Expert Opinion on Drug Discovery最新文献_第8页

Recent applications of artificial intelligence in RNA-targeted small molecule drug discovery. 人工智能在 RNA 靶向小分子药物发现中的最新应用。

IF 6.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2024-04-01 Epub Date: 2024-02-06 DOI: 10.1080/17460441.2024.2313455

Ella Czarina Morishita, Shingo Nakamura

{"title":"Recent applications of artificial intelligence in RNA-targeted small molecule drug discovery.","authors":"Ella Czarina Morishita, Shingo Nakamura","doi":"10.1080/17460441.2024.2313455","DOIUrl":"10.1080/17460441.2024.2313455","url":null,"abstract":"Introduction: Targeting RNAs with small molecules offers an alternative to the conventional protein-targeted drug discovery and can potentially address unmet and emerging medical needs. The recent rise of interest in the strategy has already resulted in large amounts of data on disease associated RNAs, as well as on small molecules that bind to such RNAs. Artificial intelligence (AI) approaches, including machine learning and deep learning, present an opportunity to speed up the discovery of RNA-targeted small molecules by improving decision-making efficiency and quality.Areas covered: The topics described in this review include the recent applications of AI in the identification of RNA targets, RNA structure determination, screening of chemical compound libraries, and hit-to-lead optimization. The impact and limitations of the recent AI applications are discussed, along with an outlook on the possible applications of next-generation AI tools for the discovery of novel RNA-targeted small molecule drugs.Expert opinion: Key areas for improvement include developing AI tools for understanding RNA dynamics and RNA - small molecule interactions. High-quality and comprehensive data still need to be generated especially on the biological activity of small molecules that target RNAs.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139697200","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

In silico drug design strategies for discovering novel tuberculosis therapeutics. 发现新型结核病疗法的硅学药物设计策略。

IF 6.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2024-04-01 Epub Date: 2024-02-19 DOI: 10.1080/17460441.2024.2319042

Christian S Carnero Canales, Aline Renata Pavan, Jean Leandro Dos Santos, Fernando Rogério Pavan

{"title":"In silico drug design strategies for discovering novel tuberculosis therapeutics.","authors":"Christian S Carnero Canales, Aline Renata Pavan, Jean Leandro Dos Santos, Fernando Rogério Pavan","doi":"10.1080/17460441.2024.2319042","DOIUrl":"10.1080/17460441.2024.2319042","url":null,"abstract":"Introduction: Tuberculosis remains a significant concern in global public health due to its intricate biology and propensity for developing antibiotic resistance. Discovering new drugs is a protracted and expensive endeavor, often spanning over a decade and incurring costs in the billions. However, computer-aided drug design (CADD) has surfaced as a nimbler and more cost-effective alternative. CADD tools enable us to decipher the interactions between therapeutic targets and novel drugs, making them invaluable in the quest for new tuberculosis treatments.Areas covered: In this review, the authors explore recent advancements in tuberculosis drug discovery enabled by in silico tools. The main objectives of this review article are to highlight emerging drug candidates identified through in silico methods and to provide an update on the therapeutic targets associated with Mycobacterium tuberculosis.Expert opinion: These in silico methods have not only streamlined the drug discovery process but also opened up new horizons for finding novel drug candidates and repositioning existing ones. The continued advancements in these fields hold great promise for more efficient, ethical, and successful drug development in the future.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139905375","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

Chemoinformatic approaches for navigating large chemical spaces. 浏览大型化学空间的化学信息学方法。

IF 6.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2024-04-01 Epub Date: 2024-02-05 DOI: 10.1080/17460441.2024.2313475

Martin Vogt

{"title":"Chemoinformatic approaches for navigating large chemical spaces.","authors":"Martin Vogt","doi":"10.1080/17460441.2024.2313475","DOIUrl":"10.1080/17460441.2024.2313475","url":null,"abstract":"Introduction: Large chemical spaces (CSs) include traditional large compound collections, combinatorial libraries covering billions to trillions of molecules, DNA-encoded chemical libraries comprising complete combinatorial CSs in a single mixture, and virtual CSs explored by generative models. The diverse nature of these types of CSs require different chemoinformatic approaches for navigation.Areas covered: An overview of different types of large CSs is provided. Molecular representations and similarity metrics suitable for large CS exploration are discussed. A summary of navigation of CSs in generative models is provided. Methods for characterizing and comparing CSs are discussed.Expert opinion: The size of large CSs might restrict navigation to specialized algorithms and limit it to considering neighborhoods of structurally similar molecules. Efficient navigation of large CSs not only requires methods that scale with size but also requires smart approaches that focus on better but not necessarily larger molecule selections. Deep generative models aim to provide such approaches by implicitly learning features relevant for targeted biological properties. It is unclear whether these models can fulfill this ideal as validation is difficult as long as the covered CSs remain mainly virtual without experimental verification.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139650636","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

Vutrisiran: a new drug in the treatment landscape of hereditary transthyretin amyloid polyneuropathy. Vutrisiran：治疗遗传性转甲状腺素淀粉样多发性神经病的新药。

IF 6.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2024-04-01 Epub Date: 2024-01-27 DOI: 10.1080/17460441.2024.2306843

Violaine Planté-Bordeneuve, Valentine Perrain

{"title":"Vutrisiran: a new drug in the treatment landscape of hereditary transthyretin amyloid polyneuropathy.","authors":"Violaine Planté-Bordeneuve, Valentine Perrain","doi":"10.1080/17460441.2024.2306843","DOIUrl":"10.1080/17460441.2024.2306843","url":null,"abstract":"Introduction: Hereditary transthyretin (ATTRv) amyloidosis is a progressive, fatal disorder caused by mutations in the transthyretin (TTR) gene leading to deposition of the misfolded protein in amyloid fibrils. The main phenotypes are peripheral neuropathy (PN) and cardiomyopathy (CM).Areas covered: Gene silencing therapy, by dramatically reducing liver production of TTR, has transformed ATTRv-PN patient care in the last decade. In this drug discovery case history, the authors discuss the treatment history of ATTRv-PN and focus on the latest siRNA therapy: vutrisiran. Vutrisiran is chemically enhanced and N-acetylgalactosamin-conjugated, allowing increased stability and specific liver delivery. HELIOS-A, a phase III, multicenter randomized study, tested vutrisiran in ATTRv-PN and showed significant improvement in neuropathy impairment, disability, quality of life (QoL), gait speed, and nutritional status. Tolerance was acceptable, no safety signals were raised.Expert opinion: Vutrisiran offers a new treatment option for patients with ATTRv-PN. Vutrisian's easier delivery and administration route, at a quarterly frequency, as well as the absence of premedication, are major improvements to reduce patients' disease burden and improve their QoL. Its place in the therapeutic strategy is to be determined, considering affordability.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139570049","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

Designing inhaled small molecule drugs for severe respiratory diseases: an overview of the challenges and opportunities. 设计治疗严重呼吸系统疾病的吸入式小分子药物：挑战与机遇概述。

IF 6.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2024-04-01 Epub Date: 2024-02-26 DOI: 10.1080/17460441.2024.2319049

Cornelia H Rinderknecht, Miaoran Ning, Connie Wu, Mark S Wilson, Christian Gampe

{"title":"Designing inhaled small molecule drugs for severe respiratory diseases: an overview of the challenges and opportunities.","authors":"Cornelia H Rinderknecht, Miaoran Ning, Connie Wu, Mark S Wilson, Christian Gampe","doi":"10.1080/17460441.2024.2319049","DOIUrl":"10.1080/17460441.2024.2319049","url":null,"abstract":"Introduction: Inhaled drugs offer advantages for the treatment of respiratory diseases over oral drugs by delivering the drug directly to the lung, thus improving the therapeutic index. There is an unmet medical need for novel therapies for lung diseases, exacerbated by a multitude of challenges for the design of inhaled small molecule drugs.Areas covered: The authors review the challenges and opportunities for the design of inhaled drugs for respiratory diseases with a focus on new target discovery, medicinal chemistry, and pharmacokinetic, pharmacodynamic, and toxicological evaluation of drug candidates.Expert opinion: Inhaled drug discovery is facing multiple unique challenges. Novel biological targets are scarce, as is the guidance for medicinal chemistry teams to design compounds with inhalation-compatible features. It is exceedingly difficult to establish a PK/PD relationship given the complexity of pulmonary PK and the impact of physical properties of the drug substance on PK. PK, PD and toxicology studies are technically challenging and require large amounts of drug substance. Despite the current challenges, the authors foresee that the design of inhaled drugs will be facilitated in the future by our increasing understanding of pathobiology, emerging medicinal chemistry guidelines, advances in drug formulation, PBPK models, and in vitro toxicology assays.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139971486","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

Molecular glue degraders: exciting opportunities for novel drug discovery. 分子胶降解剂：新药发现的激动人心的机遇。

IF 6.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2024-04-01 Epub Date: 2024-01-24 DOI: 10.1080/17460441.2024.2306845

Thomas Lemaitre, Marie Cornu, Florian Schwalen, Marc Since, Charline Kieffer, Anne Sophie Voisin-Chiret

{"title":"Molecular glue degraders: exciting opportunities for novel drug discovery.","authors":"Thomas Lemaitre, Marie Cornu, Florian Schwalen, Marc Since, Charline Kieffer, Anne Sophie Voisin-Chiret","doi":"10.1080/17460441.2024.2306845","DOIUrl":"10.1080/17460441.2024.2306845","url":null,"abstract":"Introduction: Molecular Glue Degraders (MGDs) is a concept that refers to a class of compounds that facilitate the interaction between two proteins or molecules within a cell. These compounds act as bridge that enhances specific Protein-Protein Interactions (PPIs). Over the past decade, this technology has gained attention as a potential strategy to target proteins that were traditionally considered undruggable using small molecules.Areas covered: This review presents the concept of cellular homeostasis and the balance between protein synthesis and protein degradation. The concept of protein degradation is concerned with molecular glues, which form part of the broader field of Targeted Protein Degradation (TPD). Next, pharmacochemical strategies for the rational design of MGDs are detailed and illustrated by examples of Ligand-Based (LBDD), Structure-Based (SBDD) and Fragment-Based Drug Design (FBDD).Expert opinion: Expanding the scope of what can be effectively targeted in the development of treatments for diseases that are incurable or resistant to conventional therapies offers new therapeutic options. The treatment of microbial infections and neurodegenerative diseases is a major societal challenge, and the discovery of MGDs appears to be a promising avenue. Combining different approaches to discover and exploit a variety of innovative therapeutic agents will create opportunities to treat diseases that are still incurable.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139491019","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

Molecular hybridization: a powerful tool for multitarget drug discovery. 分子杂交：发现多靶点药物的有力工具。

IF 6.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2024-04-01 Epub Date: 2024-03-08 DOI: 10.1080/17460441.2024.2322990

Pedro de Sena Murteira Pinheiro, Lucas Silva Franco, Tadeu Lima Montagnoli, Carlos Alberto Manssour Fraga

{"title":"Molecular hybridization: a powerful tool for multitarget drug discovery.","authors":"Pedro de Sena Murteira Pinheiro, Lucas Silva Franco, Tadeu Lima Montagnoli, Carlos Alberto Manssour Fraga","doi":"10.1080/17460441.2024.2322990","DOIUrl":"10.1080/17460441.2024.2322990","url":null,"abstract":"Introduction: The current drug discovery paradigm of 'one drug, multiple targets' has gained attention from both the academic medicinal chemistry community and the pharmaceutical industry. This is in response to the urgent need for effective agents to treat multifactorial chronic diseases. The molecular hybridization strategy is a useful tool that has been widely explored, particularly in the last two decades, for the design of multi-target drugs.Areas covered: This review examines the current state of molecular hybridization in guiding the discovery of multitarget small molecules. The article discusses the design strategies and target selection for a multitarget polypharmacology approach to treat various diseases, including cancer, Alzheimer's disease, cardiac arrhythmia, endometriosis, and inflammatory diseases.Expert opinion: Although the examples discussed highlight the importance of molecular hybridization for the discovery of multitarget bioactive compounds, it is notorious that the literature has focused on specific classes of targets. This may be due to a deep understanding of the pharmacophore features required for target binding, making targets such as histone deacetylases and cholinesterases frequent starting points. However, it is important to encourage the scientific community to explore diverse combinations of targets using the molecular hybridization strategy.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140059074","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

What value do zebrafish have to anticancer drug discovery? 斑马鱼对抗癌药物研发有何价值？

IF 6.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2024-04-01 Epub Date: 2024-02-07 DOI: 10.1080/17460441.2024.2313454

Boyuan Xiao, Esther Landesman-Bollag, Hui Feng

引用次数: 0

The preclinical discovery and clinical evaluation of tirzepatide for the treatment of type 2 diabetes 用于治疗 2 型糖尿病的替哌肽的临床前发现和临床评估

IF 6.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2024-03-05 DOI: 10.1080/17460441.2024.2324918

Ioannis Avgerinos, Panagiota Kakotrichi, Thomas Karagiannis, Eleni Bekiari, Apostolos Tsapas

引用次数: 0

Stroke genetics and how it Informs novel drug discovery 中风遗传学及其对新药研发的启示

IF 6.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2024-03-04 DOI: 10.1080/17460441.2024.2324916

Julija Valančienė, Kazimieras Melaika, Aleksandra Šliachtenko, Kamilė Šiaurytė-Jurgelėnė, Aleksandra Ekkert, Dalius Jatužis

引用次数: 0