In-solution affinity selection (AS) of large synthetic peptide libraries affords identification of binders to protein targets through access to an expanded chemical space. Standard affinity selection methods, however, can be time-consuming, low-throughput, or provide hits that display low selectivity to the target. Here we report an automated bio-layer interferometry (BLI)-assisted affinity selection platform. When coupled with tandem mass spectrometry (MS), this method enables both rapid discovery and affinity maturation of known peptide binders with high selectivity. The BLI-assisted AS-MS technology also features real-time monitoring of the peptide binding during the library selection process, a feature unattainable by current selection approaches. We show the utility of the BLI AS-MS platform toward rapid identification of novel nanomolar (dissociation constant, < 50 nM) non-canonical binders to the leukemia-associated oncogenic protein menin. To our knowledge, this is the first application of BLI to the affinity selection of synthetic peptide libraries. We believe our approach can significantly accelerate the use of synthetic peptidomimetic libraries in drug discovery.
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http://dx.doi.org/10.1039/d1sc02587b | DOI Listing |
Front Chem
December 2024
African Society for Bioinformatics and Computational Biology, Cape Town, South Africa.
Introduction: Dengue Fever continues to pose a global threat due to the widespread distribution of its vector mosquitoes, and . While the WHO-approved vaccine, Dengvaxia, and antiviral treatments like Balapiravir and Celgosivir are available, challenges such as drug resistance, reduced efficacy, and high treatment costs persist. This study aims to identify novel potential inhibitors of the Dengue virus (DENV) using an integrative drug discovery approach encompassing machine learning and molecular docking techniques.
View Article and Find Full Text PDFJ Assist Reprod Genet
January 2025
Department of Obstetrics and Gynecology, Division of Reproductive Endocrinology and Infertility, Northwestern University, 259 E Erie St Suite 2400, Chicago, IL, 60611, USA.
Purpose: To characterize the opinions of patients undergoing infertility treatment on the use of artificial intelligence (AI) in their care.
Methods: Patients planning or undergoing in vitro fertilization (IVF) or frozen embryo transfers were invited to complete an anonymous electronic survey from April to June 2024. The survey collected demographics, technological affinity, general perception of AI, and its applications to fertility care.
Br J Pharmacol
January 2025
Department of Biothermodynamics and Drug Design, Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania.
Background And Purpose: Tumour hypoxia frequently presents a major challenge in the treatment of neuroblastoma (NBL). The neuroblastoma cells produce carbonic anhydrase IX (CA IX), an enzyme crucial for the survival of cancer cells in low-oxygen environments.
Experimental Approach: We designed and synthesised a novel high-affinity inhibitor of CA IX.
Methods Mol Biol
January 2025
Department of Biotechnology, College of Natural and Applied Science, Addis Ababa Science and Technology University, Addis Ababa, Ethiopia.
While traditional assay methods face challenges in detecting specific proteins, aptamers, known for their high specificity and affinity, are emerging as a valuable biomarker detection tool. Aurora kinase A (AURKA) plays a role in cell division and influences stem cell reprogramming. In this study, an in silico approach method was conducted for a random ssDNA aptamer sequence selection and its binding with AURKA.
View Article and Find Full Text PDFParasitol Res
January 2025
Department of Biology, Faculty of Science, Marmara University, Goztepe, 34722, Istanbul, Türkiye.
Babesia bigemina is an apicomplexan parasite responsible for causing "Texas fever" in bovines. Current treatments for bovine babesiosis are hindered by several limitations, including toxicity, insufficient efficacy in eliminating the parasite, and the potential for resistance development. A promising approach to overcome these challenges is the identification of compounds that specifically target essential metabolic pathways unique to the parasite.
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