ArticleJournal of molecular biology2020
Mutations Strengthened SARS-CoV-2 Infectivity.
Article in Journal of molecular biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 318 papers.
What it found
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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.
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.
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Who cites it
318 citing papers in PubMed, 510 citations in OpenAlex.
- Persistent sheaf Laplacian analysis of protein stability and solubility changes upon mutation.Protein science : a publication of the Protein Society · 2026Article
- Persistent Stanley-Reisner Theory.Foundations of data science (Springfield, Mo.) · 2026Article
- An Emerging Global Threat After The COVID-19 Pandemic: Monkeypox Similarities and Differences.Polish journal of microbiology · 2026Review
- Topological data analysis and topological deep learning beyond persistent homology: a review.Artificial intelligence review · 2026Article
- Leveraging knowledge graphs and large language models for integrating molecular variants and clinical insights in COVID-19 research.Biosafety and health · 2026Article
- Optimizing computational prediction of shrimp-WSSV protein interactions through integration of homology- and topology-based predictions.Molecular genetics and genomics : MGG · 2026Article
- Structural Design and Immunogenicity of a Novel Self-Adjuvanting Mucosal Vaccine Candidate for SARS-CoV-2 Expressed in Plants.Plant biotechnology journal · 2026Article
- Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real-World Data.Advanced intelligent discovery · 2025Article
- A Review of Topological Data Analysis and Topological Deep Learning in Molecular Sciences.Journal of chemical information and modeling · 2025Review
- Modeling the Mutational Effects on Biochemical Phenotypes of SARS-CoV-2 Using Molecular Fields.Biomolecules · 2025Article
- Evolutionary Insight into Fatal Human Coronaviruses (hCoVs) with a Focus on Circulating SARS-CoV-2 Variants Under Monitoring (VUMs).Biomedicines · 2025Review
- Spatial Transcriptomics and Single Cell-RNASeq Reveals Cellular Heterogeneity of SARS-CoV-2 in Lung Tissues and Global Mutational Patterns in COVID-19 Patients.Journal of medical virology · 2025Article
- PERSISTENT DIRECTED FLAG LAPLACIAN.Foundations of data science (Springfield, Mo.) · 2025Article
- Prospects of Innovative Therapeutics in Combating the COVID-19 Pandemic.Molecular biotechnology · 2025Review
- Validation of a Traditional Medicine,Pharmaceuticals (Basel, Switzerland) · 2025Article
- Using Machine Learning to Analyze Molecular Dynamics Simulations of Biomolecules.The journal of physical chemistry. B · 2025Article
- A review of machine learning methods for imbalanced data challenges in chemistry.Chemical science · 2025Review
- Generative prediction of real-world prevalent SARS-CoV-2 mutation with in silico virus evolution.Briefings in bioinformatics · 2025Article
- Proteomic Learning of Gamma-Aminobutyric Acid (GABA) Receptor-Mediated Anesthesia.Journal of chemical information and modeling · 2025Article
- Mayer-Homology Learning Prediction of Protein-Ligand Binding Affinities.Journal of computational biophysics and chemistry · 2025Article
258 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infectivity is a major concern in coronavirus disease 2019 (COVID-19) prevention and economic reopening. However, rigorous determination of SARS-CoV-2 infectivity is very difficult owing to its continuous evolution with over 10,000 single nucleotide polymorphisms (SNP) variants in many subtypes. We employ an algebraic topology-based machine learning model to quantitatively evaluate the binding free energy changes of SARS-CoV-2 spike glycoprotein (S protein) and host angiotensin-converting enzyme 2 receptor following mutations. We reveal that the SARS-CoV-2 virus becomes more infectious. Three out of six SARS-CoV-2 subtypes have become slightly more infectious, while the other three subtypes have significantly strengthened their infectivity. We also find that SARS-CoV-2 is slightly more infectious than SARS-CoV according to computed S protein-angiotensin-converting enzyme 2 binding free energy changes. Based on a systematic evaluation of all possible 3686 future mutations on the S protein receptor-binding domain, we show that most likely future mutations will make SARS-CoV-2 more infectious. Combining sequence alignment, probability analysis, and binding free energy calculation, we predict that a few residues on the receptor-binding motif, i.e., 452, 489, 500, 501, and 505, have high chances to mutate into significantly more infectious COVID-19 strains.
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Registered trials
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.