In database mining

A variety of methods have been developed by mathematicians and computer scientists to address this task, which has become known as data mining (see Chapter 9, Section 9.8). Fayyad defined and described the term data mining as the nontrivial extraction of impHcit, previously unknown and potentially useful information from data, or the search for relationships and global patterns that exist in databases [16]. In order to extract information from huge quantities of data and to gain knowledge from this information, the analysis and exploration have to be performed by automatic or semi-automatic methods. Methods applicable for data analysis are presented in Chapter 9. 

Many reports have been published that address various aspects of diversity analysis in the context of chemical library design and database mining [77-84]. 

The are several clearance and toxicological aspects that have to be considered in the drug discovery process such as metabolic stability, enzyme selectivity, CYP inhibition and type of inhibition. Among these factors, the prediction of the site of metabolism has become one of the most successful parameters for prediction. The knowledge of the site of metabolism enhances the opportunity to chemically modify the molecule to improve the metabolic stability. There are several approaches based on database mining, chemical reactivity, protein interaction or both that have been developed for the prediction of this property, with different degree of success and applicability. 

The advantage of using QSAR models for database mining is that it affords not only the compounds selection but also quantitative prediction of their activity. For illustration, we shall discuss our recent success in developing validated predictive models of anticonvulsants [51] and their application to the discovery of novel potent compounds by the means of database mining [10]. 

Fig. 16.5 Computer-aided drug discovery workflow based on combination of QSAR modeling and consensus database mining as applied to the discovery of novel anticonvulsants [10]. The workflow emphasizes the importance of model validation and applicability domain in ensuring high hit rates as a result of database mining with predictive QSAR models.

Teopsha, a., Cho, S.)., Zheng, W. New Tricks for an Old Dog development and application of novel QSAR methods for rational design of combinatorial chemical libraries and database mining. In Rational Drug Design Novel Methodology and Practical Applications, ACS Symposium Series Vol. 719, Paeeill,... 

Once the process criteria have been identified various strategies can be followed to obtain the biocatalyst for the desired biotiansformation. Most commonly, first a literature, patent and electronic media search is performed ( database mining ) in order to find established biocatalysts that are known to catalyze the desired reaction or that catalyze a reaction that is similar to it (see 5.3.2). Databases that are becoming... 

Enrichment based methods. These focus on recovering active molecules from a test database in which a small number of known actives have been hidden in a large database of randomly selected compounds. Database mining and the utilization of receiver operating characteristic (ROC) curves [43] can be included in this category. 

Bera TK, Lee S, Salvatore G, Lee B, Pastan I. MRP8, a new member of ABC transporter superfamily, identified by EST database mining and gene prediction program, is higly expressed in breast cancer. Mol Med 2001 7 509-516. 

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