Computer-Aided Drug

Designing (CADD)

Aakshay Subramaniam

Aniketh Rao

Bioinformatics

oAn application of Computer Science to biological and Drug Development science

oBioinformatics is the field of science in which biology, computer science, and information technology merge to form a single discipline

oThe ultimate goal of the field is to enable the discovery of new biological insights

Classification

Computer-Aided Drug Designing (CADD)

oComputer-Aided Drug Designing (CADD) is a

specialized discipline that uses computational

methods to simulate drug-receptor interactions

oCADD methods are heavily dependent on

bioinformatics tools, applications and databases

R&D spending up, new drugs down

Drug Discovery & Development

Identify disease

Isolate protein

involved in

disease (2-5 years)

Find a drug effective

against disease protein

(2-5 years)

Preclinical testing

(1-3 years)

Formulation &

Scale-up

Human clinical trials

(2-10 years)

FDA approval

(2-3 years)

Bioinformatics Supports

CADD Research

Virtual High-Throughput Screening (vHTS)

Sequence Analysis

Homology Modeling

Similarity Searches

Drug Lead Optimization

Physicochemical Modeling

Drug Bioavailability and Bioactivity

Virtual High-Throughput Screening (vHTS)

oThe protein targets are screened against databases of small-molecule compounds

oWith today’s computational resources, several million compounds can be screened in a few days on sufficiently large clustered computers

oThis method provides a handful of promising leads

e.g. ZINC is a good example of a vHTS compound library

Sequence Analysis

o It is very useful to determine how similar or dissimilar the organisms are based on gene or protein sequences

oWith this information one can infer the evolutionary relationships of the organisms

oThere are many bioinformatic sequence analysis tools that can be used to determine the level of sequence similarity

e.g. DNA sequence analysis, gel electrophoresis

Homology Modeling

oA common challenge in CADD research is determining the

3-D structure of proteins

oThe 3-D structure for only a small fraction of the proteins is

known

oBioinformatics software tools are then used to predict the 3-D

structure of the target based on the known 3-D structures of

the templates

oE.g. MODELLER

SWISS-MODEL Repository

Similarity Searcheso A common activity in biopharmaceutical companies is the

search for drug analogues

o Starting with a promising drug molecule, one can search for chemical compounds with similar structure or properties to a known compound

o A variety of bioinformatic tools and search engines are available for this work

Benefits of CADD

oThe Tufts Report suggests that the cost of drug discovery and development has reached $800 million for each drug successfully brought to market

oMany biopharmaceutical companies now use computational methods and bioinformatics tools to reduce this cost burden

Benefits of CADDoVirtual screening, lead optimization and predictions of

bioavailability and bioactivity can help guide experimental

research

oOnly the most promising experimental lines of inquiry can be

followed and experimental dead-ends can be avoided early

based on the results of CADD simulations

Benefits of CADDTime-to-Market:

oCADD has predictive power

o It focuses drug research on specific lead candidates and avoids potential “dead-end” compounds

Benefits of CADDInsight:

oCADD provides a deep insight to the drug-receptor interactions acquired by the researchers

oMolecular models of drug compounds can reveal intricate, atomic scale binding properties that are difficult to envision in any other way

The Thalidomide Tragedy

Structure of Thalidomide

Structure of Penicillin

Penicillin G Penicillin V

NafcillinMethicillin

Identify disease

Isolate protein

Find drug

Preclinical testing

GENOMICS, PROTEOMICS & BIOPHARM.

HIGH THROUGHPUT SCREENING

MOLECULAR MODELING

VIRTUAL SCREENING

COMBINATORIAL CHEMISTRY

IN-VITRO & IN-SILICO ADME MODELS

Potentially producing many more targets

and “personalized” targets

Screening up to 100,000 compounds a

day for activity against a target protein

Using a computer to

predict activity

Rapidly producing vast numbers

of compounds

Computer graphics & models help improve activity

Tissue and computer models begin to replace animal testing

CADD and bioinformatics together are

a powerful combination in drug

research and development.

Research AchievementsoSoftware developed

oBioinformatics database developed

Softwares developedoSVMProt: Protein function prediction software

http://jing.cz3.nus.edu.sg/cgi-bin/svmprot.cgi

o INVDOCK: Drug target prediction software

oMoViES: Molecular vibrations evaluation server

http://ang.cz3.nus.edu.sg/cgi-bin/prog/norm.pl

Bioinformatics databases developedoTherapeutic target database

http://xin.cz3.nus.edu.sg/group/cjttd/ttd.asp

o Drug adverse reaction target databasehttp://xin.cz3.nus.edu.sg/group/drt/dart.asp

o Drug ADME associated protein databasehttp://xin.cz3.nus.edu.sg/group/admeap/admeap.asp

o Kinetic data of bio molecular interactions databasehttp://xin.cz3.nus.edu.sg/group/kdbi.asp

oComputed ligand binding energy databasehttp://xin.cz3.nus.edu.sg/group/CLiBE/CLiBE.asp