CoV-AbDab: the coronavirus antibody database

Abstract Motivation The emergence of a novel strain of betacoronavirus, SARS-CoV-2, has led to a pandemic that has been associated with over 700 000 deaths as of August 5, 2020. Research is ongoing around the world to create vaccines and therapies to minimize rates of disease spread and mortality. Crucial to these efforts are molecular characterizations of neutralizing antibodies to SARS-CoV-2. Such antibodies would be valuable for measuring vaccine efficacy, diagnosing exposure and developing effective biotherapeutics. Here, we describe our new database, CoV-AbDab, which already contains data on over 1400 published/patented antibodies and nanobodies known to bind to at least one betacoronavirus. This database is the first consolidation of antibodies known to bind SARS-CoV-2 as well as other betacoronaviruses such as SARS-CoV-1 and MERS-CoV. It contains relevant metadata including evidence of cross-neutralization, antibody/nanobody origin, full variable domain sequence (where available) and germline assignments, epitope region, links to relevant PDB entries, homology models and source literature. Results On August 5, 2020, CoV-AbDab referenced sequence information on 1402 anti-coronavirus antibodies and nanobodies, spanning 66 papers and 21 patents. Of these, 1131 bind to SARS-CoV-2. Availabilityand implementation CoV-AbDab is free to access and download without registration at http://opig.stats.ox.ac.uk/webapps/coronavirus. Community submissions are encouraged. Supplementary information Supplementary data are available at Bioinformatics online.

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CoV-AbDab: the Coronavirus Antibody Database

10.1101/2020.05.15.077313 ◽

2020 ◽

Cited By ~ 5

Author(s):

Matthew I. J. Raybould ◽

Aleksandr Kovaltsuk ◽

Claire Marks ◽

Charlotte M. Deane

Keyword(s):

Preliminary Analysis ◽

Diagnostic Value ◽

Disease Spread ◽

Receptor Binding Domain ◽

Neutralising Antibodies ◽

Epitope Region ◽

Domain Sequence ◽

The World ◽

Potential Applications ◽

Homology Models

The emergence of a novel strain of betacoronavirus, SARS-CoV-2, has led to a pandemic that has been associated with hundreds of thousands of deaths. Research is ongoing around the world to create vaccines and therapies to minimise rates of disease spread and mortality. Crucial to these efforts are molecular characterisations of neutralising antibodies to SARS-CoV-2. Such antibodies would be valuable for measuring vaccine efficacy, diagnosing exposure, and developing effective biotherapeutics. Here, we describe our new database, CoV-AbDab, which already contains data on over 380 published/patented antibodies and nanobodies known to bind to at least one betacoronavirus. This database is the first consolidation of antibodies known to bind SARS-CoV-2 and other betacoronaviruses such as SARS-CoV-1 and MERS-CoV. We supply relevant metadata such as evidence of cross-neutralisation, antibody/nanobody origin, full variable domain sequence (where available) and germline assignments, epitope region, links to relevant PDB entries, homology models, and source literature. Our preliminary analysis exemplifies a spectrum of potential applications for the database, including identifying characteristic germline usage biases in receptor-binding domain antibodies and contextualising the diagnostic value of the SARS-CoV binding CDRH3s through comparison to over 500 million antibody sequences from SARS-CoV serologically naive individuals. Community submissions are invited to ensure CoV-AbDab is efficiently updated with the growing body of data analysing SARS-CoV-2. CoV-AbDab is freely available and downloadable on our website at http://opig.stats.ox.ac.uk/webapps/coronavirus.

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Protein residues determining interaction specificity in paralogous families

Bioinformatics ◽

10.1093/bioinformatics/btaa934 ◽

2020 ◽

Author(s):

Borja Pitarch ◽

Juan A G Ranea ◽

Florencio Pazos

Keyword(s):

Amino Acid ◽

Fine Tuning ◽

Supplementary Information ◽

Sequence Information ◽

Large Set ◽

Supplementary Data ◽

Sequence Alignments ◽

Multiple Sequence ◽

Multiple Sequence Alignments ◽

Protein Residues

Abstract Motivation Predicting the residues controlling a protein’s interaction specificity is important not only to better understand its interactions but also to design mutations aimed at fine-tuning or swapping them as well. Results In this work, we present a methodology that combines sequence information (in the form of multiple sequence alignments) with interactome information to detect that kind of residues in paralogous families of proteins. The interactome is used to define pairwise similarities of interaction contexts for the proteins in the alignment. The method looks for alignment positions with patterns of amino-acid changes reflecting the similarities/differences in the interaction neighborhoods of the corresponding proteins. We tested this new methodology in a large set of human paralogous families with structurally characterized interactions, and discuss in detail the results for the RasH family. We show that this approach is a better predictor of interfacial residues than both, sequence conservation and an equivalent ‘unsupervised’ method that does not use interactome information. Availability and implementation http://csbg.cnb.csic.es/pazos/Xdet/. Supplementary information Supplementary data are available at Bioinformatics online.

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COVID-19 mRNA vaccine induced antibody responses and neutralizing antibodies against three SARS-CoV-2 variants

10.21203/rs.3.rs-343388/v1 ◽

2021 ◽

Author(s):

Pinja Jalkanen ◽

Pekka Kolehmainen ◽

Hanni Häkkinen ◽

Moona Huttunen ◽

Paula Tähtinen ◽

...

Keyword(s):

Health Care Workers ◽

Neutralizing Antibodies ◽

Protective Immunity ◽

Antibody Responses ◽

Infection Rates ◽

Vaccine Candidates ◽

Care Workers ◽

Neutralization Titre ◽

The World ◽

Cross Neutralization

Abstract As SARS-CoV-2 has been circulating for over a year, dozens of vaccine candidates are under development or in clinical use. The BNT162b2 mRNA COVID-19 vaccine induces spike protein-specific neutralizing antibodies associated with protective immunity. The emergence of the B.1.1.7 and B.1.351 variants has raised concerns of reduced vaccine efficacy and increased re-infection rates. Here we show, that after the second dose, the sera of BNT162b2-vaccinated health care workers (n = 180) effectively neutralize the SARS-CoV-2 variant with the D614G substitution and the B.1.1.7 variant, whereas the neutralization of the B.1.351 variant is five-fold reduced. Despite the reduction, 92% of the vaccinees have a neutralization titre of >20 for the B.1.351 variant indicating some protection. The vaccinees’ neutralization titres exceeded those of recovered non-hospitalized COVID-19 patients. Our work provides strong evidence that the second dose of the BNT162b2 vaccine induces efficient cross-neutralization of SARS-CoV-2 variants currently circulating in the world.

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COVID-19 Pandemic: Experiences in China and Implications for its Prevention and Treatment Worldwide

Current Cancer Drug Targets ◽

10.2174/1568009620666200414151419 ◽

2020 ◽

Vol 20 (6) ◽

pp. 410-416 ◽

Cited By ~ 6

Author(s):

Ning-Ning Liu ◽

Jing-Cong Tan ◽

Jingquan Li ◽

Shenghui Li ◽

Yong Cai ◽

...

Keyword(s):

Clinical Characteristics ◽

International Community ◽

Disease Spread ◽

Global Dynamics ◽

The World ◽

Prevention And Treatment ◽

History Of

The outbreak of COVID-19 due to SARS-CoV-2 originally emerged in Wuhan in December 2019. As of March 22, 2020, the disease spread to 186 countries, with at least 305,275 confirmed cases. Although there has been a decline in the spread of the disease in China, the prevalence of COVID-19 around the world remains serious despite containment efforts undertaken by national authorities and the international community. In this article, we systematically review the brief history of COVID-19 and its epidemic and clinical characteristics, highlighting the strategies used to control and prevent the disease in China, which may help other countries respond to the outbreak. This pandemic emphasizes the need to be constantly alert to shifts in both the global dynamics and the contexts of individual countries, making sure that all are aware of which approaches are successful for the prevention, containment and treatment of new diseases, and being flexible enough to adapt the responses accordingly.

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ccNetViz: a WebGL-based JavaScript library for visualization of large networks

Bioinformatics ◽

10.1093/bioinformatics/btaa559 ◽

2020 ◽

Vol 36 (16) ◽

pp. 4527-4529

Author(s):

Ales Saska ◽

David Tichy ◽

Robert Moore ◽

Achilles Rasquinha ◽

Caner Akdas ◽

...

Keyword(s):

Systems Biology ◽

Complex Networks ◽

Open Source ◽

High Speed ◽

A Priori ◽

Supplementary Information ◽

Network Visualization ◽

Supplementary Data ◽

Web Based ◽

Flow Of Information

Abstract Summary Visualizing a network provides a concise and practical understanding of the information it represents. Open-source web-based libraries help accelerate the creation of biologically based networks and their use. ccNetViz is an open-source, high speed and lightweight JavaScript library for visualization of large and complex networks. It implements customization and analytical features for easy network interpretation. These features include edge and node animations, which illustrate the flow of information through a network as well as node statistics. Properties can be defined a priori or dynamically imported from models and simulations. ccNetViz is thus a network visualization library particularly suited for systems biology. Availability and implementation The ccNetViz library, demos and documentation are freely available at http://helikarlab.github.io/ccNetViz/. Supplementary information Supplementary data are available at Bioinformatics online.

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Epidemiological modeling in StochSS Live!

Bioinformatics ◽

10.1093/bioinformatics/btab061 ◽

2021 ◽

Author(s):

Richard Jiang ◽

Bruno Jacob ◽

Matthew Geiger ◽

Sean Matthew ◽

Bryan Rumsey ◽

...

Keyword(s):

Stochastic Model ◽

Epidemiological Model ◽

Supplementary Information ◽

Supplementary Data ◽

Web Based ◽

Epidemiological Modeling ◽

Modeling Simulation ◽

Wide Range ◽

Biochemical Systems

Abstract Summary We present StochSS Live!, a web-based service for modeling, simulation and analysis of a wide range of mathematical, biological and biochemical systems. Using an epidemiological model of COVID-19, we demonstrate the power of StochSS Live! to enable researchers to quickly develop a deterministic or a discrete stochastic model, infer its parameters and analyze the results. Availability and implementation StochSS Live! is freely available at https://live.stochss.org/ Supplementary information Supplementary data are available at Bioinformatics online.

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KEC: unique sequence search by K-mer exclusion

Bioinformatics ◽

10.1093/bioinformatics/btab196 ◽

2021 ◽

Author(s):

Pavel Beran ◽

Dagmar Stehlíková ◽

Stephen P Cohen ◽

Vladislav Čurn

Keyword(s):

Amino Acid ◽

Nucleic Acid ◽

Source Code ◽

Unique Sequence ◽

Supplementary Information ◽

Supplementary Data ◽

Laptop Computers ◽

Sequence Search ◽

Target Sequences ◽

Cross Reference

Abstract Summary Searching for amino acid or nucleic acid sequences unique to one organism may be challenging depending on size of the available datasets. K-mer elimination by cross-reference (KEC) allows users to quickly and easily find unique sequences by providing target and non-target sequences. Due to its speed, it can be used for datasets of genomic size and can be run on desktop or laptop computers with modest specifications. Availability and implementation KEC is freely available for non-commercial purposes. Source code and executable binary files compiled for Linux, Mac and Windows can be downloaded from https://github.com/berybox/KEC. Supplementary information Supplementary data are available at Bioinformatics online.

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CorGAT: a tool for the functional annotation of SARS-CoV-2 genomes

Bioinformatics ◽

10.1093/bioinformatics/btaa1047 ◽

2020 ◽

Author(s):

Matteo Chiara ◽

Federico Zambelli ◽

Marco Antonio Tangaro ◽

Pietro Mandreoli ◽

David S Horner ◽

...

Keyword(s):

Functional Annotation ◽

Ad Hoc ◽

State Of The Art ◽

Supplementary Information ◽

Genomic Sequences ◽

Supplementary Data ◽

Evolutionary Patterns ◽

Genomic Variants ◽

Art Methods ◽

Available Resources

Abstract Summary While over 200 000 genomic sequences are currently available through dedicated repositories, ad hoc methods for the functional annotation of SARS-CoV-2 genomes do not harness all currently available resources for the annotation of functionally relevant genomic sites. Here, we present CorGAT, a novel tool for the functional annotation of SARS-CoV-2 genomic variants. By comparisons with other state of the art methods we demonstrate that, by providing a more comprehensive and rich annotation, our method can facilitate the identification of evolutionary patterns in the genome of SARS-CoV-2. Availabilityand implementation Galaxy http://corgat.cloud.ba.infn.it/galaxy; software: https://github.com/matteo14c/CorGAT/tree/Revision_V1; docker: https://hub.docker.com/r/laniakeacloud/galaxy_corgat. Supplementary information Supplementary data are available at Bioinformatics online.

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UniBioDicts: Unified access to Biological Dictionaries

Bioinformatics ◽

10.1093/bioinformatics/btaa1065 ◽

2020 ◽

Author(s):

John Zobolas ◽

Vasundra Touré ◽

Martin Kuiper ◽

Steven Vercruysse

Keyword(s):

User Interface ◽

Life Science ◽

Biological Data ◽

Supplementary Information ◽

Supplementary Data ◽

Query Interface ◽

Controlled Vocabularies ◽

Search String ◽

Software Packages ◽

The Right

Abstract Summary We present a set of software packages that provide uniform access to diverse biological vocabulary resources that are instrumental for current biocuration efforts and tools. The Unified Biological Dictionaries (UniBioDicts or UBDs) provide a single query-interface for accessing the online API services of leading biological data providers. Given a search string, UBDs return a list of matching term, identifier and metadata units from databases (e.g. UniProt), controlled vocabularies (e.g. PSI-MI) and ontologies (e.g. GO, via BioPortal). This functionality can be connected to input fields (user-interface components) that offer autocomplete lookup for these dictionaries. UBDs create a unified gateway for accessing life science concepts, helping curators find annotation terms across resources (based on descriptive metadata and unambiguous identifiers), and helping data users search and retrieve the right query terms. Availability and implementation The UBDs are available through npm and the code is available in the GitHub organisation UniBioDicts (https://github.com/UniBioDicts) under the Affero GPL license. Supplementary information Supplementary data are available at Bioinformatics online.

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CONCUR: quick and robust calculation of codon usage from ribosome profiling data

Bioinformatics ◽

10.1093/bioinformatics/btaa733 ◽

2020 ◽

Author(s):

Michaela Frye ◽

Susanne Bornelöv

Keyword(s):

Codon Usage ◽

Ribosome Profiling ◽

Supplementary Information ◽

Supplementary Data ◽

Usage Analysis

Abstract Summary CONCUR is a standalone tool for codon usage analysis in ribosome profiling experiments. CONCUR uses the aligned reads in BAM format to estimate codon counts at the ribosome E-, P- and A-sites and at flanking positions. Availability and implementation CONCUR is written in Perl and is freely available at https://github.com/susbo/concur. Supplementary information Supplementary data are available at Bioinformatics online.

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