scholarly journals Synthetic Protein Circuits and Devices Based on Reversible Protein-Protein Interactions: An Overview

Life ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 1171
Author(s):  
Stefano Rosa ◽  
Chiara Bertaso ◽  
Paolo Pesaresi ◽  
Simona Masiero ◽  
Andrea Tagliani
Keyword(s):  
Protein Interactions ◽  
De Novo ◽  
Cell Metabolism ◽  
Building Blocks ◽  
New Drugs ◽  
Cell Physiology ◽  
Protein Protein Interactions ◽  
Genetic Circuits ◽  
Cellular Targets ◽  
Synthetic Protein

Protein-protein interactions (PPIs) contribute to regulate many aspects of cell physiology and metabolism. Protein domains involved in PPIs are important building blocks for engineering genetic circuits through synthetic biology. These domains can be obtained from known proteins and rationally engineered to produce orthogonal scaffolds, or computationally designed de novo thanks to recent advances in structural biology and molecular dynamics prediction. Such circuits based on PPIs (or protein circuits) appear of particular interest, as they can directly affect transcriptional outputs, as well as induce behavioral/adaptational changes in cell metabolism, without the need for further protein synthesis. This last example was highlighted in recent works to enable the production of fast-responding circuits which can be exploited for biosensing and diagnostics. Notably, PPIs can also be engineered to develop new drugs able to bind specific intra- and extra-cellular targets. In this review, we summarize recent findings in the field of protein circuit design, with particular focus on the use of peptides as scaffolds to engineer these circuits.

scholarly journals Amalgamation of 3D structure and sequence information for protein–protein interaction prediction

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Kanchan Jha ◽  
Sriparna Saha
Keyword(s):  
Amino Acids ◽  
Deep Learning ◽  
Protein Interactions ◽  
3D Structure ◽  
Protein Sequences ◽  
Building Blocks ◽  
New Drugs ◽  
Sequence Information ◽  
Protein Protein Interactions ◽  
Structure Information

Abstract Protein is the primary building block of living organisms. It interacts with other proteins and is then involved in various biological processes. Protein–protein interactions (PPIs) help in predicting and hence help in understanding the functionality of the proteins, causes and growth of diseases, and designing new drugs. However, there is a vast gap between the available protein sequences and the identification of protein–protein interactions. To bridge this gap, researchers proposed several computational methods to reveal the interactions between proteins. These methods merely depend on sequence-based information of proteins. With the advancement of technology, different types of information related to proteins are available such as 3D structure information. Nowadays, deep learning techniques are adopted successfully in various domains, including bioinformatics. So, current work focuses on the utilization of different modalities, such as 3D structures and sequence-based information of proteins, and deep learning algorithms to predict PPIs. The proposed approach is divided into several phases. We first get several illustrations of proteins using their 3D coordinates information, and three attributes, such as hydropathy index, isoelectric point, and charge of amino acids. Amino acids are the building blocks of proteins. A pre-trained ResNet50 model, a subclass of a convolutional neural network, is utilized to extract features from these representations of proteins. Autocovariance and conjoint triad are two widely used sequence-based methods to encode proteins, which are used here as another modality of protein sequences. A stacked autoencoder is utilized to get the compact form of sequence-based information. Finally, the features obtained from different modalities are concatenated in pairs and fed into the classifier to predict labels for protein pairs. We have experimented on the human PPIs dataset and Saccharomyces cerevisiae PPIs dataset and compared our results with the state-of-the-art deep-learning-based classifiers. The results achieved by the proposed method are superior to those obtained by the existing methods. Extensive experimentations on different datasets indicate that our approach to learning and combining features from two different modalities is useful in PPI prediction.

Target-Templated de novo Design of Macrocyclic D-/L-Peptides: Inhibitors of the PD-1/PD-L1 Interaction

2020 ◽  
Author(s):  
Salvador Guardiola ◽  
Monica Varese ◽  
Xavier Roig ◽  
Jesús Garcia ◽  
Ernest Giralt
Keyword(s):  
Protein Interactions ◽  
Cyclic Peptides ◽  
General Framework ◽  
Large Scale ◽  
De Novo ◽  
Inhibitory Effect ◽  
Original Text ◽  
Protein Protein Interactions ◽  
Retraction Notice ◽  
Pharmaceutical Properties

<p>NOTE: This preprint has been retracted by consensus from all authors. See the retraction notice in place above; the original text can be found under "Version 1", accessible from the version selector above.</p><p><br></p><p>------------------------------------------------------------------------</p><p><br></p><p>Peptides, together with antibodies, are among the most potent biochemical tools to modulate challenging protein-protein interactions. However, current structure-based methods are largely limited to natural peptides and are not suitable for designing target-specific binders with improved pharmaceutical properties, such as macrocyclic peptides. Here we report a general framework that leverages the computational power of Rosetta for large-scale backbone sampling and energy scoring, followed by side-chain composition, to design heterochiral cyclic peptides that bind to a protein surface of interest. To showcase the applicability of our approach, we identified two peptides (PD-<i>i</i>3 and PD-<i>i</i>6) that target PD-1, a key immune checkpoint, and work as protein ligand decoys. A comprehensive biophysical evaluation confirmed their binding mechanism to PD-1 and their inhibitory effect on the PD-1/PD-L1 interaction. Finally, elucidation of their solution structures by NMR served as validation of our <i>de novo </i>design approach. We anticipate that our results will provide a general framework for designing target-specific drug-like peptides.<i></i></p>

Target-Templated de novo Design of Macrocyclic D-/L-Peptides: Inhibitors of the PD-1/PD-L1 Interaction

2020 ◽  
Author(s):  
Salvador Guardiola ◽  
Monica Varese ◽  
Xavier Roig ◽  
Jesús Garcia ◽  
Ernest Giralt
Keyword(s):  
Protein Interactions ◽  
Cyclic Peptides ◽  
General Framework ◽  
Large Scale ◽  
De Novo ◽  
Inhibitory Effect ◽  
Original Text ◽  
Protein Protein Interactions ◽  
Retraction Notice ◽  
Pharmaceutical Properties

<p>NOTE: This preprint has been retracted by consensus from all authors. See the retraction notice in place above; the original text can be found under "Version 1", accessible from the version selector above.</p><p><br></p><p>------------------------------------------------------------------------</p><p><br></p><p>Peptides, together with antibodies, are among the most potent biochemical tools to modulate challenging protein-protein interactions. However, current structure-based methods are largely limited to natural peptides and are not suitable for designing target-specific binders with improved pharmaceutical properties, such as macrocyclic peptides. Here we report a general framework that leverages the computational power of Rosetta for large-scale backbone sampling and energy scoring, followed by side-chain composition, to design heterochiral cyclic peptides that bind to a protein surface of interest. To showcase the applicability of our approach, we identified two peptides (PD-<i>i</i>3 and PD-<i>i</i>6) that target PD-1, a key immune checkpoint, and work as protein ligand decoys. A comprehensive biophysical evaluation confirmed their binding mechanism to PD-1 and their inhibitory effect on the PD-1/PD-L1 interaction. Finally, elucidation of their solution structures by NMR served as validation of our <i>de novo </i>design approach. We anticipate that our results will provide a general framework for designing target-specific drug-like peptides.<i></i></p>

scholarly journals Interactome Analysis of KIN (Kin17) Shows New Functions of This Protein

2021 ◽  
Vol 43 (2) ◽  
pp. 767-781
Author(s):  
Vanessa Pinatto Gaspar ◽  
Anelise Cardoso Ramos ◽  
Philippe Cloutier ◽  
José Renato Pattaro Junior ◽  
Francisco Ferreira Duarte Junior ◽  
...  
Keyword(s):  
Dna Replication ◽  
Protein Interactions ◽  
Ribosome Biogenesis ◽  
Cell Metabolism ◽  
Cell Types ◽  
Protein Protein Interactions ◽  
Cellular Mechanisms ◽  
Cancerous Cell ◽  
First Time

KIN (Kin17) protein is overexpressed in a number of cancerous cell lines, and is therefore considered a possible cancer biomarker. It is a well-conserved protein across eukaryotes and is ubiquitously expressed in all cell types studied, suggesting an important role in the maintenance of basic cellular function which is yet to be well determined. Early studies on KIN suggested that this nuclear protein plays a role in cellular mechanisms such as DNA replication and/or repair; however, its association with chromatin depends on its methylation state. In order to provide a better understanding of the cellular role of this protein, we investigated its interactome by proximity-dependent biotin identification coupled to mass spectrometry (BioID-MS), used for identification of protein–protein interactions. Our analyses detected interaction with a novel set of proteins and reinforced previous observations linking KIN to factors involved in RNA processing, notably pre-mRNA splicing and ribosome biogenesis. However, little evidence supports that this protein is directly coupled to DNA replication and/or repair processes, as previously suggested. Furthermore, a novel interaction was observed with PRMT7 (protein arginine methyltransferase 7) and we demonstrated that KIN is modified by this enzyme. This interactome analysis indicates that KIN is associated with several cell metabolism functions, and shows for the first time an association with ribosome biogenesis, suggesting that KIN is likely a moonlight protein.

scholarly journals De novo design of a reversible phosphorylation-dependent switch for membrane targeting

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Leon Harrington ◽  
Jordan M. Fletcher ◽  
Tamara Heermann ◽  
Derek N. Woolfson ◽  
Petra Schwille
Keyword(s):  
Protein Interactions ◽  
Lipid Membrane ◽  
De Novo ◽  
Protein Localization ◽  
Protein Structures ◽  
Spatiotemporal Pattern ◽  
Membrane Targeting ◽  
Protein Protein Interactions ◽  
Reversible Phosphorylation ◽  
Potential Applications

AbstractModules that switch protein-protein interactions on and off are essential to develop synthetic biology; for example, to construct orthogonal signaling pathways, to control artificial protein structures dynamically, and for protein localization in cells or protocells. In nature, the E. coli MinCDE system couples nucleotide-dependent switching of MinD dimerization to membrane targeting to trigger spatiotemporal pattern formation. Here we present a de novo peptide-based molecular switch that toggles reversibly between monomer and dimer in response to phosphorylation and dephosphorylation. In combination with other modules, we construct fusion proteins that couple switching to lipid-membrane targeting by: (i) tethering a ‘cargo’ molecule reversibly to a permanent membrane ‘anchor’; and (ii) creating a ‘membrane-avidity switch’ that mimics the MinD system but operates by reversible phosphorylation. These minimal, de novo molecular switches have potential applications for introducing dynamic processes into designed and engineered proteins to augment functions in living cells and add functionality to protocells.

Swim-exercised mice show a decreased level of protein O-GlcNAcylation and expression of O-GlcNAc transferase in heart

2011 ◽  
Vol 111 (1) ◽  
pp. 157-162 ◽  
Author(s):  
Darrell D. Belke
Keyword(s):  
Protein Interactions ◽  
Contractile Function ◽  
Cell Physiology ◽  
Protein Protein Interactions ◽  
Training Exercise ◽  
General Protein ◽  
Exercise Induced ◽  
Glcnac Transferase ◽  
The Impact ◽  
Physiological Hypertrophy

Swim-training exercise in mice leads to cardiac remodeling associated with an improvement in contractile function. Protein O-linked N-acetylglucosamine ( O-GlcNAcylation) is a posttranslational modification of serine and threonine residues capable of altering protein-protein interactions affecting gene transcription, cell signaling pathways, and general cell physiology. Increased levels of protein O-GlcNAcylation in the heart have been associated with pathological conditions such as diabetes, ischemia, and hypertrophic heart failure. In contrast, the impact of physiological exercise on protein O-GlcNAcylation in the heart is currently unknown. Swim-training exercise in mice was associated with the development of a physiological hypertrophy characterized by an improvement in contractile function relative to sedentary mice. General protein O-GlcNAcylation was significantly decreased in swim-exercised mice. This effect was mirrored in the level of O-GlcNAcylation of individual proteins such as SP1. The decrease in protein O-GlcNAcylation was associated with a decrease in the expression of O-GlcNAc transferase (OGT) and glutamine-fructose amidotransferase (GFAT) 2 mRNA. O-GlcNAcase (OGA) activity was actually lower in swim-trained than sedentary hearts, suggesting that it did not contribute to the decreased protein O-GlcNAcylation. Thus it appears that exercise-induced physiological hypertrophy is associated with a decrease in protein O-GlcNAcylation, which could potentially contribute to changes in gene expression and other physiological changes associated with exercise.

scholarly journals Cytosolic localization and in vitro assembly of human de novo thymidylate synthesis complex

2020 ◽  
Author(s):  
Sharon Spizzichino ◽  
Dalila Boi ◽  
Giovanna Boumis ◽  
Roberta Lucchi ◽  
Francesca R. Liberati ◽  
...  
Keyword(s):  
Cancer Cells ◽  
Protein Interactions ◽  
De Novo ◽  
Proximity Ligation Assay ◽  
Protein Protein Interactions ◽  
Aggregation State ◽  
Entire Complex ◽  
The Individual ◽  
Thymidylate Synthesis

ABSTRACTDe novo thymidylate synthesis is a crucial pathway for normal and cancer cells. Deoxythymidine monophosphate (dTMP) is synthesized by the combined action of three enzymes: thymidylate synthase (TYMS), serine hydroxymethyltransferase (SHMT) and dihydrofolate reductase (DHFR), targets of widely used chemotherapeutics such as antifolates and 5-fluorouracil. These proteins translocate to the nucleus after SUMOylation and are suggested to assemble in this compartment into the thymidylate synthesis complex (dTMP-SC). We report the intracellular dynamics of the complex in lung cancer cells by in situ proximity ligation assay, showing that it is also detected in the cytoplasm. We have successfully assembled the dTMP synthesis complex in vitro, employing tetrameric SHMT1 and a bifunctional chimeric enzyme comprising human TYMS and DHFR. We show that the SHMT1 tetrameric state is required for efficient complex assembly, indicating that this aggregation state is evolutionary selected in eukaryotes to optimize protein-protein interactions. Lastly, our results on the activity of the complete thymidylate cycle in vitro, provide a useful tool to develop drugs targeting the entire complex instead of the individual components.

scholarly journals Interfacial Peptides as Affinity Modulating Agents of Protein-Protein Interactions

Biomolecules ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 106
Author(s):  
Pavel V. Ershov ◽  
Yuri V. Mezentsev ◽  
Alexis S. Ivanov
Keyword(s):  
Protein Interactions ◽  
Targeted Delivery ◽  
Protein Complexes ◽  
Protein Protein Interactions ◽  
Good Efficiency ◽  
Cellular Targets ◽  
Proteolytic Stability ◽  
Clinically Significant

The identification of disease-related protein-protein interactions (PPIs) creates objective conditions for their pharmacological modulation. The contact area (interfaces) of the vast majority of PPIs has some features, such as geometrical and biochemical complementarities, “hot spots”, as well as an extremely low mutation rate that give us key knowledge to influence these PPIs. Exogenous regulation of PPIs is aimed at both inhibiting the assembly and/or destabilization of protein complexes. Often, the design of such modulators is associated with some specific problems in targeted delivery, cell penetration and proteolytic stability, as well as selective binding to cellular targets. Recent progress in interfacial peptide design has been achieved in solving all these difficulties and has provided a good efficiency in preclinical models (in vitro and in vivo). The most promising peptide-containing therapeutic formulations are under investigation in clinical trials. In this review, we update the current state-of-the-art in the field of interfacial peptides as potent modulators of a number of disease-related PPIs. Over the past years, the scientific interest has been focused on following clinically significant heterodimeric PPIs MDM2/p53, PD-1/PD-L1, HIF/HIF, NRF2/KEAP1, RbAp48/MTA1, HSP90/CDC37, BIRC5/CRM1, BIRC5/XIAP, YAP/TAZ–TEAD, TWEAK/FN14, Bcl-2/Bax, YY1/AKT, CD40/CD40L and MINT2/APP.

scholarly journals DNA-mediated engineering of multicomponent enzyme crystals

2015 ◽  
Vol 112 (15) ◽  
pp. 4564-4569 ◽  
Author(s):  
Jeffrey D. Brodin ◽  
Evelyn Auyeung ◽  
Chad A. Mirkin
Keyword(s):  
Gold Nanoparticles ◽  
Protein Interactions ◽  
Building Blocks ◽  
Inorganic Nanoparticles ◽  
Protein Protein Interactions ◽  
Dna Interactions ◽  
Interparticle Interactions ◽  
Crystalline Materials ◽  
Catalytically Active ◽  
Surface Chemistries

The ability to predictably control the coassembly of multiple nanoscale building blocks, especially those with disparate chemical and physical properties such as biomolecules and inorganic nanoparticles, has far-reaching implications in catalysis, sensing, and photonics, but a generalizable strategy for engineering specific contacts between these particles is an outstanding challenge. This is especially true in the case of proteins, where the types of possible interparticle interactions are numerous, diverse, and complex. Herein, we explore the concept of trading protein–protein interactions for DNA–DNA interactions to direct the assembly of two nucleic-acid–functionalized proteins with distinct surface chemistries into six unique lattices composed of catalytically active proteins, or of a combination of proteins and DNA-modified gold nanoparticles. The programmable nature of DNA–DNA interactions used in this strategy allows us to control the lattice symmetries and unit cell constants, as well as the compositions and habit, of the resulting crystals. This study provides a potentially generalizable strategy for constructing a unique class of materials that take advantage of the diverse morphologies, surface chemistries, and functionalities of proteins for assembling functional crystalline materials.

scholarly journals Caveolins and cavins in the trafficking, maturation, and degradation of caveolae: implications for cell physiology

2017 ◽  
Vol 312 (4) ◽  
pp. C459-C477 ◽  
Author(s):  
Anna R. Busija ◽  
Hemal H. Patel ◽  
Paul A. Insel
Keyword(s):  
Protein Interactions ◽  
Conformational Stability ◽  
Cell Physiology ◽  
Adapter Proteins ◽  
Scaffolding Proteins ◽  
Protein Protein Interactions ◽  
Outer Coat ◽  
Ligand Affinity ◽  
Cellular Changes ◽  
Raft Domains

Caveolins (Cavs) are ~20 kDa scaffolding proteins that assemble as oligomeric complexes in lipid raft domains to form caveolae, flask-shaped plasma membrane (PM) invaginations. Caveolae (“little caves”) require lipid-lipid, protein-lipid, and protein-protein interactions that can modulate the localization, conformational stability, ligand affinity, effector specificity, and other functions of proteins that are partners of Cavs. Cavs are assembled into small oligomers in the endoplasmic reticulum (ER), transported to the Golgi for assembly with cholesterol and other oligomers, and then exported to the PM as an intact coat complex. At the PM, cavins, ~50 kDa adapter proteins, oligomerize into an outer coat complex that remodels the membrane into caveolae. The structure of caveolae protects their contents (i.e., lipids and proteins) from degradation. Cellular changes, including signal transduction effects, can destabilize caveolae and produce cavin dissociation, restructuring of Cav oligomers, ubiquitination, internalization, and degradation. In this review, we provide a perspective of the life cycle (biogenesis, degradation), composition, and physiologic roles of Cavs and caveolae and identify unanswered questions regarding the roles of Cavs and cavins in caveolae and in regulating cell physiology.1

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