Computational assisted designing and test of drug candidate by self organizing molecular analysis approach using statistical measures an application of Cheminformatics

Abstract

Computational techniques have had been most extensively used in experimental research for decades. These computational models are often used in sciences for the determination of attributes of molecules. Mostly these techniques are used for describing the theories given by researchers. Now days, cheminformatics is used to evaluate and process huge quantities of data stored in the database. Many scientific experiments generate a considerable quantity of data that can be tremendously complicated to practice without the use of information technology. Several procedures in cheminformatics permit researchers to rapidly arrange and examine data in order to generate multifaceted and comprehensive computerized models from the data collected from experiments. Comparative molecular field analysis (CoMFA) has been innovative prototype tool of Cheminformatics for three-dimensional drug design. Self-Organizing Molecular Field Analysis (SoMFA) is an innovative and fresh tool of Cheminformatics for design of new drug. The investigation of properties of compounds is one of the most significant and demanding assignment in design of drug. Consequently, the analysis of the existing data set for determination these properties is a decisive task. There are various techniques and procedures available for describing individual molecules and their connection between molecules for designing of drugs in order to exemplify complete set of compounds. Data mining techniques are used to analyze the large amount of available data to extract useful information in order to understand the relationships within chemical compounds to find out the hidden and required information for decision making. The various data mining techniques can be used to analyze chemical data sets for extracting molecular patterns, their relationship, all primary and secondary relevant information for discovery and design of drug . These techniques of data mining also helpful for construction of statistical model known as QSAR Model which is useful for testing of reliabilit