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Bioinformatics and Computational Approaches in Viral Genomics and Evolution 2025–2026

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A special issue of Viruses (ISSN 1999-4915). This special issue belongs to the section "General Virology".

Deadline for manuscript submissions: 16 December 2026 | Viewed by 7633

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Special Issue Editors

Dr. Camila Malta Romano

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Guest Editor

Laboratório de Virologia, Instituto de Medicina Tropical, Universidade de São Paulo, São Paulo 05403-000, SP, Brazil
Interests: virus evolution; genomics and phylogenetics

Prof. Dr. Mariana Severo Ramundo

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Guest Editor

1. Laboratory of Immunology, INCOR, Hospital das Clínicas HCFMUSP, Faculty of Medicine, University of São Paulo, São Paulo 05403-900, Brazil
2. Department of Internal Medicine, Discipline of Clinical Immunology and Allergy, Faculty of Medicine, University of São Paulo, São Paulo 01246-903, Brazil
Interests: bioinformatics; systems biology; artificial intelligence

Dr. Nilson Coimbra

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Guest Editor

Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, SP, Brazil
Interests: bioinformatics; computational biology and evolution

Special Issue Information

Dear Colleagues,

We are pleased to invite submissions to a Special Issue of Viruses titled “Bioinformatics and Computational Approaches in Viral Genomics and Evolution 2025–2026”.

The rapid evolution of viral pathogens and the urgency for surveillance of emergent and reemergent viruses highlight the critical need for advanced computational methods in understanding their behavior, transmission, and adaptation. The integration of bioinformatics tools and genomic data analysis is essential for monitoring viral evolution, predicting new threats, and developing targeted interventions.

This Special Issue seeks to highlight innovative computational techniques, including genome-wide analysis, pipelines for NGS-generated genome assembly, phylogenetic modeling, and machine learning approaches, to study viral evolution. We welcome original research, reviews, and short communications on topics such as:

Bioinformatics tools for viral genome analysis and surveillance;
Computational methods for studying viral evolution and mutation;
Integration of genomic data with clinical and epidemiological information;
Computational models for understanding viral–host interactions and pathogenicity;
Advances in computational epidemiology and viral surveillance networks.

We invite contributions that advance our understanding of viral genomics, providing insights that will assist in the global fight against infectious diseases. We look forward to your submissions.

Dr. Camila Malta Romano
Prof. Dr. Mariana Severo Ramundo
Dr. Nilson Coimbra
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Viruses is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

bioinformatics tools
genomic surveillance
viral evolution
computational genomics
host-pathogen interactions

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Published Papers (7 papers)

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Research

15 pages, 4361 KB

Open AccessArticle

Viral Metagenomic Analysis Reveals High Prevalence of Dromedary Camel Bocavirus and Porcine Astrovirus in Bactrian Camel Intestinal Tissue

by Yi Zhang, Xiaojun Ding, Xinyu Tao, Nuermaimaiti Tuohuti, Xinhao Wang, Ailixire Maimaiti, Zhanqiang Su and Xuelian Ma

Viruses 2026, 18(3), 302; https://doi.org/10.3390/v18030302 - 28 Feb 2026

Viewed by 116

Abstract

Bactrian camels (Camelus bactrianus) are economically vital livestock in arid regions; however, their intestinal virome is poorly understood. We employed viral metagenomics to analyze intestinal tissue samples from deceased camels at a breeding facility in Urumqi, Xinjiang, China, and uncovered a diverse viral population dominated by dromedary camel bocavirus (DBoV1) and porcine astrovirus (PoAstV5). A molecular epidemiological survey of 261 anal swab samples collected across Xinjiang revealed prevalence rates of 36.40% (95/261) for DBoV1 and 26.44% (69/261) for PoAstV5, indicating their widespread circulation. Phylogenetic analyses of the DBoV1 NS1 and PoAstV5 ORF1a genes showed close relationships with known strains, with no evidence of recombination. This study expands the known viral spectrum of Bactrian camels, marking the first report of PoAstV5 in this species, a finding suggestive of cross-species transmission. These results enhance our understanding of camel viral diversity and provide critical data for managing enteric diseases in camel populations, with potential implications for livestock health and surveillance of zoonotic risks. Full article

(This article belongs to the Special Issue Bioinformatics and Computational Approaches in Viral Genomics and Evolution 2025–2026)

14 pages, 900 KB

Open AccessArticle

Alignment-Free Machine Learning Serotype Classification of the Dengue Virus

by Vladimir Gajdov, Isidora Prosic, Mihaela Kavran, Filip Bosilkov, Tamas Petrovic, Jelena Konstantinov and Gospava Lazic

Viruses 2026, 18(3), 280; https://doi.org/10.3390/v18030280 - 25 Feb 2026

Viewed by 221

Abstract

Dengue virus (DENV) serotyping is essential for epidemiological surveillance, clinical risk assessment, and vaccine evaluation, as the four dengue serotypes differ in pathogenicity, immune interactions, and population dynamics. Existing subtyping methods largely rely on sequence alignment and phylogenetic inference, which can be computationally intensive and unreliable for short, fragmented, or error-prone sequences commonly generated in diagnostic and surveillance settings. There is a need for fast, alignment-free serotyping approaches that maintain high accuracy across heterogeneous sequence lengths while remaining scalable, transparent, and suitable for real-world diagnostic inputs. We demonstrate that compact 3-mer composition features are sufficient for highly accurate dengue virus serotyping when coupled with a lineage-aware Random Forest classification framework. Using 64 normalized 3-mer frequency features per sequence with ambiguity masking and enforcing strict cluster-aware validation at both 99% and 95% nucleotide identity thresholds, our approach achieved near-perfect accuracy and macro-F1 scores on held-out internal test sets. To further ensure independence, external validation datasets were filtered to remove exact sequence matches and any sequences sharing ≥99% or ≥95% nucleotide identity with internal data. On these strictly independent external datasets, the model maintained 100% accuracy and macro-F1 performance, confirming robust generalization beyond database redundancy. Robustness analyses showed stable performance under contiguous sequence truncation down to 300 bp and in the presence of ambiguous nucleotides, indicating resilience to realistic diagnostic inputs. These results demonstrate that a lightweight, alignment-free, machine learning approach can rival alignment-dependent methods while maintaining strict lineage-aware evaluation controls. The proposed framework combines high predictive accuracy, probabilistic reliability, computational efficiency, and reproducible validation design, making it well suited for large-scale genomic surveillance, rapid pre-screening, and diagnostic decision-support applications. Full article

(This article belongs to the Special Issue Bioinformatics and Computational Approaches in Viral Genomics and Evolution 2025–2026)

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9 pages, 1629 KB

Open AccessCommunication

First Record of Isolation and Molecular Characterization of Aguas Brancas virus, a New Insect-Specific Virus Found in Brazil

by Valéria Cardoso Freitas, Fábio Silva da Silva, Daniel Damous Dias, José Wilson Rosa Junior, Bruna Laís Sena do Nascimento, Maissa Maia Santos, José Leimar Camelo Silva, Ana Raquel Lira Vieira, Ana Cecília Ribeiro Cruz, Sandro Patroca da Silva, Livia Medeiros Neves Casseb, Joaquim Pinto Nunes Neto and Valéria Lima Carvalho

Viruses 2026, 18(2), 164; https://doi.org/10.3390/v18020164 - 27 Jan 2026

Viewed by 386

Abstract

Advances in diagnostic techniques, along with environmental changes driven by human activity, have intensified the surveillance and monitoring of virus and arbovirus circulation on the Amazon. These efforts have increased the detection of insect-specific viruses in field-collected hematophagous arthropods. This study reports the first isolation of the Aguas Brancas virus from mosquitoes collected in the Brazilian Amazon and in a rural area of Brasília, Federal District, Brazil. Arthropods of the family Culicidae, genus Limatus durhamii, were collected at ground level in forest fragments. Sample BEAR812610 originated from Ananindeua, Pará, within the Evandro Chagas Institute’s grounds, and sample BEAR839941 from a forest fragment in Brasília (Ceilândia—Núcleo Rural Boa Esperança, Site B4). Specimens were identified to the species/genus level, macerated, and the supernatant inoculated into C6/36 and Vero cell cultures for viral isolation. The presence of arboviruses was determined by indirect immunofluorescence using antibodies against major arbovirus groups. Positive samples were sequenced for nucleotide and amino acid identification, and phylogenetic analysis confirmed the virus as belonging to the genus Orthoflavivirus. This represents the first report of the isolation and characterization of the insect-specific Aguas Brancas virus. Full article

(This article belongs to the Special Issue Bioinformatics and Computational Approaches in Viral Genomics and Evolution 2025–2026)

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28 pages, 5780 KB

Open AccessArticle

Multiscale Modeling and Dynamic Mutational Profiling of Binding Energetics and Immune Escape for Class I Antibodies with SARS-CoV-2 Spike Protein: Dissecting Mechanisms of High Resistance to Viral Escape Against Emerging Variants

by Mohammed Alshahrani, Vedant Parikh, Brandon Foley and Gennady Verkhivker

Viruses 2025, 17(8), 1029; https://doi.org/10.3390/v17081029 - 23 Jul 2025

Cited by 3 | Viewed by 1682

Abstract

The rapid evolution of SARS-CoV-2 has underscored the need for a detailed understanding of antibody binding mechanisms to combat immune evasion by emerging variants. In this study, we investigated the interactions between Class I neutralizing antibodies—BD55-1205, BD-604, OMI-42, P5S-1H1, and P5S-2B10—and the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein using multiscale modeling, which combined molecular simulations with the ensemble-based mutational scanning of the binding interfaces and binding free energy computations. A central theme emerging from this work is that the unique binding strength and resilience to immune escape of the BD55-1205 antibody are determined by leveraging a broad epitope footprint and distributed hotspot architecture, additionally supported by backbone-mediated specific interactions, which are less sensitive to amino acid substitutions and together enable exceptional tolerance to mutational escape. In contrast, BD-604 and OMI-42 exhibit localized binding modes with strong dependence on side-chain interactions, rendering them particularly vulnerable to escape mutations at K417N, L455M, F456L and A475V. Similarly, P5S-1H1 and P5S-2B10 display intermediate behavior—effective in some contexts but increasingly susceptible to antigenic drift due to narrower epitope coverage and concentrated hotspots. Our computational predictions show strong agreement with experimental deep mutational scanning data, validating the accuracy of the models and reinforcing the value of binding hotspot mapping in predicting antibody vulnerability. This work highlights that neutralization breadth and durability are not solely dictated by epitope location, but also by how binding energy is distributed across the interface. The results provide atomistic insight into mechanisms driving resilience to immune escape for broadly neutralizing antibodies targeting the ACE2 binding interface—which stems from cumulative effects of structural diversity in binding contacts, redundancy in interaction patterns and reduced vulnerability to mutation-prone positions. Full article

(This article belongs to the Special Issue Bioinformatics and Computational Approaches in Viral Genomics and Evolution 2025–2026)

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19 pages, 3948 KB

Open AccessArticle

Equine Parvovirus-Hepatitis Population Dynamics in a Single Horse over 16 Years

by Alexandra J. Scupham

Viruses 2025, 17(7), 947; https://doi.org/10.3390/v17070947 - 4 Jul 2025

Viewed by 897

Abstract

Many viruses mutate rapidly to adapt to host defenses, and for some of these viruses, the result is long-term infection in individual hosts. The work described here examines the infection and long-term maintenance of a newly identified virus, equine parvovirus-hepatitis (EqPV-H), in an individual horse. This description is possible because of a hypervariable region in the capsid gene; sequence variants were tracked by high-throughput sequencing of serum samples taken over a 16-year period. The data support the hypothesis that EqPV-H infection resulted in a sequence variant bottleneck. The continuing infection evolved into a complex viral population showing a pattern of emergence, dominance, and recession with replacement. This is the first temporal description of the capsid gene evolution of EqPV-H in a single animal. Full article

(This article belongs to the Special Issue Bioinformatics and Computational Approaches in Viral Genomics and Evolution 2025–2026)

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27 pages, 10890 KB

Open AccessArticle

Integrating Sequence- and Structure-Based Similarity Metrics for the Demarcation of Multiple Viral Taxonomic Levels

by Igor C. dos Santos, Rebecca di Stephano de Souza, Igor Tolstoy, Liliane S. Oliveira and Arthur Gruber

Viruses 2025, 17(5), 642; https://doi.org/10.3390/v17050642 - 29 Apr 2025

Cited by 2 | Viewed by 1719

Abstract

Viruses exhibit significantly greater diversity than cellular organisms, posing a complex challenge to their taxonomic classification. While primary sequences may diverge considerably, protein functional domains can maintain conserved 3D structures throughout evolution. Consequently, structural homology of viral proteins can reveal deep taxonomic relationships, overcoming limitations inherent in sequence-based methods. In this work, we introduce MPACT (Multimetric Pairwise Comparison Tool), an integrated tool that utilizes both sequence- and structure-based metrics. The program incorporates five metrics: sequence identity, similarity, maximum likelihood distance, TM-score, and 3Di-character similarity. MPACT generates heatmaps and distance trees to visualize viral relationships across multiple levels, enabling users to substantiate viral taxa demarcation. Taxa delineation can be achieved by specifying appropriate score cutoffs for each metric, facilitating the definition of viral groups, and storing their corresponding sequence data. By analyzing diverse viral datasets spanning various levels of divergence, we demonstrate MPACT’s capability to reveal viral relationships, even among distantly related taxa. This tool provides a comprehensive approach to assist viral classification, exceeding the current methods by integrating multiple metrics and uncovering deeper evolutionary connections. Full article

(This article belongs to the Special Issue Bioinformatics and Computational Approaches in Viral Genomics and Evolution 2025–2026)

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11 pages, 1517 KB

Open AccessArticle

A Spatiotemporal Analysis of a High-Resolution Molecular Network Reveals Shifts of HIV-1 Transmission Hotspots in Guangzhou, China

by Huanchang Yan, Yifan Lu, Shunming Li, Hao Wu, Jingyang Hu, Yefei Luo, Qingmei Li, Lingxuan Lai, Weiping Huang, Jing Gu, Lijun Ma, Yuantao Hao, Zhigang Han, Xin-lin Chen and Yu Liu

Viruses 2025, 17(3), 384; https://doi.org/10.3390/v17030384 - 7 Mar 2025

Viewed by 1435

Abstract

Background: High-resolution and longitudinal HIV molecular surveillance can inform the evolving hotspots to tailor regionally focused control strategies. Methods: HIV-1 pol sequences of three predominant genotypes (CRF01_AE, CRF07_BC, and CRF55_01B) were collected for molecular network reconstruction from people living with HIV (PLWH) in Guangzhou (2018–2020). They were categorized by geographical residences into central, suburban, and outer suburban areas. Clustering rates, assortativity coefficients, and intensity matrices were employed to assess transmission dynamics, geographic mixing patterns, and intra- and inter-area transmission, respectively. Results: Of the 2469 PLWH, 55.5% resided in the central area. Clustering rates showed no significant differences across areas (44.5%, 40.6% vs. 45.7%; p = 0.184). However, the transmission hotspots for CRF01_AE and CRF55_01B shifted to the outer suburban area. PLWH tended to form links within their local area (assortativity coefficient = 0.227, p < 0.001), particularly for CRF01_AE (0.512, p < 0.001; intra-area intensity = 69.2%). The central area exhibited the highest but decreasing intra-area transmission (74.5% to 30.2%), while intra- and inter-area transmission involving the outer suburban area increased (23.1% to 38.2%). Conclusions: Despite most PLWH residing in the central area, the outer suburban area emerged as the hotspot, requiring interventions towards both intra- and inter-area transmission. Full article

(This article belongs to the Special Issue Bioinformatics and Computational Approaches in Viral Genomics and Evolution 2025–2026)

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