A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases.

By A. Ghose, and Vellarkad N. Viswanadhan, J. Wendoloski. 1999

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The blood-brain barrier: Bottleneck in brain drug development (2005, background): “A review of the Comprehensive Medicinal Chemistry database shows that, of more than 7000 small-molecule drugs, only 5% treat the CNS, and these drugs only treat four disorders: depression, schizophrenia, chronic pain, and epilepsy.(6,7) There are few effective small- or large-molecule drugs for the ”
A data-driven approach to predicting successes and failures of clinical trials (2016, methodology): “Modiﬁed rule sets have since been proposed, such as Veber’s rule (Veber et al., 2002) and Ghose’s rule (Ghose et al., 1999), to include more properties associated with bioavailability, such as polar surface area, and to improve upon the concept proposed by Lipinski.”
Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets (2022, background): “…(5) LogP represents the octanol-water partition coefficient, and in general logP values should be between -0.4 and 5.6 to be good drug candidates (Ghose et al., 1998); (6) Lipinski measures how many rules the drug follow the Lipinski’s rule of five (Lipinski et al., 1997; Veber et al., 2002),…”
Quantifying the chemical beauty of drugs. (2012, background): “Eight widely used molecular properties were selected on the basis of published precedence for their relevance in determining drug-likenes”
SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules (2017, unknown): “The Ghose (Amgen), Veber (GSK), Egan (Pharmacia) and Muegge (Bayer) methods were adapted from refs 58–61, respectively.”
Relationships between drug activity in NCI preclinical in vitro and in vivo models and early clinical trials (2001, background): “Compounds in low MW ranges (16 480) are generally considered to be more ‘drug-like’ than thos © 2001 Cancer Research Campaign le l, he d. l ich al F to in higher ranges (Ghose et al, 1999).”
Discovery of a structural class of antibiotics with explainable deep learning (2023, background): “…rationale group may represent an active structural class, and compounds 1 and 2 simultaneously satisfy the Lipinski’s rule of five 32 and the Ghose criteria 33 for ‘druglikeness’, suggesting favourable oral bioavailability and druglike properties for further development (Supplementary Table 3).”