|Year : 2014 | Volume
| Issue : 3 | Page : 137-138
Predicting perfect drug candidates: Molecular docking 2.0
Mohamed Ismail Nounou
Department of Pharmaceutics, Faculty of Pharmacy, Alexandria University, Egypt
|Date of Web Publication||24-Jun-2014|
Mohamed Ismail Nounou
Department of Pharmaceutics, Faculty of Pharmacy, Alexandria University
Source of Support: None, Conflict of Interest: None
|How to cite this article:|
Nounou MI. Predicting perfect drug candidates: Molecular docking 2.0. J Pharm Bioall Sci 2014;6:137-8
Development of a new active pharmaceutical entity and its transformation from bench to bedside is a lengthy and costly process. On an average, it takes over 15 years and $600 million to develop one drug out of at least 10,000 candidates in its pathway from the laboratory to market.  Drug discovery process is usually initiated with identifying, isolating and validating the disease target followed by lead compounds screening, identification and optimization.
The progression and elaboration of the state-of-art computer aided drug design and development helped in overshadowing the traditional synthetic pathways in drug discovery. Advanced in-silico approaches and pharmainformatics have provided a tremendous push to pharmaceutical companies and medicinal chemists towards rapid and efficient identification of new potential drug targets and candidates. 
Traditionally, disease targets, such as isolated receptor proteins, were identified via complicated and lengthy processes such as nuclear magnetic resonance and X-ray crystallography. The advances in homology modeling have provided a quick and easy, in spite of being less accurate, tool to identify targets via constructing an atomic resolution model of the target protein from its amino acid sequence and/or its related homology proteins.  On the other hand, lead discovery and identification can be performed by in-silico techniques such as molecular docking, virtual high throughput screening, quantitative structure activity relationship, pharmacophore mapping and fragment based screening. These techniques involve possible drug candidate database filtering, similarity analysis and alignment.
Molecular docking is an effective and fast computational technique to estimate the binding affinity of a ligand (drug candidate) in the macromolecular target site (receptor). It is usually based on the receptor, if the chemical and 3D structure of the target is well-known, or ligand, if the target structure is unknown. In the case of ligand based molecular docking, a known inhibitor or activator of the target site is used to deduct the possible structural information of the target site. Molecular docking algorithms, used in such design process, depend on molecular structure flexibility and search criteria to estimate the optimal binding positions. A scoring system is used to detect the ideal docking configuration. Scoring systems usually uses entropy maximization strategies, which generally depend on electrostatic attraction forces, Van der Waal's forces and hydrophobic interactions. 
The establishment and development of well-defined and large chemical compounds' databases facilitated efficient and rapid molecular docking. PubChem databases (http://pubchem.ncbi.nlm.nih.gov) are some of the most widely used databases in molecular docking. They were first released and available online on 2004 by the United States National Institutes of Health. , PubChem databases include PubChem Substance, PubChem Compound and PubChem Bioassay. These databases provide easily accessible and free information on the 2D and 3D chemical structures and biological activities of over 130 million bioactive small chemical compounds. 
Furthermore, the current availability of numerous academically free and/or open-source virtual screening and/or docking software such as Molegro Virtual Docker® , Dock® , AutoDock® , FLO TM , Flex X® and molecular operating environment (MOE), molecular homology software such as Modeller® and molecular visualization and properties prediction software such as PyMOL® PrpSA® , PreADMet® and Mavrin Sketch® facilitated the wild spread of molecular docking research in the past 5 years. Such free software tools and free available databases encouraged and enabled researchers from all over the world to advance in the molecular docking and computer-aided drug design in a dry laboratory settings developing high quality publications with minimal costs. In addition, the decreased total cost of powerful power horse computers-aided such kind of research.
In the current research article, the authors adopted the computer aided design approach to develop therapeutics targeting the unique and essential enzyme; porphobilinogen synthase (PBGS) to control and manage the staphylococcal infections. As the structure of Staphylococcus aureus PBGS is not known, the authors adopted virtual homology modeling to construct a possible 3D model using Modeller® 9 v8 tool (University of California San Francisco, San Francisco, CA 94158-2330, USA). The X-ray crystallographic structure of PBGS from Chlorobium vibrioform was used as a template. Molecular docking was carried out using MOE docking software. As 4,5-dioxovalerate (DV) is known to inhibit PBGS, a library of dioxovalerate derivatives (DVDs) was used. DVD13 was found to be the most effective PBGS activator among all DVDs based on its docking score. The whole experimental study for this drug design process in this article was performed in a total dry laboratory setting.
In spite of the previously mentioned advantages of dry laboratory research in molecular docking, pre-clinical in-vitro and in-vivo studies are still required to determine if such discovered lead compounds are worth the time and money to proceed and initiate further clinical development and evaluation. Future wise, dry laboratory drug discovery should be accompanied with lead compounds chemical optimization and appendixed with sufficient wet laboratory in-vitro and in-vivo proof of the efficacy and safety of the proposed drug candidates.
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