Workshop 4: Molecular Docking and ADME(T) profile prediction

Dr. KRID Adel

Theoretical & Computational Research Group.

LPMS - Faculty of Sciences

Frères Mentouri University - Constantine 1 (UFMC)

Research Center on Pharmaceutical Sciences CRSP.

Email: wadelkrid@gmail.com

Abstract:

Molecular docking is a method that is used to predicts how a ligand (small molecule) fits into a target (protein or enzyme) to form a stable complex. This is crucial to study the preferred orientation and complementarity of molecules in the active site and may be used to predict the strength of association or binding affinity according to scoring function (energy evaluation).

The understanding and the knowledge of ligand-target interactions are fundamental in drug design. This will guide and help to design new therapeutic agents to by modeling new pharmacophores.

In silico prediction of biological molecules is a technique used to know the potential and the most probable therapeutic target(s) for given compounds. This allows us to identify the appropriate targets according to the structure of the ligands (molecules).

ADME(T) properties represent a challenge in the discovery of new therapeutic compounds and is very important in drug design. It is why we try to find and predict therapeutic molecules with a good ADME(T) profile. This prediction is done at the first stage by in silico techniques.

Outline:

1. Introduction to Computed-Aided Drug Design.

2. Molecular recognition.

3. Estimation of ADME(T) properties.

4. Molecular similarity.

5. Predict biological activity and Target prediction (PASS online and Swiss Target Prediction).

6. Introduction to molecular docking: validation of docking process, blind docking and cross docking.

Workshop 1: Molecular Docking protocol

a. Introduction to Validation of Docking protocol (process).

b. Blind Docking.

c. Cross Docking.

d. Analysing results: 2D and 3D analysis

Workshop 2 : In silico prediction of ADME(T) and biological activity

a) In silico predict the biological activity and Target prediction (PASS online and Swiss Target Prediction).

b) In silico prediction of ADME(T) properties: interpreting results and discrimination of bad profile molecules.

c) Molecular similarity search for new compounds and for virtual screening.