Computational Modeling and Design of Antimicrobial Peptides

抗菌肽的计算模型和设计

基本信息

批准号：
7667298
负责人：
YIANNIS KAZNESSIS
金额：
$ 21.78万
依托单位：
UNIVERSITY OF MINNESOTA
依托单位国家：
美国
项目类别：
财政年份：
2005
资助国家：
美国
起止时间：
2005-08-01 至 2012-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7667298
关键词：
Algorithms Antibiotics Antiviral Agents Area Binding Bioinformatics Biological Biological Models Blood - brain barrier anatomy Categories Cell Wall Cell membrane Chemical Engineering Classification Classification Scheme Collaborations Complex Computational Science Computer Simulation Computing Methodologies Development Doctor of Philosophy Drug resistance Electrostatics Elements Engineering Environment Equilibrium Exhibits Experimental Designs Family Feedback Foundations Hemolysis Hydrocarbons Hydrogen Bonding Hydrophobic Interactions Hydrophobicity Immune response In Vitro Institutes Knowledge Laboratories Lead Light Lipid Bilayers Mammalian Cell Measurement Mechanics Mediating Membrane Methods Micelles Minnesota Modeling Molecular Molecular Conformation Paper Pattern Pattern Recognition Peptide Synthesis Peptides Pharmacologic Substance Phospholipids Physics Postdoctoral Fellow Process Productivity Protocols documentation Public Health Publications Pulmonary Surfactant-Associated Proteins Qualifying Research Research Personnel Resistance Resolution Resources Scheme Science Scientist Solid Specificity Speed Structure Supercomputing System Technology Testing Therapeutic Toxic effect Training Trypsin Inhibitors Validation Viral Work antimicrobial antimicrobial peptide base biomedical scientist cathelicidin cell envelope cheminformatics computer science computerized tools data mining design digital experience graduate student improved in vivo knowledge base membrane model model design molecular dynamics molecular mechanics novel pathogen programs protein aminoacid sequence research study simulation skills sound success tool

项目摘要

DESCRIPTION (provided by applicant): We propose the development of computational tools that promote the progress of antimicrobial peptide engineering. Drug-resistant pathogens are becoming a significant public health concern. The prolific use of antibiotics in the last few decades inevitably increased the bacterial species with resistance. Antimicrobial peptides (AMPs), recognized as potent components of eukaryotic innate immune response mechanisms, appear to be promising therapeutic anti-pathogen agents. A wide array of experiments suggests a complex interplay between the bacterial cell envelope components and the peptides. However, how exactly AMPs modulate membrane structure remains largely unclear. We leverage the high resolution, atomic level picture of molecular dynamics simulations, to understand the interactions of AMPs with bacterial and mammalian membranes. We also develop data mining algorithms that identify recurring sequence and structural patterns in known, naturally occurring AMPs. Importantly, active collaborations with leading research groups in the areas of antimicrobial peptides and peptide/membrane interactions provide the necessary feedback mechanism for validation and refinement of computational results. The three specific aims of this project are: 1. Quantify the interactions between AMPs and mammalian, bacterial and viral model membranes using high productivity computer simulations. 2. Recognize the sequence/structural elements that are responsible for cathelicidin and minidefensin antimicrobial activity 3. Establish a process of feedback mechanisms between experiments, computer models and new experimental design in order to promote rational peptide engineering. Experimentally investigate novel peptides based on model-driven design rules.

描述（由申请人提供）：我们建议开发促进抗菌肽工程进展的计算工具。耐药的病原体已成为一个重大的公共卫生问题。在过去的几十年中，多产抗生素的多产量不可避免地增加了具有抗性的细菌物种。抗菌肽（AMP）被认为是真核先天免疫反应机制的有效成分，似乎是有希望的治疗性抗疾病剂。各种各样的实验表明细菌细胞包膜成分与肽之间存在复杂的相互作用。但是，如何确切地调节膜结构在很大程度上不清楚。我们利用分子动力学模拟的高分辨率，原子水平的图片来了解AMP与细菌和哺乳动物膜的相互作用。我们还开发了数据挖掘算法，这些算法可以识别已知的，自然发生的AMP中的经常出现的序列和结构模式。重要的是，与领先的研究小组在抗菌肽和肽/膜相互作用领域的积极合作为验证和完善计算结果提供了必要的反馈机制。该项目的三个具体目标是： 1。使用高生产力计算机模拟，量化AMP与哺乳动物，细菌和病毒模型膜之间的相互作用。 2。识别负责cathelicidin和Minidefensin抗菌活性的序列/结构元素 3。在实验，计算机模型和新的实验设计之间建立反馈机制的过程，以促进合理的肽工程。基于模型驱动的设计规则，实验研究了新型肽。

项目成果

期刊论文数量（23）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

proTeOn and proTeOff, new protein devices that inducibly activate bacterial gene expression.

proTeOn 和 proTeOff 是诱导激活细菌基因表达的新型蛋白质装置。

DOI：
10.1021/cb200168y
发表时间：
2011
期刊：
ACS chemical biology
影响因子：
4
作者：
Volzing,Katherine;Biliouris,Konstantinos;Kaznessis,YiannisN
通讯作者：
Kaznessis,YiannisN

Computational studies of protegrin antimicrobial peptides: a review.

DOI：
10.1016/j.peptides.2010.10.006
发表时间：
2011-01
期刊：
Peptides
影响因子：
3
作者：
Bolintineanu DS;Kaznessis YN
通讯作者：
Kaznessis YN

Free energy profile of the interaction between a monomer or a dimer of protegrin-1 in a specific binding orientation and a model lipid bilayer.

特定结合方向的 protegrin-1 单体或二聚体与模型脂质双层之间相互作用的自由能曲线。

DOI：
10.1021/jp909640g
发表时间：
2010
期刊：
The journal of physical chemistry. B
影响因子：
0
作者：
Vivcharuk,Victor;Kaznessis,Yiannis
通讯作者：
Kaznessis,Yiannis

Investigation of Changes in Tetracycline Repressor Binding upon Mutations in the Tetracycline Operator.

四环素操纵子突变后四环素阻遏物结合变化的研究。

DOI：
10.1021/je500225x
发表时间：
2014
期刊：
Journal of chemical and engineering data
影响因子：
0
作者：
Bolintineanu,DanS;Volzing,Katherine;Vivcharuk,Victor;Sayyed-Ahmad,Abdallah;Srivastava,Poonam;Kaznessis,YiannisN
通讯作者：
Kaznessis,YiannisN

Poisson-Nernst-Planck models of nonequilibrium ion electrodiffusion through a protegrin transmembrane pore.