Computer-aided drug design

1. Computer-Aided Drug Discovery Overview Computer-aided drug design (CADD) is a widely used technology using computational tools and resources for the storage, management, analysis and modeling of compounds. It relies on digital repositories for study of designing compounds with physicochemical characteristics, predicting whether a given molecule will be combined with the target, and if so how strongly. Computer based methods can help us to search new hits in drug discovery, screen many irrelevant compounds at the same time and study the structure-activity relationship of drug molecules.

2. The advantages of CADD The traditional strategies for discovering new drug usually begin with taking a lead structure, and then develop a chemical program to find an analog molecule which can exhibit the desired biological properties. The process often involved a long cycle and a large number of experiments, in which medical chemist utilizing their experience and intuition to ultimately select a candidate for further development. The whole process is laborious, expensive and inelegant. Contrary to traditional drug design methods, CADD has been applied as a highly effective tool for systematic assessment of potential lead candidates before they are synthesized and tested. In this way, it saves time as well as cost in drug discovery. Our Capabilities: BOC Sciences is a leader in the field of computer-aided drug design, our complete services include: Compound Docking

3. One goal of our CADD service is to predict the binding interactions of molecules. Molecule docking has become one the most useful drug design approach, in which the 3-D structure of a binding site can be analyzed and leads to a comprehensive investigation of the interactions between drug and receptor. Docking study plays an important role in the QSAR methods and homology modeling, so it is useful in the structure-based drug design. Virtual Screening Virtual screening, a commonly used computational technique in the field of drug discovery, is often applied to identify the most valuable structures, which can bind to a drug target, in a wide array of small molecules. BOC Sciences mainly focus on the designing and optimizing targeted combinatorial libraries. Additionally, our experts is able to enrich those libraries of available compounds from in-house compound repositories or vendor offerings. Activity Prediction Activity prediction is an important part in our CADD services, in order to predict the selectivity and affinity of compounds against targets. In this service, a molecule may be expanded to a wide range of conformers, and then their affinities to targets will be analyzed by our comprehensive evaluation system. QSAR Prediction As an integral part of rational drug design, Quantitative Structure Activity Relationships (QSAR) has been developed to quantitatively analysis the relationships between the chemical structural-related properties and biological activity or target property) of compounds being studied. Moreover, QSAR is also recommended as a useful tool to determine the parameters responsible for biological response which have an essential effect on the optimization of lead compound.

4. Physicochemical Prediction Physicochemical properties are key factors in controlling the interactions of xenobiotics with living organisms. Computational approaches to toxicity prediction generally rely to a very large extent on the physicochemical properties of the query compounds. Consequently the reliable silico methods are important for the rapid calculation of physicochemical properties. https://www.bocsci.com/solutions/computational-chemistry.htm