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 Experiment Videos

Sophia Alvarez1, Charisse M Nartey1, Nicholas Mercado1

  • 1Department of Biological Sciences, University of Texas at Dallas, Richardson, TX 75080, USA.

Biorxiv : the Preprint Server for Biology
|June 9, 2023
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Decoding cryptic defluorinases through a latent generative sequence landscape.

Chemical science·2026
Same author

Identification and engineering of highly functional potyviral proteases in cells using co-evolutionary models.

Nature communications·2026
Same author

A Structure-Aware Generative AI Framework for Revealing Functional Relationships in Proteins Families.

bioRxiv : the preprint server for biology·2025
Same author

Cryo-EM structures of plant Augmin reveal coiled-coil assembly, antiparallel dimerization, and NEDD1 binding.

Nature communications·2025
Same author

Generative Landscapes and Dynamics to Design Functional Multidomain Artificial Transmembrane Transporters.

ACS central science·2025
Same author

Higher-order epistasis drives evolutionary unpredictability toward novel antibiotic resistance.

bioRxiv : the preprint server for biology·2025
Same journal

A human-specific genetic modifier reconfigures large-scale cortical network dynamics underlying behavioral performance.

bioRxiv : the preprint server for biology·2026
Same journal

<i>Staphylococcus aureus</i> uses a eukaryotic-like uridyltransferase to make UDP-GlcNAc for cell wall synthesis.

bioRxiv : the preprint server for biology·2026
Same journal

Dynamic redistribution of eIF4F controls cap-dependent translation initiation.

bioRxiv : the preprint server for biology·2026
Same journal

When does additional information improve accuracy of RNA secondary structure prediction?

bioRxiv : the preprint server for biology·2026
Same journal

Normative brain-state trajectories reveal deviation from healthy aging in Alzheimer's disease.

bioRxiv : the preprint server for biology·2026
Same journal

Noradrenergic infraslow rhythm during sleep is the critical link between heart-rate dynamics and memory consolidation.

bioRxiv : the preprint server for biology·2026
See all related articles

Computational models can now evolve functional protein variants with improved activity. This new algorithm, Sequence Evolution with Epistatic Contributions (SEEC), uses natural protein family data to guide evolution for biomedical and industrial applications.

Area of Science:

  • Evolutionary biology
  • Protein engineering
  • Computational biology

Background:

  • Computational models of evolution are crucial for understanding sequence variation, phylogenetic relationships, and evolutionary pathways.
  • Validating the in vivo functionality of computationally evolved sequences enhances their utility as accurate evolutionary algorithms.
  • Epistasis, the interaction between mutations, plays a significant role in evolutionary dynamics but is often challenging to model accurately.

Approach:

  • Developed a novel algorithm, Sequence Evolution with Epistatic Contributions (SEEC), that leverages epistasis inferred from natural protein families.
  • Utilized the Hamiltonian of the joint probability of sequences within a family as a fitness metric.
  • Experimentally tested evolved beta-lactamase variants in E. coli TEM-1 for in vivo activity.

Related Experiment Videos

Key Points:

  • SEEC successfully evolved protein variants with dozens of mutations while preserving essential catalytic and interaction sites.
  • Evolved variants demonstrated retained family-like functionality and enhanced activity compared to the wild-type (WT) protein.
  • Different epistasis inference methods simulated varying selection strengths, with weaker selection aligning with neutral evolution predictions.

Conclusions:

  • SEEC offers a powerful framework for generating functional protein variants with potential applications in neofunctionalization, viral fitness landscape characterization, and vaccine development.
  • The algorithm's ability to incorporate epistatic constraints provides a more accurate and interpretable approach to evolutionary modeling.
  • Experimental validation of computationally evolved sequences is critical for advancing their practical utility.