Understanding the penetrance of intrinsic protein disorder in rotavirus proteome

Kumar, Deepak; Singh, Ankur; Kumar, Prateek; Uversky, Vladimir N.; Rao, C. Durga; Giri, Rajanish

doi:10.1016/j.ijbiomac.2019.09.166

Cited by 25 publications

(19 citation statements)

References 144 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The disorder profile of the vaccine construct was generated using PONDR pool of four predictors (http://original.disprot. org/metapredictor.php) [37][38][39] and IUPRED 2A predictor [40] as described in our previous reports [41][42][43].…”

Section: Disorder Profile Generationmentioning

confidence: 99%

Exploring the SARS-CoV-2 structural proteins for multi-epitope vaccine development: an in-silico approach

Kumar

Saumya

et al. 2020

Expert Review of Vaccines

Self Cite

View full text Add to dashboard Cite

Introduction: The ongoing life-threatening pandemic of coronavirus disease 2019 (COVID-19) has extensively affected the world. During this global health crisis, it is fundamentally crucial to find strategies to combat SARS-CoV-2. Despite several efforts in this direction and continuing clinical trials, no vaccine has been approved for it yet. Methods: To find a preventive measure, we have computationally designed a multi-epitopic subunit vaccine using immuno-informatic approaches. Results: The structural proteins of SARS-CoV-2 involved in its survival and pathogenicity were used to predict antigenic epitopes. The antigenic epitopes were capable of eliciting a strong humoral as well as cellmediated immune response, our predictions suggest. The final vaccine was constructed by joining the all epitopes with specific linkers and to enhance their stability and immunogenicity. The physicochemical property of the vaccine was assessed. The vaccine 3D structure prediction and validation were done and docked with the human TLR-3 receptor. Furthermore, molecular dynamics simulations of the vaccine-TLR-3 receptor complex are employed to assess its dynamic motions and binding stability in-silico. Conclusion: Based on this study, we strongly suggest synthesizing this vaccine, which further can be tested in-vitro and in-vivo to check its potency in a cure for COVID-19.

show abstract

Section: Disorder Profile Generationmentioning

confidence: 99%

Exploring the SARS-CoV-2 structural proteins for multi-epitope vaccine development: an in-silico approach

Kumar

Saumya

et al. 2020

Expert Review of Vaccines

Self Cite

View full text Add to dashboard Cite

show abstract

“…The sequence of NSP1 C-terminal (residues 130-180) "NH2-AGGHSYGADLKSFDLGDELGTDPYEDFQENWNTKHSSGVTRELMRELNGG-COOH" was retrieved from the UniProt (ID: P0DTC1.1). As described earlier by our group, protein intrinsic disorder predictor, PONDR® VSL2 was used for analysis of intrinsic disorder properties of NSP1-CTR (2,13,14,19,26,27). The secondary structure predisposition analysis for NSP1-CTR was performed with several different web-servers pep2d, Jpred4, and PSIPRED (28-30).…”

Section: Phylogenetic Analysis Of Sars-cov-2 On the Basis Of Nsp1mentioning

confidence: 99%

“…For a period of time bioinformatics studies show the penetrance of IDPs in viruses and all domain of life from bacteria to eukaryotes (10)(11)(12)(13)(14). Recently, bioinformatics based study by our group showed that NSP1 of SARS-CoV-2 regions (amino acids 137-145 and 172-179) are identified as a molecular recognition feature (MoRFs) region (2).…”

Section: Introductionmentioning

confidence: 99%

SARS-CoV-2 NSP1 C-terminal region (residues 130-180) is an intrinsically disordered region

Kumar¹,

Kumar²,

Kumar³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

Nonstructural protein 1 (NSP1) of SARS-CoV-2 plays a key role in downregulation of RIG-I pathways and interacts with 40 S ribosome. Recently, the cryo-EM structure in complex with 40S ribosome is deciphered. However, the structure of full length NSP1 without any partner has not been studies. Also, the conformation of NSP1-C terminal region in isolation is not been studied. In this study, we have investigated the conformational dynamics of NSP1C-terminal region (NSP1-CTR; amino acids 130-180) in isolation and under different solvent environments. The NSP1-CTR is found to be intrinsically disordered in aqueous solution. Further, we used alpha helix inducer, trifluoroethanol, and found induction of alpha helical conformation using CD spectroscopy. Additionally, in the presence of SDS, NSP1-CTR is showing a conformational change from disordered to ordered, possibly gaining alpha helix in part. But in presence of neutral lipid DOPC, a slight change in conformation is observed. This implies the possible role of hydrophobic interaction and electrostatic interaction on the conformational changes of NSP1. The changes in structural conformation were further studied by fluorescence-based studies, which showed significant blue shift and fluorescence quenching in the presence of SDS and TFE. Lipid vesicles also showed fluorescence-based quenching. In agreement to these result, fluorescence lifetime and fluorescence anisotropy decay suggests a change in conformational dynamics. The zeta potential studies further validated that the conformational dynamics is mostly because of hydrophobic interaction. In last, these experimental studies were complemented through Molecular Dynamics (MD) simulation which have also shown a good correlation and testify our experiments. We believe that the intrinsically disordered nature of the NSP1-CTR will have implications in disorder based binding promiscuity with its interacting proteins.

show abstract

“…These predictors use artificial neural networks (ANN) and machine-learning-based algorithms to predict specific disorder regions. The detailed description of the functioning of these predictors has been explained in our previous studies [82][83][84][85][86].…”

Section: Identification Of Intrinsically Disordered Protein Regions (mentioning

confidence: 99%

“…These regions were predicted using four different web servers, MoRFCHiBi_Web [87], ANCHOR [88], MoRFpred [89], and DISOPRED3 [90]. Each predictor uses a different data sets and ANN-based models for prediction, which are described in our MoRF-based studies on Zika virus, Chikungunya virus, Rotavirus, SARS-CoV-2 proteomes, and Alzheimer's-disease-associated amyloid cascade signaling proteins [56,83,84,91,92]. Along with these, another web-based predictor, D2P2 [93] has also been used, which predicts disordered regions as well as motifs in proteins.…”

Section: Molecular Recognition Features (Morfs) Predictionmentioning

confidence: 99%

Unstructured Biology of Proteins from Ubiquitin-Proteasome System: Roles in Cancer and Neurodegenerative Diseases

et al. 2020

Self Cite

View full text Add to dashboard Cite

The 26S proteasome is a large (~2.5 MDa) protein complex consisting of at least 33 different subunits and many other components, which form the ubiquitin proteasomal system (UPS), an ATP-dependent protein degradation system in the cell. UPS serves as an essential component of the cellular protein surveillance machinery, and its dysfunction leads to cancer, neurodegenerative and immunological disorders. Importantly, the functions and regulations of proteins are governed by the combination of ordered regions, intrinsically disordered protein regions (IDPRs) and molecular recognition features (MoRFs). The structure–function relationships of UPS components have not been identified completely; therefore, in this study, we have carried out the functional intrinsic disorder and MoRF analysis for potential neurodegenerative disease and anti-cancer targets of this pathway. Our report represents the presence of significant intrinsic disorder and disorder-based binding regions in several UPS proteins, such as extraproteasomal polyubiquitin receptors (UBQLN1 and UBQLN2), proteasome-associated polyubiquitin receptors (ADRM1 and PSMD4), deubiquitinating enzymes (DUBs) (ATXN3 and USP14), and ubiquitinating enzymes (E2 (UBE2R2) and E3 (STUB1) enzyme). We believe this study will have implications for the conformation-specific roles of different regions of these proteins. This will lead to a better understanding of the molecular basis of UPS-associated diseases.

show abstract

Understanding the penetrance of intrinsic protein disorder in rotavirus proteome

Cited by 25 publications

References 144 publications

Exploring the SARS-CoV-2 structural proteins for multi-epitope vaccine development: an in-silico approach

Exploring the SARS-CoV-2 structural proteins for multi-epitope vaccine development: an in-silico approach

SARS-CoV-2 NSP1 C-terminal region (residues 130-180) is an intrinsically disordered region

Unstructured Biology of Proteins from Ubiquitin-Proteasome System: Roles in Cancer and Neurodegenerative Diseases

Contact Info

Product

Resources

About