Presented by: VIKAS SONI Management Scholar, Pharmaceutical Management. NIPER, Mohali, Punjab, India. GMAIL: Vikas.niper2014@gmail.com LINKEDIN: http://in.linkedin.com/in/vikassoni11/ FACEBOOK: https://www.facebook.com/Vickysoni11

1. Hit identification
Lead optimization
Bioremediation
1. Search algorithm
2. Scoring function
The world’s major pharmaceutical and biotechnology companies use
computational design tools. Although no single drug has been designed solely by
computer techniques, the contribution of these methods to drug discovery is no
longer a matter of dispute. The theoretical calculations permit the computation
of binding free energies and other relevant molecular properties. By these
methods time, money and labor can be saved easily.
because it is less time consuming.
because it is easily adoptable.
because it is cost and labor saving.
because is it more accurate and data based.
Hence most companies are now using these
techniques.
VIRTUAL SCREENING
Virtual screening firmly established
itself as a powerful technique in drug
discovery efforts, particularly in lead
discovery as well as lead optimization.
It deals with the quick search of large
libraries of chemical structures in order
to identify those structures which are
most likely to bind to a drug target,
typically a protein receptor or enzyme,
The aim of virtual screening is to
identify molecules of novel chemical
structure that bind to the
macromolecular target of interest.
QSAR
A QSAR is a mathematical relationship between a biological activity of a
molecular system and its geometric and chemical characteristics
ADVANTAGES
Trial and error synthesis methods are expensive and time consuming.
Biological screenings of synthesized compounds are too costly, time-consuming,
sacrifice of animals, or compounds in their pure forms.
MMOOLLEECCUULLAARR DDOOCCKKIINNGG
Predicts the preferred orientation of one
molecule to a second when bound to each other
to form a stable complex.
It is a typical energy consideration of and
association.
Shows binding affinity between two molecules.
Used to predict the strength of association.
It consider the energy of final complex of drug
and receptor.
CADD and bioinformatics together are a powerful combination in drug
research and development.
An important challenge for us going forward is finding skilled, experienced
people to manage all the bioinformatics tools available to us, which will be a
topic for a future article.
Virtual screening, lead optimization and predictions of bioavailability and
bioactivity can help guide experimental research.
The predictive power of CADD can help drug research programs choose
only the most promising drug candidates.
Computer-aided drug design is no longer
merely a promising technique. But it is a
practical and realistic way of helping the
medicinal chemist.
With today’s computational resources,
several million compounds can be screened
in a few days on sufficiently large clustered
computers .
Pursuing a handful of promising leads
for further development can save
researchers considerable time and expense.
The predictive power of CADD can help
drug research programs choose only the
most promising drug candidates.
1. Beale J. M., Jr. Wilson C. O.; Wilson and Gisvold's Textbook of Organic
Medicinal and Pharmaceutical Chemistry, 12th edition,2011; Wolters Kluwer
Health/Lippincott Williams & Wilkins: Philadelphia, PA: 17-40.
2. Ghose AK, Viswanadhan VN, Wendoloski JJ. A knowledge-based approach in
designing combinatorial or medicinal chemistry libraries for drug discovery: Part
1. A qualitative and quantitative characterization of known drug databases.
JCombChem 1999;1:55–68.
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REFERENCE
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Drug Design
Lead
Optimization
Modeling &
Design
Compound
Synthesis
Lead
Compound
Crystallography
Biological
testing
Target
Identification