Organization of Swiss Dock:

In study of Computational and Molecular Docking Study

 

Neha Subhash Patil*, Sachin H. Rohane

Department of B. Pharmacy at Yashoda Technical Campus, Satara.

 

ABSTRACT:

In the present era, many fields of research are showing great importance. Apart from the applications researchers have grown their interest in pharmaceutical application. Protein play and important side in study of various in - vitro and in - vivo studies to understand the action of drugs. Docking programs have a wide range of applications ranging from protein Engineering to the drug design. Swiss dock software was guide to authors to predict the molecular interactions that may occur between a target protein and a small molecule. After review it was analysed that Swiss dock are organised for UV-VIS spectroscopy, Synthesis, crystal, structures, etc. This article presents Swiss Dock, a web server dedicated to the docking of small molecules on target proteins. It is based on the EADock DSS engine, combined with setup scripts for curating common problems and for preparing both the target protein and the ligand input files. An efficient Ajax/ HTML interface was designed and implemented so that scientists can easily submit dockings and retrieve the predicted complexes. For automated docking tasks, a programmatic SOAP interface has been set up and template programs can be downloaded in Perl, Python and PHP. The web site also provides an access to a database of manually curated complexes, based on the Ligand Protein Database.

 

 

 

INTRODUCTION:

Molecular docking is prediction of the binding affinity To achieve an optimize Conformation for both receptor and ligand and relative orientation between protein and ligand such that the free energy of the overall system minimized Molecular docking is one of the most frequently used methods in structure based drug design, due to its ability to predict the binding conformation of Small molecule ligands to the appropriate target binding site. Molecular docking has become an increasingly important tool for drug discovery Programs based on different algorithm were developed to perform molecular dockings studies which have made docking an increasingly important tool in pharmaceutical research.

 

The aim of molecular docking is to give a prediction of the ligand-receptor Complex structure using computation methods Swiss Dock a web Service to predict the molecular interaction that may occur between target protein and a small molecule many binding modes are generated either in a box or in a vicinity of all target cavities [1-3].

 

Computer aided Drug Design:

Drug design depends on knowledge of 3D structures of biomolecules that is known as structural aided drug design. in addition to small molecules biopharmaceutical induces peptides and especially therapeutic antibodies are increasingly important doss of drug and computational method for improving affinity selectivity and stability been developed.

 

Most docking programs are Complex computational machineries and require specific additional Sampling or Scaring parameters to which they might be very sensitive while convenient default values are often a proposed good understanding of the user manual and the original article is always required in order to achieve meaningful prediction.

 

Swissdock:

Swiss Dock is the docking web server that addresses limitations described above. Well a the structure of the target protein, as well as that of the ligand, can be automatically prepared for docking. Allcalculation performed on the server side, so that docking runs do not require any Computational power from the user.

 

A target protein structure can be determined either by specifying its identifier from the protein data Bank. Since the calculation are performed in the CHARMM force field, Swiss dock Supports the uploading of CHARMM. Formatted files in addition to the Commonly used PDB format protein Structure can be uploaded as a set of protein structure file, Coordinate file and extra topology and parameter files if needed. Once the target protein structure has been defined it is immediately prepaid for used with CHARMM, and the Curated structure can be downloaded and reviews prior to the docking assay if needed. The performance of the backend of Swissdock was assessed by a blinding docking assay on 251 test Complexes taken from the ligand protein Database with different presents available from the web interface. The performance of Swiss Dock depends on the number of free dihedrals of the ligand.

 

Influence of the flexibility of the success rate observed with SwissDock the docking engine of SwissDock redocking assay Carried out on 251 protein ligand Complex.

 

Table No. 01

Max No. of routable bond of the Ligands	FDA Approved Drug (in %)	SR0 (%)	SR5 (%)
5	63	84	93
10	93	77	86
15	99	69	83
20	100	66	81

 

The fraction of the surface of the ligand which becomes buried upon complexation also has Significant effect the higher this fraction, the easier it is for Swiss Dock to identify the binding pocket, and therefore to dock the ligand inside.

 

Table No. 02

Influence of the fraction of the Ligand which is buried upon complexation (% BS) on the same data set.

 

Min % BS	SR0 (%)	SR5(%)
95	82	95
90	70	85
85	66	80
80	62	75

 

Swiss Dock Input Files

·       Since docking assays are carried out in the CHARMM 22 /27 all-hydrogen force field.

·       Target proteins and ligands that have been uploaded as CHARMM- Formatted files Can be used.

·       Protein and ligands that have been submitted in PDB or be mold to format respectively have to be Converted prior to the docking itself.

 

Computer Aided Drug Design:

Simply rational design is the inventive process of finding new medication based on biological target the drugs are commonly organic small moleculesthats activates or inhibits function of biomolecules such like a protein. That is further give the therapeutic action to the patient. Basic in that isdrug design means the invole in molecules that complementry in shape and size of biomolecules. They bind with each other and form the bond. Drug design not relies on computer modelling. this type of modelling callled as computet aided drug design. Drug design depends on knowledge of 3D structures of biomolecules that is known as structural aided drug design. in addition to small molecules biopharmaceutical indudes peptides ans especially therapeutic antibodies are incresingly important dass of drug and computational method for improving affinity selectivity and stability been developed.

 

Drug design also known as efforts to develop a new drug by molecular modification of lead compound for optimization of desired efferts and minimization of side effects.

 

·         Web interface Inputs:

Only three steps are required to start a docking assay through the web interface of SwissDock: users must define a protein structure, one or several putative ligands and docking parameters. They are guided throughout this short and simple submission process by a comprehensive contextual help. As mentioned above, several sample files are supplied to users and can be directly uploaded into the form simply by clicking on a link. The corresponding sample output files are also provided.

 

·         Target selection:

A target protein structure can be determined either by specifying its identifier from the Protein Data Bank (15) or by uploading structure files. The first option allows users who are not familiar with 3D structure files to start a docking assay with only a PDB code. If several PDB records are available for the same target, those with a high resolution and a ligand similar to the one that will be docked should be considered first.

 

·         Ligand selection:

A ligand can be selected either by specifying its identifier from the ZINC database (23) or by uploading structure files. The former possibility allows users who are not familiar with 3D structure files to start a docking assay with only a ZINC accession code (AC). The latter allows uploading several ligands at once or uploading ligands that are not present in the ZINC database. As for the target protein, SwissDock not only supports the widely used Mol2 format, but also the direct upload of CHARMM input files describing the ligand.

 

Review of Litreture:

Sabrin R. M. Ibrahim and Khalid Z. Al-shaliand et al used SwissDock ADME for Molecular Docking studies of the tested metabolites estimated to shade up rational explanation of α – amylase inhibitory activity result the pharmacokinetic parameter [4].

 

Mohammad Kabrineand et al used SwissDock in article to investigate the possible mechanism by which selected drugs act an silico theoretical molecular docking approach was used, during this study they stimulated the binding mode of N3 against 6lu7 crystal structure using SwissDock to ensure the effectiveness of Dock result and to compare result produced by several drugs to those of N3 [5].

 

Kerry A. Ramshottom et al used SwissDock programme to investigate that if the software cooled accurately dock the abacavir back into the crystal structure for the protein arising from the known risk allele and if the software is able to distinguish between the HLA-associated and known HLA associated allele [6].

 

Long Ding and et al used SwissDock software to discover Bioactive peptide silico method peptide would be experimental in-vitro to identify the activity [7].

 

Dae Hawn-Kim and et al used SwissDock stimulation analysis of unbiased blind docking it was determined the top score predicted blind side for SGI-1027 and M\M to localize the binding region on PrP. The result indicates CHI-1027 interacted with and regions on PrP [8].

 

Jesus Campagna and et al used SwissDock for evaluation of an Allosteric BACE inhibiter peptide to identify mimetic that can interact with the loop and region of the Enzyme and prevent APP cleavage and to elucidate the mechanism of peptide 65007 allosteric inhibition in silico experiment were performed first by conducting molecular docking in SwissDock with 65007 and comparing the model to crystal structure of the genetech Ab and BACE [9].

 

Layla K. Mahdi and et al used SwissDock experiment with GlpO model and its Ligands shows surface representation and the carbo-hydrate ligands as sticles. A predicted binding modes for LNT with a surface representation of GlpO model [10].

 

ElahelKashoni – Amin and et al used SwissDockfor the active site celef is quite extended, some poses were found to occur for the ligand in this location, However a second putative interacting site was found that is located in the entrance of the central beta-barrel of the enzyme. It should be seen that this location was detected by Swiss Dock [11].

 

Kankana Das and et al used SwissDock in compatible lipid lingad was then docked with proteins that are available as original PDB files were SwissDock interface the results were viewed and analysed [12].

 

Flavia S. Darquiand et al used SwissDock for putative KpFat A and KpFatB protein structure when moldedbu using homology modling using the Swiss model workspace. Based on their sequence the semi-colum zero-Acpthioesterace crystal structure from G. Californica as a term plate and default primary parametaFurthemore molecular docking was performed [13].

 

Christina E. Smith and et alused SwissDock for performing the docking of NSAIDs with Capase-3 was performed [14].

 

Jamal Quazzaniand et al used SwissDock in Silico studies for the docking of GP269, target was prepared from the X-ray protein structure of the crystalized complex. Polar hydrogen atom were added to the protein, The docking of GP269 into the structure of Tb6PGL was performed using the Swiss Dock [15].

 

CONCLUSION:

From Reviewing the above literatures, it was found that the Swiss Dock Software is used to predict the molecular interaction that may occur between a target protein and a small molecule.

 

The Swiss Dock web server aims at providing a wide scientific community with a free and user-friendly, yet stateof-the-art protein/small molecule, docking tool. The automatic setup of protein and ligand structures, the different parameter presents and the convenient visualization and analysis of docking predictions makes it accessible to a wide audience. The EADock DSS engine behind SwissDock is especially suited for drug design, with very good success rates for small and relatively rigid ligands with less than 10 flexible rotatable bonds: the most favourable predicted BM is found within 2 A˚ to the crystal structures for 77% of the 251 test complexes, and for 86% of them, such a correct BM is found within the five most favourable ones. This performance is even increased if the ligand can be buried in a well-defined binding site of its target protein.

 

REFERENCES:

1.        Rohane S.H., Makwana A.G., 2017. A Review on Hydrazone, the Fascinating field of investigation in medicinal chemistry. Asian J. Res. Chem. 10, 417-430.

2.        Rohane S.H., Makwana A.G., 2019. In silico study for the prediction of multiple pharmacological activities of novel hydrazone derivatives. Ind J. Chem. Sec-B. 58, 387-402.

3.        Rohane S.H., Makwana A.G., 2020. Synthesis and in vitro antimycobacterial potential of novel hydrazones of eugenol. Arab J. Chem. 13, 4495–4504

4.        Sabrin R. M. Ibrahim, Khalid Z. Al-shaliand et al, Brazilian Journal of Pharmacognosy (04 Feb, 2019).

5.        Mohammad Kabrineand et al, Journal of Molecular Graphics and Modelling (15 Sept 2020).

6.        Kerry A. Ramshottom and et al, An Article on Molecular Immunology (2018).

7.        Long Ding and et al, Food Science and Human Wellness (3 April, 2020).

8.        Dae Hawn-Kim and et al, Acta Pharmaceutical Sinica – B (4 April, 2019).

9.        Jesus Campagna and et al, Evaluation of an Allosteric BACE Inhibiter peptide to Identify mimetic that can Interact with the loop and region of the Enzyme and prevent APP cleavage (10 Apr, 2018)

10.     Layla K. Mahdi and et al, E-Bio Medicine (2 March, 2017).

11.     ElahelKashoni–Amin and et al, NeohesperidinDihyclrochalcone presentation of a small molecule activator of mammalian alpha-amylase as an Allosteric Effector (8 Jan 2013).

12.     Kankana Das and et al, General Functional Foods (2020)

13.     Flavia S. Darquiand et al, Electronic Journal of Bio-Technology (29 Sept 2017).

14.     Christina E. Smith and et al, Chemical Biology (16 March, 2017).

15.     Jamal Quazzaniand et al, Biophysical Journal 115-2114-2126 (04 Dec, 2018).

 

 

Received on 07.11.2020                    Modified on 24.11.2020

Accepted on 15.12.2020                   ©AJRC All right reserved