Advances in pharmacology最新文献

Oxygen is essential for all mammalian species, with complex organs such as the brain requiring a large and steady supply to function. During times of low or inadequate oxygen supply (hypoxia), adaptation is required in order to continue to function. Hypoxia inducible factors (HIF) are transcription factors which are activated during hypoxia and upregulate protective genes. Normally, when oxygen levels are sufficient (normoxia) HIFs are degraded by oxygen sensing prolyl hydroxylase domain proteins (PHD), but during hypoxia PHDs no longer exert influence on HIFs allowing their activation. Given that PHDs regulate the activity of HIFs, their pharmacological inhibition through PHD inhibitors (PHDIs) is believed to be the basis of their neuroprotective benefits. This review discusses some of the potential therapeutic benefits of PHDIs in a number of neurological disorders which see hypoxia as a major pathophysiological mechanism. These include stroke, Parkinson's disease, and amyotrophic lateral sclerosis. We also explore the potential neuroprotective benefits and limitations of PHDIs in a variety of disorders in the central nervous system (CNS). Additionally, the activation of HIFs by PHDIs can have modulatory effects on CNS functions such as neurotransmission and synaptic plasticity, mechanisms critical to cognitive processes such as learning and memory.

In recent years, the pharmaceutical industry has increasingly emphasized the role of lead compound identification in developing new therapeutic agents. Lead compounds show promising pharmacological activity against specific targets and are critical in drug development. Integrative computational approaches streamline this process by efficiently screening chemical libraries and designing potential drug candidates. This chapter highlights various computational techniques for lead compound discovery, including molecular modeling, cheminformatics, ligand- and structure-based drug design, molecular dynamics simulations, ADMET prediction, drug-target interaction analysis, and high-throughput screening. These methods improve drug discovery's efficiency, cost-effectiveness, and target-specific focus. Computational pharmaceutics has gained popularity due to the longer formulation development time which in turn increases the cost as well as decrease in the drug discovery production. Conventionally, formulation development relied on costly and unpredictable trial-and-error methods. However, analyzing the big data, artificial intelligence, and multi-scale modeling in computational pharmaceutics is transforming drug delivery. This chapter provides valuable insights throughout pre-formulation, formulation screening, in vivo predictions, and personalized medicine applications. Multiscale computational modeling is advancing drug delivery systems, enabling targeted treatments with multifunctional nanoparticles. Although in its early stages, this approach helps understand complex interactions between drugs, delivery systems, and patients.

Senescent cells progressively accumulate in the endocrine glands and their target tissue during the biological aging process. Senescence leads to hormonal imbalances contributing to various age-related endocrine diseases (AREDs). Cellular senescence, characterized by irreversible cell-cycle arrest, becomes more prevalent in advanced age, and the senescent cells release pro-inflammatory and pro-fibrotic factors, exacerbating endocrine dysregulation. Senescence-associated secretory phenotype (SASP) contributes to the pathogenesis of AREDs such as metabolic syndrome, sarcopenia, osteoporosis, and type 2 diabetes mellitus. Impaired metabolism of melatonin, cortisol, insulin, growth, and thyroid hormones are all intimately linked to age-related hormonal imbalance and dysregulated circadian rhythms. Pharmacokinetic and pharmacodynamic processes are also known to be impacted by circadian oscillations, which can also impact the toxicity and effectiveness of several therapeutic agents. Diagnosing and monitoring AREDs requires an assessment of individual circadian oscillations, inappropriate polypharmacy, and the senotherapeutic benefits of routine medications in the elderly. Hormone-oriented senotherapeutic strategies combined with anti-inflammatory SASP-related treatments may alleviate the detrimental effects of ARED symptoms. However, the complexity of senotherapy and the risk of possible adverse effects necessitate personalized treatment approaches.

The aging population is expanding rapidly to reshape the social and economic structures. Aging signifies the close to the end of life and threatens health because it features unavoidable compression of body reserve and gradual suppression of organ function. Tremendous research has established twelve essential aging hallmarks that shed light on mitigation frameworks. Interestingly, aging harbors inherent heterogeneity and plasticity, reflecting its multifaceted nature. Additionally, age-related diseases, such as cardiovascular and neurodegenerative diseases, often undergo the exact mechanisms with more devastating damage and speed. Therefore, interventions to promote healthy aging improve life quality and delay the disease's prevalence to later age. Clinical studies in humans have demonstrated the potential of several interventions, including lifestyle modifications, NAD⁺ supplementation, gut microbiota modulation, antidiabetic drugs (e.g., metformin), rapamycin, and senolytics, to mitigate the aging process and delay the onset of age-related diseases. Remarkably, clinical trials exhibit heterogeneity by showing substantial inter-individual differences in response to the interventions. It is often attributed to basal health status, tissue senescent burden, and immunity level. Continuous research would validate these correlations and solidify the personalized approaches. Lastly, generative artificial intelligence can pave a promising avenue to revolutionize anti-aging research and tailor aging management to promote healthy aging and extend health span.

Isothiocyanates (ITCs) are plant secondary metabolites predominantly found in the Brassicaceae family, responsible for their characteristic pungent taste and noted for their bioactive properties. The pungency of these plants arises from mustard oils, which are generated from glucosinolates when the plant material is chewed, cut, or otherwise damaged. This chapter delves into the potential of ITCs as promising geroprotectors - agents capable of delaying aging and mitigating age-related diseases. Compounds such as sulforaphane, a well-studied ITC, exhibit remarkable antioxidant and anti-inflammatory properties, which modulate key cellular signaling pathways involved in aging. Additionally, ITCs have been shown to induce autophagy, a critical cellular process that reduces the accumulation of damaged proteins and age-related aggregates, thereby supporting cellular health. The chapter reviews the biosynthesis and bioavailability of ITCs, their role in promoting longevity, and the molecular mechanisms underlying their protective effects. It also addresses potential adverse effects and challenges associated with their application. The evidence presented underscores the potential of ITCs to contribute to healthy aging and the prevention of age-associated conditions, highlighting the need for further exploration in geriatric medicine and therapeutic development.

Senescent cells are attributed to aging and age-related diseases. Clearance of senescent cells can delay the aging process and treat age-related diseases. Senescent cells have typical phenotypes including permanent cell cycle arrest, metabolic changes, senescence-associated secretory phenotype, and other structural and functional changes. Senescent cells-targeted therapeutics containing senolytics and senomorphics have been widely investigated but still insufficient, and the internal processes are still unclear, leaving a large gap between preclinical and clinical usage for aging and age-related disease management. Thus, it is urgently demanded to discover many more drugs or new targets with in vivo pharmacodynamics and pharmacokinetics evaluation and monitoring, promoting clinical translation. As a revolutionizing approach, molecular imaging exhibited great potential in exploring the in vivo pathophysiological mechanisms and further promoting the diagnosis and therapies of diseases. It can realize the visualization of complex biochemical processes from living cells, tissues, and organs, to subjects. Benefiting from the numerous imaging probes designed and synthesized with specificity and sensitivity, molecular imaging can vigorously facilitate exploring underlying in vivo mechanisms of senescent cells and senotherapeutics for aging and age-related diseases. Moreover, conjugating the senolytics and senomorphics with imaging probes can realize in vivo image-guided therapy for senescent cells, reversing the dysfunction of aging and treating age-related diseases. Molecular imaging exhibits great potential in visualizing and monitoring senescent cells-targeted therapeutics for aging and age-related diseases, and can forcefully contribute to the clinical translation of gerophamocology.

Bioinformatics has taken a pivotal place in the life sciences field. Not only does it improve, but it also fine-tunes and complements the wet lab experiments. It has been a driving force in the so-called biological sciences, converting them into hypothesis and data-driven fields. This study highlights the translational impact of bioinformatics on experimental biology and discusses its evolution and the advantages it has brought to advancing biological research. Computational analyses make labor-intensive wet lab work cost-effective by reducing the use of expensive reagents. Genome/proteome-wide studies have become feasible due to the efficiency and speed of bioinformatics tools, which can hardly be compared with wet lab experiments. Computational methods provide the scalability essential for manipulating large and complex data of biological origin. AI-integrated bioinformatics studies can unveil important biological patterns that traditional approaches may otherwise overlook. Bioinformatics contributes to hypothesis formation and experiment design, which is pivotal for modern-day multi-omics and systems biology studies. Integrating bioinformatics in the experimental procedures increases reproducibility and helps reduce human errors. Although today's AI-integrated bioinformatics predictions have significantly improved in accuracy over the years, wet lab validation is still unavoidable for confirming these predictions. Challenges persist in multi-omics data integration and analysis, AI model interpretability, and multiscale modeling. Addressing these shortcomings through the latest developments is essential for advancing our knowledge of disease mechanisms, therapeutic strategies, and precision medicine.

The membrane proteins of viruses play a critical role, and they shield viruses and takes biochemical mechanisms like sticking to the host cell membrane, merging with them, building new viruses, and breaking free. These steps make sure the virus can infect and multiply. But the membrane proteins of Nipah, Zika, SARS-CoV-2, and Hendra virus can cause special kinds of infections. Nipah and Hendra viruses use their fusion protein to join with the host cell membrane. Their glycoprotein interacts with host receptors. The matrix protein helps to build and support the virus structure. Zika virus relies on its envelope protein to attach and fuse with host cells. Its membrane protein keeps the viral envelope stable. SARS-CoV-2 uses its spike protein to enter host cells and its envelope protein helps assemble new viruses. The membrane protein gives structural stability whereas the nucleocapsid protein interacts with the RNA genome. These viral membranes contain various kinds of lipids and proteins and they make up about 30 % of the membrane area. Yet, scientists find it hard to predict their molecular structure and different biological characters. The coarse-grained molecular dynamics simulations, enhanced sampling methods, and various structural bioinformatics investigations on viral proteins provide reliable scientific data. These investigations reveal viral membrane proteins' structural features, movement patterns, and thermodynamic properties. These computer methods are vital for drug discovery because it allows researchers to find new compounds that target viral membrane proteins to prevent their functions.

Cardiovascular diseases (CVDs) are closely associated with a chronic inflammatory condition known as senescence and present a considerable challenge when managed alongside age-associated comorbidities. Due to the coexistence of three main predisposing factors (advanced age, multiple morbidity, and polypharmacotherapy), elderly patients with CVDs are prone to the occurrence of drug interactions and adverse effects of incorrect drug combinations. Polypharmacy, routine cardiovascular medications, and age-related pharmacokinetic alterations are the major challenges in cardiovascular practice. Polypharmacy might impair the post-surgical recovery process due to ADRs and side effects. Ironically, patients with CVDs may also require conventional senotherapeutic drugs such as cardiac glycosides, statins, aspirin, ACE inhibitors, and angiotensin receptor blockers for their daily routine. Considering medical necessities, polypharmacy, and drug safety of the elderly population, the management of elderly cases presents a serious challenge. We aim to present the cardiometabolic impacts of polypharmacy management in elderly patients and to design optimal senotherapeutic strategies and drug management strategies in cardiac surgical practice.

Today, clinical biochemistry laboratories play increasingly significant roles in diagnosing patients, monitoring treatment responses, and making prognoses. Over the last 50 years, technological advances have greatly impacted laboratory medicine. The analytical performance of autoanalyzers has reached higher levels through continuous improvement processes. Nonetheless, the preanalytical phase, the most important source of error in laboratory processes, considerably affects clinical laboratory test results. In the preanalytical phase, both controllable and uncontrollable variables influence laboratory test outcomes. Medications are among the controllable variables. Drugs can affect laboratory test results in a dose-dependent manner. Some of these effects may be classified as expected, while others are unexpected. Additionally, laboratory test results may be more misleading due to increased drug interactions in the geriatric population. Polypharmacy is a concerning issue for the elderly. Older individuals are at a higher risk of adverse drug reactions (ADRs) because of metabolic changes and reduced drug clearance associated with aging; this risk is further heightened by the rising number of prescribed medications. The use of multiple drugs increases the potential for drug-drug interactions. These interactions can lead to significant changes in laboratory parameters. Polypharmacy affects different organ systems to varying degrees, subsequently altering laboratory values. Managing laboratory abnormalities in polypharmacy requires a systematic approach grounded in a comprehensive medication history, chronological correlation, clinical judgment, and interdisciplinary collaboration.