4.5 Article

Contemporary Computational Applications and Tools in Drug Discovery

Journal

ACS MEDICINAL CHEMISTRY LETTERS
Volume -, Issue -, Pages -

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acsmedchemlett.1c00662

Keywords

Structure-based drug design; Cheminformatics; Artificial intelligence; Machine learning; Retrosynthetic analysis; DMTA; CADD; Drug discovery paradigm; Design applications and tools; Software; Open source

Ask authors/readers for more resources

In recent years, there has been a significant increase in computational applications and tools, which have greatly enhanced the efficiency of medicinal chemists in modern drug discovery programs. These modern computational applications cover all areas of drug discovery, such as structure-based drug design and cheminformatics-based drug design.
In the past decade or so there has been a dramatic increase in the number of computational applications and tools that have been developed to enable medicinal chemists to prosecute modern drug discovery programs more efficiently. The upsurge of user-friendly, well-designed computational tools that enable structure-based drug design (SBDD) and cheminformatics (CI)-based drug design has equipped the medicinal chemist with an arsenal of tools and applications that significantly augments the entire design process, thereby enhancing the speed and efficiency of the design-make-test-analyze cycle. Modern computational applications and tools transcend all areas of drug discovery, and most savvy medicinal chemists can employ them effectively in a myriad of drug discovery applications. Indeed, the sheer scope and breadth of tools available to the medicinal chemist is vast and, to our knowledge, has not been comprehensively reviewed. In this article we have catalogued many computational tools, platforms, and applications that are currently available, with four main areas highlighted: commercially available tools/platforms, open-source applications, internally developed platforms (software tools developed within a pharma or biotech organization), and artificial intelligence/machine learning-based platforms. For ease of interpretation, for these categories we provide tables organized by vendor or organization name, the name of the application, whether the tool/application is employed predominantly for SBDD or CI-based design, and a summary of the main function of the tools, with associated hyperlinks to vendor Web sites. We have tried to be as comprehensive and as inclusive as possible; however, the pace of development of new and existing tools is so rapid that there may be omissions with respect to newly developed tools and current versions of the software.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available