PepSAVI-MS for discovery of novel botanical antimicrobial peptides

PepSAVI-MS 用于发现新型植物抗菌肽

基本信息

批准号：
10376454
负责人：
Leslie M. Hicks
金额：
$ 19.48万
依托单位：
UNIV OF NORTH CAROLINA CHAPEL HILL
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-05-01 至 2023-02-28
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10376454
关键词：
Academia Address Age Aging Algorithms Amaranthus Anti-Bacterial Agents Anti-Infective Agents Antibiotic Resistance Antibiotics Antifungal Agents Antimicrobial Resistance Antimicrobial susceptibility Anus Bacteria Bacterial Proteins Biological Biological Assay Botanicals Bovine Serum Albumin Breathing Calibration Capsicum Cells Characteristics Chelating Activity Chemistry Chromatography Clinical Colorectal Cancer Contracts Core Facility Coupled Cysteine Data Databases Defensins Dissociation ESKAPE pathogens Ensure Enterococcus faecalis Enzymes Equilibrium Escherichia coli Evolution Exclusion Family Fingerprint Frequencies Funding Genomics Hour Hybrids Industry Informatics Ions Iron Chelating Agents Klebsiella pneumoniae Laboratories Lead Libraries Lipid A Lytic Maintenance Manufacturer Name Manuscripts Mass Spectrum Analysis Membrane Methods Microbiology Microfluidics Mining Modernization Modification Molecular Monitor Mutagens Natural Products Paper Parsley - dietary Penetration Peptide Antibiotics Peptide Library Peptides Performance Pharmaceutical Preparations Plants Polymyxin B Positioning Attribute Post-Translational Protein Processing Preparation Procedures Process Productivity Proline Property Proteins Proteolytic Processing Proteome Proteomics Publications Quality Control Reporting Reproducibility Research Resistance Resolution Rest Ribosomes Running Sampling Schedule Seasons Source Statistical Models Structure System Testing Therapeutic Time Training Ustilago VDAC1 gene Viola analog anti-cancer antimicrobial antimicrobial peptide base bioactive natural products career computerized data processing data acquisition disulfide bond drug discovery equipment acquisition experience genome sequencing graduate student in silico infectious disease treatment innovation insight instrument instrumentation interest ion source mass analyzer member microbial novel novel therapeutics operation repaired resistance mechanism response scaffold screening skills small molecule transcriptomics

项目摘要

ABSTRACT The continued evolution of antimicrobial resistance emphasizes the dire need for discovery of antibiotic therapeutics with novel mechanisms of action. Technological advances in genome sequencing, drug library creation, and structural informatics have not advanced infectious disease treatments sufficiently. While natural products have long served as inspiration for novel therapeutic scaffolds, we posit peptide-derived entities offer great potential to address current needs due to their unique mechanisms of action, penetration and selectively. Herein, we describe our PepSAVI-MS pipeline to discover and characterize peptides with antimicrobial activity through implementation of a hybrid bioassay-guided/peptidomics platform. We directly identify botanical peptides contributing to bioactivity profiles using robust microbial bioassays optimized for peptide screening and using a mass spectrometry-based peptidomics approach coupled to statistical modeling and informatics to identify and further characterize these peptides at the molecular level. These potential lead compounds are then tested against an extensive panel of clinical ESKAPE pathogens, as well as for favorable drug characteristics and determination of mechanism-of- action. Our platform enables robust mining of plants and other natural sources for peptidyl species with unique or broad-spectrum anti-infective properties and has the potential to lead to the discovery of novel chemistries at the forefront of modern drug discovery.

抽象的抗菌抗性的持续演变强调了发现的迫切需求具有新型作用机理的抗生素治疗学。基因组的技术进步测序，药物图书馆的创建和结构信息学没有晚期传染病足够的治疗。虽然天然产品长期以来一直是小说的灵感治疗性脚手架，我们认为由肽衍生的实体提供了巨大的潜力来解决当前由于其独特的作用机制，穿透性和有选择性的需求。在此，我们描述我们的百事可乐MS管道以通过实施混合生物测定指导/肽组学平台。我们直接识别植物使用对肽优化的鲁棒微生物生物测定促进生物活性特征的肽筛选和使用基于质谱的肽组学方法与统计建模和信息学以识别和进一步在分子水平上表征这些肽。然后，针对大量临床Eskape测试这些潜在的铅化合物病原体以及有利的药物特征和确定机理行动。我们的平台可为肽基的植物和其他天然来源提供强大的采矿具有独特或广谱的抗感染特性，有可能导致在现代药物发现的最前沿发现新颖的化学物质。