Structure-based drug design is becoming an essential tool for faster and more cost-efficient lead discovery relative to the traditional method. Genomic, proteomic, and structural studies have provided hundreds of new targets and opportunities for future drug discovery. This situation poses a major problem: the necessity to handle the “big data” generated by combinatorial chemistry. Artificial intelligence (AI) and deep learning play a pivotal role in the analysis and systemization of larger data sets by statistical machine learning methods. Advanced AI-based sophisticated machine learning tools have a significant impact on the drug discovery process including medicinal chemistry. In this review, we focus on the currently available methods and algorithms for structure-based drug design including virtual screening and de novo drug design, with a special emphasis on AI- and deep-learning-based methods used for drug discovery.

Fibroblast growth factors (FGFs) are a large family of secretory molecules that act through tyrosine kinase receptors known as FGF receptors. They play crucial roles in a wide variety of cellular functions, including cell proliferation, survival, metabolism, morphogenesis, and differentiation, as well as in tissue repair and regeneration. The signaling pathways regulated by FGFs include RAS/mitogen-activated protein kinase (MAPK), phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K)–protein kinase B (AKT), phospholipase C gamma (PLCγ), and signal transducer and activator of transcription (STAT). To date, 22 FGFs have been discovered, involved in different functions in the body. Several FGFs directly or indirectly interfere with repair during tissue regeneration, in addition to their critical functions in the maintenance of pluripotency and dedifferentiation of stem cells. In this review, we summarize the roles of FGFs in diverse cellular processes and shed light on the importance of FGF signaling in mechanisms of tissue repair and regeneration.

The chemotherapeutic use of cisplatin is limited by its severe side effects. In this study, by conducting different omics data analyses, we demonstrated that cisplatin induces cell death in a proximal tubular cell line by suppressing glycolysis- and tricarboxylic acid (TCA)/mitochondria-related genes. Furthermore, analysis of the urine from cisplatin-treated rats revealed the lower expression levels of enzymes involved in glycolysis, TCA cycle, and genes related to mitochondrial stability and confirmed the cisplatin-related metabolic abnormalities. Additionally, an increase in the level of p53, which directly inhibits glycolysis, has been observed. Inhibition of p53 restored glycolysis and significantly reduced the rate of cell death at 24 h and 48 h due to p53 inhibition. The foremost reason of cisplatin-related cytotoxicity has been correlated to the generation of mitochondrial reactive oxygen species (ROS) that influence multiple pathways. Abnormalities in these pathways resulted in the collapse of mitochondrial energy production, which in turn sensitized the cells to death. The quenching of ROS led to the amelioration of the affected pathways. Considering these observations, it can be concluded that there is a significant correlation between cisplatin and metabolic dysfunctions involving mROS as the major player.

Toll‐like receptors (TLRs) are germline‐encoded receptors that are central to innate and adaptive immune responses. Owing to their vital role in inflammation, TLRs are rational targets in clinics; thus, many ligands and biologics have been reported to overcome the progression of various inflammatory and malignant conditions and support the immune system. For each TLR, at least one, and often many, drug formulations are being evaluated. Ligands reported as stand‐alone drugs may also be reported based on their use in combinatorial therapeutics as adjuvants. Despite their profound efficacy in TLR‐modulation in preclinical studies, multiple drugs have been terminated at different stages of clinical trials. Here, TLR modulating drugs that have been evaluated in clinical trials are discussed, along with their mode of action, suggestive failure reasons, and ways to improve the clinical outcomes. This review presents recent advances in TLR‐targeting drugs and provides directions for more successful immune system manipulation.

Proinflammatory cytokines and chemokines play a crucial role in regulating the inflammatory response, which is essential for the proper functioning of our immune system. When infections or threats to the body’s defense mechanisms are detected, the innate immune system takes the lead. However, an excessive inflammatory response can lead to the production of high concentrations of cytotoxic molecules, resulting in tissue damage. Inflammasomes are significant contributors to innate immunity, and one of the most extensively studied inflammasome complexes is NOD-like receptor 3 (NLRP3). NLRP3 has a wide range of recognition mechanisms that streamline immune activation and eliminate pathogens. These cytosolic multiprotein complexes are composed of effector, adaptor, and sensor proteins, which are crucial for identifying intracellular bacterial breakdown products and initiating an innate immune cascade. To understand the diverse behavior of NLRP3 activation and its significance in the development of lifestyle-related diseases, one must delve into the study of the immune response and apoptosis mediated by the release of proinflammatory cytokines. In this review, we briefly explore the immune response in the context of lifestyle associated disorders such as obesity, hyperlipidemia, diabetes, chronic respiratory disease, oral disease, and cardiovascular disease.