Influence of molecular properties on oral bioavailability of lipophilic drugs - mapping of bulkiness and different measures of polarity

Evaluating physiochemical properties of FDA-approved orally administered drugs

INTRODUCTION

Analyses of orally administered FDA-approved drugs from 1990 to 1993 enabled the identification of a set of physiochemical properties known as Lipinski's Rule of Five (Ro5). The original Ro5 and extended versions still remain the reference criteria for drug development programs. Since many bioactive compounds do not conform to the Ro5, we validated the relevance of and adherence to these rulesets in a contemporary cohort of FDA-approved drugs.

AREAS COVERED

The authors noted that a significant proportion of FDA-approved orally administered parent compounds from 2011 to 2022 deviate from the original Ro5 criteria (~38%) or the Ro5 with extensions (~53%). They then evaluated if a contemporary Ro5 criteria (cRo5) could be devised to better predict oral bioavailability. Furthermore, they discuss many case studies showcasing the need for and benefit of increasing the size of certain compounds and cover several evolving strategies for improving oral bioavailability.

EXPERT OPINION

Despite many revisions to the Ro5, the authors find that no single proposed physiochemical rule has universal concordance with absolute oral bioavailability. Innovations in drug delivery and formulation have dramatically expanded the range of physicochemical properties and the chemical diversity for oral administration.

Synthesis of 10-O-aryl-substituted berberine derivatives by Chan-Evans-Lam coupling and investigation of their DNA-binding properties

Eleven novel 10-O-aryl-substituted berberrubine and berberine derivatives were synthesized by the Cu2+-catalyzed Chan-Evans-Lam coupling of berberrubine with arylboronic acids and subsequent 9-O-methylation. The reaction is likely introduced by the Cu2+-induced demethylation of berberrubine and subsequent arylation of the resulting 10-oxyanion functionality. Thus, this synthetic route represents the first successful Cu-mediated coupling reaction of berberine substrates. The DNA-binding properties of the 10-O-arylberberine derivatives with duplex and quadruplex DNA were studied by thermal DNA denaturation experiments, spectrometric titrations as well as CD and LD spectroscopy. Fluorimetric DNA melting analysis with different types of quadruplex DNA revealed a moderate stabilization of the telomeric quadruplex-forming oligonucleotide sequence G3(TTAG3)3. The derivatives showed a moderate affinity towards quadruplex DNA (K b = 5-9 × 105 M-1) and ct DNA (K b = 3-5 × 104 M-1) and exhibited a fluorescence light-up effect upon complexation to both DNA forms, with slightly higher intensity in the presence of the quadruplex DNA. Furthermore, the CD- and LD-spectroscopic studies revealed that the title compounds intercalate into ct DNA and bind to G4-DNA by terminal stacking.

Synthesis of Degraded Limonoid Analogs as New Antibacterial Scaffolds against Staphylococcus aureus

Staphylococcus aureus and methicillin-resistant Staphylococcus aureus (MRSA) have become serious infections in humans and ruminants. S. aureus strains are showing rapid changes to develop resistance in traditional antibiotic-containing systems. In the continuous fierce fight against the emergent multi-drug resistant bacterial strains, straightforward and scalable synthetic procedures to produce new active molecules are in demand. Analysis of molecular properties points to degraded limonoids as promising candidates. In this article, we report a simple synthetic approach to obtain degraded limonoid analogs as scaffolds for new antibacterial molecules. The minimum inhibitory concentrations against S. aureus were evaluated for the stereoisomer mixtures by the broth microdilution method. Analysis of results showed that the acetylated derivatives were the most active of them all.

Therapeutic targeting of noncoding RNAs in hepatocellular carcinoma: Recent progress and future prospects

Due to the high mortality rate and unsatisfactory treatment options available, hepatocellular carcinoma (HCC) remains one of the most common malignancies and a leading cause of cancer-associated mortality. Novel therapeutic targets for HCC are urgently required. Advanced RNA sequencing technology enables the identification of considerable amounts of noncoding RNAs (ncRNAs), including small noncoding RNAs and long noncoding RNAs, which exhibit no protein-coding activities. In this respect, ncRNAs and their regulatory processes are important factors in liver tumorigenesis. The present review focuses on the characteristics and biological roles of ncRNAs in HCC. Potential therapeutic applications of ncRNAs in HCC are also evaluated.

Identification of Small Molecule Modulators of MicroRNA by Library Screening

MicroRNAs (miRNAs) function as oncogenes or tumor suppressors and are dysregulated in cancer. miRNAs therefore represent promising therapeutic targets for cancer. Small molecules that could modulate the expression of miRNAs would thus have potential as anticancer agents. Library screening of small molecules targeting miRNAs is a useful technology platform for anticancer drug development. Here, we describe a hepatocellular carcinoma (HCC) cell-based luciferase reporter system which could be used to screen for small molecule modulators of tumor suppressor microRNA-34a.

Small molecule targeting miR-34a for cancer therapy

miR-34a functions as a tumor suppressor in many cancers. In a recent issue of Cancer Research, we describe a small molecule, Rubone, with strong anticancer activity. Rubone selectively restored miR-34a expression in hepatocellular carcinoma cells in which miR-34a was silenced. Restoration of miR-34a by Rubone represents a promising therapeutic approach against cancer.

A prediction model for oral bioavailability of drugs using physicochemical properties by support vector machine

OBJECTIVE

A computational model for predicting oral bioavailability is very important both in the early stage of drug discovery to select the promising compounds for further optimizations and in later stage to identify candidates for clinical trials. In present study, we propose a support vector machine (SVM)-based kernel learning approach carried out at a set of 511 chemically diverse compounds with known oral bioavailability values.

MATERIAL AND METHODS

For each drug, 12 descriptors were calculated. The selection of optimal hyper-plane parameters was performed with 384 training set data and the prediction efficiency of proposed classifier was tested on 127 test set data.

RESULTS

The overall prediction efficiency for the test set came out to be 96.85%. Youden's index and Matthew correlation index were found to be 0.929 and 0.909, respectively. The area under receiver operating curve (ROC) was found to be 0.943 with standard error 0.0253.

CONCLUSION

The prediction model suggests that while considering chemoinformatics approaches into account, SVM-based prediction of oral bioavailability can be a significantly important tool for drug development and discovery at a preliminary level.