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Related Concept Videos

Ligand Binding Sites02:40

Ligand Binding Sites

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...
Ligand Binding Sites02:40

Ligand Binding Sites

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...
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...
The Equilibrium Binding Constant and Binding Strength02:18

The Equilibrium Binding Constant and Binding Strength

The equilibrium binding constant (Kb) quantifies the strength of a protein-ligand interaction. Kb can be calculated as follows when the reaction is at equilibrium:
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...
Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

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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 iterative knowledge-based scoring function to predict protein-ligand interactions: I. Derivation of interaction

Sheng-You Huang1, Xiaoqin Zou

  • 1Department of Biochemistry, Dalton Cardiovascular Research Center, University of Missouri, Columbia, Missouri 65211, USA.

Journal of Computational Chemistry
|September 20, 2006
PubMed
Summary

A new iterative method developed a knowledge-based scoring function (ITScore) for predicting protein-ligand interactions. This approach efficiently refines potentials, improving accuracy in binding mode discrimination and affinity prediction.

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Area of Science:

  • Computational chemistry
  • Structural biology
  • Drug discovery

Background:

  • Accurate prediction of protein-ligand interactions is crucial for drug discovery.
  • Knowledge-based scoring functions are widely used but face challenges like the reference state problem.

Purpose of the Study:

  • To develop a novel knowledge-based scoring function (ITScore) using an iterative method.
  • To address the reference state problem in deriving scoring functions.
  • To improve the prediction of protein-ligand binding affinity and modes.

Main Methods:

  • Developed a novel iterative method to derive pair potentials for ITScore.
  • Utilized 786 Protein Data Bank protein-ligand complexes for training.
  • Employed 26 atom types based on SYBYL software categories.
  • Validated the scoring function on 140 diverse protein-ligand complexes.

Main Results:

  • The iterative method efficiently converged within 20 steps, solving the reference state problem.
  • ITScore demonstrated high accuracy in discriminating binding modes from decoys.
  • Achieved a high correlation coefficient of 0.74 for affinity prediction.

Conclusions:

  • The developed ITScore is an efficient and accurate knowledge-based scoring function for protein-ligand interactions.
  • ITScore's use of SYBYL atom types ensures ease of use with common molecular modeling software.
  • This method offers a robust tool for computational drug design and virtual screening.