Evidence map›Paper›PMID 40672254›Full record

ArticlebioRxiv : the preprint server for biology2025

Accurate Site-specific Folding via Conditional Diffusion Based on Alphafold3.

Haocheng Tang, Junmei Wang

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

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

5 · Who and what money

Authors and funding

2 authors.

Haocheng TangSchool of Pharmacy, University of Pittsburgh, 3501 Terrace St, Pittsburgh, 15213, Pennsylvania, U.S..ORCID 0009-0001-5702-2847
Junmei WangSchool of Pharmacy, University of Pittsburgh, 3501 Terrace St, Pittsburgh, 15213, Pennsylvania, U.S..ORCID 0000-0002-9607-8229

Funding

New Generation of General AMBER Force Field for Biomedical ResearchR01GM147673 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI WANG, JUNMEI, YANG, WEI · 2022 to 2025
$1.5M
AI-Powered Biased Ligand DesignR01GM149705 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Junmei Wang · 2023 to 2026
$1.3M
NIGMS NIH HHS R01 GM147673NIGMS NIH HHS R01 GM149705
6 · The paper itself

Abstract

Accurate structure prediction of biomolecular complexes is crucial for understanding biological processes and enabling drug discovery. While AlphaFold3 represents a significant advancement, enhancing its accuracy for specific binding sites remains a challenge. We present SiteAF3, a novel method for accurate site-specific folding via conditional diffusion, built upon the AlphaFold3 framework. SiteAF3 refines the diffusion process by fixing the receptor structure and optionally incorporating binding pocket and hotspot residue information. Comprehensive evaluations on protein-small molecule, protein-peptide, and protein-nucleic acid datasets demonstrate that SiteAF3 consistently outperforms AlphaFold3, achieving higher accuracy in complex structure prediction especially for orphan proteins and allosteric ligands, with reduced computational cost. SiteAF3 offers a user-friendly plug-in compatible with AlphaFold3, providing a valuable tool for more accurate modeling of biomolecular interactions.

Indexed as

Alphafold3BiomoleculesDeep LearningDiffusionDockingSiteAF3

Identifiers

PMID40672254
PMCPMC12265610

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.