Genome-wide collections of yeast strains, known as libraries, revolutionized the way systematic studies are carried out. Specifically, libraries that involve a cellular perturbation, such as the deletion collection, have facilitated key biological discoveries. However, short-term rewiring and long-term accumulation of suppressor mutations often obscure the functional consequences of such perturbations.
View Article and Find Full Text PDFProtein structures are essential to understanding cellular processes in molecular detail. While advances in artificial intelligence revealed the tertiary structure of proteins at scale, their quaternary structure remains mostly unknown. We devise a scalable strategy based on AlphaFold2 to predict homo-oligomeric assemblies across four proteomes spanning the tree of life.
View Article and Find Full Text PDFAn understanding of the forces shaping protein conservation is key, both for the fundamental knowledge it represents and to allow for optimal use of evolutionary information in practical applications. Sequence conservation is typically examined at one of two levels. The first is a residue-level, where intra-protein differences are analyzed and the second is a protein-level, where inter-protein differences are studied.
View Article and Find Full Text PDFStress granules (SGs) are stress-induced membraneless condensates that store non-translating mRNA and stalled translation initiation complexes. Although metazoan SGs are dynamic compartments where proteins can rapidly exchange with their surroundings, yeast SGs seem largely static. To gain a better understanding of yeast SGs, we identified proteins that sediment after heat shock using mass spectrometry.
View Article and Find Full Text PDFIn eukaryotes, disordered regions cover up to 50% of proteomes and mediate fundamental cellular processes. In contrast to globular domains, where about half of the amino acids are buried in the protein interior, disordered regions show higher solvent accessibility, which makes them prone to engage in non-functional interactions. Such interactions are exacerbated by the law of mass action, prompting the question of how they are minimized in abundant proteins.
View Article and Find Full Text PDFThe ability to measure the abundance and visualize the localization of proteins across the yeast proteome has stimulated hypotheses on gene function and fueled discoveries. While the classic C' tagged GFP yeast library has been the only resource for over a decade, the recent development of the SWAT technology has led to the creation of multiple novel yeast libraries where new-generation fluorescent reporters are fused at the N' and C' of open reading frames. Efficient access to these data requires a user interface to visualize and compare protein abundance, localization and co-localization across cells, strains, and libraries.
View Article and Find Full Text PDFHigh-throughput in vitro methods have been extensively applied to identify linear information that encodes peptide recognition. However, these methods are limited in number of peptides, sequence variation, and length of peptides that can be explored, and often produce solutions that are not found in the cell. Despite the large number of methods developed to attempt addressing these issues, the exhaustive search of linear information encoding protein-peptide recognition has been so far physically unfeasible.
View Article and Find Full Text PDFFor successful infection and propagation viruses must overcome many obstacles such as the immune system and entry into their host cells. HIV utilizes its trimeric envelope protein gp160, specifically the gp41 subunit, to enter its host cell. During this process, a gp41-central coiled coil is formed from three N- and three C-terminal heptad repeats, termed the six-helix bundle (SHB), which drives membrane fusion.
View Article and Find Full Text PDFLinear motifs mediate a wide variety of cellular functions, which makes their characterization in protein sequences crucial to understanding cellular systems. However, the short length and degenerate nature of linear motifs make their discovery a difficult problem. Here, we introduce MotifHound, an algorithm particularly suited for the discovery of small and degenerate linear motifs.
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