| 1. |
- Allison, Timothy M., et al.
(författare)
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Complementing machine learning‐based structure predictions with native mass spectrometry
- 2022
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Ingår i: Protein Science. - : John Wiley & Sons. - 0961-8368 .- 1469-896X. ; 31:6
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Tidskriftsartikel (refereegranskat)abstract
- The advent of machine learning-based structure prediction algorithms such as AlphaFold2 (AF2) and RoseTTa Fold have moved the generation of accurate structural models for the entire cellular protein machinery into the reach of the scientific community. However, structure predictions of protein complexes are based on user-provided input and may require experimental validation. Mass spectrometry (MS) is a versatile, time-effective tool that provides information on post-translational modifications, ligand interactions, conformational changes, and higher-order oligomerization. Using three protein systems, we show that native MS experiments can uncover structural features of ligand interactions, homology models, and point mutations that are undetectable by AF2 alone. We conclude that machine learning can be complemented with MS to yield more accurate structural models on a small and large scale.
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| 2. |
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| 3. |
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| 4. |
- Armenteros, Jose Juan Almagro, et al.
(författare)
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Detecting sequence signals in targeting peptides using deep learning
- 2019
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Ingår i: Life Science Alliance. - : LIFE SCIENCE ALLIANCE LLC. - 2575-1077. ; 2:5
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Tidskriftsartikel (refereegranskat)abstract
- In bioinformatics, machine learning methods have been used to predict features embedded in the sequences. In contrast to what is generally assumed, machine learning approaches can also provide new insights into the underlying biology. Here, we demonstrate this by presenting TargetP 2.0, a novel state-of-the-art method to identify N-terminal sorting signals, which direct proteins to the secretory pathway, mitochondria, and chloroplasts or other plastids. By examining the strongest signals from the attention layer in the network, we find that the second residue in the protein, that is, the one following the initial methionine, has a strong influence on the classification. We observe that two-thirds of chloroplast and thylakoid transit peptides have an alanine in position 2, compared with 20% in other plant proteins. We also note that in fungi and single-celled eukaryotes, less than 30% of the targeting peptides have an amino acid that allows the removal of the N-terminal methionine compared with 60% for the proteins without targeting peptide. The importance of this feature for predictions has not been highlighted before.
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| 5. |
- Attwood, Misty M.
(författare)
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Membrane-bound proteins : Characterization, evolution, and functional analysis
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Alpha-helical transmembrane proteins are important components of many essential cell processes including signal transduction, transport of molecules across membranes, protein and membrane trafficking, and structural and adhesion activities, amongst others. Their involvement in critical networks makes them the focus of interest in investigating disease pathways, as candidate drug targets, and in evolutionary analyses to identify homologous protein families and possible functional activities. Transmembrane (TM) proteins can be categorized into major groups based the same gross structure, i.e., the number of transmembrane helices, which are often correlated with specific functional activities, for example as receptors or transporters. The focus of this thesis was to analyze the evolution of the membrane proteome from the last holozoan common ancestor (LHCA) through metazoans to garner insight into the fundamental functional clusters that underlie metazoan diversity and innovation. Twenty-four eukaryotic proteomes were analyzed, with results showing more than 70% of metazoan transmembrane protein families have a pre-metazoan origin. In concert with that, we characterized the previously unstudied groups of human proteins with three, four, and five membrane-spanning regions (3TM, 4TM, and 5TM) and analyzed their functional activities, involvement in disease pathways, and unique characteristics. Combined, we manually curated and classified nearly 11% of the human transmembrane proteome with these three studies. The 3TM data set included 152 proteins, with nearly 45% that localize specifically to the endoplasmic reticulum (ER), and are involved in membrane biosynthesis and lipid biogenesis, proteins trafficking, catabolic processes, and signal transduction due to the large ionotropic glutamate receptor family. The 373 proteins identified in the 4TM data set are predominantly involved in transport activities, as well as cell communication and adhesion, and function as structural elements. The compact 5TM data set includes 58 proteins that engage in localization and transport activities, such as protein targeting, membrane trafficking, and vesicle transport. Notably, ~60% are identified as cancer prognostic markers that are associated with clinical outcomes of different tumour types. This thesis investigates the evolutionary origins of the human transmembrane proteome, characterizes formerly dark areas of the membrane proteome, and extends the fundamental knowledge of transmembrane proteins.
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| 6. |
- Baldassarre, Federico, et al.
(författare)
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GraphQA: Protein Model Quality Assessment using Graph Convolutional Networks
- 2020
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Ingår i: Bioinformatics. - : Oxford University Press. - 1367-4803 .- 1367-4811 .- 1460-2059. ; 37:3, s. 360-366
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Tidskriftsartikel (refereegranskat)abstract
- MotivationProteins are ubiquitous molecules whose function in biological processes is determined by their 3D structure. Experimental identification of a protein’s structure can be time-consuming, prohibitively expensive, and not always possible. Alternatively, protein folding can be modeled using computational methods, which however are not guaranteed to always produce optimal results.GraphQA is a graph-based method to estimate the quality of protein models, that possesses favorable properties such as representation learning, explicit modeling of both sequential and 3D structure, geometric invariance, and computational efficiency.ResultsGraphQA performs similarly to state-of-the-art methods despite using a relatively low number of input features. In addition, the graph network structure provides an improvement over the architecture used in ProQ4 operating on the same input features. Finally, the individual contributions of GraphQA components are carefully evaluated.Availability and implementationPyTorch implementation, datasets, experiments, and link to an evaluation server are available through this GitHub repository: github.com/baldassarreFe/graphqaSupplementary informationSupplementary material is available at Bioinformatics online.
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| 7. |
- Bano-Polo, Manuel, et al.
(författare)
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Charge Pair Interactions in Transmembrane Helices and Turn Propensity of the Connecting Sequence Promote Helical Hairpin Insertion
- 2013
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Ingår i: Journal of Molecular Biology. - : Elsevier. - 0022-2836 .- 1089-8638. ; 425:4, s. 830-840
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Tidskriftsartikel (refereegranskat)abstract
- alpha-Helical hairpins, consisting of a pair of closely spaced transmembrane (TM) helices that are connected by a short interfacial turn, are the simplest structural motifs found in multi-spanning membrane proteins. In naturally occurring hairpins, the presence of polar residues is common and predicted to complicate membrane insertion. We postulate that the pre-packing process offsets any energetic cost of allocating polar and charged residues within the hydrophobic environment of biological membranes. Consistent with this idea, we provide here experimental evidence demonstrating that helical hairpin insertion into biological membranes can be driven by electrostatic interactions between closely separated, poorly hydrophobic sequences. Additionally, we observe that the integral hairpin can be stabilized by a short loop heavily populated by turn-promoting residues. We conclude that the combined effect of TM-TM electrostatic interactions and tight turns plays an important role in generating the functional architecture of membrane proteins and propose that helical hairpin motifs can be acquired within the context of the Sec61 translocon at the early stages of membrane protein biosynthesis. Taken together, these data further underline the potential complexities involved in accurately predicting TM domains from primary structures.
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| 8. |
- Basile, Walter, 1980-, et al.
(författare)
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Difference in disorder between eukaryotes and prokaryotes is largely due to Serine in linker regions
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- In this study we ask what are the molecular properties that make eukaryotic proteins more disordered than prokaryotic ones. First, we show that on average eukaryotic proteins contain more amino acids that are promoting disorder. In particular the fraction of Serine residues is close to 8% of all residues in eukaryotes and less than 6% in prokaryotes. Second, we show that domains unique to eukaryotes and linker regions in eukaryotes are both more disordered and more abundant than corresponding regions in prokaryotic proteins. Serine is an important residue for post-translational modification and regulatory mechanisms. Therefore, we conclude that it is not unlikely that both the need for regulation in a complex eukaryotic cell and the increased amount of longer multi-domain proteins contribute to the higher intrinsic structural disorder in eukaryotic proteins.
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| 9. |
- Basile, Walter, et al.
(författare)
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High GC content causes orphan proteins to be intrinsically disordered
- 2017
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Ingår i: PloS Computational Biology. - : Public Library of Science (PLoS). - 1553-734X .- 1553-7358. ; 13:3
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Tidskriftsartikel (refereegranskat)abstract
- De novo creation of protein coding genes involves the formation of short ORFs from noncoding regions; some of these ORFs might then become fixed in the population These orphan proteins need to, at the bare minimum, not cause serious harm to the organism, meaning that they should for instance not aggregate. Therefore, although the creation of short ORFs could be truly random, the fixation should be subjected to some selective pressure. The selective forces acting on orphan proteins have been elusive, and contradictory results have been reported. In Drosophila young proteins are more disordered than ancient ones, while the opposite trend is present in yeast. To the best of our knowledge no valid explanation for this difference has been proposed. To solve this riddle we studied structural properties and age of proteins in 187 eukaryotic organisms. We find that, with the exception of length, there are only small differences in the properties between proteins of different ages. However, when we take the GC content into account we noted that it could explain the opposite trends observed for orphans in yeast (low GC) and Drosophila (high GC). GC content is correlated with codons coding for disorder promoting amino acids. This leads us to propose that intrinsic disorder is not a strong determining factor for fixation of orphan proteins. Instead these proteins largely resemble random proteins given a particular GC level. During evolution the properties of a protein change faster than the GC level causing the relationship between disorder and GC to gradually weaken.
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| 10. |
- Basile, Walter, 1980-
(författare)
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Orphan Genes Bioinformatics : Identification and properties of de novo created genes
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Even today, many genes are without any known homolog. These "orphans" are found in all species, from Viruses to Prokaryotes and Eukaryotes. For a portion of these genes, we might simply not have enough data to find homologs yet. Some of them are imported from taxonomically distant organisms via lateral transfer; others have homologs, but mutated beyond the point of recognition.However, a sizeable fraction of orphan genes is unambiguously created via "de novo" mechanisms. The study of such novel genes can contribute to our understanding of the emergence of functional novelty and the adaptation of species to new ecological niches.In this work, we first survey the field of orphan studies, and illustrate some of the common issues. Next, we analyze some of the intrinsic properties of orphans proteins, including secondary structure elements and Intrinsic Structural Disorder; specifically, we observe that in young proteins the relationship between these properties and the G+C content of their coding sequence is stronger than in older proteins.We then tackle some of the methodological problems often found in orphan studies. We find that using evolutionarily close species, and sensitive, state-of-the art homology recognition methods is instrumental to the identification of a set of orphans enriched in de novo created ones.Finally, we compare how intrinsic disorder is distributed in bacteria versus eukaryota. Eukaryotic proteins are longer and more disordered; the difference is to be attributed primarily to eukaryotic-specific domains and linker regions. In these sections of the proteins, a higher frequency of the disorder-promoting amino acid Serine can be observed in Eukaryotes.
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