Author(s): Vishwajit S. Patil, Prithviraj A. Patil


DOI: 10.52711/2231-5691.2023.00036   

Address: Vishwajit S. Patil*, Prithviraj A. Patil
Rajarambapu College of Pharmacy, Kasegaon, Sangli, Maharashtra, India – 415404.
*Corresponding Author

Published In:   Volume - 13,      Issue - 3,     Year - 2023

Molecular docking is important tool for drug discovery. It provides a valuable tool for drug design and analysis. The most important application of molecular docking is virtual screening. In this review, we present a introduction of methods of molecular docking, and their development and applications in drug discovery. Many docking programs has developed to visualize the three dimensional structure of molecule and docking score can also get with computational methods. This article includes information on molecular docking, molecular modeling, types of docking, molecular docking models, basic requirement of molecular docking, molecular approach, evaluation, applications software available for molecular docking.

Cite this article:
Vishwajit S. Patil, Prithviraj A. Patil. Molecular Docking: A useful approach of Drug Discovery on the Basis of their Structure. Asian Journal of Pharmaceutical Research. 2023; 13(3):191-5. doi: 10.52711/2231-5691.2023.00036

Vishwajit S. Patil, Prithviraj A. Patil. Molecular Docking: A useful approach of Drug Discovery on the Basis of their Structure. Asian Journal of Pharmaceutical Research. 2023; 13(3):191-5. doi: 10.52711/2231-5691.2023.00036   Available on:

1.    T. Supriya, M. Shankar, S. Kavya Lalitha, J. Dastgiri, M. Niranjan Babu, A Overview on Molecular Docking. American J Biol Pharm Res. 2016; 3(2):83-89
2.    Pozzan A. Molecular descriptors and methods for ligand based virtual high throughput screening in drug discovery. Curr Pharm Des. 2006; 12: 2099-2110.
3.    Green DV. Virtual screening of virtual libraries. Prog Med Chem. 2003; 41: 61-97.
4.    Rarey M, Kramer B, Lengauer T. Multiple Automatic Base Selection: Protein-ligand Docking Based on Incremental Construction without Manual Intervention. J Comput Aided Mol Des. 1997; 11: 369-384
5.    Schulz-Gasch T, Stahl M. Binding Site Characteristics in Structurebased Virtual Screening: Evaluation of Current Docking Tools. J Mol Model. 2003; 9: 47-57.
6.    Friesner RA, Banks JL, Murphy RB, Halgren TA, Klicic JJ, Mainz DT, et al. Glide: A New Approach for Rapid, Accurate Docking and Scoring. 1. Method and Assessment of Docking Acuracy. J Med Chem. 2004.
7.    Abagyan RA, Totrov MM, Kuznetsov DA. ICM: A New Method For Protein Modeling and Design: Applications to Docking and Structure Prediction from the Distorted Native Conformation. J Comp Chem. 1994; 15: 488-50647: 1739-1749.
8.    Ramsay R.R., Popovic-Nikolic M.R., Nikolic K., Uliassi E., Bolognesi M.L. A perspective on multi-target drug discovery and design for complex diseases. Clin. Transl. Med. 2018; 7:3.
9.    Anighoro A., Bajorath J., Rastelli G. Polypharmacology: Challenges and opportunities in drug discovery. J. Med. Chem. 2014; 57:7874–7887.
10.    Kola I., Landis J. Can the pharmaceutical industry reduce attrition rates? Nat. Rev. Drug Discov. 2004; 3:711–716.
11.    Zhang W., Bai Y., Wang Y., Xiao W. Polypharmacology in drug discovery: A review from systems pharmacology perspective. Curr. Pharm. Des. 2016; 22:3171–3181.
12.     Anighoro A., Pinzi L., Marverti G., Bajorath J., Rastelli G. Heat shock protein 90 and serine/threonine kinase B-Raf inhibitors have overlapping chemical space. RSC Adv. 2017; 7:31069–31074.
13.    Lepailleur A., Freret T., Lemaître S., Boulouard M., Dauphin F., Hinschberger A., Dulin F., Lesnard A., Bureau R., Rault S. Dual histamine H3R/serotonin 5-HT4R ligands with antiamnesic properties: pharmacophore-based virtual screening and polypharmacology. J. Chem. Inf. Model. 2014; 54:1773–1784.
14.    Wei D., Jiang X., Zhou L., Chen J., Chen Z., He C., Yang K., Liu Y., Pei J., Lai L. Discovery of multitarget inhibitors by combining molecular docking with common pharmacophore matching. J. Med. Chem. 2008; 51:7882–7888.
15.    Rastelli G., Pinzi L. Computational polypharmacology comes of age. Front. Pharmacol. 2015; 6:157.
16.    Zhang W., Pei J., Lai L. Computational multitarget drug design. J. Chem. Inf. Model. 2017; 57:403–412.
17.    Pinzi L., Caporuscio F., Rastelli G. Selection of protein conformations for structure-based polypharmacology studies. Drug Discov. Today. 2018; 23:1889–1896.

Recomonded Articles:

Author(s): Dinesh D. Rishipathak, Trupti A. Jadhav, Sonal P. Tathe, Pavan B. Udavant

DOI: 10.5958/2231-5691.2019.00023.6         Access: Open Access Read More

Author(s): Ravindra Gaikwad, Sanket Rathod, Anilkumar Shinde

DOI: 10.52711/2231-5691.2022.00043         Access: Closed Access Read More

Author(s): Vishwajit S. Patil, Prithviraj A. Patil

DOI: 10.52711/2231-5691.2023.00036         Access: Closed Access Read More

Author(s): Soham Pawar, Chaitrali Kulkarni, Puja Gadade, Supriya Pujari, Surajkumar Kakade, S.H. Rohane, V.K. Redasani

DOI: 10.52711/2231-5691.2023.00053         Access: Closed Access Read More

Author(s): Shalini A. Shinde, Manasi J. Mhetar, Avantika G. Parit, Akash R. Thombre

DOI: 10.52711/2231-5691.2024.00005         Access: Closed Access Read More

Asian Journal of Pharmaceutical Research (AJPRes.) is an international, peer-reviewed journal, devoted to pharmaceutical sciences. AJPRes. publishes Original Research Articles, Short Communications..... Read more >>>

RNI: Not Available                     
DOI: 10.5958/2231–5691 

Recent Articles