Assessing molecular docking tools: understanding drug discovery and design

Abstract Background In this twenty-first century, artificial intelligence and computational-based studies, i.e., pharmaceutical biotechnology, are more important in every field, even in the field of drug discovery, design, and development, and they should be for managing time, cost, energy, and the environment, as well as chemical consumption in laboratories and research centers. Main Body of the Abstract The study of molecular docking with relative components like classifications, models, and different types of approaches and techniques involved, pose generation, scoring function advantages, disadvantages, and comparison with other types of docking tools to conduct the molecular docking with steps involved will be helpful to learn computer-aided drug design and artificial intelligence. The mechanism involved and the step-by-step procedure of molecular docking are well elaborated and understandable. The applications of molecular docking to finding new ligands and affinities, optimizing drug candidates, and understanding molecular interactions with different receptors like proteins and enzymes for the treatment of many diseases, viz. cancer, SARS-COVID, inflammation, gravis, glaucoma, Alzheimer’s disease, and bacterial infections, make it faster and cheaper than traditional screening. The almost or maximum molecular docking software, as applicable to the specialization in this study of drug discovery, design, and development, includes DOCK, GOLD, GLIDE, MOE, Schrödinger, FlexX, AutoDock, Hammerhead, AutoDock Vina, SwissDock, PyMol, MVD, BIOVIA, MEGADOCK, etc. Short Conclusion Overall, in the field of computational chemistry and pharmaceutical biotechnology, i.e., computational-aided drug design, molecular docking plays an important role in designing and developing a drug molecule to save time, cost, energy, and the environment. With its origins firmly rooted in the developments in computational chemistry and structural biology, molecular docking has evolved from a theoretical concept into an intricate and vital tool in contemporary drug discovery.

Authors

Institutions

Publication Details

Journal
Future Journal of Pharmaceutical Sciences
Published
2025-08-18
DOI
https://doi.org/10.1186/s43094-025-00862-y
Citations
17
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
25.57
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessing molecular docking tools: understanding drug discovery and design

Nishant Gaur, L. D. Sharma, Sonam Sonam, Raghav Mishra et al.
17 citations
Future Journal of Pharmaceutical Sciences
Computational Drug Discovery Methods
25.57
article

Assessing molecular docking tools: understanding drug discovery and design

Nishant Gaur, L. D. Sharma, Sonam Sonam, Raghav Mishra, Arun Kumar Mishra, Nitin Kumar, Vishal Singh, Anjali Singh, Harendar Kumar Nivatya
article en
17 citations

Abstract

Abstract Background In this twenty-first century, artificial intelligence and computational-based studies, i.e., pharmaceutical biotechnology, are more important in every field, even in the field of drug discovery, design, and development, and they should be for managing time, cost, energy, and the environment, as well as chemical consumption in laboratories and research centers. Main Body of the Abstract The study of molecular docking with relative components like classifications, models, and different types of approaches and techniques involved, pose generation, scoring function advantages, disadvantages, and comparison with other types of docking tools to conduct the molecular docking with steps involved will be helpful to learn computer-aided drug design and artificial intelligence. The mechanism involved and the step-by-step procedure of molecular docking are well elaborated and understandable. The applications of molecular docking to finding new ligands and affinities, optimizing drug candidates, and understanding molecular interactions with different receptors like proteins and enzymes for the treatment of many diseases, viz. cancer, SARS-COVID, inflammation, gravis, glaucoma, Alzheimer’s disease, and bacterial infections, make it faster and cheaper than traditional screening. The almost or maximum molecular docking software, as applicable to the specialization in this study of drug discovery, design, and development, includes DOCK, GOLD, GLIDE, MOE, Schrödinger, FlexX, AutoDock, Hammerhead, AutoDock Vina, SwissDock, PyMol, MVD, BIOVIA, MEGADOCK, etc. Short Conclusion Overall, in the field of computational chemistry and pharmaceutical biotechnology, i.e., computational-aided drug design, molecular docking plays an important role in designing and developing a drug molecule to save time, cost, energy, and the environment. With its origins firmly rooted in the developments in computational chemistry and structural biology, molecular docking has evolved from a theoretical concept into an intricate and vital tool in contemporary drug discovery.

Future Journal of Pharmaceutical SciencesVol. 11(1)
Shri Venkateshwara University (IN), IFTM University (IN), Chaudhary Charan Singh University (IN), National Institute of Pharmaceutical Education and Research (IN), Saraswati Dental College and Hospital (IN), Innovative Research (United States) (US), Sharda University (IN)
Openalex Percentile: Top 0%
Computational Drug Discovery Methods
25.57
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.