作者: Sandhya Kortagere , Sean Ekins
DOI: 10.1016/J.VASCN.2010.02.005
关键词: Troubleshooting 、 Workflow 、 Adme tox 、 ADME 、 Quantitative structure–activity relationship 、 Machine learning 、 Drug discovery 、 Cheminformatics 、 Biology 、 Artificial intelligence 、 Bioinformatics 、 Toxicology 、 Pharmacology
摘要: Computational approaches for drug discovery such as ligand-based and structure-based methods, are increasingly seen an efficient approach lead well providing insights on absorption, distribution, metabolism, excretion toxicity (ADME/Tox). What is perhaps less known widely described the limitations of different technologies. We have therefore presented a troubleshooting to QSAR, homology modeling, docking hybrid methods. If computational or cheminformatics methods become more used by non-experts it critical that brought user's attention addressed during their workflows. This could improve quality models results obtained.