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DIP/Dpr interactions and the evolutionary design of specificity in protein families.


ABSTRACT: Differential binding affinities among closely related protein family members underlie many biological phenomena, including cell-cell recognition. Drosophila DIP and Dpr proteins mediate neuronal targeting in the fly through highly specific protein-protein interactions. We show here that DIPs/Dprs segregate into seven specificity subgroups defined by binding preferences between their DIP and Dpr members. We then describe a sequence-, structure- and energy-based computational approach, combined with experimental binding affinity measurements, to reveal how specificity is coded on the canonical DIP/Dpr interface. We show that binding specificity of DIP/Dpr subgroups is controlled by "negative constraints", which interfere with binding. To achieve specificity, each subgroup utilizes a different combination of negative constraints, which are broadly distributed and cover the majority of the protein-protein interface. We discuss the structural origins of negative constraints, and potential general implications for the evolutionary origins of binding specificity in multi-protein families.

SUBMITTER: Sergeeva AP 

PROVIDER: S-EPMC7195491 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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DIP/Dpr interactions and the evolutionary design of specificity in protein families.

Sergeeva Alina P AP   Katsamba Phinikoula S PS   Cosmanescu Filip F   Brewer Joshua J JJ   Ahlsen Goran G   Mannepalli Seetha S   Shapiro Lawrence L   Honig Barry B  

Nature communications 20200501 1


Differential binding affinities among closely related protein family members underlie many biological phenomena, including cell-cell recognition. Drosophila DIP and Dpr proteins mediate neuronal targeting in the fly through highly specific protein-protein interactions. We show here that DIPs/Dprs segregate into seven specificity subgroups defined by binding preferences between their DIP and Dpr members. We then describe a sequence-, structure- and energy-based computational approach, combined wi  ...[more]

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