Small molecule-mediated targeting of microRNAs for drug discovery: Experiments, computational techniques, and disease implications.

Small molecules have been providing medical breakthroughs for human diseases for more than a century. Recently, identifying small molecule inhibitors that target microRNAs (miRNAs) has gained importance, despite the challenges posed by labour-intensive screening experiments and the significant efforts required for medicinal chemistry optimization. Numerous experimentally-verified cases have demonstrated the potential of miRNA-targeted small molecule inhibitors for disease treatment. This new approach is grounded in their posttranscriptional regulation of the expression of disease-associated genes. Reversing dysregulated gene expression using this mechanism may help control dysfunctional pathways. Furthermore, the ongoing improvement of algorithms has allowed for the integration of computational strategies built on top of laboratory-based data, facilitating a more precise and rational design and discovery of lead compounds. To complement the use of extensive pharmacogenomics data in prioritising potential drugs, our previous work introduced a computational approach based on only molecular sequences. Moreover, various computational tools for predicting molecular interactions in biological networks using similarity-based inference techniques have been accumulated in established studies. However, there are a limited number of comprehensive reviews covering both computational and experimental drug discovery processes. In this review, we outline a cohesive overview of both biological and computational applications in miRNA-targeted drug discovery, along with their disease implications and clinical significance. Finally, utilizing drug-target interaction (DTIs) data from DrugBank, we showcase the effectiveness of deep learning for obtaining the physicochemical characterization of DTIs.

Uptake of long-chain fatty acids from the bone marrow suppresses CD8+ T-cell metabolism and function in multiple myeloma.

T cells demonstrate impaired function in multiple myeloma (MM) but suppressive mechanisms in the bone marrow microenvironment remain poorly defined. We observe that bone marrow CD8+ T-cell function is decreased in MM compared with controls, and is also consistently lower within bone marrow samples than in matched peripheral blood samples. These changes are accompanied by decreased mitochondrial mass and markedly elevated long-chain fatty acid uptake. In vitro modeling confirmed that uptake of bone marrow lipids suppresses CD8+ T function, which is impaired in autologous bone marrow plasma but rescued by lipid removal. Analysis of single-cell RNA-sequencing data identified expression of fatty acid transport protein 1 (FATP1) in bone marrow CD8+ T cells in MM, and FATP1 blockade also rescued CD8+ T-cell function, thereby identifying this as a novel target to augment T-cell activity in MM. Finally, analysis of samples from cohorts of patients who had received treatment identified that CD8+ T-cell metabolic dysfunction resolves in patients with MM who are responsive to treatment but not in patients with relapsed MM, and is associated with substantial T-cell functional restoration.

Prolyl-tRNA synthetase as a novel therapeutic target in multiple myeloma.

Multiple myeloma (MM) is a plasma cell malignancy characterised by aberrant production of immunoglobulins requiring survival mechanisms to adapt to proteotoxic stress. We here show that glutamyl-prolyl-tRNA synthetase (GluProRS) inhibition constitutes a novel therapeutic target. Genomic data suggest that GluProRS promotes disease progression and is associated with poor prognosis, while downregulation in MM cells triggers apoptosis. We developed NCP26, a novel ATP-competitive ProRS inhibitor that demonstrates significant anti-tumour activity in multiple in vitro and in vivo systems and overcomes metabolic adaptation observed with other inhibitor chemotypes. We demonstrate a complex phenotypic response involving protein quality control mechanisms that centers around the ribosome as an integrating hub. Using systems approaches, we identified multiple downregulated proline-rich motif-containing proteins as downstream effectors. These include CD138, transcription factors such as MYC, and transcription factor 3 (TCF3), which we establish as a novel determinant in MM pathobiology through functional and genomic validation. Our preclinical data therefore provide evidence that blockade of prolyl-aminoacylation evokes a complex pro-apoptotic response beyond the canonical integrated stress response and establish a framework for its evaluation in a clinical setting.