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Antimicrobial Peptides : A Roadmap for Accelerating Discovery and Development.

Antimicrobial Peptides: A Roadmap for Accelerating Discovery and Development covers the most important efforts of scientists and engineers worldwide to accelerate the process of discovery, production, and eventual market penetration of more potent antimicrobial peptides. These efforts have been fuel...

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Bibliographic Details
Main Author: Reyes, Luis H.
Corporate Author: ScienceDirect (Online service)
Other Authors: Cruz, Juan C., Wiedman, Gregory R.
Format: eBook
Language:English
Published: Chantilly : Elsevier, 2024.
Subjects:
Peptide antibiotics.
Antibiotiques peptidiques.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Front Cover
  • Antimicrobial Peptides: A Roadmap for Accelerating Discovery and Development
  • Copyright
  • Contents
  • Contributors
  • Introduction-Antimicrobial peptides: From the bench to the bedside
  • References
  • Section A: Computational approaches
  • Chapter 1: Bioinformatic methods for the design of antimicrobial peptides
  • 1. Introduction
  • 1.1. The significance of bioinformatics in accelerating the discovery and optimization of AMPs
  • 2. Foundations of AMP design
  • 2.1. Bioinformatics-driven peptide engineering
  • 2.2. Computational tools for AMP discovery
  • 2.3. Bioinformatic resources for AMP discovery
  • 2.3.1. Databases and repositories: A comprehensive guide to specialized AMP resources
  • APD3: The antimicrobial peptide database
  • CAMP: Collection of antimicrobial peptides
  • DRAMP: Data repository of antimicrobial peptides
  • Databases and repositories in AMP research
  • 2.3.2. Sequence and structure analysis tools for AMPs
  • Peptide structure prediction
  • 2.3.3. AMP prediction and classification tools
  • Motif discovery
  • Sequence alignment and comparative analysis
  • 2.4. Theoretical frameworks for AMP structure-activity relationship (SAR)
  • 2.4.1. Bioinformatic approaches to SAR
  • 2.4.2. Case studies illustrating successful applications of SAR analysis in AMP design
  • 2.4.3. Environments role in AMP analysis
  • 2.4.4. Rational design of AMP analogs
  • 2.4.5. Integrating SAR analysis into drug development pipelines
  • 3. Stability and toxicity prediction
  • 3.1. Stability of AMPs in biological contexts
  • 3.2. Toxicity toward mammalian cells
  • 3.3. Predictive models for stability and toxicity
  • 3.4. Computational methods for predicting peptide stability
  • 3.4.1. Resistance to proteolytic degradation
  • 3.4.2. Assessing chemical stability
  • 3.4.3. Preventing peptide aggregation
  • 3.4.4. Integrating stability predictions into AMP design
  • 3.5. Toxicity prediction models
  • 3.5.1. Quantitative structure-activity relationship (QSAR) models
  • 3.5.2. Machine learning approaches
  • 3.5.3. Integrating MD and toxicity predictions
  • 3.5.4. Database and web-based tools for toxicity prediction
  • 4. Formulation and delivery system design
  • 4.1. Challenges in AMP formulation: Addressing stability, bioavailability, and controlled release in therapeutic applications
  • 4.1.1. Stability challenges in AMP formulation
  • 4.1.2. Bioavailability issues
  • 4.1.3. Controlled release strategies
  • 4.2. Integration of computational approaches
  • 4.3. Bioinformatics in formulation design
  • 4.3.1. Predictive modeling for peptide-formulation interactions
  • 4.3.2. Optimizing peptide-encapsulation efficiency
  • 4.3.3. Enhancing peptide-delivery system interactions
  • 4.4. QSAR models in formulation optimization