Evidence map›Paper›PMID 26339784›Full record

ArticlePloS one2015

Exploring Strong Interactions in Proteins with Quantum Chemistry and Examples of Their Applications in Drug Design.

Neng-Zhong Xie, Qi-Shi Du, Jian-Xiu Li, Ri-Bo Huang

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
1.5field-weighted citation impact, top 17% of its field
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

30 citing papers in PubMed, 86 citations in OpenAlex.

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  20. Δ-Quantum machine-learning for medicinal chemistry.Physical chemistry chemical physics : PCCP · 2022
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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 at 1 institution in 2 countries.

Neng-Zhong XieState Key Laboratory of Non-food Biomass and Enzyme Technology, National Engineering Research Center for Non-food Biorefinery, Guangxi Academy of Sciences, 98 Daling Road, Nanning, Guangxi, 530007, China.
Qi-Shi DuState Key Laboratory of Non-food Biomass and Enzyme Technology, National Engineering Research Center for Non-food Biorefinery, Guangxi Academy of Sciences, 98 Daling Road, Nanning, Guangxi, 530007, China; Gordon Life Science Institute, 53 South Cottage Road, Belmont, MA, 02478, United States of America.
Jian-Xiu LiState Key Laboratory of Non-food Biomass and Enzyme Technology, National Engineering Research Center for Non-food Biorefinery, Guangxi Academy of Sciences, 98 Daling Road, Nanning, Guangxi, 530007, China; Life Science and Biotechnology College, Guangxi University, Nanning, Guangxi, 530004, China.
Ri-Bo HuangState Key Laboratory of Non-food Biomass and Enzyme Technology, National Engineering Research Center for Non-food Biorefinery, Guangxi Academy of Sciences, 98 Daling Road, Nanning, Guangxi, 530007, China; Life Science and Biotechnology College, Guangxi University, Nanning, Guangxi, 530004, China.
Guangxi Academy of Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThree strong interactions between amino acid side chains (salt bridge, cation-π, and amide bridge) are studied that are stronger than (or comparable to) the common hydrogen bond interactions, and play important roles in protein-protein interactions.

methodsQuantum chemical methods MP2 and CCSD(T) are used in calculations of interaction energies and structural optimizations.

resultsThe energies of three types of amino acid side chain interactions in gaseous phase and in aqueous solutions are calculated using high level quantum chemical methods and basis sets. Typical examples of amino acid salt bridge, cation-π, and amide bridge interactions are analyzed, including the inhibitor design targeting neuraminidase (NA) enzyme of influenza A virus, and the ligand binding interactions in the HCV p7 ion channel. The inhibition mechanism of the M2 proton channel in the influenza A virus is analyzed based on strong amino acid interactions.

conclusion(1) The salt bridge interactions between acidic amino acids (Glu- and Asp-) and alkaline amino acids (Arg+, Lys+ and His+) are the strongest residue-residue interactions. However, this type of interaction may be weakened by solvation effects and broken by lower pH conditions. (2) The cation- interactions between protonated amino acids (Arg+, Lys+ and His+) and aromatic amino acids (Phe, Tyr, Trp and His) are 2.5 to 5-fold stronger than common hydrogen bond interactions and are less affected by the solvation environment. (3) The amide bridge interactions between the two amide-containing amino acids (Asn and Gln) are three times stronger than hydrogen bond interactions, which are less influenced by the pH of the solution. (4) Ten of the twenty natural amino acids are involved in salt bridge, or cation-, or amide bridge interactions that often play important roles in protein-protein, protein-peptide, protein-ligand, and protein-DNA interactions.

Indexed as

Drug DesignMolecular Docking SimulationAmidesAntiviral AgentsCationsHepacivirusHydrogen BondingHydrogen-Ion ConcentrationInfluenza A virusLigandsNeuraminidaseProtein BindingProtein Interaction Domains and MotifsQuantum TheoryThermodynamicsViral Matrix ProteinsAmidesAntiviral AgentsCationsLigandsM2 protein, Influenza A virusNeuraminidasep7 protein, Hepatitis C virusViral Matrix ProteinsViral ProteinsViroporin Proteins

Identifiers

PMID26339784
PMCPMC4560430
OpenAlexW2206846584

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.