestinal cancer.

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