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284. Oprea TI, Allu TK, Fara DC et al (2007) Lead-like, drug-like or “Pub-like”: how different
are they? J Comput Aided Mol Des 21:113–119
285. Baell JB, Holloway GA (2010) New substructure filters for removal of pan assay
interference compounds (PAINS) from screening libraries and for their exclusion in
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286. Metz JT, Huth JR, Hajduk PJ (2007) Enhancement of chemical rules for predicting
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https://doi.org/10.1007/s10822-007-9109-z
In Silico Structure-Based Prediction of Receptor–Ligand Binding …
175
opportunities. Curr Opin Chem Biol 8:378–386
278. White RE (1998) Short-and long-term projections about the use of drug metabolism in drug
discovery and development. Drug Metab Dispos 26:1213–1216
279. Eddershaw PJ, Beresford AP, Bayliss MK (2000) ADME/PK as part of a rational approach
to drug discovery. Drug Discov Today 5:409–414
280. Kola I, Landis J (2004) Can the pharmaceutical industry reduce attrition rates? Nat Rev Drug
Discov 3:711
281. Harris CJ, Hill RD, Sheppard DW et al (2011) The design and application of target-focused
compound libraries. Comb Chem High Throughput Screen 14:521–531
282. Paricharak S, Méndez-Lucio O, Chavan Ravindranath A et al (2016) Data-driven approaches
used for compound library design, hit triage and bioactivity modeling in high-throughput
screening. Brief Bioinform 19(2):277–285. https://doi.org/10.1093/bib/bbw105
283. Chuprina A, Lukin O, Demoiseaux R et al (2010) Drug-and lead-likeness, target class, and
molecular diversity analysis of 7.9 million commercially available organic compounds
provided by 29 suppliers. J Chem Inf Model 50:470–479
284. Oprea TI, Allu TK, Fara DC et al (2007) Lead-like, drug-like or “Pub-like”: how different
are they? J Comput Aided Mol Des 21:113–119
285. Baell JB, Holloway GA (2010) New substructure filters for removal of pan assay
interference compounds (PAINS) from screening libraries and for their exclusion in
bioassays. J Med Chem 53:2719–2740. https://doi.org/10.1021/jm901137j
286. Metz JT, Huth JR, Hajduk PJ (2007) Enhancement of chemical rules for predicting
compound reactivity towards protein thiol groups. J Comput Aided Mol Des 21:139–144.
https://doi.org/10.1007/s10822-007-9109-z
In Silico Structure-Based Prediction of Receptor–Ligand Binding …
175