Evidence map›Paper›PMID 40043838›Full record

ReviewJournal of molecular biology2025

The Evolving Landscape of Protein Allostery: From Computational and Experimental Perspectives.

Srinivasan Ekambaram, Grigor Arakelov, Nikolay V Dokholyan

Abstract readReview
In one paragraph

Review in Journal of molecular biology, 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. Article
  5. Optogenetic enzymes: A deep dive into design and impact.Current opinion in structural biology · 2025
    Review
  6. 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

3 authors.

Srinivasan EkambaramDepartment of Neuroscience and Experimental Therapeutics, Penn State College of Medicine, Hershey, PA 17033, USA.
Grigor ArakelovDepartment of Neuroscience and Experimental Therapeutics, Penn State College of Medicine, Hershey, PA 17033, USA; Institute of Molecular Biology of the National Academy of Sciences of the Republic of Armenia, Yerevan 0014, Armenia.
Nikolay V DokholyanDepartment of Neuroscience and Experimental Therapeutics, Penn State College of Medicine, Hershey, PA 17033, USA; Department of Biochemistry & Molecular Biology, Penn State College of Medicine, Hershey, PA 17033, USA; Department of Chemistry, Penn State University, University Park, PA 16802, USA; Department of Biomedical Engineering, Penn State University, University Park, PA 16802, USA. Electronic address: dokh@psu.edu.

Funding

Nanoscale programming of cellular and physiological phenotypes: EquipmentR35GM134864 · NIGMS · UNIVERSITY OF VIRGINIA · PI Nikolay Dokholyan · 2020 to 2026
$5.2M
AI-based Mapping of Complex Cannabis Extracts in Pain PathwaysR01AT012053 · NCCIH · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI Nikolay Dokholyan, KENT E VRANA · 2023 to 2026
$2.4M
NCCIH NIH HHS R01 AT012053NIGMS NIH HHS R35 GM134864
6 · The paper itself

Abstract

Protein allostery is a fundamental biological regulatory mechanism that allows communication between distant locations within a protein, modifying its function in response to signals. Experimental techniques, such as NMR spectroscopy and cryo-electron microscopy (cryo-EM), are critical validation tools for computational predictions and provide valuable insights into dynamic conformational changes. Combining these approaches has greatly improved our understanding of classical conformational allostery and complex dynamic coupling mechanisms. Recent advances in machine learning and enhanced sampling methods have broadened the scope of allostery research, identifying cryptic allosteric sites and directing new drug discovery approaches. Despite progress, bridging static structural data with dynamic functional states remains challenging. This review underscores the importance of combining experimental and computational approaches to comprehensively understand protein allostery and its diverse applications in biology and medicine.

Indexed as

Computational BiologyProteinsAllosteric RegulationAllosteric SiteCryoelectron MicroscopyHumansMachine LearningModels, MolecularProtein ConformationProteinsallosteric communicationsallosteric regulationallosterymachine learningmolecular dynamics simulations

Identifiers

PMID40043838
PMCPMC12353675

What Socratic holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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 Socratic graph.