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研究领域

(1)计算机辅助药物设计:这是目前国际上十分活跃的研究领域,它以计算机为工具,充分利用已知的生物大分子靶标和/或药物分子结构活性知识,通过分子模拟、虚拟筛选、理论计算和预测等现代计算化学技术,来指导和辅助新型药物分子的发现和设计。目前已有许多计算机辅助设计的成功例证,并在创新药物研究中显示了强大的优势,大大加快了药物发现的进程。实验室目前与学院内外多个教授合作,综合利用虚拟筛选、三维定量构效关系分析、药效团模建以及虚拟组合库设计等多种药物设计手段,主要针对肿瘤、神经系统疾病、代谢性疾病、感染性疾病等靶标进行先导化合物发现、设计和优化研究。 (2)药物信息学:一方面,主要基于系统生物学和化学基因组学等技术,开发网络药理学研究新方法,如基于网络的推理算法预测药物-靶标相互作用网络,可用于新药和新靶标发现,也用于老药新用研究;另一方面,主要采用化学信息学技术,比如子结构模式识别、信息增益、组合分类器等,对药物代谢动力学性质及药物安全性等进行预测研究;同时,利用所开发的方法和技术,进行化合物的生态环境风险评估、计算环境毒理学等研究。 (3)计算生物学:生物大分子之间的相互作用,如蛋白质-蛋白质、蛋白质-核酸、蛋白质-多糖之间的相互作用是生命活动的基础,同时也是药物设计研究的基础。这些相互作用不是静止不变的而是动态变化的,但目前的实验条件除了测定相互作用体的复合物之外,还难以在分子水平上研究这些动态相互作用的各个方面。而计算机模拟研究则可在虚拟现实的情况下,基于实验测定的复合物结构,在分子水平上对这些相互作用从动力学和热力学角度进行定性和定量的分析研究,是对实验研究的重要补充和完善。实验室目前主要采用分子动力学模拟和结合自由能计算方法对蛋白-蛋白、蛋白-核酸、蛋白-小分子等相互作用体系进行深入研究,阐明其相互作用机理,进而开发可以调节其生理功能的活性小分子。

近期论文

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Cheng FX, Li WH, Liu GX, Tang Y*. In silico ADMET prediction: recent advances, current challenges and future trends. Curr. Top. Med. Chem., 2013, 13(11): 1273-1289. (invited review) Cheng FX, Li WH, Zhou YD, Li J, Shen J, Lee PW, Tang Y*. Prediction of human genes and diseases targeted by xenobiotics using predictive toxicogenomics-derived models (PTDMs). Mol. BioSystems, 2013; 9(6): 1316-1325. Cheng FX, Li WH, Wu ZR, Wang XC, Zhang C, Li J, Liu GX, Tang Y*. Prediction of polypharmacological profiles of drugs by the integration of chemical, side effects and therapeutic space. J. Chem. Inf. Model., 2013; 53(4): 753-762. Cheng FX, Li WH, Wang XC, Zhou YD, Wu ZR, Shen J, Tang Y*. Adverse drug events: database construction and in silico prediction. J. Chem. Inf. Model., 2013; 53(4): 744-752. Hu GP, Li X, Zhang X, Li YZ, Ma L, Yang LM, Liu GX, Li WH, Huang J*, Shen X, Hu LH*, Zheng YT*, Tang Y*. Discovery of inhibitors to block interactions of HIV-1 integrase with human LEDGF/p75 via structure-based virtual screening and bioassays. J. Med. Chem., 2012; 55(22): 10108-10117. Cheng FX, Zhou YD, Li WH, Shen J, Wu ZR, Liu GX, Lee PW, Tang Y*. admetSAR: a comprehensive source and free tool for assessment of chemical ADMET properties. J. Chem. Inf. Model., 2012; 52(11): 3099-3105. Li WH, Fu J, Cheng FX, Zheng MY*, Zhang J, Liu GX, Tang Y*. Unbinding pathways of GW4064 from human farnesoid X receptor as revealed by molecular dynamics simulations. J. Chem. Inf. Model., 2012; 52(11): 3043-3052. Xu CY, Cheng FX, Chen L, Du Z, Li WH, Liu GX*, Lee PW, Tang Y*. In silico prediction of chemical Ames mutagenicity. J. Chem. Inf. Model., 2012; 52(11): 2840-2847. Cheng FX, Zhou YD, Li WH, Liu GX, Tang Y*. Prediction of chemical-protein interactions network with weighted network-based inference method. PLoS ONE, 2012; 7(7): e41064. Cheng FX, Zhou YD, Li J, Li WH, Liu GX, Tang Y*. Computational prediction of chemical-protein interactions: multitarget-QSAR versus computational chemogenomic methods. Mol. BioSystems, 2012; 8(9): 2373-2384. Hu GP, Kuang GL, Xiao W, Li WH, Liu GX, Tang Y*. Performance evaluation of 2D fingerprint and 3D shape similarity methods in virtual screening. J. Chem. Inf. Model. 2012; 52(5): 1103-1113. Cheng FX, Liu C, Jiang J, Lu WQ, Li WH, Liu GX, Zhou WX*, Huang J*, Tang Y*. Prediction of drug-target interactions and drug repositioning via network-based inference. PLoS Comput. Biol., 2012; 8(5): e1002503. Cheng FX, Ikenaga Y, Zhou YD, Yu Y, Shen J, Du Z, Liu GX, Li WH, Lee PW*, Tang Y*. In silico assessment of chemical biodegradability. J. Chem. Inf. Model., 2012; 52(3): 655-669. Shen ZH, Cheng FX, Xu Y, Fu J, Xiao W, Shen J, Liu GX, Li WH*, Tang Y*. Investigation of indazole unbinding pathways in CYP2E1 by molecular dynamics simulations. PLoS ONE, 2012; 7(3): e33500. Cheng FX, Yu Y, Zhou YD, Shen ZH, Xiao W, Liu GX, Li WH*, Lee PW, Tang Y*. Insights into molecular basis of cytochrome P450 inhibitory promiscuity of compounds. J. Chem. Inf. Model., 2011; 51(10): 2482-2495. Fang J, Shen J, Cheng FX, Xu ZJ, Liu GX, Tang Y*. Computational insight into ligand selectivity of estrogen receptor from 3D pharmacophore modeling. Molecular Informatics, 2011; 30(6-7): 539-549. Cheng FX, Yu Y, Shen J, Yang L, Li WH*, Liu GX, Lee PW, Tang Y*. Classification of cytochrome P450 inhibitors and non-inhibitors using combined classifiers. J. Chem. Inf. Model. 2011; 51(5): 996-1011. Shen J, Tan CF, Zhang YY, Li X, Li WH, Huang J*, Shen X, Tang Y*. Discovery of potent ligands for estrogen receptor b by structure-based virtual screening. J. Med. Chem. 2010; 53(14): 5361-5365. Li YZ, Shen J, Sun XQ, Li WH, Liu GX, Tang Y*. Accuracy assessment of protein-based docking programs against RNA targets. J. Chem. Inf. Model. 2010; 50(6): 1134-1146. Shen J, Cheng FX, Xu Y, Li WH*, Tang Y*. Estimation of ADME properties with substructure pattern recognition. J. Chem. Inf. Model. 2010; 50(6): 1034-1041. Chu YY, Yang C, Chen XJ, Zheng WY, Yang Y*, Tang Y*. Structure-function analysis of human protein Ero1-Lα. Biochem. Biophys. Res. Comm. 2009; 389(4): 645-650. Shen J, Li WH, Liu GX, Tang Y*, Jiang HL. Computational insights into the mechanism of ligand unbinding and selectivity of estrogen receptors. J. Phys. Chem. B 2009; 113(30): 10436-10444. Li WH, Ode H, Hoshino T*, Liu H, Tang Y*, Jiang HL. Reduced catalytic activity of P450 2A6 mutants with coumarin: a computational investigation. J. Chem. Theory Comput. 2009; 5(5): 1411-1420. Du L, Zhao YX, Chen J, Yang LM, Zheng YT, Tang Y*, Shen X*, Jiang HL. D77, one benzoic acid derivative, functions as a novel anti-HIV-1 inhibitor targeting the interaction between integrase and cellular LEDGF/p75. Biochem. Biophys. Res. Comm. 2008; 375(1): 139-144.

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