Quantitative Structural Activity Relationship (QSAR) is frequently used methodology for ligand-similarity based lead identification which quantitatively correlates descriptors with properties (2D and 3D QSAR based on the dimensions of properties used) like physicochemical, biological, toxicity, etc for a set of similar compounds. RASA’s QSAR modelling services will help both computational and experimental chemists to develop reliable QSAR models. These QSAR models generated from our QSAR Modelling services can optimally exploit the experimental data to guide future studies. In addition, our QSAR Modelling services encourage the use of high quality validated QSARs to provide reliable support for experimental study design and regulates decision making.
Our QSAR modelling services can be widely applied in academy, industry, and government institutions around the world. It relates chemoinformatics with biology. Recent observations suggest that the structure-based methods & value of statistically-based QSAR approaches help to guide lead optimization. These are starting to be appreciatively reconsidered by leaders of several larger CADD groups. QSAR modelling finds broad application for assessing potential impacts of chemicals, materials, and nano-materials on human health and ecological systems.
An area of active 3D QSAR expansion is in the use of predictive models for regulatory purposes by government agencies, where a still growing number of specialized regulatory tools and databases are being developed and validated.
As with any scientific discipline, there have been some voices in the community questioning the viability and our QSAR modelling services tries to build newer biologically-based models using HTS data. Also, developing trends on minimizing animal use in biomedical research place additional focus on QSAR as a source of alternative predictors of in vivo effects in both animals and humans.