Evidence map›Paper›PMID 28816025›Full record

ArticleChemical biology & drug design2018

Aromatic interactions at the ligand-protein interface: Implications for the development of docking scoring functions.

Michal Brylinski

Abstract read
In one paragraph

Article in Chemical biology & drug design, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.

0numbers the graph read from it
0cells of the map it votes in
62citing 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

62 citing papers in PubMed.

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  14. FoldX force field revisited, an improved version.Bioinformatics (Oxford, England) · 2025
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  15. The synergistic effect ofFrontiers in pharmacology · 2025
    Article
  16. Article
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  19. Article
  20. Article

2 more citing papers are in PubMed but not listed here.

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

1 author.

Michal BrylinskiDepartment of Biological Sciences, Louisiana State University, Baton Rouge, LA, USA.ORCID 0000-0002-6204-2869

Funding

Combining structure-based network biology and heterogeneous computing for rational drug repositioning and polypharmacologyR35GM119524 · NIGMS · LOUISIANA STATE UNIV A&M COL BATON ROUGE · PI BRYLINSKI, MICHAL · 2016 to 2020
$962k
NIGMS NIH HHS R35 GM119524
6 · The paper itself

Abstract

The ability to design and fine-tune non-covalent interactions between organic ligands and proteins is indispensable to rational drug development. Aromatic stacking has long been recognized as one of the key constituents of ligand-protein interfaces. In this communication, we employ a two-parameter geometric model to conduct a large-scale statistical analysis of aromatic contacts in the experimental and computer-generated structures of ligand-protein complexes, considering various combinations of aromatic amino acid residues and ligand rings. The geometry of interfacial π-π stacking in crystal structures accords with experimental and theoretical data collected for simple systems, such as the benzene dimer. Many contemporary ligand docking programs implicitly treat aromatic stacking with van der Waals and Coulombic potentials. Although this approach generally provides a sufficient specificity to model aromatic interactions, the geometry of π-π contacts in high-scoring docking conformations could still be improved. The comprehensive analysis of aromatic geometries at ligand-protein interfaces lies the foundation for the development of type-specific statistical potentials to more accurately describe aromatic interactions in molecular docking. A Perl script to detect and calculate the geometric parameters of aromatic interactions in ligand-protein complexes is available at https://github.com/michal-brylinski/earomatic. The dataset comprising experimental complex structures and computer-generated models is available at https://osf.io/rztha/.

Indexed as

LigandsMolecular Docking SimulationBenzene DerivativesBinding SitesProteinsProtein Structure, TertiaryQuantum TheoryStatic ElectricityTransaminasesWeb BrowserBenzene Derivativesglutamine-pyruvate aminotransferaseLigandsProteinsTransaminasesaromatic interactionsligand bindingligand dockingmolecular dockingmolecular modelingnon-covalent interactionsparallel stackingperpendicular stackingprotein-ligand complexesπ-π interactions

Identifiers

PMID28816025
PMCPMC5818208

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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.