scholarly journals Differentially conserved amino acid positions may reflect differences in SARS-CoV-2 and SARS-CoV behaviour

2021 ◽  
Author(s):  
Denisa Bojkova ◽  
Jake E McGreig ◽  
Katie-May McLaughlin ◽  
Stuart G Masterson ◽  
Magdalena Antczak ◽  
...  
Keyword(s):  
Cell Culture ◽  
Amino Acid ◽  
In Silico ◽  
Virus Entry ◽  
Genomic Variation ◽  
Supplementary Information ◽  
Cell Tropism ◽  
Supplementary Data ◽  
Biological Behaviour ◽  
Novel Coronavirus

Abstract Motivation SARS-CoV-2 is a novel coronavirus currently causing a pandemic. Here, we performed a combined in-silico and cell culture comparison of SARS-CoV-2 and the closely related SARS-CoV. Results Many amino acid positions are differentially conserved between SARS-CoV-2 and SARS-CoV, which reflects the discrepancies in virus behaviour, i.e. more effective human-to-human transmission of SARS-CoV-2 and higher mortality associated with SARS-CoV. Variations in the S protein (mediates virus entry) were associated with differences in its interaction with ACE2 (cellular S receptor) and sensitivity to TMPRSS2 (enables virus entry via S cleavage) inhibition. Anti-ACE2 antibodies more strongly inhibited SARS-CoV than SARS-CoV-2 infection, probably due to a stronger SARS-CoV-2 S-ACE2 affinity relative to SARS-CoV S. Moreover, SARS-CoV-2 and SARS-CoV displayed differences in cell tropism. Cellular ACE2 and TMPRSS2 levels did not indicate susceptibility to SARS-CoV-2. In conclusion, we identified genomic variation between SARS-CoV-2 and SARS-CoV that may reflect the differences in their clinical and biological behaviour. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals SARS-CoV-2 and SARS-CoV differ in their cell tropism and drug sensitivity profiles

2020 ◽  
Author(s):  
Denisa Bojkova ◽  
Jake E. McGreig ◽  
Katie-May McLaughlin ◽  
Stuart G. Masterson ◽  
Marek Widera ◽  
...  
Keyword(s):  
Drug Testing ◽  
Drug Sensitivity ◽  
Clinical Investigation ◽  
Virus Entry ◽  
Cell Tropism ◽  
Protein Cleavage ◽  
Biological Behaviour ◽  
Culture Models ◽  
Novel Coronavirus ◽  
Cell Culture Models

AbstractSARS-CoV-2 is a novel coronavirus currently causing a pandemic. We show that the majority of amino acid positions, which differ between SARS-CoV-2 and the closely related SARS-CoV, are differentially conserved suggesting differences in biological behaviour. In agreement, novel cell culture models revealed differences between the tropism of SARS-CoV-2 and SARS-CoV. Moreover, cellular ACE2 (SARS-CoV-2 receptor) and TMPRSS2 (enables virus entry via S protein cleavage) levels did not reliably indicate cell susceptibility to SARS-CoV-2. SARS-CoV-2 and SARS-CoV further differed in their drug sensitivity profiles. Thus, only drug testing using SARS-CoV-2 reliably identifies therapy candidates. Therapeutic concentrations of the approved protease inhibitor aprotinin displayed anti-SARS-CoV-2 activity. The efficacy of aprotinin and of remdesivir (currently under clinical investigation against SARS-CoV-2) were further enhanced by therapeutic concentrations of the proton pump inhibitor omeprazole (aprotinin 2.7-fold, remdesivir 10-fold). Hence, our study has also identified anti-SARS-CoV-2 therapy candidates that can be readily tested in patients.

KEC: unique sequence search by K-mer exclusion

2021 ◽  
Author(s):  
Pavel Beran ◽  
Dagmar Stehlíková ◽  
Stephen P Cohen ◽  
Vladislav Čurn
Keyword(s):  
Amino Acid ◽  
Nucleic Acid ◽  
Source Code ◽  
Unique Sequence ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Laptop Computers ◽  
Sequence Search ◽  
Target Sequences ◽  
Cross Reference

Abstract Summary Searching for amino acid or nucleic acid sequences unique to one organism may be challenging depending on size of the available datasets. K-mer elimination by cross-reference (KEC) allows users to quickly and easily find unique sequences by providing target and non-target sequences. Due to its speed, it can be used for datasets of genomic size and can be run on desktop or laptop computers with modest specifications. Availability and implementation KEC is freely available for non-commercial purposes. Source code and executable binary files compiled for Linux, Mac and Windows can be downloaded from https://github.com/berybox/KEC. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals DEEPrior: a deep learning tool for the prioritization of gene fusions

2020 ◽  
Vol 36 (10) ◽  
pp. 3248-3250
Author(s):  
Marta Lovino ◽  
Maria Serena Ciaburri ◽  
Gianvito Urgese ◽  
Santa Di Cataldo ◽  
Elisa Ficarra
Keyword(s):  
Deep Learning ◽  
Amino Acid ◽  
Gene Fusion ◽  
Supplementary Information ◽  
Gene Fusions ◽  
Supplementary Data ◽  
Learning Tool ◽  
Cancer Driver ◽  
Open Issue ◽  
Passenger Mutation

Abstract Summary In the last decade, increasing attention has been paid to the study of gene fusions. However, the problem of determining whether a gene fusion is a cancer driver or just a passenger mutation is still an open issue. Here we present DEEPrior, an inherently flexible deep learning tool with two modes (Inference and Retraining). Inference mode predicts the probability of a gene fusion being involved in an oncogenic process, by directly exploiting the amino acid sequence of the fused protein. Retraining mode allows to obtain a custom prediction model including new data provided by the user. Availability and implementation Both DEEPrior and the protein fusions dataset are freely available from GitHub at (https://github.com/bioinformatics-polito/DEEPrior). The tool was designed to operate in Python 3.7, with minimal additional libraries. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals ChIPseqSpikeInFree: a ChIP-seq normalization approach to reveal global changes in histone modifications without spike-in

2019 ◽  
Author(s):  
Hongjian Jin ◽  
Lawryn H Kasper ◽  
Jon D Larson ◽  
Gang Wu ◽  
Suzanne J Baker ◽  
...  
Keyword(s):  
Histone Modification ◽  
Histone Modifications ◽  
In Silico ◽  
Peak Detection ◽  
Normalization Method ◽  
Supplementary Information ◽  
Global Changes ◽  
Supplementary Data ◽  
Similar Magnitude ◽  
Scaling Factors

Abstract Motivation The traditional reads per million normalization method is inappropriate for the evaluation of ChIP-seq data when treatments or mutations have global effects. Changes in global levels of histone modifications can be detected with exogenous reference spike-in controls. However, most ChIP-seq studies overlook the normalization that must be corrected with spike-in. A method that retrospectively renormalizes datasets without spike-in is lacking. Results ChIPseqSpikeInFree is a novel ChIP-seq normalization method to effectively determine scaling factors for samples across various conditions and treatments, which does not rely on exogenous spike-in chromatin or peak detection to reveal global changes in histone modification occupancy. Application of ChIPseqSpikeInFree on five datasets demonstrates that this in silico approach reveals a similar magnitude of global changes as the spike-in method does. Availability and implementation St. Jude Cloud (https://pecan.stjude.cloud/permalink/spikefree) and St. Jude Github ( https://github.com/stjude/ChIPseqSpikeInFree). Supplementary information Supplementary data are available at Bioinformatics online.

Protein residues determining interaction specificity in paralogous families

2020 ◽  
Author(s):  
Borja Pitarch ◽  
Juan A G Ranea ◽  
Florencio Pazos
Keyword(s):  
Amino Acid ◽  
Fine Tuning ◽  
Supplementary Information ◽  
Sequence Information ◽  
Large Set ◽  
Supplementary Data ◽  
Sequence Alignments ◽  
Multiple Sequence ◽  
Multiple Sequence Alignments ◽  
Protein Residues

Abstract Motivation Predicting the residues controlling a protein’s interaction specificity is important not only to better understand its interactions but also to design mutations aimed at fine-tuning or swapping them as well. Results In this work, we present a methodology that combines sequence information (in the form of multiple sequence alignments) with interactome information to detect that kind of residues in paralogous families of proteins. The interactome is used to define pairwise similarities of interaction contexts for the proteins in the alignment. The method looks for alignment positions with patterns of amino-acid changes reflecting the similarities/differences in the interaction neighborhoods of the corresponding proteins. We tested this new methodology in a large set of human paralogous families with structurally characterized interactions, and discuss in detail the results for the RasH family. We show that this approach is a better predictor of interfacial residues than both, sequence conservation and an equivalent ‘unsupervised’ method that does not use interactome information. Availability and implementation http://csbg.cnb.csic.es/pazos/Xdet/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals In silico analysis of Trisindoline 1 compound against Mpro SARS-CoV-2 as novel potential drugs candidate

2021 ◽  
Vol 2 (2) ◽  
pp. 42-50
Author(s):  
Fitri Lianingsih
Keyword(s):  
Amino Acid ◽  
Viral Entry ◽  
In Silico ◽  
In Silico Analysis ◽  
Cell Receptor ◽  
The Novel ◽  
Discovery Studio ◽  
Protein Receptors ◽  
Marine Compound ◽  
Novel Coronavirus

The novel coronavirus 2019 (SARS-CoV-2) is one of the viruses that can infect humans and cause high mortality worldwide. The protease (Mpro) is key SARS-CoV-2 an enzyme mediates the viral replication and the transcription. Mpro is currently used as the candidate for the SARS-CoV-2 vaccine because Mpro is one of the key enzymes in the viral life cycle that essential for interactions between the virus and host cell receptor during viral entry. The Mpro can be a target protein to design the novel drug of SARS-CoV-2. The drug design from natural products that are considered to have low toxicity is needed against the virus. The study aims to determines the potential pharmacology of Trisindoline 1 compound from the sponge Hyrtios altum against SARS-CoV-2 and to find the amino acid residues between interaction ligand-protein receptors. The methods of this study use the virtual screening of Auto Dock Vina and visualization the amino acid residue using Bio via Discovery Studio. The result of this study was the selected marine compound from Trisindoline 1 may have potential to developed as inhibitor of SARS-CoV-2.Keywords: In Silico, Mpro, Sars Cov 2, Trisindoline 1, Sponges

Comparative Study on Mitogen Activated Protein Kinase of Plasmodium Species by Using in silico Method

2012 ◽  
Vol 9 (1) ◽  
pp. 1
Author(s):  
Mohd Fakharul Zaman Raja Yahya ◽  
Hasidah Mohd Sidek
Keyword(s):  
Amino Acid ◽  
In Silico ◽  
Nuclear Export ◽  
Nuclear Export Signal ◽  
Plasmodium Species ◽  
Mitogen Activated Protein Kinase ◽  
Multiple Sequence ◽  
Wide Range ◽  
Mitogen Activated Protein ◽  
Human Plasmodium

Malaria parasites, Plasmodium can infect a wide range of hosts including humans and rodents. There are two copies of mitogen activated protein kinases (MAPKs) in Plasmodium, namely MAPK1 and MAPK2. The MAPKs have been studied extensively in the human Plasmodium, P. falciparum. However, the MAPKs from other Plasmodium species have not been characterized and it is therefore the premise of presented study to characterize the MAPKs from other Plasmodium species-P. vivax, P. knowlesi, P. berghei, P. chabaudi and P.yoelli using a series of publicly available bioinformatic tools. In silico data indicates that all Plasmodium MAPKs are nuclear-localized and contain both a nuclear localization signal (NLS) and a Leucine-rich nuclear export signal (NES). The activation motifs of TDY and TSH were found to be fully conserved in Plasmodium MAPK1 and MAPK2, respectively. The detailed manual inspection of a multiple sequence alignment (MSA) construct revealed a total of 17 amino acid stack patterns comprising of different amino acids present in MAPKJ and MAPK2 respectively, with respect to rodent and human Plasmodia. It is proposed that these amino acid stack patterns may be useful in explaining the disparity between rodent and human Plasmodium MAPKs. 

Comparative Study on Mitogen Activated Protein Kinase of Plasmodium Species by Using In silico Method

2012 ◽  
Vol 9 (1) ◽  
pp. 1
Author(s):  
Mohd Fakharul Zaman Raja Yahya ◽  
Hasidah Mohd Sidek
Keyword(s):  
Amino Acid ◽  
In Silico ◽  
Nuclear Export ◽  
Nuclear Export Signal ◽  
Plasmodium Species ◽  
Mitogen Activated Protein Kinase ◽  
Multiple Sequence ◽  
Bioinformatic Tools ◽  
Wide Range ◽  
Human Plasmodium

Malaria parasites, Plasmodium can infect a wide range ofhosts including humans and rodents. There are two copies ofmitogen activated protein kinases (MAPKs) in Plasmodium, namely MAPK1 and MAPK2. The MAPKs have been studied extensively in the human Plasmodium, P. falciparum. However, the MAPKs from other Plasmodium species have not been characterized and it is therefore the premise ofpresented study to characterize the MAPKs from other Plasmodium species-P. vivax, P. knowlesi, P. berghei, P. chabaudi and P.yoelli using a series ofpublicly available bioinformatic tools. In silico data indicates that all Plasmodium MAPKs are nuclear-localizedandcontain both a nuclear localization signal (NLS) anda Leucine-rich nuclear export signal (NES). The activation motifs ofTDYand TSH werefound to befully conserved in Plasmodium MAPK1 and MAPK2, respectively. The detailed manual inspection ofa multiple sequence alignment (MSA) construct revealed a total of 17 amino acid stack patterns comprising ofdifferent amino acids present in MAPK1 and MAPK2 respectively, with respect to rodent and human Plasmodia. 1t is proposed that these amino acid stack patterns may be useful in explaining the disparity between rodent and human Plasmodium MAPKs.

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