This Review explores the state-of-the-art applications of artificial intelligence in small-molecule drug development, from target identification and drug synthesis up to clinical trial design and cond Show more
This Review explores the state-of-the-art applications of artificial intelligence in small-molecule drug development, from target identification and drug synthesis up to clinical trial design and conduct. Show less
Non-small cell lung cancer (NSCLC) is one of the most prevalent and lethal types of cancers worldwide and its high incidence and mortality rates pose a significant public health challenge. Despite sig Show more
Non-small cell lung cancer (NSCLC) is one of the most prevalent and lethal types of cancers worldwide and its high incidence and mortality rates pose a significant public health challenge. Despite significant advances in targeted therapy and immunotherapy, the overall prognosis of patients with NSCLC remains poor. Hypoxia is a critical driving factor in tumor progression, influencing the biological behavior of tumor cells through complex molecular mechanisms. The present review systematically examined the role of the hypoxic microenvironment in NSCLC, demonstrating its crucial role in promoting tumor cell growth, invasion and metastasis. Additionally, it has been previously reported that the hypoxic microenvironment enhances tumor cell resistance by activating hypoxia-inducible factor and regulating exosome secretion. The hypoxic microenvironment also enables tumor cells to adapt to low oxygen and nutrient-deficient conditions by enhancing metabolic reprogramming, such as through upregulating glycolysis. Further studies have shown that the hypoxic microenvironment facilitates immune escape by modulating tumor-associated immune cells and suppressing the antitumor response of the immune system. Moreover, the hypoxic microenvironment increases tumor resistance to radiotherapy, chemotherapy and other types of targeted therapy through various pathways, significantly reducing the therapeutic efficacy of these treatments. Therefore, it could be suggested that early detection of cellular hypoxia and targeted therapy based on hypoxia may offer new therapeutic approaches for patients with NSCLC. The present review not only deepened the current understanding of the mechanisms of action and role of the hypoxic microenvironment in NSCLC but also provided a solid theoretical basis for the future development of precision treatments for patients with NSCLC. Show less
The brain’s high demand for energy necessitates tightly regulated metabolic pathways to sustain physiological activity. Glucose, the primary energy substrate, undergoes complex metabolic transformatio Show more
The brain’s high demand for energy necessitates tightly regulated metabolic pathways to sustain physiological activity. Glucose, the primary energy substrate, undergoes complex metabolic transformations, with mitochondria playing a central role in ATP production via oxidative phosphorylation. Dysregulation of this metabolic interplay is implicated in Alzheimer’s disease (AD), where compromised glucose metabolism, oxidative stress, and mitochondrial dysfunction contribute to disease progression. This review explores the intricate bioenergetic crosstalk between astrocytes and neurons, highlighting the function of mitochondrial uncoupling proteins (UCPs), particularly UCP4, as important regulators of brain metabolism and neuronal function. Predominantly expressed in the brain, UCP4 reduces the membrane potential in the inner mitochondrial membrane, thereby potentially decreasing the generation of reactive oxygen species. Furthermore, UCP4 mitigates mitochondrial calcium overload and sustains cellular ATP levels through a metabolic shift from mitochondrial respiration to glycolysis. Interestingly, the levels of the neuronal UCPs, UCP2, 4 and 5 are significantly reduced in AD brain tissue and a specific UCP4 variant has been associated to an increased risk of developing AD. Few studies modulating the expression of UCP4 in astrocytes or neurons have highlighted protective effects against neurodegeneration and aging, suggesting that pharmacological strategies aimed at activating UCPs, such as protonophoric uncouplers, hold promise for therapeutic interventions in AD and other neurodegenerative diseases. Despite significant advances, our understanding of UCPs in brain metabolism remains in its early stages, emphasizing the need for further research to unravel their biological functions in the brain and their therapeutic potential. Show less
Lung cancer is a common malignant tumor that occurs in the human body and poses a serious threat to human health and quality of life. The existing treatment methods mainly include surgical treatment, Show more
Lung cancer is a common malignant tumor that occurs in the human body and poses a serious threat to human health and quality of life. The existing treatment methods mainly include surgical treatment, chemotherapy, and radiotherapy. However, due to the strong metastatic characteristics of lung cancer and the emergence of related drug resistance and radiation resistance, the overall survival rate of lung cancer patients is not ideal. There is an urgent need to develop new treatment strategies or new effective drugs to treat lung cancer. Ferroptosis, a novel type of programmed cell death, is different from the traditional cell death pathways such as apoptosis, necrosis, pyroptosis and so on. It is caused by the increase of iron-dependent reactive oxygen species due to intracellular iron overload, which leads to the accumulation of lipid peroxides, thus inducing cell membrane oxidative damage, affecting the normal life process of cells, and finally promoting the process of ferroptosis. The regulation of ferroptosis is closely related to the normal physiological process of cells, and it involves iron metabolism, lipid metabolism, and the balance between oxygen-free radical reaction and lipid peroxidation. A large number of studies have confirmed that ferroptosis is a result of the combined action of the cellular oxidation/antioxidant system and cell membrane damage/repair, which has great potential application in tumor therapy. Therefore, this review aims to explore potential therapeutic targets for ferroptosis in lung cancer by clarifying the regulatory pathway of ferroptosis. Based on the study of ferroptosis, the regulation mechanism of ferroptosis in lung cancer was understood and the existing chemical drugs and natural compounds targeting ferroptosis in lung cancer were summarized, with the aim of providing new ideas for the treatment of lung cancer. In addition, it also provides the basis for the discovery and clinical application of chemical drugs and natural compounds targeting ferroptosis to effectively treat lung cancer. Show less
The elucidation of a compound's Mechanism of Action (MoA) is a challenging task in the drug discovery process, but it is important in order to rationalise phenotypic findings and to anticipate potenti Show more
The elucidation of a compound's Mechanism of Action (MoA) is a challenging task in the drug discovery process, but it is important in order to rationalise phenotypic findings and to anticipate potential side-effects. Bioinformatic approaches, advances in machine learning techniques and the increasing deposition of high-throughput data in public databases have significantly contributed to recent advances in the field, but it is not straightforward to decide which data and methods are most suitable to use in a given case. In this review, we focus on these methods and data and their applications in generating MoA hypotheses for subsequent experimental validation. We discuss compound-specific data such as -omics, cell morphology and bioactivity data, as well as commonly used supplementary prior knowledge such as network and pathway data, and provide information on databases where this data can be accessed. In terms of methodologies, we discuss both well-established methods (connectivity mapping, pathway enrichment) as well as more developing methods (neural networks and multi-omics integration). Finally, we review case studies where the MoA of a compound was successfully suggested from computational analysis by incorporating multiple data modalities and/or methodologies. Our aim for this review is to provide researchers with insights into the benefits and drawbacks of both the data and methods in terms of level of understanding, biases and interpretation – and to highlight future avenues of investigation which we foresee will improve the field of MoA elucidation, including greater public access to -omics data and methodologies which are capable of data integration. Show less
Here, we report a novel mechanism to selectively degrade target proteins. 3-(3-Phenoxybenzyl)amino-β-carboline (PAC), a tubulin inhibitor, promotes selective degradation of αβ-tubulin heterodimers. Bi Show more
Here, we report a novel mechanism to selectively degrade target proteins. 3-(3-Phenoxybenzyl)amino-β-carboline (PAC), a tubulin inhibitor, promotes selective degradation of αβ-tubulin heterodimers. Biochemical studies have revealed that PAC specifically denatures tubulin, making it prone to aggregation that predisposes it to ubiquitinylation and then degradation. The degradation is mediated by a single hydrogen bond formed between the pyridine nitrogen of PAC and βGlu198, which is identified as a low-barrier hydrogen bond (LBHB). In contrast, another two tubulin inhibitors that only form normal hydrogen bonds with βGlu198 exhibit no degradation effect. Thus, the LBHB accounts for the degradation. We then screened for compounds capable of forming an LBHB with βGlu198 and demonstrated that BML284, a Wnt signaling activator, also promotes tubulin heterodimer degradation through the LBHB. Our study provided a unique example of LBHB function and identified a novel approach to obtain tubulin degraders. Show less
The task of drug-target interaction prediction holds significant importance in pharmacology and therapeutic drug design. In this paper, we present FRnet-DTI, an auto-encoder based feature manipulation Show more
The task of drug-target interaction prediction holds significant importance in pharmacology and therapeutic drug design. In this paper, we present FRnet-DTI, an auto-encoder based feature manipulation and a convolutional neural network based classifier for drug target interaction prediction. Two convolutional neural networks are proposed: FRnet-Encode and FRnet-Predict. Here, one model is used for feature manipulation and the other one for classification. Using the first method FRnet-Encode, we generate 4096 features for each of the instances in each of the datasets and use the second method, FRnet-Predict, to identify interaction probability employing those features. We have tested our method on four gold standard datasets extensively used by other researchers. Experimental results shows that our method significantly improves over the state-of-the-art method on three out of four drug-target interaction gold standard datasets on both area under curve for Receiver Operating Characteristic (auROC) and area under Precision Recall curve (auPR) metric. We also introduce twenty new potential drug-target pairs for interaction based on high prediction scores. The source codes and implementation details of our methods are available from https://github.com/farshidrayhanuiu/FRnet-DTI/ and also readily available to use as an web application from http://farshidrayhan.pythonanywhere.com/FRnet-DTI/ . Show less
Abstract Significance: Mitochondria are the energetic, metabolic, redox, and information signaling centers of the cell. Substrate pressure, mitochondrial network dynamics, and cristae morphology Show more
Abstract Significance: Mitochondria are the energetic, metabolic, redox, and information signaling centers of the cell. Substrate pressure, mitochondrial network dynamics, and cristae morphology state are integrated by the protonmotive force Δ p or its potential component, Δ Ψ , which are attenuated by proton backflux into the matrix, termed uncoupling. The mitochondrial uncoupling proteins (UCP1–5) play an eminent role in the regulation of each of the mentioned aspects, being involved in numerous physiological events including redox signaling. Recent Advances: UCP2 structure, including purine nucleotide and fatty acid (FA) binding sites, strongly support the FA cycling mechanism: UCP2 expels FA anions, whereas uncoupling is achieved by the membrane backflux of protonated FA. Nascent FAs, cleaved by phospholipases, are preferential. The resulting Δ p dissipation decreases superoxide formation dependent on Δ p . UCP-mediated antioxidant protection and its impairment are expected to play a major role in cell physiology and pathology. Moreover, UCP2-mediated aspartate, oxaloacetate, and malate antiport with phosphate is expected to alter metabolism of cancer cells. Critical Issues: A wide range of UCP antioxidant effects and participations in redox signaling have been reported; however, mechanisms of UCP activation are still debated. Switching off/on the UCP2 protonophoretic function might serve as redox signaling either by employing/releasing the extra capacity of cell antioxidant systems or by directly increasing/decreasing mitochondrial superoxide sources. Rapid UCP2 degradation, FA levels, elevation of purine nucleotides, decreased Mg 2+ , or increased pyruvate accumulation may initiate UCP-mediated redox signaling. Future Directions: Issues such as UCP2 participation in glucose sensing, neuronal (synaptic) function, and immune cell activation should be elucidated. Antioxid. Redox Signal. 29, 667–714. Show less