Current Drug Targets - Volume 24, Issue 6, 2023

Pyruvate kinase M2 (PKM2) has surfaced as a potential target for anti-cancer therapy. PKM2 is known to be overexpressed in the tumor cells and is a critical metabolic conduit in supplying the augmented bioenergetic demands of the recalcitrant cancer cells. The presence of PKM2 in structurally diverse tetrameric as well as dimeric forms has opened new avenues to design novel modulators. It is also a truism to state that drug discovery has advanced significantly from various computational techniques like molecular docking, virtual screening, molecular dynamics, and pharmacophore mapping. The present review focuses on the role of computational tools in exploring novel modulators of PKM2. The structural features of various isoforms of PKM2 have been discussed along with reported modulators. An extensive analysis of the structure-based and ligand- based in silico methods aimed at PKM2 modulation has been conducted with an in-depth review of the literature. The role of advanced tools like QSAR and quantum mechanics has been established with a brief discussion of future perspectives.

MicroRNAs have a plethora of roles in various biological processes in the cells and most human cancers have been shown to be associated with dysregulation of the expression of miRNA genes. MiRNA biogenesis involves two alternative pathways, the canonical pathway which requires the successful cooperation of various proteins forming the miRNA-inducing silencing complex (miRISC), and the non-canonical pathway, such as the mirtrons, simtrons, or agotrons pathway, which bypasses and deviates from specific steps in the canonical pathway. Mature miRNAs are secreted from cells and circulated in the body bound to argonaute 2 (AGO2) and miRISC or transported in vesicles. These miRNAs may regulate their downstream target genes via positive or negative regulation through different molecular mechanisms. This review focuses on the role and mechanisms of miRNAs in different stages of breast cancer progression, including breast cancer stem cell formation, breast cancer initiation, invasion, and metastasis as well as angiogenesis. The design, chemical modifications, and therapeutic applications of synthetic anti-sense miRNA oligonucleotides and RNA mimics are also discussed in detail. The strategies for systemic delivery and local targeted delivery of the antisense miRNAs encompass the use of polymeric and liposomal nanoparticles, inorganic nanoparticles, extracellular vesicles, as well as viral vectors and viruslike particles (VLPs). Although several miRNAs have been identified as good candidates for the design of antisense and other synthetic modified oligonucleotides in targeting breast cancer, further efforts are still needed to study the most optimal delivery method in order to drive the research beyond preclinical studies.

Triple negative breast cancers are malignant, heterogeneous tumors with high histological grades, increased reoccurrence, and cancer-related death rates. TNBC metastasis to the brain, lungs, liver, and lymph nodes is a complex process regulated by epithelial to mesenchymal transition, intravasation, extravasation, stem cell niche, and migration. Aberrant expression of miRNAs, also known as a transcriptional regulators of genes, may function as oncogenes or tumor suppressors. In this review, we systematically elucidated the biogenesis and tumor suppressor role of miRNA in targeting distant metastasis of TNBC cells and the above-mentioned underlying mechanisms involved in complicating the disease. Apart from their therapeutic implications, the emerging roles of miRNAs as prognostic markers have also been discussed. To overcome delivery bottlenecks, RNA nanoparticles, nano-diamonds, exosomes, and mesoporous silica nanoparticle-mediated delivery of miRNAs have been contemplated. Altogether, the present review article uncovers the potential role of miRNA in antagonizing distant metastasis of TNBC cells, and highlights their clinical significance as prognostic markers and possible drug delivery strategies to enhance the likely outcome of miRNA-based therapy against the disease.

Breast cancer has remained a global challenge and the second leading cause of cancer mortality in women and family history. Hereditary factors are some of the major risk factors associated with breast cancer. Out of total breast cancer cases, 5-10% account only for familial breast cancer, and nearly 50% of all hereditary breast cancer are due to BRCA1/BRCA2 germline mutations. BRCA1/2 mutations play an important role not only in determining the clinical prognosis of breast cancer but also in the survival curves. Since this risk factor is known, a significant amount of the healthcare burden can be reduced by taking preventive measures among people with a known history of familial breast cancer. There is increasing evidence that phytochemicals of nutrients and supplements help in the prevention and cure of BRCA-related cancers by different mechanisms such as limiting DNA damage, altering estrogen metabolism, or upregulating expression of the normal BRCA allele, and ultimately enhancing DNA repair. This manuscript reviews different approaches used to identify potential phytochemicals to mitigate the risk of familial breast cancer with BRCA mutations. The findings of this review can be extended for the prevention and cure of any BRCAmutated cancer after proper experimental and clinical validation of the data.

Global health security has been challenged by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. Due to the lengthy process of generating vaccinations, it is vital to reposition currently available drugs in order to relieve anti-epidemic tensions and accelerate the development of therapies for Coronavirus Disease 2019 (COVID-19), the public threat caused by SARS-CoV-2. High throughput screening techniques have established their roles in the evaluation of already available medications and the search for novel potential agents with desirable chemical space and more cost-effectiveness. Here, we present the architectural aspects of highthroughput screening for SARS-CoV-2 inhibitors, especially three generations of virtual screening methodologies with structural dynamics: ligand-based screening, receptor-based screening, and machine learning (ML)-based scoring functions (SFs). By outlining the benefits and drawbacks, we hope that researchers will be motivated to adopt these methods in the development of novel anti- SARS-CoV-2 agents.