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Basic Training modules: (45 days) For further details contact us here:

 

1) Basic Introduction to Bioinformatics and its role in Drug Discovery.

 

2) Various softwares to perform different tasks useful for novel drug discovery.

 

3) Molecular docking : Preparation, execution and analysis of the results.

 

4) Virtual screening : Preparation, execution and analysis of the results.

 

5) ADME and toxicology studies: ADMET screening of compounds using various online and offline tools and their interpretation. 

 

Advanced Training modules: (90 days) For further details contact us here:

 

All modules covered in above mentioned basic training module +

6) Pharmacophore modelling

 

7) Homology modelling of proteins: Preparation, execution, analysis and validation of the results.

 

8) Molecular Dynamic simulations: Preparation, execution and analysis of the results.

 

Structure and ligand based virtual screening studies

Virtual screening is a computational technique used in drug discovery research for screening of large chemical space for potential lead drug candidates towards a known drug target, typically an enzyme or a protein receptor. As the accuracy and correlation of this method of screening with experimental results is increased, the application of this technique is being highly appreciated in pharma industries towards screening enormous chemical space of over 10 million chemical compounds. Based on the available knowledge regarding potential drug target/ligand, structure/ligand based virtual screening will be implemented either individually or in combination for identifying potential lead drug like compounds.

Molecular docking

Docking is a method of predicting the most favorable binding mode between drug target and the given ligand molecule towards forming a stable complex. Orientation of the ligand molecule in the protein target has a major role to play in determining its association strength, which is also known as binding affinity. The strength of association and the orientation of the compound in the drug target determine the functioning of that particular compound as activator or inhibitor. This also plays key role off-target activity of the drug candidate which might lead to side effects. Hence, studying the various interactions involved in forming the binding complex in details is an unmatchable key step towards rational drug designing.

Protein-protein and Protein-ligand interaction studies

Most of the biological functions depends upon the protein-protein interactions, especially signal transduction mechanisms, which is the core of the entire interactomics system of any living cell. Many disease pathways such as cancer, undesired protein-protein interactions are the key factors towards malfunctioning of the cells. Most of the anti cancer drugs have been identified by blocking the protein-protein interacting pathway. Hence, studying the network pathways involving many protein interactions is crucial towards finding novel drug targets and studying the protein-ligand interactions which can specifically target a particular protein-protein interaction is vital for novel drug discovery.

Free energy calculations:

Free energy calculation/perturbation is the most common method used in computational chemistry for conformational sampling of protein and ligand mutations in order to calculate the energy barriers required for transition between one state (A) to another state/conformation (B). Quantum mechanics/molecular mechanics (QM/MM) and Umbrella sampling are the two majorly employed methods for free energy calculations.

Molecular dynamic simulations

Molecular dynamic (MD) simulations is a method in which physical movements of atoms and molecules under given physiochemical conditions. MD is widely used in determining the thermodynamic properties of the given protein structure in complex with/without ligand in the presence of solvent at given pH, temperature and pressure. Through this method total potential energy of the given protein-ligand complex along with associated interaction energies can be calculated towards validating their association strength during the conformational changes.

Homology modeling

Homology modeling is a computational modeling technique used for generating high resolution hypothetical proteins by using the evolutionarily related protein structure information. This method is highly valuable when the structure of the protein target is not known. Presently available softwares allow us to build therapeutically important drug targets with high accuracy and correlation with experimentally determined protein structures.

ADMET predictions

Absorption, distribution, metabolism, exertion and toxicity (ADMET) properties determination is an essential criteria should be considered during the initial stages of rational dug designing and a valuable tool in short listing potential drug candidates out of lacks of compounds.

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