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This chapter provides a high-level overview of all the strategies for solving challenges related to the optimization of absorption, distribution, metabolism, excretion and toxicity (ADMET) properties in small molecule drug discovery, which are detailed within the chapters of this book. In the introductory section the need to apply a holistic view of molecular properties towards the identification of candidate drugs which meet the target pharmacokinetic–pharmacodynamic profile and possess an adequate therapeutic index for a given indication is discussed. The molecular properties which have the biggest influence on ADMET parameters and which are directly amenable to structural modifications are outlined. The effects of these are visualized in an overview table. The most promising mitigation strategies for each ADMET property described in this book in detail are summarized.

This chapter provides a high-level overview of all the strategies for solving challenges arising during the optimization of absorption, distribution, metabolism, excretion and toxicity (ADMET) properties in small molecule drug discovery as described in this book. While this is meant as a quick reference for the reader's convenience, it is highly recommended to consult the pertinent chapters for a detailed yet concise discussion, including concrete examples of how these strategies were employed previously.

Each chapter describes mitigation strategies for a single ADMET property. It is clear that hit and lead optimization with a focus on just few parameters is overly simplistic, since each structural modification targeted at changing a particular property in the desired direction will inevitably confer a change on all of a compound's properties. In drug discovery it is therefore advisable to adopt a holistic perspective from the beginning, with efficacious dose predictions ultimately being the most holistic metric. Applying dose predictions early on can be an effective way to identify critical drug properties and guide further optimization.1–5  While Lipinski's “rule-of-five”, which predicts that poor absorption or permeation is more likely when there are more than five hydrogen-bond donors, more than ten hydrogen-bond acceptors, the molecular weight is greater than 500 and the calculated partition coefficient (logP) is greater than five,6  is an early version of an integrated approach, the parameters of this and similar mnemonics7  should be used for guidance rather than as strict cut-offs. This is equally true for the techniques for how to mitigate challenges associated with individual ADMET properties described in the chapters of this book. As the overview Table 1.1 in Section 1.3 reveals, the attempt to design a universally perfect drug is elusive. The medicinal chemist's task is rather to come up with candidate drugs with a good balance of molecular properties.8,9  In order to find this balance, it is essential to develop a solid understanding of the target pharmacokinetic–pharmacodynamic (PK–PD) profile and an adequate ratio of therapeutic benefits to safety risks for a given indication.1,3,5,10–14 

While a holistic consideration of molecular properties is indispensable during the hit-to-lead and lead optimization phases, medicinal chemists often encounter situations in which particular attention needs to be given to the improvement of single ADMET properties. It is the purpose of this book to provide efficient access to the most promising mitigation strategies and tactics to improve individual properties while offering a uniquely comprehensive overview of how the modifications employed as part of such optimization efforts might affect other ADMET parameters. The properties featured in this book comprise those which are most commonly and universally addressed during hit and lead optimization in small molecule drug discovery programs.

It should be mentioned that there are no chapters dedicated to two fundamental pharmacokinetic parameters, volume of distribution and plasma protein binding, since it has been recommended not to target these parameters for optimization in drug design per se, or only with caution.15–17  However, both can be modulated by changing physicochemical properties; the main trends are therefore included in Table 1.1 in Section 1.3. Lipophilic positively charged molecules have a tendency to partition into biological membranes due to a positive interaction with the phospholipid bilayer, which results in high volumes of distribution. Neutral compounds have no electrostatic interaction with the surface of membranes. Their ability to partition into membranes will thus mainly be driven by increasing lipophilicity. Negatively ionized compounds have a very low affinity for membranes and consequently low volumes of distribution but tend to bind strongly to serum albumin, the most abundant plasma protein.17  The strongest determinant of albumin binding for neutral and basic molecules is again lipophilicity.18 

Lipophilicity (or hydrophobicity) is the molecular property which has the single most profound impact on ADMET properties (Table 1.1).7,19–22  The effective lipophilicity is expressed as logD, the logarithm of the distribution coefficient, D, which is the ratio of equilibrium concentrations of all ionized and unionized forms of a solute in a mixture of a hydrophobic phase such as n-octanol and an aqueous phase at a given pH, usually 7.4. The partition coefficient, P, refers to the equilibrium concentration ratio of a hypothetical unionized compound; logP is termed intrinsic lipophilicity since it is independent of the pH of the aqueous phase. Together with logP the acid dissociation constant (pKa) values of all ionizable groups of a compound therefore determine the effective lipophilicity logD (Chapter 2).19,23  It has been suggested that an optimal lipophilicity range lies between logD 1 and 3.20  While logD values above 3 are associated with low solubility and an overall increased safety risk, low logD values below 0–1 will entail poor membrane permeability and increased renal clearance. Due to the prominent influence of lipophilicity on ADMET properties, the experimentally determined logD21,24  is invaluable to effectively guide medicinal chemistry optimization. For drug design calculated measures of lipophilicity are of great use. The most common and popular methods to estimate logP are based on the summation of lipophilicity contributions of fragments. Estimation of logD from calculated logP and pKa is intrinsically unreliable due to the uncertainty of predictions, which is exacerbated by the propagation of errors.20  Advances in computational methods, such as machine learning using large corporate data sets, have enabled the generation of robust models, even for the prediction of logD. However, these still need to be trained continuously and are not broadly available to the community. A recent compilation of logD contributions of commonly used substituents based on experimental logD data and a molecular matched pairs analysis constitutes a practical tool for compound design.25 

Beyond its crucial effect on logD, charge is also an important determinant of numerous ADMET properties in its own right (Table 1.1).7  For this reason optimization efforts often require careful fine-tuning of the pKa of ionizable groups, which highlights the need to continuously expand the knowledge base of how ionization constants of acids and bases can be modulated by structural modifications.26–28 

The size of a compound, e.g. expressed as molecular weight (MW) as a simple and intuitive measure, is another fundamental molecular property. With some exceptions, striving to keep molecular weight low – ideally below 500 or even better 400 Da7  – will broadly benefit ADMET properties, in particular membrane permeability, but also contribute to achieving high ligand binding efficiency.29  While these trends have been firmly established, it should also be mentioned, though, that there are a number of orally absorbed drugs with MW >500 Da in the “beyond rule of five” (bRo5) space.30 

In the quest to gain an ever better understanding of how molecular properties influence ADMET properties, numerous molecular descriptors have been evaluated. It should be pointed out that many descriptors of molecular shape and counts or summations of various structural features, such as number of rotatable bonds or even (topological) polar surface area [(T)PSA] are to some degree correlated with molecular weight. This is also true for hydrogen bond acceptor and donor counts. Nevertheless, these parameters are featured in Table 1.1 since hydrogen bond acceptors and, in particular, donors play a prominent role pertaining to certain ADMET properties, such as membrane permeability and phase 2 metabolism.

Contacts with aromatic rings are among the most frequent non-covalent protein–ligand interactions, which impressively underlines the importance of aryl groups in drug discovery.31,32  It is therefore to be expected that the number, nature and positioning of aromatic rings may have an effect on ADMET properties which involve a protein–ligand interaction, such as inhibition of cardiac ion channels, plasma protein binding or cytochrome P450 (CYP) inhibition. It has been shown that detrimental effects on these ADMET parameters are mainly due to the number of carboaromatic rings.33  It should be pointed out, though, that carboaromatic ring count also tends to correlate with lipophilicity, which is a key determinant of these properties. Nevertheless, it has been suggested that aromatic ring count is an important parameter in its own right and that limiting the sum of logD and the number of aromatic rings serves as a good predictor of developability.21  It is also worth mentioning that aromatic ring count does not adequately describe the relevance of aromaticity for some ADMET properties; e.g. photosensitivity, or genotoxicity due to intercalation or the formation of reactive metabolites such as nitrenium ions may be mitigated by breaking conjugation. The formation of electrophilic epoxide or quinone metabolites may be suppressed by replacement of an electron-rich aryl ring by a more electron-deficient one. In contrast, replacement of electron-deficient (aza-)heterocycles by less electron-deficient rings may be a successful strategy to disfavor DNA intercalation or reduce inhibition of CYP1A2.

by Robert J. Young

  • Reduce lipophilicity

  • Introduce charge

  • Introduce polar substituents

  • Replace aromatic CH by N or O

  • Reduce crystal packing and melting point

    • Reduce aromatic ring count or increase sp3 : sp2 ratio

    • Reduce hydrogen and halogen bonding

    • Reduce intramolecular hydrogen bonding

  • Salt forms

by Andy Pike and R. Ian Storer

  • Decrease molecular weight

  • Increase logD: increase logP and/or modulate pKa of ionizable centers

  • Reduce PSA: lower TPSA or experimental PSA (ePSA) by reduction of hydrogen bond donor (HBD) and/or hydrogen bond acceptor (HBA) count or introduction of intramolecular hydrogen bonds, via small rings in acyclic molecules and across larger macrocycles

  • Reduce HBD count

  • Prodrugs: a derivative compound with improved physicochemical characteristics for absorption which can undergo facile chemical or metabolic degradation to the pharmacologically active species

by Simone H. Stahl, Katherine S. Fenner, M. Raymond V. Finlay, Ravindra V. Alluri, Beth Williamson, Johan X. Johansson and Jason Kettle

  • Oligopeptide transporter 1 (PepT1, SLC15A1) mediated uptake

    • Modification of a compound to mimic key features of the pharmacophore of the natural substrates of PepT1, dipeptides and tripeptides, e.g. by addition of an amino acid

  • Sodium-dependent multivitamin transporter (SMVT, SLC5A6) mediated uptake

    • Drug conjugation with biotin (vitamin B7) or pantothenic acid (vitamin B5), the endogenous substrates of SMVT

  • Apical sodium-dependent bile acid transporter (ASBT, SLC10A2) mediated uptake

    • Drug conjugation with a bile acid

  • Monocarboxylate transporter 1 (MCT1, SLC16A1) mediated uptake

    • A monocarboxylate structure is the key prerequisite; other ionisable groups need to be masked, e.g. as prodrugs

  • Organic cation transporter OCTN2 (SLC22A5) mediated uptake

    • Drug conjugation with OCTN2's endogenous substrate l-carnitine

  • Organic cation transporter OCT1 (SLC22A1) and OCT3 (SLC22A3) mediated uptake (cf. Chapter 6)

    • Substrates are largely small hydrophilic compounds ranging from approximately 60 to 350 Da in size, with at least one positively charged group

  • Organic anion transporting polypeptide (OATP, SLCO, subtypes 1A2 and 2B1) mediated uptake

    • Relevance is unclear; substrates including a number of marketed drugs are lipophilic acids; endogenous substrates include prostaglandins and sulfate-conjugated steroids

  • Nucleoside transporter [concentrative nucleoside transporters (CNTs, SLC28) and equilibrative nucleoside transporters (ENTs, SLC29)] mediated uptake

    • Substrates are nucleosides and nucleobases as well as derivatives

by Peter Bungay and Sharan Bagal

  • Maximizing oral absorption

    • MW <500

    • logP <5

    • PSA <120–140 Å2

    • Hydrogen bond donor count <5

    • Hydrogen bond acceptor count <10

  • Maximizing brain penetration by minimizing P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP) mediated efflux at the blood–brain barrier

    • MW <400

    • logP 2–5

    • PSA <70–90 Å2

    • Hydrogen bond donor count <2

    • Charge: attenuate basic pKa (<8–8.5), avoid negative charge

by Pär Matsson and Maria Karlgren

  • Substrates

    • Transport usually requires a positive [organic cation transporter (OCT)] or negative [organic anion transporter (OAT)] charge

    • Molecular weight rarely exceeding 400 Da

    • Lipophilic drugs tend to be poor OCT and OAT substrates

  • Inhibitors

    • Inhibitors are usually positively (OCT) or negatively (OAT) charged

    • Greater molecular size is associated with a higher likelihood of inhibition

    • Reducing lipophilicity tends to decrease the probability of inhibition

by Maria Karlgren and Pär Matsson

  • Substrates

    • The majority of OATP1B1/1B3 substrates are negatively charged, but some neutral compounds have been reported as weaker substrates

    • Substrates tend to have a relatively high molecular weight in the 400–900 Da range

    • Lipophilic drugs tend to be less efficient OATP substrates

  • Inhibitors

    • Inhibitors are usually negatively charged but may also be neutral

    • The likelihood of inhibition correlates with descriptors of increasing molecular size, including molecular weight, volume, number of hydrogen bond acceptors and (topological) polar surface area

    • Reducing lipophilicity leads to a decreased likelihood of inhibition

by Alexander Treiber and Martin H. Bolli

  • Reduce lipophilicity

  • Decrease molecular weight

  • Cationic and zwitterionic compounds tend to be less potent inhibitors

  • Tendency toward decreased inhibition with increasing number of hydrogen bond donors

by Antonia F. Stepan and R. Scott Obach

  • Increasing metabolic stability

    • Reduce lipophilicity

    • Modify the site of metabolism: remove or block the metabolic soft spot, or disfavor binding to the catalytic site

    • Add fluorine

by Hua Lv, Wei Zhu and Hong Shen

  • Strategies to mitigate CYP3A4 induction mediated by pregnane X receptor (PXR) activation; the pharmacophore of human PXR (hPXR) agonists comprises an essential H-bond acceptor and at least two flanking (preferably aromatic) hydrophobic groups

    • Introduce a polar substituent to the hydrophobic group

    • Remove or replace the key hydrophobic group with a less hydrophobic group

    • Introduce steric hindrance or rigidify the structure

by Alexander G. Dossetter, Marcel J. de Groot and Sarah E. Skerratt

  • Strategies applicable to all CYP isoforms to impede binding of the nitrogen lone pair of an azaheterocycle to the heme group

    • Add a flanking group (e.g. a methyl group) next to an aromatic nitrogen

    • Change the heterocycle

  • 1A2

    • Increase molecular weight

    • Reduce aromaticity

  • 2C9

    • Avoid or reduce negative charge

    • Reduce lipophilicity

  • 2C19

    • Reduce lipophilicity

  • 2D6

    • Avoid or reduce positive charge

    • Reduce lipophilicity

  • 3A4

    • Decrease molecular weight

    • Reduce lipophilicity

    • Add charge; negative charge is most promising

by David C. Pryde, Dharmendra B. Yadav and Rajib Ghosh

  • Preventing oxidation of azaheterocycles featuring an aromatic carbon–hydrogen bond adjacent to an aromatic nitrogen atom

    • Remote functionalization

    • Alternative heterocycles

    • Add a blocking group adjacent to the aromatic nitrogen atom

by Yue Pan

  • Preventing glucuronidation

    • Remove or block the glucuronidation site

    • Use bioisosteres to replace the susceptible moiety

    • Sterically or electronically decrease glucuronidation rate

    • Reduce lipophilicity

    • Sterically disrupt the substrate's binding to uridine 5′-diphospho-glucuronosyltransferase (UGT)

    • Protect the soft spot as a prodrug

by Yue Pan

  • Preventing sulfation

    • Remove or block the sulfation site

    • Use bioisosteres to replace the susceptible moiety

    • Sterically or electronically decrease the sulfation rate

    • Reduce lipophilicity

    • Increase the size of the molecule to disrupt binding to sulfotransferase (SULT)

by Amit S. Kalgutkar

  • Mitigation of epoxidation of (hetero-)aromatic ring and double or triple bonds

    • Introduce innocuous metabolic soft spots

    • Replacement

    • Disfavor metabolic oxidation by reducing electron density

  • Mitigation of electron-deficient double (and triple) bonds, including quinones, quinone-methides, quinone-imines, imine-methides, diimines, classical Michael acceptors and iminium ions

    • Iminium ions

      • Structural modifications to prevent formation

      • Electronically disfavor stabilization

    • Quinones, quinone-imines, quinone-methides, diimines, imine-methides

      • Prevent formation by blocking metabolic soft spot (e.g. para or ortho position of six-membered rings, or benzylic position)

      • Disfavor metabolic oxidation by reducing electron density

    • Michael acceptors

      • Decrease electrophilicity by increasing electron-density

      • Prevent formation by metabolic oxidation followed by elimination reaction (e.g. by blocking oxidation of the β-position or replacing a proton in the α-position)

  • Reduce reactivity of acyl glucuronides of aliphatic carboxylic acids towards nucleophiles by alkyl substitution at the α-carbon

by Stephan Kirchner and Patrick Schnider

  • Avoiding the formation of aryl nitrenium ions

    • Reduce electron density of the aromatic ring to reduce nitrenium ion stabilization

    • Break or reduce conjugation

    • Impede metabolism of the amino or nitro group by steric shielding or remote substitution

    • Introduce innocuous metabolic soft spots

    • Prevent the release of an aromatic amine (e.g. from an amide or N-aryl heterocycle) by N-substitution, electronic or steric modifications of the aryl group, or replacement or modification of the amide or heterocycle

  • Avoiding alkylating agents

    • Avoid alkyl or acyl moieties substituted with good leaving groups

      • Strain in three- and four-membered rings increases reactivity

      • Ensure complete removal of alkylating agents used during synthesis

    • Prevent the metabolic formation of epoxides, Michael-type acceptors and iminium ions (cf. Chapter 15)

  • Avoiding intercalation and minor groove binding

    • Reduce planarity or aromaticity

    • Introduce bulky substituents

    • Increase electron density of the aryl system

    • Reduce positive charge

    • Disrupt hydrogen bonding (mainly minor groove binders)

  • Optimization against binding to the ATP site of kinases regulating the cell cycle

    • Modify hydrogen bond (donor–)acceptor(–donor) hinge-binding motif

by Jean-François Fournier

  • Decrease intrinsic property forecast index (iPFI): Reduce lipophilicity and number of aromatic rings

  • Break conjugation

  • Remove an aryl halogen atom

  • Introduce an intramolecular radical scavenger

  • Subtle structural modifications, e.g. change positional isomers

by Laura Goracci and Gabriele Cruciani

  • Reduce basicity

  • Reduce lipophilicity

  • Reduce amphiphilicity

  • Modulation of metabolism

    • Improve metabolism which decreases the potential of a drug to induce phospholipidosis by reduction of overall lipophilicity and basicity

    • Avoid the formation of metabolites that induce phospholipidosis more strongly (and may have a lower clearance and consequently a tendency to accumulate) than the parent, e.g. a secondary amine metabolite from a tertiary amine or an amine metabolite from deacylation

by Cinzia Bordoni, Daniel J. Brough, Gemma Davison, James H. Hunter, J. Daniel Lopez-Fernandez, Kate McAdam, Duncan C. Miller, Pasquale A. Morese, Alexia Papaioannou, Stefan Schunk, Mélanie Uguen, Paul Ratcliffe, Nikolay Sitnikov and Michael J. Waring

  • Voltage-gated sodium channel 1.5 (NaV1.5 channel) inhibition

    • Reduce lipophilicity

    • Reduce or eliminate basicity

    • Modify (hetero)aromatic rings and/or (hetero)aromatic substitution pattern

    • Disrupt binding by introduction of steric clashes

  • Voltage-gated calcium channel 1.2 (CaV1.2 channel) inhibition

    • Reduce lipophilicity

    • Reduce or eliminate basicity

    • Modify (hetero)aromatic rings and/or (hetero)aromatic substitution pattern

  • Human ether-à-go-go-related gene (hERG) potassium channel inhibition

    • Reduce lipophilicity

    • Reduce or eliminate basicity

    • Introduce acidic centres

    • Reduce the number of aromatic rings

    • Modify (hetero)aromatic rings and/or (hetero)aromatic substitution pattern

    • Disrupt binding by introduction of steric clashes and changes in conformation

Key References
  • M. P. Gleeson, J. Med. Chem., 2008, 51, 817–834.

    • Guidance on the impact of lipophilicity, molecular weight and ionization state on key ADMET properties based on an analysis of large data sets.

  • M. J. Waring, Expert Opin. Drug Discovery, 2010, 5, 235–248.

    • Comprehensive review of lipophilicity concluding that issues and risks related to ADMET properties are minimized best in the logD range between ca. 1 and 3.

  • R. J. Young, D. V. S. Green, C. N. Luscombe and A. P. Hill, Drug Discovery Today, 2011, 16, 822–830.

    • Discussion of the relative influence of intrinsic and effective lipophilicity on key ADMET properties and of the sum of logP/D and aromatic ring count as a composite index to predict developability.

  • M. M. Hann and G. M. Keserü, Nat. Rev. Drug Discovery, 2012, 11, 355–365.

    • Guide on how to effectively apply existing knowledge of key trends and principles in a holistic way to find the “sweet spot”.

  • M. V. Varma, S. J. Steyn, C. Allerton and A. F. El-Kattan, Pharm. Res., 2015, 32, 3785–3802.

    • Introduction of the Extended Clearance Classification System (ECCS) for the prediction of the predominant clearance mechanism based on physicochemical properties and passive permeability.

  • T. S. Maurer, D. Smith, K. Beaumont and L. Di, J. Med. Chem., 2020, 63, 6423–6435.

    • Overview of the opportunities and challenges associated with dose prediction, the most holistic metric reflecting a compounds potential to become a drug.

Table 1.1

High-level overview of the effects of key molecular properties on ADMET properties

ADMET propertyLipophilicityChargeMolecular weightAromatic/planar ringsHBDHBA
Solubility ↑ ↓ ↑  ↓ planarity/ring count ↑/↓ ↑/↓ 
Plasma protein binding ↓ ↓ (positive, neutral) ↓ negative ↓ ↓   
Volume of distribution ↓ ↓ (positive, neutral) ↓ positive (↑negative) (↓)    
Passive permeability ↑ ↑ ↓ negative ↓  ↓ (↓) 
P-glycoprotein (and BCRP) ↓ Efflux (↑) ↓ ↓  ↓ (↓) 
OCTs ↓ Transport ↑ ↓ positive ↑    
↓ Inhibition ↓ ↓ positive ↓    
OATs ↓ Transport ↑ ↓ negative ↑    
↓ Inhibition ↓ ↓ negative ↓    
OATPs ↓ Transport ↑ ↓ negative ↓    
↓ Inhibition ↓ ↓ negative ↓   ↓ 
BSEP ↓ Inhibition ↓ (↓ negative, ↑ positive) ↓  ↑  
CYP450 metabolism ↓ Metabolism ↓      
CYP450 induction ↓ 3A4 induction (↓)   (↓ ring count)   
CYP450 inhibition ↓ 1A2 inhibition   ↑ ↓   
↓ 2C9 inhibition ↓ ↓ negative     
↓ 2C19 inhibition ↓      
↓ 2D6 inhibition ↓ ↓ positive     
↓ 3A4 inhibition ↓ ↑ (negative) ↓    
Glucuronidation ↓ Conjugation ↓    (↓ block/remove/protect glucuronidation site)  
Sulfation ↓ Conjugation ↓  ↑  (↓ block/remove/protect sulfation site)  
Reactive metabolites ↓ Metabolism ↓   prevent aromatic ring oxidation: replace/modify   
Genotoxicity ↓ Reactive metabolite formation ↑/↓  ↑ (especially aromatic amines) ↓ break or reduce conjugation (especially aromatic amines)   
↓ Intercalation/minor groove binding ↑/↓ ↓ positive (↑) ↓ reduce planarity or aromaticity ↓ (especially groove binding) (↓) 
↓ Kinase inhibition     modify hinge-binding (donor–)acceptor(–donor) motif 
Photosensitivity ↓ Photosensitivity ↓   ↓ reduce number of rings, break aromaticity   
Phospholipidosis ↓ Phospholipidosis ↓ ↓ positive     
Cardiac ion channels ↓ NaV1.5 inhibition ↓ ↓ positive  modify rings/substitution   
↓ CaV1.2 inhibition ↓ ↓ positive  modify rings/substitution   
↓ hERG inhibition ↓ ↓ positive, ↑ negative  ↓ number of rings, modify rings/substitution   
ADMET propertyLipophilicityChargeMolecular weightAromatic/planar ringsHBDHBA
Solubility ↑ ↓ ↑  ↓ planarity/ring count ↑/↓ ↑/↓ 
Plasma protein binding ↓ ↓ (positive, neutral) ↓ negative ↓ ↓   
Volume of distribution ↓ ↓ (positive, neutral) ↓ positive (↑negative) (↓)    
Passive permeability ↑ ↑ ↓ negative ↓  ↓ (↓) 
P-glycoprotein (and BCRP) ↓ Efflux (↑) ↓ ↓  ↓ (↓) 
OCTs ↓ Transport ↑ ↓ positive ↑    
↓ Inhibition ↓ ↓ positive ↓    
OATs ↓ Transport ↑ ↓ negative ↑    
↓ Inhibition ↓ ↓ negative ↓    
OATPs ↓ Transport ↑ ↓ negative ↓    
↓ Inhibition ↓ ↓ negative ↓   ↓ 
BSEP ↓ Inhibition ↓ (↓ negative, ↑ positive) ↓  ↑  
CYP450 metabolism ↓ Metabolism ↓      
CYP450 induction ↓ 3A4 induction (↓)   (↓ ring count)   
CYP450 inhibition ↓ 1A2 inhibition   ↑ ↓   
↓ 2C9 inhibition ↓ ↓ negative     
↓ 2C19 inhibition ↓      
↓ 2D6 inhibition ↓ ↓ positive     
↓ 3A4 inhibition ↓ ↑ (negative) ↓    
Glucuronidation ↓ Conjugation ↓    (↓ block/remove/protect glucuronidation site)  
Sulfation ↓ Conjugation ↓  ↑  (↓ block/remove/protect sulfation site)  
Reactive metabolites ↓ Metabolism ↓   prevent aromatic ring oxidation: replace/modify   
Genotoxicity ↓ Reactive metabolite formation ↑/↓  ↑ (especially aromatic amines) ↓ break or reduce conjugation (especially aromatic amines)   
↓ Intercalation/minor groove binding ↑/↓ ↓ positive (↑) ↓ reduce planarity or aromaticity ↓ (especially groove binding) (↓) 
↓ Kinase inhibition     modify hinge-binding (donor–)acceptor(–donor) motif 
Photosensitivity ↓ Photosensitivity ↓   ↓ reduce number of rings, break aromaticity   
Phospholipidosis ↓ Phospholipidosis ↓ ↓ positive     
Cardiac ion channels ↓ NaV1.5 inhibition ↓ ↓ positive  modify rings/substitution   
↓ CaV1.2 inhibition ↓ ↓ positive  modify rings/substitution   
↓ hERG inhibition ↓ ↓ positive, ↑ negative  ↓ number of rings, modify rings/substitution   
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