Nature Reviews. Drug Discovery最新文献_第2页

Targeting CDKs in the RNAPII transcription cycle. 靶向RNAPII转录周期中的CDKs。

IF 91.2 1区医学

Nature Reviews. Drug Discovery Pub Date : 2026-08-24 DOI: 10.1038/s41573-026-01517-0

Robert P Fisher, Matthias Geyer

{"title":"Targeting CDKs in the RNAPII transcription cycle.","authors":"Robert P Fisher, Matthias Geyer","doi":"10.1038/s41573-026-01517-0","DOIUrl":"https://doi.org/10.1038/s41573-026-01517-0","url":null,"abstract":"Cyclin-dependent kinases (CDKs) are central regulators of both the cell division cycle and RNA polymerase II (RNAPII)-mediated transcription and have long been pursued as therapeutic targets in cancer and other diseases. Although drug discovery efforts have historically focused on cell-cycle CDKs, transcriptional CDKs have emerged in the past 10-15 years as promising therapeutic candidates. In this Review, we discuss our current understanding of how CDKs regulate gene expression throughout all stages of transcription from initiation and elongation to termination and beyond. We examine how transcriptional or co-transcriptional processes become dysregulated in cancer cells, and how this dysfunction might create targetable vulnerabilities. We also summarize advances in therapeutic strategies targeting transcriptional CDKs, including reversible and covalent inhibitors, degraders, molecular glues and bivalent proximity-inducing modalities such as transcriptional and epigenetic chemical inducers of proximity, which can rewire transcriptional networks in vivo. Finally, we highlight the key mechanistic, translational and clinical challenges that must be addressed to realise the therapeutic potential of targeting transcriptional CDKs in cancer and inflammation.","PeriodicalId":19068,"journal":{"name":"Nature Reviews. Drug Discovery","volume":" ","pages":""},"PeriodicalIF":91.2,"publicationDate":"2026-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148813571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Towards precision psychiatry: initial foundations and future directions. 走向精确精神病学：最初的基础和未来的方向。

IF 91.2 1区医学

Nature Reviews. Drug Discovery Pub Date : 2026-08-24 DOI: 10.1038/s41573-026-01509-0

Amit Etkin, Patricio O'Donnell, Kerry J Ressler, Husseini Manji

{"title":"Towards precision psychiatry: initial foundations and future directions.","authors":"Amit Etkin, Patricio O'Donnell, Kerry J Ressler, Husseini Manji","doi":"10.1038/s41573-026-01509-0","DOIUrl":"https://doi.org/10.1038/s41573-026-01509-0","url":null,"abstract":"Psychiatric disorders carry a major public health burden, yet advances in treatment have been slow to emerge, partly owing to reliance on traditional symptom-based diagnostic frameworks. In this Perspective, we explore the emerging paradigm of precision psychiatry, which seeks to align therapeutic development with underlying neural biology dysfunctions using biomarkers. Drawing lessons from the success of precision oncology and neurology, precision psychiatry utilizes patient-specific biological measures of brain function - such as electroencephalography, objective behavioural assessments, functional magnetic resonance imaging and peripheral biomarkers - to understand drugs' effects on the brain, define indications and stratify patient populations for targeted intervention development. We discuss mechanistic approaches that focus on excitation-inhibition balance, reward and aversion circuits, hippocampal-prefrontal neuroplasticity, and processing of social cues, highlighting how these frameworks can elucidate drug mechanisms and predict treatment responses. Proof-of-concept examples, including predictors of response to standard-of-care treatments, and patient subgroup-driven successes in postpartum depression and schizophrenia, underscore the potential of stratified trials to reduce development risks and improve clinical outcomes. We address ongoing and future regulatory, commercial and clinical considerations for integrating scalable and reproducible biomarkers into drug development. Precision psychiatry thus represents a new strategy to refine clinical trial design and develop biology-defined treatments, which may help to overcome longstanding challenges in psychiatric drug discovery.","PeriodicalId":19068,"journal":{"name":"Nature Reviews. Drug Discovery","volume":" ","pages":""},"PeriodicalIF":91.2,"publicationDate":"2026-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148813654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Oncolytic virus nabs FDA approval. 溶瘤病毒获得FDA批准。

IF 91.2 1区医学

Nature Reviews. Drug Discovery Pub Date : 2026-08-12 DOI: 10.1038/d41573-026-00136-z

Asher Mullard

引用次数: 0

Orexin receptor agonist secures landmark narcolepsy approval. 食欲素受体激动剂获得里程碑式嗜睡症批准

IF 91.2 1区医学

Nature Reviews. Drug Discovery Pub Date : 2026-08-10 DOI: 10.1038/d41573-026-00135-0

Katie Kingwell

引用次数: 0

Artificial intelligence in drug discovery - what it is, where we stand and the path forward. 药物发现中的人工智能——它是什么，我们的立场和前进的道路。

IF 91.2 1区医学

Nature Reviews. Drug Discovery Pub Date : 2026-08-07 DOI: 10.1038/s41573-026-01496-2

Andreas Bender, Morgan C Thomas, Jack W Scannell, David A Shaywitz, Gian Marco Ghiandoni, Joe G Greener, Lavinia-Lorena Pruteanu, Rachel DeVay Jacobson, Koichi Handa, Mariko Hirano, Srijit Seal, Manas Mahale, Marco F Schmidt, Tim Ahfeldt, Francesca Grisoni, Isidro Cortes-Ciriano

{"title":"Artificial intelligence in drug discovery - what it is, where we stand and the path forward.","authors":"Andreas Bender, Morgan C Thomas, Jack W Scannell, David A Shaywitz, Gian Marco Ghiandoni, Joe G Greener, Lavinia-Lorena Pruteanu, Rachel DeVay Jacobson, Koichi Handa, Mariko Hirano, Srijit Seal, Manas Mahale, Marco F Schmidt, Tim Ahfeldt, Francesca Grisoni, Isidro Cortes-Ciriano","doi":"10.1038/s41573-026-01496-2","DOIUrl":"https://doi.org/10.1038/s41573-026-01496-2","url":null,"abstract":"Artificial intelligence (AI) in drug discovery has attracted increasing interest over the past decade. It is now time for a critical review of progress in the field: where did we advance - and where are we yet to see impact - when it comes to what matters in drug discovery, which is to deliver safer and more efficacious medicines to patients faster? Although a wide variety of AI methods have been developed, applied and benchmarked, evidence of their clinically relevant impact is, so far, disappointingly limited. In this Perspective we discuss potential reasons, including an insufficient focus on clinical translation during model development, difficulties with applying AI algorithms on conditional life science data, and insufficient problem definitions and the resulting underspecification of computational models for real-world use cases. 'Technology push' compared with 'science pull' is also likely to be an underlying factor, as well as the substantial time required to operationalize technical capabilities into systems that are sufficiently scaled and accessible for users. We provide recommendations for the development of AI in drug discovery with the aim of increasing its translational relevance. For example, benchmarking studies of AI tools in drug discovery need to move on from model validation and instead focus on their ability to improve decision making.","PeriodicalId":19068,"journal":{"name":"Nature Reviews. Drug Discovery","volume":" ","pages":""},"PeriodicalIF":91.2,"publicationDate":"2026-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148689623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Lilly spends US$2.8 billion on psychedelic drugs for mental health 礼来公司在用于精神健康的迷幻药物上花费了28亿美元。

IF 91.2 1区医学

Nature Reviews. Drug Discovery Pub Date : 2026-08-06 DOI: 10.1038/d41573-026-00134-1

Asher Mullard

引用次数: 0

First dual BAFF and APRIL inhibitor nabs FDA approval 首个双BAFF和APRIL抑制剂获得FDA批准。

IF 91.2 1区医学

Nature Reviews. Drug Discovery Pub Date : 2026-08-06 DOI: 10.1038/d41573-026-00133-2

Asher Mullard

引用次数: 0

Expanding the molecular glue target space 扩大分子胶靶空间。

IF 91.2 1区医学

Nature Reviews. Drug Discovery Pub Date : 2026-08-05 DOI: 10.1038/d41573-026-00132-3

M. Teresa Villanueva

引用次数: 0

Phage therapy for Crohn’s disease 克罗恩病的噬菌体疗法

IF 91.2 1区医学

Nature Reviews. Drug Discovery Pub Date : 2026-08-04 DOI: 10.1038/d41573-026-00126-1

Sarah Crunkhorn

引用次数: 0

Gene megacluster produces synergistic antibiotics 基因巨簇产生协同抗生素。

IF 91.2 1区医学

Nature Reviews. Drug Discovery Pub Date : 2026-08-04 DOI: 10.1038/d41573-026-00128-z

Sarah Crunkhorn

引用次数: 0