Evidence map›Paper›PMID 42734559›Full record

ArticleJournal of chemical information and modeling2026

Probe-Atom Distributions Obtained from Mixed-Solvent Molecular Dynamics Improve the Scoring of Docking Calculations.

Kaho Akaki, Keisuke Yanagisawa, Yutaka Akiyama

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. 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

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

3 authors.

Kaho AkakiDepartment of Computer Science, School of Computing, Institute of Science Tokyo, Meguro-ku, Tokyo152-8550, Japan.
Keisuke YanagisawaDepartment of Computer Science, School of Computing, Institute of Science Tokyo, Meguro-ku, Tokyo152-8550, Japan.ORCID 0000-0003-0224-0035
Yutaka AkiyamaDepartment of Computer Science, School of Computing, Institute of Science Tokyo, Meguro-ku, Tokyo152-8550, Japan.ORCID 0000-0003-2863-8703

Funding

Japan Agency for Medical Research and Development JP25ama121026Japan Agency for Medical Research and Development JP25ama121029Japan Society for the Promotion of Science 23K24939Japan Society for the Promotion of Science 23K28185Japan Society for the Promotion of Science 25K03215Kayamori Foundation of Informational Science Advancement NA
6 · The paper itself

Abstract

Structure-based virtual screening (VS) is widely used for the computational selection of drug candidates from compound libraries. Protein-ligand docking calculations are often performed as key steps in the early stages of this process. However, current docking calculations have limited accuracy. Thus, improvements are needed to more efficiently identify promising drug candidates. In this study, we performed mixed-solvent molecular dynamics (MSMD) simulations using four types of probe molecules to improve the accuracy of large-scale VS. We proposed a method for the modification of the docking scoring function for five selected atom classifications (XS_types). This approach integrated the grid free energy derived from the relevant atoms across the probe molecules. VS experiments conducted on nine target proteins showed improved accuracy, with the average EF1% increasing from 6.65 to 7.36. Our method may facilitate drug discovery with higher accuracy than that of conventional methods.

Indexed as

Molecular Docking SimulationMolecular Dynamics SimulationMolecular ProbesProteinsSolventsLigandsLigandsMolecular ProbesProteinsSolvents

Identifiers

PMID42734559
PMCPMC13580117

What Socratic holds

Textmetadata
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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 Socratic graph.