Evidence map›Paper›PMID 27420555›Full record

ArticleLangmuir : the ACS journal of surfaces and colloids2016

Binding Preferences of Amino Acids for Gold Nanoparticles: A Molecular Simulation Study.

Qing Shao, Carol K Hall

Abstract read
In one paragraph

Article in Langmuir : the ACS journal of surfaces and colloids, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

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3 · Its place in the literature

Who cites it

21 citing papers in PubMed.

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  11. Milk Protein Adsorption on Metallic Iron Surfaces.Nanomaterials (Basel, Switzerland) · 2023
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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

2 authors.

Qing ShaoDepartment of Chemical and Biomolecular Engineering, North Carolina State University , Raleigh, North Carolina 27695, United States.
Carol K HallDepartment of Chemical and Biomolecular Engineering, North Carolina State University , Raleigh, North Carolina 27695, United States.

Funding

Biotechnology Research Partnerships Renewal: Aggregation of Therapeutic ProteinsR01EB006006 · NIBIB · UNIVERSITY OF COLORADO · PI RANDOLPH, THEODORE W · 2006 to 2017
$7.2M
NIBIB NIH HHS R01 EB006006
6 · The paper itself

Abstract

A better understanding of the binding preference of amino acids for gold nanoparticles of different diameters could aid in the design of peptides that bind specifically to nanoparticles of a given diameter. Here we identify the binding preference of 19 natural amino acids for three gold nanoparticles with diameters of 1.0, 2.0, and 4.0 nm, and investigate the mechanisms that govern these preferences. We calculate potentials of mean force between 36 entities (19 amino acids and 17 side chains) and the three gold nanoparticles in explicit water using well-tempered metadynamics simulations. Comparing these potentials of mean force determines the amino acids' nanoparticle binding preferences and if these preferences are controlled by the backbone, the side chain, or both. Twelve amino acids prefer to bind to the 4.0 nm gold nanoparticle, and seven prefer to bind to the 2.0 nm one. We also use atomistic molecular dynamics simulations to investigate how water molecules near the nanoparticle influence the binding of the amino acids. The solvation shells of the larger nanoparticles have higher water densities than those of the smaller nanoparticles while the orientation distributions of the water molecules in the shells of all three nanoparticles are similar. The nanoparticle preferences of the amino acids depend on whether their binding free energy is determined mainly by their ability to replace or to reorient water molecules in the nanoparticle solvation shell. The amino acids whose binding free energy depends mainly on the replacement of water molecules are likely to prefer to bind to the largest nanoparticle and tend to have relatively simple side chain structures. Those whose binding free energy depends mainly on their ability to reorient water molecules prefer a smaller nanoparticle and tend to have more complex side chain structures.

Indexed as

Models, ChemicalAmino AcidsGoldMetal NanoparticlesAmino AcidsGold

Identifiers

PMID27420555
PMCPMC5538574

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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.