Literature DB >> 35121384

Allostery, and how to define and measure signal transduction.

Ruth Nussinov1, Chung-Jung Tsai2, Hyunbum Jang2.   

Abstract

Here we ask: What is productive signaling? How to define it, how to measure it, and most of all, what are the parameters that determine it? Further, what determines the strength of signaling from an upstream to a downstream node in a specific cell? These questions have either not been considered or not entirely resolved. The requirements for the signal to propagate downstream to activate (repress) transcription have not been considered either. Yet, the questions are pivotal to clarify, especially in diseases such as cancer where determination of signal propagation can point to cell proliferation and to emerging drug resistance, and to neurodevelopmental disorders, such as RASopathy, autism, attention-deficit/hyperactivity disorder (ADHD), and cerebral palsy. Here we propose a framework for signal transduction from an upstream to a downstream node addressing these questions. Defining cellular processes, experimentally measuring them, and devising powerful computational AI-powered algorithms that exploit the measurements, are essential for quantitative science.
Copyright © 2022. Published by Elsevier B.V.

Entities:  

Keywords:  Allosteric; Artificial intelligence; Cellular network; Deep learning; Neurodevelopmental disorders; Signaling

Mesh:

Year:  2022        PMID: 35121384      PMCID: PMC8898294          DOI: 10.1016/j.bpc.2022.106766

Source DB:  PubMed          Journal:  Biophys Chem        ISSN: 0301-4622            Impact factor:   2.352


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  3 in total

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Review 2.  AlphaFold, Artificial Intelligence (AI), and Allostery.

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  3 in total

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