Prediction of Metabolism of Drugs Using Artificial Intelligence: How far have we Reached?

被引:24
作者
Kumar, Rajnish [1 ]
Sharma, Anju [1 ]
Siddiqui, Mohammed Haris [2 ]
Tiwari, Rajesh Kumar [1 ]
机构
[1] Amity Univ Uttar Pradesh, Amity Inst Biotechnol, Lucknow 226028, Uttar Pradesh, India
[2] Integral Univ, Dept Bioengn, PO Basha,Kursi Rd, Lucknow 226026, Uttar Pradesh, India
关键词
Artificial intelligence; drug designing; drug metabolism; machine learning; pharmacokinetics; prediction; MACHINE-LEARNING TECHNIQUES; CYP-MEDIATED SITES; CYTOCHROME-P450; 3A4; CHEMICAL METABOLISM; 1A2; INHIBITION; RS-PREDICTOR; MODELS; REGIOSELECTIVITY; CLASSIFICATION; STABILITY;
D O I
10.2174/1389200216666151103121352
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Information about drug metabolism is an essential component of drug development. Modeling the drug metabolism requires identification of the involved enzymes, rate and extent of metabolism, the sites of metabolism etc. There has been continuous attempts in the prediction of metabolism of drugs using artificial intelligence in effort to reduce the attrition rate of drug candidates entering to preclinical and clinical trials. Currently, there are number of predictive models available for metabolism using Support vector machines, Artificial neural networks, Bayesian classifiers etc. There is an urgent need to review their progress so far and address the existing challenges in prediction of metabolism. In this attempt, we are presenting the currently available literature models and some of the critical issues regarding prediction of drug metabolism.
引用
收藏
页码:129 / 141
页数:13
相关论文
共 68 条
[1]   Structural and chemical profiling of the human cytosolic sulfotransferases [J].
Allali-Hassani, Abdellah ;
Pan, Patricia W. ;
Dombrovski, Ludmila ;
Najmanovich, Rafael ;
Tempel, Wolfram ;
Dong, Aiping ;
Loppnau, Peter ;
Martin, Fernando ;
Thonton, Janet ;
Edwards, Aled M. ;
Bochkarev, Alexey ;
Plotnikov, Alexander N. ;
Vedadi, Masoud ;
Arrowsmith, Cheryl H. .
PLOS BIOLOGY, 2007, 5 (05) :1063-1078
[2]   Development of CYP3A4 inhibition models: Comparisons of machine-learning techniques and molecular descriptors [J].
Arimoto, R ;
Prasad, MA ;
Gifford, EM .
JOURNAL OF BIOMOLECULAR SCREENING, 2005, 10 (03) :197-205
[3]   Kohonen maps for prediction of binding to human cytochrome P450 3A4 [J].
Balakin, KV ;
Ekins, S ;
Bugrim, A ;
Ivanenkov, YA ;
Korolev, D ;
Nikolsky, YV ;
Skorenko, AV ;
Ivashchenko, AA ;
Savchuk, NP ;
Nikolskaya, T .
DRUG METABOLISM AND DISPOSITION, 2004, 32 (10) :1183-1189
[4]   INTERSPECIES PHARMACOKINETIC SCALING AND THE DEDRICK PLOTS [J].
BOXENBAUM, H ;
RONFELD, R .
AMERICAN JOURNAL OF PHYSIOLOGY, 1983, 245 (06) :R768-R775
[5]   Recursive partitioning for the prediction of cytochromes P450 2D6 and 1A2 inhibition: Importance of the quality of the dataset [J].
Burton, Julien ;
Ijjaali, Ismail ;
Barberan, Olivier ;
Petitet, Francois ;
Vercauteren, Daniel P. ;
Michel, Andre .
JOURNAL OF MEDICINAL CHEMISTRY, 2006, 49 (21) :6231-6240
[6]   A rapid computational filter for cytochrome P450 1A2 inhibition potential of compound libraries [J].
Chohan, KK ;
Paine, SW ;
Mistry, J ;
Barton, P ;
Davis, AM .
JOURNAL OF MEDICINAL CHEMISTRY, 2005, 48 (16) :5154-5161
[7]   Model based on GRID-derived descriptors for estimating CYP3A4 enzyme stability of potential drug candidates [J].
Crivori, P ;
Zamora, I ;
Speed, B ;
Orrenius, C ;
Poggesi, I .
JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN, 2004, 18 (03) :155-166
[8]   MetaSite: Understanding metabolism in human cytochromes from the perspective of the chemist [J].
Cruciani, G ;
Carosati, E ;
De Boeck, B ;
Ethirajulu, K ;
Mackie, C ;
Howe, T ;
Vianello, R .
JOURNAL OF MEDICINAL CHEMISTRY, 2005, 48 (22) :6970-6979
[9]  
Earnshaw C, 2010, CHEM WORLD-UK, V7, P55
[10]   Generation and validation of rapid computational filters for CYP2D6 and CYP3A4 [J].
Ekins, S ;
Berbaum, J ;
Harrison, RK .
DRUG METABOLISM AND DISPOSITION, 2003, 31 (09) :1077-1080