• Major advances in medicine from apparently unrelated discoveries:

X-rays, antibiotics, nonivasive imaging, genetic engineering

The importance of basic science

Wilhelm Roentgen

X-rays

Alexander Fleming Howard Florey Ernst Chain

Penicillin

• Major advances in medicine from apparently unrelated discoveries:

X-rays, antibiotics, nonivasive imaging, genetic engineering

• The pursuit of knowledge for its own sake

• Solve problems indirectly

The importance of basic science

Do not:

• Define specific areas or priorities – let the best ideas win

• Judge proposals on details

Do:

• Fund individual investigators, directly, based on merits of proposals

• Review and re-review

• Play the odds - the law of large numbers

Support for discovery

Confidential and Proprietary

Henry Moore, Two FormsPynkado wood, 1934

Metropolitan Museum of Art, New York© MMA, N.Y.

Drug design: Designing a ligand to fit into a protein and interfere with function

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Industrial Drug Development

High throughput screening

Long and elaborate Hit-to-Lead process

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If we did a space launch the way we design drugs we would:

•Shoot 100 rockets to the Moon in hope of landing one.

•Shoot another 500 rockets to get one to Mars.

•Each new satellite would have to be very similar to a previous one.

Confidential and Proprietary

This is one of the reasons for Pharmaceutical industry’s

troubles.

Money spent on R&DApproved Drugs

T.T. Ashburn and K.B. Thor, Nature Rev. Drug Discov. 3, 673-683 (2004)

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Crystallography -> Design -> Synthesis -> Evaluation -> Crystallography -> …

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Why can’t theory help?

The underlying physical laws necessary for the mathematical theory of a large part of physics and the whole of chemistry are thus completely known, and the difficulty is only that the exact application of these laws leads to equations much too complicated to be soluble.

P. A. M. Dirac, Proc. R. Soc. London 123, 714 (1929)

• This is no longer true, computers can solve the equations. Given 10^12 years.

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Current force-fields are too simple

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Current force-fields are parametrized depending on application: not extensible

• Do not respond to environment• Parameters change with different

applications: a sign of an incomplete model

• Polarizability fundamentally impossible

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Polarization is crucial in drug design

QUANTUM MECHANICAL POLARIZABLEFORCE FIELD (QMPFF)

• All major current force fields including AMBER and Merck Molecular Force Field (MMFF) are based on similar principles that date back decades ago

• QMPFF is designed to be physically more realistic and therefore more accurate by fully integrating quantum physics – made possible by vast increases in computer speed to do necessary calculations

QMPFF CONCEPT

+1

+6

- 0.45

- 0.45

- 7.1

+1

+ 0.4

+ 0.4

- 0.8

Conventional Molecular Representation

QMPFF Molecular Representation

Point charges known to be physically unrealistic; no natural way to include important polarization energy term

H2O H2O

Charge clouds approximate quantum reality; polarization naturally introduced via shifting of electron clouds

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QMPFF technology captures the missing details

• Quantum Mechanical Polarizable Force Field (QMPFF)

• Polarizable force field models polar interactions (see below)

• Can model water, gas phase, ligand binding better than any existing computational tools using the same parameters.

+

Produced DipoleElectric Field

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Interacting entities are cloud-like, polarizable

• Parameterized from QM calculations.

• Polarizability is essential to modeling biological interactions.

• Electron clouds adjust during the simulation-> (real VdW).

O

H

+

H+

+-

-

-

InductionDispersionExchangeicsElectostateractionsbondedQMPFF EEEEEE int

WATER SIMULATIONS WITH QMPFF2

0.94

0.96

0.98

1.00

Den

sity

(g/

cm3)

-50 -25 0 25 50 75 100

Tem perature (ºC)

Q M PFF2 classic

Q M PFF2 quantum

Q M PFF2 quantum

experim ent

Q M PFF2

TIP5P

experim ent

QMPFF vs MMFF94 RING-STACKING OF BENZENE DIMER

2 3 4 5 63 4 5

R (Å)

-5-4-3-2-1012

kcal

/mol

Q M PFF2

M M FF94

Q M

QMPFF AND DRUG DESIGN• QMPFF via MD simulation can be applied

to calculate relative binding free energy (and therefore relative binding affinity) of two related ligands for a protein

• X-ray structure of protein is required, and structure of complex with representative ligand(s) is very helpful

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We mutate one ligand into another

• Thermodynamic integration• Each alchemical mutation requires

running a series of simulations. • Takes approximately 8 days per

calculation (10 cores). • Most suitable for lead and drug

optimization.

Mutation

d

HG

1

0

BINDING FREE ENERGY CALCULATIONS FOR 1TNH AND 2BZA IN TRYPSIN

1TNH

4-fluoro-benzyl-ammonium

2BZA

benzyl-ammonium

ΔΔG (kcal/mol)

QMPFF3 0.85 0.17

MMFF94 -0.4

Exper. 0.78

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Does it work?

• Ligand substitution pilot study (trypsin, thrombin and uPA inhibitor families).

• Nothing else can predict free energies accurately (see comparison to Merck results below)

QMPFF MMFF

Actu

al

Does it work?

Mea

sure

d

L

--------- Predicted

Reference compound

Does it work?Drug design – blind prediction

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Speed-accuracy tradeoffthe exception

Speed

Prec

isio

n

QM

Conventional Force Fields

Docking(Snapshot)

QMPFFNecessary accuracy

10^12 years 1 week 0.01 sec

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Impact on drug design

•Speeding up binding optimization•Difficult synthesis can be virtual•Scaling with available computers•Making best of class drugs

SOME APPLICATIONS OF QMPFF

• Hydrogen storage and fuel cells• Batteries• Optical materials • Catalysts