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Updated: Feb 16, 2026

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Overcoming structural complexity in Galectin-3BP through an integrative computational antibody design workflow.

Andrielly H S Costa1, Eduardo M Gaieta1, Aline O Albuquerque2

  • 1Postgraduate Program in Computational and Systems Biology, Oswaldo Cruz Foundation (Fiocruz), 21040-900, Rio de Janeiro, Brazil; Structural and Functional Biology in Biopharmaceuticals Group - Fiocruz Ceará, 61760-000, Eusébio, Brazil.

Computers in Biology and Medicine
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Summary

Researchers developed a computational method to design antibodies targeting Galectin-3 binding protein (Gal-3BP), overcoming challenges like glycosylation. Optimized antibody candidates were identified for therapeutic development against cancer.

Keywords:
Antibody engineeringEpitope screeningGalectin-3 binding proteinGaussian accelerated molecular dynamicsGlycoprotein

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Area of Science:

  • Computational Biology and Bioinformatics
  • Structural Biology
  • Immunology and Antibody Engineering

Background:

  • Galectin-3 binding protein (Gal-3BP) is a significant oncology target, but its complex structure, including glycosylation and heterogeneity, hinders therapeutic antibody development.
  • Existing antibody development is costly and experimentally intensive, necessitating novel approaches for targeting complex glycoproteins like Gal-3BP.

Purpose of the Study:

  • To establish an integrative in-silico workflow for designing therapeutic antibodies against Galectin-3 binding protein (Gal-3BP).
  • To identify and engineer antibody candidates that can access glycan-shielded epitopes on Gal-3BP for potential cancer therapy.

Main Methods:

  • Utilized structural prediction, molecular dynamics (MD) simulations, and antibody engineering to analyze Gal-3BP structure, oligomerization, and N-glycan diversity.
  • Employed 3D Zernike descriptors for scaffold selection and repertoire mining for antibody template identification.
  • Applied iterative engineering, including point mutations and CDR swapping, followed by heated MD and Gaussian accelerated MD (GaMD) for stability and conformational analysis.

Main Results:

  • Identified two glycan-free epitopes (E1 and E2) on the Gal-3BP BACK domain.
  • Selected and engineered compatible antibody scaffolds (BDBV-43 for E1, E2-Ab1 for E2) with improved interaction profiles and stability.
  • GaMD simulations revealed reorganized conformational landscapes and modest free-energy profile shifts in engineered antibodies.

Conclusions:

  • Galectin-3 binding protein (Gal-3BP) is a tractable therapeutic target, with optimized antibody candidates identified.
  • The integrative computational pipeline demonstrates significant potential for designing antibodies against structurally complex proteins like Gal-3BP.
  • Developed antibodies can engage epitopes minimally affected by glycan shielding, paving the way for novel cancer therapeutics.