Evidence map›Paper›PMID 41663055›Full record

ArticleMolecular pharmaceutics2026

Hotspot Interactions between Two Fab Molecules in Molecular Dynamics Simulations Improve Predictive Models of Aggregation Kinetics.

Yuhan Wang, Hywel D Williams, Duygu Dikicioglu, Paul A Dalby

Abstract read
In one paragraph

Article in Molecular pharmaceutics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

4 authors.

Yuhan WangDepartment of Biochemical Engineering, University College London, London Wc1e 6bt, U.K.
Hywel D WilliamsCSL Ltd, Biopharmaceutical Product Development, 655 Elizabeth Street, Melbourne, VIC 3000 Australia.
Duygu DikiciogluDepartment of Biochemical Engineering, University College London, London Wc1e 6bt, U.K.ORCID 0000-0002-3018-4790
Paul A DalbyDepartment of Biochemical Engineering, University College London, London Wc1e 6bt, U.K.ORCID 0000-0002-0980-8167

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein-protein interactions (PPIs) are fundamental to numerous biological processes, and the identification of interaction hotspots is essential for understanding the mechanisms of protein aggregation and informing protein engineering efforts. Although various algorithms have been developed to predict hotspot regions for protein-protein interactions, little research has focused on understanding the relative roles of these largely protein surface-based interactions and the interactions between cross-β sheet-forming aggregation-prone regions (APRs) that are largely buried within proteins. This study uses all-atom molecular dynamics (MD) simulations to investigate the interactions between two Fab antibody fragments, focusing on the identification and characterization of the key interaction sites. Through frequency contact map analysis and principal component analysis, we identified specific residues that consistently formed stable contacts, distinguishing them from transient random interactions. Our findings revealed that while numerous contact points occurred throughout the simulations, relatively few sites acted as persistent hotspots based on the duration of their contacts. Comparison to single Fab simulations highlighted the influence of interfragment interactions on conformational dynamics. Inclusion of solvent accessibility for two surface hotspots, alongside one predicted APR, significantly improved models for predicting aggregation kinetics over 49 formulation conditions. The molecular-level insights gained will be important for guiding protein engineering strategies aimed at modulating these interactions to enhance product stability and retain therapeutic efficacy.

Indexed as

Immunoglobulin Fab FragmentsMolecular Dynamics SimulationProtein AggregatesAlgorithmsKineticsPrincipal Component AnalysisProtein BindingImmunoglobulin Fab FragmentsProtein Aggregatesantibody aggregationhotspot regionsmodel buildingmolecular dynamics simulationsmultiple antibody fragmentsprotein−protein interaction (PPI)

Identifiers

PMID41663055
PMCPMC12958343

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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.