Fingerprints are useful cheminformatics tools because they can be designed to focus on chemical features or interactions of interest, says Chris Williams, Ph.D., principal scientist, Chemical Computing Group (www.chemcorp.com). Analysis tools developed for one fingerprint, such as similarity searching and clustering, are usually applicable to other fingerprints. Fingerprints also allow the use of convenient mechanisms for combining multiple results into consensus predictions that leverage the strengths of the individual methods.
At the center of this Montreal-based companys technology is MOE, a fully integrated suite of computational chemistry software that includes molecular modeling, QSAR, protein-ligand docking, and protein bioinformatics applications. A number of fingerprint systems, including 2-, 3- and 4-point pharmacophore fingerprints in 2-D or 3-D and MACCS keys, are also supported. MOE applications are written in Scientific Vector Language (SVL), a high-level chemistry-aware programming language, designed for computational chemistry. SVL source code, provided with the MOE distribution, is easy to modify and can be used to create new applications, according to the company.
Since the SVL source code provided in the distribution can be easily customized, it was used to create custom fingerprints and novel fingerprint analysis approaches, states Dr. Williams. Information from different fingerprints can be combined by mapping bit importance values back onto the fragments used to construct the bits. The resulting fragments scores can reflect either one or multiple fingerprinting systems and can be used to visualize important pharmacophore features and to score molecules in virtual screening.
Cheminformatics is part of the lead discovery process, says Jeremy Jenkins, research investigator, lead discovery center at the Novartis Institutes for Biomedical Research (www.nibr.novartis.com). Mining HTS data is one application, and another is in silico lead discovery using 2-D and 3-D methods.
Novartis in silico chemogenetics effort, based in Cambridge, MA, is concentrated on exploiting chemical approaches to target identification. Our main focus is that we are building statistical models for large numbers of targets. This is a new area, using in silico chemogenomics as a predictive tool for biologists, said Jenkins. We can link targets with chemical structures and this data can be mined to predict ligand-target pairings.
Jenkins group de-orphans targets and phenotypically interesting molecules by using chemical fingerprinting. We work with more than 1,000 different targets then, prioritize which targets are likely to bind with what molecules, he explains.
Chemical genetics is not just an academic tool; its a really good way to discover lead targets when combined with cheminformatics, Jenkins notes.
Other companies are developing ways to screen small molecules using genomics-based technologies to better understand their action on biological systems. We are not specifically developing cheminformatics tools, says Larry Mertz, vp of R&D and product management at Gene Logic (www.genelogic.com), but we are developing a genomics-based platform so pharmaceutical and biotech customers can screen panels of small molecules to predict human toxicity. It will better enable them, at the stage of lead optimization, to rank and prioritize small molecules for further development.
Toxicogenomic profiling can accelerate the pace of uncovering critical information before making significant investments into relatively more expensive and lengthy nonclinical studies. The use of microarrays to examine gene-expression profiles, derived from mammalian cells and tissues treated with small molecules when benchmarked to large reference data sets, helps establish accurate predictive methods that identify potential toxic liabilities, even in the absence of overt injury.
In addition, Gene Logics ToxExpress Program reportedly helps to streamline, focus, and augment subsequent classical studies through specialized applications that support key research areas of predictive, investigative, and mechanistic toxicology, as well as safety biomarker discovery.
Gene Logic has seven years of experience in creating predictive algorithms to determine toxicity of compounds in both human and rat models. Its latest project is the creation of a genomics-based, 96-well hepatocyte screening platform that will provide a lower-cost toxicogenomic screening assay.