Drug-like Properties and Fraction Lipophilicity Index as a combined metric

Fraction Lipophicity Index (FLI) has been developed as a composite drug-like metric combining logP and logD in a weighted manner. In the present study an extended data set confirmed the previously established drug-like FLI range 0-8 using two calculation systems for logP /logD assessment, the freeware MedChem Designer and ClogP. The dataset was split into two classes according to percentage of fraction absorbed (%FA) - class 1 including drugs with high to medium absorption levels and class 2 including poorly absorbed drugs. The FLI and FLI© (ClogP based FLI) drug-like range covers 93% and 90 % of class 1 drugs, respectively. The dependence of the degree of ionization to intrinsic lipophilicity within the FLI (FLI©) drug-like range as well as the inter-relation between the other Ro5 properties (Mw, HD, HA) was explored, so as to define drug-like / non drug-like combinations as a safer alternative to single properties for drug candidates’ prioritization. In this sense we propose a combined metric of Mw and number of polar atoms (Mw/NO) to account for both size and polarity. Setting the value 50 as cut off, a distinct differentiation between class 1 and class 2 drugs was obtained with Mw/NO>50 for more than 70% of class 1 drugs, while the opposite was observed for class 2 drugs

Peroxisome Proliferator-Activated Receptor-γ Ligands: Potential Pharmacological Agents for Targeting the Angiogenesis Signaling Cascade in Cancer

Peroxisome proliferator-activated receptor-γ (PPAR-γ) has currently been considered as molecular target for the treatment of human metabolic disorders. Experimental data from in vitro cultures, animal models, and clinical trials have shown that PPAR-γ ligand activation regulates differentiation and induces cell growth arrest and apoptosis in a variety of cancer types. Tumor angiogenesis constitutes a multifaceted process implicated in complex downstream signaling pathways that triggers tumor growth, invasion, and metastasis. In this aspect, accumulating in vitro and in vivo studies have provided extensive evidence that PPAR-γ ligands can function as modulators of the angiogenic signaling cascade. In the current review, the crucial role of PPAR-γ ligands and the underlying mechanisms participating in tumor angiogenesis are summarized. Targeting PPAR-γ may prove to be a potential therapeutic strategy in combined treatments with conventional chemotherapy; however, special attention should be taken as there is also substantial evidence to support that PPAR-γ ligands can enhance angiogenic phenotype in tumoral cells

Immobilized artificial membrane chromatography: from medicinal chemistry to environmental sciences

Immobilized Artificial Membrane (IAM) chromatography constitutes a valuable tool for medicinal chemists to prioritize drug candidates in early drug development. The retention on IAM stationary phases encodes lipophilicity, electrostatic and other secondary interactions contrary to traditional octanol-water partitioning. An increasing number of publications in recent years have suggested that IAM indices, including isocratic log k(IAM) or extrapolated log kw(IAM) retention factors, chromatographic hydrophobicity index CHI(IAM) or the polarity parameter Δlog kw(IAM) can successfully model the passage of xeniobiotics through biological membranes and barriers and predict pharmacokinetic properties, often in combination with additional descriptors. Examples referring to the modeling of human oral absorption, blood-brain penetration and skin partition are described. More recently, IAM chromatography has been applied to estimate toxicological endpoints in regard to drug safety, such as phospholipidosis potential, or in regard to chemical risk hazards including the bioconcentration factor and aquatic organisms’ toxicity. The promising results in both medicinal chemistry and in environmental science in combination with the speed, reproducibility and low analyte consumption suggest that a broader application of IAM chromatography in the early drug discovery process and in ecotoxicity may save time and money in initial drug candidate selection and will contribute to a reduced risk hazard of chemicals

Comparison of thermal effects of stilbenoid analogs in lipid bilayers using differential scanning calorimetry and molecular dynamics: correlation of thermal effects and topographical position with antioxidant activity

In previous studies it was shown that cannabinoids (CBs) bearing a phenolic hydroxyl group modify the thermal properties of lipid bilayers more significantly than methylated congeners. These distinct differential properties were attributed to the fact that phenolic hydroxyl groups constitute an anchoring group in the vicinity of the headgroup, while the methylated analogs are embedded deeper towards the hydrophobic region of the lipid bilayers. In this work the thermal effects of synthetic polyphenolic stilbenoid analogs and their methylated congeners have been studied using differential scanning calorimetry (DSC).Molecular dynamics (MD) simulations have been performed to explain the DSC results. Thus, two of their phenolic hydroxyl groups orient in the lipid bilayers in such a way that they anchor in the region of the headgroup. In contrast, their methoxy congeners cannot anchor effectively and are embedded deeper in the hydrophobic segment of the lipid bilayers. The MD results explain the fact that hydroxystilbenoid analogs exert more significant effects on the pretransition than their methoxy congeners, especially at low concentrations. To maximize the polar interactions, the two phenolic hydroxyl groups are localized in the vicinity of the head-group region, directing the remaining hydroxy group in the hydrophobic region. This topographical position of stilbenoid analogs forms a mismatch that explains the significant broadening of the width of the phase transition and lowering of the main phasetransition temperature in the lipid bilayers. At high concentrations, hydroxy and nonhydroxy analogs appear to form different domains. The correlation of thermal effects with antioxidant activity is discusse

The Forty-Sixth Euro Congress on Drug Synthesis and Analysis: Snapshot

The 46th EuroCongress on Drug Synthesis and Analysis (ECDSA-2017) was arranged within the celebration of the 65th Anniversary of the Faculty of Pharmacy at Comenius University in Bratislava, Slovakia from 5-8 September 2017 to get together specialists in medicinal chemistry, organic synthesis, pharmaceutical analysis, screening of bioactive compounds, pharmacology and drug formulations; promote the exchange of scientific results, methods and ideas; and encourage cooperation between researchers from all over the world. The topic of the conference, Drug Synthesis and Analysis, meant that the symposium welcomed all pharmacists and/or researchers (chemists, analysts, biologists) and students interested in scientific work dealing with investigations of biologically active compounds as potential drugs. The authors of this manuscript were plenary speakers and other participants of the symposium and members of their research teams. The following summary highlights the major points/topics of the meeting

Current state of the art in HPLC methodology for lipophilicity assessment of basic drugs.

Abstract: HPLC provides a user's friendly, rapid, and compound sparing methodology, which is successfully applied to determine drug lipophilicity. Under suitable chromatographic conditions isocratic and extrapolated retention factors correlate well with octanol-water partition or distribution coefficients. The present review provides an overview of the stationary and mobile phases, which are preferably used for lipophilicity assessment mainly in the case of basic compounds. Difficulties raised by the interference of silanophilic interactions in the partition mechanism, and the ways proposed to face this problem are discussed. Attention has been given to the extrapolation procedure and the standardization of conditions to obtain 1:1 correlation between extrapolated retention factors and logP or logD. Other chromatographic indices encoding information on the lipophilic behavior are briefly presented. A separate section refers to recent advances in IAM Chromatography, its similarities/dissimilarities with reversed phase HPLC and the octanol-water system, as well as its potential to mimic specific interactions with phospholipids

Prediction Models for Brain Distribution of Drugs Based on Biomimetic Chromatographic Data

The development of high-throughput approaches for the valid estimation of brain disposition is of great importance in the early drug screening of drug candidates. However, the complexity of brain tissue, which is protected by a unique vasculature formation called the blood-brain barrier (BBB), complicates the development of robust in silico models. In addition, most computational approaches focus only on brain permeability data without considering the crucial factors of plasma and tissue binding. In the present study, we combined experimental data obtained by HPLC using three biomimetic columns, i.e., immobilized artificial membranes, human serum albumin, and alpha(1)-acid glycoprotein, with molecular descriptors to model brain disposition of drugs. K-p,K-uu,K-brain, as the ratio between the unbound drug concentration in the brain interstitial fluid to the corresponding plasma concentration, brain permeability, the unbound fraction in the brain, and the brain unbound volume of distribution, was collected from literature. Given the complexity of the investigated biological processes, the extracted models displayed high statistical quality (R-2 > 0.6), while in the case of the brain fraction unbound, the models showed excellent performance (R-2 > 0.9). All models were thoroughly validated, and their applicability domain was estimated. Our approach highlighted the importance of phospholipid, as well as tissue and protein, binding in balance with BBB permeability in brain disposition and suggests biomimetic chromatography as a rapid and simple technique to construct models with experimental evidence for the early evaluation of CNS drug candidates

Application of quantitative structure-activity relationships (QSARs) for modeling drug and chemical transport across the human placenta barrier: A multivariate data analysis approach

Pharmacological agents and environmental pollutants can transfer from mother to fetus across the placental barrier, leading to reproductive toxic effects. Ex vivo human placental perfusion constitutes the most widely used method to study placental transfer and metabolism of drugs and chemicals. The aim of the present study was to evaluate whether quantitative structure-activity relationship (QSAR) methodology could serve as an effective alternative tool to estimate drugs and chemicals transport across the human placental barrier on the basis of easily interpretable molecular, physicochemical and structural properties. Multivariate data analysis (MVDA) was applied to a set of 88 structurally diverse drugs and chemicals to model placental transfer expressed by clearance index values compiled from literature sources. An adequate and robust QSAR model (r2 = 0.73, Q2 = 0.71, RMSEE = 0.15) was established, providing an informative illustration of the contributing physicochemical, molecular and structural properties of the compounds in placental transfer process. Descriptors reflecting the polarity of compounds proved to be the most important with a negative sign. Lipophilicity and, at a lower extent, molecular size parameters exerted positive contribution in the model. Thus, QSAR analysis may be considered as a promising alternative tool to support high-throughput screening of drugs and chemicals in respect to their transport across placental barrier. Copyright © 2009 John Wiley & Sons, Ltd