Relating molecular properties and in vitro assay results to in vivo drug disposition and toxicity outcomes

A primary goal of lead optimization is to identify compounds with improved absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. A number of reports have linked computed molecular properties to desirable in vivo ADMET outcomes, but a significant limitation of these analyses is the failure to control statistically for possible covariates. We examine the relationship between molecular properties and in vitro surrogate assays vs in vivo properties within 173 chemical series from a database of 3773 compounds with rodent pharmacokinetic and toxicology data. This approach identifies the following pairs of surrogates as most predictive among those examined: rat primary hepatocyte (RPH) cytolethality/volume of distribution (V(d)) for in vivo toxicology outcomes, scaled microsome metabolism/calculated logP for in vivo unbound clearance, and calculated logD/kinetic aqueous solubility for thermodynamic solubility. The impact of common functional group substitutions is examined and provides insights for compound design.     

Toward in silico structure-based ADMET prediction in drug discovery

Quantitative structure-activity relationship (QSAR) methods and related approaches have been used to investigate the molecular features that influence the absorption, distribution, metabolism, excretion and toxicity (ADMET) of drugs. As the three-dimensional structures of several major ADMET proteins become available, structure-based (docking-scoring) computations can be carried out to complement or to go beyond QSAR studies. Applying docking-scoring methods to ADMET proteins is a challenging process because they usually have a large and flexible binding cavity; however, promising results relating to metabolizing enzymes have been reported. After reviewing current trends in the field we applied structure-based methods in the context of receptor flexibility in a case study involving the phase II metabolizing sulfotransferases. Overall, the explored concepts and results suggested that structure-based ADMET profiling will probably join the mainstream during the coming years.     

Determination of n-octanol/water partition and membrane binding of cationic porphyrins

Porphyrin and their derivatives are being systematically studied as photosensitizers for photodynamic therapy. The ability to predict their membrane partition properties is of key importance to unveil their in vivo activity and applications. Several n-octanol/water partition coefficients (logP(OW)) of porphyrin derivatives have been reported in the literature but large discrepancies have been observed. Reproducible and reliable logP(OW) data for a series of 20 cationic meso-phenyl(pyridyl)porphyrin derivatives were determined by correlating logP(OW) with the partition coefficients measured in a more adequate n-butanol/water system. Linear correlations as a function of the number of positively charged groups bound to the periphery of the porphyrin rings were found within each series. A significant effect of the stereochemistry and nature of the positively charged substituents was also observed, but diminished steadily converging to a similar value in the mono-substituted derivatives. Binding constants to liposomes were shown to be proportional to logP(OW), except for the cis-isomers of doubly charged porphyrins. The cis-isomer presented smaller logP(OW) and higher membrane affinity. The effect was explained based on the amphiphilic nature of the cis-porphyrin.     

Drug clearance during Continuous Veno-Venous Hemofiltration (CVVH). A mathematical model based on ex-vivo experiments

Introduction:

Continuous veno-venous hemofiltration (CVVH) with an AN69 membrane is used in hemodynamical unstable patients with acute renal failure admitted to the Intensive Care Unit (ICU) of the Catharina Hospital in Eindhoven (CHE), the Netherlands. Literature search revealed that only the clearance and kinetics of some antibiotics during CVVH were studied. Data obtained with different renal replacement techniques and membranes can’t easily be extrapolated to CVVH with an AN69 membrane. (Reetze-Bonorden et al., 1993; Mueller et al., 2003) Due to the lack of clinical research data, dosages in patients treated with CVVH at the ICU of the CHE or are not adjusted or are adjusted on the base of the empirical determined creatinin clearance of 30 ml/min. For aminoglycosides and vancomycin dose adjustment is performed applying therapeutic drug monitoring. Because of this a lot of drugs are possibly suboptimal dosed during CVVH.

Aim:

The aim of this study was to develop a predictive mathematical model based on ex-vivo experiments for the drug clearance by CVVH with an AN69 high-flux membrane.

Methods:

The experimental set-up consisted of a PRISMA CFM hemofiltration machine with a AN69 HF 0,9 m², 500 ml heparinised bovine blood as blood compartment, blood flow rate 150 ml/min and ultrafiltration rate 1500 ml/h. The following drugs were added to the blood compartment in therapeutic concentrations, covering a broad range in molecular weight (Mw), % protein binding (%PB), logP and charge (C): amiodarone, amitriptyline, carbamazepine, cyclosporine, clozapine, digoxin, phenobarbital, phenytoin, gentamycin, midazolam, acetaminophen, theophylline, tobramycin, valproic acid and vancomycin. The sieving coefficient (SC) was calculated by SC=(2x concentration ultrafiltrate) / (concentration post membrane + concentration pre membrane).

Results:

All four parameters; %PB, logP, C and Mw contributed statistically significant (p < 0,05) to the SC. The regression line, explaining 75% of the variance (R²=0,751) is:

Conclusion:

Based on the ex-vivo experiments a mathematical model has been extracted to predict a-priori the sieving coefficient of drugs during CVVH with an AN69 high-flux membrane on the base of protein binding, charge, logP and molecular weight. This model has to be validated in vivo and can then be used, if valid, for drugs which physico-chemical properties in the ranges studied: p%PB 0 − 98%, logP −7,32 – 7, Mw 151 – 1500, C −1 – 3.     

Cellular models for ADMET predictions and evaluation of drug-drug interactions

Deficiencies in ADMET (absorption, distribution, metabolism, excretion and toxicity) properties and drug-drug interactions are collectively the major causes of attrition during drug development. As such, assays have been developed with which to study and optimize these key properties in early dug discovery. While screening using systems expressing discrete proteins have provided valuable insight, quantitative structure-activity relationships (QSARs) and predictive computational models, the ability to study several processes in tandem is paramount to in vivo projection. In particular, the key role of transporter proteins in controlling access to drug metabolizing enzymes and other intracellular processes cannot be overlooked. In this respect, cellular models provide a key platform to study the complex interplay between xenobiotic transport and metabolism, which underlie many ADMET issues. In addition, uptake and accumulation in tissues may provide a mechanistic insight into false negatives arising from simple, primary screens, for example, cytochrome P450 (CYP) inhibition analysis. Qualitative and quantitative interspecies differences in the regulation, expression and functional activity of key ADMET processes confound extrapolation from animals to man. However, complementary screens using animal and human material may assist the interpretation of safety assessment findings and help project the risk for early human studies.     

Quantitative structure-activity relationships (QSARs) within cytochromes P450 2B (CYP2B) subfamily enzymes: the importance of lipophilicity for binding and metabolism

The results of qualitative structure-activity relationship (QSAR) analysis are reported for several series of compounds which act as substrates for mammalian CYP2B subfamily enzymes, together with a homologous series of aliphatic primary amines which are known to inhibit CYP2B enzymes. It is found that the compound lipophilicity in the form of the log P value (where P is the octanol/water partition coefficient) is related, either linearly or quadratically, to equilibrium constants of inhibition (Ki), binding (Ks) or metabolism (Km) depending on the series of compounds in question. In some instances, the difference between frontier orbital energy levels (deltaE) also features in several of the log P expressions with biological activity. Also present in a small number of correlations are parameters which are likely to be related to logP: namely, Rm, which is the partitioning factor derived from thin layer chromatography (TLC) retention times, and also the compound molecular weight (Mr). All of these three parameters ((log P, Rm and Mr) are thought to be related to the compound's ability to desolvate the P450 active site when they bind to the enzyme. Although the linear relationships between lipophilicity and CYP2B-related activity point to a major role for desolvation of the enzyme binding site in the overall interaction, it is noted that there may be an optimal log P value displayed by preferred substrates as shown by parabolic relationships with this lipophilic parameter. In addition, there is a remarkable similarity in the coefficients for the log P term of any QSAR expression, which suggests that the hydrophobicity of CYP2B active sites may be broadly equivalent between the various mammalian species.     

Molecular lipophilicity determination of a huperzine series by HPLC: comparison of C18 and IAM stationary phases

Two hydrophobic parameters (logkw-C18 and logkw-IAM, respectively) of a huperzine A series were extrapolated by high performance liquid chromatography (HPLC) using both C18 and immobilised artificial membrane (IAM) columns. A mathematical correlation between C18 and IAM hydrophobic parameters was completed, suggesting a similar behaviour on both columns. This behaviour was principally led by hydrophobic forces. The theoretical lipophilicity (logP) of each compound was computed using Pallas software and compared to experimental values, showing a similar lipophilic behaviour. Finally, the huperzine logkw-IAM and logkw-C18 values were correlated with the relative bound percentage of huperzine in human serum albumin, confirming that hydrophobic forces are predominant in the huperzine-HSA binding mechanism.     

Insights into structure-activity relationships from lipophilicity profiles of pyridin-2(1H)-one analogs of the cardiotonic agent milrinone.

The pH-dependent distribution profiles of a series of pyridin-2(1H)-one analogs of the inotropic/vasodilator agent milrinone, determined in 1-octanol/water (and for a number of them also in chloroform-water) using a pH-metric technique, showed that partition coefficients of the neutral forms (logP(N)) significantly encode for 2-pyridone/2-hydroxypyridine tautomerism. A comparison between experimental and calculated logP (CLOG P) values indicated that electron-withdrawing substituents, at the C(6) position, and to a lesser extent at the C(3) and C(5) positions, push up logPs toward the values of the more lipophilic 2-hydroxypyridine tautomers. RP-HPLC parameters (log k'omega) carry for large part similar information related to tautomerism-dependent lipophilicity, but they were also found to reasonably correlate with the solute molar volumes (r2 = 0.75). Investigating the implications of ionization and partition properties in modulating the in vitro cardiotonic activity of the examined compounds revealed that a high fraction of the neutral species at physiological pH, predominantly in the more polar pyridone (OX) tautomer, increases the positive inotropic potency.     

石斛酚与丁香酸的ADMET分子模拟预测

目的分子模拟预测石斛酚与丁香酸的吸收、分布、代谢、排泄和毒理性(ADMET),为进一步开发研究奠定基础。方法采用DS2.1中ADMET模块,从吸收性、水溶性、血脑屏障穿透性、与人细胞色素P450 2D6酶结合、肝毒性、与血浆蛋白结合6个方面进行测定。结果石斛酚的肝毒性比标准稍高,石斛酚与丁香酸的其他各方面的预测值都在正常范围内。结论石斛酚、丁香酸的ADMET测定结果符合药物研究开发的标准,可作为新药进一步研究。     

基于系统药理学方法的苓桂术甘汤治疗NAFLD的关键成分挖掘及协同机制分析

目的：从系统药理学视角结合计算方法,深入解析中药复方苓桂术甘汤（LZD）中的主要有效活性成分对非酒精性脂肪性肝病（nonalcoholic fatty liver disease,NAFLD）的分子作用机制及其协同性。方法：应用TCMSP数据库以及PubChem中检索出LZD的主要化学成分,使用ACD/Labs软件对LZD主要化学成分进行ADMET筛选;从GeneCards、OMIM、DisGeNET等数据库收集NAFLD相关的作用靶点,运用SEA、HitPick靶点预测系统依次检索各活性成分的潜在作用靶点,通过取两者交集获得LZD治疗NAFLD的潜在作用靶点集,同时,提出利用最小集合覆盖算法（SCP）优化出LZD治疗NAFLD的关键成分集;进一步利用STRING数据库获得LZD潜在作用靶点的PPI网络,通过基于网络距离的计算方法发现LZD关键成分之间的协同治疗作用;最后,利用DAVID平台进行GO功能注释和KEGG信号通路富集分析。结果：通过ADMET筛选、靶点预测与识别,筛选出LZD中主要活性成分116个及其作用的78个潜在NAFLD靶点;利用SCP算法优化出LZD中的22个关键成分;对基于STRING构建的PPI网络分析,发现2个核心子模块,同时利用网络扰动计算方法,发现LZD中22个关键成分中有14个成分之间存在协同治疗作用;KEGG通路富集分析,显示LZD主要通过25条相关信号通路,主要涉及：乙型肝炎（hepatitis B）、TNF、丙型肝炎（hepatitis C）、HIF-1等;最后,分子对接验证显示,LZD中的Quercetin、2-methoxyphenylacetone、cinnamic acid、methyl cinnamate、dimethyl phthalate、diethyl phthalate等有效成分与AKT1、CXCL8、JUN、MAPK8、TNF等5个重要靶点均具有较好的结合力。结论：本研究初步揭示了LZD的药效物质基础,探讨了LZD的药理作用机制,为LZD的临床应用以及实验研究提供了重要参考依据。     

Stability of atenolol, acebutolol and propranolol in acidic environment depending on its diversified polarity

The main objective of this research was to investigate the relationship between the polarity of atenolol, acebutolol, and propranolol described by logP and kinetic and thermodynamic parameters characterizing their degradation process in acidic solution. Hydrolysis was carried out in hydrochloric acid at molal concentrations of 0.1 mol/L, 0.5 mol/L, and 1 mol/L for 2 hr at 40 degrees C, 60 degrees C, and 90 degrees C. Chromatographic-densitometric method was used for the determination of drugs under investigation. The identification of degradation products was carried out by using 1H NMR. The degradation processes that occurred in drugs under investigation are described with kinetic parameters (k, t0.1, and t0.5) and energy of activation (Ea). It has been found that the stability of drugs increases toward lipophilic propranolol in the assumed experimental model. The rate constants k decrease, contrary to t0.1, t0.5, and Ea, which vary comparably to logP, thus increasing from the most hydrophilic atenolol, through acebutolol, of lower polarity, to the most lipophilic propranolol. This study demonstrated that the stability of chosen beta-adrenergic blocking agents increases with their lipophilicity.     

A QSAR model for the eye irritation of cationic surfactants.

A QSAR model for the eye irritation of cationic surfactants has been constructed using a dataset consisting of the maximum average scores (MAS-accordance to Draize) for 29 in vivo rabbit eye irritation tests on 19 different cationic surfactants. The parameters used were logP (log [octanol/water partition coefficient]) and molecular volume (to model the partition of the surfactants into the membranes of the eye), logCMC (log critical micelle concentration-a measure of the reactivity of the surfactants with the eye) together with surfactant concentration. The model was constructed using neural network analysis. MAS showed strongly positive, non-linear correlations with surfactant concentration and logCMC and a strongly negative, non-linear correlation with logP. The Pearson correlation between the actual and predicted values of MAS was 0.838 showing that around 70% (r(2)=0.702) of the variance in the dataset is explained by the model. This value is consistent with levels of biological variability reported historically for the Draize rabbit eye test. The relationship provides a potentially useful prediction model for the eye irritation potential of new or untested cationic surfactants with physicochemical properties lying within the parameter space of the model.     

Utility of protein structures in overcoming ADMET-related issues of drug-like compounds

The number of solved X-ray structures of proteins relevant for ADMET processes of drug molecules has increased remarkably over recent years. In principle, this development offers the possibility to complement the quantitative structure-property relationship (QSPR)-dominated repertoire of in silico ADMET methods with protein-structure-based approaches. However, the complex nature and the weak nonspecific ligand-binding properties of ADMET proteins take structural biology methods and current docking programs to the limit. In this review we discuss the utility of protein-structure-based design and docking approaches aimed at overcoming issues related to plasma protein binding, active transport via P-glycoprotein, hERG channel mediated cardiotoxicity and cytochrome P450 inhibition, metabolism and induction.