Panoramic Review on Progress and Development of Molecular Docking

Kiran Dudhat

doi:doi:10.11648/j.pst.20230701.11

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Panoramic Review on Progress and Development of Molecular Docking

Kiran Dudhat

Published in Pharmaceutical Science and Technology (Volume 7, Issue 1)

Received: 7 November 2022 Accepted: 28 November 2022 Published: 15 March 2023

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Abstract

In structural molecular biology and computer-assisted drug creation, molecular docking is a crucial tool. Predicting the prevailing binding mode (s) of a ligand with a protein having a known three-dimensional structure is the aim of ligand-protein docking. Effective docking methods use a scoring system that correctly ranks candidate dockings and efficiently explore high-dimensional spaces. Lead optimization benefits greatly from the use of docking to do virtual screening on huge libraries of compounds, rate the outcomes, and offer structural ideas for how the ligands inhibit the target. It can be difficult to interpret the findings of stochastic search methods, and setting up the input structures for docking is just as crucial as docking itself. In recent years, computer-assisted drug design has relied heavily on the molecular docking technique to estimate the binding affinity and assess the interactive mode since it can significantly increase efficiency and lower research costs. The main concepts, techniques, and frequently utilized molecular docking applications are introduced in this work. Additionally, it contrasts the most popular docking applications and suggests relevant study fields. Finally, a brief summary of recent developments in molecular docking, including the integrated technique and deep learning, is provided. Current docking applications are not precise enough to forecast the binding affinity due to the insufficient molecular structure and the inadequacies of the scoring mechanism.

Published in	Pharmaceutical Science and Technology (Volume 7, Issue 1)
DOI	10.11648/j.pst.20230701.11
Page(s)	1-4
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2023. Published by Science Publishing Group

Keywords

Molecular Docking, Use, Optimization, Software for Molecular Docking, Virtual Screening

References

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APA Style

Kiran Dudhat. (2023). Panoramic Review on Progress and Development of Molecular Docking. Pharmaceutical Science and Technology, 7(1), 1-4. https://doi.org/10.11648/j.pst.20230701.11

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ACS Style

Kiran Dudhat. Panoramic Review on Progress and Development of Molecular Docking. Pharm. Sci. Technol. 2023, 7(1), 1-4. doi: 10.11648/j.pst.20230701.11

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AMA Style

Kiran Dudhat. Panoramic Review on Progress and Development of Molecular Docking. Pharm Sci Technol. 2023;7(1):1-4. doi: 10.11648/j.pst.20230701.11

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@article{10.11648/j.pst.20230701.11,
  author = {Kiran Dudhat},
  title = {Panoramic Review on Progress and Development of Molecular Docking},
  journal = {Pharmaceutical Science and Technology},
  volume = {7},
  number = {1},
  pages = {1-4},
  doi = {10.11648/j.pst.20230701.11},
  url = {https://doi.org/10.11648/j.pst.20230701.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.pst.20230701.11},
  abstract = {In structural molecular biology and computer-assisted drug creation, molecular docking is a crucial tool. Predicting the prevailing binding mode (s) of a ligand with a protein having a known three-dimensional structure is the aim of ligand-protein docking. Effective docking methods use a scoring system that correctly ranks candidate dockings and efficiently explore high-dimensional spaces. Lead optimization benefits greatly from the use of docking to do virtual screening on huge libraries of compounds, rate the outcomes, and offer structural ideas for how the ligands inhibit the target. It can be difficult to interpret the findings of stochastic search methods, and setting up the input structures for docking is just as crucial as docking itself. In recent years, computer-assisted drug design has relied heavily on the molecular docking technique to estimate the binding affinity and assess the interactive mode since it can significantly increase efficiency and lower research costs. The main concepts, techniques, and frequently utilized molecular docking applications are introduced in this work. Additionally, it contrasts the most popular docking applications and suggests relevant study fields. Finally, a brief summary of recent developments in molecular docking, including the integrated technique and deep learning, is provided. Current docking applications are not precise enough to forecast the binding affinity due to the insufficient molecular structure and the inadequacies of the scoring mechanism.},
 year = {2023}
}

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TY  - JOUR
T1  - Panoramic Review on Progress and Development of Molecular Docking
AU  - Kiran Dudhat
Y1  - 2023/03/15
PY  - 2023
N1  - https://doi.org/10.11648/j.pst.20230701.11
DO  - 10.11648/j.pst.20230701.11
T2  - Pharmaceutical Science and Technology
JF  - Pharmaceutical Science and Technology
JO  - Pharmaceutical Science and Technology
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EP  - 4
PB  - Science Publishing Group
SN  - 2640-4540
UR  - https://doi.org/10.11648/j.pst.20230701.11
AB  - In structural molecular biology and computer-assisted drug creation, molecular docking is a crucial tool. Predicting the prevailing binding mode (s) of a ligand with a protein having a known three-dimensional structure is the aim of ligand-protein docking. Effective docking methods use a scoring system that correctly ranks candidate dockings and efficiently explore high-dimensional spaces. Lead optimization benefits greatly from the use of docking to do virtual screening on huge libraries of compounds, rate the outcomes, and offer structural ideas for how the ligands inhibit the target. It can be difficult to interpret the findings of stochastic search methods, and setting up the input structures for docking is just as crucial as docking itself. In recent years, computer-assisted drug design has relied heavily on the molecular docking technique to estimate the binding affinity and assess the interactive mode since it can significantly increase efficiency and lower research costs. The main concepts, techniques, and frequently utilized molecular docking applications are introduced in this work. Additionally, it contrasts the most popular docking applications and suggests relevant study fields. Finally, a brief summary of recent developments in molecular docking, including the integrated technique and deep learning, is provided. Current docking applications are not precise enough to forecast the binding affinity due to the insufficient molecular structure and the inadequacies of the scoring mechanism.
VL  - 7
IS  - 1
ER  -

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Author Information

Kiran Dudhat

School of Pharmacy, RK University, Gujarat, India

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Plain Text BibTeX RIS

APA Style

Kiran Dudhat. (2023). Panoramic Review on Progress and Development of Molecular Docking. Pharmaceutical Science and Technology, 7(1), 1-4. https://doi.org/10.11648/j.pst.20230701.11

Copy | Download

ACS Style

Kiran Dudhat. Panoramic Review on Progress and Development of Molecular Docking. Pharm. Sci. Technol. 2023, 7(1), 1-4. doi: 10.11648/j.pst.20230701.11

Copy | Download

AMA Style

Kiran Dudhat. Panoramic Review on Progress and Development of Molecular Docking. Pharm Sci Technol. 2023;7(1):1-4. doi: 10.11648/j.pst.20230701.11

Copy | Download

@article{10.11648/j.pst.20230701.11,
  author = {Kiran Dudhat},
  title = {Panoramic Review on Progress and Development of Molecular Docking},
  journal = {Pharmaceutical Science and Technology},
  volume = {7},
  number = {1},
  pages = {1-4},
  doi = {10.11648/j.pst.20230701.11},
  url = {https://doi.org/10.11648/j.pst.20230701.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.pst.20230701.11},
  abstract = {In structural molecular biology and computer-assisted drug creation, molecular docking is a crucial tool. Predicting the prevailing binding mode (s) of a ligand with a protein having a known three-dimensional structure is the aim of ligand-protein docking. Effective docking methods use a scoring system that correctly ranks candidate dockings and efficiently explore high-dimensional spaces. Lead optimization benefits greatly from the use of docking to do virtual screening on huge libraries of compounds, rate the outcomes, and offer structural ideas for how the ligands inhibit the target. It can be difficult to interpret the findings of stochastic search methods, and setting up the input structures for docking is just as crucial as docking itself. In recent years, computer-assisted drug design has relied heavily on the molecular docking technique to estimate the binding affinity and assess the interactive mode since it can significantly increase efficiency and lower research costs. The main concepts, techniques, and frequently utilized molecular docking applications are introduced in this work. Additionally, it contrasts the most popular docking applications and suggests relevant study fields. Finally, a brief summary of recent developments in molecular docking, including the integrated technique and deep learning, is provided. Current docking applications are not precise enough to forecast the binding affinity due to the insufficient molecular structure and the inadequacies of the scoring mechanism.},
 year = {2023}
}

Copy | Download

TY  - JOUR
T1  - Panoramic Review on Progress and Development of Molecular Docking
AU  - Kiran Dudhat
Y1  - 2023/03/15
PY  - 2023
N1  - https://doi.org/10.11648/j.pst.20230701.11
DO  - 10.11648/j.pst.20230701.11
T2  - Pharmaceutical Science and Technology
JF  - Pharmaceutical Science and Technology
JO  - Pharmaceutical Science and Technology
SP  - 1
EP  - 4
PB  - Science Publishing Group
SN  - 2640-4540
UR  - https://doi.org/10.11648/j.pst.20230701.11
AB  - In structural molecular biology and computer-assisted drug creation, molecular docking is a crucial tool. Predicting the prevailing binding mode (s) of a ligand with a protein having a known three-dimensional structure is the aim of ligand-protein docking. Effective docking methods use a scoring system that correctly ranks candidate dockings and efficiently explore high-dimensional spaces. Lead optimization benefits greatly from the use of docking to do virtual screening on huge libraries of compounds, rate the outcomes, and offer structural ideas for how the ligands inhibit the target. It can be difficult to interpret the findings of stochastic search methods, and setting up the input structures for docking is just as crucial as docking itself. In recent years, computer-assisted drug design has relied heavily on the molecular docking technique to estimate the binding affinity and assess the interactive mode since it can significantly increase efficiency and lower research costs. The main concepts, techniques, and frequently utilized molecular docking applications are introduced in this work. Additionally, it contrasts the most popular docking applications and suggests relevant study fields. Finally, a brief summary of recent developments in molecular docking, including the integrated technique and deep learning, is provided. Current docking applications are not precise enough to forecast the binding affinity due to the insufficient molecular structure and the inadequacies of the scoring mechanism.
VL  - 7
IS  - 1
ER  -

Copy | Download