Cells are intricate systems that coordinate numerous molecular reactions to function properly. While the mechanisms of many of these individual processes are understood, their overall coordination remains largely mysterious. One aspect of the spatial organisation of the cell interior is compartmentalisation, and in recent years, membraneless organelles known as biomolecular condensates have emerged as important players in this process [1,2]. Unlike classical membrane-bound organelles, biomolecular condensates lack a membrane envelope and exhibit rapid assembly and disassembly. They are ubiquitous in cells [3], both in the cytoplasm and the nucleoplasm, and in many cases form through liquid-liquid phase separation, facilitated by multivalent and non-covalent interactions among biomolecules, such as proteins and/or nucleic acids [1,2].

Condensates have been found to play fundamental roles in reducing protein concentration noise within cells [4,5], orchestrating cell plasticity, sensing and transducing mechanical forces [6], and in general providing distinct environments to host biochemical reactions [7,8]. Additionally, the abnormal phase behavior of these condensates has implications in various pathologies. In particular, many biomolecular condensates mature over time into less dynamic structures and eventually undergo liquid-to-solid transitions to form aberrant protein aggregates linked to neurodegenerative diseases like Alzheimer's, Parkinson's, and amyotrophic lateral sclerosis [9-11].

The significance of biomolecular condensates has prompted quests to understand the molecular mechanisms driving phase separation and aggregation, attracting the attention of theorists from diverse disciplines, including physics, chemistry, and soft matter, who already possess tools to study biopolymers, droplets and emulsions. However, it has become apparent that the traditional equilibrium thermodynamic description of phase separation falls short in providing a quantitative understanding and making predictions for systems characterized by multiple components [12] and/or nonequilibrium biological activity [13-15]. Therefore, this emerging research field offers an avenue for exciting new theoretical advancements.

To advance our understanding of biomolecular condensates, multi-scale and multi-resolution theories and simulations are essential [16]. This workshop will discuss recent progress in three types of approaches to model biomolecular condensates: theoretical methods [17-20], physics-driven atomistic and coarse-grained simulations [21,22], and data-driven machine learning approaches [23,24]. While each one of these approaches contribute unique insights, there is a need to generalise them in order to establish connections across disparate scales, leading to the development of comprehensive multi-resolution models. These integrated approaches, in combination with well-characterised experiments, will collectively contribute to a comprehensive understanding of the driving forces behind biomolecular phase separation and aggregation.

This interdisciplinary field thus presents a unique opportunity for collaboration among physical chemists, soft matter physicists, bioinformaticians, and biologists. By exchanging concepts, knowledge, and expertise across these scientific communities, this workshop will allow us to collectively develop a new understanding of the properties, functions, and potential applications of biomolecular condensates that surpasses what can be achieved by each community individually.

Confirmed invited speakers: