Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

7.6K
The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
7.6K
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

3.2K
3.2K
Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

13.4K
Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to...
13.4K
Protein and Protein Structure02:15

Protein and Protein Structure

83.8K
Proteins are one of the most abundant organic molecules in living systems and have the most diverse range of functions of all macromolecules. Proteins may be structural, regulatory, contractile, or protective. They may serve in transport, storage, or membranes; or they may be toxins or enzymes. Their structures, like their functions, vary greatly. They are all, however, amino acid polymers arranged in a linear sequence.
A protein's shape is critical to its function. For example, an enzyme...
83.8K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

6.5K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
6.5K
Protein and Protein Structures02:15

Protein and Protein Structures

14.7K
14.7K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

How to think about designing smart antibodies in the age of genAI: integrating biology, technology, and experience.

mAbs·2025
Same author

Recent advances in generative biology for biotherapeutic discovery.

Trends in pharmacological sciences·2024
Same author

Development of in silico models to predict viscosity and mouse clearance using a comprehensive analytical data set collected on 83 scaffold-consistent monoclonal antibodies.

mAbs·2023
Same author

Identifying promising sequences for protein engineering using a deep transformer protein language model.

Proteins·2023
Same author

Building the foundation for a community-generated national research blueprint for inherited bleeding disorders: facilitating research through infrastructure, workforce, resources and funding.

Expert review of hematology·2023
Same author

Unifying cardiovascular modelling with deep reinforcement learning for uncertainty aware control of sepsis treatment.

PLOS digital health·2023
Same journal

Haplotype-aware long-read error correction.

Algorithms for molecular biology : AMB·2026
Same journal

Extension of partial atom-to-atom maps: uniqueness and algorithms.

Algorithms for molecular biology : AMB·2026
Same journal

Lossless pangenome indexing using tag arrays.

Algorithms for molecular biology : AMB·2026
Same journal

Dolphyin: a combinatorial algorithm for identifying 1-Dollo phylogenies in cancer.

Algorithms for molecular biology : AMB·2026
Same journal

Probing transcription factor subsets in gene regulatory networks.

Algorithms for molecular biology : AMB·2026
Same journal

Comparing the ability of embedding methods on metabolic hypergraphs for capturing taxonomy-based features.

Algorithms for molecular biology : AMB·2026
See all related articles

Related Experiment Video

Updated: Oct 30, 2025

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

17.2K

Bayesian optimization with evolutionary and structure-based regularization for directed protein evolution.

Trevor S Frisby1, Christopher James Langmead2

  • 1Computational Biology Department, School of Computer Science, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA, 15213, USA.

Algorithms for Molecular Biology : AMB
|July 2, 2021
PubMed
Summary
This summary is machine-generated.

Directed evolution (DE) uses Bayesian optimization with regularization to improve protein engineering. Structure-based constraints enhance protein designs by focusing the search and improving experimental efficiency.

Keywords:
Active learningBayesian optimizationDirected evolutionGaussian process regressionProtein designProtein language modelRational designRegularization

More Related Videos

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

7.4K
Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
08:49

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

684

Related Experiment Videos

Last Updated: Oct 30, 2025

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

17.2K
Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

7.4K
Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
08:49

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

684

Area of Science:

  • Protein Engineering
  • Computational Biology
  • Machine Learning

Background:

  • Directed evolution (DE) is a protein engineering technique for optimizing protein properties through mutagenesis and screening.
  • Standard DE may compromise unmeasured properties like solubility or stability.
  • This study addresses DE's under-determined optimization by incorporating regularization.

Purpose of the Study:

  • To formulate directed evolution as a regularized Bayesian optimization problem.
  • To investigate the impact of evolutionary and structure-based constraints on DE.
  • To improve the efficiency and outcome of protein engineering.

Main Methods:

  • Formulated directed evolution as a regularized Bayesian optimization problem.
  • Incorporated evolutionary and structure-based constraints as regularization terms.
  • Applied the method to GB1, BRCA1, and SARS-CoV-2 Spike proteins.

Main Results:

  • Structure-based regularization consistently improved protein designs compared to unregularized DE.
  • Evolutionary-based regularization showed limited effectiveness.
  • Regularization focused the search space, optimizing experimental budget usage.
  • The approach significantly reduced the experimental burden of DE.

Conclusions:

  • Regularization in Bayesian ML-assisted DE alters search patterns, favoring variants with multiple desirable properties.
  • Structure-based regularization enhances variant selection without negative consequences.
  • This framework offers a more effective approach to protein engineering.