Searching for tunnels of proteins – comparison of approaches and available software tools

Jaiswal, Deepti; Vařeková, Radka Svobodová; Ionescu, Crina-Maria; Sehnal, David; Koča, Jaroslav

doi:10.1186/1758-2946-4-s1-p60

Cited by 2 publications

(2 citation statements)

References 4 publications

(2 reference statements)

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“…Tunnels are access paths connecting the interior of molecular systems with the surrounding environment. The presence of tunnels in proteins influences their reactivity, as they determine the nature and intensity of the interaction that these proteins can take part in (Jaiswal et al, 2012). Tunnel analysis of the newly predicted structures of the present study have estimated the presence of multiple tunnels in NSP1, NSP3, NSP6, ORF3a protein, ORF6 protein, membrane glycoprotein, ORF7a protein and Nucleocapsid phosphoprotein.…”

Section: Hetero-oligomeric Complexesmentioning

confidence: 75%

In silicoProteome analysis of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)

Baruah¹,

Devi²,

Sharma

2020

Preprint

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (2019-nCoV), is a positive-sense, single-stranded RNA coronavirus. The virus is the causative agent of coronavirus disease 2019 (COVID-19) and is contagious through human-to-human transmission. The present study reports sequence analysis, complete coordinate tertiary structure prediction and in silico sequence-based and structure-based functional characterization of full SARS-CoV-2 proteome based on the NCBI reference sequence NC_045512 (29903 bp ss-RNA) which is identical to GenBank entry MN908947 and MT415321. The proteome includes 12 major proteins namely orf1ab polyprotein (includes 15 proteins), surface glycoprotein, ORF3a protein, envelope protein, membrane glycoprotein, ORF6 protein, ORF7a protein, orf7b, ORF8, Nucleocapsid phosphoprotein and ORF10 protein. Each protein of orf1ab polyprotein group has been studied separately. A total of 25 polypeptides have been analyzed out of which 15 proteins are not yet having experimental structures and only 10 are having experimental structures with known PDB IDs. Out of 15 newly predicted structures six (6) were predicted using comparative modeling and nine (09) proteins having no significant similarity with so far available PDB structures were modeled using ab-initio modeling. Structure verification using recent tools QMEANDisCo 4.0.0 and ProQ3 for global and local (per-residue) quality estimates indicate that the all-atom model of tertiary structure of high quality and may be useful for structure-based drug designing targets. The study has identified nine major targets (spike protein, envelop protein, membrane protein, nucleocapsid protein, 2’-O-ribose methyltransferase, endoRNAse, 3’-to-5’ exonuclease, RNA-dependent RNA polymerase and helicase) for which drug design targets could be considered. There are other 16 nonstructural proteins (NSPs), which may also be percieved from the drug design angle. The protein structures have been deposited to ModelArchive. Tunnel analysis revealed the presence of large number of tunnels in NSP3, ORF 6 protein and membrane glycoprotein indicating a large number of transport pathways for small ligands influencing their reactivity.

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Section: Hetero-oligomeric Complexesmentioning

confidence: 75%

In silicoProteome analysis of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)

Baruah¹,

Devi²,

Sharma

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Tunnels are access paths connecting the interior of molecular systems with the surrounding environment. The presence of tunnels in proteins influences their reactivity, as they determine the nature and intensity of the interaction that these proteins can take part in [65]. Tunnel and ligand-binding pocket analysis in the newly predicted structures of the present study had estimated pockets with high druggability scores in envelope glycoprotein (0.97), membrane glycoprotein (0.87), NSP6 (0.79), ORF7a (0.79), ORF8 (0.75), ORF3a (0.72), and NSP4 (0.70), indicating the ability to bind drug-like molecules with high affinity, which is of major interest in the target identification phase of drugs.…”

Section: Gravymentioning

confidence: 99%

Untitled

2021

J Nanotechnol Nanomaterials

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This study reports sequence data mining and analysis, complete coordinate tertiary structure prediction including Deep Learning inspired validation, and in silico functional characterization of the full SARS-CoV-2 proteome based on the NCBI reference sequence NC_045512 (29903 bp ss-RNA). Out of 25 polypeptides analyzed, 3D structures of 15 of them were predicted using comparative protein structure prediction method and ab-initio modelling method due to unavailability of experimentally determined structures. Deep Learning and Neural Network based tools such as QMEANDisCo 4.0.0, MolProbity 4.4, ProQ3D and Procheck were used to verify the predicted 3D structures. Tunnel analysis revealed the presence of multiple tunnels in NSP4, nucleocapsid phosphoprotein, NSP3, membrane glycoprotein, ORF6 protein, NSP1, NSP6, and envelop protein, indicating a large number of transport pathways for small ligands that influence their reactivity. Ligand-binding pockets with high estimates of druggability scores were detected in envelope glycoprotein (0.97), membrane glycoprotein (0.87), NSP6 (0.79), ORF7a (0.79), ORF8 (0.75), ORF3a (0.72), and NSP4 (0.70), indicating the ability to bind drug-like molecules with high affinity indicating that the predicted structures would be useful for protein nanotechnology in understanding protein machinery towards drug repurposing and discovery studies. Moreover, the molecular phylogenetic analysis of orf1ab polyprotein indicates close relatedness of SARS-CoV-2 to the bat coronavirus.

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Searching for tunnels of proteins – comparison of approaches and available software tools

Cited by 2 publications

References 4 publications

In silicoProteome analysis of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)

In silicoProteome analysis of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)

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