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1. Universal protein misfolding intermediates can bypass the proteostasis network and remain soluble and less functional

   https://doi.org/10.1038/s41467-022-30548-5  

   Nissley, Daniel A.; Jiang, Yang; Trovato, Fabio; Sitarik, Ian; Narayan, Karthik B.; To, Philip; Xia, Yingzi; Fried, Stephen D.; O’Brien, Edward P. (December 2022, Nature Communications)

   Abstract Some misfolded protein conformations can bypass proteostasis machinery and remain soluble in vivo. This is an unexpected observation, as cellular quality control mechanisms should remove misfolded proteins. Three questions, then, are: how do long-lived, soluble, misfolded proteins bypass proteostasis? How widespread are such misfolded states? And how long do they persist? We address these questions using coarse-grain molecular dynamics simulations of the synthesis, termination, and post-translational dynamics of a representative set of cytosolic E. coli proteins. We predict that half of proteins exhibit misfolded subpopulations that bypass molecular chaperones, avoid aggregation, and will not be rapidly degraded, with some misfolded states persisting for months or longer. The surface properties of these misfolded states are native-like, suggesting they will remain soluble, while self-entanglements make them long-lived kinetic traps. In terms of function, we predict that one-third of proteins can misfold into soluble less-functional states. For the heavily entangled protein glycerol-3-phosphate dehydrogenase, limited-proteolysis mass spectrometry experiments interrogating misfolded conformations of the protein are consistent with the structural changes predicted by our simulations. These results therefore provide an explanation for how proteins can misfold into soluble conformations with reduced functionality that can bypass proteostasis, and indicate, unexpectedly, this may be a wide-spread phenomenon. 

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2. Protein misfolding involving entanglements provides a structural explanation for the origin of stretched-exponential refolding kinetics

   https://doi.org/10.1126/sciadv.ads7379  

   Jiang, Yang; Xia, Yingzi; Sitarik, Ian; Sharma, Piyoosh; Song, Hyebin; Fried, Stephen D; O’Brien, Edward P (March 2025, Science Advances)

   Stretched-exponential protein refolding kinetics, first observed decades ago, were attributed to a nonnative ensemble of structures with parallel, non-interconverting folding pathways. However, the structural origin of the large energy barriers preventing interconversion between these folding pathways is unknown. Here, we combine simulations with limited proteolysis (LiP) and cross-linking (XL) mass spectrometry (MS) to study the protein phosphoglycerate kinase (PGK). Simulations recapitulate its stretched-exponential folding kinetics and reveal that misfolded states involving changes of entanglement underlie this behavior: either formation of a nonnative, noncovalent lasso entanglement or failure to form a native entanglement. These misfolded states act as kinetic traps, requiring extensive unfolding to escape, which results in a distribution of free energy barriers and pathway partitioning. Using LiP-MS and XL-MS, we propose heterogeneous structural ensembles consistent with these data that represent the potential long-lived misfolded states PGK populates. This structural and energetic heterogeneity creates a hierarchy of refolding timescales, explaining stretched-exponential kinetics. 

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3. Machine learning coarse-grained potentials of protein thermodynamics

   https://doi.org/10.1038/s41467-023-41343-1  

   Majewski, Maciej; Pérez, Adrià; Thölke, Philipp; Doerr, Stefan; Charron, Nicholas E; Giorgino, Toni; Husic, Brooke E; Clementi, Cecilia; Noé, Frank; De_Fabritiis, Gianni (December 2023, Nature Communications)

   Abstract A generalized understanding of protein dynamics is an unsolved scientific problem, the solution of which is critical to the interpretation of the structure-function relationships that govern essential biological processes. Here, we approach this problem by constructing coarse-grained molecular potentials based on artificial neural networks and grounded in statistical mechanics. For training, we build a unique dataset of unbiased all-atom molecular dynamics simulations of approximately 9 ms for twelve different proteins with multiple secondary structure arrangements. The coarse-grained models are capable of accelerating the dynamics by more than three orders of magnitude while preserving the thermodynamics of the systems. Coarse-grained simulations identify relevant structural states in the ensemble with comparable energetics to the all-atom systems. Furthermore, we show that a single coarse-grained potential can integrate all twelve proteins and can capture experimental structural features of mutated proteins. These results indicate that machine learning coarse-grained potentials could provide a feasible approach to simulate and understand protein dynamics. 

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4. To Kill or to Be Killed: How Does the Battle between the UPS and Autophagy Maintain the Intracellular Homeostasis in Eukaryotes?

   https://doi.org/10.3390/ijms24032221  

   Yu, Peifeng; Hua, Zhihua (February 2023, International Journal of Molecular Sciences)

   The ubiquitin-26S proteasome system and autophagy are two major protein degradation machineries encoded in all eukaryotic organisms. While the UPS is responsible for the turnover of short-lived and/or soluble misfolded proteins under normal growth conditions, the autophagy-lysosomal/vacuolar protein degradation machinery is activated under stress conditions to remove long-lived proteins in the forms of aggregates, either soluble or insoluble, in the cytoplasm and damaged organelles. Recent discoveries suggested an integrative function of these two seemly independent systems for maintaining the proteome homeostasis. One such integration is represented by their reciprocal degradation, in which the small 76-amino acid peptide, ubiquitin, plays an important role as the central signaling hub. In this review, we summarized the current knowledge about the activity control of proteasome and autophagosome at their structural organization, biophysical states, and turnover levels from yeast and mammals to plants. Through comprehensive literature studies, we presented puzzling questions that are awaiting to be solved and proposed exciting new research directions that may shed light on the molecular mechanisms underlying the biological function of protein degradation. 

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5. Martini 3 coarse-grained model of enzymes: Framework with validation by all-atom simulations and x-ray diffraction measurements

   https://doi.org/10.1063/5.0247634  

   Hooten, Mason; Murthy, N Sanjeeva; Pal, Nityananda; Khare, Sagar D; Gormley, Adam J; Dutt, Meenakshi (April 2025, The Journal of Chemical Physics)

   Recent experiments have shown that complexation with a stabilizing compound can preserve enzyme activity in harsh environments. Such complexation is believed to be driven by noncovalent interactions at the enzyme surface, including hydrophobicity and electrostatics. Molecular modeling of these interactions is costly at the all-atom scale due to the long time scales and large particle counts needed to characterize binding. Protein structure at the scale of amino acid residues is parsimoniously represented by a coarse-grained model in which one particle represents several atoms, significantly reducing the cost of simulation. Coarse-grained models may then be used to generate reduced surface descriptions to underlie detailed theories of surface adhesion. In this study, we present two coarse-grained enzyme models—lipase and dehalogenase—that have been prepared using the Martini 3 top-down modeling framework. We simulate each enzyme in aqueous solution and calculate the statistics of protein surface features and shape descriptors. The values from the coarse-grained data are compared with the same calculations performed on all-atom reference systems, revealing key similarities of surface chemistry at the two scales. Structural measures are calculated from the all-atom reference systems and compared with estimates from small-angle x-ray scattering experiments, with good agreement between the two. The described procedures of modeling and analysis comprise a framework for the development of coarse-grained models of protein surfaces with validation to experiment. 

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