Evidence map›Paper›PMID 40671268›Full record

ReviewProtein science : a publication of the Protein Society2025

Exploring binding and allosteric energy landscapes for the KRAS interactions with effector proteins using Markov state modeling of conformational ensembles and allosteric network modeling.

Sian Xiao, Mohammed Alshahrani, Guang Hu, Peng Tao, Gennady Verkhivker

Abstract readReview
In one paragraph

Review in Protein science : a publication of the Protein Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. M-Ras distinct activation scenarios: A mechanistic outlook and targeting.Computational and structural biotechnology journal · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Sian XiaoDepartment of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, Texas, USA.
Mohammed AlshahraniKeck Center for Science and Engineering, Schmid College of Science and Technology, Chapman University, Orange, California, USA.
Guang HuDepartment of Bioinformatics and Computational Biology, School of Life Sciences, Suzhou Medical College of Soochow University, Suzhou, China.
Peng TaoDepartment of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, Texas, USA.ORCID 0000-0002-2488-0239
Gennady VerkhivkerKeck Center for Science and Engineering, Schmid College of Science and Technology, Chapman University, Orange, California, USA.ORCID 0000-0002-4507-4471

Funding

Probing Hidden Conformational Space and Dynamical States of Circadian Clock Proteins through Rigid Residue Scan and Machine LearningR15GM122013 · NIGMS · SOUTHERN METHODIST UNIVERSITY · PI TAO, PENG · 2018 to 2023
$800k
Kay Family Foundation A20-0032NIH HHS 1R01AI181600-01NIH HHS 6069-SC24-11NIH HHS R15GM122013
6 · The paper itself

Abstract

Kirsten rat sarcoma viral oncogene homolog (KRAS) is a pivotal oncoprotein that regulates cell proliferation and survival through interactions with downstream effectors such as RAF1. Despite significant advances, the dynamic and energetic mechanisms of KRAS allostery by which oncogenic mutations can modulate KRAS-RAF1 signaling remain poorly understood. In this study, we employ microsecond molecular dynamics simulations, mutational scanning, and binding free energy calculations together with dynamic network modeling to elucidate the effect of KRAS G12V, G13D, and Q61R mutations and characterize the thermodynamic drivers and hotspots of KRAS binding and allostery. We found that these mutations stabilize the active state and enhance RAF1 binding by differentially modulating the flexibility of switch regions. The G12V mutation rigidifies both switch I and switch II, locking KRAS in a stable active state. In contrast, the G13D mutation moderately reduces switch I flexibility, while the Q61R mutation induces a more dynamic conformational landscape. Mutational scanning and binding free energy analysis of KRAS-RAF1 complexes identified key binding affinity hotspots that leverage synergistic electrostatic and hydrophobic binding interactions in stabilizing the KRAS-RAF1 interfaces. Dynamic network analysis identifies critical allosteric centers and a conserved allosteric architecture that mediate long-range interactions in the KRAS-RAF1 complexes and enable precision modulation of KRAS dynamics in oncogenic contexts. The predictions accurately reproduced the experimental data on KRAS allostery and provided a detailed map of allosteric communications mediated by the central β-sheet region of KRAS that connects the binding interface hotspots with allosteric hubs transmitting functional conformational changes. Together, these findings advance our understanding of mechanisms underlying allosteric regulation of KRAS binding and underscore the importance of targeting mutant-specific conformations for therapeutic interventions.

Indexed as

Proto-Oncogene Proteins c-rafProto-Oncogene Proteins p21(ras)Allosteric RegulationHumansMarkov ChainsMolecular Dynamics SimulationProtein BindingProtein ConformationThermodynamicsKRAS protein, humanProto-Oncogene Proteins c-rafProto-Oncogene Proteins p21(ras)Raf1 protein, humanallosteric mechanismbinding energeticscomputer simulationseffector proteinsintegrative protein modelingKRAS proteinmarkov state modelsmolecular dynamicsmutational scanningprotein network analysis

Identifiers

PMID40671268
PMCPMC12267112

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.