Grid Drug Discovery by DrBib

8/14/2019 Grid Drug Discovery by DrBib

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Biosciences WG, PRAGMA 12, March 2007

RUG DISCOVERY & GRID COMPUTINGRUG DISCOVERY & GRID COMPUTING

Habibah A Wahab, PhD

School of Pharmaceutical Sciences,

Universiti Sains Malaysia


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Opportunity For Computer Scientistin Pharma Industries

Ranks among the fastest growing manufacturing industries.

More than 6 out of 10 workers have a bachelors, masters,professional, or Ph.D. degreetwice the proportion for allindustries combined.

Fifty-nine percent of all jobs are in large establishmentsemploying more than 500 workers.

Earnings are much higher than in other manufacturingindustries.

Provided 291,000 wage and salary jobs in 2004.

Nearly 60 percent of this industrys jobs in 2004 were inestablishments that employed more than 500 workers.


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Outlook for computer scientistsin pharmaceutical industries

Computer specialists such assystems analysts, biostatisticians,and computer support specialists

also will be in demand as disciplinessuch as biology, chemistry, andelectronics continue to converge andbecome more interdisciplinary,creating demand in rapidly emergingfields such as bioinformatics andnanotechnology.


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DRUG DISCOVERY

PostClinical

ClinicalSafety&Efficacy

PreClinicalLeadOptimisation

LeadIdentification

TargetValidation

Disease /TargetIdentification

Lengthy and expensive:

10 15 Years; USD 800 1 billion

Out of 5000 medicine tested, 5 reach clinical trial (PharmaceuticalResearch & Manufacturer of America)

Out of 5, 1 reach market (Tufts Center of Research on DrugDevelopment)

Delay can cost $4-5 million/day.

Multidisciplinary Efforts involving individuals, partnerships,corporations, government agencies, manufacturer, scientific

institutions.

Big Pharma/ Outsource to Small

Companies

Big Pharma

Discovery Phase Preclinical PhaseClinical PhasePost-clinicalPhase


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Source of Drugs

Drugs are derived from the following two main

sources: Natural Product: From plant parts or products. Seeds, stem, roots, leaves, resin, and

other parts yield these drugs. Examples, salicylic acid, digitalis,vincristine and opium.

From animal sources: Glandular products from animals are used,

such as insulin and thyroid. Marine organisms:

Microorganisms: Penicillin, erythromycin

Mineral sources: Some drugs are prepared from minerals, forexample, potassium, chloride, and lithium carbonate (anantipsychotic).

Synthetic sources: Frequently this can eliminate side effects and increase the potency

of the drug. Examples include barbiturates, sulfonamides, andaspirin.


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Virtual Screening to Find Hit/Lead


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Virtual Screening

Usually employ docking computationas it gives detailed representation ofbinding site



Target

IdentificationTarget

Validation

Lead

Identification

Lead

Optimization

Target discovery Lead discovery

Phases of a pharmaceutical development

Pre- & ClinicalPhases (I-III)

vHTS

Similarity

analysis

Database

filtering

Computer Aided

Drug Design(CADD)

de novo

design

diversity

selection

Biophores

Alignment

Combinatorial

libraries

ADMET

QSAR

Molecular Docking: Predict how small molecules, such as

substrates or drug candidates, bind to a receptor of known 3Dstructure



NaPIMM

Natural Product Information and MolecularModelling (NaPIMM) Portal



INTRODUCING NAPIMm

COMPUTATIONAL PLATFORM Grid enabled molecular modelling platform

Automatic docking & reverse docking server

MD simulation server Protein-structure prediction server

DATABASE SYSTEM: NADI

NADI-CHEM

MNATCHEM

NADI-RA

NADI-HERBS



NaDI: Features

COPYRIGHTED DATABASE SYSTEM

Comprehensive 3D chemical structureDatabase of natural products Inclusive of chemical properties and biological

activities references

2D structures

3D structures ready for in silico drug screening

Drug Receptor Database

provide drug receptor and disease information. 3D structure of drug target

Herbal Monographs Comprehensive description about traditional

uses of Malaysian and Chinese medicinalplants



WHY NaPIMM ?

Malaysia has 12,000 flowering species

plants (10% already known for medicinalvalues).

Analysis of compounds isolated fromnatural products showed that most ofthem are not available in chemicaldatabase.

Research experience in molecular

modelling of natural products on : Xanthine oxidase

protein tyrosine kinase receptor.

Dihydrofolate reductase, etc.

DOCK AROUND THE CLOCK REPEATINGLY DOING THE SAME THING



DRUG DISCOVERY USING NAPIMM

in silico

studies

Molecular Modelling

(Physical (non-real/simplified) system that

mimics biological/chemical system)

Database

Content

Development

(Receptor

&

Small Molecule

Database

Design

(Receptor

&

Small Molecule

Bioinformatics

Enzyme

Inhibition

(in vitro

assay)

Validation



Docking Workflow in NAPIMm

2 D Structure(ligand)

3 D Structure(Target &

Ligand)

literature(Target & Ligand)

AutoDockGPF & DPFsetup

Grid &Docking

Ranking

Optimised3 D Structure &Partial charge

assignment

In NADI DATABASES

AUTOMATED, GENERATED WITHINMMSERVER



Source of datasets

Available database; usually knownchemicals Commercial, Daylight, Cambridge CSD, MDL

etc Public domain e.g. ZINC, NCI, PubChem

Totally virtual compounds generated bycomputers (either has existed or yet to be

existed). Or build one yourself; perhaps a dedicated

one like natural product database



Natural Products: Facts

Plants Extracts Fractions Chemicals

H3

NNH

2

NH2

OSO3

H

H

OH

squalamine

NH O

O

OH

CH3

Jaspine A

Jaspine B

NH2 OH

O CH3

OCH3

CH3

OH

OO

CH3

CH3 CH3

CH3CH

3

OAc

Norcarotenoid



Natural Products: Drug Source



Natural Products: Drug Source

65% drugs exist today originally derived fromnatural sources.

E.g. digitalis, aspirin and paclitaxel (Taxol)

natural products are biologically validatedstarting points for library design.

Synthesised/modified by proteins highly likely tobind to proteins having similar folds.



Hawk server

Malaysia

(hawk.usm.my)

User User

AccessHawk,

login&uploadligandinputfileAc

cess

Hawk

,login

&uploa

dligand

inputfi

le

Process ligand input file, create parameter

files & shell script files

Cluster C

Cluster B Cluster A

Submit input files and distribute jobs toseveral clusters on Grid environment

Cluster D

ViewordownloadresultVie

wor

down

loadr

esult

Receive input files from Hawk andrun jobs on each assigned nodes

Receive

inputfil

esfrom

Hawk

andrun

docking

jobs

oneac

hassign

edno

des

Receiveinputfilesfrom

Hawkand

rundockingjobsoneachassigned

nodes

Receiveinputfiles

fromH

awkandrun

docking

jobsoneach

assig

nednodes

Grid environment

Outpu

tfiles

gene

ratedan

d

uploa

dedt

oHawk

Output files generated and

uploaded to Hawk Outputfilesge

neratedand

upload

edtoHaw

k

Outputfilesgenerated

anduplo

adedtoHawk

Input files



NaPIMM CASE STUDY

Screening of flavonoids on Dengue-2Protease



Dengue

Dengue is a serious infectious disease that is endemic in over 100countries.

An estimated of 50 million infection per year globally with morethan 2.5 billion people are at risk for epidemic transmission.

Major affected regions are the south-east Asia and the westernPacific (increasing reports of this disease in the Americas).

Caused by the dengue virus which is a member of the Flaviviridae.

Spread by the highly domesticatedAedes aegypti mosquito.

Dengue can be classified into: Dengue Fever (DF)

a flu-like illness with symptoms like fever, headaches, joint aches andrashes

Dengue Haemorrhagic Fever (DHF). more severe and often fatal complication of DF as a result of the dengue

shock syndrome (DSS).

To date, no licensed vaccine or therapeutic drug available for DFand DHF/DSS, although there have been reports of some vaccinecandidates in clinical trials.

The treatment for DF and DHF/DSS has only been supportive thusfar.


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Flavonoids

Flavonoids belong to a class of chemicalcompounds that are ubiquitous in thevegetable kingdom with about 6000structures of flavonoids are known.

Among the most widely studied flavonoidsis quercetin (Fig. 1) which is presentwidely in vegetables and fruits, with adaily intake of up to 25 mg/day in anormal human diet.

Most flavonoids are known to be apowerful antioxidant that can scavengethe reactive oxidative species and apotent chemopreventive agent.

Now, we would like to see whether it has

anti-dengue activity

O

OH

OH

OH

OOH

OH

The chemical structure of quercetin


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Screening of flavonoids on Dengue-2 Protease


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B. rotunda (1)

B. rotunda (2)

B. rotunda (3)


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WHATS NEXT

We are very interested to further develop AMEXg,MMServer on GridSphere

Further develop NAPIMm so that it fully utiliseGrid Computing current test only involve 4

PRAGMA sites. To incorporate Quantum Chemical Calculation

and Cheminformatics application within NAPIMm

Use NAPIMm for PRAGMA real science project

Have PRIUS students in USM to help us achievingabove.

Sipadan Island, Sabah, Malaysia


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p , , y

I would like to thank all system administrators within PRAGMAcommunity especially:

Nguyen Viet Han dr Vietnam, IOIT

Eduardo Murrieta Len, Mexico, malicia cluster

Yusuke Tanimura, Japan, AISTX cluster


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Acknowledgement

Academic Collaborators Dr. Nornisah Mohamed Dr. Rashidah Abdul Rahim Professor Noorsaadah Abdul

Rahman

Professor Nazalan Najimudin Dr. Razip Samian Dr. Chan Huah Yong

Professor Janez Mavri

Professor Tom Scior Dr. Stephen Doughty Dr. Andre Aubry Dr. Regis Venderesse Dr. Bridget Jamart

Postgraduates: Belal O Najjar (MSc Candidate) Nur Hanani Che Mat

Choong Yee Siew

Choy Sy Bing Ezatul Ezleen Kamarulzaman Imtiaz Khalid Ismail Mohd Shah Nurul Bahiyyah Ahmad Khairudin Yam Wai Keat

Suriyati Muhamad

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