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}
{"title":"Language models for protein design","authors":"Jin Sub Lee , Osama Abdin , Philip M. Kim","doi":"10.1016/j.sbi.2025.103027","DOIUrl":"10.1016/j.sbi.2025.103027","url":null,"abstract":"<div><div>The recent surge of large language models has shown that machines are capable of reading, understanding, and communicating through language, even sometimes displaying capabilities surpassing those of humans. Proteins can be represented as strings of amino acids akin to words in a sentence, and the same principles of language modeling can be used to learn informative representations for protein structure prediction, design, and property prediction. In this review, we will focus on applications of language modeling to protein design. We will first cover the foundations of protein language modeling and discuss recent advances such as context-conditioned design and structure integration. We also consider current shortcomings and promising avenues of research for protein language modeling to facilitate future development of improved protein language models for design.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"92 ","pages":"Article 103027"},"PeriodicalIF":6.1,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562679","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}
Ardan Patwardhan, Richard Henderson, Christopher J Russo
{"title":"Extending the reach of single-particle cryoEM.","authors":"Ardan Patwardhan, Richard Henderson, Christopher J Russo","doi":"10.1016/j.sbi.2025.103005","DOIUrl":"https://doi.org/10.1016/j.sbi.2025.103005","url":null,"abstract":"<p><p>Molecular structure determination using electron cryomicroscopy (cryoEM) is poised in early 2025 to surpass X-ray crystallography as the most used method for experimentally determining new structures. But the technique has not reached the physical limits set by radiation damage and the signal-to-noise ratio in individual images of molecules. By examining these limits and comparing the number and resolution of structures determined versus molecular weight, we identify opportunities for extending the application of single-particle cryoEM. This will help guide technology development to continue the exponential growth of structural biology.</p>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":" ","pages":"103005"},"PeriodicalIF":6.1,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143556200","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}
Manuel Fernández Merino , Maria Pia Cosma , Maria Victoria Neguembor
{"title":"Super-resolving chromatin in its own terms: Recent approaches to portray genomic organization","authors":"Manuel Fernández Merino , Maria Pia Cosma , Maria Victoria Neguembor","doi":"10.1016/j.sbi.2025.103021","DOIUrl":"10.1016/j.sbi.2025.103021","url":null,"abstract":"<div><div>Chromatin organizes in a highly hierarchical manner that affects gene regulation. While many discoveries in the field have been driven by genomic techniques, super-resolution microscopy has proved to be an essential method to fully understand folding in single cells. In this article we summarize the main strategies to probe chromatin architecture using single-molecule localization microscopy and some of the key findings this has enabled. We specifically focus on the recent developments in techniques using oligonucleotide libraries and how their versatility drives multiplexing. These multiplexed libraries allow to super-resolve architectural proteins, DNA folding and transcription. We compare the latest results in this field and reflect about the future of these methods.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"92 ","pages":"Article 103021"},"PeriodicalIF":6.1,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529249","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}