Structural Bioinformatics in Drug Discovery Melissa Passino

Structural Bioinformatics in Drug Discovery

Melissa Passino

Structural BioinformaticsStructural Bioinformatics

• What is SBI?“Structural bioinformatics is a subset of bioinformatics concerned with the use of biological structures – proteins, DNA, RNA, ligands etc. and complexes thereof to further our understanding of biological systems.”

http://biology.sdsc.edu/strucb.html

SBI in Drug Design and DiscoverySBI in Drug Design and Discovery

• SBI can be used to examine:• drug targets (usually proteins)• binding of ligands

↓

“rational” drug design

(benefits = saved time and $$$)

Traditional Methods of Drug DiscoveryTraditional Methods of Drug Discovery

natural (plant-derived)

treatment for illness/ailments

↓

isolation of active

compound(small, organic)

synthesisof compound

↓

manipulation of structure to get

better drug(greater efficacy, fewer side effects)Aspirin

Modern Methods of Drug DiscoveryModern Methods of Drug Discovery

What’s different?

• Drug discovery process begins with a disease (rather than a treatment)

• Use disease model to pinpoint relevant genetic/biological components (i.e. possible drug targets)

Modern Drug DiscoveryModern Drug Discovery

disease → genetic/biological target

↓

discovery of a “lead” molecule- design assay to

measure function of target- use assay to look for

modulators of target’s function

↓high throughput screen (HTS)

- to identify “hits” (compounds with binding in low nM to low μM range)

Modern Drug DiscoveryModern Drug Discovery

small molecule hits↓

manipulate structure to increase potency i.e. decrease Ki to low nM affinity

↓

*optimization of lead molecule into candidate drug*

fulfillment of required pharmacological properties:potency, absorption, bioavailability, metabolism, safety

↓

clinical trials

Interesting facts...Interesting facts...

• Over 90% of drugs entering clinical trials fail to make it to market

• The average cost to bring a new drug to market is estimated at $770 million

Impact of Structural BioinformaticsImpact of Structural Bioinformatics on Drug Discovery on Drug Discovery

• Speeds up key steps in DD process by combining aspects of bioinformatics, structural biology, and structure-based drug design

Bio-informatics

Structure-based Drug Design

Structural Biology

Fig 1 & 2

Fauman et al.

Identifying Targets: Identifying Targets: The “Druggable Genome”The “Druggable Genome”

human genome

polysaccharides

lipids nucleic acids proteins

Problems with toxicity, specificity, and difficulty in creating potent inhibitors

eliminate the first 3 categories...

human genome

polysaccharides

lipids nucleic acids proteins

proteins with binding site

“druggable genome” = subset of genes which express proteins capable of binding small drug-like molecules

Relating druggable targets Relating druggable targets to disease...to disease...

GPCR

STY kinases

Zinc peptidases

Serine proteases

PDE

Other 110 families

Cys proteases

Gated ion-channel Ion channels

Nuclear receptor

P450 enzymes

Analysis of pharm industry reveals:

• Over 400 proteins used as drug targets

• Sequence analysis of these proteins shows that most targets fall within a few major gene families (GPCRs, kinases, proteases and peptidases)

Fig. 3, Fauman et al.

Assessing Target DruggabilityAssessing Target Druggability

• Once a target is defined for your disease of interest, SBI can help answer the question:

Is this a “druggable” target?

• Does it have sequence/domains similar to known targets?

• Does the target have a site where a drug can bind, and with appropriate affinity?

Other roles for SBI in drug discoveryOther roles for SBI in drug discovery

• Binding pocket modeling

• Lead identification• Similarity with known

proteins or ligands

• Chemical library design / combinatorial chemistry

• Virtual screening

• *Lead optimization*• Binding• ADMET

SBI in cancer therapy:SBI in cancer therapy:MMPIsMMPIs

• Inability to control metastasis is the leading cause of death in patients with cancer (Zucker et al. Oncogene. 2000, 19, 6642-6650.)

• Matrix metalloproteinase inhibitors (MMPIs) are a newer class of cancer therapeutics

• can prevent metastasis (but not cytotoxic); may also play role in blocking tumor angiogenesis (growth inhibition)

• Used to treat “major” cancers: lung, GI, prostate

What is an MMP?What is an MMP?

• Family of over 20 structurally related proteinases

• Principal substrates:• protein components of extracellular matrix

(collagen, fibronectin, laminin, proteoglycan core protein)

• Functions:• Breakdown of connective tissue; tissue

remodeling

• Role in cancer:• Increased levels/activity of MMPs in area

surrounding tumor

Brown PD. Breast Cancer Res Treat 1998, 52, 125-136.

Whittaker et al. Chem. Rev. 1999, 99, 2735-2776

MMP-1,3,8

MMP-2

MMP-7

MMP-9

MMP-10 to 13,19,20

MMP-14

to 17Whittaker et al. Chem. Rev. 1999, 99, 2735-

2776

Whittaker et al. Chem. Rev. 1999, 99, 2735-

2776

“metallo” in MMP = zinc

→ catalytic domain contains 2 zinc atoms

MMP catalysisMMP catalysis

Peptidic inhibitorsPeptidic inhibitors

• Structure based design – based on natural

substrate collagen– zinc binding group

• Poor Ki values, not very selective (inhibit other MPs)

Brown PD. Breast Cancer Res Treat 1998, 52, 125-136.

Peptidic hydroxamate inhibitorsPeptidic hydroxamate inhibitors

• Specificity for MMPs over other MPs

• Better binding (low nM Ki)

• But poor oral bioavailability

A (not very) long time ago, in a town (not too) far

away……lived a company named Agouron…

…and this company had a dream, a

dream to design a nonpeptidic

hydroxamate inhibitor of MMPs…

...so they made some special crystals…

used x-ray crystallography/3D

structure of recombinant human

MMPs bound to various inhibitors

↓to determine key a.a.

residues, ligand substituents needed

for binding Gelatinase A

http://www.rcsb.org/pdb/

…and used the magic of structural bioinformatics to design many, many

nonpeptidic hydroxylates.

oral bioavailabityK i

anti-growth

anti-metastasis

repeat…

Results…Results…

AG3340 “Prinomastat”

• Good oral bioavailability

• Selective for specific MMPs – may implicate their

roles in certain cancers

PrinomastatPrinomastat

• Evidence showing prevention of lung cancer metastasis in rat and mice models

• Clinical trials

→ non small cell lung cancer

→ hormone refractory prostate cancer…stopped at Phase 3 (Aug 2000) because did not show effects against late stage metastasis

Morals of the story…Morals of the story…

• SBI can be used as basis for lead discovery and optimization

• MMPs are good targets for chemotherapy to help control metastasis…

…but MMPIs must be combined with other cytotoxic drugs to get maximum benefits, and used at earliest stage possible