scholarly journals SARS-CoV-2 structural coverage map reveals state changes that disrupt host immunity

2020 ◽  
Author(s):  
Seán I. O’Donoghue ◽  
Andrea Schafferhans ◽  
Neblina Sikta ◽  
Christian Stolte ◽  
Sandeep Kaur ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Viral Protein ◽  
Molecular Mechanisms ◽  
3D Structure ◽  
Structural Data ◽  
3D Models ◽  
Host Immune Responses ◽  
One Stop ◽  
Structural Coverage ◽  
Coverage Map

AbstractIn response to the COVID-19 pandemic, many life scientists are focused on SARS-CoV-2. To help them use available structural data, we systematically modeled all viral proteins using all related 3D structures, generating 872 models that provide detail not available elsewhere. To organise these models, we created a structural coverage map: a novel, one-stop visualization summarizing what is — and is not — known about the 3D structure of the viral proteome. The map highlights structural evidence for viral protein interactions, mimicry, and hijacking; it also helps researchers find 3D models of interest, which can then be mapped with UniProt, PredictProtein, or CATH features. The resulting Aquaria-COVID resource (https://aquaria.ws/covid) helps scientists understand molecular mechanisms underlying coronavirus infection. Based on insights gained using our resource, we propose mechanisms by which the virus may enter immune cells, sense the cell type, then switch focus from viral reproduction to disrupting host immune responses.SignificanceCurrently, much of the COVID-19 viral proteome has unknown molecular structure. To improve this, we generated ∼1,000 structural models, designed to capture multiple states for each viral protein. To organise these models, we created a structure coverage map: a novel, one-stop visualization summarizing what is — and is not — known about viral protein structure. We used these data to create an online resource, designed to help COVID-19 researchers gain insight into the key molecular processes that drive infection. Based on insights gained using our resource, we speculate that the virus may sense the type of cells it infects and, within certain cells, it may switch from reproduction to disruption of the immune system.

scholarly journals Struct2Graph: A graph attention network for structure based predictions of protein-protein interactions

2020 ◽  
Author(s):  
Mayank Baranwal ◽  
Abram Magner ◽  
Jacob Saldinger ◽  
Emine S. Turali-Emre ◽  
Shivani Kozarekar ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Intracellular Signaling ◽  
Metabolic Regulation ◽  
Selection Process ◽  
3D Structure ◽  
Structural Data ◽  
Sequence Information ◽  
Protein Protein Interactions ◽  
Attention Network ◽  
Interaction Sites

AbstractDevelopment of new methods for analysis of protein-protein interactions (PPIs) at molecular and nanometer scales gives insights into intracellular signaling pathways and will improve understanding of protein functions, as well as other nanoscale structures of biological and abiological origins. Recent advances in computational tools, particularly the ones involving modern deep learning algorithms, have been shown to complement experimental approaches for describing and rationalizing PPIs. However, most of the existing works on PPI predictions use protein-sequence information, and thus have difficulties in accounting for the three-dimensional organization of the protein chains. In this study, we address this problem and describe a PPI analysis method based on a graph attention network, named Struct2Graph, for identifying PPIs directly from the structural data of folded protein globules. Our method is capable of predicting the PPI with an accuracy of 98.89% on the balanced set consisting of an equal number of positive and negative pairs. On the unbalanced set with the ratio of 1:10 between positive and negative pairs, Struct2Graph achieves a five-fold cross validation average accuracy of 99.42%. Moreover, unsupervised prediction of the interaction sites by Struct2Graph for phenol-soluble modulins are found to be in concordance with the previously reported binding sites for this family.Author summaryPPIs are the central part of signal transduction, metabolic regulation, environmental sensing, and cellular organization. Despite their success, most strategies to decode PPIs use sequence based approaches do not generalize to broader classes of chemical compounds of similar scale as proteins that are equally capable of forming complexes with proteins that are not based on amino acids, and thus lack of an equivalent sequence-based representation. Here, we address the problem of prediction of PPIs using a first of its kind, 3D structure based graph attention network (available at https://github.com/baranwa2/Struct2Graph). Despite its excellent prediction performance, the novel mutual attention mechanism provides insights into likely interaction sites through its knowledge selection process in a completely unsupervised manner.

scholarly journals SARS‐CoV‐2 structural coverage map reveals viral protein assembly, mimicry, and hijacking mechanisms

2021 ◽  
Vol 17 (9) ◽  
Author(s):  
Seán I O’Donoghue ◽  
Andrea Schafferhans ◽  
Neblina Sikta ◽  
Christian Stolte ◽  
Sandeep Kaur ◽  
...  
Keyword(s):  
Viral Protein ◽  
Protein Assembly ◽  
Structural Coverage ◽  
Coverage Map

scholarly journals Distinct Molecular Mechanisms of Host Immune Response Modulation by Arenavirus NP and Z Proteins

Viruses ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 784
Author(s):  
Robert J. Stott ◽  
Thomas Strecker ◽  
Toshana L. Foster
Keyword(s):  
Immune Responses ◽  
Protein Interactions ◽  
Molecular Mechanisms ◽  
Significant Risk ◽  
Host Protein ◽  
Response Modulation ◽  
Species Barrier ◽  
African Countries ◽  
Host Immune Responses ◽  
Cellular Pathways

Endemic to West Africa and South America, mammalian arenaviruses can cross the species barrier from their natural rodent hosts to humans, resulting in illnesses ranging from mild flu-like syndromes to severe and fatal haemorrhagic zoonoses. The increased frequency of outbreaks and associated high fatality rates of the most prevalent arenavirus, Lassa, in West African countries, highlights the significant risk to public health and to the socio-economic development of affected countries. The devastating impact of these viruses is further exacerbated by the lack of approved vaccines and effective treatments. Differential immune responses to arenavirus infections that can lead to either clearance or rapid, widespread and uncontrolled viral dissemination are modulated by the arenavirus multifunctional proteins, NP and Z. These two proteins control the antiviral response to infection by targeting multiple cellular pathways; and thus, represent attractive targets for antiviral development to counteract infection. The interplay between the host immune responses and viral replication is a key determinant of virus pathogenicity and disease outcome. In this review, we examine the current understanding of host immune defenses against arenavirus infections and summarise the host protein interactions of NP and Z and the mechanisms that govern immune evasion strategies.

scholarly journals 3D-GNOME 2.0: a three-dimensional genome modeling engine for predicting structural variation-driven alterations of chromatin spatial structure in the human genome

2020 ◽  
Vol 48 (W1) ◽  
pp. W170-W176
Author(s):  
Michal Wlasnowolski ◽  
Michal Sadowski ◽  
Tymon Czarnota ◽  
Karolina Jodkowska ◽  
Przemyslaw Szalaj ◽  
...  
Keyword(s):  
Human Genome ◽  
Conformational Changes ◽  
Genomic Sequence ◽  
Genome Structure ◽  
3D Structure ◽  
Three Dimensional ◽  
Structural Data ◽  
3D Models ◽  
3D Genome ◽  
The One

Abstract Structural variants (SVs) that alter DNA sequence emerge as a driving force involved in the reorganisation of DNA spatial folding, thus affecting gene transcription. In this work, we describe an improved version of our integrated web service for structural modeling of three-dimensional genome (3D-GNOME), which now incorporates all types of SVs to model changes to the reference 3D conformation of chromatin. In 3D-GNOME 2.0, the default reference 3D genome structure is generated using ChIA-PET data from the GM12878 cell line and SVs data are sourced from the population-scale catalogue of SVs identified by the 1000 Genomes Consortium. However, users may also submit their own structural data to set a customized reference genome structure, and/or a custom input list of SVs. 3D-GNOME 2.0 provides novel tools to inspect, visualize and compare 3D models for regions that differ in terms of their linear genomic sequence. Contact diagrams are displayed to compare the reference 3D structure with the one altered by SVs. In our opinion, 3D-GNOME 2.0 is a unique online tool for modeling and analyzing conformational changes to the human genome induced by SVs across populations. It can be freely accessed at https://3dgnome.cent.uw.edu.pl/.

scholarly journals Analyzing Effects of Naturally Occurring Missense Mutations

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Zhe Zhang ◽  
Maria A. Miteva ◽  
Lin Wang ◽  
Emil Alexov
Keyword(s):  
Amino Acid ◽  
Protein Stability ◽  
Protein Interactions ◽  
Molecular Mechanisms ◽  
Single Point ◽  
3D Structure ◽  
Genetic Mutation ◽  
Single Point Mutation ◽  
Missense Mutations ◽  
Single Nucleotide

Single-point mutation in genome, for example, single-nucleotide polymorphism (SNP) or rare genetic mutation, is the change of a single nucleotide for another in the genome sequence. Some of them will produce an amino acid substitution in the corresponding protein sequence (missense mutations); others will not. This paper focuses on genetic mutations resulting in a change in the amino acid sequence of the corresponding protein and how to assess their effects on protein wild-type characteristics. The existing methods and approaches for predicting the effects of mutation on protein stability, structure, and dynamics are outlined and discussed with respect to their underlying principles. Available resources, either as stand-alone applications or webservers, are pointed out as well. It is emphasized that understanding the molecular mechanisms behind these effects due to these missense mutations is of critical importance for detecting disease-causing mutations. The paper provides several examples of the application of 3D structure-based methods to model the effects of protein stability and protein-protein interactions caused by missense mutations as well.

NMR spectroscopy in the conformational analysis of peptides: an overview

2020 ◽  
Vol 27 ◽  
Author(s):  
Marian Vincenzi ◽  
Flavia Anna Mercurio ◽  
Marilisa Leone
Keyword(s):  
Nmr Spectroscopy ◽  
Protein Interactions ◽  
3D Structure ◽  
Theoretical Background ◽  
Triple Resonance ◽  
Protein Protein Interactions ◽  
Nmr Studies ◽  
Conformational Preferences ◽  
Dynamic Perspective ◽  
Nmr Methods

Background: NMR spectroscopy is one of the most powerful tools to study the structure and interaction properties of peptides and proteins from a dynamic perspective. Knowing the bioactive conformations of peptides is crucial in the drug discovery field to design more efficient analogue ligands and inhibitors of protein-protein interactions targeting therapeutically relevant systems. Objective: This review provides a toolkit to investigate peptide conformational properties by NMR. Methods: Articles cited herein, related to NMR studies of peptides and proteins were mainly searched through Pubmed and the web. More recent and old books on NMR spectroscopy written by eminent scientists in the field were consulted as well. Results: The review is mainly focused on NMR tools to gain the 3D structure of small unlabeled peptides. It is more application-oriented as it is beyond its goal to deliver a profound theoretical background. However, the basic principles of 2D homonuclear and heteronuclear experiments are briefly described. Protocols to obtain isotopically labeled peptides and principal triple resonance experiments needed to study them, are discussed as well. Conclusion: NMR is a leading technique in the study of conformational preferences of small flexible peptides whose structure can be often only described by an ensemble of conformations. Although NMR studies of peptides can be easily and fast performed by canonical protocols established a few decades ago, more recently we have assisted to tremendous improvements of NMR spectroscopy to investigate instead large systems and overcome its molecular weight limit.

scholarly journals Adhesion and Growth of Neuralized Mouse Embryonic Stem Cells on Parylene-C/SiO2 Substrates

Materials ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3174
Author(s):  
Alan F. Murray ◽  
Evangelos Delivopoulos
Keyword(s):  
Stem Cells ◽  
Embryonic Stem Cells ◽  
Protein Interactions ◽  
Molecular Mechanisms ◽  
Embryonic Stem ◽  
Mouse Embryonic Stem Cells ◽  
Primary Neurons ◽  
Tissue Engineering Scaffolds ◽  
Parylene C ◽  
Unexpected Outcome

Neuronal patterning on microfabricated architectures has developed rapidly over the past few years, together with the emergence of soft biocompatible materials and tissue engineering scaffolds. Previously, we introduced a patterning technique based on serum and the biopolymer parylene-C, achieving highly compliant growth of primary neurons and astrocytes on different geometries. Here, we expanded this technique and illustrated that neuralized cells derived from mouse embryonic stem cells (mESCs) followed stripes of variable widths with conformity equal to or higher than that of primary neurons and astrocytes. Our results indicate the presence of undifferentiated mESCs, which also conformed to the underlying patterns to a high degree. This is an exciting and unexpected outcome, as molecular mechanisms governing cell and ECM protein interactions are different in stem cells and primary cells. Our study enables further investigations into the development and electrophysiology of differentiating patterned neural stem cells.

scholarly journals Experimental Models of Hepatocellular Carcinoma—A Preclinical Perspective

Cancers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 3651
Author(s):  
Alexandru Blidisel ◽  
Iasmina Marcovici ◽  
Dorina Coricovac ◽  
Florin Hut ◽  
Cristina Adriana Dehelean ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Molecular Mechanisms ◽  
Prediction Models ◽  
3D Models ◽  
Experimental Models ◽  
Health Concern ◽  
Liver Carcinoma ◽  
Tumor Type

Hepatocellular carcinoma (HCC), the most frequent form of primary liver carcinoma, is a heterogenous and complex tumor type with increased incidence, poor prognosis, and high mortality. The actual therapeutic arsenal is narrow and poorly effective, rendering this disease a global health concern. Although considerable progress has been made in terms of understanding the pathogenesis, molecular mechanisms, genetics, and therapeutical approaches, several facets of human HCC remain undiscovered. A valuable and prompt approach to acquire further knowledge about the unrevealed aspects of HCC and novel therapeutic candidates is represented by the application of experimental models. Experimental models (in vivo and in vitro 2D and 3D models) are considered reliable tools to gather data for clinical usability. This review offers an overview of the currently available preclinical models frequently applied for the study of hepatocellular carcinoma in terms of initiation, development, and progression, as well as for the discovery of efficient treatments, highlighting the advantages and the limitations of each model. Furthermore, we also focus on the role played by computational studies (in silico models and artificial intelligence-based prediction models) as promising novel tools in liver cancer research.

Structure, Function, Involvement in Diseases and Targeting of 14-3-3 Proteins: An Update

2018 ◽  
Vol 25 (1) ◽  
pp. 5-21 ◽  
Author(s):  
Ylenia Cau ◽  
Daniela Valensin ◽  
Mattia Mori ◽  
Sara Draghi ◽  
Maurizio Botta
Keyword(s):  
Protein Interactions ◽  
Molecular Mechanisms ◽  
Physiological Role ◽  
Specific Protein ◽  
Protein Protein Interactions ◽  
Cellular Processes ◽  
Protein Partners ◽  
High Sequence Homology ◽  
Small Molecule Modulators

14-3-3 is a class of proteins able to interact with a multitude of targets by establishing protein-protein interactions (PPIs). They are usually found in all eukaryotes with a conserved secondary structure and high sequence homology among species. 14-3-3 proteins are involved in many physiological and pathological cellular processes either by triggering or interfering with the activity of specific protein partners. In the last years, the scientific community has collected many evidences on the role played by seven human 14-3-3 isoforms in cancer or neurodegenerative diseases. Indeed, these proteins regulate the molecular mechanisms associated to these diseases by interacting with (i) oncogenic and (ii) pro-apoptotic proteins and (iii) with proteins involved in Parkinson and Alzheimer diseases. The discovery of small molecule modulators of 14-3-3 PPIs could facilitate complete understanding of the physiological role of these proteins, and might offer valuable therapeutic approaches for these critical pathological states.

scholarly journals Proteomic Discovery of VEEV E2-Host Partner Interactions Identifies GRP78 Inhibitor HA15 as a Potential Therapeutic for Alphavirus Infections

Pathogens ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 283
Author(s):  
Michael D. Barrera ◽  
Victoria Callahan ◽  
Ivan Akhrymuk ◽  
Nishank Bhalla ◽  
Weidong Zhou ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Protein Trafficking ◽  
Viral Protein ◽  
Sindbis Virus ◽  
Encephalitis Virus ◽  
Host Proteins ◽  
Atp Production ◽  
Equine Encephalitis Virus ◽  
E2 Glycoprotein ◽  
Late Stages

Alphaviruses are a genus of the Togaviridae family and are widely distributed across the globe. Venezuelan equine encephalitis virus (VEEV) and eastern equine encephalitis virus (EEEV), cause encephalitis and neurological sequelae while chikungunya virus (CHIKV) and Sindbis virus (SINV) cause arthralgia. There are currently no approved therapeutics or vaccines available for alphaviruses. In order to identify novel therapeutics, a V5 epitope tag was inserted into the N-terminus of the VEEV E2 glycoprotein and used to identify host-viral protein interactions. Host proteins involved in protein folding, metabolism/ATP production, translation, cytoskeleton, complement, vesicle transport and ubiquitination were identified as VEEV E2 interactors. Multiple inhibitors targeting these host proteins were tested to determine their effect on VEEV replication. The compound HA15, a GRP78 inhibitor, was found to be an effective inhibitor of VEEV, EEEV, CHIKV, and SINV. VEEV E2 interaction with GRP78 was confirmed through coimmunoprecipitation and colocalization experiments. Mechanism of action studies found that HA15 does not affect viral RNA replication but instead affects late stages of the viral life cycle, which is consistent with GRP78 promoting viral assembly or viral protein trafficking.

Sign in / Sign up

Export Citation Format

Share Document