1. Machine Learning techniques has been used in virtual screening of compounds as one of the promising and effective method in assessing a large of compounds based on physico-chemical properties. The availability of high-throughput screening data is used for making computational model which can be used for predicting novel compounds. Machine learning involves the use of classifiers (Algorithms for Classification) such as Random forest, Bayesian classifiers etc., which are used to train the model. This kind of work is categorized as Supervised learning approach where based on the Training data MODEL is developed.
2. Soft computing in Drug discovery: Neural networks an unsupervised method of learning is applied for the analysis and modeling of non-linear relationships between molecular structures and pharmacological activity. It is used in analyzing the complex relationship based on linear and radial molecular descriptors.
3.Rapid Overlay of structure: ROCS is a product from Open-eye which uses a shape based methods to superimpose the structure. ROCS is a fast shape comparison application, based on the idea that molecules have similar shape if their volumes overlay well and any volume mismatch is a measure of dissimilarity. It uses a smooth Gaussian function to represent the molecular volume , so it is possible to routinely minimize to the best global match.
4. Docking: Molecular docking can be thought of as a problem of “lock-and-key”, where one is interested in finding the correct relative orientation of the “key” which will open up the “lock” (where on the surface of the lock is the key hole, which direction to turn the key after it is inserted, etc.,). Here, the protein can be thought of as the “lock” and the ligand can be thought of as a “key”. Molecular docking may be defined as an optimization problem, which would describe the “best-fit” orientation of a ligand that binds to a particular protein of interest. However, since both the ligand and the protein are flexible, a “hand-in-glove” analogy is more appropriate than “lock-and-key”. During the course of the process, the ligand and the protein adjust their conformation to achieve an overall “best-fit” and this kind of conformational adjustments resulting in the overall binding is referred to as “induced-fit”.