AIMC Topic: Virulence Factors

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Coevolutionary signals in multiple sequence alignments improve virulence factor prediction with an MSA Transformer.

Scientific reports
Identification of virulence factors (VFs) is critical for expanding our knowledge on bacterial pathogenesis and also for developing targeted strategies for the prevention and treatment of related infectious diseases. Understanding virulence factors r...

Fungal virulence factors datasets for inflammatory bowel disease-specific antifungal drug discovery.

Scientific data
Fungi are closely associated with various diseases, among which Candida albicans (C. albicans) is recognized as an important pathogen in inflammatory bowel disease (IBD). Fungal pathogenicity is primarily mediated by virulence factors (VFs); therefor...

Advancing virulence factor prediction using protein language models.

BMC biology
BACKGROUND: Bacterial infections rank as the second leading cause of death globally, with virulence factors (VFs) being crucial to their pathogenicity. Predicting VFs accurately can uncover mechanisms of bacterial diseases and suggest new treatments....

Overcoming Immune Evasion in : Strategies for Rational Vaccine Design.

ACS infectious diseases
remains one of the most elusive targets in bacterial vaccinology, primarily due to its complex immune evasion strategies and the phenomenon of immune imprinting. Despite decades of research and numerous clinical trials, no vaccine has demonstrated p...

Pathogen virulence genes: Advances, challenges and future directions in infectious disease research (Review).

International journal of molecular medicine
Pathogens, including bacteria, viruses and fungi, employ virulence genes to invade their hosts, circumvent immunity and induce diseases. The present review examines the categorization and regulatory mechanisms of virulence genes and their co‑evolutio...

Multi-Omics Analysis of the virulence factors and designing of next-generation multi-epitopes Vaccines against Rickettsia prowazekii: a computer-aided vaccine designing approach.

Journal of computer-aided molecular design
Rickettsia is a genus of bacteria that are obligate intracellular parasites and are responsible for the febrile diseases known collectively as Rickettsioses. The emergence of antibiotic resistance is an escalating concern and thus developing a vaccin...

Contrastive-learning of language embedding and biological features for cross modality encoding and effector prediction.

Nature communications
Identifying and characterizing virulence proteins secreted by Gram-negative bacteria are fundamental for deciphering microbial pathogenicity as well as aiding the development of therapeutic strategies. Effector predictors utilizing pre-trained protei...

Protein interactions in human pathogens revealed through deep learning.

Nature microbiology
Identification of bacterial protein-protein interactions and predicting the structures of these complexes could aid in the understanding of pathogenicity mechanisms and developing treatments for infectious diseases. Here we developed RoseTTAFold2-Lit...

DTVF: A User-Friendly Tool for Virulence Factor Prediction Based on ProtT5 and Deep Transfer Learning Models.

Genes
Virulencefactors (VFs) are key molecules that enable pathogens to evade the immune systems of the host. These factors are crucial for revealing the pathogenic processes of microbes and drug discovery. Identification of virulence factors in microbes b...

Protein function annotation and virulence factor identification of Klebsiella pneumoniae genome by multiple machine learning models.

Microbial pathogenesis
Klebsiella pneumoniae is a type of Gram-negative bacterium which can cause a range of infections in human. In recent years, an increasing number of strains of K. pneumoniae resistant to multiple antibiotics have emerged, posing a significant threat t...