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Protein design and structure /

Protein Design and Structure, Volume 130 in the Advances in Protein Chemistry and Structural Biology series, highlights new advances in the field, with this new volume presenting interesting chapters.

Bibliographic Details
Corporate Author: ScienceDirect (Online service)
Other Authors: Donev, Rossen (Editor)
Format: eBook
Language:English
Published: Cambridge, MA : Academic Press is an imprint of Elsevier, 2022.
Series:Advances in protein chemistry and structural biology ; v. 130.
Subjects:
Proteins > Analysis.
Proteins > Structure.
Protéines > Analyse.
Protéines > Structure.
Proteins > Analysis
Proteins > Structure
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Intro
  • Advances in Protein Chemistry and Structural Biology: Protein Design and Structure
  • Copyright
  • Contents
  • Contributors
  • Chapter One: Algorithms for protein design
  • 1. Introduction
  • 2. Applications of protein design
  • 3. Design goals
  • 4. Target function design
  • 5. Algorithms for protein design
  • 5.1. Algorithms for discretized search space
  • 5.1.1. Enumeration
  • 5.1.1.1. Side chain conformations and rotamer enumeration
  • 5.1.1.2. Lattice models
  • 5.1.2. Graph algorithms
  • 5.1.2.1. Tree search
  • 5.1.2.1.1. The dead end elimination algorithm (DEE)
  • 5.1.2.1.2. The branch-and-bound algorithm
  • 5.1.2.1.3. The A* algorithm
  • 5.1.2.1.4. Dynamic programming
  • 5.2. Algorithms for optimization
  • 5.2.1. Linear programming
  • 5.2.2. Backrub
  • 5.2.3. Backpropagation
  • 5.2.4. Genetic algorithms
  • 5.2.5. Mean field optimization
  • 5.3. Parametric modeling and model fitting
  • 5.3.1. Parametric modeling
  • 5.3.2. Constraint satisfaction
  • 5.3.3. Threading or fold prediction
  • 5.4. Stochastic and ensemble based algorithms
  • 5.4.1. Stochastic algorithms
  • 5.4.1.1. Evolutionary algorithms
  • 5.4.2. Ensemble based methods
  • 5.4.2.1. Protein design using electrostatics
  • 5.4.3. Distance Geometry
  • 5.4.4. Quantum Annealing algorithm
  • 5.5. Neural networks
  • 5.5.1. Deep learning
  • 5.5.2. Graph convolutional neural network
  • 5.5.3. Variational AutoEncoders
  • 5.5.4. Generative adversarial networks (GANs)
  • 5.6. Hybrid algorithms
  • 5.6.1. Tertiary structural motifs
  • 5.7. Multilevel design
  • 5.8. Hierarchical design
  • 5.9. Protein design with iteration and feedback
  • 5.9.1. Iterative approach
  • 5.9.2. Design feedback
  • 6. Software
  • 7. Discussion
  • 8. Conclusion
  • Acknowledgments
  • References
  • Chapter Two: Computational prediction of protein functional sites-Applications in biotechnology and biomedicine.
  • 1. Introduction
  • 2. Sequence-based approaches
  • 2.1. Based on sequence similarity
  • 2.2. Conservation
  • 2.3. Correlated mutations
  • 2.4. Specificity-determining positions
  • 2.4.1. Approaches bases on subfamily partitioning
  • 2.4.2. Approaches based on mutational behavior
  • 2.4.3. Approaches based on multivariate analysis
  • 2.5. Disordered regions
  • 3. Structure-based approaches
  • 4. Machine learning
  • 5. Conclusions and future trends
  • Acknowledgments
  • References
  • Chapter Three: Structure and chemistry of enzymatic active sites that play a role in the switch and conformation mechanism
  • 1. Introduction
  • 2. Proteins as drug targets
  • 3. Protein conformations
  • 4. Enzymes in reaction mechanism
  • 5. Enzymes active site
  • 6. Metal and ion oriented active site
  • 7. Substrate binding models
  • 7.1. Lock and key model
  • 7.2. Induced fit model
  • 7.3. Conformational selection model
  • 8. Understanding allosteric site and active site
  • 9. Role of charges in active site
  • 10. Reported proteins with active site switches
  • 11. Open and closed conformation in active sites
  • 12. Conformational changes in active sites
  • 13. Role of water in active site
  • 14. Future prospectus
  • Acknowledgment
  • References
  • Chapter Four: Accelerating therapeutic protein design
  • 1. Introduction
  • 1.1. Proteins as sophisticated therapeutics
  • 1.2. Challenges in protein drug discovery and development
  • 1.2.1. Structural stability aspects
  • 1.2.2. Physicochemical aspects
  • 1.2.3. Clinical aspects
  • 2. Computational design of protein drugs
  • 2.1. Elements of protein design
  • 2.1.1. Sampling
  • 2.1.2. Scoring
  • 2.2. Advantages of computational design
  • 3. Advances in computational design of therapeutic proteins
  • 3.1. Inhibitor design
  • 3.2. Activator design
  • 3.3. Enzyme design
  • 3.4. Switch design.