QSAR Prediction

1. QSAR Prediction Quantitative structure–activity relationship (QSAR) is a method to build computational models, which attempts to find a significant correlation in statistics between structure and function. In drug design, structure refers to the molecular property or descriptor, their substituent or the interaction energy field, which corresponds to a biochemical experiment endpoint such as activity, binding affinity, toxicity or rate constant, and the chemometrics methods include multiple linear regression, partial least squares, principal component analysis, and so on. QSAR has been developed for more than one hundred years as valuable tools for prediction, especially in the design of pharmaceuticals and agrochemicals. The method has been developed from the one- dimensional or two-dimensional linear free-energy relations of Hansch and Free-Wilson to sixth-dimensional QSAR of Vedani. For example, biological activity can be quantitatively expressed as the concentration of a substance, and if physicochemical properties or structures are expressed by numbers, the mathematical expression can then be used to predict the modeled response of chemical structures. BOC Sciences has scientists with a wealth of professional knowledge in computational chemistry, which offers QSAR prediction service to support our customers with the compliance process. There are mainly two methods provided by BOC Sciences. 2D QSAR

2. 2D QSAR is a method of drug design based on the structural properties of molecules as parameter of regression analysis for molecular physiological activity, and establishment of correlation model between chemical structure and physiological activity. It is a powerful tool to explain the relationship between chemical structure and experimental observation. The key elements of 2D QSAR are the numerical descriptor used to convert chemical structures into mathematical variables, the quality of the observed data and the statistical method used to derive the relationship between observations and descriptors. In clinical trials, 2D QSAR model is often used in the optimization of a range of chemicals, and it can become a routine part of medicinal chemistry design workflow when scientists have ability to build up their own hypothesis and know the underlying model and give a reasonable output. As more and more knowledge is acquired in this field, 2D style will become an acceptable alternative to the experimental observation. 3D QSAR 3D QSAR is a method containing drug molecular 3D structure information, which indirectly reflects the noncovalent interaction between drug molecules and macromolecules in the process. Compared with 2D QSAR, 3D QSAR has more explicit physical meaning, and more abundant information, and it emerges as one of the main methods for rational drug design based on mechanism. 3D QSAR is a natural extension to the classic Hansch and Free Wilson methods, which utilizes the 3D properties of ligands to predict the biological activities of drug molecules. It is also an important tool for the prediction in the field of pharmaceuticals and agrochemicals. Although the experimental error factors involved in new drug development can not be ignored completely, 3D QSAR will undoubtedly reduce the number of synthetic compounds by selecting the most promising candidates. BOC Sciences provides QSAR prediction service to predict the physicochemical, biological and environmental fate properties of compounds from their chemical structure in a qualitative or quantitative

3. manner. If you have any questions in QSAR prediction, please contact us without hesitation.