Evidence map›Paper›PMID 40388499›Full record

ArticleJournal of chemical information and modeling2025

Template-Based Docking Using Automated Maximum Common Substructure Identification with EnzyDock: Mechanistic and Inhibitor Docking.

Renana Schwartz, Amit Hadar-Volk, Kwangho Nam, Dan T Major

Abstract read
In one paragraph

Article in Journal of chemical information and modeling, 2025. 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. Article
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

4 authors.

Renana SchwartzDepartment of Chemistry, Israel National Institute of Energy Storage (INIES) and Institute for Nanotechnology & Advanced Materials, Bar-Ilan University, Ramat-Gan 5290002, Israel.ORCID 0000-0003-0552-6434
Amit Hadar-VolkDepartment of Chemistry, Israel National Institute of Energy Storage (INIES) and Institute for Nanotechnology & Advanced Materials, Bar-Ilan University, Ramat-Gan 5290002, Israel.ORCID 0009-0009-4728-6329
Kwangho NamDepartment of Chemistry and Biochemistry and Division of Data Science, University of Texas at Arlington, Arlington, Texas 76019, United States.ORCID 0000-0003-0723-7839
Dan T MajorDepartment of Chemistry, Israel National Institute of Energy Storage (INIES) and Institute for Nanotechnology & Advanced Materials, Bar-Ilan University, Ramat-Gan 5290002, Israel.ORCID 0000-0002-9231-0676

Funding

Multiscale ab initio QM/MM and Machine Learning Methods for Accelerated Free Energy SimulationsR44GM133270 · NIGMS · Q-CHEM, INC. · PI FENG, XINTIAN · 2023 to 2024
$1.3M
EnzyDock-based Multistate and Multiscale Tools for Covalent Drug DesignR21GM148895 · NIGMS · UNIVERSITY OF TEXAS ARLINGTON · PI NAM, KWANGHO · 2023 to 2024
$361k
NIGMS NIH HHS R21 GM148895NIGMS NIH HHS R44 GM133270
6 · The paper itself

Abstract

EnzyDock is a multistate, multiscale CHARMM-based docking program which enables mechanistic docking, i.e., modeling enzyme reactions by docking multiple reaction states, like substrates, intermediates, transition states, and products to the enzyme, in addition to standard protein-ligand docking. To achieve docking of multiple reaction states with similar poses (i.e., consensus docking), EnzyDock employs consensus pose restraints of the docked ligand states relative to a docking template. In the current work, we present an implementation of a Maximum Common Substructure (MCS)-guided docking strategy using EnzyDock, enabling the automatic detection of similarity among query ligands. Specifically, the MCS multistate approach is employed to efficiently dock ligands along enzyme reaction coordinates, including reactants, intermediates, and products, which allows efficient and robust mechanistic docking. To demonstrate the effectiveness of the MCS strategy in modeling enzymes, it is first applied to two highly complex enzyme reaction cascades catalyzed by the diterpene synthase CotB2 and the Diels-Alderase LepI. In addition, the MCS strategy is applied to dock enzyme inhibitors using cocrystallized inhibitors or substrates to guide the docking in the enzymes dihydrofolate reductase and the SARS-CoV-2 enzyme M

Indexed as

Enzyme InhibitorsMolecular Docking SimulationAlgorithmsAutomationLigandsSARS-CoV-2SoftwareEnzyme InhibitorsLigands

Identifiers

PMID40388499
PMCPMC13107496

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Registered trials

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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.