scholarly journals Evolving geographic diversity in SARS-CoV2 and in silico analysis of replicating enzyme 3CLpro targeting repurposed drug candidates

2020 ◽  
Author(s):  
Nitin Chitranshi ◽  
Vivek Kumar Gupta ◽  
Rashi Rajput ◽  
Angela Godinez ◽  
Kanishka Pushpitha ◽  
...  
Keyword(s):  
Sequence Alignment ◽  
In Silico ◽  
Genomic Sequence ◽  
In Silico Analysis ◽  
Multiple Sequence ◽  
Drug Candidates ◽  
Recurrent Mutations ◽  
Depth Analysis ◽  
Repurposed Drugs ◽  
Genetic Pool

Abstract Background: Severe acute respiratory syndrome (SARS) has been initiating pandemics since the beginning of the century. In December 2019, the world was hit again by a devastating SARS episode that has so far infected almost four million individuals worldwide, with over 200,000 fatalities having already occurred by mid-April 2020, and the infection rate continues to grow exponentially. SARS coronavirus 2 (SARS-CoV-2) is a single stranded RNA pathogen which is characterised by a high mutation rate. It is vital to explore the mutagenic capability of the viral genome that enables SARS-CoV-2 to rapidly jump from one host immunity to another and adapt to the genetic pool of local populations. Methods: For this study, we analysed 2,301 complete viral sequences reported from SARS-CoV-2 infected patients. SARS-CoV-2 host genomes were collected from The Global Initiative on Sharing All Influenza Data (GISAID) database containing 9 genomes from pangolin-CoV origin and 3 genomes from bat-CoV origin, Wuhan SARS-CoV2 reference genome was collected from GeneBank database. The Multiple sequence alignment tool, Clustal Omega was used for genomic sequence alignment. The viral replicating enzyme, 3-chymotrypsin-like cysteine protease (3CLpro) that plays a key role in its pathogenicity was used to assess its affinity with pharmacological inhibitors and repurposed drugs such as anti-viral flavones, biflavanoids, anti-malarial drugs and vitamin supplements. Results: Our results demonstrate that bat-CoV shares >96% similar identity, while pangolin-CoV shares 85.98% identity with Wuhan SARS-CoV-2 genome. This in-depth analysis has identified 12 novel recurrent mutations in South American and African viral genomes out of which 3 were unique in South America, 4 unique in Africa and 5 were present in-patient isolates from both populations. Using state of the art in silico approaches, this study further investigates the interaction of repurposed drugs with the SARS-CoV-2 3CLpro enzyme, which regulates viral replication machinery. Conclusions: Overall, this study provides insights into the evolving mutations, with implications to understand viral pathogenicity and possible new strategies for repurposing compounds to combat the nCovid-19 pandemic.

scholarly journals Evolving geographic diversity in SARS-CoV2 and in silico analysis of replicating enzyme 3CLPro targeting repurposed drug candidates

2020 ◽  
Author(s):  
Nitin Chitranshi ◽  
Vivek Kumar Gupta ◽  
Rashi Rajput ◽  
Angela Godinez ◽  
Kanishka Pushpitha ◽  
...  
Keyword(s):  
Sequence Alignment ◽  
In Silico ◽  
Genomic Sequence ◽  
In Silico Analysis ◽  
Multiple Sequence ◽  
Drug Candidates ◽  
Recurrent Mutations ◽  
Depth Analysis ◽  
Repurposed Drugs ◽  
Genetic Pool

Abstract Background: Severe acute respiratory syndrome (SARS) has been initiating pandemics since the beginning of this century. In December 2019, the world was hit again by a devastating SARS episode that has so far infected almost four million individuals worldwide with over 200,000 fatalities having already occurred by mid-April 2020, and the infection rate continues to grow exponentially. SARS coronavirus 2 (SARS-CoV-2) is a single stranded RNA pathogen which is characterised by a high mutation rate. It is vital to explore mutagenic capability of the viral genome that enables SARS-CoV-2 to rapidly jump from one host immunity to another and adapt to genetic pool of the local populations.Methods: For this study, we have analysed 1,921 complete viral sequences reported from SARS-CoV-2 infected patients. SARS-CoV-2 host genomes were collected from The Global Initiative on Sharing All Influenza Data (GISAID) database containing 9 genomes from pangolin-CoV origin and 3 genomes from bat-CoV origin, Wuhan SARS-CoV2 reference genome was collected from GeneBank database. The Multiple sequence alignment tool, Clustal Omega was used for genomic sequence alignment. The viral replicating enzyme, 3-chymotrypsin-like cysteine protease (3CL pro ) that plays a key role in its pathogenicity was used to assess its affinity with pharmacological inhibitors and repurposed drugs such as anti-viral flavones, biflavanoids, anti-malarial drugs and vitamin supplements.Results: Our results demonstrate that bat-CoV shares >96% similar identity, while pangolin-CoV shares 85.98% identity with Wuhan SARS-CoV-2 genome. This in-depth analysis has identified 12 novel recurrent mutations in South American and African viral genomes out of which 3 were unique in South America, 4 unique in Africa and 5 were present in-patient isolates from both populations. The study further investigated the interaction of repurposed drugs with SARS-CoV-2 3CL pro enzyme which regulates viral replication machinery, using state of the art in silico approaches.Conclusions: Overall, this study provides insights into the evolving mutations with implications to understand viral pathogenicity and possible new strategies for repurposing compounds to combat Covid-19 pandemic.

Amino Acids Sequence-based Analysis of Arginine Deiminase from Different Prokaryotic Organisms: An In Silico Approach

2020 ◽  
Vol 14 (3) ◽  
pp. 235-246
Author(s):  
Sara Abdollahi ◽  
Mohammad H. Morowvat ◽  
Amir Savardashtaki ◽  
Cambyz Irajie ◽  
Sohrab Najafipour ◽  
...  
Keyword(s):  
Amino Acid ◽  
Physicochemical Properties ◽  
Sequence Alignment ◽  
Multiple Sequence Alignment ◽  
In Silico ◽  
Bacterial Species ◽  
Arginine Deiminase ◽  
Antitumor Effects ◽  
Multiple Sequence ◽  
In Silico Studies

Background: Arginine deiminase is a bacterial enzyme, which degrades L-arginine. Some human cancers such as hepatocellular carcinoma (HCC) and melanoma are auxotrophic for arginine. Therefore, PEGylated arginine deiminase (ADI-PEG20) is a good anticancer candidate with antitumor effects. It causes local depletion of L-arginine and growth inhibition in arginineauxotrophic tumor cells. The FDA and EMA have granted orphan status to this drug. Some recently published patents have dealt with this enzyme or its PEGylated form. Objective: Due to increasing attention to it, we aimed to evaluate and compare 30 arginine deiminase proteins from different bacterial species through in silico analysis. Methods: The exploited analyses included the investigation of physicochemical properties, multiple sequence alignment (MSA), motif, superfamily, phylogenetic and 3D comparative analyses of arginine deiminase proteins thorough various bioinformatics tools. Results: The most abundant amino acid in the arginine deiminase proteins is leucine (10.13%) while the least amino acid ratio is cysteine (0.98%). Multiple sequence alignment showed 47 conserved patterns between 30 arginine deiminase amino acid sequences. The results of sequence homology among 30 different groups of arginine deiminase enzymes revealed that all the studied sequences located in amidinotransferase superfamily. Based on the phylogenetic analysis, two major clusters were identified. Considering the results of various in silico studies; we selected the five best candidates for further investigations. The 3D structures of the best five arginine deiminase proteins were generated by the I-TASSER server and PyMOL. The RAMPAGE analysis revealed that 81.4%-91.4%, of the selected sequences, were located in the favored region of arginine deiminase proteins. Conclusion: The results of this study shed light on the basic physicochemical properties of thirty major arginine deiminase sequences. The obtained data could be employed for further in vivo and clinical studies and also for developing the related therapeutic enzymes.

scholarly journals Cloning, Sequencing, and In Silico Analysis of β-Propeller Phytase Bacillus licheniformis Strain PB-13

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Vinod Kumar ◽  
Gopal Singh ◽  
Punesh Sangwan ◽  
A. K. Verma ◽  
Sanjeev Agrawal
Keyword(s):  
Phylogenetic Tree ◽  
Bacillus Licheniformis ◽  
In Silico ◽  
Catalytic Mechanism ◽  
Specific Activity ◽  
In Silico Analysis ◽  
Homology Search ◽  
Multiple Sequence ◽  
Bioinformatic Tools ◽  
C Terminus

β-Propeller phytases (BPPhy) are widely distributed in nature and play a major role in phytate-phosphorus cycling. In the present study, a BPPhy gene from Bacillus licheniformis strain was expressed in E. coli with a phytase activity of 1.15 U/mL and specific activity of 0.92 U/mg proteins. The expressed enzyme represented a full length ORF “PhyPB13” of 381 amino acid residues and differs by 3 residues from the closest similar existing BPPhy sequences. The PhyPB13 sequence was characterized in silico using various bioinformatic tools to better understand structural, functional, and evolutionary aspects of BPPhy class by multiple sequence alignment and homology search, phylogenetic tree construction, variation in biochemical features, and distribution of motifs and superfamilies. In all sequences, conserved sites were observed toward their N-terminus and C-terminus. Cysteine was not present in the sequence. Overall, three major clusters were observed in phylogenetic tree with variation in biophysical characteristics. A total of 10 motifs were reported with motif “1” observed in all 44 protein sequences and might be used for diversity and expression analysis of BPPhy enzymes. This study revealed important sequence features of BPPhy and pave a way for determining catalytic mechanism and selection of phytase with desirable characteristics.

scholarly journals ViralMSA: Massively scalable reference-guided multiple sequence alignment of viral genomes

2020 ◽  
Author(s):  
Niema Moshiri
Keyword(s):  
Sequence Alignment ◽  
Multiple Sequence Alignment ◽  
Genomic Sequence ◽  
Sequence Data ◽  
Software Project ◽  
Multiple Sequence ◽  
Viral Genomes ◽  
Alignment Tool ◽  
Multiple Sequence Alignment Tool ◽  
Algorithmic Techniques

AbstractMotivationIn molecular epidemiology, the identification of clusters of transmissions typically requires the alignment of viral genomic sequence data. However, existing methods of multiple sequence alignment scale poorly with respect to the number of sequences.ResultsViralMSA is a user-friendly reference-guided multiple sequence alignment tool that leverages the algorithmic techniques of read mappers to enable the multiple sequence alignment of ultra-large viral genome datasets. It scales linearly with the number of sequences, and it is able to align tens of thousands of full viral genomes in seconds.AvailabilityViralMSA is freely available at https://github.com/niemasd/ViralMSA as an open-source software [email protected]

scholarly journals Curated multiple sequence alignment for the Adenomatous Polyposis Coli (APC) gene and accuracy of in silico pathogenicity predictions

PLoS ONE ◽  
2020 ◽  
Vol 15 (8) ◽  
pp. e0233673
Author(s):  
Alexander D. Karabachev ◽  
Dylan J. Martini ◽  
David J. Hermel ◽  
Dana Solcz ◽  
Marcy E. Richardson ◽  
...  
Keyword(s):  
Adenomatous Polyposis Coli ◽  
Sequence Alignment ◽  
Multiple Sequence Alignment ◽  
In Silico ◽  
Apc Gene ◽  
Adenomatous Polyposis ◽  
Polyposis Coli ◽  
Multiple Sequence

scholarly journals In Silico Characterization of Histidine Acid Phytase Sequences

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Vinod Kumar ◽  
Gopal Singh ◽  
A. K. Verma ◽  
Sanjeev Agrawal
Keyword(s):  
Sequence Alignment ◽  
Multiple Sequence Alignment ◽  
In Silico ◽  
Animal Feed ◽  
Protein Sequences ◽  
Homology Search ◽  
Protein Database ◽  
Multiple Sequence ◽  
Conserved Sequence ◽  
Signature Sequence

Histidine acid phytases (HAPhy) are widely distributed enzymes among bacteria, fungi, plants, and some animal tissues. They have a significant role as an animal feed enzyme and in the solubilization of insoluble phosphates and minerals present in the form of phytic acid complex. A set of 50 reference protein sequences representing HAPhy were retrieved from NCBI protein database and characterized for various biochemical properties, multiple sequence alignment (MSA), homology search, phylogenetic analysis, motifs, and superfamily search. MSA using MEGA5 revealed the presence of conserved sequences at N-terminal “RHGXRXP” and C-terminal “HD.” Phylogenetic tree analysis indicates the presence of three clusters representing different HAPhy, that is, PhyA, PhyB, and AppA. Analysis of 10 commonly distributed motifs in the sequences indicates the presence of signature sequence for each class. Motif 1 “SPFCDLFTHEEWIQYDYLQSLGKYYGYGAGNPLGPAQGIGF” was present in 38 protein sequences representing clusters 1 (PhyA) and 2 (PhyB). Cluster 3 (AppA) contains motif 9 “KKGCPQSGQVAIIADVDERTRKTGEAFAAGLAPDCAITVHTQADTSSPDP” as a signature sequence. All sequences belong to histidine acid phosphatase family as resulted from superfamily search. No conserved sequence representing 3- or 6-phytase could be identified using multiple sequence alignment. This in silico analysis might contribute in the classification and future genetic engineering of this most diverse class of phytase.

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