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Editorial overview–Artificial intelligence methodologies in structural biology: Bridging the gap to medical applications 编辑综述-结构生物学中的人工智能方法：缩小医学应用差距
IF 6.8 2区 生物学
Current opinion in structural biology Pub Date : 2024-06-12 DOI: 10.1016/j.sbi.2024.102862
Tero Aittokallio, Evandro Fei Fang
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引用次数: 0
Microscale measurements of protein complexes from single cells 单细胞蛋白质复合物的微尺度测量
IF 6.8 2区 生物学
Current opinion in structural biology Pub Date : 2024-06-07 DOI: 10.1016/j.sbi.2024.102860
Tanushree Dutta, Julea Vlassakis
{"title":"Microscale measurements of protein complexes from single cells","authors":"Tanushree Dutta,&nbsp;Julea Vlassakis","doi":"10.1016/j.sbi.2024.102860","DOIUrl":"https://doi.org/10.1016/j.sbi.2024.102860","url":null,"abstract":"<div><p>Proteins execute numerous cell functions in concert with one another in protein–protein interactions (PPI). While essential in each cell, such interactions are not identical from cell to cell. Instead, PPI heterogeneity contributes to cellular phenotypic heterogeneity in health and diseases such as cancer. Understanding cellular phenotypic heterogeneity thus requires measurements of properties of PPIs such as abundance, stoichiometry, and kinetics at the single-cell level. Here, we review recent, exciting progress in single-cell PPI measurements. Novel technology in this area is enabled by microscale and microfluidic approaches that control analyte concentration in timescales needed to outpace PPI disassembly kinetics. We describe microscale innovations, needed technical capabilities, and methods poised to be adapted for single-cell analysis in the near future.</p></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"87 ","pages":"Article 102860"},"PeriodicalIF":6.8,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0959440X24000873/pdfft?md5=ea9b53936db1adace07cdda4f671e88d&pid=1-s2.0-S0959440X24000873-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141285979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Structural overview of DNA and RNA G-quadruplexes in their interaction with proteins DNA 和 RNA G 型四联体与蛋白质相互作用的结构概述
IF 6.8 2区 生物学
Current opinion in structural biology Pub Date : 2024-06-07 DOI: 10.1016/j.sbi.2024.102846
Romualdo Troisi , Filomena Sica
{"title":"Structural overview of DNA and RNA G-quadruplexes in their interaction with proteins","authors":"Romualdo Troisi ,&nbsp;Filomena Sica","doi":"10.1016/j.sbi.2024.102846","DOIUrl":"https://doi.org/10.1016/j.sbi.2024.102846","url":null,"abstract":"<div><p>Since the discovery of G-quadruplex (G4) participation in vital cellular processes, the regulation of the interaction of naturally occurring G4s with the relative target proteins has emerged as a promising approach for therapeutic development. Additionally, a synthetic strategy has produced several oligonucleotide aptamers, embodying a G4 module, which exhibit relevant biological activity by binding selectively to a target protein. In this context, the G4-protein structures available in the Protein Data Bank represent a valuable molecular view of the different G4 topologies involved in protein interaction. Interestingly, recent results have showed the co-existence of G4s with other structural domains such as duplexes. Overall, these findings allow a better understanding of the mechanisms that regulate intricate biological functions and suggest new design for innovative medical treatments.</p></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"87 ","pages":"Article 102846"},"PeriodicalIF":6.8,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0959440X24000733/pdfft?md5=dfa46267980c60cd160c02fbbe8ef1ee&pid=1-s2.0-S0959440X24000733-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141285980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Structure-based virtual screening of vast chemical space as a starting point for drug discovery 以结构为基础，对广阔的化学空间进行虚拟筛选，作为药物发现的起点
IF 6.8 2区 生物学
Current opinion in structural biology Pub Date : 2024-06-06 DOI: 10.1016/j.sbi.2024.102829
Jens Carlsson , Andreas Luttens
{"title":"Structure-based virtual screening of vast chemical space as a starting point for drug discovery","authors":"Jens Carlsson ,&nbsp;Andreas Luttens","doi":"10.1016/j.sbi.2024.102829","DOIUrl":"https://doi.org/10.1016/j.sbi.2024.102829","url":null,"abstract":"<div><p>Structure-based virtual screening aims to find molecules forming favorable interactions with a biological macromolecule using computational models of complexes. The recent surge of commercially available chemical space provides the opportunity to search for ligands of therapeutic targets among billions of compounds. This review offers a compact overview of structure-based virtual screens of vast chemical spaces, highlighting successful applications in early drug discovery for therapeutically important targets such as G protein-coupled receptors and viral enzymes. Emphasis is placed on strategies to explore ultra-large chemical libraries and synergies with emerging machine learning techniques. The current opportunities and future challenges of virtual screening are discussed, indicating that this approach will play an important role in the next-generation drug discovery pipeline.</p></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"87 ","pages":"Article 102829"},"PeriodicalIF":6.8,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0959440X24000563/pdfft?md5=87874c62059ab5f7bf458e18f128bdb5&pid=1-s2.0-S0959440X24000563-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141264211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Integrating AI in fighting advancing Alzheimer: diagnosis, prevention, treatment, monitoring, mechanisms, and clinical trials 将人工智能融入抗击阿尔茨海默氏症的工作中：诊断、预防、治疗、监测、机制和临床试验
IF 6.8 2区 生物学
Current opinion in structural biology Pub Date : 2024-06-04 DOI: 10.1016/j.sbi.2024.102857
Francesco Angelucci , Alice Ruixue Ai , Lydia Piendel , Jiri Cerman , Jakub Hort
{"title":"Integrating AI in fighting advancing Alzheimer: diagnosis, prevention, treatment, monitoring, mechanisms, and clinical trials","authors":"Francesco Angelucci ,&nbsp;Alice Ruixue Ai ,&nbsp;Lydia Piendel ,&nbsp;Jiri Cerman ,&nbsp;Jakub Hort","doi":"10.1016/j.sbi.2024.102857","DOIUrl":"https://doi.org/10.1016/j.sbi.2024.102857","url":null,"abstract":"<div><p>The application of artificial intelligence (AI) in neurology is a growing field offering opportunities to improve accuracy of diagnosis and treatment of complicated neuronal disorders, plus fostering a deeper understanding of the aetiologies of these diseases through AI-based analyses of large omics data. The most common neurodegenerative disease, Alzheimer’s disease (AD), is characterized by brain accumulation of specific pathological proteins, accompanied by cognitive impairment. In this review, we summarize the latest progress on the use of AI in different AD-related fields, such as analysis of neuroimaging data enabling early and accurate AD diagnosis; prediction of AD progression, identification of patients at higher risk and evaluation of new treatments; improvement of the evaluation of drug response using AI algorithms to analyze patient clinical and neuroimaging data; the development of personalized AD therapies; and the use of AI-based techniques to improve the quality of daily life of AD patients and their caregivers.</p></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"87 ","pages":"Article 102857"},"PeriodicalIF":6.8,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0959440X24000848/pdfft?md5=eae7764a6735afc1235a469251675644&pid=1-s2.0-S0959440X24000848-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141242996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Embracing exascale computing in nucleic acid simulations 在核酸模拟中采用超大规模计算。
IF 6.8 2区 生物学
Current opinion in structural biology Pub Date : 2024-05-29 DOI: 10.1016/j.sbi.2024.102847
Jun Li, Yuanzhe Zhou, Shi-Jie Chen
{"title":"Embracing exascale computing in nucleic acid simulations","authors":"Jun Li,&nbsp;Yuanzhe Zhou,&nbsp;Shi-Jie Chen","doi":"10.1016/j.sbi.2024.102847","DOIUrl":"10.1016/j.sbi.2024.102847","url":null,"abstract":"<div><p>This mini-review reports the recent advances in biomolecular simulations, particularly for nucleic acids, and provides the potential effects of the emerging exascale computing on nucleic acid simulations, emphasizing the need for advanced computational strategies to fully exploit this technological frontier. Specifically, we introduce recent breakthroughs in computer architectures for large-scale biomolecular simulations and review the simulation protocols for nucleic acids regarding force fields, enhanced sampling methods, coarse-grained models, and interactions with ligands. We also explore the integration of machine learning methods into simulations, which promises to significantly enhance the predictive modeling of biomolecules and the analysis of complex data generated by the exascale simulations. Finally, we discuss the challenges and perspectives for biomolecular simulations as we enter the dawning exascale computing era.</p></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"87 ","pages":"Article 102847"},"PeriodicalIF":6.8,"publicationDate":"2024-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141179147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Microsecond time-resolved cryo-electron microscopy 微秒时间分辨冷冻电镜。
IF 6.8 2区 生物学
Current opinion in structural biology Pub Date : 2024-05-28 DOI: 10.1016/j.sbi.2024.102840
Ulrich J. Lorenz
{"title":"Microsecond time-resolved cryo-electron microscopy","authors":"Ulrich J. Lorenz","doi":"10.1016/j.sbi.2024.102840","DOIUrl":"10.1016/j.sbi.2024.102840","url":null,"abstract":"<div><p>Microsecond time-resolved cryo-electron microscopy has emerged as a novel approach for directly observing protein dynamics. By providing microsecond temporal and near-atomic spatial resolution, it has the potential to elucidate a wide range of dynamics that were previously inaccessible and therefore, to significantly advance our understanding of protein function. This review summarizes the properties of the laser melting and revitrification process that underlies the technique and describes different experimental implementations. Strategies for initiating and probing dynamics are discussed. Finally, the microsecond time-resolved observation of the capsid dynamics of cowpea chlorotic mottle virus, an icosahedral plant virus, is reviewed, which illustrates important features of the technique as well as its potential.</p></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"87 ","pages":"Article 102840"},"PeriodicalIF":6.8,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0959440X24000678/pdfft?md5=a1a9acc08f0aea04cea6e8a3a5ff5ddc&pid=1-s2.0-S0959440X24000678-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141175018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Structure-based discovery and rational design of microtubule-targeting agents 基于结构发现和合理设计微管靶向药物
IF 6.8 2区 生物学
Current opinion in structural biology Pub Date : 2024-05-27 DOI: 10.1016/j.sbi.2024.102845
Michel O. Steinmetz , Andrea E. Prota
{"title":"Structure-based discovery and rational design of microtubule-targeting agents","authors":"Michel O. Steinmetz ,&nbsp;Andrea E. Prota","doi":"10.1016/j.sbi.2024.102845","DOIUrl":"https://doi.org/10.1016/j.sbi.2024.102845","url":null,"abstract":"<div><p>Microtubule-targeting agents (MTAs) have demonstrated remarkable efficacy as antitumor, antifungal, antiparasitic, and herbicidal agents, finding applications in the clinical, veterinary, and agrochemical industry. Recent advances in tubulin and microtubule structural biology have provided powerful tools that pave the way for the rational design of innovative small-molecule MTAs for future basic and applied life science applications. In this mini-review, we present the current status of the tubulin and microtubule structural biology field, the recent impact it had on the discovery and rational design of MTAs, and exciting avenues for future MTA research.</p></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"87 ","pages":"Article 102845"},"PeriodicalIF":6.8,"publicationDate":"2024-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0959440X24000721/pdfft?md5=4f479ef4c76ddb2355a88d54e1f15dc2&pid=1-s2.0-S0959440X24000721-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141156250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Artificial intelligence for high content imaging in drug discovery 人工智能在药物发现中的高分辨率成像技术
IF 6.8 2区 生物学
Current opinion in structural biology Pub Date : 2024-05-25 DOI: 10.1016/j.sbi.2024.102842
Jordi Carreras-Puigvert, Ola Spjuth
{"title":"Artificial intelligence for high content imaging in drug discovery","authors":"Jordi Carreras-Puigvert,&nbsp;Ola Spjuth","doi":"10.1016/j.sbi.2024.102842","DOIUrl":"https://doi.org/10.1016/j.sbi.2024.102842","url":null,"abstract":"<div><p>Artificial intelligence (AI) and high-content imaging (HCI) are contributing to advancements in drug discovery, propelled by the recent progress in deep neural networks. This review highlights AI's role in analysis of HCI data from fixed and live-cell imaging, enabling novel label-free and multi-channel fluorescent screening methods, and improving compound profiling. HCI experiments are rapid and cost-effective, facilitating large data set accumulation for AI model training. However, the success of AI in drug discovery also depends on high-quality data, reproducible experiments, and robust validation to ensure model performance. Despite challenges like the need for annotated compounds and managing vast image data, AI's potential in phenotypic screening and drug profiling is significant. Future improvements in AI, including increased interpretability and integration of multiple modalities, are expected to solidify AI and HCI's role in drug discovery.</p></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"87 ","pages":"Article 102842"},"PeriodicalIF":6.8,"publicationDate":"2024-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0959440X24000691/pdfft?md5=98863a80109ecc0824c5aa21065f8ee0&pid=1-s2.0-S0959440X24000691-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141095293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Impact of quantum and neuromorphic computing on biomolecular simulations: Current status and perspectives 量子计算和神经形态计算对生物分子模拟的影响：现状与展望
IF 6.8 2区 生物学
Current opinion in structural biology Pub Date : 2024-05-24 DOI: 10.1016/j.sbi.2024.102817
Sandra Diaz-Pier , Paolo Carloni
{"title":"Impact of quantum and neuromorphic computing on biomolecular simulations: Current status and perspectives","authors":"Sandra Diaz-Pier ,&nbsp;Paolo Carloni","doi":"10.1016/j.sbi.2024.102817","DOIUrl":"https://doi.org/10.1016/j.sbi.2024.102817","url":null,"abstract":"<div><p>New high-performance computing architectures are becoming operative, in addition to exascale computers. Quantum computers (QC) solve optimization problems with unprecedented efficiency and speed, while neuromorphic hardware (NMH) simulates neural network dynamics. Albeit, at the moment, both find no practical use in all atom biomolecular simulations, QC might be exploited in the not-too-far future to simulate systems for which electronic degrees of freedom play a key and intricate role for biological function, whereas NMH might accelerate molecular dynamics simulations with low energy consumption. Machine learning and artificial intelligence algorithms running on NMH and QC could assist in the analysis of data and speed up research. If these implementations are successful, modular supercomputing could further dramatically enhance the overall computing capacity by combining highly optimized software tools into workflows, linking these architectures to exascale computers.</p></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"87 ","pages":"Article 102817"},"PeriodicalIF":6.8,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0959440X24000447/pdfft?md5=572fde927378e84697c8378fa6377638&pid=1-s2.0-S0959440X24000447-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141090675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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