There is continued interest in predicting the structure of proteins either at the simplest level of identifying their fold class or persevering all the way to an atomic resolution structure. Protein folding methods have become very sophisticated and many successes have been recorded with claims to have solved the native structure of the protein. But for any given protein, there may be more than one solution. Many proteins can exist in one of the other two (or more) different forms and some populate multiple metastable states. Here, the two-state case is considered and the key structural changes that take place when the protein switches from one state to the other are identified. Analysis of these results show that hydrogen bonding patterns and hydrophobic contacts vary considerably between different conformers. Contrary to what has often been assumed previously, these two types of interaction operate essentially independently of one another. Core packing is critical for proper protein structure and function and it is shown that there are considerable changes in internal cavity volumes in many cases. The way in which these switches are made is fold dependent. Considerations such as these need to be taken into account in protein structure prediction.
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http://dx.doi.org/10.1080/07391102.2012.703062 | DOI Listing |
Simulating large molecular systems over long timescales requires force fields that are both accurate and efficient. In recent years, E(3) equivariant neural networks have lifted the tension between computational efficiency and accuracy of force fields, but they are still several orders of magnitude more expensive than established molecular mechanics (MM) force fields. Here, we propose Grappa, a machine learning framework to predict MM parameters from the molecular graph, employing a graph attentional neural network and a transformer with symmetry-preserving positional encoding.
View Article and Find Full Text PDFPlant Biotechnol J
January 2025
Institute of Plant Biotechnology and Cell Biology, Department of Applied Genetics and Cell Biology, University of Natural Resources and Life Sciences, Vienna, Austria.
The production of complex multimeric secretory immunoglobulins (SIgA) in Nicotiana benthamiana leaves is challenging, with significant reductions in complete protein assembly and consequently yield, being the most important difficulties. Expanding the physical dimensions of the ER to mimic professional antibody-secreting cells can help to increase yields and promote protein folding and assembly. Here, we expanded the ER in N.
View Article and Find Full Text PDFNat Chem
January 2025
Department of Biotechnology and Biomedicine, Technical University of Denmark, Kgs. Lyngby, Denmark.
Amyloid fibrils are highly stable misfolded protein assemblies that play an important role in several neurodegenerative and systemic diseases. Although structural information of the amyloid state is now abundant, mechanistic details about the misfolding process remain elusive. Inspired by the Φ-value analysis of protein folding, we combined experiments and molecular simulations to resolve amino-acid contacts and determine the structure of the transition-state ensemble-the rate-limiting step-for fibril elongation of PI3K-SH3 amyloid fibrils.
View Article and Find Full Text PDFIUCrJ
March 2025
Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, People's Republic of China.
Heat-shock protein 90 (HSP90) is a highly active molecular chaperone that plays a crucial role in cellular function. It facilitates the folding, assembly and stability of various oncogenic proteins, particularly kinases and transcription factors involved in regulating tumor growth and maintenance signaling pathways. Consequently, HSP90 inhibitors are being explored as drugs for cancer therapy.
View Article and Find Full Text PDFAm J Physiol Endocrinol Metab
January 2025
Turku PET Centre, University of Turku, FI-20520 Turku, Finland.
In this study, we investigated the impact of bariatric surgery on the adipose proteome to better understand the metabolic and cellular mechanisms underlying weight loss following the procedure. A total of 46 patients with severe obesity were included, with samples collected both before and after bariatric surgery. Additionally, 15 healthy, non-obese individuals who did not undergo surgery served as controls and were studied once.
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