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1. Protein folding and surface interaction phase diagrams in vitro and in cells

   https://doi.org/10.1002/1873-3468.14058  

   Gruebele, Martin (March 2021, FEBS Letters)

   Protein stability is subject to environmental perturbations such as pressure and crowding, as well as sticking to other macromolecules and quinary structure. Thus, the environment inside and outside the cell plays a key role in how proteins fold, interact, and function on the scale from a few molecules to macroscopic ensembles. This review discusses three aspects of protein phase diagrams: first, the relevance of phase diagrams to protein folding and functionin vitroand in cells; next, how the evolution of protein surfaces impacts on interaction phase diagrams; and finally, how phase separation plays a role on much larger length‐scales than individual proteins or oligomers, when liquid phase‐separated regions form to assist protein function and cell homeostasis. 

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2. Learning the shape of protein microenvironments with a holographic convolutional neural network

   https://doi.org/10.1073/pnas.2300838121  

   Pun, Michael N; Ivanov, Andrew; Bellamy, Quinn; Montague, Zachary; LaMont, Colin; Bradley, Philip; Otwinowski, Jakub; Nourmohammad, Armita (February 2024, Proceedings of the National Academy of Sciences)

   Proteins play a central role in biology from immune recognition to brain activity. While major advances in machine learning have improved our ability to predict protein structure from sequence, determining protein function from its sequence or structure remains a major challenge. Here, we introduce holographic convolutional neural network (H-CNN) for proteins, which is a physically motivated machine learning approach to model amino acid preferences in protein structures. H-CNN reflects physical interactions in a protein structure and recapitulates the functional information stored in evolutionary data. H-CNN accurately predicts the impact of mutations on protein stability and binding of protein complexes. Our interpretable computational model for protein structure–function maps could guide design of novel proteins with desired function. 

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3. Students authoring molecular case studies as a partial course‐based undergraduate research experience (CURE) for lab instruction

   https://doi.org/10.1002/bmb.21578  

   Riley, Kasandra J.; Vardar‐Ulu, Didem; Pollock, Elizabeth; Dutta, Shuchismita (September 2021, Biochemistry and Molecular Biology Education)

   Abstract Understanding the relationship between protein structure and function is a core‐learning goal in biochemistry. Students often struggle to visualize proteins as three‐dimensional objects that interact with other molecules to affect its biochemical consequences. We describe here a partial course‐based undergraduate research experiences that has students exploring protein structure and function hands‐on while authoring a molecular case study intended for others to use. 

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4. Structural motifs in protein cores and at protein–protein interfaces are different

   https://doi.org/10.1002/pro.3996  

   Hadarovich, Anna; Chakravarty, Devlina; Tuzikov, Alexander V.; Ben‐Tal, Nir; Kundrotas, Petras J.; Vakser, Ilya A. (November 2020, Protein Science)

   Abstract Structures of proteins and protein–protein complexes are determined by the same physical principles and thus share a number of similarities. At the same time, there could be differences because in order to function, proteins interact with other molecules, undergo conformations changes, and so forth, which might impose different restraints on the tertiary versus quaternary structures. This study focuses on structural properties of protein–protein interfaces in comparison with the protein core, based on the wealth of currently available structural data and new structure‐based approaches. The results showed that physicochemical characteristics, such as amino acid composition, residue–residue contact preferences, and hydrophilicity/hydrophobicity distributions, are similar in protein core and protein–protein interfaces. On the other hand, characteristics that reflect the evolutionary pressure, such as structural composition and packing, are largely different. The results provide important insight into fundamental properties of protein structure and function. At the same time, the results contribute to better understanding of the ways to dock proteins. Recent progress in predicting structures of individual proteins follows the advancement of deep learning techniques and new approaches to residue coevolution data. Protein core could potentially provide large amounts of data for application of the deep learning to docking. However, our results showed that the core motifs are significantly different from those at protein–protein interfaces, and thus may not be directly useful for docking. At the same time, such difference may help to overcome a major obstacle in application of the coevolutionary data to docking—discrimination of the intramolecular information not directly relevant to docking. 

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5. An expanded allosteric network in PTP1B by multitemperature crystallography, fragment screening, and covalent tethering

   https://doi.org/10.7554/elife.36307  

   Keedy, Daniel A; Hill, Zachary B; Biel, Justin T; Kang, Emily; Rettenmaier, T Justin; Brandão-Neto, José; Pearce, Nicholas M; von_Delft, Frank; Wells, James A; Fraser, James S (June 2018, eLife)

   Allostery is an inherent feature of proteins, but it remains challenging to reveal the mechanisms by which allosteric signals propagate. A clearer understanding of this intrinsic circuitry would afford new opportunities to modulate protein function. Here, we have identified allosteric sites in protein tyrosine phosphatase 1B (PTP1B) by combining multiple-temperature X-ray crystallography experiments and structure determination from hundreds of individual small-molecule fragment soaks. New modeling approaches reveal 'hidden' low-occupancy conformational states for protein and ligands. Our results converge on allosteric sites that are conformationally coupled to the active-site WPD loop and are hotspots for fragment binding. Targeting one of these sites with covalently tethered molecules or mutations allosterically inhibits enzyme activity. Overall, this work demonstrates how the ensemble nature of macromolecular structure, revealed here by multitemperature crystallography, can elucidate allosteric mechanisms and open new doors for long-range control of protein function. 

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