Unit-IV Computer Aided Drug Design (CADD)
Part-1 Introduction to molecular docking, rigid docking, flexible docking
Docking: Docking is an attempt to find best match between two molecules
Docking is a method which predicts preferred orientation of one ligand when bound to an active
site to form stable complex. It takes decades to create new drug via conventional wet chemical
process. Therefore computational docking is done to cut down cost and research time line.
Molecular docking:
Molecular docking is a kind of computational modelling of the complexes, which is formed from
the interaction of two or more molecules. It predicts the three-dimensional structure of adducts,
based upon binding properties of participating ligand and target molecules. Molecular docking
generates different possible candidate structures, which are ranked and grouped together using
scoring function in the software of molecular docking tool. Docking simulations predict
optimized docked conformer based upon total energy of the system.
Introduction:
Molecular docking is a kind of computational modelling, which facilitates the prediction of
preferred binding orientation of one molecule (eg. ligand) to another (eg. Receptor), when both
interact each other in order to form a stable complex. Information gained from the preferred
orientation of bound molecules may be employed to predict the energy profiling (such as binding
free energy), strength and stability (like binding affinity and binding constant) of complexes.
This can be done using scoring function of molecular docking. Now days, molecular docking is
often utilized to forecast the binding orientation of small molecules (drug candidates) to their
biomolecular target (such as protein, carbohydrate and nucleic acid) with the aim to determine
their tentative binding parameters. This establishes raw data for the rational drug designing
, (structure-based-drug development) of new agents with better efficacy and more specificity. The
main objective of molecular docking is to attain an optimized docked conformer of both the
interacting molecules in furtherance of achieving lessen free energy of the whole system. Final
predicted binding free energy (∆G) is modelled in terms of dispersion & repulsion (∆Gvdwbind),
hydrogen bond (∆G), desolvation (∆Gdesolv), electrostatic (∆G), torsional free energy(∆Gtor),
final total internal energy (∆Gelec) and unbound system’s energy (∆Gunbtotal). Therefore,
detailed understanding of the general principles that govern predicted binding free energy (∆G)
provides auxiliary information about the nature of various kinds of interactions driving the
docking of molecules.
Practical application of molecular
docking requires structural data bank for the search of target of interest and a methodology to
evaluate ligand. To accomplish this, there are various molecular docking tools and
methodologies are available. These computational tools provide the hierarchy to potential
ligands based upon their ability to interact with given target candidates. Molecular docking of
small molecules to a biological target includes an imaginative sampling of possible poses of the
ligand in the specified groove or pocket of target candidate in an order to establish the optimal
binding geometry. This can be performed using user defined fitness or scoring function of
docking software. However, X-ray crystallography and Nuclear Magnetic Resonance (NMR)
spectroscopy are the primary techniques for the investigation and establishment of three
dimensional structure data for biomolecular targets. Nevertheless, homology modeling facilitates
the determination of tentative structure of those proteins (of unknown structure) having high
sequence homology to known structure. This presents a substitute approach for target structure
establishment, which forms an initiation point for in silico discovery of high affinity drug
candidates. There are various databases available, which offer information on small ligand
molecules such as CSD (Cambridge Structural Database), ACD (Available Chemical Directory),
MDDR (MDL Drug Data Report) and NCI (National Cancer Institute Database). While
Part-1 Introduction to molecular docking, rigid docking, flexible docking
Docking: Docking is an attempt to find best match between two molecules
Docking is a method which predicts preferred orientation of one ligand when bound to an active
site to form stable complex. It takes decades to create new drug via conventional wet chemical
process. Therefore computational docking is done to cut down cost and research time line.
Molecular docking:
Molecular docking is a kind of computational modelling of the complexes, which is formed from
the interaction of two or more molecules. It predicts the three-dimensional structure of adducts,
based upon binding properties of participating ligand and target molecules. Molecular docking
generates different possible candidate structures, which are ranked and grouped together using
scoring function in the software of molecular docking tool. Docking simulations predict
optimized docked conformer based upon total energy of the system.
Introduction:
Molecular docking is a kind of computational modelling, which facilitates the prediction of
preferred binding orientation of one molecule (eg. ligand) to another (eg. Receptor), when both
interact each other in order to form a stable complex. Information gained from the preferred
orientation of bound molecules may be employed to predict the energy profiling (such as binding
free energy), strength and stability (like binding affinity and binding constant) of complexes.
This can be done using scoring function of molecular docking. Now days, molecular docking is
often utilized to forecast the binding orientation of small molecules (drug candidates) to their
biomolecular target (such as protein, carbohydrate and nucleic acid) with the aim to determine
their tentative binding parameters. This establishes raw data for the rational drug designing
, (structure-based-drug development) of new agents with better efficacy and more specificity. The
main objective of molecular docking is to attain an optimized docked conformer of both the
interacting molecules in furtherance of achieving lessen free energy of the whole system. Final
predicted binding free energy (∆G) is modelled in terms of dispersion & repulsion (∆Gvdwbind),
hydrogen bond (∆G), desolvation (∆Gdesolv), electrostatic (∆G), torsional free energy(∆Gtor),
final total internal energy (∆Gelec) and unbound system’s energy (∆Gunbtotal). Therefore,
detailed understanding of the general principles that govern predicted binding free energy (∆G)
provides auxiliary information about the nature of various kinds of interactions driving the
docking of molecules.
Practical application of molecular
docking requires structural data bank for the search of target of interest and a methodology to
evaluate ligand. To accomplish this, there are various molecular docking tools and
methodologies are available. These computational tools provide the hierarchy to potential
ligands based upon their ability to interact with given target candidates. Molecular docking of
small molecules to a biological target includes an imaginative sampling of possible poses of the
ligand in the specified groove or pocket of target candidate in an order to establish the optimal
binding geometry. This can be performed using user defined fitness or scoring function of
docking software. However, X-ray crystallography and Nuclear Magnetic Resonance (NMR)
spectroscopy are the primary techniques for the investigation and establishment of three
dimensional structure data for biomolecular targets. Nevertheless, homology modeling facilitates
the determination of tentative structure of those proteins (of unknown structure) having high
sequence homology to known structure. This presents a substitute approach for target structure
establishment, which forms an initiation point for in silico discovery of high affinity drug
candidates. There are various databases available, which offer information on small ligand
molecules such as CSD (Cambridge Structural Database), ACD (Available Chemical Directory),
MDDR (MDL Drug Data Report) and NCI (National Cancer Institute Database). While
