New tool enables target discovery for new class of diseases not yet mechanically understood

Insilico, a clinical-stage generative artificial intelligence (AI)-drive drug discovery company, says recent research demonstrates that protein phase separation (PPS) is widely present in cells and drives a range of important biological functions. PPS at the wrong place or time, it says, could create clogs or aggregates of molecules linked to neurodegenerative diseases, and poorly formed cellular condensates could contribute to cancers and may explain the ageing process.

An emerging link between human disease and the PPS process has led scientists to look for ways to identify potential targets for therapeutic interventions based on PPS regulation.

The university and Insilico have jointly published a paper in Proceedings of the National Academy of Sciences (PNAS)​, presenting an approach to identify therapeutic targets for human diseases associated with PPS. It recognizes a significant research milestone in their collaboration launched in September 2021, they say.

Protein separation prediction

In this study, researchers combined Insilico's proprietary artificial intelligence (AI)-driven target identification engine PandaOmics with the FuzDrop method for predicting protein separation to identify PPS-prone disease-associated proteins. PandaOmics integrates multiple omics and text-based AI bioinformatics models to assess the potential of proteins as therapeutic targets.

The FuzDrop is a pioneering tool introduced by Michele Vendruscolo’s group at the University of Cambridge, which calculates the propensity of a protein to undergo spontaneous phase separation, aiding in the identification of proteins prone to forming liquid-liquid phase-separated condensates.

“It has been challenging so far to understand the role of protein phase separation in cellular functions,” said Vendruscolo, co-director, Centre for Misfolding Diseases, Yusuf Hamied department of chemistry, University of Cambridge and lead author on the paper.

“Even more difficult has been to clarify the exact nature of its association with human disease. By working with Insilico Medicine, we have developed a multi-omic approach to systematically address this problem and identify a variety of possible targets for therapeutic intervention. We have thus provided a roadmap for researchers to navigate this complex terrain.” 

"The method described in the paper enables target discovery for a new class of diseases that have not been fully mechanistically understood yet. Until now, it has been challenging to identify actionable targets for drug discovery companies in this space -- this provides a new tool for finding them."

Large scale multi-omic study​

Using this approach, the researchers conducted a large-scale multi-omic study of human sample data, quantified the relative impact of PPS in regulating various pathological processes associated with human disease, prioritized candidates with high PandaOmics and FuzDrop scores, and generated a list of possible therapeutic targets for human diseases linked with PPS.

Researchers validated the differential phase separation behaviors of three predicted Alzheimer’s disease targets (MARCKS, CAMKK2 and p62) in two cell models of Alzheimer’s disease, which provides experimental validation for the involvement of these predicted targets in Alzheimer's disease and support their potential as therapeutic targets. By modulating the formation and behavior of these condensates, it may be possible to develop novel interventions to mitigate the pathological processes associated with Alzheimer's disease.

“We are pleased to reach this milestone in our collaboration with the University of Cambridge,” said Frank Pun, head of Insilico Medicine Hong Kong, and co-author of the paper.

“The study is intended to provide initial directions for targeting PPS-prone disease-associated proteins. With ongoing technical advancements in studying the PPS process, coupled with growing data about its roles in both cellular function and dysfunction, it is now possible to comprehend the causal relationship between PPS targets and diseases. We anticipate facilitating the translation of this preclinical research into novel therapeutic interventions in the near future.”