In medicinal chemistry, the relationship between molecular structure of a compound and its biological activity is referred to as Structure Activity Relationship (SAR). Medicinal chemists modify biomedical molecules by inserting new chemical groups into the compound and test those modifications for their biological effects. Determining and identifying SARs is key to many aspects of the drug discovery process, ranging from hit identification to lead optimization.
Although information on millions of compounds and their bio-activities e.g. reaction ability, solubility, target activity etc., is freely available to the public, it is very challenging to infer a meaningful and novel SAR from that information. The underlying problem in here is the un-structured and heterogeneous nature of these datasets contributed by the scientific & research community in journals, scientific articles, patents, regulatory documents and various secondary sources. Owing to the increasing structural diversity among hit compounds and their potency distribution, it is becoming a challenge to analyze the SAR information. If these relationships are properly extracted, associated and analyzed, they provide valuable information that would support drug discovery and development. To this end, there has been an increasing need and interest in mining and structuring SAR information from bioactivity data available in the public domain.
Excelra, a leading global biopharma data and analytics company, has responded to this pertinent need by developing a knowledge repository, Global Online Structure Activity Relationship Database (GOSTAR), which provides a 360-degree view of millions of compounds linking their chemical structure to the biological, pharmacological and therapeutic information. GOSTAR contains high-quality, manually annotated and very well-structured SAR data captured from various primary sources (patents and top journals of medicinal chemistry) and secondary sources (conference meetings & abstracts, company drug development pipelines, company annual reports, clinical registries and drug approval reports).
The main objective for creating GOSTAR is to assist medicinal chemists, computational chemists and cheminformaticians in their quest for identifying potential small molecules that have decent biological effect and could be of a specific therapeutic use. GOSTAR enables users to quickly visualize, explore, analyze and evaluate SAR data based on their project requirements. The users can explore various SAR associations by searching various identifiers like drug names, chemical structures, bibliography, compound development stage and activity endpoints.
Better understanding of SAR data will enable the users to take correct decisions in exploring the chemical space while designing a drug.
Following are the applications of GOSTAR:
Currently, there are hundreds and thousands of chemical classes, and it often becomes daunting task to identify potential candidates for therapeutic use. In such cases, using knowledge repositories like GOSTAR, we can rapidly characterize data points that can help to efficiently capture and encode specific SAR. Below are the key features that showcase why GOSTAR is the ideal and simplistic solution for the complex task of gathering SAR data.
Try GOSTAR today. To schedule a free demo, write to us at: marketing@excelra.com
For more information on GOSTAR, visit: https://www.gostardb.com/gostar/
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