- 1.1 Introduction
- 1.2 Strategies by ADMET Properties
- 1.2.1 Tactics to Improve Solubility (Chapter 2)
- 1.2.2 Optimisation of Passive Permeability for Oral Absorption (Chapter 3)
- 1.2.3 Targeting Gastrointestinal Uptake Transporters (Chapter 4)
- 1.2.4 Drug Efflux Transporters: P-gp and BCRP (Chapter 5)
- 1.2.5 OATs and OCTs: The SLC22 Family of Organic Anion and Cation Transporters (Chapter 6)
- 1.2.6 OATPs: The SLCO Family of Organic Anion Transporting Polypeptide Transporters (Chapter 7)
- 1.2.7 Bile Salt Export Pump (BSEP) Inhibition (Chapter 8)
- 1.2.8 Cytochrome P450 Metabolism (Chapter 9)
- 1.2.9 Cytochrome P450 Induction (Chapter 10)
- 1.2.10 Strategies to Mitigate CYP450 Inhibition (Chapter 11)
- 1.2.11 Aldehyde and Xanthine Oxidase Metabolism (Chapter 12)
- 1.2.12 Glucuronidation (Chapter 13)
- 1.2.13 Sulfation (Chapter 14)
- 1.2.14 Reactive Metabolites (Chapter 15)
- 1.2.15 Genotoxicity (Chapter 16)
- 1.2.16 Drug-induced Photosensitivity (Chapter 17)
- 1.2.17 Drug-induced Phospholipidosis (Chapter 18)
- 1.2.18 Cardiac Ion Channel Inhibition (Chapter 19)
- 1.3 Strategies by Molecular Properties
- References
CHAPTER 1: Overview of Strategies for Solving ADMET Challenges Free
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Published:20 Aug 2021
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Special Collection: 2021 ebook collectionSeries: Drug Discovery Series
P. Schnider, in The Medicinal Chemist's Guide to Solving ADMET Challenges, ed. P. Schnider, The Royal Society of Chemistry, 2021, pp. 1-15.
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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.
1.1 Introduction
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.
1.2 Strategies by ADMET Properties
1.2.1 Tactics to Improve Solubility (Chapter 2)
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
1.2.2 Optimisation of Passive Permeability for Oral Absorption (Chapter 3)
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
1.2.3 Targeting Gastrointestinal Uptake Transporters (Chapter 4)
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
1.2.4 Drug Efflux Transporters: P-gp and BCRP (Chapter 5)
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
1.2.5 OATs and OCTs: The SLC22 Family of Organic Anion and Cation Transporters (Chapter 6)
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
1.2.6 OATPs: The SLCO Family of Organic Anion Transporting Polypeptide Transporters (Chapter 7)
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
1.2.7 Bile Salt Export Pump (BSEP) Inhibition (Chapter 8)
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
1.2.8 Cytochrome P450 Metabolism (Chapter 9)
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
1.2.9 Cytochrome P450 Induction (Chapter 10)
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
1.2.10 Strategies to Mitigate CYP450 Inhibition (Chapter 11)
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
1.2.11 Aldehyde and Xanthine Oxidase Metabolism (Chapter 12)
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
1.2.12 Glucuronidation (Chapter 13)
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
1.2.13 Sulfation (Chapter 14)
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)
1.2.14 Reactive Metabolites (Chapter 15)
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
1.2.15 Genotoxicity (Chapter 16)
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
1.2.16 Drug-induced Photosensitivity (Chapter 17)
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
1.2.17 Drug-induced Phospholipidosis (Chapter 18)
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
1.2.18 Cardiac Ion Channel Inhibition (Chapter 19)
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.
1.3 Strategies by Molecular Properties
High-level overview of the effects of key molecular properties on ADMET properties
ADMET property . | Lipophilicity . | Charge . | Molecular weight . | Aromatic/planar rings . | HBD . | HBA . | |
---|---|---|---|---|---|---|---|
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 property . | Lipophilicity . | Charge . | Molecular weight . | Aromatic/planar rings . | HBD . | HBA . | |
---|---|---|---|---|---|---|---|
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 |