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PreprintCited by 6Protein Kinase Regulation and GTPase SignalingProtein Structure and DynamicsComputational Drug Discovery Methods

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Structure-based prediction of Ras-effector binding affinities and design of ‘branchegetic’ interface mutations

Open access
Junk, Philipp, Kiel, Christina·2022·Structure
DOI 10.1101/2022.09.04.506480

Preprint — published as 10.1016/j.str.2023.04.007

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Abstract

Summary: Ras is a central cellular hub protein controlling multiple cell fates. How Ras interacts with a variety of potential effector proteins is relatively unexplored, with only some key effectors characterized in great detail. Here, we have used homology modelling based on X-ray and AlphaFold2 templates to build structural models for 54 Ras-effectors complexes. These models were used to estimate binding affinities using a supervised learning regressor. Furthermore, we systematically introduced Ras ‘branch-pruning’ (or branchegetic) mutations to identify 200 interface mutations that affect the binding energy with at least one of the model structures. The impacts of these branchegetic mutants were integrated into a mathematical model to assess the potential for rewiring interactions at the Ras hub on a systems level. These findings have provided a quantitative understanding of Ras-effector interfaces and their impact on systems properties of a key cellular hub.

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Metadata

Authors
Junk, P., & Kiel, C.
Affiliations
University College Dublin (IE)
Corresponding author
Junk, Philipp
ORCID
Venue
Structure
Publisher
openRxiv
Published
2022-09-05
Volume
31
Issue
7
Pages
870-883.e5
ISSN
0969-2126 (ISSN-L)
DOI
10.1101/2022.09.04.506480
OpenAlex
W4376113646
Cited by
6
References
1
Citations by year
2026: 1 · 2025: 3 · 2024: 2
FWCI
0.53
Type
journal article
Language
en
Open access
Locations
  • Structure (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
Science Foundation Ireland (16/FRL/3886)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Kinase Regulation and GTPase Signaling
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
Keywords
Ras, binding affinity prediction, interaction rewiring, homology modeling, AlphaFold2, binding energy, system-level modeling
MeSH terms
Mutation, Protein Binding, Proteins, ras Proteins, Molecular Dynamics Simulation

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