PhEVER: a database for the global exploration of virus-host evolutionary relationships

MOI is a comprehensive database collecting processed multi-omics data associated with viral infection

Viral infections pose significant public health challenges, exemplified by the global impact of COVID-19 caused by SARS-CoV-2. Understanding the intricate molecular mechanisms governing virus-host interactions is pivotal for effective intervention strategies. Despite the burgeoning multi-omics data on viral infections, a centralized database elucidating host responses to viruses remains lacking. In response, we have developed a comprehensive database named 'MOI' (available at http://www.fynn-guo.cn/ ), specifically designed to aggregate processed Multi-Omics data related to viral Infections. This meticulously curated database serves as a valuable resource for conducting detailed investigations into virus-host interactions. Leveraging high-throughput sequencing data and metadata from PubMed and Gene Expression Omnibus (GEO), MOI comprises over 3200 viral-infected samples, encompassing human and murine infections. Standardized processing pipelines ensure data integrity, including bulk RNA sequencing (RNA-seq), single-cell RNA-seq (scRNA-seq), Chromatin Immunoprecipitation sequencing (ChIP-seq), and Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq). MOI offers user-friendly interfaces presenting comprehensive cell marker tables, gene expression data, and epigenetic landscape charts. Analytical tools for DNA sequence conversion, FPKM calculation, differential gene expression, and Gene Ontology (GO)/ Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment enhance data interpretation. Additionally, MOI provides 16 visualization plots for intuitive data exploration. In summary, MOI serves as a valuable repository for researchers investigating virus-host interactions. By centralizing and facilitating access to multi-omics data, MOI aims to advance our understanding of viral pathogenesis and expedite the development of therapeutic interventions.

Navigating the Landscape: A Comprehensive Review of Current Virus Databases

Viruses are abundant and diverse entities that have important roles in public health, ecology, and agriculture. The identification and surveillance of viruses rely on an understanding of their genome organization, sequences, and replication strategy. Despite technological advancements in sequencing methods, our current understanding of virus diversity remains incomplete, highlighting the need to explore undiscovered viruses. Virus databases play a crucial role in providing access to sequences, annotations and other metadata, and analysis tools for studying viruses. However, there has not been a comprehensive review of virus databases in the last five years. This study aimed to fill this gap by identifying 24 active virus databases and included an extensive evaluation of their content, functionality and compliance with the FAIR principles. In this study, we thoroughly assessed the search capabilities of five database catalogs, which serve as comprehensive repositories housing a diverse array of databases and offering essential metadata. Moreover, we conducted a comprehensive review of different types of errors, encompassing taxonomy, names, missing information, sequences, sequence orientation, and chimeric sequences, with the intention of empowering users to effectively tackle these challenges. We expect this review to aid users in selecting suitable virus databases and other resources, and to help databases in error management and improve their adherence to the FAIR principles. The databases listed here represent the current knowledge of viruses and will help aid users find databases of interest based on content, functionality, and scope. The use of virus databases is integral to gaining new insights into the biology, evolution, and transmission of viruses, and developing new strategies to manage virus outbreaks and preserve global health.

Exploration of Computational Aids for Effective Drug Designing and Management of Viral Diseases: A Comprehensive Review

BACKGROUND

Microbial diseases, specifically originating from viruses are the major cause of human mortality all over the world. The current COVID-19 pandemic is a case in point, where the dynamics of the viral-human interactions are still not completely understood, making its treatment a case of trial and error. Scientists are struggling to devise a strategy to contain the pandemic for over a year and this brings to light the lack of understanding of how the virus grows and multiplies in the human body.

METHODS

This paper presents the perspective of the authors on the applicability of computational tools for deep learning and understanding of host-microbe interaction, disease progression and management, drug resistance and immune modulation through in silico methodologies which can aid in effective and selective drug development. The paper has summarized advances in the last five years. The studies published and indexed in leading databases have been included in the review.

RESULTS

Computational systems biology works on an interface of biology and mathematics and intends to unravel the complex mechanisms between the biological systems and the inter and intra species dynamics using computational tools, and high-throughput technologies developed on algorithms, networks and complex connections to simulate cellular biological processes.

CONCLUSION

Computational strategies and modelling integrate and prioritize microbial-host interactions and may predict the conditions in which the fine-tuning attenuates. These microbial-host interactions and working mechanisms are important from the aspect of effective drug designing and fine- tuning the therapeutic interventions.

Viral informatics: bioinformatics-based solution for managing viral infections

Several new viral infections have emerged in the human population and establishing as global pandemics. With advancements in translation research, the scientific community has developed potential therapeutics to eradicate or control certain viral infections, such as smallpox and polio, responsible for billions of disabilities and deaths in the past. Unfortunately, some viral infections, such as dengue virus (DENV) and human immunodeficiency virus-1 (HIV-1), are still prevailing due to a lack of specific therapeutics, while new pathogenic viral strains or variants are emerging because of high genetic recombination or cross-species transmission. Consequently, to combat the emerging viral infections, bioinformatics-based potential strategies have been developed for viral characterization and developing new effective therapeutics for their eradication or management. This review attempts to provide a single platform for the available wide range of bioinformatics-based approaches, including bioinformatics methods for the identification and management of emerging or evolved viral strains, genome analysis concerning the pathogenicity and epidemiological analysis, computational methods for designing the viral therapeutics, and consolidated information in the form of databases against the known pathogenic viruses. This enriched review of the generally applicable viral informatics approaches aims to provide an overview of available resources capable of carrying out the desired task and may be utilized to expand additional strategies to improve the quality of translation viral informatics research.

Bioinformatics Applications in Advancing Animal Virus Research

Viruses serve as infectious agents for all living entities. There have been various research groups that focus on understanding the viruses in terms of their host-viral relationships, pathogenesis and immune evasion. However, with the current advances in the field of science, now the research field has widened up at the ‘omics’ level. Apparently, generation of viral sequence data has been increasing. There are numerous bioinformatics tools available that not only aid in analysing such sequence data but also aid in deducing useful information that can be exploited in developing preventive and therapeutic measures. This chapter elaborates on bioinformatics tools that are specifically designed for animal viruses as well as other generic tools that can be exploited to study animal viruses. The chapter further provides information on the tools that can be used to study viral epidemiology, phylogenetic analysis, structural modelling of proteins, epitope recognition and open reading frame (ORF) recognition and tools that enable to analyse host-viral interactions, gene prediction in the viral genome, etc. Various databases that organize information on animal and human viruses have also been described. The chapter will converse on overview of the current advances, online and downloadable tools and databases in the field of bioinformatics that will enable the researchers to study animal viruses at gene level.

The unequivocal preponderance of biocomputation in clinical virology

Bioinformatics and computer based data simulation and modeling are captivating biological research, delivering great results already and promising to deliver more. As biological research is a complex, intricate, diverse field, any available support is gladly taken. With recent outbreaks and epidemics, pathogens are a constant threat to the global economy and security. Virus related plagues are somehow the most difficult to handle. Biocomputation has provided appreciable help in resolving clinical virology related issues. This review, for the first time, surveys the current status of the role of computation in virus related research. Advances made in the fields of clinical virology, antiviral drug design, viral immunology and viral oncology, through input from biocomputation, have been discussed. The amount of progress made and the software platforms available are consolidated in this review. The limitations of computation based methods are presented. Finally, the challenges facing the future of biocomputation in clinical virology are speculated upon.

Biocomputation in clinical virology.

Unraveling the web of viroinformatics: computational tools and databases in virus research

The beginning of the second century of research in the field of virology (the first virus was discovered in 1898) was marked by its amalgamation with bioinformatics, resulting in the birth of a new domain--viroinformatics. The availability of more than 100 Web servers and databases embracing all or specific viruses (for example, dengue virus, influenza virus, hepatitis virus, human immunodeficiency virus [HIV], hemorrhagic fever virus [HFV], human papillomavirus [HPV], West Nile virus, etc.) as well as distinct applications (comparative/diversity analysis, viral recombination, small interfering RNA [siRNA]/short hairpin RNA [shRNA]/microRNA [miRNA] studies, RNA folding, protein-protein interaction, structural analysis, and phylotyping and genotyping) will definitely aid the development of effective drugs and vaccines. However, information about their access and utility is not available at any single source or on any single platform. Therefore, a compendium of various computational tools and resources dedicated specifically to virology is presented in this article.

Use of host-like peptide motifs in viral proteins is a prevalent strategy in host-virus interactions

Viruses interact extensively with host proteins, but the mechanisms controlling these interactions are not well understood. We present a comprehensive analysis of eukaryotic linear motifs (ELMs) in 2,208 viral genomes and reveal that viruses exploit molecular mimicry of host-like ELMs to possibly assist in host-virus interactions. Using a statistical genomics approach, we identify a large number of potentially functional ELMs and observe that the occurrence of ELMs is often evolutionarily conserved but not uniform across virus families. Some viral proteins contain multiple types of ELMs, in striking similarity to complex regulatory modules in host proteins, suggesting that ELMs may act combinatorially to assist viral replication. Furthermore, a simple evolutionary model suggests that the inherent structural simplicity of ELMs often enables them to tolerate mutations and evolve quickly. Our findings suggest that ELMs may allow fast rewiring of host-virus interactions, which likely assists rapid viral evolution and adaptation to diverse environments.

VPDB: Viral Protein Structural Database

Viral Protein Database is an interactive database for three dimensional viral proteins. Our aim is to provide a comprehensive resource to the community of structural virology, with an emphasis on the description of derived data from structural biology. Currently, VPDB includes ˜1,670 viral protein structures from >277 viruses with more than 465 virus strains. The whole database can be easily accessed through the user convenience text search. Interactivity has been enhanced by using Jmol, WebMol and Strap to visualize the viral protein molecular structure.