CovMT: an interactive SARS-CoV-2 mutation tracker, with a focus on critical variants

Álam, Intikhab; Radovanović, Aleksandar; Incitti, Roberto; Kamau, Allan; Alarawi, Mohammed; Azhar, Esam I.; Gojobori, Takashi

doi:10.1016/s1473-3099(21)00078-5

Cited by 65 publications

(60 citation statements)

References 3 publications

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“…Viruses naturally accumulate mutations over time; since SARS-CoV-2 was first identified in China, thousands of mutations have been recorded [ 42 ]. The vast majority of these mutations have a little apparent impact on the viral infectivity but some give rise to lineages that are selected because they confer an advantage in transmission or carriage, and hence lead to a rapid rise in COVID-19 cases worldwide.…”

Section: Sars-cov-2 Variantsmentioning

confidence: 99%

Structural Evaluation of the Spike Glycoprotein Variants on SARS-CoV-2 Transmission and Immune Evasion

Salleh

Derrick

Deris

2021

IJMS

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The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presents significant social, economic and political challenges worldwide. SARS-CoV-2 has caused over 3.5 million deaths since late 2019. Mutations in the spike (S) glycoprotein are of particular concern because it harbours the domain which recognises the angiotensin-converting enzyme 2 (ACE2) receptor and is the target for neutralising antibodies. Mutations in the S protein may induce alterations in the surface spike structures, changing the conformational B-cell epitopes and leading to a potential reduction in vaccine efficacy. Here, we summarise how the more important variants of SARS-CoV-2, which include cluster 5, lineages B.1.1.7 (Alpha variant), B.1.351 (Beta), P.1 (B.1.1.28/Gamma), B.1.427/B.1.429 (Epsilon), B.1.526 (Iota) and B.1.617.2 (Delta) confer mutations in their respective spike proteins which enhance viral fitness by improving binding affinity to the ACE2 receptor and lead to an increase in infectivity and transmission. We further discuss how these spike protein mutations provide resistance against immune responses, either acquired naturally or induced by vaccination. This information will be valuable in guiding the development of vaccines and other therapeutics for protection against the ongoing coronavirus disease 2019 (COVID-19) pandemic.

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Section: Sars-cov-2 Variantsmentioning

confidence: 99%

Structural Evaluation of the Spike Glycoprotein Variants on SARS-CoV-2 Transmission and Immune Evasion

Salleh

Derrick

Deris

2021

IJMS

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“…Mutations in the spike protein's RBD region could potentially impact disease severity and treatment strategies. The top 10 RBD region mutations (data from CovMT, a COVID-19 virus mutation tracker system [ 42 ]) were structurally analyzed ( Figure 7 ). Among them, E484, S494, L452, S477, T478, N501, and N439 are either in direct contact with P2B-2F6 or in close proximity to the interaction site.…”

Section: Resultsmentioning

confidence: 99%

“…However, the E484K spike protein mutation decreased its binding affinity with both the WT and optimized P2B-2F6 antibodies. Some SARS-CoV-2 variants possess combination mutations such as E484K/N501Y and K417N/E484K/N501Y [ 42 ]. We also calculated the mutation energy between the combination spike mutants and the antibodies ( Table 3 ).…”

Section: Resultsmentioning

confidence: 99%

Rational optimization of a human neutralizing antibody of SARS-CoV-2

Chen

Lin

et al. 2021

Computers in Biology and Medicine

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SARS-CoV-2 has caused a worldwide epidemic of coronavirus disease 19 (COVID-19). Antibody drugs present an effective weapon for tens of millions of COVID-19 patients. Antibodies disrupting the interactions between the receptor-binding domain (RBD) of SARS-CoV-2 S protein and the angiotensin converting enzyme 2 (ACE2) effectively block SARS-CoV-2 cell entry into host cells. In order to rapidly develop more potent neutralizing antibodies, we utilized virtual scanning mutageneses and molecular dynamics simulations to optimize the antibody of P2B-2F6 isolated from single B cells of SARS-CoV-2 infected patients. Two potent P2B-2F6 mutants, namely H:V106R and H:V106R/H:P107Y, were found to possess higher binding affinities with the RBD domain of SARS-CoV-2 than others. Polar interactions are preferred near 106 and 107 paratope residues of the heavy chain. The mutations also increase the hydrogen-bonding network formed between the antibody and the RBD. Notably, the optimized antibodies possess potential neutralizing activity against the alarming SARS-CoV-2 variant of N501Y. This study provides insights into structure-based optimization of antibodies with higher affinity to the antigen. We hope that our proposed antibody mutants could contribute to the development of improved therapies against COVID-19.

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“…Undoubtedly, the analysis aiming to distinguish between advantageous and neutral mutations becomes important, and the present AI is thought to be useful for this purpose. Extensive data of mutations observed for SARS-CoV-2 have been published by various sources, e.g., Alam et al (2021) and COG-UK / Mutation Explorer (http:// http://sars2.cvr.gla.ac.uk/cog-uk/). Use of preformed BLSOMs for analyses of newly-obtained sequences One distinctive characteristic of SARS-CoV-2 is the rapid increase in sequence data, and GISAID has very recently added a new clade, GRY, which corresponds to variants originating in the UK and rapidly expanding worldwide.…”

Section: Mutations Responsible For Separation Into Clades and Their Subgroupsmentioning

confidence: 99%

Unsupervised explainable AI for the collective analysis of a massive number of genome sequences: various examples from the small genome of pandemic SARS-CoV-2 to the human genome

Ikemura

Iwasaki

Wada

et al. 2021

Preprint

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In genetics and related fields, huge amounts of data, such as genome sequences, are accumulating, and the use of artificial intelligence (AI) suitable for big data analysis has become increasingly important. Unsupervised AI that can reveal novel knowledge from big data without prior knowledge or particular models is highly desirable for analyses of genome sequences, particularly for obtaining unexpected insights. We have developed a batch-learning self-organizing map (BLSOM) for oligonucleotide compositions that can reveal various novel genome characteristics. Here, we explain the data mining by the BLSOM: unsupervised and explainable AI. As a specific target, we first selected SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) because a large number of the viral genome sequences have been accumulated via worldwide efforts. We analyzed more than 0.6 million sequences collected primarily in the first year of the pandemic. BLSOMs for short oligonucleotides (e.g., 4~6-mers) allowed separation into known clades, but longer oligonucleotides further increased the separation ability and revealed subgrouping within known clades. In the case of 15-mers, there is mostly one copy in the genome; thus, 15-mers appeared after the epidemic start could be connected to mutations. Because BLSOM is an explainable AI, BLSOM for 15-mers revealed the mutations that contributed to separation into known clades and their subgroups. After introducing the detailed methodological strategies, we explained BLSOMs for various topics. The tetranucleotide BLSOM for over 5 million 5-kb fragment sequences derived from almost all microorganisms currently available and its use in metagenome studies. We also explained BLSOMs for various eukaryotes, such as fishes, frogs and Drosophila species, and found a high separation ability among closely related species. When analyzing the human genome, we found evident enrichments in transcription factor-binding sequences (TFBSs) in centromeric and pericentromeric heterochromatin regions. The tDNAs (tRNA genes) were separated by the corresponding amino acid.

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CovMT: an interactive SARS-CoV-2 mutation tracker, with a focus on critical variants

Cited by 65 publications

References 3 publications

Structural Evaluation of the Spike Glycoprotein Variants on SARS-CoV-2 Transmission and Immune Evasion

Structural Evaluation of the Spike Glycoprotein Variants on SARS-CoV-2 Transmission and Immune Evasion

Rational optimization of a human neutralizing antibody of SARS-CoV-2

Unsupervised explainable AI for the collective analysis of a massive number of genome sequences: various examples from the small genome of pandemic SARS-CoV-2 to the human genome

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