[SCAN] Tailor-made development of antiviral biopharmaceuticals: It's all about interactions!
Diana Lousa
When |
09 Oct, 2024
from
12:00 pm to 01:00 pm |
---|---|
Where | ITQB NOVA Auditorium |
Contact Name | Sandra Viegas |
Contact Email | sviegas@itqb.unl.pt |
Add event to your calendar | iCal |
Title: Tailor-made development of antiviral biopharmaceuticals: It's all about interactions!
Speaker: Diana Lousa
Affiliation: Protein Modelling Lab, ITQB NOVA
Abstract: The recent COVID-19 pandemic has highlighted the devastating consequences of unpreparedness for such events, not only on public health but also on social and economic levels. As it is not possible to accurately predict which virus(es) will cause the next pandemic(s), it is of utmost importance to find new solutions that allow the effective targeting of a broad range of viruses and have easy and cost-effective discovery, development, production and validation process trajectories.
Within the scope of the BioPlaTTAR project and EvaMobs projects, funded by the La Caixa oudantion and Horizon Europe, respectively, we have built an integrated platform for biopharmaceutical development, to quickly and efficiently respond to viral threats in a streamlined pipeline, ranging from rational design to in vivo validation. This pipeline starts from the computational design of a diverse set of protein leads that block targets on the viral surface; then takes these designs, produces them in a high-throughput expression platform, and selects top leads after several rounds of physical-chemical characterization and in vitro and in vivo validation of activity. This pipeline has been validated consecutive rounds of design and experimental evaluation leading to the development of several miniproteins that bind to the SARS-CoV-2 receptor binding domain with high affinity (in the low nm range) and were shown to neutralize this virus in high-throughput neutralization assays using ACE2-expressing cells. The combination of artificial intelligence and physics based modelling methods, as well as the close integration of computational and experimental data have been key factors for the consecutive improvement of this platform.