scholarly journals Atg8-Family Proteins—Structural Features and Molecular Interactions in Autophagy and Beyond

Cells ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 2008 ◽  
Author(s):  
Nicole Wesch ◽  
Vladimir Kirkin ◽  
Vladimir V. Rogov
Keyword(s):  
Protein Interactions ◽  
Membrane Trafficking ◽  
Structural Features ◽  
Structural Level ◽  
Interacting Proteins ◽  
Therapeutic Approaches ◽  
Basic Principles ◽  
Interaction Partners ◽  
Shed Light

Autophagy is a common name for a number of catabolic processes, which keep the cellular homeostasis by removing damaged and dysfunctional intracellular components. Impairment or misbalance of autophagy can lead to various diseases, such as neurodegeneration, infection diseases, and cancer. A central axis of autophagy is formed along the interactions of autophagy modifiers (Atg8-family proteins) with a variety of their cellular counter partners. Besides autophagy, Atg8-proteins participate in many other pathways, among which membrane trafficking and neuronal signaling are the most known. Despite the fact that autophagy modifiers are well-studied, as the small globular proteins show similarity to ubiquitin on a structural level, the mechanism of their interactions are still not completely understood. A thorough analysis and classification of all known mechanisms of Atg8-protein interactions could shed light on their functioning and connect the pathways involving Atg8-proteins. In this review, we present our views of the key features of the Atg8-proteins and describe the basic principles of their recognition and binding by interaction partners. We discuss affinity and selectivity of their interactions as well as provide perspectives for discovery of new Atg8-interacting proteins and therapeutic approaches to tackle major human diseases.

scholarly journals Phylogenetic correlations can suffice to infer protein partners from sequences

2019 ◽  
Author(s):  
Guillaume Marmier ◽  
Martin Weigt ◽  
Anne-Florence Bitbol
Keyword(s):  
Protein Interactions ◽  
Evolutionary History ◽  
Sequence Data ◽  
Sequence Similarity ◽  
Interacting Proteins ◽  
Protein Protein Interactions ◽  
Coupling Analysis ◽  
Interaction Partners ◽  
Direct Coupling Analysis ◽  
Partner Proteins

AbstractDetermining which proteins interact together is crucial to a systems-level understanding of the cell. Recently, algorithms based on Direct Coupling Analysis (DCA) pairwise maximum-entropy models have allowed to identify interaction partners among the paralogs of ubiquitous prokaryotic proteins families, starting from sequence data alone. Since DCA allows to infer the three-dimensional structure of protein complexes, its success in predicting protein-protein interactions could be mainly based on contacting residues coevolving to remain physicochemically complementary. However, interacting proteins often possess similar evolutionary histories, which also gives rise to correlations among their sequences. What is the role of purely phylogenetic correlations in the performance of DCA-based methods to infer interaction partners? To address this question, we employ controlled synthetic data that only involves phylogeny and no interactions or contacts. We find that DCA accurately identifies the pairs of synthetic sequences that only share evolutionary history. It performs as well as methods explicitly based on sequence similarity, and even slightly better with large and accurate training sets. We further demonstrate the ability of these various methods to correctly predict pairings among actual paralogous proteins with genome proximity but no known direct physical interaction, which illustrates the importance of phylogenetic correlations in real data. However, for actually interacting and strongly coevolving proteins, DCA and mutual information outperform sequence similarity.Author summaryMany biologically important protein-protein interactions are conserved over evolutionary time scales. This leads to two different signals that can be used to computationally predict interactions between protein families and to identify specific interaction partners. First, the shared evolutionary history leads to highly similar phylogenetic relationships between interacting proteins of the two families. Second, the need to keep the interaction surfaces of partner proteins biophysically compatible causes a correlated amino-acid usage of interface residues. Employing simulated data, we show that the shared history alone can be used to detect partner proteins. Similar accuracies are achieved by algorithms comparing phylogenetic relationships and by coevolutionary methods based on Direct Coupling Analysis, which are a priori designed to detect the second type of signal. Using real sequence data, we show that in cases with shared evolutionary but without known physical interactions, both methods work with similar accuracy, while for physically interacting systems, methods based on correlated amino-acid usage outperform purely phylogenetic ones.

scholarly journals Statistical physics of interacting proteins: impact of dataset size and quality assessed in synthetic sequences

2019 ◽  
Author(s):  
Carlos A. Gandarilla-Pérez ◽  
Pierre Mergny ◽  
Martin Weigt ◽  
Anne-Florence Bitbol
Keyword(s):  
Protein Interactions ◽  
Statistical Physics ◽  
Sequence Data ◽  
Training Data ◽  
Interacting Proteins ◽  
Protein Protein Interactions ◽  
Interaction Partners ◽  
Dataset Size ◽  
Direct Coupling Analysis ◽  
Block Models

Identifying protein-protein interactions is crucial for a systems-level understanding of the cell. Recently, algorithms based on inverse statistical physics, e.g. Direct Coupling Analysis (DCA), have allowed to use evolutionarily related sequences to address two conceptually related inference tasks: finding pairs of interacting proteins, and identifying pairs of residues which form contacts between interacting proteins. Here we address two underlying questions: How are the performances of both inference tasks related? How does performance depend on dataset size and the quality? To this end, we formalize both tasks using Ising models defined over stochastic block models, with individual blocks representing single proteins, and inter-block couplings protein-protein interactions; controlled synthetic sequence data are generated by Monte-Carlo simulations. We show that DCA is able to address both inference tasks accurately when sufficiently large training sets of known interaction partners are available, and that an iterative pairing algorithm (IPA) allows to make predictions even without a training set. Noise in the training data deteriorates performance. In both tasks we find a quadratic scaling relating dataset quality and size that is consistent with noise adding in square-root fashion and signal adding linearly when increasing the dataset. This implies that it is generally good to incorporate more data even if its quality is imperfect, thereby shedding light on the empirically observed performance of DCA applied to natural protein sequences.

scholarly journals A short guided tour through functional and structural features of saposin-like proteins

2005 ◽  
Vol 389 (2) ◽  
pp. 249-257 ◽  
Author(s):  
Heike Bruhn
Keyword(s):  
Three Dimensional ◽  
Structural Features ◽  
Common Mechanism ◽  
Interacting Proteins ◽  
Sequence Variability ◽  
Cellular Functions ◽  
Phylogenetic Relations ◽  
Interaction Partners ◽  
Guided Tour ◽  
Lipid Interaction

SAPLIPs (saposin-like proteins) are a diverse family of lipid-interacting proteins that have various and only partly understood, but nevertheless essential, cellular functions. Their existence is conserved in phylogenetically most distant organisms, such as primitive protozoa and mammals. Owing to their remarkable sequence variability, a common mechanism for their actions is not known. Some shared principles beyond their diversity have become evident by analysis of known three-dimensional structures. Whereas lipid interaction is the basis for their functions, the special cellular tasks are often defined by interaction partners other than lipids. Based on recent findings, this review summarizes phylogenetic relations, function and structural features of the members of this family.

scholarly journals New factors for protein transport identified by a genome-wide CRISPRi screen in mammalian cells

2019 ◽  
Author(s):  
Laia Bassaganyas ◽  
Stephanie J. Popa ◽  
Max Horlbeck ◽  
Anupama Ashok ◽  
Sarah E. Stewart ◽  
...  
Keyword(s):  
Membrane Trafficking ◽  
Mammalian Cells ◽  
Secretory Pathway ◽  
Protein Transport ◽  
Basic Principles ◽  
Golgi Membranes ◽  
Genome Wide ◽  
A Genome ◽  
Powerful Strategy ◽  
Shed Light

AbstractProtein and membrane trafficking pathways are critical for cell and tissue homeostasis. Traditional genetic and biochemical approaches have shed light on basic principles underlying these processes. However, the list of factors required for secretory pathways function remains incomplete, and mechanisms involved in their adaptation poorly understood. Here, we present a powerful strategy based on a pooled genome-wide CRISPRi screen that allowed the identification of new factors involved in protein transport. Two newly identified factors, TTC17 and CCDC157, localized along the secretory pathway and were found to interact with resident proteins of ER-Golgi membranes. In addition, we uncovered that upon TTC17 knockdown, the polarized organization of Golgi cisternae was altered, creating glycosylation defects, and that CCDC157 is an important factor for the fusion of transport carriers to the Golgi complex. In conclusion, our work identified and characterized new actors in the mechanisms of protein transport and secretion, and opens stimulating perspectives for the use of our platform in physiological and pathological contexts.

scholarly journals Pseudokinases: From Allosteric Regulation of Catalytic Domains and the Formation of Macromolecular Assemblies to Emerging Drug Targets

Catalysts ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. 778 ◽  
Author(s):  
Andrada Tomoni ◽  
Jonathan Lees ◽  
Andrés G. Santana ◽  
Victor M. Bolanos-Garcia ◽  
Agatha Bastida
Keyword(s):  
Cell Proliferation ◽  
Protein Interactions ◽  
Drug Targets ◽  
Structural Features ◽  
Therapeutic Window ◽  
Amino Acid Residues ◽  
Protein Protein Interactions ◽  
Therapeutic Approaches ◽  
Macromolecular Assemblies ◽  
Catalytic Domains

Pseudokinases are a member of the kinase superfamily that lack one or more of the canonical residues required for catalysis. Protein pseudokinases are widely distributed across species and are present in proteins that perform a great diversity of roles in the cell. They represent approximately 10% to 40% of the kinome of a multicellular organism. In the human, the pseudokinase subfamily consists of approximately 60 unique proteins. Despite their lack of one or more of the amino acid residues typically required for the productive interaction with ATP and metal ions, which is essential for the phosphorylation of specific substrates, pseudokinases are important functional molecules that can act as dynamic scaffolds, competitors, or modulators of protein–protein interactions. Indeed, pseudokinase misfunctions occur in diverse diseases and represent a new therapeutic window for the development of innovative therapeutic approaches. In this contribution, we describe the structural features of pseudokinases that are used as the basis of their classification; analyse the interactome space of human pseudokinases and discuss their potential as suitable drug targets for the treatment of various diseases, including metabolic, neurological, autoimmune, and cell proliferation disorders.

Arab Translators’ Problems at the Discourse Level

Babel ◽  
2001 ◽  
Vol 47 (4) ◽  
pp. 304-322 ◽  
Author(s):  
Abdul-Fattah M. Jabr
Keyword(s):  
Text Analysis ◽  
Structural Features ◽  
Structural Level ◽  
Text Type ◽  
Text Types ◽  
Varient Selon ◽  
Shed Light

Abstract Arab translators, whether they be freelance or translator trainees, continue to encounter problems in translation from Arabic into English and vice versa at the textual and structural level. This is partly due to the sentence-based approach still favored and practiced by most translators and translation teachers. In addition, most of those translators seem to be unaware of the differences between the two languages and between different text types in terms of their textual and structural features. This paper attempts to shed light on such problems in three texts that represent three different text types. Two texts that are translated from Arabic into English and one text translated from English into Arabic have been analyzed. The text analysis has confirmed the tentative assumptions of the author. Arab translators are shown to have problems at thetextual and the structural level in both languages and different text types. It is also shown that such problems vary according to language and text type. Résumé Les traducteurs arabes, qu’ils soient indépendants ou en formation, ne cessent de rencontrer des problèmes de traductions de la langue arabe vers la langue anglaise et vice-versa tant au niveau textuel que structurel. Ceci est partiellement dû à l’approche encore en vogue et pratiquée par la plupart des traducteurs et des professeurs de traduction, notamment en se basant sur la phrase. En outre, la plupart de ces traducteurs semblent ne pas avoir conscience des différences entre les deux langues et des divers types de textes au point de vue de leurs caractéristiques textuelles et structurelles. Cet article tend á éclairer ce type de problèmes dans trois textes qui représentent trois types de textes différents. Ont été analysés deux textes traduits de la langue arabe vers la langue anglaise et l’un déux de la langue anglaise vers la langue arabe. L’analyse du texte a confirmé les suppositions provisoires de l’auteur. Les traducteurs arabes rencontrent des problèmes tant au niveau textuel que structurel dans le deux langues et les différents types de textes. Il est aussi démontré que ces problèmes varient selon la langue et le type de texte.

Basic principles for classification of equipment of energy facilities

2020 ◽  
Vol 13 (1) ◽  
pp. 4-10
Author(s):  
E. P. Grabchak ◽  
A. I. Vorobyev ◽  
S. V. Mischeryakov
Keyword(s):  
Basic Principles

Immune Checkpoint Inhibitors: Basics and Challenges

2019 ◽  
Vol 26 (17) ◽  
pp. 3009-3025 ◽  
Author(s):  
Bin Li ◽  
Ho Lam Chan ◽  
Pingping Chen
Keyword(s):  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Complete Response ◽  
Modern World ◽  
Basic Principles ◽  
Mutation Status ◽  
Anti Cancer ◽  
Cancer Types ◽  
Shed Light

Cancer is one of the most deadly diseases in the modern world. The last decade has witnessed dramatic advances in cancer treatment through immunotherapy. One extremely promising means to achieve anti-cancer immunity is to block the immune checkpoint pathways – mechanisms adopted by cancer cells to disguise themselves as regular components of the human body. Many review articles have described a variety of agents that are currently under extensive clinical evaluation. However, while checkpoint blockade is universally effective against a broad spectrum of cancer types and is mostly unrestricted by the mutation status of certain genes, only a minority of patients achieve a complete response. In this review, we summarize the basic principles of immune checkpoint inhibitors in both antibody and smallmolecule forms and also discuss potential mechanisms of resistance, which may shed light on further investigation to achieve higher clinical efficacy for these inhibitors.

Protein Interaction Domains and Post-Translational Modifications: Structural Features and Drug Discovery Applications

2020 ◽  
Vol 27 (37) ◽  
pp. 6306-6355 ◽  
Author(s):  
Marian Vincenzi ◽  
Flavia Anna Mercurio ◽  
Marilisa Leone
Keyword(s):  
Drug Discovery ◽  
Protein Interaction ◽  
Protein Interactions ◽  
Structural Information ◽  
Protein Complexes ◽  
Structural Features ◽  
Protein Protein Interactions ◽  
Modular Architecture ◽  
Post Translational Modifications ◽  
Interaction Domains

Background:: Many pathways regarding healthy cells and/or linked to diseases onset and progression depend on large assemblies including multi-protein complexes. Protein-protein interactions may occur through a vast array of modules known as protein interaction domains (PIDs). Objective:: This review concerns with PIDs recognizing post-translationally modified peptide sequences and intends to provide the scientific community with state of art knowledge on their 3D structures, binding topologies and potential applications in the drug discovery field. Method:: Several databases, such as the Pfam (Protein family), the SMART (Simple Modular Architecture Research Tool) and the PDB (Protein Data Bank), were searched to look for different domain families and gain structural information on protein complexes in which particular PIDs are involved. Recent literature on PIDs and related drug discovery campaigns was retrieved through Pubmed and analyzed. Results and Conclusion:: PIDs are rather versatile as concerning their binding preferences. Many of them recognize specifically only determined amino acid stretches with post-translational modifications, a few others are able to interact with several post-translationally modified sequences or with unmodified ones. Many PIDs can be linked to different diseases including cancer. The tremendous amount of available structural data led to the structure-based design of several molecules targeting protein-protein interactions mediated by PIDs, including peptides, peptidomimetics and small compounds. More studies are needed to fully role out, among different families, PIDs that can be considered reliable therapeutic targets, however, attacking PIDs rather than catalytic domains of a particular protein may represent a route to obtain selective inhibitors.

Skin and dry adhesion

2018 ◽  
Author(s):  
Changhyun Pang ◽  
Chanseok Lee ◽  
Hoon Eui Jeong ◽  
Kahp-Yang Suh
Keyword(s):  
Material Properties ◽  
Structural Features ◽  
Mechanical Interlocking ◽  
Multi Scale ◽  
Skin Patch ◽  
Reversible Adhesion ◽  
Dry Adhesion ◽  
Close Observation ◽  
Dry Adhesives ◽  
Shed Light

Close observation of various attachment systems in animal skins has revealed various exquisite multi-scale architectures for essential functions such as locomotion, crawling, mating, and protection from predators. Some of these adhesion systems of geckos and beetles have unique structural features (e.g. high-aspect ratio, tilted angle, and hierarchical nanostructure), resulting in mechanical interlocking mediated by van der Waals forces or liquid secretion (capillary force). In this chapter, we present an overview of recent advances in bio-inspired, artificial dry adhesives, and biomimetics in the context of nanofabrication and material properties. In addition, relevant bio-inspired structural materials, devices (clean transportation device, interlocker, biomedical skin patch, and flexible strain-gauge sensor) and microrobots are briefly introduced, which would shed light on future smart, directional, and reversible adhesion systems.

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