In silico docking and drug design of herbal ligands for anticancer property

Abstract

In silico approaches have been widely recognized to be useful for drug discovery. Here, we consider the significance of available databases of medicinal plants and chemo and bioinformatics tools for in silico drug discovery beyond the traditional use of medicines. Whereas computational methods for molecular design are well established in medicinal chemistry research, their application in the field of natural products is still not exhaustively explored. The challenge is which selection criteria and/or multiple filtering tools to apply for a target-oriented isolation of potentially. The amount of available data on the biological activity of the investigated compounds (including herbal medicines) and the number of target macromolecules related to their therapeutic effects increase every year. At the same time, the pool of data on compositions of medicinal plants has also increased. Therefore, the need for use of in silico methods to determine the biological activity of medicinal plants is obvious. In-silico studies are done to identify the exact target of the drug. Which finds a drug for the particular binding site and final stage animal testing can be done for obtaining a conform result. Specific software on a computer allows researchers to analyze enormous data without actually conducting a large number of experiments. It helps to give the existing information to model disease pathway and identifies precise targets of the selected drugs. Later stage in vivo and in vitro studies can be done for obtaining the confirmatory result. Introduction Natural products have been used in folk medicine for thousands of years. One-third of the indian population and more than 80% of the population uses herbal medicinal products to promote health and to treat common illnesses such as colds, inflammation, heart diseases, diabetes and central nervous system disorders. It is believed that plant and its chemical constituents interacting with human biological system by altering environmental stresses and adapt to these changes [1]. This type of adaptation is accompanied by unusual phytochemical diversity. These data confirm the assertion by Dhawan [2] that the study of plants, based on their use in traditional systems of medicine, is a viable and cost-effective strategy for the development of new drugs [3]. Because there are several thousand pharmacological targets and because most natural compounds exhibit pleiotropic effects by interacting with different targets, computational methods are the methods of choice in drug discovery based on natural products [4]. The use of chemo-and bioinformatics methods for the exploration of their pleiotropic pharmacological potential beyond the traditional uses may be possible with the availability of medicinal plant databases including data on chemical structures and therapeutic uses of phytoconstituents identified over the years from medicinal plants.