* Please be kindly noted that our services and products can only be used for research to organizations or companies and not intended for any clinical or individuals.

3D-QSAR has emerged as a natural extension to the classical Hansch and Free-Wilson approaches, which has served as a valuable predictive tool in the design of pharmaceuticals. BOC Sciences provides tailored 3D-QSAR model building services to accelerate your drug discovery process.


Many scientific methods have been applied to drug design, and one of the most popular methods is computer-aided drug design (CADD). The quantitative structure-activity relationship (QSAR) modeling was used to explore the relationship between the chemical structure and biological activity of a given group of small molecules. As an extension of the classical QSAR method initiated by Hansch and Free-Wilson, 3D-QSAR makes use of the three-dimensional properties of ligands and robust stoichiometric techniques such as PLS, G/PLS and ANN to predict their biological activities. They are valuable prediction tools in the design of drugs. Although the trial and error factors involved in the development of new drugs cannot be completely ignored, QSAR will certainly reduce the number of compounds to be synthesized by promoting the selection of the most promising candidates.

Our Services

Our 3D-QSAR analysis is a valuable pharmaceutical chemical tool that enables researchers to effectively perform force field calculations that require a three-dimensional structure of the training set (to measure known activities through experiments). More and more information from structural biology will provide valuable feedback on the assumptions that form the basis of the 3D-QSAR method.

  • Biological data analysis
  • Optimization of 3D structure of the biomolecules
  • Determination of bioactive conformations of biomolecules
  • Calculation of molecular interaction energy fields
  • 3D QSAR model generation and validation

Our Advantages

  • Automatic 3D-QSAR workflow
  • Experienced scientists and technicians for modeling
  • Improve the biological activity of the existing leading compounds
  • Predicting the activity of unknown compounds
  • Technical advice on data selection for further processing, such as docking analysis


  1. Fan, F., Warshaviak, D. T., Hamadeh, H. K., & Dunn, R. T. (2019). The integration of pharmacophore-based 3D QSAR modeling and virtual screening in safety profiling: A case study to identify antagonistic activities against adenosine receptor, A2A, using 1,897 known drugs. PloS one, 14(1).
  2. Verma, J., Khedkar, V. M., & Coutinho, E. C. (2010). 3D-QSAR in drug design-a review. Current topics in medicinal chemistry, 10(1), 95-115.

* PROTAC® is a registered trademark of Arvinas Operations, Inc., and is used under license.

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