Evidence map›Paper›PMID 41400222›Full record

ArticleJournal of chemical information and modeling2026

Discovery of Tetrahydroisoquinoline-Based SARS-CoV-2 Helicase Inhibitors with Iterative, Deep Learning-Enhanced Virtual Screening.

Alma C Castañeda-Leautaud, Ambuj Srivastava, Eunjung Kim, Donghoon Chung, Thomas D Bannister, Rommie E Amaro

Abstract read
In one paragraph

Article in Journal of chemical information and modeling, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Drugs against broad-spectrum of coronaviruses.Frontiers in immunology · 2026
    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

6 authors.

Alma C Castañeda-LeautaudDepartment of Chemistry & Biochemistry, University of California, La Jolla, California 92093-0533, United States.ORCID 0009-0002-6287-3811
Ambuj SrivastavaDepartment of Molecular Biology, University of California, La Jolla, California 92093-0533, United States.
Eunjung KimDepartment of Microbiology & Immunology, University of Louisville, Louisville, Kentucky 40202, United States.
Donghoon ChungDepartment of Microbiology & Immunology, University of Louisville, Louisville, Kentucky 40202, United States.ORCID 0000-0003-2626-172X
Thomas D BannisterDepartment of Molecular Medicine, The Herbert Wertheim UF Scripps Institute for Biomedical Innovation & Technology, Jupiter, Florida 33458, United States.ORCID 0000-0003-0683-8886
Rommie E AmaroDepartment of Molecular Biology, University of California, La Jolla, California 92093-0533, United States.ORCID 0000-0002-9275-9553

Funding

Project 5: Pandemic Virus Helicase InhibitorsU19AI171954 · NIAID · UNIVERSITY OF MINNESOTA · PI Reuben S Harris, Fang Li · 2022 to 2026
$100.9M
NIAID NIH HHS U19 AI171954
6 · The paper itself

Abstract

In this study, we pursued a structure-based drug discovery campaign targeting the SARS-CoV-2 helicase through three rounds of virtual screening (VS) enhanced with Artificial Intelligence (AI). The third round incorporated a deep neural network (DNN) in a virtual screening protocol to prioritize commercial molecules containing fragments related to previously identified hits. This model predicted binary activity toward the target and contributed to a 21% improvement in hit-identification efficiency compared with the previous approach, which used the same virtual screening protocol. In total, we have identified at least six hits with selectivity indexes (CC

Indexed as

Antiviral AgentsDeep LearningDrug DiscoveryEnzyme InhibitorsSARS-CoV-2TetrahydroisoquinolinesCOVID-19 Drug TreatmentDrug Evaluation, PreclinicalHumansMolecular Docking SimulationMolecular Dynamics SimulationAntiviral AgentsEnzyme InhibitorsTetrahydroisoquinolines

Identifiers

PMID41400222
PMCPMC13571900

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.