Hidden long evolutionary memory in a model biochemical network

Physical Review. E
Md Zulfikar AliRanjan Mukhopadhyay

Abstract

We introduce a minimal model for the evolution of functional protein-interaction networks using a sequence-based mutational algorithm, and apply the model to study neutral drift in networks that yield oscillatory dynamics. Starting with a functional core module, random evolutionary drift increases network complexity even in the absence of specific selective pressures. Surprisingly, we uncover a hidden order in sequence space that gives rise to long-term evolutionary memory, implying strong constraints on network evolution due to the topology of accessible sequence space.

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Citations

Jun 25, 2020·Scientific Reports·Ammar TareenRanjan Mukhopadhyay

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