[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122622-en":3,"doc-seo-122622-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},122622,1099513958762,"Logic","https://ap-avatar.wpscdn.com/avatar/1000023916a998db790?x-image-process=image/resize,m_fixed,w_180,h_180&k=1784791008015729253",8,"Research & Report","Characterization of RNA polymerase II trigger loop mutations using molecular dynamics simulations and machine learning - Research article summary","Catalysis and fidelity of multisubunit RNA polymerases depend on the conserved trigger loop (TL), which drives transcription through conformational changes and interactions with NTP substrates. TL residue mutations produce distinct outcomes, including altered catalytic activity and fidelity. This study uses molecular dynamics simulations and machine learning to analyze TL mutations in Saccharomyces cerevisiae RNA polymerase II, linking individual variants to phenotypes derived from mutant fitness under stress and uncovering structural patterns associated with loss- and gain-of-function effects.","UC Merced  \nUC Merced Previously Published Works  \nTitle  \nCharacterization of RNA polymerase II trigger loop mutations using molecular dynamics simulations and machine learning  \nPermalink  \n[https://escholarship.org/uc/item/4dd7h4wr](https://escholarship.org/uc/item/4dd7h4wr)  \nJournal  \nPLOS Computational Biology, 19(3)  \nISSN  \n1553-734X  \nAuthors  \nDutagaci, Bercem  \nDuan, Bingbing Qiu, Chenxi et al.  \nPublication Date  \n2023  \nDOI  \n10.1371/journal.pcbi.1010999  \nCopyright Information  \nThis work is made available under the terms of a Creative Commons Attribution License, available at [https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/)  \nPeer reviewed  \n[eScholarship.org](eScholarship.org) Powered by the California Digital Library  \nUniversity of California  \nPLOS COMPUTATIONAL BIOLOGY  \nOPEN ACCESS  \nCitation: Dutagaci B, Duan B, Qiu C, Kaplan CD, Feig M (2023) Characterization of RNA polymerase II trigger loop mutations using molecular dynamics simulations and machine learning. PLoS Comput Biol 19(3): e1010999 . [https://doi.org/10.1371/](https://doi.org/10.1371/)[ ](https://doi.org/10.1371/)[journal.pcbi.1010999](journal.pcbi.1010999)  \nEditor: Guanghong Wei, Fudan University, CHINA  \nReceived: August 15, 2022  \nAccepted: March 6, 2023  \nPublished: March 22, 2023  \nPeer Review History: PLOS recognizes the benefits of transparency in the peer review process; therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. The editorial history of this article is available here:  \n[https://doi.org/10.1371/journal.pcbi.1010999](https://doi.org/10.1371/journal.pcbi.1010999)  \n[Copyright:](Copyright:) © [2023](2023) Dutagaci et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.  \nData Availability Statement: The experimental data is in S1 Spreadsheet, average distances extracted from MD are in S2 Spreadsheet. The ML models and protocols are found at: [https://github](https://github). com/bercemd/PolII-mutants All derivative analysis  \nRESEARCH ARTICLE  \nCharacterization of RNA polymerase II trigger loop mutations using molecular dynamics simulations and machine learning  \nBercem Dutagaci1 *, Bingbing Duan2, Chenxi Qiu3, Craig D. Kaplan2, Michael Feig4 *  \n1 Department of Molecular and Cell Biology, University of California Merced, Merced, California, United States of America, 2 Department of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America, 3 Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America, 4 Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan, United States of America  \n* [bercemdutagaci@gmail.com](bercemdutagaci@gmail.com) (BD); [mfeiglab@gmail.com](mfeiglab@gmail.com) (MF)  \nAbstract  \nCatalysis and fidelity of multisubunit RNA polymerases rely on a highly conserved active site domain called the trigger loop (TL), which achieves roles in transcription through conformational changes and interaction with NTP substrates. The mutations of TL residues cause distinct effects on catalysis including hypo-and hyperactivity and altered fidelity. We applied molecular dynamics simulation (MD) and machine learning (ML) techniques to characterize TL mutations in the Saccharomyces cerevisiae RNA Polymerase II (Pol II) system. We did so to determine relationships between individual mutations and phenotypes and to associate phenotypes with MD simulated structural alterations. Using fitness values of mutants under various stress conditions, we modeled phenotypes along a spectrum of continual values. We found that ML could predict the phenotypes with 0.68 R2 correlation from amino acid sequences alone. It","cbCaitA3VZTSFVec","https://ap.wps.com/l/cbCaitA3VZTSFVec","pdf",4010842,1,28,"English","en",105,"# Abstract\n## Methods and data integration\n## Phenotype prediction and clustering\n## Key structural findings","[{\"question\":\"What role does the RNA polymerase II trigger loop play in transcription?\",\"answer\":\"The trigger loop (TL) contributes to catalysis and fidelity by undergoing conformational changes and interacting with NTP substrates during RNA synthesis.\"},{\"question\":\"How did the study link TL mutations to functional phenotypes?\",\"answer\":\"It combined molecular dynamics simulations with machine learning and used mutant fitness values under various stress conditions to model phenotypes across a continuum.\"},{\"question\":\"What structural trends were observed for loss-of-function and lethal mutations?\",\"answer\":\"A subset of loss-of-function (LOF) and lethal mutations increased distances between TL residues and the NTP substrate, while another subset increased distances between TL and the bridge helix (BH).\"}]","Characterization of RNA polymerase II trigger loop mutations using molecular dynamics simulations and machine learning - Research article summary | PDF",1785811769,71,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"characterization-of-rna-polymerase-ii-trigger-loop-mutations-using-molecular-dynamics-simulations-and-machine-learning-research-article-summary","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/characterization-of-rna-polymerase-ii-trigger-loop-mutations-using-molecular-dynamics-simulations-and-machine-learning-research-article-summary/122622/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What role does the RNA polymerase II trigger loop play in transcription?","Question",{"text":75,"@type":76},"The trigger loop (TL) contributes to catalysis and fidelity by undergoing conformational changes and interacting with NTP substrates during RNA synthesis.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How did the study link TL mutations to functional phenotypes?",{"text":80,"@type":76},"It combined molecular dynamics simulations with machine learning and used mutant fitness values under various stress conditions to model phenotypes across a continuum.",{"name":82,"@type":73,"acceptedAnswer":83},"What structural trends were observed for loss-of-function and lethal mutations?",{"text":84,"@type":76},"A subset of loss-of-function (LOF) and lethal mutations increased distances between TL residues and the NTP substrate, while another subset increased distances between TL and the bridge helix (BH).","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]