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Related Concept Videos

Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

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 form...
Conservation of Protein Domains02:26

Conservation of Protein Domains

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 form...
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

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...
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

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...
Protein-protein Interfaces02:04

Protein-protein Interfaces

Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a polypeptide...

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Related Experiment Video

Updated: Jun 13, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

Deep Prior Framework: integrating functional specificity with general plausibility for targeted protein evolution.

Senxin Zhang1, Yining Qin2, Hanwen Zhu3,4

  • 1Department of Mathematics, Shanghai Normal University, No. 100 Guilin Road, Xuhui District, Shanghai 200234, China.

Briefings in Bioinformatics
|June 12, 2026
PubMed
Summary
This summary is machine-generated.

The Deep Prior Framework (DPF) enhances protein engineering by combining general sequence plausibility with specific functional goals. This computational method efficiently identifies high-fitness mutants for targeted protein evolution.

Keywords:
UniProtKBfunctional specificitymachine learningprotein evolutionprotein language models

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Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
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An Integrated Approach for Microprotein Identification and Sequence Analysis
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An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

Area of Science:

  • Computational Biology
  • Protein Engineering
  • Bioinformatics

Background:

  • Directed protein evolution relies on computational methods to identify high-fitness mutants.
  • Current methods using Protein Language Models (PLMs) lack specificity due to reliance on general sequence plausibility.
  • Limited experimental feedback hinders the ability of traditional methods to guide evolution toward specific functions.

Purpose of the Study:

  • To introduce the Deep Prior Framework (DPF), a novel computational paradigm for protein engineering.
  • To integrate universal structural plausibility with task-oriented specificity priors for improved mutant screening.
  • To advance efficient and targeted protein engineering by incorporating specificity-aware functional priors.

Main Methods:

  • Developed the Deep Prior Framework (DPF) integrating structural plausibility and specificity priors.
  • Incorporated a Bernoulli-Attention (BATT) module within a Mixture of Experts architecture.
  • Benchmarked DPF on nine deep mutational scanning datasets and applied it to in silico directed evolution of Blastobotrys adeninivorans xanthine dehydrogenase (BaXD).

Main Results:

  • DPF outperformed existing PLM-based methods in computational screening of high-fitness mutants.
  • Achieved significant activity enhancement (average >4-fold, best >9-fold) in engineered BaXD mutants.
  • Successfully annotated millions of unreviewed proteins in UniProtKB with high-confidence functional labels.

Conclusions:

  • DPF significantly advances efficient and targeted protein engineering by incorporating specificity-aware functional priors.
  • The framework demonstrates superior performance in identifying beneficial protein mutations.
  • DPF has broad applicability in protein engineering and large-scale functional annotation.