Biofilm forming microorganisms substantially enhance their virulence and drug resistance causing and alternatives are need to combat this health problem. In this context, peptides are an exceptional strategy in drug design and pharmaceutical innovation due to their diverse chemical features, biological activity and biotechnological relevance. Therefore, this study proposes a comprehensive assessment of a wide range of peptides, targeting biofilms. It provides chemical and molecular information and a Structural Activity Relationship perspective in order to delineate minimal requirements for antibiofilm activity and contributing to the development of new antibiofilm agents. In light of this, it was possible to propose a peptide design model (X-X-X-X-X-X-X-X-X-X-X-X-X-X-X-X-X-X-X-X) to be tested in the war against resistant microorganisms.
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http://dx.doi.org/10.1016/j.ejps.2017.11.008 | DOI Listing |
Brief Bioinform
November 2024
School of Computer Science, Northwestern Polytechnical University, Xi'an, 710129 Shaanxi, China.
The identification of neoantigens is crucial for advancing vaccines, diagnostics, and immunotherapies. Despite this importance, a fundamental question remains: how to model the presentation of neoantigens by major histocompatibility complex class I molecules and the recognition of the peptide-MHC-I (pMHC-I) complex by T cell receptors (TCRs). Accurate prediction of pMHC-I binding and TCR recognition remains a significant computational challenge in immunology due to intricate binding motifs and the long-tail distribution of known binding pairs in public databases.
View Article and Find Full Text PDFBrief Bioinform
November 2024
Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong, Hong Kong, 999077, China.
The complexity of T cell receptor (TCR) sequences, particularly within the complementarity-determining region 3 (CDR3), requires efficient embedding methods for applying machine learning to immunology. While various TCR CDR3 embedding strategies have been proposed, the absence of their systematic evaluations created perplexity in the community. Here, we extracted CDR3 embedding models from 19 existing methods and benchmarked these models with four curated datasets by accessing their impact on the performance of TCR downstream tasks, including TCR-epitope binding affinity prediction, epitope-specific TCR identification, TCR clustering, and visualization analysis.
View Article and Find Full Text PDFJ Med Chem
January 2025
Medicinal Chemistry and Bioinformatics Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
Retrosynthesis is a strategy to analyze the synthetic routes for target molecules in medicinal chemistry. However, traditional retrosynthesis predictions performed by chemists and rule-based expert systems struggle to adapt to the vast chemical space of real-world scenarios. Artificial intelligence (AI) has revolutionized retrosynthesis prediction in recent decades, significantly increasing the accuracy and diversity of predictions for target compounds.
View Article and Find Full Text PDFProbiotics Antimicrob Proteins
January 2025
Department of Food Science and Technology, Faculty of Nutrition & Food Sciences, Nutrition, Tabriz, Iran.
Infertility poses a global challenge that impacts a significant proportion of the populace. Presently, there is a substantial emphasis on investigating the potential of probiotics and their derivatives, called postbiotics, as an alternative therapeutic strategy for addressing infertility. The term of "postbiotics" refers to compounds including peptides, enzymes, teichoic acids, and muropeptides derived from peptidoglycans, polysaccharides, proteins, and organic acids that are excreted by living bacteria or released after bacterial lysis.
View Article and Find Full Text PDFBreast Cancer (Dove Med Press)
January 2025
Clinic for Plastic, Aesthetic and Reconstructive Surgery, Spine, Orthopedic and Hand Surgery, Preventive Medicine - ETHIANUM, Heidelberg, 69115, Germany.
Background: Adipokines, bioactive peptides secreted by adipose tissue, appear to contribute to breast cancer development and progression. While numerous studies suggest their role in promoting tumor growth, the exact mechanisms of their involvement are not yet completely understood.
Methods: In this project, varying concentrations of recombinant human adipokines (Leptin, Lipocalin-2, PAI-1, and Resistin) were used to study their effects on four selected breast cancer cell lines (EVSA-T, MCF-7, MDA-MB-231, and SK-Br-3).
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