Can the Internet help to meet the challenges in ADME and e-ADME?

The high-throughput screening (HTS) of large proprietary compound collections and combinatorial libraries has put an increased pressure on getting pharmacokinetic and drug metabolism data as early as possible. Properties related to absorption, distribution, metabolism and excretion (ADME) can be estimated by a range of in vivo and in vitro methods. Most are now available or under development in high(er) throughput modus. In addition progress has been made in in silico methods using various QSAR and modeling techniques using a range of recently introduced descriptors tailored to e-ADME. These approaches are promising as a filter for virtual libraries to decide on synthesis as well as in the selection of compounds for acquisition and screening. This paper will discuss a number of Internet resources relevant to ADME studies and predictions. We have focused on areas related to metabolism including metabolic pathways and P450 metabolism, transporters, bioavailability and absorption, pharmacokinetics and pharmacodynamics, molecular properties and tools for data analysis.

Substructure and whole molecule approaches for calculating log P.

Lipophilicity is a major determinant of pharmacokinetic and pharmacodynamic properties of drug molecules. Correspondingly, there is great interest in medicinal chemistry in developing methods of deriving the quantitative descriptor of lipophilicity, the partition coefficient P, from molecular structure. Roughly, methods for calculating log P can be divided into two major classes: Substructure approaches have in common that molecules are cut into atoms (atom contribution methods) or groups (fragmental methods); summing the single-atom or fragmental contributions (supplemented by applying correction rules in the latter case) results in the final log P. Whole molecule approaches inspect the entire molecule; they use for instance molecular lipophilicity potentials (MLP), topological indices or molecular properties to quantify log P. In this review, representative members of substructure and whole molecule approaches for calculating log P are described; their advantages and shortcomings are discussed. Finally, the predictive power of some calculation methods is compared and a scheme for classifying calculation methods is proposed.

Lipophilicity in PK design: methyl, ethyl, futile.

Lipophilicity, often expressed as distribution coefficients (log D) in octanol/water, is an important physicochemical parameter influencing processes such as oral absorption, brain uptake and various pharmacokinetic (PK) properties. Increasing log D values increases oral absorption, plasma protein binding and volume of distribution. However, more lipophilic compounds also become more vulnerable to P450 metabolism, leading to higher clearance. Molecular size and hydrogen bonding capacity are two other properties often considered as important for membrane permeation and pharmacokinetics. Interrelationships among these physicochemical properties are discussed. Increasing size (molecular weight) often gives higher potency, but inevitably also leads to either higher lipophilicity, and hence poorer dissolution/solubility, or to more hydrogen bonding capacity, which limits oral absorption. Differences in optimal properties between gastrointestinal absorption and uptake into the brain are addressed. Special attention is given to the desired lipophilicity of CNS drugs. In examples using beta-blockers, Ca channel antagonists and peptidic renin inhibitors we will demonstrate how potency and pharmacokinetic properties need to be balanced.

Pharmacokinetics and metabolism in early drug discovery.

The need for high-throughput approaches in absorption, distribution, metabolism and excretion studies is driven by the impact of high-speed chemistry and pharmacological screening. Perhaps an even greater impact is that these studies will, in the future, provide large data sets that can be used to predict biological events related to absorption, bioavailability and metabolism of drugs. Through linking of in silico and in vitro methods, considerable progress has recently been made towards this future perspective. Despite this progress, these approaches do not yet replace in vivo methods.

The fundamental variables of the biopharmaceutics classification system (BCS): a commentary.

Based on in vitro solubility and in vivo permeability drugs can be divided into four groups: class 1 (high permeability, high solubility, HP:HS), class 2 (high permeability, low solubility, HP:LS), class 3 (low permeability, high solubility, LP:HS), and class 4 (low permeability, low solubility, LP:LS) (Amidon et al., 1995; Amidon, G.L., Lennernas, H., Shah, V.P., Olson, J.R., 1995. Pharm. Res. 12, 413-420). The high permeability boundary has been suggested to be 70% (Walter et al., 1996; Walter, E., Janich, S., Roessler, B.J., Hilfinger, J.H., Amidon, G., 1996. J. Pharm. Sci. 85, 1070-1076) or 90% (Hussain et al., 1997; Hussain, A.S., Kaus, L.C., Lesko, L.J., Williams, R.L., 1997. Eur. J. Pharm. Sci. 5 (Suppl. 2), S43-S44), and more recently was compromised by the FDA to 80% human intestinal absorption (Hussain, A.S., 1998. Information presented at the BCS and in vitro-in vivo correlations workshop. Frankfurt/M., Germany, March 1998). The biopharmaceutics classification system (BCS) is now being considered by the FDA to develop new regulatory guidance for bioequivalence studies (Hussain, 1998; Lesko, 1997; Lesko, L.J., 1997. Eur. J. Pharm. Sci. 5 (Suppl. 2), S42). Both properties, solubility and permeability, are being considered as fundamental to define the rate and extent of absorption of the active ingredient of a drug product. However, since both these properties are dependent ones, it may be questioned whether these are indeed sufficiently 'fundamental' or should be further unravelled.

Estimation of permeability by passive diffusion through Caco-2 cell monolayers using the drugs' lipophilicity and molecular weight.

A recently developed, new theoretical absorption model for passive diffusion through biological membranes describing the dependency of membrane permeability on lipophilicity and molecular size, predicts different sigmoid-hyperbolic permeability-lipophilicity relationships for different molecular weight ranges. This model has been tested with experimental in vitro cultured epithelial cell (Caco-2) permeability data for structurally diverse drugs differing in lipophilicity, ionization state and molecular size. These data were pooled with literature values. Using this simple physicochemical approach, the permeability of a compound through Caco-2 cells by passive diffusion can be predicted from the compounds' distribution coefficient in 1-octanol/water (log D(oct)) and its molecular weight (MW). Deviations from this expected behaviour may point to the involvement of biological components in the transport process, which may require further investigations.

Shapes of membrane permeability-lipophilicity curves: extension of theoretical models with an aqueous pore pathway.

The objective of this study was to rationalize the shape of membrane permeability-lipophilicity curves, when considering, in addition to the usual transcellular route, a parallel diffusion pathway through aqueous pores as present in biological membranes. The theoretical influence of different pH in donor and acceptor compartment and the molecular weight on the permeability curves was studied. We combined and extended two previously proposed absorption models, namely one describing diffusion through a simple membrane (two stagnant aqueous and two organic layers in series, no pores) as the sum of the two distribution steps at both membrane interfaces, and a second theoretical model considering the sum of different diffusional resistances through stagnant layers and membrane, respectively. Under certain conditions the equivalence of the two-step distribution model and the diffusional resistance model can be demonstrated. Incorporation of an aqueous diffusion pathway leads to an extended two-step distribution model. This theoretical membrane permeation model will permit a more physicochemical-based interpretation of permeation data and shows that combined log D values and molecular weight are important determinants for membrane transport processes through, e.g. Caco-2 monolayers and the mucosal GI membranes. We have demonstrated that the well-known sigmoidal permeability-lipophilicity relationship should be considered as a molecular weight-dependent set of sigmoidal relationships.

Estimation of blood-brain barrier crossing of drugs using molecular size and shape, and H-bonding descriptors.

The influence of physicochemical properties, including lipophilicity, H-bonding capacity and molecular size and shape descriptors on brain uptake has been investigated using a selection of marketed CNS and CNS-inactive drugs. It is demonstrated that the polar surface area of a drug can be used as a suitable descriptor for the drugs' H-bonding potential. A combination of a H-bonding and a molecular size descriptor, i.e., the major components of lipophilicity and permeability, avoiding knowledge of distribution coefficients, is proposed to estimate brain penetration potential of new drug candidates. Previously reported experimental surface activity data appear to be strongly correlated to molecular size of the drug compounds. Present analysis offers a modern basis for property-based design and targeting of CNS drugs.

Review of theoretical passive drug absorption models: historical background, recent developments and limitations.

In the drug discovery process the optimization of a promising lead to an orally bioavailable drug remains a difficult task. Recent progress in the understanding of the role of physicochemical properties in membrane permeability relevant to important processes such as drug absorption and blood-brain barrier crossing, brings rational drug delivery more within reach. In the last thirty years a number of theoretical transport and absorption models have been developed to describe mathematically how a drug is being passively transported from its site of administration to its site of action and how a compound passes a membrane. The goal of such models is to rationalize the physical significance of the observed non-linear structure-permeability relationships. The models are based on various views on the composition of the biological membranes and on the underlying diffusion and distribution mechanisms. Often simplifications reducing the mathematical complexity are made. We review here a selection of the most important models and discuss modern views on the role of lipophilicity and various pathways through membranes.

The prediction of the lipophilicity of peptidomimetics. A comparison between experimental and theoretical lipophilicity values of renin inhibitors and their building blocks.

In order to test how well the lipophilicity of large and flexible molecules can be predicted by theoretical approaches, renin inhibitors and their building blocks have been investigated. Different experimental methods have been used for the determination of lipophilicity of the selected compounds, including RP-HPLC and a new pH-metric or two-phase titration method. This latter method appears to be well-suited for the log P measurement of lipophilic compounds. The experimental results have been compared to computer-assisted log P calculations (CLOGP and PrologP). Different correction terms have been introduced to correlate the experimental to the calculated results. Finally, in view of the poor oral bioavailability of most renin inhibitors, we have investigated the correlation between aqueous solubility data and their log P values.

Structure-lipophilicity relationships of peptides and peptidomimetics.

Understanding the physicochemical and structural properties of peptides are important prerequisites for the rational design of bioactive peptides and peptidomimetics. The present contribution reviews methods used for the assessment and prediction of lipophilicity (or hydrophobicity) and their correlation with structural elements of peptides and closely related peptidomimetics.

Lipophilicity of amino acids.

The lipophilicity (or hydrophobicity) of amino acids is an important property relevant for protein folding and therefore of great interest in protein engineering. For peptides or peptidomimetics of potential therapeutic interest, lipophilicity is related to absorption and distribution, and thus indirectly relates to their bioactivity. A rationalization of peptide lipophilicity requires basic knowledge of the lipophilicity of the constituting amino acids. In the present contribution we will review methods to measure or calculate the lipophilicities of amino acids, including unusual amino acids, and we will make a comparison between various lipophilicity scales.

Recent progress in QSAR-technology.

A short overview is given of some key developments in the field of structure-property correlations (SPC). Important improvements in hard- and software, as well as in methodology has given the chemist a number of tools permitting a rapid testing of structure-property ideas and which may be highly useful in unravelling the most relevant molecular properties in a particular series of compounds. Two main topics will be treated: method development and the use and understanding of molecular descriptors in SPC studies.

Pattern recognition study of QSAR substituent descriptors.

Parameter values for 59 common substituents and 74 descriptors used in QSAR studies were compiled. This data matrix was analysed by a variety of multivariate techniques. Linear regression confirmed that lipophilicity can be factorized into two terms, one related to molecular bulk and the other to polarity. Principal component analysis (PCA) of parameters revealed 5 significant principal components and a grouping of lipophilic, steric and electronic parameters. The different loadings of parameters with 5 PCA were also explored. The classification of substituents by cluster analysis (CA) proved rather disappointing. In contrast, the SIMCA method classified substituents of increasing bulk into 5 groups of increasing polarity.