The role of complementary shape in protein dimerization

Fengyi Gao; Jens Glaser; Sharon C. Glotzer

doi:10.1039/d1sm00468a

The role of complementary shape in protein dimerization

Fengyi Gao, Jens Glaser, Sharon C. Glotzer

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

Shape guides colloidal nanoparticles to form complex assemblies, but its role in defining interfaces in biomolecular complexes is less clear. In this work, we isolate the role of shape in protein complexes by studying the reversible binding processes of 46 protein dimer pairs, and investigate when entropic effects from shape complementarity alone are sufficient to predict the native protein binding interface. We employ depletants using a generic, implicit depletion model to amplify the magnitude of the entropic forces arising from lock-and-key binding and isolate the effect of shape complementarity in protein dimerization. For 13% of the complexes studied here, protein shape is sufficient to predict native complexes as equilibrium assemblies. We elucidate the results by analyzing the importance of competing binding configurations and how it affects the assembly. A machine learning classifier, with a precision of 89.14% and a recall of 77.11%, is able to identify the cases where shape alone predicts the native protein interface.

Original language	English
Pages (from-to)	7376-7383
Number of pages	8
Journal	Soft Matter
Volume	17
Issue number	31
DOIs	https://doi.org/10.1039/d1sm00468a
State	Published - Aug 21 2021
Externally published	Yes

Funding

This material is based upon work supported by the U.S. Army Research Laboratory and the U.S. Army Research Office under contract/Grant No. W911NF-18-1-0167. This research primarily used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725; INCITE Project MAT110: Nucleation and Growth of Colloidal Crystals on the Summit supercomputer. Exploratory study and algorithm testing used the Extreme Science and Engineering Discovery Environment75 (XSEDE), which is supported by National Science Foundation grant number ACI-1548562; XSEDE award DMR 140129. The computational workflow in general and data management in particular for this publication was primarily supported by the signac data management framework.76

Funders	Funder number
National Science Foundation	DMR 140129, ACI-1548562
Army Research Office	W911NF-18-1-0167
Office of Science	MAT110, DE-AC05-00OR22725
Army Research Laboratory

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abstract = "Shape guides colloidal nanoparticles to form complex assemblies, but its role in defining interfaces in biomolecular complexes is less clear. In this work, we isolate the role of shape in protein complexes by studying the reversible binding processes of 46 protein dimer pairs, and investigate when entropic effects from shape complementarity alone are sufficient to predict the native protein binding interface. We employ depletants using a generic, implicit depletion model to amplify the magnitude of the entropic forces arising from lock-and-key binding and isolate the effect of shape complementarity in protein dimerization. For 13% of the complexes studied here, protein shape is sufficient to predict native complexes as equilibrium assemblies. We elucidate the results by analyzing the importance of competing binding configurations and how it affects the assembly. A machine learning classifier, with a precision of 89.14% and a recall of 77.11%, is able to identify the cases where shape alone predicts the native protein interface.",

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AU - Gao, Fengyi

AU - Glaser, Jens

AU - Glotzer, Sharon C.

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PY - 2021/8/21

Y1 - 2021/8/21

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AB - Shape guides colloidal nanoparticles to form complex assemblies, but its role in defining interfaces in biomolecular complexes is less clear. In this work, we isolate the role of shape in protein complexes by studying the reversible binding processes of 46 protein dimer pairs, and investigate when entropic effects from shape complementarity alone are sufficient to predict the native protein binding interface. We employ depletants using a generic, implicit depletion model to amplify the magnitude of the entropic forces arising from lock-and-key binding and isolate the effect of shape complementarity in protein dimerization. For 13% of the complexes studied here, protein shape is sufficient to predict native complexes as equilibrium assemblies. We elucidate the results by analyzing the importance of competing binding configurations and how it affects the assembly. A machine learning classifier, with a precision of 89.14% and a recall of 77.11%, is able to identify the cases where shape alone predicts the native protein interface.

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The role of complementary shape in protein dimerization

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