{"title":"Correction to: The Largest Subunit of Human TFIIIC Complex, TFIIIC220, a Lysine Acetyltransferase Targets Histone H3K18.","authors":"","doi":"10.1093/jb/mvae025","DOIUrl":"10.1093/jb/mvae025","url":null,"abstract":"","PeriodicalId":15234,"journal":{"name":"Journal of biochemistry","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140119566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mural cell adhesion is important for the localization of basement membrane components during angiogenesis, and cell-cell interactions are thought to be critical for basement membrane formation. Type IV collagen, a component of the basement membrane, and non-triple helical type IV collagen α1 chain (NTH α1(IV)) co-localize in the basement membrane of neovascular vessels. However, it remains unclear how type IV collagen and NTH α1(IV) are produced around the basement membrane. In the present study, we developed a de novo angiogenesis model using human umbilical vein endothelial cell spheroids and TIG-1 fibroblast cells and demonstrated that NTH α1(IV), probably with α1(IV) chain before forming triple helix molecule, was localized in the fibroblasts in contact with vascular endothelial cells. This localization was disrupted by DAPT, a Notch signaling inhibitor. DAPT treatment also reduced type IV collagen and NTH α1(IV) secretion in TIG-1 fibroblasts, along with diminished COL4A1 and COL4A2 gene expression. Downregulation of Notch3 in TIG-1 fibroblasts decreased the secretion of type IV collagen and NTH α1(IV). Taken together, these findings suggest that heterogeneous and homogeneous intercellular Notch signaling via Notch3 induces type IV collagen and NTH α1(IV) expression in fibroblasts and contributes to basement membrane formation in neovascular vessels.
壁细胞粘附对血管生成过程中基底膜成分的定位非常重要,而细胞-细胞间的相互作用被认为是基底膜形成的关键。基底膜的一种成分 IV 型胶原和非三螺旋 IV 型胶原 α1 链(NTH α1(IV))共同定位在新生血管的基底膜上。然而,IV 型胶原蛋白和 NTH α1(IV)是如何在基底膜周围产生的仍不清楚。在本研究中,我们利用人体脐静脉内皮细胞球和 TIG-1 成纤维细胞建立了一个新生血管生成模型,并证明 NTH α1(IV)可能与 α1(IV)链在形成三螺旋分子之前定位于与血管内皮细胞接触的成纤维细胞中。这种定位被 Notch 信号抑制剂 DAPT 破坏。DAPT 还能减少 TIG-1 成纤维细胞中 IV 型胶原蛋白和 NTH α1(IV)的分泌,同时减少 COL4A1 和 COL4A2 基因的表达。下调 TIG-1 成纤维细胞中的 Notch3 可减少 IV 型胶原和 NTH α1(IV)的分泌。综上所述,这些研究结果表明,异质性和同质性细胞间 Notch 信号通过 Notch3 诱导成纤维细胞表达 IV 型胶原和 NTH α1(IV),并促进新生血管基底膜的形成。
{"title":"Notch signaling pathway induces expression of type IV collagen in angiogenesis.","authors":"Kazuki Kukita, Nanaka Matsuzaka, Mikihisa Takai, Yasutada Imamura, Yongchol Shin","doi":"10.1093/jb/mvad120","DOIUrl":"10.1093/jb/mvad120","url":null,"abstract":"<p><p>Mural cell adhesion is important for the localization of basement membrane components during angiogenesis, and cell-cell interactions are thought to be critical for basement membrane formation. Type IV collagen, a component of the basement membrane, and non-triple helical type IV collagen α1 chain (NTH α1(IV)) co-localize in the basement membrane of neovascular vessels. However, it remains unclear how type IV collagen and NTH α1(IV) are produced around the basement membrane. In the present study, we developed a de novo angiogenesis model using human umbilical vein endothelial cell spheroids and TIG-1 fibroblast cells and demonstrated that NTH α1(IV), probably with α1(IV) chain before forming triple helix molecule, was localized in the fibroblasts in contact with vascular endothelial cells. This localization was disrupted by DAPT, a Notch signaling inhibitor. DAPT treatment also reduced type IV collagen and NTH α1(IV) secretion in TIG-1 fibroblasts, along with diminished COL4A1 and COL4A2 gene expression. Downregulation of Notch3 in TIG-1 fibroblasts decreased the secretion of type IV collagen and NTH α1(IV). Taken together, these findings suggest that heterogeneous and homogeneous intercellular Notch signaling via Notch3 induces type IV collagen and NTH α1(IV) expression in fibroblasts and contributes to basement membrane formation in neovascular vessels.</p>","PeriodicalId":15234,"journal":{"name":"Journal of biochemistry","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139087012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Recently, the development of protein degraders (protein-degrading compounds) has prominently progressed. There are two remarkable classes of protein degraders: proteolysis-targeting chimeras (PROTACs) and molecular glue degraders (MGDs). Almost 70 years have passed since thalidomide was initially developed as a sedative-hypnotic drug, which is currently recognized as one of the most well-known MGDs. During the last two decades, a myriad of PROTACs and MGDs have been developed, and the molecular mechanism of action (MOA) of thalidomide was basically elucidated, including identifying its molecular target cereblon (CRBN). CRBN forms a Cullin Ring Ligase 4 with Cul4 and DDB1, whose substrate specificity is controlled by its binding ligands. Thalidomide, lenalidomide and pomalidomide, three CRBN-binding MGDs, were clinically approved to treat several intractable diseases (including multiple myeloma). Several other MGDs and CRBN-based PROTACs (ARV-110 and AVR-471) are undergoing clinical trials. In addition, several new related technologies regarding PROTACs and MGDs have also been developed, and achievements of protein degraders impact not only therapeutic fields but also basic biological science. In this article, I introduce the history of protein degraders, from the development of thalidomide to the latest PROTACs and related technologies.
{"title":"Protein degraders - from thalidomide to new PROTACs.","authors":"Takumi Ito","doi":"10.1093/jb/mvad113","DOIUrl":"10.1093/jb/mvad113","url":null,"abstract":"<p><p>Recently, the development of protein degraders (protein-degrading compounds) has prominently progressed. There are two remarkable classes of protein degraders: proteolysis-targeting chimeras (PROTACs) and molecular glue degraders (MGDs). Almost 70 years have passed since thalidomide was initially developed as a sedative-hypnotic drug, which is currently recognized as one of the most well-known MGDs. During the last two decades, a myriad of PROTACs and MGDs have been developed, and the molecular mechanism of action (MOA) of thalidomide was basically elucidated, including identifying its molecular target cereblon (CRBN). CRBN forms a Cullin Ring Ligase 4 with Cul4 and DDB1, whose substrate specificity is controlled by its binding ligands. Thalidomide, lenalidomide and pomalidomide, three CRBN-binding MGDs, were clinically approved to treat several intractable diseases (including multiple myeloma). Several other MGDs and CRBN-based PROTACs (ARV-110 and AVR-471) are undergoing clinical trials. In addition, several new related technologies regarding PROTACs and MGDs have also been developed, and achievements of protein degraders impact not only therapeutic fields but also basic biological science. In this article, I introduce the history of protein degraders, from the development of thalidomide to the latest PROTACs and related technologies.</p>","PeriodicalId":15234,"journal":{"name":"Journal of biochemistry","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138885083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cellular senescence occurs in response to endogenous or exogenous stresses and is characterized by stable cell cycle arrest, alterations in nuclear morphology and secretion of proinflammatory factors, referred to as the senescence-associated secretory phenotype (SASP). An increase of senescent cells is associated with the development of several types of cancer and aging-related diseases. Therefore, senolytic agents that selectively remove senescent cells may offer opportunities for developing new therapeutic strategies against such cancers and aging-related diseases. This review outlines senescence inducers and the general characteristics of senescent cells. We also discuss the involvement of senescent cells in certain cancers and diseases. Finally, we describe a series of senolytic agents and their utilization in therapeutic strategies.
{"title":"Therapeutic strategies targeting cellular senescence for cancer and other diseases.","authors":"Xuebing Wang, Takeshi Fukumoto, Ken-Ichi Noma","doi":"10.1093/jb/mvae015","DOIUrl":"10.1093/jb/mvae015","url":null,"abstract":"<p><p>Cellular senescence occurs in response to endogenous or exogenous stresses and is characterized by stable cell cycle arrest, alterations in nuclear morphology and secretion of proinflammatory factors, referred to as the senescence-associated secretory phenotype (SASP). An increase of senescent cells is associated with the development of several types of cancer and aging-related diseases. Therefore, senolytic agents that selectively remove senescent cells may offer opportunities for developing new therapeutic strategies against such cancers and aging-related diseases. This review outlines senescence inducers and the general characteristics of senescent cells. We also discuss the involvement of senescent cells in certain cancers and diseases. Finally, we describe a series of senolytic agents and their utilization in therapeutic strategies.</p>","PeriodicalId":15234,"journal":{"name":"Journal of biochemistry","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11058315/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139746705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tissue stem cells are maintained in the adult body throughout life and are crucial for tissue homeostasis as they supply newly functional cells. Quiescence is a reversible arrest in the G0/G1 phase of the cell cycle and a strategy to maintain the quality of tissue stem cells. Quiescence maintains stem cells in a self-renewable and differentiable state for a prolonged period by suppressing energy consumption and cell damage and depletion. Most adult neural stem cells in the brain maintain the quiescent state and produce neurons and glial cells through differentiation after activating from the quiescent state to the proliferating state. In this process, proteostasis, including proteolysis, is essential to transition between the quiescent and proliferating states associated with proteome remodeling. Recent reports have demonstrated that quiescent and proliferating neural stem cells have different expression patterns and roles as proteostatic molecules and are affected by age, indicating differing processes for protein homeostasis in these two states in the brain. This review discusses the multiple regulatory stages from protein synthesis (protein birth) to proteolysis (protein death) in quiescent neural stem cells.
{"title":"Protein homeostasis and degradation in quiescent neural stem cells.","authors":"Taeko Kobayashi","doi":"10.1093/jb/mvae006","DOIUrl":"10.1093/jb/mvae006","url":null,"abstract":"<p><p>Tissue stem cells are maintained in the adult body throughout life and are crucial for tissue homeostasis as they supply newly functional cells. Quiescence is a reversible arrest in the G0/G1 phase of the cell cycle and a strategy to maintain the quality of tissue stem cells. Quiescence maintains stem cells in a self-renewable and differentiable state for a prolonged period by suppressing energy consumption and cell damage and depletion. Most adult neural stem cells in the brain maintain the quiescent state and produce neurons and glial cells through differentiation after activating from the quiescent state to the proliferating state. In this process, proteostasis, including proteolysis, is essential to transition between the quiescent and proliferating states associated with proteome remodeling. Recent reports have demonstrated that quiescent and proliferating neural stem cells have different expression patterns and roles as proteostatic molecules and are affected by age, indicating differing processes for protein homeostasis in these two states in the brain. This review discusses the multiple regulatory stages from protein synthesis (protein birth) to proteolysis (protein death) in quiescent neural stem cells.</p>","PeriodicalId":15234,"journal":{"name":"Journal of biochemistry","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139650827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mitochondria are essential eukaryotic organelles that produce ATP as well as synthesize various macromolecules. They also participate in signalling pathways such as the innate immune response and apoptosis. These diverse functions are performed by >1,000 different mitochondrial proteins. Although mitochondria are continuously exposed to potentially damaging conditions such as reactive oxygen species, proteases/peptidases localized in different mitochondrial subcompartments, termed mitoproteases, maintain mitochondrial quality and integrity. In addition to processing incoming precursors and degrading damaged proteins, mitoproteases also regulate metabolic reactions, mitochondrial protein half-lives and gene transcription. Impaired mitoprotease function is associated with various pathologies. In this review, we highlight recent advances in our understanding of mitochondrial quality control regulated by autophagy, ubiquitin-proteasomes and mitoproteases.
线粒体是真核生物的重要细胞器,可产生 ATP 并合成各种大分子。它们还参与信号传导途径,如先天免疫反应和细胞凋亡。这些不同的功能由超过 1000 种不同的线粒体蛋白执行。尽管线粒体不断暴露于活性氧等潜在的破坏性环境中,但分布在不同线粒体亚区的蛋白酶/肽酶(称为丝裂蛋白酶)却能保持线粒体的质量和完整性。除了处理进入的前体和降解受损蛋白质外,有丝分裂蛋白酶还能调节新陈代谢反应、线粒体蛋白质半衰期和基因转录。有丝分裂蛋白酶功能受损与各种病症有关。在这篇综述中,我们将重点介绍在了解由自噬、泛素蛋白酶体和有丝分裂蛋白酶调控的线粒体质量控制方面的最新进展。
{"title":"Mitochondrial quality control via organelle and protein degradation.","authors":"Koji Yamano, Hiroki Kinefuchi, Waka Kojima","doi":"10.1093/jb/mvad106","DOIUrl":"10.1093/jb/mvad106","url":null,"abstract":"<p><p>Mitochondria are essential eukaryotic organelles that produce ATP as well as synthesize various macromolecules. They also participate in signalling pathways such as the innate immune response and apoptosis. These diverse functions are performed by >1,000 different mitochondrial proteins. Although mitochondria are continuously exposed to potentially damaging conditions such as reactive oxygen species, proteases/peptidases localized in different mitochondrial subcompartments, termed mitoproteases, maintain mitochondrial quality and integrity. In addition to processing incoming precursors and degrading damaged proteins, mitoproteases also regulate metabolic reactions, mitochondrial protein half-lives and gene transcription. Impaired mitoprotease function is associated with various pathologies. In this review, we highlight recent advances in our understanding of mitochondrial quality control regulated by autophagy, ubiquitin-proteasomes and mitoproteases.</p>","PeriodicalId":15234,"journal":{"name":"Journal of biochemistry","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138802027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Glycosylation changes in cancer proteins have been associated with malignant transformation. However, techniques for analyzing site-specific glycosylation changes in target proteins obtained from clinical tissue samples are insufficient. To overcome these problems, we developed a targeted N-glycoproteomic approach consisting of immunoprecipitation, glycopeptide enrichment, LC/MS/MS and structural assignment using commercially available analytical software followed by manual confirmation. This approach was applied to the comparative site-specific glycosylation analysis of lysosome-associated membrane glycoprotein 1 (LAMP1) between breast cancer (BC) tumors and normal tissues adjacent to tumors. Extensive determination of glycan heterogeneity from four N-glycosylation sites (Asn84/103/249/261) in LAMP1 identified 262 glycoforms and revealed remarkable diversity in tumor glycan structures. A significant increase in N-glycoforms with multiple fucoses and sialic acids at Asn84/249 and high-mannose-type glycans at Asn103/261 were observed in the tumor. Principal component analysis revealed that tumors of different subtypes have independent distributions. This approach enables site-specific glycopeptide analysis of target glycoprotein in breast cancer tissue and become a powerful tool for characterizing tumors with different pathological features by their glycan profiles.
{"title":"Comparative Analysis of Site-Specific N-glycosylation of LAMP1 from Breast Cancer Tissues.","authors":"Shoko Ohashi, Daisuke Takakura, Noritoshi Kobayashi, Motohiko Tokuhisa, Yasushi Ichikawa, Nana Kawasaki","doi":"10.1093/jb/mvae001","DOIUrl":"10.1093/jb/mvae001","url":null,"abstract":"<p><p>Glycosylation changes in cancer proteins have been associated with malignant transformation. However, techniques for analyzing site-specific glycosylation changes in target proteins obtained from clinical tissue samples are insufficient. To overcome these problems, we developed a targeted N-glycoproteomic approach consisting of immunoprecipitation, glycopeptide enrichment, LC/MS/MS and structural assignment using commercially available analytical software followed by manual confirmation. This approach was applied to the comparative site-specific glycosylation analysis of lysosome-associated membrane glycoprotein 1 (LAMP1) between breast cancer (BC) tumors and normal tissues adjacent to tumors. Extensive determination of glycan heterogeneity from four N-glycosylation sites (Asn84/103/249/261) in LAMP1 identified 262 glycoforms and revealed remarkable diversity in tumor glycan structures. A significant increase in N-glycoforms with multiple fucoses and sialic acids at Asn84/249 and high-mannose-type glycans at Asn103/261 were observed in the tumor. Principal component analysis revealed that tumors of different subtypes have independent distributions. This approach enables site-specific glycopeptide analysis of target glycoprotein in breast cancer tissue and become a powerful tool for characterizing tumors with different pathological features by their glycan profiles.</p>","PeriodicalId":15234,"journal":{"name":"Journal of biochemistry","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139432511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aging is a major risk factor for many diseases. Recent studies have shown that age-related disruption of proteostasis leads to the accumulation of abnormal proteins and that dysfunction of the two major intracellular proteolytic pathways, the ubiquitin-proteasome pathway, and the autophagy-lysosome pathway, is largely responsible for this process. Conversely, it has been shown that activation of these proteolytic pathways may contribute to lifespan extension and suppression of pathological conditions, making it a promising intervention for anti-aging. This review provides an overview of the important role of intracellular protein degradation in aging and summarizes how the disruption of proteostasis is involved in age-related diseases.
{"title":"Relationships between protein degradation, cellular senescence, and organismal aging.","authors":"Jun Hamazaki, Shigeo Murata","doi":"10.1093/jb/mvae016","DOIUrl":"10.1093/jb/mvae016","url":null,"abstract":"<p><p>Aging is a major risk factor for many diseases. Recent studies have shown that age-related disruption of proteostasis leads to the accumulation of abnormal proteins and that dysfunction of the two major intracellular proteolytic pathways, the ubiquitin-proteasome pathway, and the autophagy-lysosome pathway, is largely responsible for this process. Conversely, it has been shown that activation of these proteolytic pathways may contribute to lifespan extension and suppression of pathological conditions, making it a promising intervention for anti-aging. This review provides an overview of the important role of intracellular protein degradation in aging and summarizes how the disruption of proteostasis is involved in age-related diseases.</p>","PeriodicalId":15234,"journal":{"name":"Journal of biochemistry","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11058314/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139722810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Understanding the mechanisms of drug action in the brain, from the genetic to the neural circuit level, is crucial for the development of new agents that act upon the central nervous system. Determining the brain regions and neurons affected by a drug is essential for revealing its mechanism of action in the brain. c-Fos, a marker of neuronal activation, has been widely used to detect neurons activated by stimuli with high spatial resolution. In this review, the use of c-Fos for the visualization and manipulation of activated neurons is introduced. I also explain that a higher temporal resolution can be achieved by changing the staining method for visualization of c-Fos. Moreover, a new method that allows labeling and manipulating commonly activated neurons using two different stimuli is proposed.
{"title":"Rethinking c-Fos for understanding drug action in the brain.","authors":"Katsuyasu Sakurai","doi":"10.1093/jb/mvad110","DOIUrl":"10.1093/jb/mvad110","url":null,"abstract":"<p><p>Understanding the mechanisms of drug action in the brain, from the genetic to the neural circuit level, is crucial for the development of new agents that act upon the central nervous system. Determining the brain regions and neurons affected by a drug is essential for revealing its mechanism of action in the brain. c-Fos, a marker of neuronal activation, has been widely used to detect neurons activated by stimuli with high spatial resolution. In this review, the use of c-Fos for the visualization and manipulation of activated neurons is introduced. I also explain that a higher temporal resolution can be achieved by changing the staining method for visualization of c-Fos. Moreover, a new method that allows labeling and manipulating commonly activated neurons using two different stimuli is proposed.</p>","PeriodicalId":15234,"journal":{"name":"Journal of biochemistry","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139048777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Phosphorylation is the most important and studied post-translational modification (PTM), which plays a crucial role in protein function studies and experimental design. Many significant studies have been performed to predict phosphorylation sites using various machine-learning methods. Recently, several studies have claimed that deep learning-based methods are the best way to predict the phosphorylation sites because deep learning as an advanced machine learning method can automatically detect complex representations of phosphorylation patterns from raw sequences and thus offers a powerful tool to improve phosphorylation site prediction. In this study, we report DF-Phos, a new phosphosite predictor based on the Deep Forest to predict phosphorylation sites. In DF-Phos, the feature vector taken from the CkSAApair method is as input for a Deep Forest framework for predicting phosphorylation sites. The results of 10-fold cross-validation show that the Deep Forest method has the highest performance among other available methods. We implemented a Python program of DF-Phos, which is freely available for non-commercial use at https://github.com/zahiriz/DF-Phos Moreover, users can use it for various PTM predictions.
{"title":"DF-Phos: Prediction of Protein Phosphorylation Sites by Deep Forest.","authors":"Zeynab Zahiri, Nasser Mehrshad, Maliheh Mehrshad","doi":"10.1093/jb/mvad116","DOIUrl":"10.1093/jb/mvad116","url":null,"abstract":"<p><p>Phosphorylation is the most important and studied post-translational modification (PTM), which plays a crucial role in protein function studies and experimental design. Many significant studies have been performed to predict phosphorylation sites using various machine-learning methods. Recently, several studies have claimed that deep learning-based methods are the best way to predict the phosphorylation sites because deep learning as an advanced machine learning method can automatically detect complex representations of phosphorylation patterns from raw sequences and thus offers a powerful tool to improve phosphorylation site prediction. In this study, we report DF-Phos, a new phosphosite predictor based on the Deep Forest to predict phosphorylation sites. In DF-Phos, the feature vector taken from the CkSAApair method is as input for a Deep Forest framework for predicting phosphorylation sites. The results of 10-fold cross-validation show that the Deep Forest method has the highest performance among other available methods. We implemented a Python program of DF-Phos, which is freely available for non-commercial use at https://github.com/zahiriz/DF-Phos Moreover, users can use it for various PTM predictions.</p>","PeriodicalId":15234,"journal":{"name":"Journal of biochemistry","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139048776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}