key: cord-0872401-ien3hwzo
authors: Kangabam, Rajiv; Sahoo, Susrita; Ghosh, Arpan; Roy, Riya; Silla, Yumnam; Misra, Namrata; Suar, Mrutyunjay
title: Next-Generation Computational Tools and Resources for Coronavirus Research: from Detection to Vaccine Discovery
date: 2020-12-01
journal: Comput Biol Med
DOI: 10.1016/j.compbiomed.2020.104158
sha: c1f49dfded54d32f8a97efa33d711b1e4512a4e5
doc_id: 872401
cord_uid: ien3hwzo

The COVID-19 pandemic has affected 215 countries and territories around the world with 60,187,347 coronavirus cases and 17,125,719 currently infected patients confirmed as of the 25th of November 2020. Currently, many countries are working on developing new vaccines and therapeutic drugs for this novel virus strain, and a few of them are in different phases of clinical trials. The advancement in high-throughput sequence technologies, along with the application of bioinformatics, offers invaluable knowledge on genomic characterization and molecular pathogenesis of coronaviruses. Recent multi-disciplinary studies using bioinformatics methods like sequence-similarity, phylogenomic, and computational structural biology have provided an in-depth understanding of the molecular and biochemical basis of infection, atomic-level recognition of the viral-host receptor interaction, functional annotation of important viral proteins, and evolutionary divergence across different strains. Additionally, various modern immunoinformatic approaches are also being used to target the most promiscuous antigenic epitopes from the SARS-CoV-2 proteome for accelerating the vaccine development process. In this review, we summarize various important computational tools and databases available for systematic sequence-structural study on coronaviruses. The features of these public resources have been comprehensively discussed, which may help experimental biologists with predictive insights useful for ongoing research efforts to find therapeutics against the infectious COVID-19 disease.

Since the first discovery of coronavirus in domestic poultry in the 1930s, to date various novel coronaviruses strains have been often reported causing respiratory, gastrointestinal, liver, and neurologic diseases in animals, including humans [1 -3] . The earlier human-infected coronavirus strains such as NL63, HKU1, 229E, and OC43 are known to be associated with mild to moderate upper-respiratory tract illnesses. While the three major human infected coronaviruses viz., the SARS-CoV-1 of 2002 popularly known as severe acute respiratory syndrome coronavirus [5] , the 2012 middle east respiratory syndrome coronavirus (MERS-CoV) [6] and the new SARS-CoV-2, the cause of the current pandemic that was first identified in Wuhan City (China) in 2019 [7, 8] , are associated with a high rate of mortality and morbidity worldwide. Further, the World Health Organization (WHO) declared this pandemic as the Public Health Emergency of International Concern on 30 th of January 2020 [9] . All these three coronaviruses belong to the betacoronavirus genera of the coronaviridae family [10] , with a genome size of approximately 30 Kb [11] . Comparative genomic analysis of SARS-CoV-2 sequences exhibited 79.5% and 96% nucleotide similarity with SARS-CoV-1 and SARSr-CoV-RaTG13 strain originated from bats, respectively. Thus, indicating its partial similarity with SARS-CoV-1 and bats as the most probable host organism [12] . Further, high sequence-structure conservation noted between SARS-CoV-2 and SARS-CoV-1 genomes, speculated that they have a common ACE2 receptor (angiotensin-converting enzyme 2) [13] . Moreover, in comparison to SARS-CoV-1 and MERS-CoV, SARS-CoV-2 has relatively higher contagiousness and morbidity (with a R o value ranging from 2.2 -3.77); but a lower mortality rate (3.4%) [14, 15] .

The four major structural glycoproteins responsible for coronavirus pathogenesis in the host are (i)Spike (S), (ii)Membrane (M), (iii) Nucleocapsid (N) and, (iv)Envelope (E) proteins ( Figure 1 ) [16] . Particularly, the receptor-binding domain (RBD) region of the S protein facilitates the viral entry into the host cells via binding to the receptor, ACE2 [17, 18] , triggering a cascade of multiple events initiating the fusion of both viral and host membranes. [19] . Earlier studies on vaccine platforms for SARS-CoV-1 and MERS-CoV have identified that the RBD region of the S protein on the virus surface is the target for ideal vaccine development, as it reduces host immunopotentiation and generates neutralizing antibodies against coronavirus [20] [21] [22] . Many SARS-CoV-1 vaccines have been in the advanced stage of development and tested using various animal models [23] . Although these vaccines showed encouraging results in animal models, only a few of them have reached the initial phase I clinical trials before the next round of funding dried up. Nonetheless, virus eradication was possible through preventive measures and social distancing [23] .Due to the absence of clinically approved vaccines against coronavirus, the COVID-19 disease has J o u r n a l P r e -p r o o f 4 | P a g e created a global menace to public health while the spread of the virus infection is continuing across the globe.

Access to multiple coronaviruses genome sequences now provides abundant opportunities for the application of bioinformatics approaches to unravel the evolutionary origin of new strains and the mechanism of viral entry and pathogenesis in the host. A study performed in this direction by Pachetti et al. has identified the genomic hotspots that are likely to mutate easily by carrying out genome alignment of 220 sequences from coronavirus isolates across several countries. With this prior knowledge, they hypothesized that the occurrence of such transformations might determine the variation in the mortality rate of SARS-CoV-2 infected people in different geographic regions [25] . Another recent study, using an integrated network approach by combining protein-protein interaction and SARS-CoV-2/Human Interactome, has shed light on the evolutionary origin of SARS-CoV-2 by finding out the mechanism of host interaction [26] . Besides, sequence information, the availability of crystal structures in RCSB PDB (Protein Data Bank) of SARS-CoV-1 (PDB Id: 2GHV) [27] and SAR-CoV-2 S proteins complexed with ACE2 receptors (PDB Id: 6M0J) [28] have identified the conserved residues responsible for the host receptor-binding in SARS-CoV-2 based on comparative sequence-structure similarity against SARS-CoV-1 [29, 30] . Furthermore, using a computational approach the probable host range of SARS-CoV-2 has been predicted by analyzing the conserved amino acid properties located within the binding site interface [30 -32] . Moreover, by employing molecular docking and dynamics simulation approach, the interaction of human SARS-CoV-2 E protein with various phytochemicals has been analyzed, which might be utilized as potential drugs for SARS-CoV-2 [33] .While in silico approaches using immunoinformatic tools and databases are now indispensable in the search of potential immunogenic targets for drug and vaccine development and also have been demonstrated successfully in diseases like HIV-1 [34] and cancer [35 -37] , its application in the identification of potential vaccine candidates against coronaviruses is just beginning to emerge in the last few years [38] .Recently, few studies using immunoinformatics and reverse vaccinology approach have identified promiscuous T-cell and B-cell epitopes as vaccine candidates against SARS-CoV-2 which may excite cellular and humoral immune response [39 -42] . Using similar bioinformatics methods, an epitope-based vaccine construct was suggested based on linear amino acid motifs which are found to be conserved in a wide range of coronaviruses including SARS-CoV-2 [43] . Similarly, using known immunogenic epitopes from the SARS-CoV-1 genome available on IEDB and ViPR immunology databases, homologous amino acids present at the equivalent position in SARS-CoV-2 have been proposed for vaccine design [44] . These studies conclusively highlight the potential utility of the next-generation bioinformatics approaches in J o u r n a l P r e -p r o o f 5 | P a g e providing greater insights into coronavirus genome structure and molecular mechanism of viral pathogenesis in the host organism.

To further accelerate the ongoing experimental studies, various bioinformatics databases, tools, and web servers have been recently developed which systematically stores various genomic, epidemiology, and biological data pertinent to coronaviruses. These publicly available comprehensive resources can also be applied as platform tools for deriving useful information from complex and large datasets scattered across different databases. Therefore, in the present review for the first time, various computational resources have been discussed along with the integrated features they provide specifically for coronavirus research.

We have categorized these popular tools and databases depending on the utility and application such as for the detection of coronavirus, comparative genomics analysis, vaccine and drug discovery, molecular docking, and other applications in coronaviruses study ( Figure 2 , Table 1 ). This review will certainly constitute an important resource for experimental biologists, immunologists, vaccinologists, and computational biologists across the globe to spur R&D efforts on designing strategies to combat COVID-19 disease. identification and characterization of coronaviruses [66] , nevertheless the high mutation rates in the genomic sequences of SARS-CoV-2 is a major challenge for the efficiency of available assays [67] . In with information on its target type, techniques, target, sequence, genomic region, and detection protocol, diversity study at a genetic level across the genome of SARS-CoV-2 and a quick guide to perform laboratory testing for SARS-CoV-2.Users can retrieve an oligonucleotide with a specific CoV2ID score by browsing through the search tab or can manually design a novel oligonucleotide under the "Genome variation" of the database.

The necessity of achieving an urgent solution for the ongoing pandemic has led to the sequencing of thousands of SARS-CoV-2 genomes. By leveraging the advancement of nextgeneration sequencing technology, more than 11500 complete SARS-CoV-2 genome sequences and over 6100partial genomes are available at NCBI to date (https://www.ncbi.nlm.nih.gov/).

Among all known RNA viruses, coronaviruses possess the largest genomes (approximately 26,000 and 32,000 bases) with G+C contents varying from 32% to 43% [68] . Although wet lab techniques represent the most accurate method for viral genome annotation, however, these experiments are time-consuming and expensive [69] . In this context, computational tools and databases can become a reliable alternative, and cost economic approach for identifying, annotating, and understanding the genomic characteristics of the novel viruses [70] .

J o u r n a l P r e -p r o o f 9 | P a g e

The comprehensive database for comparative analysis of coronavirus genes and genomes (CoVDB;

http://covdb.microbiology.hku.hk) [46] is an user-friendly database of annotated coronavirus genomes that currently holds records on >3000 coronavirus sequences, belonging to coronavirus HKU1, bat SARS 

It is reported that approximately 60% of the evolving communicable diseases agents affecting humans are of zoonotic origin [74] and bats are the most important reservoir for many viruses including the coronaviruses [75] [76] [77] [78] .The Database of Bat-associated Viruses (DBatVir;

http://www.mgc.ac.cn/DBatVir/) [47] , is a well-curate repository for specific bat-associated animal 

Genome Detective Typing Tool (www.genomedetective.com) [48] is an easy-to-use a tool that permits rapid characterization and identification of SARS-CoV-2 sequences isolated across the world. Recently, a study employing the tool has shown that the novel SARS-CoV-2 shares 79.5 % similarity with the genome of SARS-CoV-1 [79] . Also, another study demonstrated a variant analysis of SARS-CoV-2 genomes using this Typing Tool and found 483 variations within the 29,903 bp long genome of SARS-CoV-2, which comprises115 variations in the UTR region, 130 synonymous variations, 228 nonsynonymous variations, 16 INDELs, and variations in two non-coding regions [80] .

The 

NCBI virus [49] is a community portal especially created to retrieve, exhibit, and analyze a set of curated 

The GISAID (Global Initiative on Sharing All Influenza Data (https://www.gisaid.org/))consortium assists rapid sharing of all influenza viruses data, including the SARS-CoV-2 coronavirus [51] . Further, the database also provides geographical sites along with species-specific data to help in understanding the 

Various virtual screening analysis has exploited the major proteins targets, including 3C-like proteinase (M pro ) [87, 88] , ACE2 [89] , papain-like proteinase (PLpro) [90] and furin [91] to discover effective drugs against the deadly coronavirus. However, none of the clinical studies provides effective therapies to combat COVID-19 disease. Thus, identification of potential drug targets by employing virtual screening and docking analysis is highly essential for a detailed investigation of protein structural and functional mechanisms against the SARS-CoV-2. Recently many tools and web-servers have been developed to assist in coronavirus-specific docking studies which have been discussed in this section. The tool has been successfully validated for six potential antiviral agents including the active form of remdesivir, favipiravir, ribavirin, penciclovir, N3 compound, and teriflunomide against important SARS-CoV-2 proteins.

To date, there is no definitive FDA-approved antiviral-drug for the COVID-19treatment. Besides, most of the treatment strategies concentrate only on symptomatic management and supportive therapy [98] .Various research organizations are tirelessly working hard to evaluate multiple compounds that can inhibit the spread of SARS-CoV-2 in humans. Nevertheless, these efforts are tedious and involve a meticulously extensive process. Thus, in addition to experimental work, specialized computational resources focusing on antiviral compounds/peptides can be utilized to evaluate the identified antivirals and repurpose them against single agents or in combinations to effectively control the spread of the virus [98, 99] .

Antiviral Compound Prediction (AVCpred; http://crdd.osdd.net/servers/avcpred) [55] is a freely accessible web server using a quantitative structure-activity relationship (QSAR) based approach to 

Database of Antiviral Peptides (AVPdb; http://crdd.osdd.net/servers/avpdb) [56] is an exclusive resource for experimentally proved Antiviral peptides (AVPs) targeting over 60 therapeutically significant viruses, 

To expedite the antiviral drug discovery processes, AVPpred (http://crdd.osdd.net/servers/avppred) [57] and AntiVPP 1.0 (https://github.com/bio-coding/AntiVPP) [58] are two virus-specific resources to explore potential peptides as therapeutic agents for various infectious diseases caused by viral pathogens.

AVPpred and AntiVPP 1.0 use a support vector machine and Random Forest algorithm respectively, for predicting antiviral peptides. Using AVPpred a comparative genomic study revealed that a peptide KWPWYIWLGFIAGLI shows high binding affinity with spike protein (0.98 prediction score) and also found that no AVPs were associated with N protein and ORF7a, while an AVP VNCLDDRCILHCANF is associated with both NSP7 and NSP10 [103] .

ClinicalTrials.gov (https://clinicaltrials.gov/ct2/results/details?cond=COVID-19) is a government website novel coronavirus, and one on Wuhan coronavirus.

Various research organizations are working relentlessly investigating many probable vaccine candidates and technologies for SARS-CoV-2 such as the subunit vaccines, nucleic acid vaccines, and whole virus vaccines [104] . As of August 2020, 234 vaccine candidates were under development; however, none of the candidates has completed successful clinical trials to prove its efficacy and safety [105] .Keeping in view the current COVID-19 situation, it is very much essential to expeditiously combine computational and experimental vaccine designing techniques to reduce the cost and time in the identification of target vaccine candidates [106] , followed by further evaluation for safety and efficacy.

CoronaVIR (https://webs.iiitd.edu.in/raghava/coronavir/) [59] a multi-omics website that contains detailed information about genomic, proteomic, therapeutic, and diagnostic knowledge of novel SARS-CoV-2coronaviruses, that have been manually curated from literature, existing databases and also contain predicted useful information obtained using various computational tools. To provide a holistic platform, four major modules, viz., "Genomics", "Diagnosis", "Immunotherapy" and "Drug Designing" have been integrated with CoronaVIR. The Genomics module contains genome data of different coronaviruses strains to facilitate genomic level alterations studies. The Diagnosis module provides updated information on widely used diagnostics tests for this virus as well as five novel universal primers set predicted using in silico approach. The Immunotherapy module contains many computationally predicted antigenic peptide sequences (B-cell and T-cell epitopes) which might elicit antibody-mediated immunity and cellular immune responses against the coronavirus infection. Lastly, the drug module provides tertiary structure information of important FDA approved drug molecules, drug targets, repurposing drugs, and monoclonal antibodies.

The Immune Epitope Database and Analysis Resource (IEDB, www.iedb.org) [60, 61] a freely available Recently, promiscuous epitopes were evaluated as candidate targets for immune responses against SARS-CoV-2 has been mapped using the known epitopes at the equivalent position in SARS-CoV-1 and MERS-CoV present at the IEDB server [42] . Similar in silico studies with the help of prediction and analysis tools of IEDB have identified potential vaccine candidates belonging to B-cell and T-cell epitopes from SARS-CoV-2 antigenic proteins, using epitopes conservancy, potential immunogenicity, and conservancy analysis. [39] [40] [41] [42] . Therefore, IEDB is a useful resource in the development of vaccines against SARS-CoV-2 coronaviruses usingepitope-based subunit.

The Virus Pathogen Resource (ViPR; http://www.viprbrc.org) [62] , supported by, NIAID,is a data 

For effective and preventive control measures against the ongoing pandemic, immediate surveillance and monitoring of the spread of disease are highly essential. Notably, re-emerging infectious diseases are major health problems occurring in a particular geographic location or population. Nevertheless, they can rapidly disperse globally/locally with specific modes of transmission and pandemic capability. The emergence of various infectious diseases is particularly related to human factors viz., travel, population density, the interaction between humans and wildlife, trade, and environmental factors [107] . However, advancement in the field of computational technologies has aided efforts of disease surveillance and also guided the inefficient construction of mathematical models to gain significant insights into the disease dynamics and epidemic prediction [107] . As revealed during the 2003 SARS outbreak, H1N1 influenza pandemic in 2009 and 2012 MERS-CoV, various computational techniques for epidemic models help in real-time analysis of the public health crisis [107, 108] . These computational models have the unique ability to recognize disease hotspots of different emerging infectious diseases, including identification of which emerging pathogen is more likely to occur in which particular hotspot.

The global epidemic and mobility model (GLEAMviz, http://www.gleamviz.org/) [64] have a user- 

In the absence of any vaccine against coronavirus, various alternatives encompassing monoclonal antibodies, interferon, oligonucleotide, and peptides based therapies are being currently studied to fight against the disease [111] . In addition, several promising drug molecules are observed to have properties effective against SARS-CoV-2 coronavirus in cell lines studies [112] . Many researchers have studied the effect of hydroxychloroquine, a conventional drug used for the treatment of malaria, on SARS-CoV-2 in vitro, and the results have been found promising [113] . In an early report, Nafamostat, an inhibitor, used as an anti-pancreatitis and anticoagulant to treat cystic fibrosis, was also shown to possess have mucolytic action that can inhibit lung function deterioration caused by coronaviruses [114] .Remdesivir, anadenosine triphosphate prodrug, is shown to play an important role against SARS-CoV-2 by impeding the polymerase activity of RNAand has been suggested as the most promising candidate to treat COVID-19 according to WHO [115] . Based on the results of phase III trials performed using remdesivir as shown by ACTT study (directed by NIAID) and SIMPLE study (managed by Gilead),the US Food and Drug Administration (USFDA) has recently approved the usage of remdesivir to cure COVID-19 infections, through the Special Emergency Use Authorization [116, 117] .The combination of ritonavir and lopinavir protease inhibitors (treatment for HIV), in the presence or absence of IFNβ, has also been suggested to be a potential candidate against SARS-CoV-2,by preventing the 3-chymotrypsin-like protease of the virus [118] . Moreover, an earlier study based on the influenza virus showed that the addition of umifenovir (inhibitor of viral fusion using human cell membranes) to the combination of ritonavir and lopinavir resulted in quick elimination of nasopharyngeal virus and regression of lung imaging, compared to the patients receiving both ritonavir and lopinavir monotherapy [119] .

WHO conducted a study named SOLIDARITY, trial to help in rapid identification of the most effective antiviral candidate against SARS-CoV-2 using ritonavir, lopinavir, and remdesivir +chloroquine combination [120] . The main objective of the trial is to track mortality rate, duration of hospitalization, identification of patients requiring intensive medical support, and administration of these drug candidates. causes systemic and tissue inflammation, pulmonary fibrosis, and fever [121] . According to ClinicalTrials.gov, a novel, double-blind, placebo-controlled phase III study 'COVACTA', investigated the overall safety and efficacy of intravenous tocilizumab (basically used in rheumatology), a monoclonal antibody with the property to inhibit interleukin-6 (IL-6) receptor, in adult patients hospitalized with COVID-19 infection [122] .

A recent report shows that SARS-CoV-2 needs Transmembrane Serine Protease 2 (TMPRSS2) for penetration into the host and further revealed that Camostat Mesylate, a serine protease inhibitor prevents the entry of the SARS-CoV-2 into the lung cells [123] . Later, it was shown that nafamostat blocked

Mesylate, [124] .At present, the efficacy of Camostat Mesylate (CamoCO-19 study) and Nafamostat (RACONA study) on COVID-19 infection in the clinical trials is underway. A clinical trial has revealed that the combination of hydroxychloroquine and azithromycin treatment is efficient in the reduction of viral load in SARS-CoV-2 infected patients [125] .

A docking study showed that amodiaquine can act as an alternative inhibitor to SARS-CoV-2 in comparison to the approved medicines, such as hydroxychloroquine, and remdesivir [126] . Moreover, studies using novel AI-based systems approach identified Vitamin E, ruxolitinib, and glutamine to have a high binding affinity with ACE 2 [127] .Recently Hemmat et al., suggested that serpins and arginase inhibitors can be effective against SARS-CoV-1 infection, and can also be effective against SARS-CoV-2 as it shares high similarity with SARS-CoV-1 [128] . Using integrated molecular modeling approaches, various reports indicated that phytochemicals such as carvacrol, oleanolic acid, and ursolic acid, might act as probable inhibitors in modulating the M pro protein function and regulating replication of virus [129] . A computational study has hypothesized that plant-origin compounds viz., bisdemethoxycurcumin, demethoxycurcumin, scutellarin, myricetin, and quercetin could act as possible drug candidates against M pro and NSP15 proteins of SARS-CoV-2 [130] .Further, repurposed existing drugs viz., disulfiram, carmofur, ebselen, shikonin, tideglusib, PX-12, and TDZD-8 might be promising inhibitors targeting M pro [131] . Similarly, Isavuconazonium (triazole), α-KI (ketoamide), and Pentagastrin (peptide) are suggested as possible drug candidates to treat infected patients with COVID-19 [132] .Currently, several worldwide research organizations and pharmaceutical companies are steadily involved in developing an effective vaccine against the virulent SARS-CoV-2 virus [133] . According to the WHO (as of August 2020), a total of146 vaccines were identified as probable candidates which are under the pre-clinical stage,36

vaccine candidates were in clinical research(24 in Phase I-II trials, and 12 in Phase II-III trials;

https://www.who.int/). At present, to develop a potential rapid vaccine on high priority, various J o u r n a l P r e -p r o o f 24 | P a g e computational based reports [106, 134 -136] have applied immunoinformatics approach to design promiscuous multi-epitope vaccine candidates using a combination of B-cell and T-cell epitopes which would provoke both cellular and humoral immune responses to successfully combat COVID-19 disease.

Several recent studies by integrating in silico sequence-structural analysis have advanced our understanding of the molecular and evolutionary origin of SARS-CoV-2, detailed mechanism of viralhost binding interaction as well as identification of potential antiviral peptides and epitopic vaccine candidates as potential therapeutic options against coronaviruses. These advances are complemented by the development of novel computational databases and tools specific for coronavirus study which not only have accelerated research efforts to prevent COVID-19 but also strive to assemble the huge amount of genomic data and important research findings on freely accessible unified platforms to disseminate to the wider scientific community across the globe for further application. This review presents a comprehensive and up-to-date overview of newly developed computational resources including tools for coronavirus detection, resources for host-pathogen genome analysis, web servers for vaccine/drug discovery, docking tools for COVID-19 targets-ligand interactions, and visualization tools to real-time map the coronavirus spread and evolution, which will not only assist in handling this pandemic but also will make us better prepared for the re-emerging coronaviruses outbreak. 

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This is with reference to the manuscript entitled "Next-Generation Computational Tools and Resources for Coronavirus Research: from Detection to Vaccine Discovery; CBM-D-20-01872R6". We are sincerely grateful for considering the manuscript for publication in your esteemed journal. We are also thankful to the expert reviewers for their encouraging remarks on the scope of the paper. As per the suggestions by the reviewers and editor in chief, we had revised the manuscript with addition of more detailed discussion on the relevance of the article in the present global R&D efforts to combat COVID 19 pandemic. We are happy that the revised manuscript has been finally accepted for publication only after proof reading and correcting the typo errors and other English grammar mistakes.We fully realize the time and efforts involved in the painstaking review process and spotting the small typo errors, and therefore we have meticulously gone through the manuscript with many rounds of revision and have also shared with my colleagues with years of experience in the relevant field to improve the language of the manuscript.Honestly speaking, due to pandemic situation, no funds have been released for our ongoing govt sponsored research work and moreover this work is an exploratory in house research work and is not supported by any external funding agency. It would be extremely difficult to bear the expense of the suggested English editing services. However, we have used all free editing services that were available online and have also refined English grammatical structure and phraseology and hope that now the standard meets the journal criteria. Please find attached the revised manuscript [CBM-D-20-01872R6] with further corrections highlighted in track changing option and clean manuscript in this email. The same has also been uploaded online in the author dashboard.We have also employed the same protocol for another manuscript entitled "DBCOVP: A database of coronavirus virulent glycoprotein's" in Computers in Biology and Medicine which has been recently accepted and the proof ready copy has been received [CBM_104131].

Research is first of its kind and no similar published article is yet available, and most importantly it has been a long time invested in taking this article forward to get it published in your esteemed journal, we look forward to final confirmation of acceptance and publication in the Computers in Biology and Medicine to disseminate the knowledge to wider scientific community.Awaiting for a positive response 

The authors declare that they have no known competing financial interestsor personal relationships that could have appeared to influence the work reported in this paper.

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:J o u r n a l P r e -p r o o f