SAR Database

The Danish (Q)SAR database is a repository of estimates from over 70 [28] (Q)SAR models for 166,072 chemicals. The (Q)SAR models encompass endpoints for physicochemical properties, fate, ecotoxicity, absorption, metabolism, and toxicity... 

Danish Environmental Protection Agency (2005) User Manual for the Internet Version of the Danish (Q)SAR Database. http //130.226.165.14/User Manual Danish Database.pdf. 

In addition to Target SAR databases, other databases contain information on ADME and Toxicity parameters, information on proteins and signaling systems involved in the pathways specific genes/proteins, such as Sequence information, SNP details and their functions. Information is derived from public domain data as well as patents and scientific journal articles. 

Establish an SAR database through the use of reliable quantitative measurements of the target property and a preferred set of molecular descriptors. 

Danish (Q) SAR Database Database of Danish Agency for Environmental Protection includes more than 70 QSAR models and the information about biological effects for 166,072 chemical compounds http //qsar.food.dtu.dk/... 

In the process of clustering compounds to try to form series, and examining all of the data for the compound in a cluster, it may become apparent that there is an insufficient number of compounds, or enough range in the data to reach a decision as to whether a cluster of compounds is a series with demonstrated SAR. This problem can be addressed through searching of databases for additional related compounds or limited synthesis to provide the critical compounds. 

A method to identify common scaffolds in databases by scaffold detection, alignment, and assignment has been reported [58]. This method could be used to create meaningful SAR analyses of large medicinal chemistry databases. 

IUCLID International Chemical Information Database SAR SDS Structure-activity relationships Safety data sheet... 

Among the large number of existing lipophilicity parameters [31], the descriptor frequently estimated by in silica methods is the partition coefficient of a solute between 1-octanol and water, expressed as log Poet [32]. However, lipophilicity determination in different solvent systems, such as alkane/water system, proved its utility in (Q)SAR studies and therefore some predictive methods also emerged in this field. Many publically available databases include numerous experimental values collected through the literature the quality of the experimental data represents the cornerstone of most of the models developed to predict lipophilicity. 

This is the realm of in silica simulations, text mining, database management, classic in silica qualitative SAR modeling and physiology modeling. 

Developing a system capable of collecting multivariate SAR data and exploiting the data to produce predictive SAR models is a major systems integration task. However, recent advances in computers, operating systems, and computational chemical tools now enables the implementation of a system that can track compounds, store chemical property data in a comprehensive relational database, and operate on virtual libraries in an iterative fashion to develop SAR models and refine chemical properties [28]. 

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