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Beta Sandwich-Like Folds: Sequences, Contacts, Classification of Invariant Substructures and Beta Sandwich Protein Grammar.
Methods Mol Biol
November 2024
Department of Mathematics, Rutgers University, Piscataway, NJ, USA.
This chapter addresses the following fundamental question: Do sequences of protein domains with sandwich architecture have common sequence characteristics even though they belong to different superfamilies and folds? The analysis was carried out in two stages: (1) determination of domain substructures shared by all sandwich proteins and (2) detection of common sequence characteristics within the substructures. Analysis of supersecondary structures in domains of proteins revealed two types of four-strand substructures that are common to sandwich proteins. At least one of these common substructures was found in proteins of 42 sandwich-like folds (per structural classification in the CATH database).
View Article and Find Full Text PDFAI-Predicted Protein Deformation Encodes Energy Landscape Perturbation.
Phys Rev Lett
August 2024
Center for Algorithmic and Robotized Synthesis, Institute for Basic Science, Ulsan 44919, South Korea.
AI algorithms have proven to be excellent predictors of protein structure, but whether and how much these algorithms can capture the underlying physics remains an open question. Here, we aim to test this question using the Alphafold2 (AF) algorithm: We use AF to predict the subtle structural deformation induced by single mutations, quantified by strain, and compare with experimental datasets of corresponding perturbations in folding free energy ΔΔG. Unexpectedly, we find that physical strain alone-without any additional data or computation-correlates almost as well with ΔΔG as state-of-the-art energy-based and machine-learning predictors.
View Article and Find Full Text PDFInventing Novel Protein Folds.
J Mol Biol
November 2024
Laboratory for Protein Design, Institute for Protein Research (IPR), Osaka University, Suita, Osaka 565-0871, Japan.
The vastness of unexplored protein fold universe remains a significant question. Through systematic de novo design of proteins with novel αβ-folds, we demonstrated that nature has only explored a tiny portion of the possible folds. Numerous possible protein folds are still untouched by nature.
View Article and Find Full Text PDFDeep-learning-based design of synthetic orthologs of SH3 signaling domains.
Cell Syst
August 2024
Pritzker School for Molecular Engineering, University of Chicago, Chicago, IL 60637, USA. Electronic address:
Evolution-based deep generative models represent an exciting direction in understanding and designing proteins. An open question is whether such models can learn specialized functional constraints that control fitness in specific biological contexts. Here, we examine the ability of generative models to produce synthetic versions of Src-homology 3 (SH3) domains that mediate signaling in the Sho1 osmotic stress response pathway of yeast.
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