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Protein Organization01:24

Protein Organization

6.3K
Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence....
6.3K
Ligand Binding Sites02:40

Ligand Binding Sites

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Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
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Protein-protein Interfaces02:04

Protein-protein Interfaces

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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...
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Conserved Binding Sites01:49

Conserved Binding Sites

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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...
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Related Experiment Video

Updated: Jun 12, 2025

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

68.6K

Protein language models are performant in structure-free virtual screening.

Hilbert Yuen In Lam1,2, Jia Sheng Guan1, Xing Er Ong2

  • 1School of Biological Sciences, Nanyang Technological University, 60 Nanyang Dr, Singapore 637551, Singapore, Republic of Singapore.

Briefings in Bioinformatics
|September 27, 2024
PubMed
Summary

This study introduces a faster virtual screening (VS) method using protein language models and molecular graphs. This approach achieves drug design capabilities without needing 3D protein structures, significantly reducing computational costs.

Keywords:
cheminformaticscomputer-aided drug designprotein language modelsvirtual screening

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Area of Science:

  • Computational chemistry
  • Drug discovery
  • Bioinformatics

Background:

  • Virtual screening (VS) traditionally relies on structure-based drug design (SBDD).
  • SBDD methods like molecular docking are computationally intensive and time-consuming.
  • High-resolution 3D protein structures are essential for traditional VS.

Purpose of the Study:

  • To develop a novel, computationally efficient VS method.
  • To enable computer-aided drug design (CADD) without 3D protein structures.
  • To achieve VS performance comparable to SBDD methods.

Main Methods:

  • Utilized protein language models as input.
  • Employed molecular graphs as input.
  • Developed a novel graph-to-transformer cross-attention mechanism.

Main Results:

  • Achieved screening power comparable to state-of-the-art structure-based models.
  • Demonstrated significantly reduced computational requirements for VS.
  • Enabled VS in the absence of 3D protein structures.

Conclusions:

  • The novel method offers a highly expedited VS approach.
  • This technique reduces the computational burden of drug design.
  • It facilitates early-stage CADD without requiring 3D protein structures.