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Article

AI-driven prediction of SARS-CoV-2 variant binding trends from atomistic simulations.

The European physical journal. E, Soft matter - 6 Oct 2021

Capponi Sara, Wang Shangying, Navarro Erik J, Bianco Simone

Abstract excerpt

We present a novel technique to predict binding affinity trends between two molecules from atomistic molecular dynamics simulations. The technique uses a neural network algorithm applied to a series of images encoding the distance between two molecules in time. We demonstrate that our algorithm is capable of separating with high accuracy non-hydrophobic mutations with low binding affinity from those with high...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Source

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Identifiers

PMID: 34613523
DOI: 10.1140/epje/s10189-021-00119-5
PMCID: PMC8493367

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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