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

Preclinical in vitro models of HNSCC and their role in drug discovery - an emphasis on the cancer microenvironment and microbiota.

IF 6 2区医学

Expert Opinion on Drug Discovery Pub Date : 2025-01-01 Epub Date: 2024-12-15 DOI: 10.1080/17460441.2024.2439456

Anne-Sophie Becker, Sonja Oehmcke-Hecht, Erik Dargel, Philipp Kaps, Thomas Freitag, Bernd Kreikemeyer, Christian Junghanss, Claudia Maletzki

{"title":"Preclinical in vitro models of HNSCC and their role in drug discovery - an emphasis on the cancer microenvironment and microbiota.","authors":"Anne-Sophie Becker, Sonja Oehmcke-Hecht, Erik Dargel, Philipp Kaps, Thomas Freitag, Bernd Kreikemeyer, Christian Junghanss, Claudia Maletzki","doi":"10.1080/17460441.2024.2439456","DOIUrl":"10.1080/17460441.2024.2439456","url":null,"abstract":"Introduction: Head and neck squamous cell carcinoma (HNSCC) is the seventh most common cancer worldwide. Treatment options and patient outcomes have not improved significantly over the past decades, increasing the need for better preclinical models. Holistic approaches that include an intact and functional immune compartment along with the patient's individual tumor microbiome will help improve the predictive value of novel drug efficacy.Areas covered: In this review, we describe the challenges of modeling the complex and heterogeneous tumor landscape in HNSCC and the importance of sophisticated patient-specific 3D in vitro models to pave the way for clinical trials with novel immunomodulatory drugs. We also discuss the impact of the tumor microbiome and the potential implications for prospective drug screening and validation trials.Expert opinion: The repertoire of well-characterized preclinical 3D in vitro models continues to grow. With the increasing attention to the complex cellular, immunological, molecular, and spatio-temporal characteristics of tumors, well-designed proof-of-concept studies to test novel drug efficacy are on the verge of providing valuable, practice-changing insights for clinical trials. Bringing together expertise and improving collaboration between clinicians, academics, and regulatory agencies will facilitate the translation of preclinical findings into clinically meaningful outcomes.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"81-101"},"PeriodicalIF":6.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142827674","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

Human pluripotent stem cell (hPSC)-derived models for autism spectrum disorder drug discovery.

IF 6 2区医学

Expert Opinion on Drug Discovery Pub Date : 2024-12-24 DOI: 10.1080/17460441.2024.2416484

Lingdi Nie, Courtney Irwin, Sarah Geahchan, Karun K Singh

{"title":"Human pluripotent stem cell (hPSC)-derived models for autism spectrum disorder drug discovery.","authors":"Lingdi Nie, Courtney Irwin, Sarah Geahchan, Karun K Singh","doi":"10.1080/17460441.2024.2416484","DOIUrl":"https://doi.org/10.1080/17460441.2024.2416484","url":null,"abstract":"Introduction: Autism spectrum disorder (ASD) is a prevalent and complex neurodevelopmental disorder (NDD) with genetic and environmental origins. Currently, there are no effective pharmacological treatments targeting core ASD features. This leads to unmet medical needs of individuals with ASD and requires relevant human disease models recapitulating genetic and clinical heterogeneity to better understand underlying mechanisms and identify potential pharmacological therapies. Recent advancements in stem cell technology have enabled the generation of human pluripotent stem cell (hPSC)-derived two-dimensional (2D) and three-dimensional (3D) neural models, which serve as powerful tools for ASD modeling and drug discovery.Areas covered: This article reviews the applications of hPSC-derived 2D and 3D neural models in studying various forms of ASD using pharmacological perturbation and drug screenings, highlighting the potential use of these models to develop novel pharmacological treatment strategies for ASD.Expert opinion: hPSC-derived models recapitulate early human brain development spatiotemporally and have allowed patient-specific mechanistic investigation and therapeutic development using advanced molecular technologies, which will contribute to precision medicine for ASD therapy. Improvements are still required in hPSC-based models to further enhance their physiological relevance, clinical translation, and scalability for ASD drug discovery.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1-19"},"PeriodicalIF":6.0,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142881761","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

Lessons learned from phenotypic drug discovery efforts. 从表型药物发现工作中汲取的经验教训。

IF 6 2区医学

Expert Opinion on Drug Discovery Pub Date : 2024-12-18 DOI: 10.1080/17460441.2024.2442741

David C Swinney

引用次数: 0

Advances in the design and discovery of next-generation janus kinase-2 (JAK2) inhibitors for the treatment of myeloproliferative neoplasms. 用于治疗骨髓增生性肿瘤的新一代破伤风激酶-2 (JAK2)抑制剂的设计和发现进展。

IF 6 2区医学

Expert Opinion on Drug Discovery Pub Date : 2024-12-01 Epub Date: 2024-10-16 DOI: 10.1080/17460441.2024.2417368

Safa Daoud, Mutasem Omar Taha

{"title":"Advances in the design and discovery of next-generation janus kinase-2 (JAK2) inhibitors for the treatment of myeloproliferative neoplasms.","authors":"Safa Daoud, Mutasem Omar Taha","doi":"10.1080/17460441.2024.2417368","DOIUrl":"10.1080/17460441.2024.2417368","url":null,"abstract":"Introduction: Myeloproliferative neoplasms (MPNs) are rare hematopoietic disorders driven by mutations in the JAK-STAT signaling pathway genes. While JAK2 inhibitors have transformed MPN treatment, they do not eliminate the malignant clone or prevent disease progression in most patients. This limitation underscores the need for more effective therapies.Area covered: This review examines the evolution of JAK2 inhibitors for treating MPNs. Current JAK2 inhibitors primarily function as type I inhibitors, targeting the active kinase conformation, but their effectiveness is limited by ongoing JAK-STAT signaling. To overcome these limitations, next-generation therapies, such as type II JAK2 inhibitors and pseudokinase domain inhibitors, are being developed to target inactive kinase conformations and alternative signaling pathways. Furthermore, combination therapies with PI3K, mTOR, CDK4/6 inhibitors, and epigenetic modulators are being investigated for their potential synergistic effects, aiming for deeper and more durable responses in MPN patients.Expert opinion: Next-generation JAK2 inhibitors are needed to enhance current MPNs treatments by overcoming resistance, improving selectivity, targeting specific patient groups, and exploring combination therapies. Addressing challenges in drug design, preclinical testing, and clinical trials is crucial. Developing dual or multiple inhibitors targeting JAK2 and other MPN-related pathways is urgent to address complex signaling networks and improve efficacy.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1403-1415"},"PeriodicalIF":6.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142461543","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

Advances in chalcone-based anticancer therapy: mechanisms, preclinical advances, and future perspectives.

IF 6 2区医学

Expert Opinion on Drug Discovery Pub Date : 2024-12-01 Epub Date: 2024-12-05 DOI: 10.1080/17460441.2024.2436908

Shefali Chowdhary, Preeti, Shekhar, Nikita Gupta, Rajesh Kumar, Vipan Kumar

{"title":"Advances in chalcone-based anticancer therapy: mechanisms, preclinical advances, and future perspectives.","authors":"Shefali Chowdhary, Preeti, Shekhar, Nikita Gupta, Rajesh Kumar, Vipan Kumar","doi":"10.1080/17460441.2024.2436908","DOIUrl":"10.1080/17460441.2024.2436908","url":null,"abstract":"Introduction: Cancer remains a leading cause of death worldwide with traditional treatments like chemotherapy, and radiotherapy becoming less effective due to multidrug resistance (MDR). This highlights the necessity for novel chemotherapeutics like chalcone-based compounds, which demonstrate broad anti-cancer properties and target multiple pathways. These compounds hold promise for improving cancer treatment outcomes compared to existing therapies.Areas covered: This review provides a comprehensive synopsis of the recent literature (2018-2024) for anti-proliferative/anti-cancer activity of chalcones. It includes the identification of potential targets, their mechanisms of action, and possible modes of binding. Additionally, chalcone derivatives in preclinical trials are also discussed.Expert opinion: Chalcones mark a significant stride in anticancer therapies due to their multifaceted approach in targeting various cellular pathways. Their ability to simultaneously target multiple pathways enables them to overcome drug resistance as compared to traditional therapies. With well-defined mechanisms of action, these compounds can serve as lead molecules for designing new, more promising treatments. Continued progress in synthesis and structural optimization, along with promising results from preclinical trials, offers hope for the development of more potent molecules, heralding a new era in cancer therapeutics.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1417-1437"},"PeriodicalIF":6.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142766684","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

Fragment-based approaches to discover ligands for tumor-specific E3 ligases. 基于片段的方法发现肿瘤特异性 E3 连接酶的配体。

IF 6 2区医学

Expert Opinion on Drug Discovery Pub Date : 2024-12-01 Epub Date: 2024-10-17 DOI: 10.1080/17460441.2024.2415310

Junhyeong Yim, Solbi Kim, Hyung Ho Lee, Jin Soo Chung, Jongmin Park

{"title":"Fragment-based approaches to discover ligands for tumor-specific E3 ligases.","authors":"Junhyeong Yim, Solbi Kim, Hyung Ho Lee, Jin Soo Chung, Jongmin Park","doi":"10.1080/17460441.2024.2415310","DOIUrl":"10.1080/17460441.2024.2415310","url":null,"abstract":"Introduction: Targeted protein degradation (TPD) has emerged as an innovative therapeutic strategy through selective degradation of specific proteins by harnessing the cellular ubiquitin-proteasome system (UPS), which involves over 600 E3 ubiquitin ligases. Recent proteome profiling reported tumor-specific E3 ligases in human. Development of those tumor-specific E3 ligase ligands would provide a solution for tumor-specific TPD for effective cancer treatment.Areas covered: This review provides a comprehensive list of E3 ligases found only in specific types of tumor from public databases and highlights examples of their ligands discovered through fragment-based approaches. It details their discovery process and potential applications for precise TPD and effective cancer treatments.Expert opinion: Current TPD strategies using proteolysis-targeting chimeras (PROTACs) primarily utilize general E3 ligases, such as CRBN and VHL. Since these E3 ligases demonstrate effective protein degradation activity in most human cell types, CRBN and VHL-based PROTACs can exhibit undesired TPD in off-target tissues, which often leads to the side effects. Therefore, developing tumor-specific E3 ligase ligands can be crucial for effective cancer treatments. Fragment-based ligand discovery (FBLD) approaches would accelerate the identification of these tumor-specific E3 ligase ligands and associated PROTACs, thereby advancing the field of targeted cancer therapies.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1471-1484"},"PeriodicalIF":6.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142461545","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

High-throughput and computational techniques for aptamer design. 用于适配体设计的高通量和计算技术。

IF 6 2区医学

Expert Opinion on Drug Discovery Pub Date : 2024-12-01 Epub Date: 2024-10-10 DOI: 10.1080/17460441.2024.2412632

Rajiv K Kar

{"title":"High-throughput and computational techniques for aptamer design.","authors":"Rajiv K Kar","doi":"10.1080/17460441.2024.2412632","DOIUrl":"10.1080/17460441.2024.2412632","url":null,"abstract":"Introduction: Aptamers refer to short ssDNA/RNA sequences that target small molecules, proteins, or cells. Aptamers have significantly advanced diagnostic applications, including biosensors for detecting specific biomarkers, state-of-the-art imaging, and point-of-care technology. Molecular computation helps identify aptamers with high-binding affinity, enabling high-throughput screening, predicting 3D structures, optimizing aptamers for improved stability, specificity, and complex target interactions.Area covered: Aptamers are versatile in the development of specific and sensitive diagnostics. However, there needs to be more understanding of the precise workflow that integrates sequence, structure, and interaction with the target. In this review, the author discusses how significant progress has been made in aptamer discovery using bioinformatics for sequence analysis, docking to model interactions, and MD simulations to account for dynamicity and predict free-energy. Furthermore, the author discusses how quantum chemical calculations are critical for modelling electronic structures and assignin spectroscopic signals.Expert opinion: Incorporating machine learning into the aptamer discovery brings a transformative advancement. With NGS datasets, SELEX, and experimental structures, the implementation of newer workflows yields aptamers with improved binding affinity. Leveraging transfer learning to models using experimental structures and aptamer sequences expands the aptamer design space significantly. As ML continues to evolve, it is poised to become central in accelerating aptamer discovery for biomedical applications in the next 5 years.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1457-1469"},"PeriodicalIF":6.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142399906","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 latest developments in the design and discovery of non-nucleoside reverse transcriptase inhibitors (NNRTIs) for the treatment of HIV. 设计和发现用于治疗艾滋病的非核苷类逆转录酶抑制剂（NNRTIs）的最新进展。

IF 6 2区医学

Expert Opinion on Drug Discovery Pub Date : 2024-12-01 Epub Date: 2024-10-13 DOI: 10.1080/17460441.2024.2415309

Junyi Li, Bing Ye, Shenghua Gao, Xinyong Liu, Peng Zhan

引用次数: 0

Exploring open source as a strategy to enhance R&D productivity. 探索将开放源代码作为提高研发生产力的战略。

IF 6 2区医学

Expert Opinion on Drug Discovery Pub Date : 2024-12-01 Epub Date: 2024-10-15 DOI: 10.1080/17460441.2024.2417352

Alexander Schuhmacher

引用次数: 0

Data-centric challenges with the application and adoption of artificial intelligence for drug discovery. 在药物研发中应用和采用人工智能所面临的以数据为中心的挑战。

IF 6 2区医学

Expert Opinion on Drug Discovery Pub Date : 2024-11-01 Epub Date: 2024-09-24 DOI: 10.1080/17460441.2024.2403639

Ghita Ghislat, Saiveth Hernandez-Hernandez, Chayanit Piyawajanusorn, Pedro J Ballester

{"title":"Data-centric challenges with the application and adoption of artificial intelligence for drug discovery.","authors":"Ghita Ghislat, Saiveth Hernandez-Hernandez, Chayanit Piyawajanusorn, Pedro J Ballester","doi":"10.1080/17460441.2024.2403639","DOIUrl":"10.1080/17460441.2024.2403639","url":null,"abstract":"Introduction: Artificial intelligence (AI) is exhibiting tremendous potential to reduce the massive costs and long timescales of drug discovery. There are however important challenges currently limiting the impact and scope of AI models.Areas covered: In this perspective, the authors discuss a range of data issues (bias, inconsistency, skewness, irrelevance, small size, high dimensionality), how they challenge AI models, and which issue-specific mitigations have been effective. Next, they point out the challenges faced by uncertainty quantification techniques aimed at enhancing and trusting the predictions from these AI models. They also discuss how conceptual errors, unrealistic benchmarks and performance misestimation can confound the evaluation of models and thus their development. Lastly, the authors explain how human bias, whether from AI experts or drug discovery experts, constitutes another challenge that can be alleviated by gaining more prospective experience.Expert opinion: AI models are often developed to excel on retrospective benchmarks unlikely to anticipate their prospective performance. As a result, only a few of these models are ever reported to have prospective value (e.g. by discovering potent and innovative drug leads for a therapeutic target). The authors have discussed what can go wrong in practice with AI for drug discovery. The authors hope that this will help inform the decisions of editors, funders investors, and researchers working in this area.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1297-1307"},"PeriodicalIF":6.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142307469","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