GatorAffinity: Boosting Protein-Ligand Binding Affinity Prediction with Large-Scale Synthetic Structural Data.

Jinhang Wei, Yupu Zhang, Peter A Ramdhan, Zihang Huang, Gustavo Seabra, Zhe Jiang, Chenglong Li, Yanjun Li

Abstract readPreprint

In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. 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

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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

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

8 authors.

Jinhang WeiDepartment of Medicinal Chemistry, Center for Natural Products, Drug Discovery and Development, University of Florida, Gainesville, FL 32610, USA.ORCID 0009-0003-6957-3472

Yupu ZhangDepartment of Computer & Information Science & Engineering, University of Florida, Gainesville, FL 32611, USA.ORCID 0009-0007-4448-9089

Peter A RamdhanDepartment of Medicinal Chemistry, Center for Natural Products, Drug Discovery and Development, University of Florida, Gainesville, FL 32610, USA.ORCID 0000-0002-2027-1591

Zihang HuangDepartment of Medicinal Chemistry, Center for Natural Products, Drug Discovery and Development, University of Florida, Gainesville, FL 32610, USA.

Gustavo SeabraDepartment of Medicinal Chemistry, Center for Natural Products, Drug Discovery and Development, University of Florida, Gainesville, FL 32610, USA.ORCID 0000-0002-1303-4483

Zhe JiangDepartment of Computer & Information Science & Engineering, University of Florida, Gainesville, FL 32611, USA.ORCID 0000-0002-3576-6976

Chenglong LiDepartment of Medicinal Chemistry, Center for Natural Products, Drug Discovery and Development, University of Florida, Gainesville, FL 32610, USA.ORCID 0000-0001-9460-3168

Yanjun LiDepartment of Medicinal Chemistry, Center for Natural Products, Drug Discovery and Development, University of Florida, Gainesville, FL 32610, USA.ORCID 0000-0002-6277-4189

Funding

Cell Morphology-guided, Scalable and Controllable Molecule Design via Generative AIR21EB037868 · NIBIB · UNIVERSITY OF FLORIDA · PI LI, YANJUN, YUAN, XIAOYONG · 2025 to 2025

$617k

NIBIB NIH HHS R21 EB037868

6 · The paper itself

Abstract

Protein-ligand binding affinity prediction is a fundamental task in computational drug discovery. Although substantial efforts have been made to enhance prediction accuracy using data-driven approaches, progress remains limited by persistent data scarcity. The widely used PDBbind dataset, for example, contains fewer than 20, 000 experimental structures with annotated binding affinities, while a vast number of affinity measurements remain underutilized due to missing structural data. Here, we investigate this untapped potential by curating more than 450, 000 synthetic protein-ligand complexes annotated with

Identifiers

PMID41256614

DOI10.1101/2025.09.29.679384

PMCPMC12621780

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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.