César A. Ramírez-Sarmiento

arXiv2026

Expanding Protein Structure Prediction into Conformational State Space

Recent AI advances have enabled protein structure prediction at near-experimental accuracy, largely solving the problem of identifying a dominant conformation from sequence. Many proteins, however, function as dynamic systems populating multiple conformational states with activity emerging from shifts in relative occupancy--an incomplete picture when reduced to one structure. Here, we argue that structure prediction should be reformulated as a state-space inference problem: recovering not one conformation's coordinates but accessible states, their energetic and kinetic relationships, context dependence, and responses to perturbations. We review emerging strategies--deep learning ensemble generators, physics-based simulations, and experimental constraints--and outline a roadmap toward state-space prediction.

q-bio.BM↗

arXiv2025

Computations Meet Experiments to Advance the Enzymatic Depolymerization of Plastics One Atom at a Time

Plastics are essential to modern life, yet poor disposal practices contribute to low recycling rates and environmental accumulation-biological degradation and by-product reuse offer a path to mitigate this global threat. This report highlights key insights, future challenges, and research priorities identified during the CECAM workshop "Computations Meet Experiments to Advance the Enzymatic Depolymerization of Plastics One Atom at a Time", held in Trieste from May 6-8, 2025. The workshop brought together an interdisciplinary community of scientists focused on advancing the sustainable use of plastics through enzyme-based degradation. A key point from the discussions is that many bottlenecks in enzymatic recycling arise not only from process engineering challenges, but also from a limited understanding of the underlying molecular mechanisms. We argue that constraints on economic viability and sustainability (e.g., harsh solvents, high temperatures, substrate crystallinity, pretreatments) can-and should-be addressed directly through enzyme design, provided these factors are understood at the molecular level, in synergy with process optimization. For this, it is essential to rely on the integration of experimental and computational approaches to uncover the molecular and mechanistic basis of enzymatic plastic degradation. We highlight how the small-format structure of the workshop, in line with the usual CECAM format, fostered a collaborative, friendly, and relaxed atmosphere. We hope this report encourages future initiatives and the formation of shared consortia to support an open, collaborative, and bio-based plastic recycling community.

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