Sheng Zhong1, Bo Wu2,3, Wenzhuo Yang2, Junliang Ge2, Xiangheng Zhang1, Zhenghe Chen1, Hao Duan1, Zhenqiang He1, Yibing Liu2, Hongyu Wang2, Yuting Jiang2, Zhiyun Zhang2, Xinhui Wang4, Weihang Li5, Naimeng Liu2, Xiaoyu Guo1, Yonggao Mou1. 1. Neurosurgery and Neuro-Oncology Department, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China. 2. Clinical College, Jilin University, Changchun, China. 3. Department of Orthopaedics, The First Hospital of Jilin University, Changchun, China. 4. Department of Oncology, The First Bethune Hospital of Jilin University, Changchun, China. 5. Department of Orthopaedics, Xijing Hospital, The Fourth Military Medical University, Xi'an, China.
Abstract
OBJECT: This study was designed to screen ideal lead compounds and drug candidates with an inhibitory effect on PARP from the drug library (ZINC database). RESULTS: Two effective natural compounds ZINC000003938684 and ZINC000014811844 were found to bind to PARP in the ZINC database, showing a higher binding affinity. Also, they were predicted to have lower rodent carcinogenicity, Ames mutagenicity, developmental toxicity potential, and high tolerance to cytochrome P4502D6. Molecular dynamics simulation showed that ZINC000003938684 and ZINC000014811844 had a more favorable potential energies with PARP, which could exist stably in natural circumstances. CONCLUSION: This study suggested that ZINC000003938684 and ZINC000014811844 were ideal potential inhibitors of PARP targeting. These compounds were safe drug candidates and had important implications for the design and improvement of CMET target drugs. METHODS: A battery of computer-aided virtual techniques were used to identify potential inhibitors of PARP. LibDock is used for structure-based screening followed by ADME (absorption distribution, metabolic excretion) and toxicity prediction. Molecular docking was performed to demonstrate the binding affinity mechanism between the ligand and PARP. Molecular dynamics simulations were used to evaluate the stability of ligand-receptor complexes.
OBJECT: This study was designed to screen ideal lead compounds and drug candidates with an inhibitory effect on PARP from the drug library (ZINC database). RESULTS: Two effective natural compounds ZINC000003938684 and ZINC000014811844 were found to bind to PARP in the ZINC database, showing a higher binding affinity. Also, they were predicted to have lower rodent carcinogenicity, Ames mutagenicity, developmental toxicity potential, and high tolerance to cytochrome P4502D6. Molecular dynamics simulation showed that ZINC000003938684 and ZINC000014811844 had a more favorable potential energies with PARP, which could exist stably in natural circumstances. CONCLUSION: This study suggested that ZINC000003938684 and ZINC000014811844 were ideal potential inhibitors of PARP targeting. These compounds were safe drug candidates and had important implications for the design and improvement of CMET target drugs. METHODS: A battery of computer-aided virtual techniques were used to identify potential inhibitors of PARP. LibDock is used for structure-based screening followed by ADME (absorption distribution, metabolic excretion) and toxicity prediction. Molecular docking was performed to demonstrate the binding affinity mechanism between the ligand and PARP. Molecular dynamics simulations were used to evaluate the stability of ligand-receptor complexes.
Entities:
Keywords:
PARP; drug treatment; glioblastoma; natural products; virtual screening
Authors: B R Brooks; C L Brooks; A D Mackerell; L Nilsson; R J Petrella; B Roux; Y Won; G Archontis; C Bartels; S Boresch; A Caflisch; L Caves; Q Cui; A R Dinner; M Feig; S Fischer; J Gao; M Hodoscek; W Im; K Kuczera; T Lazaridis; J Ma; V Ovchinnikov; E Paci; R W Pastor; C B Post; J Z Pu; M Schaefer; B Tidor; R M Venable; H L Woodcock; X Wu; W Yang; D M York; M Karplus Journal: J Comput Chem Date: 2009-07-30 Impact factor: 3.376
Authors: Magdolna Szántó; Attila Brunyánszki; Borbála Kiss; Lilla Nagy; Pál Gergely; László Virág; Péter Bai Journal: Cell Mol Life Sci Date: 2012-05-13 Impact factor: 9.261