Any disease is generally caused to humans because of biological disorders. These diseases may be an infection from external factors due to deficiency in chemical components, physiological changes or heredity.

The objective is to find the right drug for curable and chronic diseases. The drug is a combination of various chemical compounds that suit biological deformation inside the human metabolic system. Many Pharmaceutical companies worldwide have been trying their best to invest in rational drug design processes to avail of a suitable drug in the market.

The investment is typically in terms of chemicals used and human resources. The research and development efforts are sometimes not incurred because the clinical trial and error method of preparing a newly designed drug takes more time and money. The drug design is tried with a combination of chemical components in many possible ways and then tested through a clinical trial. It is also frustrating not to get the right drug after spending so much time. In this context, the use of computer-aided tools has been fruitful in finding the best chemical compounds and their properties that can be tested in a biological lab by reducing the chemical cost and time of resource engagement.

The Computer-Aided Drug Design uses the chemical databases which contain numerous atoms and molecules and their combinatory properties. It uses structural prediction of molecules which is easier for the researchers and biochemical labs to predict the best chemical compound that can be used for drug discovery. The CADD is a Molecular Dynamic simulation software tool.

Currently, there are two types of approaches used by CADD. The first one is Structure-Based Drug Design (SBDD) which uses 3-dimensional structure prediction of protein to identify key biological functions responsible for particular diseases. The second one is Ligand-Based Drug Design (LBDD) which used antibiotic ligand for judging biological reactions depend on the method where one molecule or atom that joins with another to create relations.

Various molecular simulation tools that supported drug design are CHARMM, AMBER, NAMD, GROMACS, and OpenMM. These programs run on a multicore central processing unit (CPU) and recently being operated as well on graphics processing units (GPU) to visualize as video simulation. The 3D structure of the biological molecules is obtained from the Protein Data Bank (PDB) which is funded by the National Science Foundation, USA. The online web-server called as SWISS-MODEL facilitated various 3D structures as well. The database screening techniques encapsulate the appropriate hit to particular chemical molecule. The databases used in various CADD are part of Cheminformatics and Bioinformatics knowledge bases. These knowledge bases help in identifying and producing diverse library which can cluster only drug-like compounds.

The in silico representation of chemical structures facilitates drug design by implementing Chemical Markup Language format which often stores large chemical databases. Therefore, computational approaches such as data mining techniques, structural prediction, and combinatorial statistics are helpful to interpret and suggest experiments to expedite the drug discovery and design process. 

Pharmaceutical and Biochemical industries are now mobilizing the key potential area called pharmacology looking at CADD services. Some of the prominent market leaders who emphasize the end-to-end CADD services are Allesh Biosciences Labs, Comp Chem Solutions, Evotec, Gfree Bio, GVK Biosciences, Quantitative Medicine, etc. No doubt CADD solutions and services have been significantly reduced the cost and time spent in early-stage drug discovery, which is leading the way to find critical drugs for life-threating diseases in less consuming time.