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Drug discovery is much like working a jigsaw puzzle. The chemical compounds behind drug molecules must be shaped to fit with the proteins in our bodies to produce therapeutic effects. That requirement for a meticulous fit means the creation of new drugs is extremely complex and time-consuming.

To speed up the puzzle-fitting process, researchers at SMU have created SmartCADD. This open-source virtual tool combines artificial intelligence, quantum mechanics and Computer Assisted Drug Design (CADD) techniques to speed up the screening of chemical compounds, significantly reducing drug discovery timelines. In a recent study published in the Journal of Chemical Information and Modeling , researchers demonstrated SmartCADD's ability to identify promising HIV drug candidates.



This new tool grew from an interdisciplinary collaboration between SMU's department of chemistry in Dedman College of Humanities and Sciences and the computer science department in the Lyle School of Engineering. There is an urgency to discover new classes of drugs like antibiotics, cancer treatments, antivirals and more. Despite AI's rapid adoption in many fields, there has been a hesitancy for using it in scientific research, mainly because of its opaqueness and the quality of data used for training.

SmartCADD addresses those concerns and can sift through billions of chemical compounds in one day, which significantly reduces the time needed to identify promising drug candidates." Elfi Kraka, Head of the Compu.

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