scholarly journals Phylogenetic analysis of Harmonin homology domains

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Baptiste Colcombet-Cazenave ◽  
Karen Druart ◽  
Crystel Bonnet ◽  
Christine Petit ◽  
Olivier Spérandio ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Functional Divergence ◽  
Usher Syndrome ◽  
Alpha Helix ◽  
Amino Acid Sequences ◽  
Protein Protein Interactions ◽  
Helix Bundle ◽  
Sequence Features ◽  
Pathogenic Variants ◽  
Community Clustering

Abstract Background Harmonin Homogy Domains (HHD) are recently identified orphan domains of about 70 residues folded in a compact five alpha-helix bundle that proved to be versatile in terms of function, allowing for direct binding to a partner as well as regulating the affinity and specificity of adjacent domains for their own targets. Adding their small size and rather simple fold, HHDs appear as convenient modules to regulate protein–protein interactions in various biological contexts. Surprisingly, only nine HHDs have been detected in six proteins, mainly expressed in sensory neurons. Results Here, we built a profile Hidden Markov Model to screen the entire UniProtKB for new HHD-containing proteins. Every hit was manually annotated, using a clustering approach, confirming that only a few proteins contain HHDs. We report the phylogenetic coverage of each protein and build a phylogenetic tree to trace the evolution of HHDs. We suggest that a HHD ancestor is shared with Paired Amphipathic Helices (PAH) domains, a four-helix bundle partially sharing fold and functional properties. We characterized amino-acid sequences of the various HHDs using pairwise BLASTP scoring coupled with community clustering and manually assessed sequence features among each individual family. These sequence features were analyzed using reported structures as well as homology models to highlight structural motifs underlying HHDs fold. We show that functional divergence is carried out by subtle differences in sequences that automatized approaches failed to detect. Conclusions We provide the first HHD databases, including sequences and conservation, phylogenic trees and a list of HHD variants found in the auditory system, which are available for the community. This case study highlights surprising phylogenetic properties found in orphan domains and will assist further studies of HHDs. We unveil the implication of HHDs in their various binding interfaces using conservation across families and a new protein–protein surface predictor. Finally, we discussed the functional consequences of three identified pathogenic HHD variants involved in Hoyeraal-Hreidarsson syndrome and of three newly reported pathogenic variants identified in patients suffering from Usher Syndrome.

Bi-allelic mutations in TRAPPC2L result in a neurodevelopmental disorder and have an impact on RAB11 in fibroblasts

2018 ◽  
Vol 55 (11) ◽  
pp. 753-764 ◽  
Author(s):  
Miroslav P Milev ◽  
Claudio Graziano ◽  
Daniela Karall ◽  
Willemijn F E Kuper ◽  
Noraldin Al-Deri ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Membrane Trafficking ◽  
Neurodevelopmental Disorder ◽  
Febrile Illness ◽  
Missense Variant ◽  
Energy Status ◽  
Protein Protein Interactions ◽  
Neurodevelopmental Delay ◽  
Pathogenic Variants ◽  
Similar Phenotype

BackgroundThe combination of febrile illness-induced encephalopathy and rhabdomyolysis has thus far only been described in disorders that affect cellular energy status. In the absence of specific metabolic abnormalities, diagnosis can be challenging.ObjectiveThe objective of this study was to identify and characterise pathogenic variants in two individuals from unrelated families, both of whom presented clinically with a similar phenotype that included neurodevelopmental delay, febrile illness-induced encephalopathy and episodes of rhabdomyolysis, followed by developmental arrest, epilepsy and tetraplegia.MethodsWhole exome sequencing was used to identify pathogenic variants in the two individuals. Biochemical and cell biological analyses were performed on fibroblasts from these individuals and a yeast two-hybrid analysis was used to assess protein-protein interactions.ResultsProbands shared a homozygous TRAPPC2L variant (c.109G>T) resulting in a p.Asp37Tyr missense variant. TRAPPC2L is a component of transport protein particle (TRAPP), a group of multisubunit complexes that function in membrane traffic and autophagy. Studies in patient fibroblasts as well as in a yeast system showed that the p.Asp37Tyr protein was present but not functional and resulted in specific membrane trafficking delays. The human missense mutation and the analogous mutation in the yeast homologue Tca17 ablated the interaction between TRAPPC2L and TRAPPC10/Trs130, a component of the TRAPP II complex. Since TRAPP II activates the GTPase RAB11, we examined the activation state of this protein and found increased levels of the active RAB, correlating with changes in its cellular morphology.ConclusionsOur study implicates a RAB11 pathway in the aetiology of the TRAPPC2L disorder and has implications for other TRAPP-related disorders with similar phenotypes.

Protein–Protein Interactions Affect Alpha Helix Stability in Crowded Environments

2015 ◽  
Vol 119 (7) ◽  
pp. 2956-2967 ◽  
Author(s):  
Bryanne Macdonald ◽  
Shannon McCarley ◽  
Sundus Noeen ◽  
Alan E. van Giessen
Keyword(s):  
Protein Interactions ◽  
Alpha Helix ◽  
Protein Protein Interactions ◽  
Helix Stability ◽  
Crowded Environments

scholarly journals Bcl-2 and FKBP12 bind to IP3 and ryanodine receptors at overlapping sites: the complexity of protein–protein interactions for channel regulation

2015 ◽  
Vol 43 (3) ◽  
pp. 396-404 ◽  
Author(s):  
Tim Vervliet ◽  
Jan B. Parys ◽  
Geert Bultynck
Keyword(s):  
Protein Interactions ◽  
Hippocampal Neurons ◽  
Binding Protein ◽  
Ryanodine Receptors ◽  
B Cell Lymphoma ◽  
Experimental Models ◽  
Amino Acid Sequences ◽  
Protein Protein Interactions ◽  
Fk506 Binding Protein ◽  
Fk506 Binding Proteins

The 12- and 12.6-kDa FK506-binding proteins, FKBP12 (12-kDa FK506-binding protein) and FKBP12.6 (12.6-kDa FK506-binding protein), have been implicated in the binding to and the regulation of ryanodine receptors (RyRs) and inositol 1,4,5-trisphosphate receptors (IP3Rs), both tetrameric intracellular Ca2+-release channels. Whereas the amino acid sequences responsible for FKBP12 binding to RyRs are conserved in IP3Rs, FKBP12 binding to IP3Rs has been questioned and could not be observed in various experimental models. Nevertheless, conservation of these residues in the different IP3R isoforms and during evolution suggested that they could harbour an important regulatory site critical for IP3R-channel function. Recently, it has become clear that in IP3Rs, this site was targeted by B-cell lymphoma 2 (Bcl-2) via its Bcl-2 homology (BH)4 domain, thereby dampening IP3R-mediated Ca2+ flux and preventing pro-apoptotic Ca2+ signalling. Furthermore, vice versa, the presence of the corresponding site in RyRs implied that Bcl-2 proteins could associate with and regulate RyR channels. Recently, the existence of endogenous RyR–Bcl-2 complexes has been identified in primary hippocampal neurons. Like for IP3Rs, binding of Bcl-2 to RyRs also involved its BH4 domain and suppressed RyR-mediated Ca2+ release. We therefore propose that the originally identified FKBP12-binding site in IP3Rs is a region critical for controlling IP3R-mediated Ca2+ flux by recruiting Bcl-2 rather than FKBP12. Although we hypothesize that anti-apoptotic Bcl-2 proteins, but not FKBP12, are the main physiological inhibitors of IP3Rs, we cannot exclude that Bcl-2 could help engaging FKBP12 (or other FKBP isoforms) to the IP3R, potentially via calcineurin.

ChemInform Abstract: Design and Synthesis of Thienylpyridyl Garlands as Non-Peptidic Alpha Helix Mimetics and Potential Protein-Protein Interactions Disruptors.

ChemInform ◽  
2011 ◽  
Vol 42 (52) ◽  
pp. no-no
Author(s):  
Marcella De Giorgi ◽  
Anne Sophie Voisin-Chiret ◽  
Jana Sopkova-de Oliveira Santos ◽  
Filomena Corbo ◽  
Carlo Franchini ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Alpha Helix ◽  
Protein Protein Interactions ◽  
Design And Synthesis ◽  
Helix Mimetics

scholarly journals Computational and experimental studies of plasmodium falciparum protein PfAMA1 domain-II loop dynamics: implications in PfAMA1-PfRON2 binding event

2021 ◽  
Author(s):  
Suman Sinha ◽  
Anamika Biswas ◽  
Jagannath Mondal ◽  
Kalyaneswar Mandal
Keyword(s):  
Drug Discovery ◽  
Protein Interactions ◽  
Experimental Studies ◽  
Alpha Helix ◽  
Dynamics Simulation ◽  
Malarial Parasite ◽  
Titration Calorimetry ◽  
Protein Protein Interactions ◽  
Human Red Blood Cells ◽  
Developed Nations

Protein-protein interactions are interesting targets for various drug discovery campaigns. One such promising and therapeutically pertinent protein-protein complex is PfAMA1-PfRON2, which is involved in malarial parasite invasion into human red blood cells. A thorough understanding of the interactions between these macromolecular binding partners is absolutely necessary to design better therapeutics to fight against the age-old disease affecting mostly under-developed nations. Although crystal structures of several PfAMA1-PfRON2 complexes have been solved to understand the molecular interactions between these two proteins, the mechanistic aspects of the domain II loop-PfRON2 association is far from clear. The current work investigates a crucial part of the recognition event; i.e., how the domain II loop of PfAMA1 exerts its effect on the alpha helix of the PfRON2, thus influencing the overall kinetics of this intricate recognition phenomenon. To this end, we have conducted thorough computational investigation of the dynamics and free energetics of domain II loop closing processes using molecular dynamics simulation. The computational results are validated by systematic alanine substitutions of the PfRON2 peptide helix. The subsequent evaluation of the binding affinity of Ala-substituted PfRON2 peptide ligands by surface plasmon resonance (SPR) and isothermal titration calorimetry (ITC) provides a rank of the relative importance of the residues in context. Our combined (computational and experimental) investigation has revealed that the domain II loop of PfAMA1 is in fact responsible for arresting the PfRON2 molecule from egress, K2027 and D2028 of PfRON2 being the determinant residues for the capturing event. Our study provides a comprehensive understanding of the molecular recognition event between PfAMA1 and PfRON2, specifically in the post binding stage, which potentially can be utilized for drug discovery against malaria.

Protein–protein interaction site prediction through combining local and global features with deep neural networks

2019 ◽  
Author(s):  
Min Zeng ◽  
Fuhao Zhang ◽  
Fang-Xiang Wu ◽  
Yaohang Li ◽  
Jianxin Wang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Protein Interactions ◽  
Supplementary Information ◽  
Protein Protein Interactions ◽  
Global Features ◽  
Site Prediction ◽  
Sequence Features ◽  
Protein Protein Interaction ◽  
Contextual Features ◽  
Interaction Site Prediction

Abstract Motivation Protein–protein interactions (PPIs) play important roles in many biological processes. Conventional biological experiments for identifying PPI sites are costly and time-consuming. Thus, many computational approaches have been proposed to predict PPI sites. Existing computational methods usually use local contextual features to predict PPI sites. Actually, global features of protein sequences are critical for PPI site prediction. Results A new end-to-end deep learning framework, named DeepPPISP, through combining local contextual and global sequence features, is proposed for PPI site prediction. For local contextual features, we use a sliding window to capture features of neighbors of a target amino acid as in previous studies. For global sequence features, a text convolutional neural network is applied to extract features from the whole protein sequence. Then the local contextual and global sequence features are combined to predict PPI sites. By integrating local contextual and global sequence features, DeepPPISP achieves the state-of-the-art performance, which is better than the other competing methods. In order to investigate if global sequence features are helpful in our deep learning model, we remove or change some components in DeepPPISP. Detailed analyses show that global sequence features play important roles in DeepPPISP. Availability and implementation The DeepPPISP web server is available at http://bioinformatics.csu.edu.cn/PPISP/. The source code can be obtained from https://github.com/CSUBioGroup/DeepPPISP. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals The interactome: Predicting the protein-protein interactions in cells

2009 ◽  
Vol 14 (1) ◽  
pp. 1-22 ◽  
Author(s):  
Dariusz Plewczyński ◽  
Krzysztof Ginalski
Keyword(s):  
Protein Interactions ◽  
Three Dimensional ◽  
Short Review ◽  
Amino Acid Sequences ◽  
Protein Protein Interactions ◽  
Structure Information ◽  
Cellular Processes ◽  
Molecular Machinery ◽  
Genome Scale ◽  
In Cells

AbstractThe term Interactome describes the set of all molecular interactions in cells, especially in the context of protein-protein interactions. These interactions are crucial for most cellular processes, so the full representation of the interaction repertoire is needed to understand the cell molecular machinery at the system biology level. In this short review, we compare various methods for predicting protein-protein interactions using sequence and structure information. The ultimate goal of those approaches is to present the complete methodology for the automatic selection of interaction partners using their amino acid sequences and/or three dimensional structures, if known. Apart from a description of each method, details of the software or web interface needed for high throughput prediction on the whole genome scale are also provided. The proposed validation of the theoretical methods using experimental data would be a better assessment of their accuracy.

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