Harnessing AI agents and human expertise, researchers accelerate the design of innovative nanobodies to combat evolving SARS-CoV-2 variants. Study: The Virtual Lab: AI Agents Design New SARS-CoV-2 Nanobodies with Experimental Validation . Image Credit: Shutterstock AI *Important notice: bioRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.
In a recent preprint posted to the bioRxiv preprint* server, researchers at Stanford University and the Chan Zuckerberg Biohub created a “Virtual Lab,” a research collaboration of artificial intelligence and humans, to design nanobody binders targeting the variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using a computational pipeline. They found that Virtual Lab could successfully design 92 new nanobodies, with two showing improved binding to recent SARS-CoV-2 variants, specifically the JN.1 and KP.
3 variants, serving as promising candidates for further investigation. Background Sophisticated agent roles in Virtual Lab: The Virtual Lab architecture includes distinct agents such as the Principal Investigator, Scientific Critic, and domain-specific experts (e.g.
, immunologists and computational biologists), facilitating interdisciplinary collaboration through structured team and individual meetings. Interdisciplinary science research requires collaborat.