{"title":"Virtual reality in drug design: Benefits, applications and industrial perspectives","authors":"Marc Baaden , David R. Glowacki","doi":"10.1016/j.sbi.2025.103044","DOIUrl":"10.1016/j.sbi.2025.103044","url":null,"abstract":"<div><div>Virtual reality (VR) is a tool which has transformative potential in domains which involve the visualization of complex 3D data such as structure-based drug design (SBDD), where it offers new ways to visualize and manipulate complex molecular structures in three dimensions, and enable intuitive exploration of protein-ligand complexes. In this article, we outline three levels of interaction which are available in immersive VR environments for drug discovery, and provide illustrative case studies with applications in COVID-19 research and protein-ligand docking. We discuss VR's role in drug discovery based on conversations with experts from the pharmaceutical industry. While industry experts are mostly optimistic about the potential of VR, they point to the challenges related to integration with existing workflows and the need for improved hardware ergonomics, as well as ensuring a synergistic relationship between VR and an expanding suite of artificial intelligence (AI) tools.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"92 ","pages":"Article 103044"},"PeriodicalIF":6.1,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143785386","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}
{"title":"The evolving role of solid state nuclear magnetic resonance methods in studies of amyloid fibrils","authors":"Robert Tycko","doi":"10.1016/j.sbi.2025.103043","DOIUrl":"10.1016/j.sbi.2025.103043","url":null,"abstract":"<div><div>Beginning in the 1990s, solid state nuclear magnetic resonance (ssNMR) methods played a major role in elucidating the molecular structures and properties of amyloid fibrils. General principles that explain these structures and properties were uncovered and experimentally-based structural models were first developed from ssNMR data. Since 2017, cryogenic electron microscopy (cryo-EM) techniques have become capable of solving amyloid structures at near-atomic resolution. Although cryo-EM measurements are now the main approach for structural studies of amyloid fibrils, ssNMR measurements remain essential for studies of certain structures and structural features, as well as studies of dynamical and mechanistic aspects. Recent publications from various research groups illustrate the continuing importance of ssNMR and the unique information available from ssNMR measurements in amyloid research.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"92 ","pages":"Article 103043"},"PeriodicalIF":6.1,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143785387","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}
{"title":"Raman spectroscopy and imaging of protein droplet formation and aggregation","authors":"Matthew D. Watson, Jennifer C. Lee","doi":"10.1016/j.sbi.2025.103041","DOIUrl":"10.1016/j.sbi.2025.103041","url":null,"abstract":"<div><div>Raman microscopy offers a unique combination of chemical and spatial resolution with structural sensitivity. This makes it an ideal tool for studies of protein structural changes in heterogenous samples such as protein liquid–liquid phase separation (LLPS) and amyloid formation. These processes are characterized by the spontaneous assembly of proteins to form either microscopic liquid droplets or insoluble filaments stabilized by β-sheets. LLPS and amyloid formation are closely related, with many proteins that undergo LLPS also forming amyloids. This has led to the proposal that development of β-sheets in droplets is an initiating event in toxic amyloid formation. This review surveys recent applications of Raman microscopic methods to studies of LLPS and amyloid formation both <em>in vitro</em> and <em>in cellulo</em>.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"92 ","pages":"Article 103041"},"PeriodicalIF":6.1,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739213","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}
Neera Borkakoti , António J.M. Ribeiro , Janet M. Thornton
{"title":"A structural perspective on enzymes and their catalytic mechanisms","authors":"Neera Borkakoti , António J.M. Ribeiro , Janet M. Thornton","doi":"10.1016/j.sbi.2025.103040","DOIUrl":"10.1016/j.sbi.2025.103040","url":null,"abstract":"<div><div>In this perspective, we analyse the progress made in our knowledge of enzyme sequences, structures and functions in the last 2 years. We review how much new enzyme data have been garnered and annotated, derived from the study of proteins using structural and computational approaches. Recent advances towards capturing ‘Catalysis <em>in silico</em>’ are described, including knowledge and predictions of enzyme structures, their interactions and mechanisms. We highlight the flood of enzyme data, driven by metagenomic sequencing, the improved enzyme data resources, the high coverage in Protein Data Bank of E.C. classes and the AI-driven structure prediction techniques that facilitate the accurate prediction of protein structures. We note the focus on disordered regions in the context of enzyme regulation and specificity and comment on emerging bioinformatic approaches that capture reaction mechanisms computationally for comparing and predicting enzyme mechanisms. We also consider the drivers of progress in this field in the next five years.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"92 ","pages":"Article 103040"},"PeriodicalIF":6.1,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725468","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}
{"title":"Mechanistic insights into INO80-type chromatin remodelers","authors":"Gregory D. Bowman","doi":"10.1016/j.sbi.2025.103030","DOIUrl":"10.1016/j.sbi.2025.103030","url":null,"abstract":"<div><div>Chromatin remodelers are adenosine triphosphate (ATP)-driven enzymes that physically reorganize nucleosomes, the basic packaging unit of all eukaryotic chromosomes. INO80, SWR1/SRCAP, and TIP60 are large multisubunit remodelers that share similar components yet have distinct biochemical and biological functions. This review summarizes key architectural features of these complexes and how they engage DNA, nucleosomes, and hexasomes to carry out their tasks.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"92 ","pages":"Article 103030"},"PeriodicalIF":6.1,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143706379","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}
Sören von Bülow , Giulio Tesei , Kresten Lindorff-Larsen
{"title":"Machine learning methods to study sequence–ensemble–function relationships in disordered proteins","authors":"Sören von Bülow , Giulio Tesei , Kresten Lindorff-Larsen","doi":"10.1016/j.sbi.2025.103028","DOIUrl":"10.1016/j.sbi.2025.103028","url":null,"abstract":"<div><div>Recent years have seen tremendous developments in the use of machine learning models to link amino-acid sequence, structure, and function of folded proteins. These methods are, however, rarely applicable to the wide range of proteins and sequences that comprise intrinsically disordered regions. We here review developments in the study of sequence–ensemble–function relationships of disordered proteins that exploit or are used to train machine learning models. These include methods for generating conformational ensembles and designing new sequences, and for linking sequences to biophysical properties and biological functions. We highlight how these developments are built on a tight integration between experiment, theory and simulations, and account for evolutionary constraints, which operate on sequences of disordered regions differently than on those of folded domains.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"92 ","pages":"Article 103028"},"PeriodicalIF":6.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143601866","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}
Fidha Nazreen Kunnath Muhammedkutty , Matthew MacAinsh , Huan-Xiang Zhou
{"title":"Atomistic molecular dynamics simulations of intrinsically disordered proteins","authors":"Fidha Nazreen Kunnath Muhammedkutty , Matthew MacAinsh , Huan-Xiang Zhou","doi":"10.1016/j.sbi.2025.103029","DOIUrl":"10.1016/j.sbi.2025.103029","url":null,"abstract":"<div><div>Recent years have seen remarkable gains in the accuracy of atomistic molecular dynamics (MD) simulations of intrinsically disordered proteins (IDPs) and expansion in the types of calculated properties that can be directly compared with experimental measurements. These advances occurred due to the use of IDP-tested force fields and the porting of MD simulations to GPUs and other computational technologies. All-atom MD simulations are now explaining the sequence-dependent dynamics of IDPs; elucidating the mechanisms of their binding to other proteins, nucleic acids, and membranes; revealing the modes of drug action on them; and characterizing their phase separation. Artificial intelligence (AI) and machine learning (ML) are further expanding the reach of atomistic MD simulations.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"92 ","pages":"Article 103029"},"PeriodicalIF":6.1,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143576926","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}
Catherine E. Rowland, Gustavo Arruda Bezerra, Michael J. Skynner
{"title":"Rational design of cyclic peptides, with an emphasis on bicyclic peptides","authors":"Catherine E. Rowland, Gustavo Arruda Bezerra, Michael J. Skynner","doi":"10.1016/j.sbi.2025.103025","DOIUrl":"10.1016/j.sbi.2025.103025","url":null,"abstract":"<div><div>Macrocyclic peptides are a promising chemotype for drug discovery, given their attractive properties of proteolytic stability, bioavailability and the ability to inhibit protein–protein interactions. Approaches to the generation of macrocyclic peptides include optimisation of hits from library screening; <em>de novo</em> design from known ligands and antibody paratopes or protein–protein interactions; constraint of linear peptides to afford beneficial properties of macrocycles; and novel approaches to cyclisation. We describe the recent literature and exemplify these approaches in the design of peptide macrocycles, and the benefits of incorporating computational and structure-guided approaches into compound design and optimisation. The benefits of the use of structural biology as a component part of phage display campaigns are further exemplified by reference to the optimisation of Bicycle® molecules.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"92 ","pages":"Article 103025"},"PeriodicalIF":6.1,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143594127","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}
{"title":"Deciphering driving forces of biomolecular phase separation from simulations","authors":"Lars V. Schäfer , Lukas S. Stelzl","doi":"10.1016/j.sbi.2025.103026","DOIUrl":"10.1016/j.sbi.2025.103026","url":null,"abstract":"<div><div>The formation and modulation of biomolecular condensates as well as their structural and dynamic properties are determined by an intricate interplay of different driving forces, which down at the microscopic scale involve molecular interactions of the biological macromolecules and the surrounding solvent and ions. Molecular simulations are increasingly used to provide detailed insights into the various processes and thermodynamic driving forces at play, thereby yielding mechanistic understanding and aiding the interpretation of experiments at the level of individual amino acid residues or even atoms. Here we summarize recent advances in the field of biocondensate simulations with a focus on coarse-grained and all-atom molecular dynamics (MD) simulations. We highlight possible future challenges concerning computationally efficient and physically accurate simulations of increasingly large and complex biocondensate systems.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"92 ","pages":"Article 103026"},"PeriodicalIF":6.1,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143576923","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}