Presenting a New Paradigm for Drug Discovery: Combining Computational Biophysics and AI through MatchMaker

by Naheed Kurji    Contributor        Biopharma insight / New Tools, Products and Technologies

Disclaimer: All opinions expressed by Contributors are their own and do not represent those of their employers, or BiopharmaTrend.com.
Contributors are fully responsible for assuring they own any required copyright for any content they submit to BiopharmaTrend.com. This website and its owners shall not be liable for neither information and content submitted for publication by Contributors, nor its accuracy.

  
Topics: AI & Digital   
Share:   Share in LinkedIn  Share in Reddit  Share in X  Share in Hacker News  Share in Facebook  Send by email

In this Special Perspective, our fourth in an ongoing series, we will be presenting MatchMaker™, a novel deep proteome screening technology that we have developed and validated over the past 2 years to identify DTIs. MatchMaker builds on Cyclica’s passions of combining protein, chemistry, and genomic data, and augmenting it with high performance computing and algorithm development supported on the cloud.

The Pharmaceutical Industry is Changing.

Fast, accurate, and generalizable drug-target interaction (DTI) predictions have the potential to transform pharmaceutical R&D. In this Special Perspective, our fourth in an ongoing series, we will be presenting MatchMaker™, a novel deep proteome screening technology that we have developed and validated over the past 2 years to identify DTIs. MatchMaker builds on Cyclica’s passions of combining protein, chemistry, and genomic data, and augmenting it with high performance computing and algorithm development supported on the cloud.

MatchMaker combines molecular biophysics and deep learning to predict binding of new drug molecules to all proteins, i.e. the “cell”, with high accuracy and high throughput, moving beyond the reliance on molecular docking. MatchMaker will be the engine that powers our Ligand Express proteome screening platform, and our yet to be released Differential Drug Design (DDD) technology for lead optimization as well as single and multi-target target drug design. MatchMaker will increase the speed, predictive power, and generalizability of these technologies, enabling an integrated in silico first workflow and turning our attention to designing drugs for patients, not just one protein. Prior to releasing this Special Perspective and the accompanying validation notes, we shared the story with a number of partners and investors during the annual JP Morgan Healthcare Conference between January, 7-9, 2019. The response was energizing. We are therefore thrilled to share with you MatchMaker, but before diving into details, let’s take a quick step back.

Cyclica combines knowledge about proteins, drug design, ‘-omics’ big data, and artificial intelligence to bring a revolutionary platform to the market.
Cyclica combines knowledge about proteins, drug design, ‘-omics’ big data, and artificial intelligence to bring a revolutionary platform to the market.

 

A Review of the First Three Special Perspectives

Over the past 1.5 years, we have released three Special Perspectives with the goal of exciting the world about what we are doing at Cyclica:

Continue reading

This content available exclusively for BPT Mebmers

Topics: AI & Digital   

Share:   Share in LinkedIn  Share in Reddit  Share in X  Share in Hacker News  Share in Facebook  Send by email

You may also be interested to read: