Background:
In this fast-growing era, high throughput data is now being so easily accessed by getting transformed into datasets which store the information. Such information is valuable to optimize the hypothesis and drug design
via computer-aided drug design (CADD). Nowadays, we can explore the role of CADD in various disciplines like Nanotechnology, Biochemistry, Medical Sciences, Molecular Biology, etc.
Methods:
We searched the valuable literature using a pertinent database with given keywords like computer-aided drug
design, antidiabetic, drug design, etc. We retrieved all valuable articles which are recent and discussing the role of computation in the designing of antidiabetic agents.
Results:
To facilitate the drug discovery process, the computational approach has set landmarks in the whole pipeline for
drug discovery from target identification and mechanism of action to the identification of leads and drug candidates. Along
with this, there is a determined endeavor to describe the significance of in-silico studies in predicting the absorption, distribution, metabolism, excretion, and toxicity profile. Thus, globally CADD is accepted with a variety of tools for studying
QSAR, virtual screening, protein structure prediction, quantum chemistry, material design, physical and biological property
prediction.
Conclusion:
Computer-assisted tools are used as the drug discovery tool in the area of different diseases, and here we
reviewed the collaborative aspects of information technologies and chemoinformatics tools in the discovery of antidiabetic
agents keeping in-view of the growing importance for treating diabetes.
Development of Quantitative Structure-Activity Relationships and Computer-Aided Drug Design
