Abstract
The comprehensive information of small molecules and their biological activities in the PubChem database allows chemoinformatic researchers to access and make use of large-scale biological activity data to improve the precision of drug profiling. A Quantitative Structure-Activity Relationship approach, for classification, was used for the prediction of active/inactive compounds relatively to overall biological activity, antitumor and antibiotic activities using a data set of 1804 compounds from PubChem. Using the best classification models for antibiotic and antitumor activities a data set of marine and microbial natural products from the AntiMarin database were screened - 57 and 16 new lead compounds for antibiotic and antitumor drug design were proposed, respectively. All compounds proposed by our approach are classified as non-antibiotic and non-antitumor compounds in the AntiMarin database. Recently several of the lead-like compounds proposed by us were reported as being active in the literature.
Original language | English |
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Pages (from-to) | 757-778 |
Number of pages | 22 |
Journal | Marine Drugs |
Volume | 12 |
Issue number | 2 |
DOIs | |
Publication status | Published - Feb 2014 |
Keywords
- Antibiotic
- Antitumor
- Drug discovery
- Marine natural products
- Microbial natural products
- Quantitative structure-activity relationships (QSAR)