New AI technique helps find Alzheimer’s drug targets


New AI technique helps find Alzheimer’s drug targets

The use of artificial intelligence in new drug discovery and development has been going on for more than a decade. However, recent advances in AI technology and research have actually enabled us to bridge the gap between theory and realistic treatment options.

InSilico Medicine and the University of Cambridge jointly published a paper in the Proceedings of the National Academy of Sciences (PNAS) on the success of AI-based technology, which has made a major breakthrough in identifying new targets for Alzheimer’s and other diseases with a protein phase. Have achieved success. Separation (PPS).

Dr. Michelle Vandroscolo, lead author and co-director of the Center for Misfolding Diseases at the University of Cambridge, called the breakthrough a “game changer.”

PPS can lead to a variety of neurodegenerative diseases and cancer because it causes molecules to become “blocked.” Dr. Vendrucolo introduced a new method called FuseDrop to determine which proteins in the body will undergo PPS. The FuseDrop method is able to predict which proteins will undergo phase separation by sequence-based identification of both regions that promote droplet formation and regions that promote aggregation within droplets.

However, it has been a challenge to find connections between these proteins and related diseases so that new treatments can be developed. Now for the first time, AI technology has allowed us to bridge this gap.

A team of researchers led by Dr. Vandroscolo and Insilico Medicine’s AI target discovery platform, Pandaomics, have enabled the FuzzDrop method to discover three new targets associated with Alzheimer’s disease. This paves the way for future drug development not only for Alzheimer’s but also for other diseases and cancer.

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(Vonaua/Shutterstock)

InSilico Medicine is one of the leading generative AI drug discovery and biomarker development companies. Based in Hong Kong, the company is advancing new therapeutics using generation AI. InSilico uses clinical trial analysis with next-generation AI systems to help discover and develop innovative medicines. It is collaborating with the University of Cambridge since September 2021 to find new ways to identify solutions to PSS-prone diseases such as Parkinson’s and Alzheimer’s.

Commenting on this breakthrough, Alex Zhavoronkov, Founder and CEO of Insilico Medicine, told Datanami that “Protein phase separation has been a major research focus for scientists like Dr. Vandroscolo, who have long been interested in its important role in diseases such as Alzheimer’s and Parkinson’s. understand the role it plays in cancer. But until this methodology was applied, they were not able to link the proteins involved in this process to diseases to identify actionable targets for the development of new drugs.

He also told Datanomy that “Pandomics uses AI to sort through massive amounts of data – including OMIC data, and data from clinical trials, grants, patents, and publications, to identify targets.” “Relationships between biological processes and diseases that can be acted upon – drugs are used to stop the disease from progressing.”

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(Panchenko Vladimir/Shutterstock)

Dr. Vandroscolo’s FuzzDrop method was combined with Insilco Medicine’s AI target discovery engine, PandaOmics, to discover targets that have associations with specific diseases. Pandaomics uses AI technology to search large amounts of data – including OMIC data, and data from clinical trials, patents, publications and grants, to identify targets – targeting biological processes and Relationships between diseases that can be acted upon by drugs to stop the progression of a disease.

“We are delighted to reach this milestone in our collaboration with the University of Cambridge,” said Frank Pun, PhD, head of Insilico Medicine Hong Kong and co-author of the paper. “The study aims to provide initial guidelines for targeting PPS-prone disease-associated proteins. With ongoing technological advances in the study of the PPS process, along with increasing data regarding its roles in both cellular function and dysfunction, it is now possible to understand the causal relationship between PPS targets and diseases. We hope to facilitate the translation of this preclinical research into novel therapeutic interventions in the near future.

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