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UK QSAR Symposium at Syngenta 'Rapid Physicochemical Profiling' Derek P. Reynolds. 25th April 2001. Physical Chemistry Team. Christopher Bevan, Alan Hill, Klara Valko, Pat McDonough. Chemical and Analytical Technologies Department, GlaxoWellcome R&D, Stevenage, UK.

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uk qsar symposium at syngenta rapid physicochemical profiling derek p reynolds

UK QSAR Symposium at Syngenta 'Rapid Physicochemical Profiling'Derek P. Reynolds

25th April 2001

physical chemistry team

Physical Chemistry Team

Christopher Bevan, Alan Hill, Klara Valko, Pat McDonough

Chemical and Analytical Technologies Department,

GlaxoWellcome R&D,

Stevenage, UK

turning hits and leads into new medicines
Turning Hits and Leads into New Medicines
  • GlaxoWellcome has funded a worldwide project to deliver high throughput screens for Physicochemical, Pharmacokinetic, Metabolic, and Toxicological Factors
  • OBJECTIVES:
    • High-throughput to screens support discovery projects
    • A large international repository of consistent data which can help us learn more about fundamental mechanisms regulating kinetics and toxicology
    • Construction of predictive models which aid the design of drugs
screens available
Screens Available
  • Physicochemical Screens
    • Lipophilicity (CHI)
    • Solubility
    • pKa
  • ADME
    • In-vitro metabolism (Liver Microsomes)
    • Permeation (MDCK)
    • In-vivo pharmacokinetics - (Cassette Dosing)
  • Genetox
    • SOS gene, umuC mutagenicity assay
  • Analysis Tools
    • Calculated properties
    • Modeling
slide5

The Physicochemical Properties of a Drug have an important influence on its Absorption and Distribution in-vivoPredictive models aid drug designhowevermodels are built on real data and novel compounds often need new rules!

slide7

Part 1 Experimental Methods for Measurement of Lipophilicity, pKa, and SolubilityPart 2Using Physicochemical Data to Understand Biological Data. An Example: Intestinal Absorption of Drugs

slide8

What is high-throughput ?

  • Is it:

high total numbers?

speed of measurement?

rapid response?

lower total cost?

lower cost per sample?

accurate?

flexible?

toolkit of high throughput methods for lipophilicity solubility and pka
‘Toolkit’ of High Throughput Methods for lipophilicity, solubility, and pKa
  • Standardised general methods suitable for libraries and large compound sets (deployed globally)
  • Rapid response ‘open-access’ versions for ‘immediate answers’ and project specific investigations
  • Automated versions of classical determinations e.g. octanol logD
  • Over 17,000 accurate determinations of lipophilicity, solubility, and pKa made by GW in the UK over the last 12 months
  • Some methods now developed are suitable for deployment alongside in-vitro biological screens
slide10

Fast Generic Gradient HPLC: The basis for high throughput characterisation, purification, and property determination of new compounds and libraries

For details see:

‘Separation Methods in Drug Synthesis and Purification’

Ed. KlaraValko, Elsevier, October 2000

Relevant Chapters:

  • Fast generic HPLC methods- I.M.Mutton
  • Coupled chromatography-mass spectrometry techniques for the analysis of combinatorial libraries- S.Lane
  • The development and industrial application of automated preparative HPLC- T.Underwood, R. Boughtflower and K.A. Brinded
  • Measurements of physical properties for drug design in industry- K. Valko
fast generic gradient hplc as a basis for physicochemical property measurement
Fast Generic Gradient HPLC as a basis for Physicochemical Property Measurement

Advantages:

  • Fast, accurate and automation friendly
  • Can analyse DMSO solutions directly
  • Tolerant of impure compounds
  • Compatible with MS for identity confirmation
options for lipophilicity measurement
Options for Lipophilicity Measurement
  • logD measurement by automation of the classical partition experiment. Solute concentration measured by gradient HPLC
  • HPLC retention time as a measure of lipophilicity
slide13

Octanol/Water LogP Determination

The aqueous phase can be sampled through the octanol phase without cross-contamination

Analysis:The samples and blanks are analysed using either an HP1050 or HP1100 HPLC system using a fast generic gradient.

slide14

Generic Gradient HPLC ( ‘Five minute CHI method’)

LunaC18(2) 50 x 4.6 mm; 2.00 ml/min; Mobile phase A 50 mM ammonium acetate pH 7.4 and B is 100% acetonitrile. Gradient: 0 - 2.5 min 0 - to 100% B; 2.5 - 2.7 min 100% B.

chi chromatographic hydrophobicity index a measurement for the pragmatist not the purist
CHI - Chromatographic Hydrophobicity IndexA measurement for the Pragmatist not the Purist !
  • CHI is an HPLC retention index derived from retention time in a gradient HPLC run and scaled using a set of standard compounds
  • Provided the same stationary phase and mobile phase are used, then CHI for a given compound should be a reproducible measure of lipophilicity (independent of equipment, operator, or laboratory)
  • CHI is essentially a solvent strength parameter (scaled to approximate to the % organic concentration in the mobile phase when logk=0)

CHI = f (logkwater, logkorganic)

Where: logkwater=retention factor extrapolated to pure water

logkorganic= retention factor extrapolated to 100% organic

slide16

General Solvation Equation

logSP = Solute Property, i.e., property of a series of solutes

in a given phase system, e.g., logP, logBBB,

logk, CHI, etc

logSP = c + e.E + s.S + a.A + b.B + v.Vx

  • Descriptors are specific to each molecule, where:
  • E = Excess Molar Refraction
  • S= Polarisability
  • A= Hydrogen Bond Acidity
  • B= Hydrogen Bond Basicity
  • Vx = McGowan Volume

The coefficients

c, e, s, a, b, and v

are specific to each

Solute Property

Equations are robust and apply to molecules in their unionized state. Correlation coeffs R > 0.90 for most processes

slide17

SOLVATION EQUATIONS FOR CHI

CHI = C+ v(e’ E+ s’ S+ a’ A+ b’ B+ Vx)

E - excess molar refraction term, normalised to alkanes

S- solute dipolarity/polarisability descriptor

A- solute hydrogen bond acidity descriptor

B- solute hydrogen bond basicity descriptor

Vx- McGowan characteristic volume

Equations are robust and apply to molecules in their unionised state. Correlation coeffs R > 0.95

slide18

Measurements of molecular descriptors via retention data from several diverse HPLC systems

  • We can set up solvation equations for various reversed-phase HPLC partition systems.
  • Knowing the regression constants for the HPLC systems, the molecular descriptors can be derived by iterative fitting from the retention data of the solute.
slide19

Selected HPLC systems

  • Luna C-18 column with acetonitrile gradient (CHIACN)

CHIACN = 7.1 + 0.41E - 1.06S - 1.59A - 4.88B + 4.8Vx

  • Luna C-18 column with trifluoroethanol gradient (CHITFE)

CHITFE = 6.9 + 0.67E - 1.96S - 3.1A - 3.94B + 5.67Vx

  • Polymer C-18 column with acetonitrile gradient (CHIPLRP)

CHIPLRP = 8.19 - 0.41E - 0.44S - 2.50A - 5.64B + 4.38Vx

  • DevelosilCN column with methanol gradient (CHICN-MeOH)

CHICN-MeOH = 3.93 + 0.79E - 1.05S - 0.72A - 4.5B - 5.42Vx

  • DevelosilCN column with acetonitrile gradient (CHICN-AcN)

CHICN-AcN = 5.67 + 0.2E - 0.28S - 0.55A - 4.15B + 3.68Vx

  • Fluorooctyl column with trifluoroethanol (CHIFO-TFE)

CHIFO-TFE = 7.45 - 0.12E - 0.57S - 3.67A - 1.89B + 3.11Vx

slide20

Lipophilicity and Solubility are pKa-dependent

  • Lipophilicity v pH profiles are needed to fully understand partition behaviour
  • pH cannot be properly controlled in the CHI experiment because of the organic modifier. Ionisation can be suppressed with buffer additives to give reliable CHIN values (I.e. CHI lipophilicity of the neutral form of the molecule)
  • A rapid method for pKa determination is needed to allow the computation of lipophilicity v pH profiles
gradient titration a faster way to measure pk a values
Gradient Titration: a faster way to measure pKa values
  • Prototype instrument developed by Alan Hill at GlaxoWellcome Research (Stevenage, UK)
  • Collaboration with Sirius from 1997 to develop instrument.
  • First Sirius commercial instrument now in routine use at Stevenage
  • The Team:

GlaxoWellcome: Alan Hill*, Chris Bevan*, Derek Reynolds*

Sirius: John Comer, Brett Hughes, Karl Box, Kin Tam, Roger Allen, Simon Thomson, Paul Hosking

*GT inventors; Patent applied for (WO99/13328)

a faster way to measure pk a values
A faster way to measure pKa values
  • The goal:
    • >96 samples per day
    • pKa measurement between pH3 and pH11
    • automatic dilution: samples in DMSO solution in microtitre plates
    • Easy to use and suitable for ‘open-access’ operation
  • A new instrument
    • Sirius Gradient Titrator for pKa measurement
    • Spectroscopic measurement technique
    • Commercial instrument launched 1Q 2000
slide24

Calibrating GT with standard compounds

Five standards. First derivative peak maxima correlated with pH-metric pKa values (25°C, I = 0.15M). Standards can be mixed for rapid calibration. Time (seconds) is proportional to pH.

Benzoic acid pKa 3.978

Phthalic acid pKa 4.843

Nitrophenol pKa 6.973

Chlorophenol pKa 9.240

Phenol pKa 9.796

what are suitable measurements for physicochemical screening
What are suitable measurements for physicochemical screening?
  • Lipophilicity and pKa are valuable for compound selection- but there are not usually any absolute pass/fail criteria
  • Lipophilicity is essentially a composite parameter which reflects the properties of both the polar surface and the hydrophobic surface of a molecule. Descriptors which are derived from several partition systems will be more likely to yield general QSAR relationships
  • Aqueous solubility depends on specific packing and intermolecular interactions in the solid as well as on the properties and ionisation state of the molecule in solution- For some drug targets (e.g. related to arachidonic acid cascade or fatty acid metabolism) then low solubility of leads may be a general issue that may require a solubility screen
options for solubility measurement
Options for Solubility Measurement
  • Solubility measurement by equilibration of solid sample with buffer. After filtration the solute concentration is measured by gradient HPLC. Sample preparation is rate limiting (20 per day)
  • Precipitation by dilution of concentrated DMSO solution. After filtration the solute concentration is measured by generic gradient HPLC. Can be automated (96 well plate per day)
  • Precipitation by dilution of concentrated DMSO solution. Detect appearance/disappearance of precipitate by nephelometry. The introduction of microtitre plate nephelometers makes this suitable for use by biochemical screening groups (Many plates per day)
solubility by laser nephelometry
Solubility by Laser Nephelometry

The laser nephelometer used is the NEPHELOstar (BMG LabTechnologies Offenburg, Germany). This instrument is a forward scattering Laser-Nephelometer employing a polarised laser diode that lases in the red at 635 nm. The Laser beam is passed through the well in a vertical and concentric path as shown below: Forward scattered light is measured beneath the well.

References:

1. C. D. Bevan, R. S. Lloyd, Anal. Chem. 72 (2000) 1781.

solubility by laser nephelometry28
Solubility by Laser Nephelometry

Procedure:

Compounds are supplied as 10 mM solutions in DMSO in 96 well microtitre plates. These are initially diluted 20 times with aqueous buffer to give a 5% DMSO/aqueous buffer solution. Then stepwise serial dilutions are made with 5% DMSO/aqueous buffer until precipitated compounds just redissolved. These dilutions are then monitored nephelometrically.

This technique is able to reproducibly detect turbidity in suspensions and distinguishes them from true solutions.

The method is non-destructive and simple and uses procedures very similar to those used for determination of dose response curves in biochemical assays. It is easy to integrate in a high throughput drug screening process.

slide29

AUTOMATING THE DETERMINATION OF AQUEOUS DRUG SOLUBILITY USING LASER NEPHELOMETRY IN MICROTITRE PLATES

David Proudlock*, Malcolm Willson, Barbara Carey, Glaxo Wellcome R&D Medicines Research Centre, Stevenage UK

Three pieces of equipment were required for plate handling, reagent addition and measurement. They were:Zymark Twister, Labsystem Multidrop, BMG Nephelostar

summary measurements that characterise the properties of molecules are now readily available
Summary: Measurements that characterise the properties of molecules are now readily available
  • Conventional measurements (octanol partition and solubility) can be automated to some degree
  • Rapid gradient HPLC retention times can be converted into a reliable index of lipophilicity (CHI)
  • HPLC at extremes of pH provide a convenient way to determine the lipophilicity of the unionised form of acids and bases (CHIN)
  • CHIN values from HPLC systems with different selectivity characteristics can be combined to determine molecular parameters that define solute polarity and H-bonding (S, A, B)
  • A new type of titration (gradient titration) provides rapid pKa measurement
  • Solubility can be rapidly estimated alongside biological screening by using a microtitre plate based nephelometer
  • Measured pKa values can be combined with single point solubility or lipophilicity determinations to calculate pH profiles
slide31
Part 2Using Physicochemical Data to Understand Biological Data. An Example: Intestinal Absorption of Drugs
what should we use physicochemical profiles for
What should we use physicochemical profiles for?
  • Comparison with calculated properties
  • Derivation of both general and project specific QSAR models
  • Selection of physico-chemically diverse molecules for biological investigation (in vitro and in-vivo)
  • To provide insight into the mechanisms of biological partition and in-vivo transport processes
slide33

What about ‘Biomimetic’ measurements? (e.g. Membrane affinity, Serum albumin binding, Cell Permeability) Do they predict in-vivo properties better than ‘classical’ measurements?(e.g. logP, solubility, pKa) Provide additional rather than alternative information

high throughput permeability screens
High-throughput permeability screens?
  • CACO2 (e.g Artursson et. al.)
  • MDCK
  • PAMPA (Kansy et. al., Hoffman-La Roche)
  • Alkane/Water membranes (Wohnsland and Faller, Novartis)

Simplistic interpretation of data can be misleading. All are potentially valuable when used systematically to help in the understanding of biologically relevant mechanisms of action.

predicting human oral absorption plot of human intestinal absorption v mdck cell permeability

120

100

80

60

HIA %

40

20

0

50

1

10

100

1000

MDCK Papp (nm/sec)

Predicting Human Oral Absorption(Plot of Human Intestinal Absorption v MDCK Cell Permeability)
model for mdck cells based on chi values logp app mdck 0 0372chi meoh 0 227 cmr 0 78ind acid 1 659
Model for MDCK cellsbased on CHI valueslogP app MDCK = 0.0372CHI(MeOH) - 0.227 cMR -0.78Ind (acid) + 1.659
slide38

Predicting Human Oral Absorption(Model includes measured lipophilicity and calculated molecular size)% Human Oral Absorption = 1.31 CHI(MeOH) -10.93cMR + 88.6n=52 r=0.81 s=19.7 F=15.9

% absorbed drug

slide39
Solvation equation for oral absorption% Abs = 92 + 2.9E + 4.1S - 21.7A - 21.1B + 10.5Vxn=170 r2=0.74 sd=14%
  • Note that the relative size of the v coefficient is smaller than for water/solvent partitions.
  • The e and s coefficients are insignificant
  • Absorption is generally high (90%) unless several H-bond donor/acceptor groups on a molecule decrease absorption. The equation is not affected by whether a compound is acidic or basic
  • The equation is consistent with other models e.g.
    • polar surface area (Palm and Clark)
    • CHI - CMR
    • logD v CMR
advantages of abraham qsar models abs 92 2 9 e 4 1 s 21 7 a 21 1 b 10 5 v x n 170 r 2 0 74 sd 14
Advantages of Abraham QSAR Models% Abs = 92 + 2.9E + 4.1S - 21.7A - 21.1B + 10.5Vxn=170 r2=0.74 sd=14%
  • Solute parameters can be estimated from molecular structure fragments or derived from experimental partition measurements
    • Allows prediction drug behaviour prior to synthesis and a test of the model after synthesis by accurate physicochemical property measurement
  • The same parameters are always used so that different systems can be directly compared
    • Can be used to investigate molecular mechanisms
slide41

100

80

Training set

60

Drugs 229-241

40

Predicted

Low solubility

20

Dose dependant

0

-20

0

20

40

60

80

100

Observed

Prediction of Human Intestinal Absorption from the Solvation Equation

% Abs = 92 + 2.9E + 4.1S - 21.7A - 21.1B + 10.5Vx

slide42
Solvation equation for oral absorption % Abs = 92 + 2.9E + 4.1S - 21.7A - 21.1B + 10.5Vxn=170 r2=0.74 sd=14%

Comparison with other processesA pseudo-rate equation can be derived from the equation for %of Absorbed Dose log{ln[100/(100-%Abs.)]} = 0.54 - 0.025 E + 0.14 S - 0.41 A - 0.51 B + 0.20Vx n = 127, r2 = 0.80, SD = 0.29, F = 94Zhao YH, Le J, Abraham MH, Hersey A, Eddershaw PJ, Luscombe CN, Butina D, Beck G, Sherborne B, Cooper I, Platts,J.A.. J Pharm Sci., submitted

slide43

A very different equation when compared to:A pseudo-rate equation can be derived from the equation for %of Absorbed Doselog{ln[100/(100-%Abs.)]} = 0.54 - 0.025 E + 0.14 S - 0.41 A - 0.51 B + 0.20Vxn = 127 r2 = 0.80 SD = 0.29 F = 94Zhao YH, Le J, Abraham MH, Hersey A, Eddershaw PJ, Luscombe CN, Butina D, Beck G, Sherborne B, Cooper I, Platts,J.A.. J Pharm Sci., submitted

slide44

This does not fit a partition model of membrane transport (e.g. octanol/water) logkoct = 0.088 + 0.562 E – 1.054S + 0.034A - 3.46B + 3.814Vx

A very different equation when compared to:A pseudo-rate equation can be derived from the equation for %of Absorbed Doselog{ln[100/(100-%Abs.)]} = 0.54 - 0.025 E + 0.14 S - 0.41 A - 0.51 B + 0.20Vxn = 127 r2 = 0.80 SD = 0.29 F = 94Zhao YH, Le J, Abraham MH, Hersey A, Eddershaw PJ, Luscombe CN, Butina D, Beck G, Sherborne B, Cooper I, Platts,J.A.. J Pharm Sci., submitted

slide45

A very different equation when compared to:A pseudo-rate equation can be derived from the equation for %of Absorbed Doselog{ln[100/(100-%Abs.)]} = 0.54 - 0.025 E + 0.14 S - 0.41 A - 0.51 B + 0.20Vxn = 127 r2 = 0.80 SD = 0.29 F = 94Zhao YH, Le J, Abraham MH, Hersey A, Eddershaw PJ, Luscombe CN, Butina D, Beck G, Sherborne B, Cooper I, Platts,J.A.. J Pharm Sci., submitted

slide46

Solvation equation for rate of uptake into C18 extraction disclogkup = -5.34 + 0.08 E + 0.20 S - 0.08 A - 0.28 B + 0.33 Vxn=21 r2=0.95 sd=0.08 F=30

A very similar equation to:A pseudo-rate equation can be derived from the equation for %of Absorbed Doselog{ln[100/(100-%Abs.)]} = 0.54 - 0.025 E + 0.14 S - 0.41 A - 0.51 B + 0.20Vxn = 127 r2 = 0.80 SD = 0.29 F = 94Zhao YH, Le J, Abraham MH, Hersey A, Eddershaw PJ, Luscombe CN, Butina D, Beck G, Sherborne B, Cooper I, Platts,J.A.. J Pharm Sci., submitted

slide47

Cell Permeability Models logPapp (CaCo2) = - 4.4 - 0.20E + 0.26S - 1.27A - 0.24 B + 0.09Vx logPapp (MDCK) = 4.3 + 0.10E + 0.19S - 1.73 A - 0.79B - 0.17Vx

Similar but not identical to:A pseudo-rate equation can be derived from the equation for %of Absorbed Doselog{ln[100/(100-%Abs.)]} = 0.54 - 0.025 E + 0.14 S - 0.41 A - 0.51 B + 0.20Vxn = 127 r2 = 0.80 SD = 0.29 F = 94Zhao YH, Le J, Abraham MH, Hersey A, Eddershaw PJ, Luscombe CN, Butina D, Beck G, Sherborne B, Cooper I, Platts,J.A.. J Pharm Sci., submitted

slide48

Wohnsland and Faller, J. Med. Chem. 2001, 44, 923 - 930Artificial Alkane/Water Membranes

Figure 4 pH-dependent permeability of ionizable compounds: (a) diclofenac (acidic pKa = 4.0), (b) desipramine (basic pKa = 10.6), and determination of their permeabilities through the unstirred water layer: (c) diclofenac; (d) desipramine.

slide49

Wohnsland and Faller, J. Med. Chem. 2001, 44, 923 - 930Artificial Alkane/Water Membranes

  • They analyse their data based on two transport processes that contribute to effective measured membrane permeability Pe (I.e. Intrinsic membrane permeability Po and permeability through an unstirred water layer Pul)
  • Relative contributions from Po and Pul were deduced from pH Permeability profiles and using literature values for aqueous diffusion coefficients, they estimate the thickness of the unstirred layer
  • They demonstrate that intrinsic permeabilities are directly proportional to the alkane/water partition coefficients
  • The estimated thickness of the unstirred layer in their model was 300mm and they quote estimates of 1500mm in the CACO2 model and 50mm in-vivo in the GI tract
  • Are their assumptions correct? They ignore diffusion across the interface and assume that diffusion rates are the same for all molecules 
slide50

Mechanistic Inferences from the Different Data Types

  • The different types of information (measured properties, experimental permeability models, and calculated Abraham parameters) are consistent with the idea that human intestinal absorption and permeability models involve similar processes
  • Diffusion across the membrane interface (across the unstirred water layer?) is often the step that controls the overall permeability
  • Molecular diffusion rates and interfacial transfer rates are significantly slowed by the presence of polar functionality and hydrogen bonding interactions but appear to be relatively insensitive to ionisaton of acidic and basic groups
  • General empirical QSAR models for intestinal absorption are possible based on a diffusion controlled process. They will produce high estimates when other mechanisms become rate limiting (e.g. solubility and dissolution, active efflux, low intrinsic membrane affinity)
slide51

Where to next? What should we measure?

  • Direct measurement of diffusion rates of molecules (in free solution and at interfaces)?
    • What are the QSAR relationships (e.g. Abraham Solvation Equations)?
  • Overall bioavailability (I.e.not just intestinal absorption) is the key parameter in candidate selection. In general increasing lipophilicity of drugs tends to increase their susceptibility to metabolism
    • What are the specific QSAR relationships for partition and rate of uptake into liver? What would this tell us about the mechanisms of uptake and penetration to the sites of metabolism?
collaborators and co workers
Collaborators and Co-workers
  • University College London
    • Mike Abraham, Chau My Du, James Platts, Yuan Zhao, Joelle Le
  • BMG LabTechnologies
    • Derek Patton, Monika Siggelkow
  • Sirius
    • John Comer, Brett Hughes, Karl Box, Kirsty Powell, Kin Tam, Paul Hosking, Roger Allen, Lynne Trowbridge, Colin Peake
  • GlaxoWellcome
    • CLOP- Mike Tarbit, Om Dhingra, Mark Patrick, Lori Takahashi
    • Rachel Thornley, Anne Hersey, Darko Butina, John Hollerton, Keith Brinded, Ian Mutton
    • Chris Bevan, Alan Hill, Klara Valko, Pat McDonough