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Computational Tool for Drug Designing

Chhavi Jain

Abstract


Drug designing is very time and resource consuming process, requiring optimization of several parameters. Computer-aided drug designing plays a vital role in drug discovery and development and has become an important tool in the pharmaceutical industry. Here, the two basic methods of computer-aided drug designing, viz., structure-based computer-aided drug designing and ligand-based computer-aided drug designing technology are discussed.


Keywords: drug, drug designing, QSAR, structure-based, virtual screening

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Mandal S., Moudgil M., Mandal S.K.

Rational drug design, Eur J

Pharmacol. 2009; 625(1–3): 90–100p.

Sliwoski G., Kothiwale S., Meiler J., et

al. Computational methods in drug

discovery, Pharmacol Rev. 2013;

(1): 334–95p.

Kalyaanamoorthy S., Chen Y.P.

Structure-based drug design to

augment hit discovery, Drug Discov

Today. 2011; 16: 831–9p.

Jorgensen W.L. Drug discovery: pulled

from a protein’s embrace, Nature.

; 466: 42–3p.

Irwin J.J., Shoichet B.K. ZINC is a

free database of commerciallyavailable

compounds for virtual

screening. ZINC contains over 8

million purchasable compounds in

ready-to-dock, 3D formats, J Chem Inf

Model. 2005; 45: 177–82p.

Haraki K.S., Sheridan R.P.,

Venkataraghavan R., et al. Looking for

pharmacophores in 3-D databases:

does conformational searching

improve the yield of actives?

Tetrahedron Comput Methodol. 1990;

: 565–73p.

Blaney J.M., Dixon J.S. A good ligand

is bard to find: automated docking

methods, Perspect Drug Discov Des.

; 1: 301–19p.

Jones G., Willett P., Glen R.C., et al.

Development and validation of a

genetic algorithm for flexible docking,

J Mol Biol. 1997; 267: 727–48p.

Wang R., Liu L., Lai L., et al. SCORE:

a new empirical method for estimating

the binding affinity of a protein-ligand

complex, J Mol Model. 1998; 4: 379–

p.

Walters W.P., Stahl M.T., Murcko

M.A. Virtual screening: an overview,

Drug Discov Today. 1998; 3: 160–78p.

Leach A.R., Hann M.M. The in silica

world of virtual libraries, Drug Discov

Today. 2000; 5: 326–36p.

Lewis R.A., Pickett S.D., Clark D.E.

Computer-aided molecular diversity

analysis and combinatorial library

design, Rev Comput Chem. 2000; 16:

–51p.

Vyas V., Jain A., Jain A., et al. Virtual

screening: a fast tool for drug design.

Sci Pharm. 2008; 76: 333–60p.

Abagyan R., Totrov M. Highthroughput

docking for lead

generation, Curr Opin Chem Biol.

; 4: 375–82p.

Lipinski C.A., Lombardo F., Dominy

B.W., et al. Experimental and

computational approaches to estimate

solubility and permeability in drug

discovery and development settings,

Adv Drug Del Rev. 1997; 23: 3–25p.

Ghose A.K., Viswanadhan V.N.,

Wendoloski J.J. A knowledge-based

approach in designing combinatorial or

medicinal chemistry libraries for drug

discovery, J Combin Chem. 1999; 1:

–68p.

Johnson M.A., Maggiora G.M.

Concepts and Applications of

Molecular Similarity. New York:

Wiley; 1990.


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