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Related Concept Videos

Molecular Models02:00

Molecular Models

Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
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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.
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Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence the...
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

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Induced-fit Model01:13

Induced-fit Model

Most chemical reactions in cells require enzymes—biological catalysts that speed up the reaction without being consumed or permanently changed. They reduce the activation energy needed to convert the reactants into products. Enzymes are proteins, that usually work by binding to a substrate—a reactant molecule that they act upon.
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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.
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Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
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Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

Homology models in docking and high-throughput docking.

Claudio N Cavasotto1

  • 1School of Biomedical Informatics, The University of Texas Health Science Center at Houston, 7000 Fannin, Suite 690, Houston, TX 77030, USA. Claudio.N.Cavasotto@uth.tmc.edu

Current Topics in Medicinal Chemistry
|April 23, 2011
PubMed
Summary
This summary is machine-generated.

Homology modeling offers an affordable alternative for drug discovery when experimental structures are unavailable. This review covers the latest developments and successes in using these structural models for virtual screening and drug design.

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

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Area of Science:

  • Computational chemistry
  • Structural biology
  • Drug discovery

Background:

  • Homology modeling is an established technique in drug discovery, providing a cost-effective alternative to experimental structures.
  • Recent studies validate the use of structural models in molecular docking and virtual screening.
  • Advancements in model refinement are anticipated for improved accuracy.

Purpose of the Study:

  • To review recent developments in homology modeling for structure-based virtual screening.
  • To highlight successful applications of homology modeling in drug discovery projects.
  • To discuss the current state and future prospects of homology modeling in computational drug design.

Main Methods:

  • Review of recent literature on homology modeling techniques.
  • Analysis of benchmarking studies for homology models in docking.
  • Case study analysis of successful drug discovery endeavors utilizing homology models.

Main Results:

  • Homology models are increasingly feasible and effective for docking-based drug discovery.
  • Successful implementation of homology modeling has been demonstrated in real-world drug discovery projects.
  • Ongoing research focuses on enhancing the accuracy and refinement of homology models.

Conclusions:

  • Homology modeling remains a valuable and computationally affordable tool in drug discovery.
  • Continued methodological advancements will further improve the utility of homology models in virtual screening.
  • The integration of homology modeling with docking accelerates the identification of potential drug candidates.