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VenusMutHub:A systematic evaluation of protein mutation effect predictors on small-scale experimental data 被引量:1
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作者 Liang Zhang Hua Pang +11 位作者 Chenghao Zhang Song Li Yang Tan a Fan Jiang a Mingchen Li Yuanxi Yu Ziyi Zhou Banghao Wu Bingxin Zhou Hao Liu Pan Tan Liang Hong 《Acta Pharmaceutica Sinica B》 2025年第5期2454-2467,共14页
In protein engineering,while computational models are increasingly used to predict mutation effects,their evaluations primarily rely on high-throughput deep mutational scanning(DMS)experiments that use surrogate reado... In protein engineering,while computational models are increasingly used to predict mutation effects,their evaluations primarily rely on high-throughput deep mutational scanning(DMS)experiments that use surrogate readouts,which may not adequately capture the complex biochemical properties of interest.Many proteins and their functions cannot be assessed through high-throughput methods due to technical limitations or the nature of the desired properties,and this is particularly true for the real industrial application scenario.Therefore,the desired testing datasets,will be small-size(∼10–100)experimental data for each protein,and involve as many proteins as possible and as many properties as possible,which is,however,lacking.Here,we present VenusMutHub,a comprehensive benchmark study using 905 small-scale experimental datasets curated from published literature and public databases,spanning 527 proteins across diverse functional properties including stability,activity,binding affinity,and selectivity.These datasets feature direct biochemical measurements rather than surrogate readouts,providing a more rigorous assessment of model performance in predicting mutations that affect specific molecular functions.We evaluate 23 computational models across various methodological paradigms,such as sequence-based,structure-informed and evolutionary approaches.This benchmark provides practical guidance for selecting appropriate prediction methods in protein engineering applications where accurate prediction of specific functional properties is crucial. 展开更多
关键词 Protein engineering mutation effect prediction BENCHMARK Small-sCale experimental data Stability ACTIVITY Binding affinity SELECTIVITY
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Histone 3 lysine 36 to methionine mutations stably interact with and sequester SDG8 in Arabidopsis thaliana 被引量:3
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作者 Guang Lin Ying Zhou +1 位作者 Min Li Yuda Fang 《Science China(Life Sciences)》 SCIE CAS CSCD 2018年第2期225-234,共10页
Post-transcriptional modifications of histones play important roles in various biological processes. Here, we report that Arabidopsis plants overexpressing histone H3 lysine to methionine mutations at histone H3.1K36(... Post-transcriptional modifications of histones play important roles in various biological processes. Here, we report that Arabidopsis plants overexpressing histone H3 lysine to methionine mutations at histone H3.1K36(H3.1K36M) and H3.3K36(H3.3K36M) have serious developmental defects with early-flowering and change in the modifications of endogenous histone H3, including acetylation at lysine 9(H3K9ac), trimethylation at lysine 27(H3K27me3), di-and tri-methylation at lysine 36(H3K36me2 and H3K36me3). In addition, H3K36M mutation alters its subcellular localization and interacts with H3K36 methyltransferase SDG8. Our results support a model in which H3K36M stably interacts with SDG8, and inhibits the activity of SDG8 by sequestering SDG8, resulting in a dominant negative effect to affect the proper expression levels of a variety of genes and plant development. 展开更多
关键词 histone H3 lysine to methionine mutation SDG8 dominant negative effect Arabidopsis
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Evolutionary characteristics,biochemical structure,and function impact of MSTN gene
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作者 Rui Zhang Yunpeng Wu +3 位作者 Tianqi Sun Zhengxing Lian Jingqing Chen Yefeng Qiu 《Genes & Diseases》 2025年第6期73-76,共4页
The myostatin(MSTN)gene,also known as growth and differentiation factor 8(GDF8),plays a critical role in regulating muscle mass in animals by negatively controlling the number and size of skeletal myocytes.MSTN mutati... The myostatin(MSTN)gene,also known as growth and differentiation factor 8(GDF8),plays a critical role in regulating muscle mass in animals by negatively controlling the number and size of skeletal myocytes.MSTN mutations have been demonstrated to cause the double-muscling(DBM)phenomenon in various species,including cattle,sheep,mice,pigs,dogs,rabbits,and even humans.1 In this study,we explored the evolutionary characteristics,biochemical structure and function impacts of the sheep MSTN gene(oMSTN)using phylogenetic analysis,mutation effect evaluation,residue conservation studies,structural modeling,and protein–protein docking. 展开更多
关键词 mstn gene phylogenetic analysis biochemical structure function impacts evolutionary characteristics regulating muscle mass mutation effect skeletal myocytesmstn
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