Property distribution of drug-related chemical databases

被引:507
作者
Oprea, TI [1 ]
机构
[1] Astra Hassle AB, Med Chem, S-43183 Molndal, Sweden
关键词
combinatorial chemistry; computer chemistry; database filtering; drug-likeness; drug research; hydrogen bonds; property distribution; 'rule of 5' test;
D O I
10.1023/A:1008130001697
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
The process of compound selection and prioritization is crucial for both combinatorial chemistry (CBC) and high throughput screening (HTS). Compound libraries have to be screened for unwanted chemical structures, as well as for unwanted chemical properties. Property extrema can be eliminated by using property filters, in accordance with their actual distribution. Property distribution was examined in the following compound databases: MACCS-II Drug Data Report (MDDR), Current Patents Fast-alert, Comprehensive Medicinal Chemistry, Physician Desk Reference, New Chemical Entities, and the Available Chemical Directory (ACD). The ACDF and MDDRF subsets were created by removing reactive functionalities from the ACD and MDDR databases, respectively. The ACDF subset was further filtered by keeping only molecules with a 'drug-like' score [Ajay et al., J. Med. Chem., 41 (1998) 3314; Sadowski and Kubinyi, J. Med. Chem., 41 (1998) 3325] below 0.8. The following properties were examined: molecular weight (MW), the calculated octanol/water partition coefficient (CLOGP), the number of rotatable (RTB) and rigid bonds (RGB), the number of rings (RNG), and the number of hydrogen bond donors (HDO) and acceptors (HAC). Of these, MW and CLOGP follow a Gaussian distribution, whereas all other descriptors have an asymmetric (truncated Gaussian) distribution. Four out of five compounds in ACDF and MDDRF pass the 'rule of 5' test, a probability scheme that estimates oral absorption proposed by Lipinski et al. [Adv. Drug Deliv. Rev., 23 (1997) 3]. Because property distributions of HDO, HAC, MW and CLOGP (used in the 'rule of 5' test) do not differ significantly between these datasets, the 'rule of 5' does not distinguish 'drugs' from 'nondrugs'. Therefore, Pareto analyses were performed to examine skewed distributions in all compound collections. Seventy percent of the `drug-like' compounds were found between the following limits: 0 less than or equal to HDO less than or equal to 2, 2 less than or equal to HAC less than or equal to 9, 2 less than or equal to RTB less than or equal to 8, and 1 less than or equal to RNG less than or equal to 4, respectively. The number of launched drugs in MDDR having 0 less than or equal to HDO less than or equal to 2 is 4.8 times higher than the number of drugs having 3 less than or equal to HDO less than or equal to 5. Skewed distributions can be exploited to focus on the 'drug-like space': 62.68% of ACDF ('nondrug-like') compounds have 0 less than or equal to RNG less than or equal to 2, and RGB less than or equal to 17, while 28.88% of ACDF compounds have 3 less than or equal to RNG less than or equal to 13, and 18 less than or equal to RGB less than or equal to 56. By contrast, 61.22% of MDDRF compounds have RNG greater than or equal to 3, and RGB greater than or equal to 18, and only 24.73% of MDDRF compounds have 0 less than or equal to RNG less than or equal to 2 rings, and RGB less than or equal to 17. The probability of identifying 'drug-like' structures increases with molecular complexity.
引用
收藏
页码:251 / 264
页数:14
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