Direct and indirect cooperation between temporal and parietal networks for invariant visual recognition

International audienc

Neural network models of cortical functions based on the computational properties of the cerebral cortex

International audienc

Design of Proteins Specifically Tailored to Bind to NS1 Protein from Variants of Dengue and Zika

<p>Viruses of the family <i>Flaviviridae </i>such as Dengue and Zika, are arboviruses endemic to the equatorial regions of Brazil, Asia and Africa. The global incidence of dengue fever is estimated between 100 and 400 million infections per year. The Zika virus is responsible for serious congenital diseases and the resurgence of Guillain-Barré syndrome. There is no treatment or vaccine for these diseases, and diagnosis remains difficult because only access to PCR can identify the virus and the variant. During infection, many viral proteins are found in the blood, including envelope proteins and nonstructural protein 1 (NS1). It has been identified as an early marker of the disease as well as a potential target for the development of vaccines and drugs. Recent developments have been made in the creation of anti-NS1 antibodies designed to interact with the widest possible range of flavivirus strains, with varying affinities and specificities. These new molecules for therapeutic purposes do not solve the problem of diagnosis: in fact, diseases such as dengue fever and zika are difficult to discern because they are present in the same regions and the symptoms caused are not very specific. As the complications can be serious, it is important to propose new diagnostic methods which identify precisely the virus, going as far as discrimination between variants. The objective of this project is to provide a library of antibodies capable of recognizing with high specificity the NS1 proteins of the different variants of dengue and Zika viruses. Specific NS1 Zika nanobodies were created in the laboratory by the Pasteur Institute, we predicted their three-dimensional structures from the sequence, and we compared the results of the <i>in vitro</i> affinity experiments carried out by the Institute with our <i>in silico</i> docking results. We have also identified a method based on machine learning and on the signature of the antigen-antibody contact which makes it possible to evaluate the quality of the interaction between an antibody and NS1, these methods have been tested on ns1-antibody complexes of the PDB. Our results indicate that it is relevant to apply these methods on nanobodies produced in the laboratory because the interactions with the antigen are similar. Once the binding site and the affinity have been predicted, the antibody sequence can be modified to modulate its specificity. Thus we aim to design new protein sequences for antibodies and nanobodies adapted specifically to bind to NS1 from variants of the two studied flavivirus.</p&gt