Evidence map›Paper›PMID 42898797›Full record

ArticleFrontiers in chemistry2026

Engineering a hemoglobin variant with enhanced stability and oxygen affinity using a protein language model.

Sergey Shityakov, Alexander S Novikov, Ekaterina V Skorb, Thomas Dandekar

Abstract read
In one paragraph

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

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Sergey ShityakovLaboratory of Chemoinformatics, Infochemistry Scientific Center, ITMO University, Saint Petersburg, Russia.
Alexander S NovikovLaboratory of Chemoinformatics, Infochemistry Scientific Center, ITMO University, Saint Petersburg, Russia.
Ekaterina V SkorbLaboratory of Chemoinformatics, Infochemistry Scientific Center, ITMO University, Saint Petersburg, Russia.
Thomas DandekarDepartment of Bioinformatics, Biocenter, Am Hubland, Julius-Maximilians University of Würzburg, Würzburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Engineered hemoglobin variants offer therapeutic promise for artificial blood substitutes and oxygen therapeutics, but rational design is constrained by protein stability and heme-binding. Protein language models (pLMs) predict mutation fitness, yet their integration with biophysical validation remains limited. Methods: We developed a hybrid pipeline combining pLM (ESM3) with molecular docking, Monte Carlo simulation, molecular dynamics, MM-GBSA/PBSA binding free energy calculations, and density functional theory (DFT) to engineer a stabilized hemoglobin variant (esmHb) with enhanced oxygen affinity, benchmarking against the clinically characterized Hb Fort de France mutation (α45 His→Arg). Results: ESM3 accurately assessed the fitness effect of the Hb Fort de France mutation and generated structurally stable esmHb models. Compared with the wild-type variant (wtHb), esmHb exhibited improved thermodynamic stability (ΔG: -18.48 vs. -12.22 kcal/mol), increased heme-binding affinity (ΔGbind: -11.79 vs. -8.42 kcal/mol), and greater thermodynamic favorability of oxidation according to DFT calculations (ΔE: -173.1 vs. -149.9 kcal/mol). MM-GBSA and MM-PBSA binding free energy calculations further supported improved protein-heme and protein-protein interactions, with esmHb showing more favorable values in both implicit solvation models. Statistical significance (p < 0.05) was reached for protein-protein interactions via both methods and for protein-heme interactions via MM-PBSA. We interpret the MM-GBSA results as a suggestive trend rather than definitive evidence. Discussion: This work establishes a generalizable framework for pLM-driven protein engineering applicable to therapeutic Hb variants and beyond.

Indexed as

computational protein designDFT calculationshemoglobinmolecular dynamicsMonte Carlo simulationmyoglobinoxygen affinityprotein language model

Identifiers

PMID42898797
PMCPMC13678298

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.