Computational Methods for Analysis of High-Throughput Screening Data

Authors: Balakin, Konstantin V.; Savchuk, Nikolay P.

Source: Current Computer - Aided Drug Design, Volume 2, Number 1, March 2006 , pp. 1-19(19)

Publisher: Bentham Science Publishers

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Abstract:

The huge data sets produced by high-throughput screening (HTS) technologies have created a tremendous challenge for the drug discovery industry. Rapid processing of HTS data and identification of hits are essential in order to accelerate the discovery of quality lead compounds. In addition to finding active compounds among those screened, it is useful to identify the molecular features associated with the activity. To do this, one needs to analyze the initial HTS data to find quantitative relationships between biological activity and specific compound features. There are several challenges in the development of biological activity models from HTS data. First, the hit compounds belonging to different chemotypes may be acting via different mechanisms. Second, many HTS data sets have substantial measurement errors. Third, despite of large exploratory sets which may include thousands of compounds, HTS programs usually provide relatively few active compounds. Powerful and flexible data management systems are key to addressing these challenges. In this review, we elucidate the modern approaches to processing HTS data and developing biological activity models. In our opinion, such systems provide a functional interface between real and virtual screening programs. The synergy of these powerful technologies will increase the efficiency with which high quality clinical candidates are produced, thus providing a great benefit to the industry.

Keywords: High-throughput screening; data mining; quality control; machine learning; visualization; chemogenomics

Document Type: Research article

Affiliations: 1: ChemDiv, Inc. 11558 Sorrento Valley Rd., Ste. 5, San Diego, CA 92121, USA.

Publication date: 2006-03-01

More about this publication?

Current Computer-Aided Drug Design aims to publish all the latest developments in drug design based on computational techniques. The field of computer-aided drug design has had extensive impact in the area of drug design. Current Computer-Aided Drug Design is an essential journal for all medicinal chemists who wish to be kept informed and up-to-date with all the latest and important developments in computer-aided methodologies and their applications in drug discovery. Each issue contains a series of timely, in-depth reviews written by leaders in the field, covering a range of computational techniques for drug design, screening, ADME studies, etc., providing excellent rationales for drug development.

Computational Methods for Analysis of High-Throughput Screening Data

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