Evidence map›Paper›PMID 40693731›Full record

ReviewGlycobiology2025

Editor's Choice Protein engineering strategies to develop lectins by design.

Ryoma Hombu, Lauren E Beatty, Sriram Neelamegham

Abstract readReview
In one paragraph

Review in Glycobiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
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.

Ryoma HombuChemical and Biological Engineering, University at Buffalo, State University of New York, Buffalo, NY 14260, USA.
Lauren E BeattyBiomedical Engineering, University at Buffalo, State University of New York, Buffalo, NY 14260, USA.
Sriram NeelameghamChemical and Biological Engineering, University at Buffalo, State University of New York, Buffalo, NY 14260, USA.ORCID 0000-0002-1371-8500

Funding

Systems Biology of GlycosylationR01HL103411 · NHLBI · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI NEELAMEGHAM, SRIRAM · 2011 to 2025
$7.1M
Engineering of glycosyltransferases to obtain glycan binding proteinsR21GM139160 · NIGMS · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI NEELAMEGHAM, SRIRAM, PARK, SHELDON · 2020 to 2021
$422k
NHLBI NIH HHS R01 HL103411NIGMS NIH HHS R21 GM139160NIH HHS GM139160NIH HHS HL103411
6 · The paper itself

Abstract

Glycans regulate a wide array of biological processes, making them central to studies of cell biology. Thus, it is essential to characterize the spatiotemporal dynamics of glycans on cells and tissues, and to elucidate how glycan structures affect protein and cell function. Among the available molecular tools, glycan-binding proteins (GBPs), including naturally occurring lectins, are uniquely suited to provide this information at single-cell resolution. However, the diversity of cell-surface glycans far exceeds the number of readily available GBPs. Moreover, conventional lectins often possess shallow binding pockets that limit their recognition to terminal glycan epitopes, and such recognition often proceeds with low binding affinity. Protein engineering offers a promising strategy to expand GBP specificity, enhance affinity, and introduce novel binding capabilities. Currently, large gaps remain between the available protein design principles and their application to GBP engineering. This has somewhat slowed progress in the development of glycan-targeted tools. In this review, we outline recent efforts that use rational design to inform GBP engineering for specific tasks. We also present methods to select suitable protein scaffolds and the application of directed evolution for optimizing lectin design. This includes our recent efforts to modify glycosyltransferases into GBPs, which potentially offers a predictive strategy to design lectins based on desired properties. Together, the presentation offers a roadmap for developing next-generation glycan binding proteins capable of decoding the complex glycan landscape of cells.

Indexed as

LectinsPolysaccharidesProtein EngineeringAnimalsHumansLectinsPolysaccharidesdirected evolutionglycanlectinmutagenesissurface display

Identifiers

PMID40693731
PMCPMC12598746

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.