Pharmacophore based...

Copyrighted material © S.Prasanth Kumar, 2011 1

Pharmacophore-based Ligand Designing using Substructure Searching to Explore New Chemical Entities

(NCEs)

S.Prasanth Kumar, Bioinformatician

Copyrights Copyright © 2011 S.Prasanth Kumar. This is an open access document distributed under the public domain, which permits unrestricted use, distribution, and reproduction in any medium. This protocol should be a demonstration to better understand the concepts and the learners are advised to do it themselves. Don’t forget to acknowledge the contributors.


AIM OF THIS PROTOCOL:

Scientists always rely on active-site directed ligand designing to design a novel molecule. It can be based on fragment based

drug designing (FBDD) or de novo drug design. This work can be performed if we know the crystallography data (3D structure) of

the receptor protein. If the 3D structure is not available and having in hands, proven activity against a known protein, structure

determination of the ligand molecule is done so that the ligand molecular structure can be enhanced to be an efficient binder. This

case is known as ligand based drug designing (LBDD).

To study the biological activity for a specific receptor protein, lots of ligands having biological activity measured in terms of

IC50 or Ki or MIC50 value and its 3D structure for its identification of pharmacophoric key features, is taken into consideration. Only

at active-site directed ligand designing, new chemical entities (NCEs) are discovered. In this present protocol, the aim is to identify

the pharmacophore of a known activity molecule (in other words, a patented and an already marketing drug molecule). We shall call

it as a pivot/key molecule and a substructure searching on this pivot molecule using its SMILES and/or InChi key chemical formats,

will enlist a lots of compounds having similar scaffold. By selecting a wide range of compounds, we can come across a common

pharmacophore key features which are responsible for its biological activity. Here, we stress after overlaying all the

pharmacophore features, select some functional groups which has similar pharmacophore feature (e.g. OH group act as hydrogen

bond acceptor/donor and it can be placed with NH2 group which has hydrogen bond acceptor and/or donor). In this way, there is a

potential way of identifying NCEs having known pharmacophore features and a docking analysis will help us to identify whether is

a efficient binder or not. This task greatly reduces the virtual and/or organic combinatorial library screening procedure which has

been done on known ligands having broader biological activity spectrum. Now, the specificity and the NCEs identifications are


really disappearing in the library screening. Hence, we propose the above procedure without creating analogs and there is a high

possibility of developing derivatives which can be patented by you!!!

Confusing!!! Contact me at [email protected]

PROGRAMS/SERVERS USED:

1. NCBI’s PubChem (http://pubchem.ncbi.nlm.nih.gov/) 2. PharmaGist (http://bioinfo3d.cs.tau.ac.il/pharma) 3. Marvin Sketch (Free for Academic usage, www.chemaxon.com)

PROTOCOL:

Select a molecule which you want to start a work on generating NCEs or derivatives.

Structure of Imatinib (marketed by Novartis as GleevecTM)

mailto:[email protected]

http://pubchem.ncbi.nlm.nih.gov/%29

http://bioinfo3d.cs.tau.ac.il/pharma

www.chemaxon.com


Go to Pubchem and copy the imatinib’s smiles (only Canonical smiles not Isomeric smiles) or you can copy its InChi Key Go to Pubchem Structure Search, select “Identity/Similarity”, paste your smiles or InChi key and hit the Search button leaving all the parameters default.

From the search list, select molecules and download their respective structures in 3D-SDF format. In case, if the 3D-SDF format is not available, download the 2D-SDF file, open it in Marvin Sketch, Structure > Add > Add Explicit Hydrogens and then choose Cleaning in 3D under the same submenu and save the file in the same format.


In this example, we retrieved two molecules having same scaffold and identical chemical structure. But notice that the two structures are having different conformation

CID: 10435761 CID: 25235726

These structures are of 3D-SDF format. We need structures only on .mol2 format which is the only one format accepted by PharmaGist Just open the structure in any Marvin applications, say Marvin Space and do the following: File>Save As>Type the molecule name and select Tripos molecule (.mol2 format) to save in prescribed format. We are now uploading three molecules to PharmaGist, the Imatinib, CID 10435761 and CID: 25235726. Create a ZIP file (Desktop>Right Click > New > ZIP folder and name the folder according to your convenience, say imatinibspharma.zip). Now, open the ZIP folder and paste the three molecular structures in .mol2 format.


Go to PharmaGist, upload the ZIP file using Browse option, provide your email ID without spelling mistakes, no of output pharmacophores is 5 (default). Without using advanced options, click on Submit Query button.

You will be directed to a page (snapshot in next page) where you can find your submission status. The server will validate our molecules, run the program and the result will be emailed to us. Please note that the results will not be displayed after the execution of the program, they will notify us the results on email providing the link to retrieve the results.


Clicking on link in the received email will be directed to a page where you can find the results.


INTERPRETATION OF RESULTS OBTAINED:

In the eighth page, we can get an overview of all the existing pharmacophore features available in all ligand molecules. Under Sort by Score (eighth page, second image), you can see the multiple structural alignment. Here, you can see each and every molecule was given a chance to act as pivot molecule, upon which the rest two molecules will be aligned. This approach has been adopted to have a blind search and possibly, get the correct alignment based on repeated iterations on selecting pivot molecule and aligning the rest of the molecules. We can judge the best alignment using the score 40.530 using CID: 10435761 acted as the pivot molecule. Click on the corresponding row having the header “Jmol” (e.g. J3_1.html and the link will be directed to open another page: see snapshot of ninth page bottom snapshot). (We can also check the pairwise structure alignment as we do in multiple sequence alignment by clicking on “View Best Pairwise Alignment” header and as usual, you will be directed to another page, which looks like in the top image given at the ninth page).


In the tenth page, we can see the pharmacophore overlaid on aligned 3D ligand molecules (Java Plugin required to visualize). * Symbol indicates the pivot molecule as we know already. Checking on all the options under the header “Show Molecule” and “Show Features” will help you to study the pharmacophore as reported in page no.10. Uncheck all the options under Show Molecule header, to get an overview what are the pharmacophore features actually aligned. You can see the color scheme adopted for every pharmacophore feature will help you to recognize. Finally, clicking on “Download Pharmacophore and Alignment File” will open up a pop-up window to download/save the file. Please note that this aligned file will be in .mol2 format. Opening this file will get you a structural alignment (superimposed structures).


Copyright © 2011 S.Prasanth Kumar. This is an open access document distributed under the public domain, which permits unrestricted use, distribution, and reproduction in any medium. If any errors or corrections or comments to make, please feel free to email me at [email protected]

Pharmacophore based...

Education

Transcript of Pharmacophore based...