RNA viruses are prominently featured on the list of pathogens likely to cause future pandemics, making their study a high priority for global health. These viruses are responsible for a wide range of emerging diseases in humans, including COVID-19, Zika, Dengue, West Nile, Ebola, Chikungunya, and influenza, as well as slower-spreading diseases such as HIV and Hepatitis. Understanding their biology, transmission mechanisms, and pathogenesis is crucial for developing strategies to control, prevent, and treat these diseases.

To date, most therapeutic efforts against viruses have targeted their proteins. However, RNA viral proteins are highly prone to mutations due to the lack of proofreading during replication, allowing these viruses to easily evade vaccines and drugs (10.1038/s41573-023-00692-8). Viral RNA pose attractive alternative therapeutic targets (10.1002/wrna.1373) to viral proteins because there are highly conserved RNA with much less relative mutations than the protein counterparts. Consequently, there is an urgent need to understand the complex RNA machinery of these viruses and its interplay with viral functions and pathogenicity. This workshop will focus on the biophysical modeling of RNA viruses, spanning from the molecular scale to the mesoscopic level, while maintaining a strong interaction with experimental approaches and medical applications.

While significant progress has been made toward this goal, several challenges remain. For instance, molecular simulations of RNAs are notoriously difficult: existing force fields, despite substantial improvements over the past decade, often fail to provide consistent results for a given RNA system (10.1016/j.bpj.2022.12.022). Additionally, the RNA conformational landscape, especially in viruses, is vast and difficult to sample with current simulation techniques (10.1021/acs.chemrev.7b00427).

On the larger scale, the recognition between RNAs and partner proteins involved in translation as well as in capsid assembly are near the limits of what we can currently achieve with simulations. Because of the large size of the systems and of the presence of multiple partners, they often require the development of coarse-grained models and elaborate simulation approaches (10.1016/B978-0-12-821978-2.00118-5). Moreover, RNA being highly charged, physics and simulation techniques of charged polymers have to be applied, including long-range charge regulations and pH effects to study molecular recognition (10.1007/978-3-031-36815-8_1). 

A critical issue is the generally poor collaboration and dialogue between research groups from different communities, despite targeting the same objectives with various techniques. The goal of this workshop is to foster the creation of a new community of researchers from diverse fields, including experimental biophysics, virology, statistical physics, biophysical modeling, mathematical sciences, computer sciences, and chemistry to spread such collaborations. We will emphasize the synergy between experimental, computational, and theoretical approaches, with particular attention to the latest developments in AI, which are rapidly transforming some of these methodologies.