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Using In Silico bioinformatics algorithms for the Accurate Prediction of the Impact of Spike Protein Mutations on the Pathogenicity, Stability, and Functionality of the SARS-CoV-2 Virus and Analysis of Potential Therapeutic Targets

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BIOCHEMICAL GENETICS 2023年第2期61卷 778-808页

作者： Alizadehmohajer, Negin Zahedifar, Shahrzad Sohrabi, Ehsan Basir, Sedighe Shaddel Nourigheimasi, Shima Falak, Reza Nedaeinia, Reza Ferns, Gordon A. Nejad, Asieh Emami Manian, Mostafa Univ Milan Dept Med Biotechnol & Translat Med I-20133 Milan Italy Islamic Azad Univ Fac Adv Sci & Technol Dept Genet Tehran Med Sci Tehran Iran Iran Univ Med Sci Fac Med Dept Med Genet & Mol Biol Tehran Iran Islamic Azad Univ Fac New Sci & Technol Branch Dept Microbiol Tehran Iran Arak Univ Med Sci Fac Med Arak Iran Iran Univ Med Sci Sch Med Dept Immunol Tehran Iran Isfahan Univ Med Sci Pediat Inherited Dis Res Ctr Res Inst Primordial Prevent Noncommunicable Dis Esfahan Iran Brighton & Sussex Med Sch Div Med Educ Brighton BN1 9PH E Sussex England Payame Noor Univ PNU Dept Biol POB 19395-3697 Tehran Iran Islamic Azad Univ Fac Med Sci Dept Med Lab Sci Kermanshah Branch Imam Khomeini CampusFarhikhtegan Bld Kermanshah *** Iran Isfahan Univ Med Sci Child Growth & Dev Res Ctr Res Inst Primordial Prevent Noncommunicable Dis Esfahan Iran

Coronavirus disease 2019 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We have used bioinformatics to investigate seventeen mutations in the spike protein of SARS-CoV-2, as this mediates infection of human cells and is the target of most vaccine strategies and antibody-based therapies. Two mutations, H146Y and S221W, were identified as being most pathogenic. Mutations at positions D614G, A829T, and P1263L might also have deleterious effects on protein function. We hypothesized that candidate small molecules may be repurposed to combat viral infection. We investigated changes in binding energies of the ligands and the mutant proteins by assessing molecular docking. For an understanding of cellular function and organization, protein-protein interactions are also critical. Protein-protein docking for naive and mutated structures of SARS-CoV-2 S protein was evaluated for their binding energy with the angiotensin-converting enzyme 2 (ACE2). These interactions might limit the binding of the SARS-CoV-2 spike protein to the ACE2 receptor or may have a deleterious effect on protein function that may limit infection. These results may have important implications for the transmission of SARS-CoV-2, its pathogenesis, and the potential for drug repurposing and immune therapies.

关键词： Spike mutations SARS-CoV-2 bioinformatics algorithms

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Opportunities from the Use of FPGAs as Platforms for bioinformatics algorithms

Opportunities from the Use of FPGAs as Platforms for Bioinfo...

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12th IEEE International Conference on bioinformatics and BioEngineering (BIBE)

作者： Chrysos, Grigorios Sotiriades, Euripides Rousopoulos, Christos Dollas, Apostolos Papadopoulos, Agathoklis Kirmitzoglou, Ioannis Promponas, Vasilis Theocharides, Theocharis Petihakis, George Lagnel, Jacques Vavylis, Panagiotis Kotoulas, George Tech Univ Crete Khania Greece Univ Cyprus CY-1678 Nicosia Cyprus Hellen Ctr Marine Res Iraklion Greece

ISBN: (纸本)9781467343589;9781467343572

This paper presents an in-depth look of how FPGA computing can offer substantial speedups in the execution of bioinformatics algorithms, with specific results achieved to date for a broad range of algorithms. Examples and case studies are presented for sequence comparison (BLAST, CAST), multiple sequence alignment (MAFFT, T-Coffee), RNA and protein secondary structure prediction (Zuker, Predator), gene prediction (Glimmer/GlimmerHMM) and phylogenetic tree computation (RAxML), running on mainstream FPGA technologies as well as high-end FPGA-based systems (Convey HC1, BeeCube). This work also presents technological and other obstacles that need to be overcome in order for FPGA computing to become a mainstream technology in bioinformatics.

关键词： bioinformatics algorithms FPGA based systems high performance

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An agent-based solution for dynamic multi-node wavefront balancing in biological sequence comparison

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EXPERT SYSTEMS WITH APPLICATIONS 2014年第10期41卷 4929-4938页

作者： Sandes, Edans Flavius de O. Ralha, Celia Ghedini de Melo, Alba Cristina M. A. Univ Brasilia Inst Exact Sci Dept Comp Sci BR-70 90497 Brasilia DF Brazil

Many parallel and distributed strategies were created to reduce the execution time of bioinformatics algorithms. One well-known bioinformatics algorithm is the Smith-Waterman, that may be parallelized using the wavefront method. When the wavefront is distributed across many heterogeneous nodes, it must be balanced to create a synchronous data flow. This is a very challenging problem if the nodes have variable computational power. This paper presents an agent-based solution for parallel biological sequence comparison applications that use the multi-node wavefront method. In our approach, autonomous agents are able to identify unbalanced computations and dynamically rebalance the load among the nodes. Two strategies were developed to the balancer agent in order to identify if the computations are balanced, one using global information and other using only local information. The global strategy demands a huge amount of data transfers, incurring in more communication, whereas the local strategy can decide about the balancing status using only local information. The results show that the balancing gains of strategies are very close. Thus, the local strategy is preferred, since it can be implemented in real wavefront balancers with almost the same benefits as the global strategy. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Agent-based approach bioinformatics algorithms Heterogeneous multi-node wavefront method Parallel biological sequence comparison Smith-Waterman algorithm

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RNA-mediated translation regulation in viral genomes: computational advances in the recognition of sequences and structures

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BRIEFINGS IN bioinformatics 2020年第4期21卷 1151-1163页

作者： Gupta, Asmita Bansal, Manju Ctr DNA Fingerprinting & Diagnost Hyderabad India

RNA structures are widely distributed across all life forms. The global conformation of these structures is defined by a variety of constituent structural units such as helices, hairpin loops, kissing-loop motifs and pseudoknots, which often behave in a modular way. Their ubiquitous distribution is associated with a variety of functions in biological processes. The location of these structures in the genomes of RNA viruses is often coordinated with specific processes in the viral life cycle, where the presence of the structure acts as a checkpoint for deciding the eventual fate of the process. These structures have been found to adopt complex conformations and exert their effects by interacting with ribosomes, multiple host translation factors and small RNA molecules like miRNA. A number of such RNA structures have also been shown to regulate translation in viruses at the level of initiation, elongation or termination. The role of various computational studies in the preliminary identification of such sequences and/or structures and subsequent functional analysis has not been fully appreciated. This review aims to summarize the processes in which viral RNA structures have been found to play an active role in translational regulation, their global conformational features and the bioinformatics/computational tools available for the identification and prediction of these structures.

关键词： RNA viruses non-canonical translation bioinformatics algorithms RNA secondary structure RNA structure dynamics viral bioinformatics

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Computational complexity of algorithms for sequence comparison, short-read assembly and genome alignment

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BIOSYSTEMS 2017年 156卷 72-85页

作者： Baichoo, Shakuntala Ouzounis, Christos A. Univ Mauritius Dept Comp Sci & Engn Reduit 80837 Mauritius Ctr Res & Technol Hellas Chem Proc & Energy Resources Inst Biol Computat & Proc Lab Thessaloniki 57001 Greece

A multitude of algorithms for sequence comparison, short-read assembly and whole-genome alignment have been developed in the general context of molecular biology, to support technology development for high-throughput sequencing, numerous applications in genome biology and fundamental research on comparative genomics. The computational complexity of these algorithms has been previously reported in original research papers, yet this often neglected property has not been reviewed previously in a systematic manner and for a wider audience. We provide a review of space and time complexity of key sequence analysis algorithms and highlight their properties in a comprehensive manner, in order to identify potential opportunities for further research in algorithm or data structure optimization. The complexity aspect is poised to become pivotal as we will be facing challenges related to the continuous increase of genomic data on unprecedented scales and complexity in the foreseeable future, when robust biological simulation at the cell level and above becomes a reality. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Computational complexity bioinformatics algorithms Sequence comparison Short-read assembly Genome alignment

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Exploring crop genomes: assembly features, gene prediction accuracy, and implications for proteomics studies

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BMC GENOMICS 2024年第1期25卷 619页

作者： Abbas, Qussai Wilhelm, Mathias Kuster, Bernhard Poppenberger, Brigitte Frishman, Dmitrij Tech Univ Munich Chair Bioinformat TUM Sch Life Sci Freising Weihenstephan Germany Tech Univ Munich TUM Sch Life Sci Computat Mass Spectrometry Freising Weihenstephan Germany Tech Univ Munich Munich Data Sci Inst Garching Germany Tech Univ Munich Chair Prote & Bioanalyt TUM Sch Life Sci Freising Weihenstephan Germany Tech Univ Munich TUM Sch Life Sci Biotechnol Hort Crops Freising Weihenstephan Germany

Plant genomics plays a pivotal role in enhancing global food security and sustainability by offering innovative solutions for improving crop yield, disease resistance, and stress tolerance. As the number of sequenced genomes grows and the accuracy and contiguity of genome assemblies improve, structural annotation of plant genomes continues to be a significant challenge due to their large size, polyploidy, and rich repeat content. In this paper, we present an overview of the current landscape in crop genomics research, highlighting the diversity of genomic characteristics across various crop species. We also assessed the accuracy of popular gene prediction tools in identifying genes within crop genomes and examined the factors that impact their performance. Our findings highlight the strengths and limitations of BRAKER2 and Helixer as leading structural genome annotation tools and underscore the impact of genome complexity, fragmentation, and repeat content on their performance. Furthermore, we evaluated the suitability of the predicted proteins as a reliable search space in proteomics studies using mass spectrometry data. Our results provide valuable insights for future efforts to refine and advance the field of structural genome annotation.

关键词： Crop genomics Genome annotation Gene prediction Plant evolution Peptide identification bioinformatics algorithms

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HAPLOTYPE INFERENCE FROM SHORT SEQUENCE READS USING A POPULATION GENEALOGICAL HISTORY MODEL

HAPLOTYPE INFERENCE FROM SHORT SEQUENCE READS USING A POPULA...

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16th Pacific Symposium on Biocomputing

作者： Zhang, Jin Wu, Yufeng Univ Connecticut Dept Comp Sci & Engn Storrs CT 06269 USA

ISBN: (纸本)9789814335058

High-throughput sequencing is currently a major transforming technology in biology. In this paper, we study a population genomics problem motivated by the newly available short reads data from high-throughput sequencing. In this problem, we are given short reads collected from individuals in a population. The objective is to infer haplotypes with the given reads. We first formulate the computational problem of haplotype inference with short reads. Based on a simple probabilistic model on short reads, we present a new approach of inferring haplotypes directly from given reads (i.e. without first calling genotypes). Our method is finding the most likely haplotypes whose local genealogical history can be approximately modeled as a perfect phylogeny. We show that the optimal haplotypes under this objective can be found for many data using integer linear programming for modest sized data when there is no recombination. We then develop a related heuristic method which can work with larger data, and also allows recombination. Simulation shows that the performance of our method is competitive against alternative approaches.

关键词： High-throughput sequencing haplotype inference bioinformatics algorithms population genomics

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A network-based approach to mine temporal genes exhibiting significant expression variation in Caenorhabditis elegans

A network-based approach to mine temporal genes exhibiting s...

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Biological Ontologies and Knowledge Bases Workshop at IEEE International Conference on bioinformatics and Biomedicine (IEEE BIBM)

作者： Cooper, Kathryn Hassan, Wail Ali, Hesham Univ Nebraska Coll Informat Sci & Technol Omaha NE 68182 USA Univ Missouri Kansas City Sch Med Dept Biomed Sci Kansas City MO USA

ISBN: (纸本)9781509030507

It is critical to be able to identify longitudinally changing genes in temporal data so that studies can be focused on how gene expression changes in a dynamic way. While biological networks continue to play a significant role in modeling and characterizing complex relationships in biological systems, most network modeling studies in biomedical research focus on snapshot or "static" network-based analysis to identify genes of interest. In this study, we use a temporal non-sampling network-based approach to identify and rank genes that exhibit significant co-expression variation over time. We use in the C. elegans gene correlation network obtained from mRNA expression profiles to illustrate the value of the proposed approach. We compare the results of this method to results obtained from traditional statistical analysis that focuses on identifying simple differentially expressed genes. We show that rank-based temporal network analysis can identify genes that contribute to changes in the network structure and consequently contribute to changes in the genetic regulatory machine.

关键词： temporal network analysis gene expression co-expression networks bioinformatics algorithms

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Network traffic classification by common subsequence finding

Network traffic classification by common subsequence finding

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8th International Conference on Computational Science

作者： Fabjanski, Krzysztof Kruk, Tomasz NASK Div Res PL-02796 Warsaw Poland

ISBN: (纸本)9783540693833

The paper describes issues related to network traffic analysis. The scope of this article includes discussion regarding the problem of network traffic identification and classification. Furthermore, paper presents two bioinformatics methods: Clustal and Center Star. Both methods were precisely adapted to the network security purpose. In both methods, the concept of extraction of a common subsequence, based on multiple sequence alignment of more than two network attack signatures, was used. This concept was inspired by bioinformatics solutions for the problems related to finding similarities in a set of DNA, RNA or amino acids sequences. Additionally, the scope of the paper includes detailed description of test procedures and their results. At the end some relevant evaluations and conclusions regarding both methods are presented.

关键词： network traffic analysis anomaly detection network intrusion detection systems common subsequence finding bioinformatics algorithms Clustal algorithm Center Star method automated generation of network attack signatures

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Predicting HIV-1 broadly neutralizing antibody epitope networks using neutralization titers and a novel computational method

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BMC bioinformatics 2014年第1期15卷 1-15页

作者： Evans, Mark C. Phung, Pham Paquet, Agnes C. Parikh, Anvi Petropoulos, Christos J. Wrin, Terri Haddad, Mojgan Monogram Biosci Inc San Francisco CA 94080 USA

Background: Recent efforts in HIV-1 vaccine design have focused on immunogens that evoke potent neutralizing antibody responses to a broad spectrum of viruses circulating worldwide. However, the development of effective vaccines will depend on the identification and characterization of the neutralizing antibodies and their epitopes. We developed bioinformatics methods to predict epitope networks and antigenic determinants using structural information, as well as corresponding genotypes and phenotypes generated by a highly sensitive and reproducible neutralization assay. 282 clonal envelope sequences from a multiclade panel of HIV-1 viruses were tested in viral neutralization assays with an array of broadly neutralizing monoclonal antibodies (mAbs: b12, PG9,16,PGT121-128, PGT130-131, PGT135-137, PGT141-145, and PGV04). We correlated IC50 titers with the envelope sequences, and used this information to predict antibody epitope networks. Structural patches were defined as amino acid groups based on solvent-accessibility, radius, atomic depth, and interaction networks within 3D envelope models. We applied a boosted algorithm consisting of multiple machine-learning and statistical models to evaluate these patches as possible antibody epitope regions, evidenced by strong correlations with the neutralization response for each antibody. Results: We identified patch clusters with significant correlation to IC50 titers as sites that impact neutralization sensitivity and therefore are potentially part of the antibody binding sites. Predicted epitope networks were mostly located within the variable loops of the envelope glycoprotein (gp120), particularly in V1/V2. Site-directed mutagenesis experiments involving residues identified as epitope networks across multiple mAbs confirmed association of these residues with loss or gain of neutralization sensitivity. Conclusions: Computational methods were implemented to rapidly survey protein structures and predict epitope networks ass

关键词： HIV-1 antibody Thick patch analysis bioinformatics algorithms Boosting algorithm Machine learning Neutralization in-silico epitope mapping Epitope networks Structural mapping Sequence and structure analysis

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