Pharmaceutical chemistry deals with the process of isolating organic compounds from natural sources or chemically synthesizing them in order to explore potential drugs. Drugs are small molecules, used to prevent or treat various diseases. Of several lead molecules, only few of them reach clinical trial phases and emerge as effective drugs, whereas the majority will be eliminated at different stages. On the other hand, due to the lack of proper identification of their pharmacokinetic properties and biological potential, many small molecules fail to reach this stage. This could be because of the fact that it is either time consuming and costly or there is full of uncertainty due to lack of analyses that are necessary for the confirmation. In the post-genomic era, computational methods have been implemented in almost all stages of drug research and development owing to the drastic increase in the available knowledge about small molecules and the target biomacromolecule. This includes identifying the suitable and specific targets for drug candidates, lead discovery, lead optimization and ultimately preclinical phases. In this context, numerous websites have become highly valuable and influence the drug development and discovery process. Here, we have attempted to bring together some of the online computational approaches and tools that are available to facilitate research efforts in the field of drug discovery and drug design. The output information from these tools is extremely helpful in selecting and deciding about the future direction or specific path needed to be followed by the researchers. These computational methods are indeed help to focus the intended research in the right direction. As detailed in this review, the information provided about the servers and methods should be useful throughout the process of screening of synthesized or chemical database originated small molecules to find the appropriate targets along with the active sites without depending on any commercial tools or time-consuming and costly assays. It should however be remembered that the bioinformatics-based prediction cannot completely replace the wet lab data of chemical compounds or specific assays.