Since the outbreak of Covid-19, a number of databases on coronaviruses have been created. However, there is none as yet that provide useful information such as the binding affinity (how tightly an antibody binds to the virus) and how coronavirus antibodies effectively kill the viruses.
In an effort to fill this gap, a group of scientists from IIT Madras pored through thousands of research articles related to coronaviruses from PubMed, a free resource that supports the search and retrieval of biomedical and life sciences literature. Information related to binding affinity and inhibitory concentration of neutralising antibodies was meticulously gathered from them. In addition, the amino acid sequence information of all coronavirus-related antibodies was included from a sequence database called CoV-AbDab.
The result was the creation of what researchers call Ab-CoV, a database of 1,780 coronavirus-related antibodies, including 211 nanobodies. The database additionally gives information about each antibody, such as how the antibody was obtained, which strain of virus it binds to and which part of the spike-protein (epitope) does it bind to.
Ab-CoV has a wide range of search and display options. Users can directly search and download based on antibody name, viral protein epitope, neutralised viral strain, antibody, nanobody, etc, says an article in the IIT-Madras’ publication, IIT-M TechTalk. The database also has an option to view the structures of antibody or viral protein as a 3D model.
The Ab-CoV database will be a vital resource for coronaviruses-related studies. The database also has the potential to assist researchers for antibody engineering, analysing immune escape for known and future variants of SARS-CoV-2, for computational studies of neutralising antibodies, to relate structural features with binding affinity specific to SARS-CoV-2, and for design of therapeutic interventions, says IIT-M TechTalk.
Some of the data in this database have already been used to understand the relationship between structural features and binding affinities of spike protein-antibody complexes as well as antibody repurposing. These studies have been published in Proteins: Structure, Function and Bioinformatics, and Scientific Reports, respectively by Prof. Gromiha and collaborators. This research was partially funded by The Robert Bosch Centre for Data Science and AI (RBCDSAI) at IIT Madras.
IIT-M TechTalk quotes, Prof. R. Sowdhamini, of the National Centre for Biological Sciences (NCBS), Tata Institute of Fundamental Research, Bengaluru, as saying that the AbCoV database “is a comprehensive and good collection of data, relevant for vaccine design.”
Sowdhamini observed that experimental data on 107 crystal structures and close to 1,500 antibody data have been employed as start points. Several relevant data, such as kinetic parameters of neutralising antibodies are also provided along with user-friendly search engines. Contents of this database will be a valuable resource for future design of antibodies.
The researchers who worked on this are Dr Puneet Rawat, Ms Divya Sharma, Dr R Prabakaran, Ms Fathima Ridha, Ms Mugdha Mohkhedkar, Dr Vani Janakiraman, and Prof. M Michael Gromiha from the Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, IIT Madras.