Evidence map›Paper›PMID 33430461›Full record

ReviewMolecules (Basel, Switzerland)2021

Molecular Recognition and Self-Organization in Life Phenomena Studied by a Statistical Mechanics of Molecular Liquids, the RISM/3D-RISM Theory.

Masatake Sugita, Itaru Onishi, Masayuki Irisa, Norio Yoshida, Fumio Hirata

Abstract readReview
In one paragraph

Review in Molecules (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Human Serum Albumin: 3D Insight on Protein Hydration.International journal of molecular sciences · 2025
    Article
  2. Review
  3. Protein 3D Hydration: A Case of Bovine Pancreatic Trypsin Inhibitor.International journal of molecular sciences · 2022
    Article
  4. 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

5 authors.

Masatake SugitaDepartment of Computer Science, School of Computing, Tokyo Institute of Technology, W8-76, 2-12-1, Ookayama Meguro-ku, Tokyo 152-8550, Japan.ORCID 0000-0002-6298-4055
Itaru OnishiDepartment of Bioscience and Bioinformatics, Kyushu Institute of Technology, Iizuka, Fukuoka 820-8502, Japan.
Masayuki IrisaDepartment of Bioscience and Bioinformatics, Kyushu Institute of Technology, Iizuka, Fukuoka 820-8502, Japan.ORCID 0000-0002-1000-8888
Norio YoshidaDepartment of Chemistry, Kyushu University, Fukuoka, Fukuoka 812-8581, Japan.
Fumio HirataTheoretical and Computational Molecular Science, Institute for Molecular Science, Okazaki, Aichi 444-8585, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There are two molecular processes that are essential for living bodies to maintain their life: the molecular recognition, and the self-organization or self-assembly. Binding of a substrate by an enzyme is an example of the molecular recognition, while the protein folding is a good example of the self-organization process. The two processes are further governed by the other two physicochemical processes: solvation and the structural fluctuation. In the present article, the studies concerning the two molecular processes carried out by Hirata and his coworkers, based on the statistical mechanics of molecular liquids or the RISM/3D-RISM theory, are reviewed.

Indexed as

Chemical PhenomenaMolecular Docking SimulationMolecular Dynamics SimulationAlgorithmsDrug DiscoveryModels, TheoreticalSolventsStructure-Activity RelationshipThermodynamicsWaterSolventsWaterdrug screeningenzymatic reactionfluctuationmolecular recognitionproteinRISM/3D-RISM theoryselective ion bindingself-organizationsolvationwater

Identifiers

PMID33430461
PMCPMC7826681

What OpenQuestion holds

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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.