Progress in molecular biology and translational science最新文献

Preface. 前言。

3区生物学

Progress in molecular biology and translational science Pub Date : 2026-01-01 DOI: 10.1016/S1877-1173(26)00077-3

Vijai Singh

引用次数: 0

Calcium-sensing receptor involved in the oral perception of kokumi substances. 钙感知受体参与口腔对高味物质的感知。

3区生物学

Progress in molecular biology and translational science Pub Date : 2026-01-01 Epub Date: 2026-03-31 DOI: 10.1016/bs.pmbts.2026.03.004

Hiroki Yamaguchi, Seiji Kitajima

引用次数: 0

Microcrystal electron diffraction (MicroED) for high-resolution structure determination. 微晶电子衍射（MicroED）用于高分辨率结构测定。

3区生物学

Progress in molecular biology and translational science Pub Date : 2026-01-01 Epub Date: 2026-06-02 DOI: 10.1016/bs.pmbts.2026.05.002

Brent L Nannenga, Michael W Martynowycz

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GoToCloud: Development and future of the cloud-based platform for cryo-EM structure-based drug DesignDevelopment and future of GoToCloud. GoToCloud：基于低温电镜结构的药物设计云平台的发展与未来。

3区生物学

Progress in molecular biology and translational science Pub Date : 2026-01-01 Epub Date: 2026-04-03 DOI: 10.1016/bs.pmbts.2026.03.006

Toshio Moriya

{"title":"GoToCloud: Development and future of the cloud-based platform for cryo-EM structure-based drug DesignDevelopment and future of GoToCloud.","authors":"Toshio Moriya","doi":"10.1016/bs.pmbts.2026.03.006","DOIUrl":"10.1016/bs.pmbts.2026.03.006","url":null,"abstract":"The \"Resolution Revolution\" in cryogenic electron microscopy (Cryo-EM) has fundamentally advanced structure-based drug design (SBDD), moving beyond static snapshots to dynamic conformational analysis. However, the resulting exponential growth in data volume has created critical computational bottlenecks where traditional on-premise high-performance computing lacks necessary scalability and economic flexibility. This chapter describes \"GoToCloud,\" a platform leveraging Amazon Web Services (AWS) ParallelCluster to overcome these barriers. We introduce a \"Shared EFS\" architecture and automated scripts allowing researchers to deploy secure virtual clusters within a Virtual Private Cloud (VPC), pre-installed with essential software like RELION. This design eliminates specialized IT maintenance needs for researchers using Cryo-EM while ensuring consistent analysis environments across distributed groups. Extensive benchmarking using practical datasets, including Nitrite Reductase and Streptavidin, validates the platform's effectiveness. Crucially, we provide a detailed economic analysis optimizing cost-performance by identifying specific GPU instance types (e.g., NVIDIA T4 vs. A10G) that balance processing speed with expense. The platform achieved 1.83Å resolution, revealing the \"2.0Å wall\" for cost-performance. Additionally, the platform addresses global data logistics by integrating Zettar zx, a high-speed transfer technology utilizing burst-buffer architecture. This successfully demonstrated ∼4.6 Gbps throughput over intercontinental distances despite 10 Gbps on-premise bottlenecks, replacing slow physical media transport. By democratizing access to High-Performance Computing (HPC) and enabling rapid data mobility, GoToCloud establishes a robust foundation for next-generation SBDD, facilitating fully automated high-throughput screening and experimental validation of AI-predicted models.","PeriodicalId":21157,"journal":{"name":"Progress in molecular biology and translational science","volume":"223 ","pages":"203-233"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148472507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Artificial intelligence for cell-free systems. 无细胞系统的人工智能。

3区生物学

Progress in molecular biology and translational science Pub Date : 2026-01-01 Epub Date: 2025-09-20 DOI: 10.1016/bs.pmbts.2025.08.009

Ingita Dey Munshi, Indra Mani

{"title":"Artificial intelligence for cell-free systems.","authors":"Ingita Dey Munshi, Indra Mani","doi":"10.1016/bs.pmbts.2025.08.009","DOIUrl":"10.1016/bs.pmbts.2025.08.009","url":null,"abstract":"Cell-free systems let researchers carry out biological processes like protein synthesis and metabolism without using living cells. This approach has become increasingly important in synthetic biology because it allows for quick testing of ideas, running many experiments simultaneously, and maintaining tight control over reaction conditions. The main challenge has been figuring out how to optimize these systems, since there are so many variables that interact in unpredictable ways. Artificial intelligence (AI), including machine learning, deep learning, and generative models, has begun to tackle this problem by helping predict experimental outcomes, design new proteins, and find better reaction conditions. The discovery of antimicrobial peptides through deep learning and cell-free protein synthesis, along with a 34-fold increase in protein yield through buffer optimization guided by active learning, are some of the major advancements made possible. The use of Bayesian optimization and neural networks has helped to streamline metabolic pathway designing, enzyme engineering as well as yield prediction, which in turn has diversified the use of AI-driven approaches in biomanufacturing, pharmaceuticals, and diagnostics. In spite of hurdles like data requirements, model transferability, and scalability, the compatibility of AI and cell-free systems gives adequate probabilities of innovations like digital twins and self-driven biomanufacturing units. This chapter explores the integration of AI with cell-free systems, focusing on recent advances, industrial applications, and ending with future directions for synthetic biology.","PeriodicalId":21157,"journal":{"name":"Progress in molecular biology and translational science","volume":"218 ","pages":"87-108"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146047255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Pursuing the physics of cryo-EM image formation. 研究低温电子显微镜成像的物理原理。

3区生物学

Progress in molecular biology and translational science Pub Date : 2026-01-01 Epub Date: 2026-06-15 DOI: 10.1016/bs.pmbts.2026.05.001

Joel Yeo, N Duane Loh

{"title":"Pursuing the physics of cryo-EM image formation.","authors":"Joel Yeo, N Duane Loh","doi":"10.1016/bs.pmbts.2026.05.001","DOIUrl":"https://doi.org/10.1016/bs.pmbts.2026.05.001","url":null,"abstract":"Cryo-electron microscopy (cryo-EM) has revolutionized structural biology, enabling near-atomic resolution determination of biological macromolecules. The success of modern reconstruction algorithms relies heavily on simplified image formation models, particularly the projection and weak-phase approximations, which linearize the relationship between the measured images and the specimen's three-dimensional (3D) scattering potential - commonly referred to as the map in cryo-EM. While these approximations have proven remarkably effective, the underlying physics of electron imaging is considerably richer, more complex, and arguably under-exploited. This chapter revisits the foundational principles of image formation in cryo-EM from first principles, tracing the physical pathway from electron-matter interaction through wave propagation to final image detection. Here, we show how the contrast transfer function (CTF) model commonly used in cryo-EM arises directly from the underlying image formation model, under standard approximations. Finally, we connect these physical models to reconstruction by introducing our own reconstruction algorithm, Ghostbuster, which leverages a physically accurate forward model to go beyond conventional CTF-based approaches. By grounding contemporary cryo-EM practice in rigorous physical principles, this chapter aims to provide essential context for assessing the validity of standard assumptions and guiding future methodological developments as the field continues to push toward its ultimate resolution limits.","PeriodicalId":21157,"journal":{"name":"Progress in molecular biology and translational science","volume":"223 ","pages":"41-69"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148471884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Cryo-EM of amyloid fibrils: Advances, challenges, and translational applications. 淀粉样蛋白原纤维的低温电镜：进展、挑战和转化应用。

3区生物学

Progress in molecular biology and translational science Pub Date : 2026-01-01 Epub Date: 2026-04-01 DOI: 10.1016/bs.pmbts.2026.03.007

Dylan Valli, Michał Maj

{"title":"Cryo-EM of amyloid fibrils: Advances, challenges, and translational applications.","authors":"Dylan Valli, Michał Maj","doi":"10.1016/bs.pmbts.2026.03.007","DOIUrl":"https://doi.org/10.1016/bs.pmbts.2026.03.007","url":null,"abstract":"Cryo-electron microscopy (cryo-EM) has emerged as a transformative technique in structural biology, driving an exponential increase in the number of amyloid fibril structures deposited in the Protein Data Bank. Current workflows now routinely achieve the near-atomic resolution essential for understanding the molecular pathology of neurodegenerative and metabolic disorders. This chapter provides a comprehensive overview of the field, tracing the evolution from early structural studies to modern pipelines powered by deep-learning algorithms for helical reconstruction. We address the persistent bottleneck of sample preparation, detailing the physical challenges of fibril clumping and interfacial adsorption, alongside emerging solutions to these problems. Furthermore, we examine the complexities of structural polymorphism, discussing how environmental factors and seeding drive conformational diversity and how this heterogeneity impacts biochemical assays. Finally, we highlight the translational value of these high-resolution maps, demonstrating how they enable the rational, structure-based design of peptide inhibitors and small molecules capable of disaggregating pathogenic fibrils.","PeriodicalId":21157,"journal":{"name":"Progress in molecular biology and translational science","volume":"223 ","pages":"115-146"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148472441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Challenges and opportunities in cell-free systems. 无细胞系统的挑战和机遇。

3区生物学

Progress in molecular biology and translational science Pub Date : 2026-01-01 Epub Date: 2025-09-06 DOI: 10.1016/bs.pmbts.2025.08.006

Hue Vu Thi, Yen-Vy Nguyen Thi, Minh Chau Nguyen, Huong Ly Nguyen, Phuong Anh Nguyen, Dinh-Toi Chu

{"title":"Challenges and opportunities in cell-free systems.","authors":"Hue Vu Thi, Yen-Vy Nguyen Thi, Minh Chau Nguyen, Huong Ly Nguyen, Phuong Anh Nguyen, Dinh-Toi Chu","doi":"10.1016/bs.pmbts.2025.08.006","DOIUrl":"10.1016/bs.pmbts.2025.08.006","url":null,"abstract":"Cell-free systems (CFS) are in vitro technologies (outside living cells) that use cellular components to reproduce cellular processes outside living organisms, such as protein synthesis, gene expression, and metabolic reactions. Nowadays, CFS has been improved over time and is considered one of the most useful tools for exploring and illustrating the fundamental principles of biological systems. In the medical field, CFS is being widely applied in vaccine production, gene expression research and point-of-care diagnostics. However, despite its significant benefits, CFS still faces many technological challenges and scientific limitations. In addition, sustainable development goes hand in hand with the balance between innovation and ethical, environmental and social issues. However, in the context of promoting biological solutions, CFS also opens many new opportunities. Therefore, challenges and some issues related to CFS technologies have been comprehensively evaluated in this chapter. The opportunities of CFS technologies have also been discussed in this chapter to highlight the huge potential of this technology in the near future. The evidence presented can serve as a foundational reference for research, teaching, and strategic policy-making in the field of next-generation synthetic biology.","PeriodicalId":21157,"journal":{"name":"Progress in molecular biology and translational science","volume":"219 ","pages":"237-254"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146195673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Preface. 前言。

3区生物学

Progress in molecular biology and translational science Pub Date : 2026-01-01 DOI: 10.1016/S1877-1173(26)00029-3

Vijai Singh

引用次数: 0

Development of cell-free transcription translation. 无细胞转录翻译的研究进展。

3区生物学

Progress in molecular biology and translational science Pub Date : 2026-01-01 Epub Date: 2025-09-09 DOI: 10.1016/bs.pmbts.2025.08.003

Ajay Kumar, Juveriya Israr, Shabroz Alam

{"title":"Development of cell-free transcription translation.","authors":"Ajay Kumar, Juveriya Israr, Shabroz Alam","doi":"10.1016/bs.pmbts.2025.08.003","DOIUrl":"10.1016/bs.pmbts.2025.08.003","url":null,"abstract":"Cell-free transcription-translation (TXTL) systems provide a robust platform for in vitro protein synthesis, transforming molecular biology, synthetic biology, and biotechnology by replicating natural protein synthesis outside of living cells with exceptional control and flexibility. Initially developed by Nirenberg and Matthaei in the 1960s using E. coli extracts, these systems have undergone substantial evolution, and now incorporate extracts from bacteria, yeast, and eukaryotes to construct comprehensive TXTL platforms. A cell-free extract comprises essential components, such as ribosomes, RNA polymerase, and tRNAs, enabling protein synthesis directed by DNA templates through transcription and translation. TXTL systems, offer distinct advantages, including rapid, efficient, and accurate synthesis of natural and non-natural proteins, enhanced chemical resistance, and streamlined labeling-often surpassing cell-based techniques. Their extensive application span synthetic biology and biopharmaceutical production. Despite this promise, challanges remain, including high cost, limited protein yield, lack of complex post-translational modifications, and extract instability. Future efforts will focus on overcoming these challenges by reducing costs, improving yields, expanding post-translational modification capabilities, enhancing stability, and developing continuous-flow systems. Ultimately, cell-free systems are poised to deepen our understanding of biological processes and drive the development of innovative biotechnological tools.","PeriodicalId":21157,"journal":{"name":"Progress in molecular biology and translational science","volume":"218 ","pages":"49-64"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146047224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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