Expert Opinion on Drug Discovery最新文献_第2页

Combining cutting edge computational and experimental methods for targeting KRAS mutations in non-small cell lung cancer. 结合尖端的计算和实验方法靶向kras突变在非小细胞肺癌。

IF 4.9 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-05-01 Epub Date: 2026-04-26 DOI: 10.1080/17460441.2026.2654614

Ram Samudrala, Liana Bruggemann, Zackary Falls, Supriya D Mahajan

{"title":"Combining cutting edge computational and experimental methods for targeting KRAS mutations in non-small cell lung cancer.","authors":"Ram Samudrala, Liana Bruggemann, Zackary Falls, Supriya D Mahajan","doi":"10.1080/17460441.2026.2654614","DOIUrl":"10.1080/17460441.2026.2654614","url":null,"abstract":"Introduction: Historically, KRAS mutations have been notoriously difficult to target despite their status as the most commonly mutated oncogene in the RAS gene family. Pioneering work by Shokat and colleagues has led to the discovery of KRAS G12C-GDP mutant-specific inhibitors, with two such inhibitors adagrasib and sotorasib now FDA approved for treatment of non-small cell lung cancer (NSCLC). Unfortunately, several patients did not achieve full treatment response. Further drug discovery is urgently needed to identify compounds capable of synergizing with available KRAS G12C inhibitors to prevent drug resistance, pan-KRAS inhibitors capable of binding multiple KRAS mutations, and KRAS-GTP inhibitors.Areas covered: This review encompasses the development of the first KRAS G12C inhibitors to recent advances in precision oncology utilizing artificial intelligence (AI) to identify compounds capable of targeting KRAS G12C, D, and V individually, as well as pan-KRAS and SOS1 inhibitors.Expert opinion: Recent studies support the view that integration of AI algorithms with experimental methods is a key aspect in stream-lining the drug discovery process and identifying molecules with greater structural diversity, less off-target effects than traditional screening methods. Furthermore, the authors believe that AI will eventually become standardized in drug discovery for aggressive driver oncogenes across multiple cancers.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"507-516"},"PeriodicalIF":4.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147722271","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}

引用次数: 0

Multi-target approaches to prion disease Drug discovery: a status update. 朊病毒疾病的多靶点方法药物发现：现状更新。

IF 4.9 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-04-29 DOI: 10.1080/17460441.2026.2667912

Lea Nikolić, Giuseppe Legname

{"title":"Multi-target approaches to prion disease Drug discovery: a status update.","authors":"Lea Nikolić, Giuseppe Legname","doi":"10.1080/17460441.2026.2667912","DOIUrl":"https://doi.org/10.1080/17460441.2026.2667912","url":null,"abstract":"Introduction: Prion diseases comprise a heterogeneous group of rare and fatal neurodegenerative disorders characterized by self-propagating misfolding of the cellular prion protein. Although no therapy has yet proven capable of halting disease progression, several promising approaches are beginning to shift the field from repeated disappointment toward cautious but genuine translational optimism.Areas covered: This review examines emerging therapeutic approaches targeting key nodes of prion biology, including prion protein-targeting strategies and interventions directed at cellular pathways involved in disease pathogenesis. The authors further discuss the potential and challenges associated with polypharmacology, such as drug combinations and multi-target-directed ligands, which aim to address the biological complexity of prion disease.Expert opinion: The persistent limitations of single-target therapies for human prion disease emphasize the need to better align therapeutic strategies with disease stage, biological heterogeneity, and network-level pathogenesis. Achieving meaningful therapeutic impact will require an integrated strategy that brings together earlier intervention, improved patient stratification, and rational use of combination and multi-target approaches, supported by advances in biomarkers and experimental modeling.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147766667","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}

引用次数: 0

The root cause: why do so many drugs fail to translate from bench to bedside? 根本原因是：为什么这么多的药物不能从实验室转化为临床？

IF 4.9 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-04-23 DOI: 10.1080/17460441.2026.2665217

Andre Levchenko, Mark Corrigan, Bruce Wexler

引用次数: 0

The latest in vitro models for novel uveal melanoma drug discovery: how effective are they and what needs to be done? 新型葡萄膜黑色素瘤药物发现的最新体外模型：它们的效果如何？需要做些什么？

IF 4.9 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-04-01 Epub Date: 2026-03-10 DOI: 10.1080/17460441.2026.2642974

Lauren A Dalvin, Stephanie D Burr, Hien Ong, James A Armitage

{"title":"The latest in vitro models for novel uveal melanoma drug discovery: how effective are they and what needs to be done?","authors":"Lauren A Dalvin, Stephanie D Burr, Hien Ong, James A Armitage","doi":"10.1080/17460441.2026.2642974","DOIUrl":"10.1080/17460441.2026.2642974","url":null,"abstract":"Introduction: Uveal melanoma (UM) is the most common primary intraocular malignancy in adults, but primary tumor treatment carries a high risk of permanent vision loss and does not adequately prevent metastatic progression. In vitro UM models are needed to accurately represent human disease to support translation of laboratory research to the clinic.Areas covered: This review covers current and emerging in vitro UM models. A PubMed search used keywords 'uveal melanoma' and 'cell line,' 'spheroid,' 'organoid,' 'culture,' or 'in vitro' to identify cell lines, three-dimensional (3D) cultures (spheroids and organoids), and co-culture systems. Model successes and shortcomings are described, considering features that make models more or less representative of in vivo human UM. Insights are provided for consideration when selecting UM models for novel drug discovery.Expert opinion: While traditional cell lines have provided an important foundation for UM research, emerging spheroid and patient-derived organoid models may more accurately represent in vivo tumor behavior and the tumor microenvironment. Pairing these 3D models with co-culture techniques could dramatically improve the representativeness of UM models. Researchers should consider testing promising therapeutics on a panel of models representing different UM subtypes, with particular attention to high-risk UM, such as those with BAP1 loss.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"393-404"},"PeriodicalIF":4.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13010537/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147431486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Advanced in silico drug design strategies for mitigating transplant rejection: a status update. 缓解移植排斥反应的先进硅药物设计策略：现状更新。

IF 4.9 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-04-01 Epub Date: 2026-03-10 DOI: 10.1080/17460441.2026.2642965

Rafael Alfaro, Gema González-Martínez, Manuel Muro-Pérez, José A Galián, Helios Martínez-Banaclocha, Marina Fernández-González, Carmen Botella, María R Moya-Quiles, Javier Muro, Santiago Llorente, Manuel Muro

{"title":"Advanced in silico drug design strategies for mitigating transplant rejection: a status update.","authors":"Rafael Alfaro, Gema González-Martínez, Manuel Muro-Pérez, José A Galián, Helios Martínez-Banaclocha, Marina Fernández-González, Carmen Botella, María R Moya-Quiles, Javier Muro, Santiago Llorente, Manuel Muro","doi":"10.1080/17460441.2026.2642965","DOIUrl":"10.1080/17460441.2026.2642965","url":null,"abstract":"Introduction: Current immunosuppressive regimens in solid organ transplantation (SOT) have markedly improved short-term graft survival. However, the adverse effects of these drugs, together with incomplete control of rejection, underscore the need for new, more selective therapies. In silico approaches offer a useful and underexploited avenue in SOT.Areas covered: This review summarizes in silico strategies used to discover drugs for the prevention of allograft rejection. The authors discuss the identification of therapeutic targets using omics data, followed by computational drug repositioning approaches and the main principles of computer-aided drug design (CADD). They also highlight applications to immune targets that are relevant to transplantation. Finally, the authors examine emerging advances in quantitative systems pharmacology (QSP) and virtual clinical trials and their potential use in SOT. The literature was identified through searches of PubMed and Scopus for articles published between 2015 and 2025, from the last 10 years in SOT and, when necessary, on work in related immune-mediated diseases.Expert opinion: In silico approaches already offer a framework to prioritize safer and more selective immunomodulators in SOT. However, integration across omics-based target discovery, CADD, computational repurposing and QSP is still uncommon in this field. Building multidisciplinary consortia and adopting more standardized analytical workflows will be essential to unlock their full translational potential.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"405-416"},"PeriodicalIF":4.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147389478","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}

引用次数: 0

An introduction to GitHub and its significance for AI-driven drug discovery. 介绍GitHub及其对ai驱动的药物发现的意义。

IF 4.9 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-04-01 Epub Date: 2026-03-07 DOI: 10.1080/17460441.2026.2641511

Abdallah Abou Hajal, Lana Bustanji, Richard A Bryce, Mohammad A Ghattas

{"title":"An introduction to GitHub and its significance for AI-driven drug discovery.","authors":"Abdallah Abou Hajal, Lana Bustanji, Richard A Bryce, Mohammad A Ghattas","doi":"10.1080/17460441.2026.2641511","DOIUrl":"10.1080/17460441.2026.2641511","url":null,"abstract":"Introduction: GitHub has become essential to AI-driven drug discovery by facilitating code sharing, collaboration, and reproducible workflows. As more tools for screening, modeling, and data-driven decision-making are hosted on GitHub, researchers need clear, rigorous methods to identify, evaluate, and reuse repositories in a scientifically robust manner.Areas covered: In this report, the authors summarize GitHub concepts most relevant to research practice (e.g. repositories, documentation, licensing, releases, testing, and archiving) and propose a practical framework for navigating drug-discovery repositories. The report incorporates a Scopus trend analysis from 2013 to 2024 using a GitHub-focused search with drug discovery keywords, as well as keyword-based counts of GitHub repositories in selected categories to show topic density.Expert opinion: GitHub repositories should be recognized as peer-assessable research outputs in AI-driven drug discovery rather than as supplementary material. At a minimum, this means clear documentation of intended use and limitations, a pinned environment or container for reproducibility, an explicit license, and automated testing via continuous integration. In addition, enhanced validation and governance are necessary to bridge exploratory research code with translational and industrial reliability expectations.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"387-392"},"PeriodicalIF":4.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147354442","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}

引用次数: 0

The futility of the familiar: rethinking strategies for the development of small molecules for neurodegenerative disorders. 无用的熟悉：重新思考策略的发展小分子神经退行性疾病。

IF 4.9 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-04-01 Epub Date: 2026-03-22 DOI: 10.1080/17460441.2026.2646603

Manuel Novás, Maria João Matos, Christina Li Lin Chai

{"title":"The futility of the familiar: rethinking strategies for the development of small molecules for neurodegenerative disorders.","authors":"Manuel Novás, Maria João Matos, Christina Li Lin Chai","doi":"10.1080/17460441.2026.2646603","DOIUrl":"10.1080/17460441.2026.2646603","url":null,"abstract":"Introduction: As life expectancy increases globally, the prevalence of neurodegenerative disorders such as Alzheimer's and Parkinson's diseases continues to rise. Despite decades of intensive research and substantial investment, effective preventive or curative treatments remain unavailable. Much of the drug discovery efforts has focused on small-molecule therapeutics. However, these approaches have yielded limited clinical success. This lack of progress underscores the inherent complexity of neurodegenerative diseases and suggests that conventional drug discovery paradigms may be overly simplistic or fundamentally flawed.Areas covered: In this article, the authors explore the key challenges underlying the failure of small-molecule strategies in neurodegenerative research and discuss emerging avenues that may offer more promising therapeutic outcomes for brain disorders.Expert opinion: Conventional approaches in CNS drug discovery and development have not yielded disease-modifying CNS drugs. To be successful, it is important to rethink strategies, assays, animal models from scratch and redesign how R&D in CNS diseases should be carried out.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"375-386"},"PeriodicalIF":4.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147466798","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}

引用次数: 0

Recent developments in pharmacophore-based modeling of Ca^2+/Calmodulin-dependent protein kinase II delta (CaMkIIδ) inhibitors for heart failure therapy. 基于药物团模型的Ca2+/钙调素依赖性蛋白激酶IIδ (CaMkIIδ)抑制剂治疗心力衰竭的最新进展。

IF 4.9 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-04-01 Epub Date: 2026-03-13 DOI: 10.1080/17460441.2026.2643408

Safa Dauod, Mutasem O Taha

{"title":"Recent developments in pharmacophore-based modeling of Ca2+/Calmodulin-dependent protein kinase II delta (CaMkIIδ) inhibitors for heart failure therapy.","authors":"Safa Dauod, Mutasem O Taha","doi":"10.1080/17460441.2026.2643408","DOIUrl":"10.1080/17460441.2026.2643408","url":null,"abstract":"Introduction: Calcium/calmodulin-dependent protein kinase II delta (CaMKIIδ) regulates cardiac excitation - contraction coupling and contributes to heart failure onset and progression. Sustained CaMKIIδ activation promotes sarcoplasmic reticulum Ca2+ leak, arrhythmias, maladaptive remodeling, and contractile dysfunction, making CaMKIIδ inhibition an attractive therapeutic strategy.Areas covered: This narrative review surveys computational approaches for discovering CaMKIIδ inhibitors, emphasizing pharmacophore modeling. The authors summarize ligand- and structure-based pharmacophore methods, their coupling to docking and QSAR, and their use in virtual screening and scaffold hopping, highlighting studies that prospectively identified and synthesized new inhibitors. They also cover machine learning - assisted discovery and drug-repurposing efforts that nominated approved agents (e.g. ruxolitinib and hesperadin) as CaMKIIδ inhibitors, and outline major ATP-site - targeting chemotypes reported to date. Literature was searched in PubMed, Scopus, Web of Science, and Google Scholar (January 2000-December 2025) using 'CaMKII inhibitor,' 'CaMKIIδ pharmacophore,' 'CaMKII molecular modeling,' 'CaMKII virtual screening,' and 'CaMKII drug discovery,' followed by manual reference mining.Expert opinion: Pharmacophore-driven CaMKIIδ modeling remains underused. Progress should integrate AI/deep learning, isoform-aware selectivity filters, state- and PTM-specific targeting, and rigorous experimental validation to deliver potent, selective, clinically viable inhibitors for heart failure. Standardized benchmarking, transparent negative results, and selectivity panels against CaMKIIα/β/γ and kinome off-targets will aid translation substantially.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"417-431"},"PeriodicalIF":4.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147456064","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}

引用次数: 0

Advancing AI-driven drug discovery: an interview with Professor Alan Talevi. 推进人工智能驱动的药物发现：Alan Talevi教授访谈

IF 4.9 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-04-01 Epub Date: 2026-03-05 DOI: 10.1080/17460441.2026.2638026

Alan Talevi

引用次数: 0

The integration of AI in fragment-based lead discovery and medicinal chemistry - an interview with professor György M Keserű. 人工智能在基于片段的铅发现和药物化学中的整合-对György M kesersel教授的采访。

IF 4.9 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-04-01 Epub Date: 2026-03-06 DOI: 10.1080/17460441.2026.2638054

György M Keserű

引用次数: 0