Development of nimesulide analogs as a dual inhibitor targeting tubulin and HSP27 for treatment of female cancers

Tubulin inhibitors. Selected scaffolds and main trends in the design of novel anticancer and antiparasitic agents

Design of tubulin inhibitors as anticancer drugs dynamically developed over the past 20 years. The modern arsenal of potential tubulin-targeting anticancer agents is represented by small molecules, monoclonal antibodies, and antibody-drug conjugates. Moreover, targeting tubulin has been a successful strategy in the development of antiparasitic drugs. In the present review, an overall picture of the research and development of potential tubulin-targeting agents using small molecules between 2018 and 2023 is provided. The data about some most often used and prospective chemotypes of small molecules (privileged heterocycles, moieties of natural molecules) and synthetic methodologies (analogue-based, fragment-based drug design, molecular hybridization) applied for the design of novel agents with an impact on the tubulin system are summarized. The design and prospects of multi-target agents with an impact on the tubulin system were also highlighted. Reported in the review data contribute to the "structure-activity" profile of tubulin-targeting small molecules as anticancer and antiparasitic agents and will be useful for the application by medicinal chemists in further exploration, design, improvement, and optimization of this class of molecules.

Cancer targeted drug delivery using active low-density lipoprotein nanoparticles encapsulated pyrimidines heterocyclic anticancer agents as microtubule inhibitors

Recently, nanomedicine had the potential to increase the delivery of active compounds to specific cell sites. Nano-LDL particles are recognized as an excellent active nano-platform for cancer-targeted delivery. Loading of therapeutic agents into nano-LDL particles achieved by surface loading, core loading, and apolipoprotein-B100 interaction. Therefore, loading nano-LDL particles’ core with pyrimidine heterocyclic anticancer agents will increase cancer cytotoxic activity targeting tubulin protein. First, by mimicking the native LDL particle's metabolic pathway, and second the agent’s chemical functional groups like the native amino acids cytosine and thymine structures will not be recognized as a foreign entity from the cell’s immune system. Nano-LDL particles will internalize through LDL-receptors endocytosis and transport the anticancer agent into the middle of the cancer cell, reducing its side effects on other healthy cells. Generally, the data revealed that pyrimidine heterocyclic anticancer agents’ size is at the nano level. Agents’ morphological examination showed nanofibers, thin sheets, clusters, and rod-like structures. LDL particles’ size became bigger after loading with pyrimidine heterocyclic anticancer agents and ranged between 121.6 and 1045 nm. Then, particles were tested for their cytotoxicity against breast (MDA468) and prostate (DU145) cancer cell lines as surrogate models with dose-response study 10, 5, 1 µM. The IC₅₀ values of the agents against DU145 and MDA468 possessed cell growth inhibition even at the 1 µM concentration ranges of 3.88 ± 1.05 µM and 3.39 ± 0.97 µM, respectively. In sum, nano-LDL particles proved their efficiency as active drug delivery vehicles to target tubulin in cancer cells.

Computationally repurposing drugs for breast cancer subtypes using a network-based approach

‘De novo’ drug discovery is costly, slow, and with high risk. Repurposing known drugs for treatment of other diseases offers a fast, low-cost/risk and highly-efficient method toward development of efficacious treatments. The emergence of large-scale heterogeneous biomolecular networks, molecular, chemical and bioactivity data, and genomic and phenotypic data of pharmacological compounds is enabling the development of new area of drug repurposing called ‘in silico’ drug repurposing, i.e., computational drug repurposing (CDR). The aim of CDR is to discover new indications for an existing drug (drug-centric) or to identify effective drugs for a disease (disease-centric). Both drug-centric and disease-centric approaches have the common challenge of either assessing the similarity or connections between drugs and diseases. However, traditional CDR is fraught with many challenges due to the underlying complex pharmacology and biology of diseases, genes, and drugs, as well as the complexity of their associations. As such, capturing highly non-linear associations among drugs, genes, diseases by most existing CDR methods has been challenging. We propose a network-based integration approach that can best capture knowledge (and complex relationships) contained within and between drugs, genes and disease data. A network-based machine learning approach is applied thereafter by using the extracted knowledge and relationships in order to identify single and pair of approved or experimental drugs with potential therapeutic effects on different breast cancer subtypes. Indeed, further clinical analysis is needed to confirm the therapeutic effects of identified drugs on each breast cancer subtype.

Methoxybenzamide derivative of nimesulide from anti-fever to anti-cancer: chemical characterization and cytotoxicity

The repurposing strategy of converting nimesulide from an anti-fever drug to an anti-cancer agent by modifying its main structure targeting HSP27 is gaining great attention these days. The goal of this study focuses on synthesizing a new nimesulide derivative with new ligands that have biological anti-cancer activities in different cancer models using the in-vitro assay. Nimesulide derivative L1 was synthesized, characterized by 1H NMR, 13C NMR, FTIR, melting point, mass spectra, and TGA analysis. A single crystal was diffracted and showed colorless block group P-1. The results revealed that L1 demonstrates potent anti-cancer activity with lung (H292), ovarian (SKOV3), and breast (SKBR3) cancer cell lines in-vitro models with IC₅₀ values below 8.8 µM.