Abstract
The physical properties of investigational molecules in drug discovery programmes have been the subjects of intense scrutiny, largely due to a propensity for the pursuit of examples where they are sub-optimal. This chapter introduces the noteworthy contributions that identified the shortcomings and then defines and discusses the key physical parameters (lipophilicity, pK a and solubility) and contemporary developments in their measurement and use. These physical characteristics impact the passage of a drug molecule from the administered dose to the site of action, profoundly influencing its pharmacokinetics and pharmacology. In particular, lipophilicity has a major influence on various parameters used to assess the developability of experimental molecules; the additional impact of aromaticity or flatness in structures and differentiation between the roles intrinsic (log P) and effective (log D) are also illustrated. In conclusion, the combined influences of good properties in efficient molecules are presented as powerful indicators of quality.
Keywords
- Physical properties
- Lipophilicity
- Hydrophobicity
- pKa
- Solubility
- log P
- log D
- Chromatographic hydrophocbity measurements
- Aromaticity
- Property forecast index
- Drug efficiency
- Ligand efficiency
- Ligand lipophilicity Efficiency
- Developability classification system
- Thermodynamics
- Structure property relationships
- Developability
- Attrition
- Permeation
- Cytochrome P450
- hERG
- Promiscuity
- Plasma protein binding
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- ADME (or ADMET):
-
Absorption, distribution, metabolism and elimination
- BBB:
-
Blood–brain barrier
- BEI:
-
Binding efficiency index
- CHI:
-
Chromatographic hydrophobicity index
- CLND:
-
Chemiluminescent nitrogen detection
- cmr:
-
Calculated molar refraction
- DCS:
-
Developability classification system
- DMPK:
-
Drug metabolism and pharmacokinetics
- FaSSIF:
-
Fasted state simulated intestinal fluids
- FeSSIF:
-
Fed state simulated intestinal fluids
- GSE:
-
General solubility equation
- GSK:
-
GlaxoSmithKline
- hERG:
-
Human ether-a-go-go-related gene
- HSA:
-
Human serum albumin
- IAM:
-
Immobilised artificial membrane
- ITC:
-
Isothermal titration calorimetry
- LE:
-
Ligand efficiency
- LLE:
-
Ligand lipophilicity efficiency
- MPbAP:
-
Melting point based absorption potential
- OW:
-
Octanol/water
- PAMPA:
-
Parallel artificial membrane permeation assays
- PFI:
-
Property forecast index
- QED:
-
Quantitative estimate of drug-likeness
- QSAR:
-
Quantitative structure activity relationships
- QSPR:
-
Quantitative structure property relationships
- SGF:
-
Simulated gastric fluid
- SILE:
-
Size-independent ligand efficiency
References
Meanwell NA (2011) Improving drug candidates by design: a focus on physicochemical properties as a means of improving compound disposition and safety. Chem Res Toxicol 24:1420–1456
Hansch C, Bjorkroth J, Leo A (1987) Hydrophobicity and central nervous system agents: on the principle of minimal hydrophobicity. J Pharm Sci 76:663–687
Hann MM (1994) Considerations for the use of computational chemistry techniques by medicinal chemists. In: King FD (ed) Medicinal chemistry, principles and practice. RSC, Cambridge, pp 130–142
Lipinski CA et al (2001) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 46:3–26
Leeson PD, Springthorpe B (2007) The influence of drug-like concepts on decision-making in medicinal chemistry. Nat Rev Drug Discov 6:881–890
Hann MM (2011) Molecular obesity, potency and other addictions in drug discovery. Med Chem Comm 2:349–355
Hubbard RE, Murray JB (2011) Experiences in fragment-based lead discovery. Methods Enzymol 493:509–531
Congreve M et al (2008) Recent developments in fragment-based drug discovery. J Med Chem 51:3661–3680
Erlanson DA et al (2004) Fragment-based drug discovery. J Med Chem 47:3463–3482
Muresan S, Sadowski J (2008) Properties guiding drug- and lead-likeness. In: Mannhold R (ed) Molecular drug properties – measurement and prediction. Wiley-VCH, Weinheim, pp 439–461
Hopkins AL, Groom CR, Alex A (2004) Ligand efficiency: a useful metric for lead selection. Drug Discov Today 9:430–431
Leeson PD, Empfield JR (2010) Reducing the risk of drug attrition associated with physicochemical properties. Annu Rep Med Chem 45:393–407
Van De Waterbeemd H et al (2001) Property-based design: optimization of drug absorption and pharmacokinetics. J Med Chem 44:1313–1333
Tarcsay Á, Nyíri K, Keserű GM (2012) Impact of lipophilic efficiency on compound quality. J Med Chem 55:1252–1260
Gleeson MP et al (2011) Probing the links between in vitro potency, ADMET and physicochemical parameters. Nat Rev Drug Discov 10:197–208
Hill AP, Young RJ (2010) Getting physical in drug discovery: a contemporary perspective on solubility and hydrophobicity. Drug Discov Today 15:648–655
Roden DM, George AL Jr (2002) The genetic basis of variability in drug responses. Nat Rev Drug Discov 1:37–44
Faller B et al (2011) Evolution of the physicochemical properties of marketed drugs: can history foretell the future? Drug Discov Today 16:976–984
Zhao H (2010) Lead optimization in the nondrug-like space. Drug Discov Today 16:158–163
Van de Waterbeemd H, Gifford E (2003) Admet in silico modelling: towards prediction paradise? Nat Rev Drug Discov 2:192–204
Bickerton GR et al (2012) Quantifying the chemical beauty of drugs. Nat Chem 4:90–98
Kerns EH, Di L (2004) Physicochemical profiling: overview of the screens. Drug Discov Today Technol 1:343–348
Kerns EH, Di L (2004) Drug-like properties: concepts, structure design and methods: from ADME to toxicity optimization. Academic, Amsterdam, Boston
Wan H, Holmen AG (2009) High throughput screening of physicochemical properties and in vitro ADME profiling in drug discovery. Comb Chem High Throughput Screen 12:315–329
Smith RN et al (1975) Selection of a reference partitioning system for drug design work. J Pharm Sci 64:599–606
Tute MS (1996) Lipophilicity: a history. In: Mannhold R et al (eds) Methods and principles in medicinal chemistry. Wiley, New York, pp 7–26
Fujita T, Iwasha J, Hansch C (1964) A new substituent constant, π, derived from partition coefficients. J Am Chem Soc 86:5175–5180
Leo A, Hansch C, Elkins D (1971) Partition coefficients and their uses. Chem Rev 71:525–616
Young RJ et al (2011) Getting physical in drug discovery II: the impact of chromatographic hydrophobicity measurements and aromaticity. Drug Discov Today 16:822–830
He Y-L et al (1998) Species differences in size discrimination in the paracellular pathway reflected by oral bioavailability of polyethylene glycol and D-peptides. J Pharm Sci 87:626–633
Kirch W, Görg KG (1982) Clinical pharmacokinetics of atenolol. Eur J Drug Metab Pharmacokinet 7:81–91
Bunnage ME et al (2007) Discovery of potent & selective inhibitors of activated thrombin-activatable fibrinolysis inhibitor for the treatment of thrombosis. J Med Chem 50:6095–6103
Hansch C, Leo A (1979) Substituent constants for correlation analysis in chemistry and biology. Wiley, New York
Leo AJ (1993) Calculating log POct from structures. Chem Rev 93:1281–1306
Rekker RE et al (1993) On the reliability of calculated log P-values: Rekker, Hansch-Leo and Suzuki approach. Quant Struct Act Relat 12:152–157
Ribeiro MMB et al (2010) Drug–lipid interaction evaluation: why a 19th century solution? Trends Pharmacol Sci 31:449–454
Wenlock MC, Barton P, Luker T (2011) Lipophilicity of acidic compounds: impact of ion pair partitioning on drug design. Bioorg Med Chem Lett 21:3550–3556
Valkó K (2004) Application of high-performance liquid chromatography based measurements of lipophilicity to model biological distribution. J Chromatogr A 1037:299–310
Valkó K et al (1997) Chromatographic hydrophobicity index by fast-gradient RP-HPLC: a high-throughput alternative to log P/log D. Anal Chem 69:2022–2029
Albert A, Serjeant EP (1984) The determination of ionization constants, 3rd edn. Chapman and Hall, New York
Avdeef A, Bucher JJ (1978) Accurate measurements of the concentration of hydrogen ions with a glass electrode. Anal Chem 50:2137–2142
Avdeef A et al (2000) pH-metric solubility: correlation between the acid–base titration and the saturation shake-flask solubility-pH methods. Pharm Res 17:85–89
Allen RI et al (1998) Multiwavelength spectrophotometric determination of acid dissociation constants of ionisable drugs. J Pharm Biomed Anal 17:699–712
Gift AD et al (2012) Experimental determination of pK a values by use of NMR chemical shifts, revisited. J Chem Educ 89:1458–1460
Cleveland JA et al (1993) Automated pK a determination at low solute concentrations by capillary electrophoresis. J Chromatogr A 652:301–308
Box K et al (2003) High throughput measurement of pK a values in a mixed-buffer linear pH gradient system. Anal Chem 75:883–892
Perrin DD, Dempsey B, Serjeant EP (1981) pK a prediction for organic acids and bases. Chapman and Hall, London
Di L, Fish PV, Mano T (2012) Bridging solubility between drug discovery and development. Drug Discov Today 17:486–495
Sugano K et al (2007) Solubility and dissolution profile assessment in drug discovery. Drug Metab Pharmacokinet 22:225–254
Huang LF, Tong WQ (2004) Impact of solid state properties on developability assessment of drug candidates. Adv Drug Deliv Rev 56:321–334
Bhattachar SN et al (2006) Evaluation of the chemiluminescent nitrogen detector for solubility determinations to support drug discovery. J Pharm Biomed Anal 41:152–157
Jain N, Yalkowsky SH (2001) Estimation of the aqueous solubility I: application to organic non-electrolytes. J Pharm Sci 90:234–252
European pharmacopeia. http://pharmeuropa.edqm.eu/home/
Bergström CA et al (2007) Poorly soluble marketed drugs display solvation limited solubility. J Med Chem 50:5858–5862
Ishikawa, Hashimoto (2011) Improvement in aqueous solubility in small molecule drug discovery programs by disruption of molecular planarity and symmetry. J Med Chem 54:1539–1554
Chu KA, Yalkowsky SH (2009) An interesting relationship between drug absorption and melting point. Int J Pharm 373:24–40
Llinàs A, Glen RC, Goodman JM (2008) Can you predict solubilities of thirty-two molecules using a database of one hundred reliable measurements? J Chem Inf Model 48:1289–1303
Elder D, Holm R (2013) Aqueous solubility: simple predictive methods (in silico, in vitro and bio-relevant approaches). Int J Pharm 453:3–11
Jantratid E et al (2008) Dissolution media simulating conditions in the proximal human gastrointestinal tract: an update. Pharm Res 25:1663–1676
Holm R et al (2013) Bile salts and their importance for drug absorption. Int J Pharm 453:44–45
Bevernage J et al (2013) Evaluation of gastrointestinal drug supersaturation and precipitation: strategies and issues. Int J Pharm 453:25–35
Ritchie TJ, Macdonald SJF (2009) The impact of aromatic ring count on compound developability – are too many aromatic rings a liability in drug design? Drug Discov Today 14:1011–1020
Lovering F, Bikker J, Humblet C (2009) Escape from flatland: increasing saturation as an approach to improving clinical success. J Med Chem 52:6752–6756
Yang Y et al (2012) Beyond size, ionization state, and lipophilicity: influence of molecular topology on absorption, distribution, metabolism, excretion, and toxicity for drug-like compounds. J Med Chem 55:3667–3677
Lovering F (2013) Escape from Flatland 2: complexity and promiscuity. Med Chem Comm 4:515
Ritchie TJ et al (2011) The impact of aromatic ring count on compound developability – further insights by examining carbo- and hetero- aromatic and aliphatic ring types. Drug Discov Today 16:164–171
Kimura T, Higaki K (2002) Gastrointestinal transit and drug absorption. Biol Pharm Bull 25:149–164
Davies B, Morris T (1993) Physiological parameters in laboratory animals and humans. Pharm Res 10:1093–1095
Riley RJ et al (2002) The influence of DMPK as an integrated partner in modern drug discovery. Curr Drug Metab 3:527–550
Schiller C et al (2005) Intestinal fluid volumes and transit of dosage forms as assessed by magnetic resonance imaging. Aliment Pharmacol Ther 22:971–979
Uetrecht JP, Trager W (2007) Conjugation pathways. Drug metabolism, chemical and enzymatic aspects. Informa Healthcare, New York, pp 130–144
Wager TT et al (2010) Moving beyond rules: the development of a central nervous system multiparameter optimization (CNS MPO) approach to enable alignment of drug-like properties. ACS Chem Neurosci 1:435–449
Butler JM, Dressman JB (2010) The developability classification system: application of biopharmaceutics concepts to formulation development. J Pharm Sci 99:4940–4954
Kola I, Landis J (2004) Can the pharmaceutical industry reduce attrition rates? Nat Rev Drug Discov 3:711–715
Waring MJ (2010) Lipophilicity in drug discovery. Expert Opin Drug Discov 5:235–248
Hann MM, Keserű GM (2012) Finding the sweet spot – the role of nature and nurture in medicinal chemistry. Nat Rev Drug Discov 11:355–365
Waring MJ (2009) Defining optimum lipophilicity and molecular weight ranges for drug candidates – molecular weight dependent lower logD limits based on permeability. Bioorg Med Chem Lett 19:2844–2851
Gleeson MP (2008) Generation of a set of simple, interpretable ADMET rules of thumb. J Med Chem 51:817–834
Kenny PW, Montanari CA (2013) Inflation of correlation in the pursuit of drug-likeness. J Comput Aided Mol Des 27:1–13
Sugano K et al (2010) Coexistence of passive and carrier-mediated processes in drug transport. Nat Rev Drug Discov 9:597–614
Gleeson MP, Hersey A, Hannongbua S (2011) In-silico ADME models: a general assessment of their utility in drug discovery applications. Curr Top Med Chem 11:358–381
Kell DB, Dobson PD, Oliver SG (2011) Pharmaceutical drug transport: the issues and the implications that it is essentially carrier-mediated only. Drug Discov Today 16:704–714
Di L et al (2012) Evidence-based approach to assess passive diffusion and carrier-mediated drug transport. Drug Discov Today 17:905–912
Kubinyi H (1978) Drug partitioning: relationships between forward and reverse rate constants and partition coefficient. J Pharm Sci 67:262–263
Kubinyi H (1979) Lipophilicity and drug activity. Prog Drug Res 23:97–198
Glen RC et al (1995) Computer-aided design and synthesis of 5-substituted tryptamines and their pharmacology at the 5-HT1D receptor: discovery of compounds with potential anti-migraine properties. J Med Chem 38:3566–3580
Young RJ (2011) The successful quest for oral factor Xa inhibitors; learnings for all of medicinal chemistry? Bioorg Med Chem Lett 21:6228–6235
Johnson TW et al (2009) Using the Golden Triangle to optimize clearance and oral absorption. Bioorg Med Chem Lett 19:5560–5564
Obach RL et al (2005) In vitro cytochrome P450 inhibition data and the prediction of drug–drug interactions: qualitative relationships, quantitative predictions, and the rank-order approach. Clin Pharmacol Ther 78:582–592
Lewis DFV et al (2007) Quantitative structure-activity relationships (QSARs) in inhibitors of various cytochromes P450: the importance of compound lipophilicity. J Enzyme Inhib Med Chem 22:1–6
Lewis DFV et al (2004) Compound lipophilicity for substrate binding to human P450s in drug metabolism. Drug Discov Today 9:530–537
Lewis DFV, Dickins M (2002) Substrate SAR in human p450s. Drug Discov Today 7:918–925
Jamieson C et al (2006) Medicinal chemistry of hERG optimizations: highlights and hang-ups. J Med Chem 49:5029–5046
Waring MJ, Johnstone C (2007) A quantitative assessment of hERG liability as a function of lipophilicity. Bioorg Med Chem Lett 17:1759–1764
Wood A, Armour D (2005) The discovery of the CCR5 receptor antagonist, UK-427,857, a new agent for the treatment of HIV infection and AIDS. Prog Med Chem 43:239–271
Diller DJ (2009) In silico hERG modelling: challenges and progress. Curr Comput Aided Drug Des 5:106–121
Tarcsay Á, Keserű GM (2013) Contributions of molecular properties to drug promiscuity. J Med Chem 56:1789–1795
Hopkins AL, Mason JS, Overington JP (2006) Can we rationally design promiscuous drugs? Curr Opin Struct Biol 16:127–136
Hughes JD et al (2008) Physiochemical drug properties associated with in vivo toxicological outcomes. Bioorg Med Chem Lett 18:4872–4875
Morphy R, Rankovic Z (2007) Fragments, network biology and designing multiple ligands. Drug Discov Today 12:156–160
Azzaoui K et al (2007) Modeling promiscuity based on in vitro safety pharmacology profiling data. ChemMedChem 2007(2):874–880
Peters J-U et al (2009) Pharmacological promiscuity: dependence on compound properties and target specificity in a set of recent Roche compounds. ChemMedChem 4:680–686
Yang Y et al (2010) Investigation of the relationship between topology and selectivity for drug-like molecules. J Med Chem 53:7709–7714
Peters J-U et al (2012) Can we discover pharmacological promiscuity early in the drug discovery process? Drug Discov Today 17:325–335
Lounkine E et al (2012) Large-scale prediction and testing of drug activity on side-effect targets. Nature 486:361–367
Leeson PD et al (2011) Impact of ion class and time on oral drug molecular properties. Med Chem Comm 2:91–105
Leach AR, Hann MM (2011) Molecular complexity and fragment-based drug discovery: ten years on. Curr Opin Chem Biol 15:489–496
Trainor GL (2007) The importance of plasma protein binding in drug discovery. Expert Opin Drug Discov 2:51–64
Valkó K et al (2003) Fast gradient HPLC method to determine compounds binding to human serum albumin: relationships with octanol/water and immobilized artificial membrane lipophilicity. J Pharm Sci 92:2236–2248
Smith DA et al (2010) The effect of plasma protein binding on in vivo efficacy: misconceptions in drug discovery. Nat Rev Drug Discov 9:929–939
Riley RJ et al (2005) A unified model for predicting human hepatic metabolic clearance from in vitro intrinsic clearance data in hepatocytes and microsomes. Drug Metab Dispos 33:1304–1311
Braggio et al (2010) Drug efficiency: a new concept to guide lead optimization programs towards the selection of better clinical candidates. Expert Opin Drug Discov 5:609–618
Montanari D et al (2011) Application of drug efficiency index in drug discovery: a strategy towards low therapeutic dose. Expert Opin Drug Discov 6:913–920
Valkó K et al (2012) In vitro measurement of drug efficiency index to aid early lead optimization. J Pharm Sci 101:4155–4169
Valkó K, Nunhuck SB, Hill AP (2011) Estimating unbound volume of distribution and tissue binding by in vitro HPLC-based human serum albumin and immobilized artificial membrane-binding measurements. J Pharm Sci 100:849–862
Hopkins AL et al (2014) The role of ligand efficiency measures in drug discovery. Nat Rev Drug Discov 13:105–121
Reynolds CH et al (2008) Ligand binding efficiency: trends, physical basis, and implications. J Med Chem 51:2432–2438
Nissink JWM (2009) Simple size-independent measure of ligand efficiency. J Chem Inf Model 49:1617–1622
Hann MM, Leach AR, Harper G (2001) Molecular complexity and its impact on the probability of finding leads for drug discovery. J Chem Inf Comput Sci 41:856–864
Mortenson PN, Murray CW (2011) Assessing the lipophilicity of fragments and early hits. J Comput Aided Mol Des 25:663–667
Wyatt PG et al (2008) Identification of N-(4-Piperidinyl)-4-(2,6-dichlorobenzoylamino)-1H-pyrazole-3-carboxamide (AT7519), a novel cyclin dependent kinase inhibitor using fragment-based X-ray crystallography and structure based drug design. J Med Chem 51:4986–4999
Gill AL et al (2005) Identification of novel p38alpha MAP kinase inhibitors using fragment-based lead generation. J Med Chem 48:414–426
Freeman-Cook KD, Hoffman RL, Johnson TW (2013) Lipophilic efficiency: the most important efficiency metric in medicinal chemistry. Future Med Chem 5:113–115
Gill AL et al (2007) A comparison of physicochemical property profiles of marketed oral drugs and orally bioavailable anti-cancer protein kinase inhibitors in clinical development. Curr Top Med Chem 7:1408–1422
McTigue M et al (2012) Molecular conformations, interactions, and properties associated with drug efficiency and clinical performance among VEGFR TK inhibitors. Proc Natl Acad Sci U S A 109:18281–18289
Shultz MD (2013) Setting expectations in molecular optimizations: strengths and limitations of commonly used composite parameters. Bioorg Med Chem Lett 23:5980–5991
Freire E (2008) Do enthalpy and entropy distinguish first in class from best in class? Drug Discov Today 13:869–874
Shultz MD (2013) The thermodynamic basis for the use of lipophilic efficiency (LipE) in enthalpic optimizations. Bioorg Med Chem Lett 23:5992–6000
Morgan P et al (2012) Can the flow of medicines be improved? fundamental pharmacokinetic and pharmacological principles toward improving Phase II survival. Drug Discov Today 17:419–424
Acknowledgements
The educational help of the many who have turned a maths-averse organic chemist into a medicinal chemist conversant in physical properties is gratefully acknowledged. In particular long-time friend and mentor Alan Hill has been the source of much knowledge and inspiration. The expertise of, and stimulating conversations with, Paul Leeson, Chris Luscombe, Darren Green, Mike Hann, Klára Valkó, Andrew Leach and Tim Ritchie have also contributed much to the growing debate and wider acceptance of the impact of physical properties.
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Young, R.J. (2014). Physical Properties in Drug Design. In: Meanwell, N. (eds) Tactics in Contemporary Drug Design. Topics in Medicinal Chemistry, vol 9. Springer, Berlin, Heidelberg. https://doi.org/10.1007/7355_2013_35
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