{"id":46,"date":"2022-05-07T05:35:22","date_gmt":"2022-05-07T05:35:22","guid":{"rendered":"https:\/\/src.cikeys.com\/2022\/?page_id=46"},"modified":"2022-05-07T05:35:22","modified_gmt":"2022-05-07T05:35:22","slug":"a-novel-ml-based-3d-pharmacophore-fingerprinting-approach-to-the-screening-of-potential-hiv-1-rt-inhibitors","status":"publish","type":"page","link":"https:\/\/src.cikeys.com\/2022\/a-novel-ml-based-3d-pharmacophore-fingerprinting-approach-to-the-screening-of-potential-hiv-1-rt-inhibitors\/","title":{"rendered":"A Novel ML-based 3D Pharmacophore Fingerprinting Approach to the Screening of Potential HIV-1 RT Inhibitors"},"content":{"rendered":"\n

Nathaniel Thomas, Anya Iyer, Aneri Sheth, Zachary Bashkin, and Robert Downing<\/h3>\n\n\n\n\n\n\n\n
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Abstract<\/h2>\n\n\n\n

With advancements in the field of machine learning-powered by on-demand computing and information processing on a large scale, computationally driven proteomics and high throughput virtual screening have become increasingly popular in reducing traditional in vitro screening costs and the timeframe for hit-to-lead identification of drug candidates. The efficiency of high throughput fingerprinting using cheminformatics-based approaches coupled with machine learning holds immense potential in screening possible inhibitors. To identify these potential targets, we propose a reductionist approach in identifying key pharmacophoric elements of chemical entities, dramatically reducing the relative compute cost for large-scale chemical screening efforts. By minimizing the 3D structure of our molecules to their key points we are able to screen a larger sample of chemical space while effectively filtering for ideal small molecule drugs. Platforms such as PaDEL and Mordred were used in identifying notable descriptors of a class of FDA-approved NNRTIs, and this data was later implemented in a machine learning-based model when screening for the structural similarity between NNRTIs and other datasets of organic compounds. Herein, we present a novel pharmacophore fingerprinting method based on 3D reductions of molecule libraries, enabling a relatively more efficient and rapid screening of effective inhibitors of the HIV-1 RT enzyme.<\/p>\n<\/div>\n\n\n\n

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Presentation<\/h2>\n\n\n