Pub Date : 2024-06-01Epub Date: 2024-05-07DOI: 10.1080/17460441.2024.2350567
Ana Margarida Sousa, Maria Olívia Pereira
{"title":"Challenges with drug efficacy prediction of in vitro models of biofilms infecting cystic fibrosis airway.","authors":"Ana Margarida Sousa, Maria Olívia Pereira","doi":"10.1080/17460441.2024.2350567","DOIUrl":"10.1080/17460441.2024.2350567","url":null,"abstract":"","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140857673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Introduction: Peptide foldamers play a critical role in pharmaceutical research and biomedical applications. This review highlights recent (post-2020) advancements in novel foldamers, synthetic techniques, and their applications in pharmaceutical research.
Areas covered: The authors summarize the structures and applications of peptide foldamers such as α, β, γ-peptides, hydrocarbon-stapled peptides, urea-type foldamers, sulfonic-γ-amino acid foldamers, aromatic foldamers, and peptoids, which tackle the challenges of traditional peptide drugs. Regarding antimicrobial use, foldamers have shown progress in their potential against drug-resistant bacteria. In drug development, peptide foldamers have been used as drug delivery systems (DDS) and protein-protein interaction (PPI) inhibitors.
Expert opinion: These structures exhibit resistance to enzymatic degradation, are promising for therapeutic delivery, and disrupt crucial PPIs associated with diseases such as cancer with specificity, versatility, and stability, which are useful therapeutic properties. However, the complexity and cost of their synthesis, along with the necessity for thorough safety and efficacy assessments, necessitate extensive research and cross-sector collaboration. Advances in synthesis methods, computational modeling, and targeted delivery systems are essential for fully realizing the therapeutic potential of foldamers and integrating them into mainstream medical treatments.
{"title":"Innovative peptide architectures: advancements in foldamers and stapled peptides for drug discovery.","authors":"Zhou Dongrui, Maho Miyamoto, Hidetomo Yokoo, Yosuke Demizu","doi":"10.1080/17460441.2024.2350568","DOIUrl":"10.1080/17460441.2024.2350568","url":null,"abstract":"<p><strong>Introduction: </strong>Peptide foldamers play a critical role in pharmaceutical research and biomedical applications. This review highlights recent (post-2020) advancements in novel foldamers, synthetic techniques, and their applications in pharmaceutical research.</p><p><strong>Areas covered: </strong>The authors summarize the structures and applications of peptide foldamers such as α, β, γ-peptides, hydrocarbon-stapled peptides, urea-type foldamers, sulfonic-γ-amino acid foldamers, aromatic foldamers, and peptoids, which tackle the challenges of traditional peptide drugs. Regarding antimicrobial use, foldamers have shown progress in their potential against drug-resistant bacteria. In drug development, peptide foldamers have been used as drug delivery systems (DDS) and protein-protein interaction (PPI) inhibitors.</p><p><strong>Expert opinion: </strong>These structures exhibit resistance to enzymatic degradation, are promising for therapeutic delivery, and disrupt crucial PPIs associated with diseases such as cancer with specificity, versatility, and stability, which are useful therapeutic properties. However, the complexity and cost of their synthesis, along with the necessity for thorough safety and efficacy assessments, necessitate extensive research and cross-sector collaboration. Advances in synthesis methods, computational modeling, and targeted delivery systems are essential for fully realizing the therapeutic potential of foldamers and integrating them into mainstream medical treatments.</p>","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140957000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-01Epub Date: 2024-05-16DOI: 10.1080/17460441.2024.2354287
Guixian Zhao, Mengping Zhu, Yangfeng Li, Gong Zhang, Yizhou Li
Introduction: The effectiveness of Fragment-based drug design (FBDD) for targeting challenging therapeutic targets has been hindered by two factors: the small library size and the complexity of the fragment-to-hit optimization process. The DNA-encoded library (DEL) technology offers a compelling and robust high-throughput selection approach to potentially address these limitations.
Area covered: In this review, the authors propose the viewpoint that the DEL technology matches perfectly with the concept of FBDD to facilitate hit discovery. They begin by analyzing the technical limitations of FBDD from a medicinal chemistry perspective and explain why DEL may offer potential solutions to these limitations. Subsequently, they elaborate in detail on how the integration of DEL with FBDD works. In addition, they present case studies involving both de novo hit discovery and full ligand discovery, especially for challenging therapeutic targets harboring broad drug-target interfaces.
Expert opinion: The future of DEL-based fragment discovery may be promoted by both technical advances and application scopes. From the technical aspect, expanding the chemical diversity of DEL will be essential to achieve success in fragment-based drug discovery. From the application scope side, DEL-based fragment discovery holds promise for tackling a series of challenging targets.
导言:基于片段的药物设计(FBDD)针对具有挑战性的治疗靶点的有效性一直受到两个因素的阻碍:小规模的文库和片段到靶点优化过程的复杂性。DNA编码文库(DEL)技术提供了一种引人注目且稳健的高通量选择方法,有可能解决这些局限性:在这篇综述中,作者提出了一种观点,即 DEL 技术与 FBDD 的概念完全匹配,可促进命中发现。他们首先从药物化学的角度分析了FBDD的技术局限性,并解释了为什么DEL可以为这些局限性提供潜在的解决方案。随后,他们详细阐述了 DEL 与 FBDD 的整合工作原理。此外,他们还介绍了一些案例研究,包括新药发现和全配体发现,特别是针对具有广泛药物靶点界面的挑战性治疗靶点:基于 DEL 的片段发现的未来可能会受到技术进步和应用范围的双重推动。从技术层面来看,扩大 DEL 的化学多样性对于片段药物发现的成功至关重要。从应用范围来看,基于 DEL 的片段发现有望解决一系列具有挑战性的靶点。
{"title":"Using DNA-encoded libraries of fragments for hit discovery of challenging therapeutic targets.","authors":"Guixian Zhao, Mengping Zhu, Yangfeng Li, Gong Zhang, Yizhou Li","doi":"10.1080/17460441.2024.2354287","DOIUrl":"10.1080/17460441.2024.2354287","url":null,"abstract":"<p><strong>Introduction: </strong>The effectiveness of Fragment-based drug design (FBDD) for targeting challenging therapeutic targets has been hindered by two factors: the small library size and the complexity of the fragment-to-hit optimization process. The DNA-encoded library (DEL) technology offers a compelling and robust high-throughput selection approach to potentially address these limitations.</p><p><strong>Area covered: </strong>In this review, the authors propose the viewpoint that the DEL technology matches perfectly with the concept of FBDD to facilitate hit discovery. They begin by analyzing the technical limitations of FBDD from a medicinal chemistry perspective and explain why DEL may offer potential solutions to these limitations. Subsequently, they elaborate in detail on how the integration of DEL with FBDD works. In addition, they present case studies involving both <i>de novo</i> hit discovery and full ligand discovery, especially for challenging therapeutic targets harboring broad drug-target interfaces.</p><p><strong>Expert opinion: </strong>The future of DEL-based fragment discovery may be promoted by both technical advances and application scopes. From the technical aspect, expanding the chemical diversity of DEL will be essential to achieve success in fragment-based drug discovery. From the application scope side, DEL-based fragment discovery holds promise for tackling a series of challenging targets.</p>","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140957008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-01Epub Date: 2024-05-10DOI: 10.1080/17460441.2024.2348157
Davide Bassani, Neil John Parrott, Nenad Manevski, Jitao David Zhang
Introduction: Prediction of pharmacokinetic (PK) properties is crucial for drug discovery and development. Machine-learning (ML) models, which use statistical pattern recognition to learn correlations between input features (such as chemical structures) and target variables (such as PK parameters), are being increasingly used for this purpose. To embed ML models for PK prediction into workflows and to guide future development, a solid understanding of their applicability, advantages, limitations, and synergies with other approaches is necessary.
Areas covered: This narrative review discusses the design and application of ML models to predict PK parameters of small molecules, especially in light of established approaches including in vitro-in vivo extrapolation (IVIVE) and physiologically based pharmacokinetic (PBPK) models. The authors illustrate scenarios in which the three approaches are used and emphasize how they enhance and complement each other. In particular, they highlight achievements, the state of the art and potentials of applying machine learning for PK prediction through a comphrehensive literature review.
Expert opinion: ML models, when carefully crafted, regularly updated, and appropriately used, empower users to prioritize molecules with favorable PK properties. Informed practitioners can leverage these models to improve the efficiency of drug discovery and development process.
导言:药代动力学(PK)特性预测对于药物发现和开发至关重要。机器学习(ML)模型利用统计模式识别来学习输入特征(如化学结构)和目标变量(如 PK 参数)之间的相关性,正越来越多地用于这一目的。为了将用于 PK 预测的 ML 模型嵌入工作流程并指导未来的发展,有必要深入了解这些模型的适用性、优势、局限性以及与其他方法的协同作用:这篇叙述性综述讨论了预测小分子 PK 参数的 ML 模型的设计和应用,特别是考虑到体外-体内外推法(IVIVE)和基于生理的药代动力学(PBPK)模型等既定方法。作者举例说明了这三种方法的应用场景,并强调了它们如何相互促进和补充。特别是,他们通过全面的文献综述,强调了应用机器学习进行 PK 预测的成就、技术水平和潜力:专家观点:机器学习模型经过精心设计、定期更新和合理使用,可以帮助用户优先选择具有良好 PK 特性的分子。知情的从业人员可以利用这些模型提高药物发现和开发过程的效率。
{"title":"Another string to your bow: machine learning prediction of the pharmacokinetic properties of small molecules.","authors":"Davide Bassani, Neil John Parrott, Nenad Manevski, Jitao David Zhang","doi":"10.1080/17460441.2024.2348157","DOIUrl":"10.1080/17460441.2024.2348157","url":null,"abstract":"<p><strong>Introduction: </strong>Prediction of pharmacokinetic (PK) properties is crucial for drug discovery and development. Machine-learning (ML) models, which use statistical pattern recognition to learn correlations between input features (such as chemical structures) and target variables (such as PK parameters), are being increasingly used for this purpose. To embed ML models for PK prediction into workflows and to guide future development, a solid understanding of their applicability, advantages, limitations, and synergies with other approaches is necessary.</p><p><strong>Areas covered: </strong>This narrative review discusses the design and application of ML models to predict PK parameters of small molecules, especially in light of established approaches including <i>in vitro-in vivo</i> extrapolation (IVIVE) and physiologically based pharmacokinetic (PBPK) models. The authors illustrate scenarios in which the three approaches are used and emphasize how they enhance and complement each other. In particular, they highlight achievements, the state of the art and potentials of applying machine learning for PK prediction through a comphrehensive literature review.</p><p><strong>Expert opinion: </strong>ML models, when carefully crafted, regularly updated, and appropriately used, empower users to prioritize molecules with favorable PK properties. Informed practitioners can leverage these models to improve the efficiency of drug discovery and development process.</p>","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140897857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-01Epub Date: 2024-05-10DOI: 10.1080/17460441.2024.2354279
Claudio N Cavasotto, Juan I Di Filippo, Valeria Scardino
{"title":"Lessons learnt from machine learning in early stages of drug discovery.","authors":"Claudio N Cavasotto, Juan I Di Filippo, Valeria Scardino","doi":"10.1080/17460441.2024.2354279","DOIUrl":"10.1080/17460441.2024.2354279","url":null,"abstract":"","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140897858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-01Epub Date: 2024-05-07DOI: 10.1080/17460441.2024.2349155
Silvane Maria Fonseca Murta, Pedro Augusto Lemos Santana, Thibault Joseph William Jacques Dit Lapierre, André Berndt Penteado, Marissa El Hajje, Thabata Corazza Navarro Vinha, Daniel Barbosa Liarte, Mariana Laureano de Souza, Gustavo Henrique Goulart Trossini, Celso de Oliveira Rezende Júnior, Renata Barbosa de Oliveira, Rafaela Salgado Ferreira
Introduction: Benznidazole, the drug of choice for treating Chagas Disease (CD), has significant limitations, such as poor cure efficacy, mainly in the chronic phase of CD, association with side effects, and parasite resistance. Understanding parasite resistance to benznidazole is crucial for developing new drugs to treat CD.
Areas covered: Here, the authors review the current understanding of the molecular basis of benznidazole resistance. Furthermore, they discuss the state-of-the-art methods and critical outcomes employed to evaluate the efficacy of potential drugs against T.cruzi, aiming to select better compounds likely to succeed in the clinic. Finally, the authors describe the different strategies employed to overcome resistance to benznidazole and find effective new treatments for CD.
Expert opinion: Resistance to benznidazole is a complex phenomenon that occurs naturally among T.cruzi strains. The combination of compounds that inhibit different metabolic pathways of the parasite is an important strategy for developing a new chemotherapeutic protocol.
导言:苯并咪唑是治疗南美锥虫病(CD)的首选药物,但它有很大的局限性,如疗效不佳(主要是在 CD 的慢性期)、副作用和寄生虫抗药性。了解寄生虫对苯并咪唑的抗药性对于开发治疗南美锥虫病的新药至关重要:在此,作者回顾了目前对苯并咪唑耐药性分子基础的理解。此外,他们还讨论了评估潜在药物对 T. cruzi 的疗效所采用的最先进方法和关键结果,旨在筛选出可能在临床上取得成功的更好的化合物。最后,作者介绍了为克服苯并咪唑耐药性并找到有效的CD新疗法而采用的不同策略:对苯并咪唑的耐药性是一种复杂的现象,在克鲁斯绦虫菌株中自然存在。结合抑制寄生虫不同代谢途径的化合物是开发新化疗方案的重要策略。
{"title":"New drug discovery strategies for the treatment of benznidazole-resistance in <i>Trypanosoma cruzi</i>, the causative agent of Chagas disease.","authors":"Silvane Maria Fonseca Murta, Pedro Augusto Lemos Santana, Thibault Joseph William Jacques Dit Lapierre, André Berndt Penteado, Marissa El Hajje, Thabata Corazza Navarro Vinha, Daniel Barbosa Liarte, Mariana Laureano de Souza, Gustavo Henrique Goulart Trossini, Celso de Oliveira Rezende Júnior, Renata Barbosa de Oliveira, Rafaela Salgado Ferreira","doi":"10.1080/17460441.2024.2349155","DOIUrl":"10.1080/17460441.2024.2349155","url":null,"abstract":"<p><strong>Introduction: </strong>Benznidazole, the drug of choice for treating Chagas Disease (CD), has significant limitations, such as poor cure efficacy, mainly in the chronic phase of CD, association with side effects, and parasite resistance. Understanding parasite resistance to benznidazole is crucial for developing new drugs to treat CD.</p><p><strong>Areas covered: </strong>Here, the authors review the current understanding of the molecular basis of benznidazole resistance. Furthermore, they discuss the state-of-the-art methods and critical outcomes employed to evaluate the efficacy of potential drugs against <i>T.</i> <i>cruzi</i>, aiming to select better compounds likely to succeed in the clinic. Finally, the authors describe the different strategies employed to overcome resistance to benznidazole and find effective new treatments for CD.</p><p><strong>Expert opinion: </strong>Resistance to benznidazole is a complex phenomenon that occurs naturally among <i>T.</i> <i>cruzi</i> strains. The combination of compounds that inhibit different metabolic pathways of the parasite is an important strategy for developing a new chemotherapeutic protocol.</p>","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140876171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Introduction: Modern drug discovery revolves around designing ligands that target the chosen biomolecule, typically proteins. For this, the evaluation of affinities of putative ligands is crucial. This has given rise to a multitude of dedicated computational and experimental methods that are constantly being developed and improved.
Areas covered: In this review, the authors reassess both the industry mainstays and the newest trends among the methods for protein - small-molecule affinity determination. They discuss both computational affinity predictions and experimental techniques, describing their basic principles, main limitations, and advantages. Together, this serves as initial guide to the currently most popular and cutting-edge ligand-binding assays employed in rational drug design.
Expert opinion: The affinity determination methods continue to develop toward miniaturization, high-throughput, and in-cell application. Moreover, the availability of data analysis tools has been constantly increasing. Nevertheless, cross-verification of data using at least two different techniques and careful result interpretation remain of utmost importance.
{"title":"Recent advances in computational and experimental protein-ligand affinity determination techniques.","authors":"Visvaldas Kairys, Lina Baranauskiene, Migle Kazlauskiene, Asta Zubrienė, Vytautas Petrauskas, Daumantas Matulis, Egidijus Kazlauskas","doi":"10.1080/17460441.2024.2349169","DOIUrl":"10.1080/17460441.2024.2349169","url":null,"abstract":"<p><strong>Introduction: </strong>Modern drug discovery revolves around designing ligands that target the chosen biomolecule, typically proteins. For this, the evaluation of affinities of putative ligands is crucial. This has given rise to a multitude of dedicated computational and experimental methods that are constantly being developed and improved.</p><p><strong>Areas covered: </strong>In this review, the authors reassess both the industry mainstays and the newest trends among the methods for protein - small-molecule affinity determination. They discuss both computational affinity predictions and experimental techniques, describing their basic principles, main limitations, and advantages. Together, this serves as initial guide to the currently most popular and cutting-edge ligand-binding assays employed in rational drug design.</p><p><strong>Expert opinion: </strong>The affinity determination methods continue to develop toward miniaturization, high-throughput, and in-cell application. Moreover, the availability of data analysis tools has been constantly increasing. Nevertheless, cross-verification of data using at least two different techniques and careful result interpretation remain of utmost importance.</p>","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140876172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Introduction: Narcolepsy is a chronic and rare neurological disorder characterized by disordered sleep. Based on animal models and further research in humans, the dysfunctional orexin system was identified as a contributing factor to the pathophysiology of narcolepsy. Animal models played a larger role in the discovery of some of the pharmacological agents with established benefit/risk profiles.
Areas covered: In this review, the authors examine the phenotypes observed in animal models of narcolepsy and the characteristics of clinically used pharmacological agents in these animal models. Additionally, the authors compare the effects of clinically used pharmacological agents on the phenotypes in animal models with those observed in narcolepsy patients.
Expert opinion: Research in canine and mouse models have linked narcolepsy to the O×R2mutation and orexin deficiency, leading to new diagnostic criteria and a drug development focus. Advancements in pharmacological therapies have significantly improved narcolepsy management, with insights from both clinical experience and from animal models having led to new treatments such as low sodium oxybate and solriamfetol. However, challenges persist in addressing symptoms beyond excessive daytime sleepiness and cataplexy, highlighting the need for further research, including the development of diurnal animal models to enhance understanding and treatment options for narcolepsy.
{"title":"Hits and misses with animal models of narcolepsy and the implications for drug discovery.","authors":"Ramakrishna Nirogi, Pradeep Jayarajan, Vijay Benade, Renny Abraham, Vinod Kumar Goyal","doi":"10.1080/17460441.2024.2354293","DOIUrl":"10.1080/17460441.2024.2354293","url":null,"abstract":"<p><strong>Introduction: </strong>Narcolepsy is a chronic and rare neurological disorder characterized by disordered sleep. Based on animal models and further research in humans, the dysfunctional orexin system was identified as a contributing factor to the pathophysiology of narcolepsy. Animal models played a larger role in the discovery of some of the pharmacological agents with established benefit/risk profiles.</p><p><strong>Areas covered: </strong>In this review, the authors examine the phenotypes observed in animal models of narcolepsy and the characteristics of clinically used pharmacological agents in these animal models. Additionally, the authors compare the effects of clinically used pharmacological agents on the phenotypes in animal models with those observed in narcolepsy patients.</p><p><strong>Expert opinion: </strong>Research in canine and mouse models have linked narcolepsy to the O×R2mutation and orexin deficiency, leading to new diagnostic criteria and a drug development focus. Advancements in pharmacological therapies have significantly improved narcolepsy management, with insights from both clinical experience and from animal models having led to new treatments such as low sodium oxybate and solriamfetol. However, challenges persist in addressing symptoms beyond excessive daytime sleepiness and cataplexy, highlighting the need for further research, including the development of diurnal animal models to enhance understanding and treatment options for narcolepsy.</p>","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140920935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-01Epub Date: 2024-03-19DOI: 10.1080/17460441.2024.2331734
José L Medina-Franco, Edgar López-López
{"title":"What is the plausibility that all drugs will be designed by computers by the end of the decade?","authors":"José L Medina-Franco, Edgar López-López","doi":"10.1080/17460441.2024.2331734","DOIUrl":"10.1080/17460441.2024.2331734","url":null,"abstract":"","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140157875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-01Epub Date: 2024-03-13DOI: 10.1080/17460441.2024.2329104
Marc Rogers, Alison Obergrussberger, Artem Kondratskyi, Niels Fertig
Introduction: Automated patch clamp (APC) is now well established as a mature technology for ion channel drug discovery in academia, biotech and pharma companies, and in contract research organizations (CRO), for a variety of applications including channelopathy research, compound screening, target validation and cardiac safety testing.
Areas covered: Ion channels are an important class of drugged and approved drug targets. The authors present a review of the current state of ion channel drug discovery along with new and exciting developments in ion channel research involving APC. This includes topics such as native and iPSC-derived cells in ion channel drug discovery, channelopathy research, organellar and biologics in ion channel drug discovery.
Expert opinion: It is our belief that APC will continue to play a critical role in ion channel drug discovery, not only in 'classical' hit screening, target validation and cardiac safety testing, but extending these applications to include high throughput organellar recordings and optogenetics. In this way, with advancements in APC capabilities and applications, together with high resolution cryo-EM structures, ion channel drug discovery will be re-invigorated, leading to a growing list of ion channel ligands in clinical development.
{"title":"Using automated patch clamp electrophysiology platforms in ion channel drug discovery: an industry perspective.","authors":"Marc Rogers, Alison Obergrussberger, Artem Kondratskyi, Niels Fertig","doi":"10.1080/17460441.2024.2329104","DOIUrl":"10.1080/17460441.2024.2329104","url":null,"abstract":"<p><strong>Introduction: </strong>Automated patch clamp (APC) is now well established as a mature technology for ion channel drug discovery in academia, biotech and pharma companies, and in contract research organizations (CRO), for a variety of applications including channelopathy research, compound screening, target validation and cardiac safety testing.</p><p><strong>Areas covered: </strong>Ion channels are an important class of drugged and approved drug targets. The authors present a review of the current state of ion channel drug discovery along with new and exciting developments in ion channel research involving APC. This includes topics such as native and iPSC-derived cells in ion channel drug discovery, channelopathy research, organellar and biologics in ion channel drug discovery.</p><p><strong>Expert opinion: </strong>It is our belief that APC will continue to play a critical role in ion channel drug discovery, not only in 'classical' hit screening, target validation and cardiac safety testing, but extending these applications to include high throughput organellar recordings and optogenetics. In this way, with advancements in APC capabilities and applications, together with high resolution cryo-EM structures, ion channel drug discovery will be re-invigorated, leading to a growing list of ion channel ligands in clinical development.</p>","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140119220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}