Multiple Sequence Alignment Techniques Research Articles

Identification of Human miRNA Biomarkers Targeting the SARS-CoV-2 Genome.

SARS-CoV-2 poses a great challenge toward mankind, majorly due to its evolution and frequently occurring variants. On the other hand, in human hosts, microRNA (miRNA) plays a vital role in replication and propagation during a viral infection and can control the biological processes. This may be essential for the progression of viral infection. Moreover, human miRNAs can play a therapeutic role in treatment of different viral diseases by binding to the target sites of the virus genome, thereby hindering the essential functioning of the virus. Motivated by this fact, we have hypothesized a new approach in order to identify human miRNAs that can target the mRNA (genome) of SARS-CoV-2 to degrade their protein synthesis. In this regard, the multiple sequence alignment technique Clustal Omega is used to align a complement of 2656 human miRNAs with the SARS-CoV-2 reference genome (mRNA). Thereafter, ranking of these aligned human miRNAs is performed with the help of a new scoring function that takes into account the (a) total number of nucleotide matches between the human miRNA and the SARS-CoV-2 genome, (b) number of consecutive nucleotide matches between the human miRNA and the SARS-CoV-2 genome, (c) number of nucleotide mismatches between the human miRNA and the SARS-CoV-2 genome, and (d) the difference in length before and after alignment of the human miRNA. As a result, from the 2656 ranked miRNAs, the top 20 human miRNAs are reported, which are targeting different coding and non-coding regions of the SARS-CoV-2 genome. Moreover, molecular docking of such human miRNAs with virus mRNA is performed to verify the efficacy of the interactions. Furthermore, 4 miRNAs out of the top 20 miRNAs are identified to have the seed region. In order to inhibit the virus, the key human targets of the seed regions may be targeted. Repurposable drugs like carfilzomib, bortezomib, hydralazine, and paclitaxel are identified for such purpose.

Prevalence and Molecular Mapping of Multidrug-resistant Mycobacterium tuberculosis in Sokoto, North-Western Nigeria

Background: The emergence of multidrug-resistant tuberculosis tuberculosis (MDR-TB) poses a significant danger to Nigeria’s TB control efforts. Nigeria records 570000 new TB cases each year, and it is one of the world’s greatest TB-burden countries as well as one of the top ten countries with MDR-TB. This study aimed to determine the MDR prevalence, phylogenetic analysis, and molecular mapping as well as the link between MDR prevalence and demographic data. Methods: The study comprised 100 TB patients recruited consecutively. The proportion method on Lowenstein-Jensen (LJ) medium was used for drug susceptibility testing. Conventional polymerase chain reaction (PCR) was used, and the rrs genes were amplified and sequenced. Multiple sequence alignment techniques were used to compare the PCR product sequences to reference sequences retrieved from GenBank. Results: Rifampicin (RIF) resistance was found in 29% (22.75), ethambutol resistance was found in 20% (15.75), and isoniazid (INH) resistance was found in 28% (21.75). Further, RIF and INH resistance were found in 20% (15.75) of the samples. At nucleotide position 892, four isolates (31%) contained a G-A transition, and the most prevalent mutation found in the rrs gene was S531L (80%, 12.15). The phylogenetic analysis indicated that three of the Sokoto isolates are closely linked to reference isolates from Iran, Germany, China, and Sudan in terms of geographical relatedness. Conclusions: The obtained data revealed that acquired resistance is a major factor in the establishment of MDR-TB in Sokoto, which could be owing to poor adherence to medication or poor treatment of TB patients.

Human miRNAs to Identify Potential Regions of SARS-CoV-2.

It is two years now but the world is still struggling against COVID-19 due to the havoc created by the SARS-CoV-2 virus and its multiple variants. Considering this perspective, in this work, we have hypothesized a new approach in order to identify potential regions in SARS-CoV-2 similar to the human miRNAs. Thus, they may have similar consequences as caused by the human miRNAs in human body. Therefore, the same way by which human miRNAs are inhibited can be applied for such potential regions of virus as well by administering drugs to the interacting human proteins. In this regard, the multiple sequence alignment technique Clustal Omega is used to align 2656 human miRNAs with the SARS-CoV-2 reference genome to identify the potential regions within the virus reference genome which have high similarities with the human miRNAs. The potential regions in virus genome are identified based on the highest number of nucleotide match, greater than or equal to 5 at a genomic position, for the aligned miRNAs. As a result, 38 potential SARS-CoV-2 regions are identified consisting of 249 human miRNAs. Among these 38 potential regions, some top regions belong to nucleocapsid, RdRp, helicase, and ORF8. To understand the biological significance of these potential regions, the targets of the human miRNAs are considered for KEGG pathways and protein–protein and drug–protein interaction analysis as the human miRNAs are similar to the potential regions of SARS-CoV-2. Significant pathways are found which lead to comorbidities. Subsequently, drugs like emodin, bicalutamide, vorinostat, etc. are identified that may be used for clinical trials.

Immunogenicity and antigenicity based T-cell and B-cell epitopes identification from conserved regions of 10664 SARS-CoV-2 genomes.

The surge of SARS-CoV-2 has created a wave of pandemic around the globe due to its high transmission rate. To contain this virus, researchers are working around the clock for a solution in the form of vaccine. Due to the impact of this pandemic, the economy and healthcare have immensely suffered around the globe. Thus, an efficient vaccine design is the need of the hour. Moreover, to have a generalised vaccine for heterogeneous human population, the virus genomes from different countries should be considered. Thus, in this work, we have performed genome-wide analysis of 10,664 SARS-CoV-2 genomes of 73 countries around the globe in order to identify the potential conserved regions for the development of peptide based synthetic vaccine viz. epitopes with high immunogenic and antigenic scores. In this regard, multiple sequence alignment technique viz. Clustal Omega is used to align the 10,664 SARS-CoV-2 virus genomes. Thereafter, entropy is computed for each genomic coordinate of the aligned genomes. The entropy values are then used to find the conserved regions. These conserved regions are refined based on the criteria that their lengths should be greater than or equal to 60 nt and their corresponding protein sequences are without any stop codons. Furthermore, Nucleotide BLAST is used to verify the specificity of the conserved regions. As a result, we have obtained 17 conserved regions that belong to NSP3, NSP4, NSP6, NSP8, RdRp, Helicase, endoRNAse, 2’-O-RMT, Spike glycoprotein, ORF3a protein, Membrane glycoprotein and Nucleocapsid protein. Finally, these conserved regions are used to identify the T-cell and B-cell epitopes with their corresponding immunogenic and antigenic scores. Based on these scores, the most immunogenic and antigenic epitopes are then selected for each of these 17 conserved regions. Hence, we have obtained 30 MHC-I and 24 MHC-II restricted T-cell epitopes with 14 and 13 unique HLA alleles and 21 B-cell epitopes for the 17 conserved regions. Moreover, for validating the relevance of these epitopes, the binding conformation of the MHC-I and MHC-II restricted T-cell epitopes are shown with respect to HLA alleles. Also, the physico-chemical properties of the epitopes are reported along with Ramchandran plots and Z-Scores and the population coverage is shown as well. Overall, the analysis shows that the identified epitopes can be considered as potential candidates for vaccine design.

Genome-wide analysis of Indian SARS-CoV-2 genomes to identify T-cell and B-cell epitopes from conserved regions based on immunogenicity and antigenicity

SARS-CoV-2 has a high transmission rate and shows frequent mutations, thus making vaccine development an arduous task. However, researchers around the globe are working hard to find a solution e.g. synthetic vaccine. Here, we have performed genome-wide analysis of 566 Indian SARS-CoV-2 genomes to extract the potential conserved regions for identifying peptide based synthetic vaccines, viz. epitopes with high immunogenicity and antigenicity. In this regard, different multiple sequence alignment techniques are used to align the SARS-CoV-2 genomes separately. Subsequently, consensus conserved regions are identified after finding the conserved regions from each aligned result of alignment techniques. Further, the consensus conserved regions are refined considering that their lengths are greater than or equal to 60nt and their corresponding proteins are devoid of any stop codons. Subsequently, their specificity as query coverage are verified using Nucleotide BLAST. Finally, with these consensus conserved regions, T-cell and B-cell epitopes are identified based on their immunogenic and antigenic scores which are then used to rank the conserved regions. As a result, we have ranked 23 consensus conserved regions that are associated with different proteins. This ranking also resulted in 34 MHC-I and 37 MHC-II restricted T-cell epitopes with 16 and 19 unique HLA alleles and 29 B-cell epitopes. After ranking, the consensus conserved region from NSP3 gene is obtained that is highly immunogenic and antigenic. In order to judge the relevance of the identified epitopes, the physico-chemical properties and binding conformation of the MHC-I and MHC-II restricted T-cell epitopes are shown with respect to HLA alleles.

Inferring the genetic variability in Indian SARS-CoV-2 genomes using consensus of multiple sequence alignment techniques.

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is a threat to the human population and has created a worldwide pandemic. Daily thousands of people are getting affected by the SARS-CoV-2 virus; India being no exception. In this situation, there is no doubt that vaccine is the primary prevention strategy to contain the wave of COVID-19 pandemic. In this regard, genome-wide analysis of SARS-CoV-2 is important to understand its genetic variability. This has motivated us to analyse 566 Indian SARS-CoV-2 sequences using multiple sequence alignment techniques viz. ClustalW, MUSCLE, ClustalO and MAFFT to align and subsequently identify the lists of mutations as substitution, deletion, insertion and SNP. Thereafter, a consensus of these results, called as Consensus Multiple Sequence Alignment (CMSA), is prepared to have the final list of mutations so that the advantages of all four alignment techniques can be preserved. The analysis shows 767, 2025 and 54 unique substitutions, deletions and SNPs in Indian SARS-CoV-2 genomes. More precisely, out of 54 SNPs, 4 SNPs are present close to the 60% of the virus population. The results of this experiment can be useful for virus classification, designing and defining the dose of vaccine for the Indian population.

Optimised parallel implementation with dynamic programming technique for the multiple sequence alignment

Gene sequencing techniques are very useful in analysing various diseases, especially cancer. The various techniques have been applied for the gene sequence for the effective analysis. These technique help also in reducing the computation time. Most existing methods are of low efficiency in the gene sequence alignment due to lack of proper technique to reduce the gap penalty. In this research, the optimised Needleman-Wunsch (ONW) algorithm is applied for multiple sequence alignment (MSA). The ONW technique uses Needleman-Wunsch (NW) algorithm in parallel implementation for multiple genes. The dynamic programming technique such as the backtracking algorithm is applied for reducing the gap penalty in the gene alignment. The proposed ONW algorithm is applied in the case study and being analysed for its performance. This proves that the proposed ONW algorithm has higher performance compared to the other existing method in the MSA techniques. The proposed method has an average similarity of 88.85%, while the existing method has a similarity of 60.23%.

LegumeDB: Development of Legume Medicinal Plant Database and Comparative Molecular Evolutionary Analysis of matK Proteins of Legumes and Mangroves

Background: Legume plants are known for their rich medicinal and nutritional values. Large amount of medicinal information of various legume plants have been dispersed in the form of text. Objective: It is essential to design and construct a legume medicinal plants database, which integrate respective classes of legumes and include knowledge regarding medicinal applications along with their protein/enzyme sequences. Methods: The design and development of Legume Medicinal Plants Database (LegumeDB) has been done by using Microsoft Structure Query Language Server 2017. DBMS was used as back end and ASP.Net was used to lay out front end operations. VB.Net was used as arranged program for coding. Multiple sequence alignment, phylogenetic analysis and homology modeling techniques were also used. Results: This database includes information of 50 Legume medicinal species, which might be helpful to explore the information for researchers. Further, maturase K (matK) protein sequences of legumes and mangroves were retrieved from NCBI for multiple sequence alignment and phylogenetic analysis to understand evolutionary lineage between legumes and mangroves. Homology modeling technique was used to determine three-dimensional structure of matK from Legume species i.e. Vigna unguiculata using matK of mangrove species, Thespesia populnea as a template. The matK sequence analysis results indicate the conserved residues among legume and mangrove species. Conclusion: Phylogenetic analysis revealed closeness between legume species Vigna unguiculata and mangrove species Thespesia populnea to each other, indicating their similarity and origin from common ancestor. Thus, these studies might be helpful to understand evolutionary relationship between legumes and mangroves. : LegumeDB availability: http://legumedatabase.co.in

Modelling melodic variation and extracting melodic templates from flamenco singing performances

A key concept in flamenco singing is the constant re-interpretation of orally transmitted melodic templates, which undergo variation and ornamentation during spontaneous performances. We propose a novel framework which allows us to model a set of interpretations of the same melody and analyse differences among them. We apply a multiple progressive sequence alignment technique to obtain a graphical model holding the frequency of occurrence of characteristic notes and note transitions, from which the underlying melodic template can be approximated. In a case study, we showcase how visualisations of the derived model yield insights into local and global melodic stability and inter-style contour similarities. We furthermore show how the extracted templates can used to identify instances of a particular melody in a large corpus of automatic transcriptions.

MARS: improving multiple circular sequence alignment using refined sequences

BackgroundA fundamental assumption of all widely-used multiple sequence alignment techniques is that the left- and right-most positions of the input sequences are relevant to the alignment. However, the position where a sequence starts or ends can be totally arbitrary due to a number of reasons: arbitrariness in the linearisation (sequencing) of a circular molecular structure; or inconsistencies introduced into sequence databases due to different linearisation standards. These scenarios are relevant, for instance, in the process of multiple sequence alignment of mitochondrial DNA, viroid, viral or other genomes, which have a circular molecular structure. A solution for these inconsistencies would be to identify a suitable rotation (cyclic shift) for each sequence; these refined sequences may in turn lead to improved multiple sequence alignments using the preferred multiple sequence alignment program.ResultsWe present MARS, a new heuristic method for improving Multiple circular sequence Alignment using Refined Sequences. MARS was implemented in the C++ programming language as a program to compute the rotations (cyclic shifts) required to best align a set of input sequences. Experimental results, using real and synthetic data, show that MARS improves the alignments, with respect to standard genetic measures and the inferred maximum-likelihood-based phylogenies, and outperforms state-of-the-art methods both in terms of accuracy and efficiency. Our results show, among others, that the average pairwise distance in the multiple sequence alignment of a dataset of widely-studied mitochondrial DNA sequences is reduced by around 5% when MARS is applied before a multiple sequence alignment is performed.ConclusionsAnalysing multiple sequences simultaneously is fundamental in biological research and multiple sequence alignment has been found to be a popular method for this task. Conventional alignment techniques cannot be used effectively when the position where sequences start is arbitrary. We present here a method, which can be used in conjunction with any multiple sequence alignment program, to address this problem effectively and efficiently.

A time warping approach to multiple sequence alignment.

We propose an approach for multiple sequence alignment (MSA) derived from the dynamic time warping viewpoint and recent techniques of curve synchronization developed in the context of functional data analysis. Starting from pairwise alignments of all the sequences (viewed as paths in a certain space), we construct a median path that represents the MSA we are looking for. We establish a proof of concept that our method could be an interesting ingredient to include into refined MSA techniques. We present a simple synthetic experiment as well as the study of a benchmark dataset, together with comparisons with 2 widely used MSA softwares.

Multiple Sequence Alignment.

The increasing importance of Next Generation Sequencing (NGS) techniques has highlighted the key role of multiple sequence alignment (MSA) in comparative structure and function analysis of biological sequences. MSA often leads to fundamental biological insight into sequence-structure-function relationships of nucleotide or protein sequence families. Significant advances have been achieved in this field, and many useful tools have been developed for constructing alignments, although many biological and methodological issues are still open. This chapter first provides some background information and considerations associated with MSA techniques, concentrating on the alignment of protein sequences. Then, a practical overview of currently available methods and a description of their specific advantages and limitations are given, to serve as a helpful guide or starting point for researchers who aim to construct a reliable MSA.

다중 서열 정렬 기법을 이용한 악성코드 패밀리 추천

악성코드 개발자들은 악성코드 탐지를 회피하기 위하여 변종 악성코드를 유포한다. 정적 분석기반의 안티 바이러스로는 변종 악성코드를 탐지하기 어려우며, 따라서 API 호출 정보 기반의 동적 분석이 필요하다. 본 논문에서는 악성코드 분석가의 변종 악성코드 패밀리 분류에 도움을 줄 수 있는 악성코드 패밀리 추천 기법을 제안하였다. 악성코드 패밀리의 API 호출 정보를 동적 분석을 통하여 추출하였다. 추출한 API 호출 정보에 다중 서열 정렬 기법을 적용하였다. 정렬 결과로부터 각 악성코드 패밀리의 시그니쳐를 추출하였다. 시그니쳐와의 유사도를 기준으로, 제안하는 기법이 새로운 악성코드의 패밀리 후보를 3개까지 추천하도록 하였다. 실험을 통하여 제안한 악성코드 패밀리 추천 기법의 정확도를 측정하였다.

Molecular cloning, characterization and expression of a gene encoding phosphoketolase from Termitomyces clypeatus

A phosphoketolase (pk) gene from the fungus Termitomyces clypeatus (TC) was cloned and partially characterized. Oligonucleotide primers specific for the phosphoketolase gene (pk) were designed from the regions of homologies found in the primary structure of the enzyme from other fungal sources related to TC, using multiple sequence alignment technique. The cDNA of partial lengths were amplified, cloned and sequenced in three parts by 3′ and 5′ RACE and RT-PCR using these oligonucleotide primers. The full length ds cDNA was constructed next by joining these three partial cDNA sequences having appropriate overlapping regions using Overlap Extension PCR technique. The constructed full length cDNA exhibited an open reading frame of 2487 bases and 5′ and 3′ UTRs. The deduced amino acid sequence, which is of 828 amino acids, when analyzed with NCBI BLAST, showed high similarities with the phosphoketolase enzyme (Pk) superfamily with expected domains. The part of the TC genomic DNA comprising of the pk gene was also amplified, cloned and sequenced and was found to contain two introns of 68 and 74 bases that interrupt the pk reading frame. The coding region of pk cDNA was subcloned in pKM260 expression vector in correct frame and the protein was expressed in Escherichia coli BL21 (DE3) transformed with this recombinant expression plasmid. The recombinant protein purified by His-tag affinity chromatography indicated the presence of a protein of the expected size. In vivo expression studies of the gene in presence of different carbon sources indicated synthesis of Pk specific mRNA, as expected. Phylogenetic studies revealed a common ancestry of the fungal and bacterial Pk. The TC is known to secrete several industrially important enzymes involved in carbohydrate metabolism. However, the presence of Pk, a key enzyme in pentose metabolism, has not been demonstrated conclusively in this organism. Cloning, sequencing and expression study of this gene establishes the functioning of this gene in T. clypeatus. The Pk from TC is a new source for commercial exploitation.

DNA Multiple Sequence Alignment by a Hidden Markov Model and Fuzzy Levenshtein Distance based Genetic Algorithm

In the last decade, biologists have experienced a fundamental shift away from the traditional empirical research to largescale, computer-based research. Today bio-informatics is a systematic and predictive discipline which encompasses genomics, informatics, automation, and miniaturization. This fusion of biology and information science is expected to continue and expand for the foreseeable future. DNA Sequence alignment is a commonly observed problem in bioinformatics for establishing similarity and evolutionary relationship between DNA sequences. This paper has presented a DNA multiple sequence alignment technique by a genetic algorithm based on Hidden Markov Model and Fuzzy Levenshtein Distance. General Terms Bio-informatics, DNA, Sequence Alignment

A Knowledge-Based Multiple-Sequence Alignment Algorithm

A common and cost-effective mechanism to identify the functionalities, structures, or relationships between species is multiple-sequence alignment, in which DNA/RNA/protein sequences are arranged and aligned so that similarities between sequences are clustered together. Correctly identifying and aligning these sequence biological similarities help from unwinding the mystery of species evolution to drug design. We present our knowledge-based multiple sequence alignment (KB-MSA) technique that utilizes the existing knowledge databases such as SWISSPROT, GENBANK, or HOMSTRAD to provide a more realistic and reliable sequence alignment. We also provide a modified version of this algorithm (CB-MSA) that utilizes the sequence consistency information when sequence knowledge databases are not available. Our benchmark tests on BAliBASE, PREFAB, HOMSTRAD, and SABMARK references show accuracy improvements up to 10 percent on twilight data sets against many leading alignment tools such as ISPALIGN, PADT, CLUSTALW, MAFFT, PROBCONS, and T-COFFEE.

Evaluation of a Set of C9 N-acyl Neu5Ac2en Mimetics as Viral Sialidase Selective Inhibitors.

Identification of selective influenza viral sialidase inhibitors is highly desirable in order to minimize or avoid the adverse effects due to the possible inhibition of endogenous human sialidases. We recently reported the evaluation of C9 N-acyl Neu5Ac2en mimetics as probes for human sialidases. Herein, we describe the in vitro activity of the same set of C9 N-acyl Neu5Ac2en mimetics against sialidases expressed by influenza virus A/PR/8/34 (H1N1), A/Memphis/1/72 (H3N2), and A/Duck/313/78 (H5N3) strains. Compound 8 is identified as a promising starting point for the development of viral sialidase selective inhibitors. Multiple sequence alignment and molecular docking techniques are also performed to explore the plausible interaction of compound 8 with viral sialidases.

Using a bioinformatics approach to generate accurate exploit-based signatures for polymorphic worms

In this paper, we propose Simplified Regular Expression (SRE) signature, which uses multiple sequence alignment techniques, drawn from bioinformatics, in a novel approach to generating more accurate exploit-based signatures. We also provide formal definitions of what is “a more specific” and what is “the most specific” signature for a polymorphic worm and show that the most specific exploit-based signature generation is NP-hard. The approach involves three steps: multiple sequence alignment to reward consecutive substring extractions, noise elimination to remove noise effects, and signature transformation to make the SRE signature compatible with current IDSs. Experiments on a range of polymorphic worms and real-world polymorphic shellcodes show that our bioinformatics approach is noise-tolerant and as that because it extracts more polymorphic worm characters, like one-byte invariants and distance restrictions between invariant bytes, the signatures it generates are more accurate and precise than those generated by some other exploit-based signature generation schemes.

A bio-inspired application of natural language processing: A case study in extracting multiword expression

For the multiword expression (MWE) extraction, the multiple sequence alignment (MSA) is proposed on the motivation of gene recognition. Because textual sequence is similar to gene sequence in pattern analysis. This MSA technique is combined with error-driven rules, with the improved efficiency beyond the traditional methods. It provides a guarantee for the MWE recall. It uses the dynamic programming method to prevent candidates from combinational explosion, and provides a global solution for pattern extraction instead of sub-pattern redundancy. Consequently, it has accurate measures for flexible patterns. In experiment, some advanced statistical measures are performed for ranking candidates. In the comparison experiment, the MSA approach achieved better results.

An Overview of Multiple Sequence Alignment

Multiple sequence alignment is perhaps the most commonly applied bioinformatics technique. It often leads to fundamental biological insight into sequence-structure-function relationships of nucleotide or protein sequence families. In this unit, an overview of multiple sequence alignment techniques is presented, covering a history of nearly 30 years from the early pioneering methods to the current state-of-the-art techniques. Methodological and biological issues and end-user considerations, as well as alignment evaluation issues, are discussed.