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Explainable deep learning and virtual evolution identifies antimicrobial peptides with activity against multidrug-resistant human pathogens.
Nat Microbiol
January 2025
School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China.
Artificial intelligence (AI) is a promising approach to identify new antimicrobial compounds in diverse microbial species. Here we developed an AI-based, explainable deep learning model, EvoGradient, that predicts the potency of antimicrobial peptides (AMPs) and virtually modifies peptide sequences to produce more potent AMPs, akin to in silico directed evolution. We applied this model to peptides encoded in low-abundance human oral bacteria, resulting in the virtual evolution of 32 peptides into potent AMPs.
View Article and Find Full Text PDFExploring the anticancer activities of Sulfur and magnesium oxide through integration of deep learning and fuzzy rough set analyses based on the features of Vidarabine alkaloid.
Sci Rep
January 2025
Faculty of Computer and AI, Cairo University, Giza, Egypt.
Drug discovery and development is a challenging and time-consuming process. Laboratory experiments conducted on Vidarabine showed IC 6.97 µg∕mL, 25.
View Article and Find Full Text PDFDental Implant Rehabilitation in Patients Carrying WNT10A Mutations With Different Molecular Statuses and Phenotypes: A Retrospective Cohort Study.
Clin Oral Implants Res
January 2025
Second Dental Center, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Objectives: WNT10A mutations are associated with tooth agenesis. This study aimed to assess the clinical outcomes of dental implants in patients carrying WNT10A mutations with different molecular statuses and phenotypes over a long-term follow-up period.
Materials And Methods: Patients with tooth agenesis were screened by whole-exome sequencing (WES) from January 2010 to September 2023.
FedKD-CPI: Combining the federated knowledge distillation technique to accomplish synergistic compound-protein interaction prediction.
Methods
January 2025
School of Computer Science and Engineering, Central South University, Changsha 410083, China; Hunan Provincial Key Lab on Bioinformatics, Central South University, Changsha 410083, China.
Compound-protein interaction (CPI) prediction is critical in the early stages of drug discovery, narrowing the search space for CPIs and reducing the cost and time required for traditional high-throughput screening. However, CPI-related data are usually distributed across different institutions and their sharing is restricted because of data privacy and intellectual property rights. Constructing a scheme that enhances multi-institutional collaboration to improve prediction accuracy while protecting data privacy is essential.
View Article and Find Full Text PDFImpedimetric multi-sensor system with gold and silver nanoparticles applied for basic taste assessment compared with human threshold method sensory analysis.
Food Chem
January 2025
Department of Food Engineering and Technology, School of Food Engineering, State University of Campinas, Campinas, SP, Brazil. Electronic address:
Threshold determination forms an integral part of sensory and consumer studies applied for product control and development. The authors examined the potential of an impedimetric electronic tongue to discriminate basic tastes and consider limitations pertaining to the sensory evaluation process. Three samples at lower, medium, and higher concentration levels of basic taste compounds were prepared and subjected to consumer studies (n = 60) using the difference from-control (DFC) test.
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