Allostery, and how to define and measure signal transduction

Ruth Nussinov*, Chung Jung Tsai, Hyunbum Jang

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review


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.

Original languageEnglish
Article number106766
JournalBiophysical Chemistry
StatePublished - Apr 2022


  • Allosteric
  • Artificial intelligence
  • Cellular network
  • Deep learning
  • Neurodevelopmental disorders
  • Signaling


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