Expert Opinion on Drug Discovery最新文献

Introduction: The advent of variant-specific disease-modifying drugs into clinical practice has provided remarkable benefits for people with cystic fibrosis (PwCF), a multi-organ life-limiting inherited disease. However, further efforts are needed to maximize therapeutic benefits as well as to increase the number of PwCF taking CFTR modulators.

Area covered: The authors discuss some of the key limitations of the currently available CFTR modulator therapies (e.g. adverse reactions) and strategies in development to increase the number of available therapeutics for CF. These include novel methods to accelerate theratyping and identification of novel small molecules and cellular targets representing alternative or complementary therapies for CF.

Expert opinion: While the CF therapy development pipeline continues to grow, there is a critical need to optimize strategies that will accelerate testing and approval of effective therapies for (ultra)rare CFTR variants as traditional assays and trials are not suitable to address such issues. Another major barrier that needs to be solved is the restricted access to currently available modulator therapies, which remains a significant burden for PwCF who are from racial and ethnic minorities or living in underprivileged regions.

Introduction: In recent months, monkeypox (mpox) virus (MPXV) infections has grown to be a major worldwide concern. Cynomolgus monkeys, rhesus macaques, marmosets, and baboons are the nonhuman primate (NHP) models that provide the much needed means for developing new therapies against MPXV due to their genetic proximity to humans.

Area covered: In this review, the authors discuss epidemiology, transmission, clinical presentation, and the use of NHP in studying the treatment of MPXV over the past two decades on Google Scholar. NHP models have been widely used to evaluate the efficacy of antiviral drugs and antibodies, providing important information regarding immune responses and disease. NHPs continue to be an important mainstay in preclinical testing, enabling the optimization of the efficacy and safety of drugs, antibodies, and vaccines to accelerate the development of effective MPXV treatments for humans.

Expert opinion: The intravenous forms of medications like cidofovir, brincidofovir, and Vaccinia Immune Globulin (VIG) constitute the basis of MPXV therapy. Additionally, antibodies such as HAI, PN, and CF assess the efficacy of smallpox vaccination against MPXV in primates. This would help both the development of diagnostic tools and the optimization of vaccine strategies. Moreover, the similarities between MPXV and vaccinia or variola can play a role in developing targeted antiviral treatment methods.

Introduction: Targeted protein degradation (TPD) is a cutting-edge technology that provides new avenues for drug discovery and development. PROteolysis TArgeting Chimeras (PROTACs) are the most established and advanced TPD strategy, enabling the selective degradation of disease-associated and 'undruggable' proteins of interest (POIs) by leveraging the cell's natural protein degradation machinery. To confirm that PROTAC-induced proximity drives protein degradation, target validation and ternary complex formation must be thoroughly assessed.

Areas covered: In this perspective, the authors detail some of the most widely used in silico, structural, in vitro, and in cellulo methods to validate PROTAC target engagement and ternary complex formation. Additionally, they discuss the growing use of PROTACs as chemical probes for novel target identification and validation.

Expert opinion: Target validation is essential in the PROTAC approach, and ongoing PROTAC studies should prioritize confirming ternary complex formation using assays conducted under physiologically relevant cellular conditions. The authors believe that proteomics analyses are among the most valuable tools for elucidating the mechanism, selectivity, and outcomes of PROTACs. They also remain optimistic about the future of PROTACs in drug development and their use as probes to confirm target engagement. While PROTAC technology is rapidly advancing, it still holds vast opportunities for future exploration, offering significant potential to further both chemical and biological research and to drive the development of new drugs.

Introduction: Proximity-inducing compounds promote protein-protein interactions by bringing proteins into close spatial alignment. Among them, targeted protein degradation (TPD) compounds are noteworthy for their potential to target previously 'undruggable' proteins. Native mass spectrometry (nMS), a technique that enables the detection of non-covalent interactions, is emerging as a key tool for studying compound-induced ternary complex formation.

Areas covered: This review highlights the use of nMS in unraveling the mechanisms of proximity-inducing compounds, focusing on all available studies published since 2020, identified through a PubMed database search. The authors explore how nMS helps investigate the efficacy and mechanisms of proteolysis-targeting chimeras (PROTACs) and molecular glues by capturing the binary and ternary complexes formed by E3 ligases, protein of interest (POI), and these molecules.

Expert opinion: nMS excels at analyzing intact protein complexes, providing real-time insights into interactions between E3 ligases, POIs, and proximity-inducing agents. This analysis helps understand the formation, stability, and dynamic nature of the complexes along with precise data on stoichiometry and binding affinities, which are crucial for selecting and refining effective degraders. The future of nMS in TPD research is promising, with potential applications in kinetic analysis, degrader screenings, and exploration of novel E3 ligases and target proteins.

Introduction: Irritable bowel syndrome (IBS) is a common gastrointestinal disorder that is often therapeutically challenging. While research has advanced our understanding of IBS pathophysiology, developing precise models to predict drug response and treatment outcomes remains a significant hurdle.

Areas covered: This perspective provides an overview of the use of animal models alongside cutting-edge technologies used to bring drugs from bench to bedside.Furthermore, the authors examine the progress and limitations of IBS modeling. The authors further discuss the challenges of traditional animal models and gives a spotlight to the potential of innovative technologies, such as organ-on-chip systems, computational models, and artificial intelligence (AI). These approaches intend to enhance both the understanding and treatment of IBS.

Expert opinion: Although animal models have been central to understanding IBS research, they have limitations. The future of IBS research resides in integrating organ-on-chip systems and utilizing modern technological developments, such as AI. These tools will enable the design of more effective treatment strategies and improve patients' overall well-being. To achieve this, collaboration between experts from various disciplines is essential to improve these models and guarantee their clinical application and reliability.

Introduction: Drug discovery is a complex and multifaceted process driven by scientific innovation and advanced technologies. Next-Generation Sequencing (NGS) platforms, encompassing both short-read and long-read technologies, have revolutionized the field by enabling the high-throughput and cost-effective analysis of DNA and RNA molecules. Continuous advancements in NGS-based technologies have enabled their seamless integration across preclinical and clinical workflows in drug discovery, encompassing early-stage drug target identification, candidate selection, genetically stratified clinical trials, and pharmacogenetic studies.

Area covered: This review provides an overview of the current and potential applications of NGS-based technologies in drug discovery and development process, including their roles in novel drug target identification, high-throughput screening, clinical trials, and clinical medication studies. The review is based on literature retrieval from the PubMed and Web of Science databases between 2018 and 2024.

Expert opinion: As technologies advance rapidly, NGS enhances accuracy and generates vast datasets. These datasets are extensively integrated with other heterogeneous data in systems biology and are mined using machine learning to extract significant insights, thereby driving progress in drug discovery.

Introduction: Identifying treatments that can alter the natural history of amyotrophic lateral sclerosis (ALS) is challenging. For years, drug discovery in ALS has relied upon traditional approaches with limited success. Drug repurposing, where clinically approved drugs are reevaluated for other indications, offers an alternative strategy that overcomes some of the challenges associated with de novo drug discovery.

Areas covered: In this review, the authors discuss the challenge of drug discovery in ALS and examine the potential of drug repurposing for the identification of new effective treatments. The authors consider a range of approaches, from screening in experimental models to computational approaches, and outline some general principles for preclinical and clinical research to help bridge the translational gap. Literature was reviewed from original publications, press releases and clinical trials.

Expert opinion: Despite remaining challenges, drug repurposing offers the opportunity to improve therapeutic options for ALS patients. Nevertheless, stringent preclinical research will be necessary to identify the most promising compounds together with innovative experimental medicine studies to bridge the translational gap. The authors further highlight the importance of combining expertise across academia, industry and wider stakeholders, which will be key in the successful delivery of repurposed therapies to the clinic.

Introduction: The landscape of early drug discovery is rapidly evolving, fueled by significant advancements in artificial intelligence (AI) and machine learning (ML), which are transforming the way drugs are discovered. As traditional drug discovery faces growing challenges in terms of time, cost, and efficacy, there is a pressing need to integrate these emerging technologies to enhance the discovery process.

Areas covered: In this perspective, the authors explore the role of AI and ML in modern early drug discovery and discuss their application in drug target identification, compound screening, and biomarker discovery. This article is based on a thorough literature search using the PubMed database to identify relevant studies that highlight the use of AI/ML models in computational chemistry, systems biology, and data-driven approaches to drug development. Emphasis is placed on how these technologies address key challenges such as data integration, predictive performance, and cost-efficiency in the drug discovery pipeline.

Expert opinion: AI and ML have the potential to revolutionize early drug discovery by improving the accuracy and speed of identifying viable drug candidates. However, successful integration of these technologies requires overcoming challenges related to data quality, model interpretability, and the need for interdisciplinary collaboration.

Introduction: The rapid emergence of infectious diseases poses a significant threat to global economies and public health. To combat this, it is crucial to develop effective treatments. One essential tool in drug design is molecular topology, which uses topological indices to build QSAR models. This mathematical framework describes chemical compound structures, facilitating easy characterization.

Areas covered: Classical ligand-based molecular topology has a series of limitations that can be overcome by shifting focus into structure-based approaches. Recent developments have emerged, focusing on target protein topology rather than drug molecules. Techniques like TDA, ESPH, LWPH, and molecular GDL are among the new methods being explored. This review is based on literature searches utilizing PubMed, Web of Science, and Google Scholar to identify articles published between the year 2000 and 2024.

Expert opinion: The authors believe that it is time to move away from traditional molecular topology and toward innovative approaches and technologies. Shifting focus from ligand-based to structure-based molecular topology, combined with new databases and algorithms, can aid in fighting drug-resistant microorganisms. This shift opens a broader chemical space for developing new anti-infective drugs, ultimately improving public health outcomes.

Introduction: Erectile dysfunction (ED) is a common condition that often signals underlying endothelial dysfunction, although the underlying causative factor(s) are likely complex and multifactorial. Various animal models have been developed to provide a research platform to study ED and served as an important basis for the discovery and subsequent development of novel therapeutic drugs for ED.

Areas covered: The review article provides an overview of various animal models in ED research with an emphasis on important drug target discovery relating to each specific experimental model. The authors highlight translation from basic science research to major preclinical and clinical studies in this evolving field of ED research.

Expert opinion: Animal models simulate the pathological features of various types of ED and clarify their molecular mechanisms. These mechanisms aid in discovering drug targets, while established ED models also provide a basis for validating drug efficacy, safety, and specific action mechanisms. The development of techniques in detection methods, cellular experimental, and omics has a profound impact on disease prediction, model evaluation, and optimization of therapeutic modalities. On this basis, many drug therapies targeting these ED-related mechanisms, especially in the nitric oxide/cyclic guanosine monophosphate pathways have been applied in preclinical studies. However, focusing on drug development for those types of ED where phosphodiesterase 5 inhibitor therapy is limited may be more valuable.