bioRxivBiophysicsPreprint
Intramolecular Communication and Allosteric Sites in Enzymes Unraveled by Time-Dependent Linear Response Theory
Bang-Chieh Huang, Yi-Yun ChengiD, Chi-Hong Chang Chien, Chao‐Ling YaoiD, Lee‐Wei YangiD
Abstract
It has been an established idea in recent years that protein is a physiochemically connected network. Allostery, understood in this new context, is a manifestation of residue communicating between remote sites in this network, and hence a rising interest to identify functionally relevant communication pathways and the frequent communicators within. However, there have been limited computationally trackable general methods to discover proteins allosteric sites in atomistic resolution with good accuracy. In this study, we devised a time-dependent linear response theory (td-LRT) integrating intrinsic protein dynamics and perturbation forces that excite proteins temporary reconfiguration at the non-equilibrium state, to describe atom-specific time responses as the propagating mechanical signals and discover that the most frequent remote communicators can be important allosteric sites, mutation of which could deteriorate the hydride transfer rate in DHFR by 3 orders. The preferred directionality of the signal propagation can be inferred from the asymmetric connection matrix (CM), where the coupling strength between a pair of residues is suggested by their communication score (CS) in the CM, which is found consistent with experimentally characterized nonadditivity of double mutants. Also, the intramolecular communication centers (ICCs), having high CSs, are found evolutionarily conserved, suggesting their biological importance. We also identify spatially clustered top ICCs as the newly found allosteric site in ATG4B. Among 2016 FDA-approved drugs screened to target the site, two interacting with the site most favorably, confirmed by MD simulations, are found to inhibit ATG4B biochemically and be tumor suppressive in colorectal, pancreatic and breast cancer cell lines with an observed additive therapeutic effect when co-used with an active-site inhibitor.
- assay: protein structure
- assay: protein sequence
- research focus: protein folding & dynamics
- research focus: drug response / drug discovery
- research focus: cell type annotation
- research focus: gene regulatory network inference
- approach: deep learning
- approach: statistical model
- Citations
- 2
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