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Sargsyan K, Lim C. Using protein language models for protein interaction hot spot prediction with limited data. BMC Bioinformatics 2024; 25:115. [PMID: 38493120 PMCID: PMC10943781 DOI: 10.1186/s12859-024-05737-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Accepted: 03/11/2024] [Indexed: 03/18/2024] Open
Abstract
BACKGROUND Protein language models, inspired by the success of large language models in deciphering human language, have emerged as powerful tools for unraveling the intricate code of life inscribed within protein sequences. They have gained significant attention for their promising applications across various areas, including the sequence-based prediction of secondary and tertiary protein structure, the discovery of new functional protein sequences/folds, and the assessment of mutational impact on protein fitness. However, their utility in learning to predict protein residue properties based on scant datasets, such as protein-protein interaction (PPI)-hotspots whose mutations significantly impair PPIs, remained unclear. Here, we explore the feasibility of using protein language-learned representations as features for machine learning to predict PPI-hotspots using a dataset containing 414 experimentally confirmed PPI-hotspots and 504 PPI-nonhot spots. RESULTS Our findings showcase the capacity of unsupervised learning with protein language models in capturing critical functional attributes of protein residues derived from the evolutionary information encoded within amino acid sequences. We show that methods relying on protein language models can compete with methods employing sequence and structure-based features to predict PPI-hotspots from the free protein structure. We observed an optimal number of features for model precision, suggesting a balance between information and overfitting. CONCLUSIONS This study underscores the potential of transformer-based protein language models to extract critical knowledge from sparse datasets, exemplified here by the challenging realm of predicting PPI-hotspots. These models offer a cost-effective and time-efficient alternative to traditional experimental methods for predicting certain residue properties. However, the challenge of explaining why specific features are important for determining certain residue properties remains.
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Affiliation(s)
- Karen Sargsyan
- Institute of Biomedical Sciences, Academia Sinica, Taipei, 115, Taiwan.
| | - Carmay Lim
- Institute of Biomedical Sciences, Academia Sinica, Taipei, 115, Taiwan.
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2
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Bai R, Luo Y. Exploring the role of mitochondrial-associated and peripheral neuropathy genes in the pathogenesis of diabetic peripheral neuropathy. BMC Neurol 2024; 24:95. [PMID: 38481183 PMCID: PMC10936109 DOI: 10.1186/s12883-024-03589-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Accepted: 02/27/2024] [Indexed: 03/17/2024] Open
Abstract
BACKGROUND Diabetic peripheral neuropathy (DPN) is a prevalent and serious complication of diabetes mellitus, impacting the nerves in the limbs and leading to symptoms like pain, numbness, and diminished function. While the exact molecular and immune mechanisms underlying DPN remain incompletely understood, recent findings indicate that mitochondrial dysfunction may play a role in the advancement of this diabetic condition. METHODS Two RNA transcriptome datasets (codes: GSE185011 and GSE95849), comprising samples from diabetic peripheral neuropathy (DPN) patients and healthy controls (HC), were retrieved from the Gene Expression Omnibus (GEO) database hosted by the National Center for Biotechnology Information (NCBI). Subsequently, differential expression analysis and gene set enrichment analysis were performed. Protein-protein interaction (PPI) networks were constructed to pinpoint key hub genes associated with DPN, with a specific emphasis on genes related to mitochondria and peripheral neuropathy disease (PND) that displayed differential expression. Additionally, the study estimated the levels of immune cell infiltration in both the HC and DPN samples. To validate the findings, quantitative polymerase chain reaction (qPCR) was employed to confirm the differential expression of selected genes in the DPN samples. RESULTS This research identifies four hub genes associated mitochondria or PN. Furthermore, the analysis revealed increased immune cell infiltration in DPN tissues, particularly notable for macrophages and T cells. Additionally, our investigation identified potential drug candidates capable of regulating the expression of the four hub genes. These findings were corroborated by qPCR results, reinforcing the credibility of our bioinformatics analysis. CONCLUSIONS This study provides a comprehensive overview of the molecular and immunological characteristics of DPN, based on both bioinformatics and experimental methods.
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Affiliation(s)
- Ruojing Bai
- Department of Geriatric Medicine, School of Clinical Medicine, Beijing Tsinghua Changgung Hospital, Tsinghua University, Beijing, China
| | - Yuanyuan Luo
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China.
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Senoo A, Hoshino M, Shiomi T, Nakakido M, Nagatoishi S, Kuroda D, Nakagawa I, Tame JRH, Caaveiro JMM, Tsumoto K. Structural basis for the recognition of human hemoglobin by the heme-acquisition protein Shr from Streptococcus pyogenes. Sci Rep 2024; 14:5374. [PMID: 38438508 PMCID: PMC10912661 DOI: 10.1038/s41598-024-55734-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Accepted: 02/27/2024] [Indexed: 03/06/2024] Open
Abstract
In Gram-positive bacteria, sophisticated machineries to acquire the heme group of hemoglobin (Hb) have evolved to extract the precious iron atom contained in it. In the human pathogen Streptococcus pyogenes, the Shr protein is a key component of this machinery. Herein we present the crystal structure of hemoglobin-interacting domain 2 (HID2) of Shr bound to Hb. HID2 interacts with both, the protein and heme portions of Hb, explaining the specificity of HID2 for the heme-bound form of Hb, but not its heme-depleted form. Further mutational analysis shows little tolerance of HID2 to interfacial mutations, suggesting that its interaction surface with Hb could be a suitable candidate to develop efficient inhibitors abrogating the binding of Shr to Hb.
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Affiliation(s)
- Akinobu Senoo
- Laboratory of Protein Drug Discovery, Graduate School of Pharmaceutical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka City, 812-8582, Japan
- Department of Chemistry and Biotechnology, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan
| | - Masato Hoshino
- Department of Bioengineering, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan
| | - Toshiki Shiomi
- Laboratory of Protein Drug Discovery, Graduate School of Pharmaceutical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka City, 812-8582, Japan
| | - Makoto Nakakido
- Department of Bioengineering, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan
| | - Satoru Nagatoishi
- Medical Device Development and Regulation Research Center, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan
| | - Daisuke Kuroda
- Research Center for Drug and Vaccine Development, National Institute of Infectious Diseases, 1-23-1 Toyama, Shinjuku-ku, Tokyo, 162-8640, Japan
| | - Ichiro Nakagawa
- Department of Microbiology, Graduate School of Medicine, Kyoto University, Yoshida-Konoe-cho, Sakyo-ku, Kyoto, 606-8501, Japan
| | - Jeremy R H Tame
- Drug Design Laboratory, Graduate School of Medical Life Science, Yokohama City University, 1-7-29 Suehiro, Yokohama, Kanagawa, 230-0045, Japan
| | - Jose M M Caaveiro
- Laboratory of Protein Drug Discovery, Graduate School of Pharmaceutical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka City, 812-8582, Japan.
- Department of Bioengineering, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan.
| | - Kouhei Tsumoto
- Department of Chemistry and Biotechnology, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan.
- Department of Bioengineering, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan.
- The Institute of Medical Sciences, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8629, Japan.
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Zhang YH, Huang F, Li J, Shen W, Chen L, Feng K, Huang T, Cai YD. Identification of Protein-Protein Interaction Associated Functions Based on Gene Ontology. Protein J 2024:10.1007/s10930-024-10180-6. [PMID: 38436837 DOI: 10.1007/s10930-024-10180-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/07/2024] [Indexed: 03/05/2024]
Abstract
Protein-protein interactions (PPIs) involve the physical or functional contact between two or more proteins. Generally, proteins that can interact with each other always have special relationships. Some previous studies have reported that gene ontology (GO) terms are related to the determination of PPIs, suggesting the special patterns on the GO terms of proteins in PPIs. In this study, we explored the special GO term patterns on human PPIs, trying to uncover the underlying functional mechanism of PPIs. The experimental validated human PPIs were retrieved from STRING database, which were termed as positive samples. Additionally, we randomly paired proteins occurring in positive samples, yielding lots of negative samples. A simple calculation was conducted to count the number of positive samples for each GO term pair, where proteins in samples were annotated by GO terms in the pair individually. The similar number for negative samples was also counted and further adjusted due to the great gap between the numbers of positive and negative samples. The difference of the above two numbers and the relative ratio compared with the number on positive samples were calculated. This ratio provided a precise evaluation of the occurrence of GO term pairs for positive samples and negative samples, indicating the latent GO term patterns for PPIs. Our analysis unveiled several nuclear biological processes, including gene transcription, cell proliferation, and nutrient metabolism, as key biological functions. Interactions between major proliferative or metabolic GO terms consistently correspond with significantly reported PPIs in recent literature.
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Affiliation(s)
- Yu-Hang Zhang
- School of Life Sciences, Shanghai University, Shanghai, 200444, People's Republic of China
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - FeiMing Huang
- School of Life Sciences, Shanghai University, Shanghai, 200444, People's Republic of China
| | - JiaBo Li
- School of Computer Engineering and Science, Shanghai University, Shanghai, 200444, People's Republic of China
| | - WenFeng Shen
- School of Computer and Information Engineering, Shanghai Polytechnic University, Shanghai, 201209, People's Republic of China
| | - Lei Chen
- College of Information Engineering, Shanghai Maritime University, Shanghai, 201306, People's Republic of China
| | - KaiYan Feng
- Department of Computer Science, Guangdong AIB Polytechnic College, Guangzhou, 510507, People's Republic of China
| | - Tao Huang
- Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, People's Republic of China.
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, People's Republic of China.
| | - Yu-Dong Cai
- School of Life Sciences, Shanghai University, Shanghai, 200444, People's Republic of China.
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Balakrishnan S, Bhasker R, Ramasamy Y, Dev SA. Genome-wide analysis of cellulose synthase gene superfamily in Tectona grandis L.f. 3 Biotech 2024; 14:86. [PMID: 38385141 PMCID: PMC10876501 DOI: 10.1007/s13205-024-03927-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 01/08/2024] [Indexed: 02/23/2024] Open
Abstract
This study aimed to explore Cellulose synthase gene superfamily of teak, and its evolutionary relationship with homologous genes of other woody species. The incidence of evolutionary events like gene duplication and gene loss, influence of the selection pressure, and consequent adaptive functional divergence of the duplicated TgCes gene were assessed alongside it's role in wood coloration. This study identified 39 full-length non-redundant proteins belonging to CesA and Csl gene families. TgCesA and TgCsl proteins with Cellulose synthase domain repeats indicated tandem gene duplication and probable genetic variability, enabling local adaptation. Further, multi-domain protein (MYB-like DNA-binding domain and CesA domain) with maximum introns was also identified indicating gene fusion and formation of complex protein with novel functions. Phylogenetic analysis grouped the genes into seven subfamilies (CesA, CslA, CslC, CslD, CslE, CslG, and CslM) with each undergoing gene duplication and loss along their evolutionary history. Post-species gene duplications and probable neofunctionalization were identified in TgCesA and TgCsl gene families. Each subfamily was found to be under strong purifying selection with a few or no sites under positive selection. Functional divergence analysis further revealed site-specific selective constraints in CesA and Csl genes of the teak Cellulose synthase gene family. Furthermore, protein-protein interaction network analysis identified co-expression of Cellulose synthase gene with flavonoid 3',5'-hydroxylase (F3'5'H, CYP75A), involved in the biosynthesis of xylem anthocyanin compounds, probably responsible for wood coloration. This study thus offers a foundation for future research in wood formation and wood property traits specific to teak and its provenances. Supplementary Information The online version contains supplementary material available at 10.1007/s13205-024-03927-6.
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Affiliation(s)
- Swathi Balakrishnan
- Forest Genetics and Biotechnology Division, Kerala Forest Research Institute, Peechi, Thrissur, Kerala 680653 India
- Cochin University of Science and Technology, Kochi, Kerala India
| | - Reshma Bhasker
- Forest Genetics and Biotechnology Division, Kerala Forest Research Institute, Peechi, Thrissur, Kerala 680653 India
- Cochin University of Science and Technology, Kochi, Kerala India
| | - Yasodha Ramasamy
- Division of Plant Biotechnology, Institute of Forest Genetics and Tree Breeding, R.S. Puram, Coimbatore, 641002 India
| | - Suma Arun Dev
- Forest Genetics and Biotechnology Division, Kerala Forest Research Institute, Peechi, Thrissur, Kerala 680653 India
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Hirano K, Sueda S. A fluorescence-based binding assay for proteins using the cell surface as a sensing platform. ANAL SCI 2024; 40:563-571. [PMID: 38091253 DOI: 10.1007/s44211-023-00476-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 11/17/2023] [Indexed: 02/27/2024]
Abstract
Protein-protein interaction (PPI) analysis is very important for elucidating the functions of proteins because many proteins execute their functions in living cells by interacting with one another. In PPI analysis, methods using the sensor chips are widely employed to obtain quantitative data. However, these methods require that the target proteins be immobilized on the sensor chips, and the immobilization processes can affect the binding of the target proteins to their binding partners. In the present work, we propose a PPI analysis system in which the surface of the living cells is utilized as a sensing platform. In our approach, the target protein is displayed on the cell surface by expressing it as a fusion protein with a membrane protein, and the PPI analysis is then conducted by applying its binding partner labeled with a fluorescent dye to the cell surface. We have constructed a model of this binding analysis system using the interaction between biotin protein ligase (BPL) and biotin carboxyl carrier protein (BCCP), where BCCP was displayed on the cell surface and BPL labeled with fluorescein was applied to the cell surface. Here, a red fluorescent protein, mApple, was attached to the C-terminus of the fusion protein of BCCP with a membrane protein. We evaluated the binding level of the labeled BPL by using the intensity ratios of fluorescence from fluorescein to that from mApple. We found that the binding level of the labeled BPL was stably evaluated at least across 60 min observation period and estimated the binding dissociation constant between BPL and BCCP by equilibrium analysis to be 0.33 ± 0.05 μM.
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Affiliation(s)
- Kazuki Hirano
- Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, 820-8502, Japan
| | - Shinji Sueda
- Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, 820-8502, Japan.
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Wang G, Hua R, Chen X, He X, Dingming Y, Chen H, Zhang B, Dong Y, Liu M, Liu J, Liu T, Zhao J, Zhao YQ, Qiao L. MX1 and UBE2L6 are potential metaflammation gene targets in both diabetes and atherosclerosis. PeerJ 2024; 12:e16975. [PMID: 38406276 PMCID: PMC10893863 DOI: 10.7717/peerj.16975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 01/29/2024] [Indexed: 02/27/2024] Open
Abstract
Background The coexistence of diabetes mellitus (DM) and atherosclerosis (AS) is widespread, although the explicit metabolism and metabolism-associated molecular patterns (MAMPs) responsible for the correlation are still unclear. Methods Twenty-four genetically wild-type male Ba-Ma mini pigs were randomly divided into five groups distinguished by different combinations of 90 mg/kg streptozotocin (STZ) intravenous injection and high-cholesterol/lipid (HC) or high-lipid (HL) diet feeding for 9 months in total. Pigs in the STZ+HC and STZ+HL groups were injected with STZ first and then fed the HC or HL diet for 9 months. In contrast, pigs in the HC+STZ and HL+STZ groups were fed the HC or HL diet for 9 months and injected with STZ at 3 months. The controls were only fed a regular diet for 9 months. The blood glucose and abdominal aortic plaque observed through oil red O staining were used as evaluation indicators for successful modelling of DM and AS. A microarray gene expression analysis of all subjects was performed. Results Atherosclerotic lesions were observed only in the HC+STZ and STZ+HC groups. A total of 103 differentially expressed genes (DEGs) were identified as common between them. The most significantly enriched pathways of 103 common DEGs were influenza A, hepatitis C, and measles. The global and internal protein-protein interaction (PPI) networks of the 103 common DEGs consisted of 648 and 14 nodes, respectively. The top 10 hub proteins, namely, ISG15, IRG6, IRF7, IFIT3, MX1, UBE2L6, DDX58, IFIT2, USP18, and IFI44L, drive aspects of DM and AS. MX1 and UBE2L6 were the intersection of internal and global PPI networks. The expression of MX1 and UBE2L6 was 507.22 ± 342.56 and 96.99 ± 49.92 in the HC+STZ group, respectively, which was significantly higher than others and may be linked to the severity of hyperglycaemia-related atherosclerosis. Further PPI network analysis of calcium/micronutrients, including MX1 and UBE2L6, consisted of 58 and 18 nodes, respectively. The most significantly enriched KEGG pathways were glutathione metabolism, pyrimidine metabolism, purine metabolism, and metabolic pathways. Conclusions The global and internal PPI network of the 103 common DEGs consisted of 648 and 14 nodes, respectively. The intersection of the nodes of internal and global PPI networks was MX1 and UBE2L6, suggesting their key role in the comorbidity mechanism of DM and AS. This inference was partly verified by the overexpression of MX1 and UBE2L6 in the HC+STZ group but not others. Further calcium- and micronutrient-related enriched KEGG pathway analysis supported that MX1 and UBE2L6 may affect the inflammatory response through micronutrient metabolic pathways, conceptually named metaflammation. Collectively, MX1 and UBE2L6 may be potential common biomarkers for DM and AS that may reveal metaflammatory aspects of the pathological process, although proper validation is still needed to determine their contribution to the detailed mechanism.
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Affiliation(s)
- Guisheng Wang
- Department of Radiology, Third Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Rongrong Hua
- Department of Radiology, Third Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xiaoxia Chen
- Department of Radiology, Third Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xucheng He
- Department of Radiology, Third Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Yao Dingming
- Department of Radiology, Third Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Hua Chen
- Laboratory Animal Center, Chinese People’s Liberation Army General Hospital, Beijing, China
| | - Buhuan Zhang
- Department of Radiology, Third Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Yuru Dong
- Department of Radiology, Third Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Muqing Liu
- Department of Radiology, Third Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Jiaxiong Liu
- Department of Radiology, Third Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Ting Liu
- Department of Radiology, Beijing YouAn Hospital, Capital Medical University, Beijing, China
| | - Jingwei Zhao
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yu Qiong Zhao
- Laboratory Animal Center, Chinese People’s Liberation Army General Hospital, Beijing, China
| | - Li Qiao
- Department of International Business, Business College of Beijing Union University, Beijing, China
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Dhiman V, Biswas S, Shekhawat RS, Sadhukhan A, Yadav P. In silico characterization of five novel disease-resistance proteins in Oryza sativa sp. japonica against bacterial leaf blight and rice blast diseases. 3 Biotech 2024; 14:48. [PMID: 38268986 PMCID: PMC10803709 DOI: 10.1007/s13205-023-03893-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 12/16/2023] [Indexed: 01/26/2024] Open
Abstract
In the current study, gene network analysis revealed five novel disease-resistance proteins against bacterial leaf blight (BB) and rice blast (RB) diseases caused by Xanthomonas oryzae pv. oryzae (Xoo) and Magnaporthe oryzae (M. oryzae), respectively. In silico modeling, refinement, and model quality assessment were performed to predict the best structures of these five proteins and submitted to ModelArchive for future use. An in-silico annotation indicated that the five proteins functioned in signal transduction pathways as kinases, phospholipases, transcription factors, and DNA-modifying enzymes. The proteins were localized in the nucleus and plasma membrane. Phylogenetic analysis showed the evolutionary relation of the five proteins with disease-resistance proteins (XA21, OsTRX1, PLD, and HKD-motif-containing proteins). This indicates similar disease-resistant properties between five unknown proteins and their evolutionary-related proteins. Furthermore, gene expression profiling of these proteins using public microarray data showed their differential expression under Xoo and M. oryzae infection. This study provides an insight into developing disease-resistant rice varieties by predicting novel candidate resistance proteins, which will assist rice breeders in improving crop yield to address future food security through molecular breeding and biotechnology. Supplementary Information The online version contains supplementary material available at 10.1007/s13205-023-03893-5.
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Affiliation(s)
- Vedikaa Dhiman
- Department of Bioscience and Bioengineering, Indian Institute of Technology, Jodhpur, 342030 Rajasthan India
| | - Soham Biswas
- Department of Biotechnology and Bioinformatics, University of Hyderabad, Hyderabad, Telangana India
| | - Rajveer Singh Shekhawat
- Department of Bioscience and Bioengineering, Indian Institute of Technology, Jodhpur, 342030 Rajasthan India
| | - Ayan Sadhukhan
- Department of Bioscience and Bioengineering, Indian Institute of Technology, Jodhpur, 342030 Rajasthan India
| | - Pankaj Yadav
- Department of Bioscience and Bioengineering, Indian Institute of Technology, Jodhpur, 342030 Rajasthan India
- School of Artificial Intelligence and Data Science, Indian Institute of Technology, Jodhpur, Rajasthan India
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Lazou M, Hutton JR, Chakravarty A, Joseph-McCarthy D. Identification of a druggable site on GRP78 at the GRP78-SARS-CoV-2 interface and virtual screening of compounds to disrupt that interface. J Comput Aided Mol Des 2024; 38:6. [PMID: 38263499 DOI: 10.1007/s10822-023-00546-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Accepted: 12/02/2023] [Indexed: 01/25/2024]
Abstract
SARS-CoV-2, the virus that causes COVID-19, led to a global health emergency that claimed the lives of millions. Despite the widespread availability of vaccines, the virus continues to exist in the population in an endemic state which allows for the continued emergence of new variants. Most of the current vaccines target the spike glycoprotein interface of SARS-CoV-2, creating a selection pressure favoring viral immune evasion. Antivirals targeting other molecular interactions of SARS-CoV-2 can help slow viral evolution by providing orthogonal selection pressures on the virus. GRP78 is a host auxiliary factor that mediates binding of the SARS-CoV-2 spike protein to human cellular ACE2, the primary pathway of cell infection. As GRP78 forms a ternary complex with SARS-CoV-2 spike protein and ACE2, disrupting the formation of this complex is expected to hinder viral entry into host cells. Here, we developed a model of the GRP78-Spike RBD-ACE2 complex. We then used that model together with hot spot mapping of the GRP78 structure to identify the putative binding site for spike protein on GRP78. Next, we performed structure-based virtual screening of known drug/candidate drug libraries to identify binders to GRP78 that are expected to disrupt spike protein binding to the GRP78, and thereby preventing viral entry to the host cell. A subset of these compounds has previously been shown to have some activity against SARS-CoV-2. The identified hits are starting points for the further development of novel SARS-CoV-2 therapeutics, potentially serving as proof-of-concept for GRP78 as a potential drug target for other viruses.
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Affiliation(s)
- Maria Lazou
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA
| | - Jonathan R Hutton
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA
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Chen X, Zhang J, Wang S, Cai H, Yang M, Dong Y. Genome-wide molecular evolution analysis of the GRF and GIF gene families in Plantae (Archaeplastida). BMC Genomics 2024; 25:74. [PMID: 38233778 PMCID: PMC10795294 DOI: 10.1186/s12864-024-10006-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 01/11/2024] [Indexed: 01/19/2024] Open
Abstract
BACKGROUND Plant growth-regulating factors (GRFs) and GRF-interacting factors (GIFs) interact with each other and collectively have important regulatory roles in plant growth, development, and stress responses. Therefore, it is of great significance to explore the systematic evolution of GRF and GIF gene families. However, our knowledge and understanding of the role of GRF and GIF genes during plant evolution has been fragmentary. RESULTS In this study, a large number of genomic and transcriptomic datasets of algae, mosses, ferns, gymnosperms and angiosperms were used to systematically analyze the evolution of GRF and GIF genes during the evolution of plants. The results showed that GRF gene first appeared in the charophyte Klebsormidium nitens, whereas the GIF genes originated relatively early, and these two gene families were mainly expanded by segmental duplication events after plant terrestrialization. During the process of evolution, the protein sequences and functions of GRF and GIF family genes are relatively conservative. As cooperative partner, GRF and GIF genes contain the similar types of cis-acting elements in their promoter regions, which enables them to have similar transcriptional response patterns, and both show higher levels of expression in reproductive organs and tissues and organs with strong capacity for cell division. Based on protein-protein interaction analysis and verification, we found that the GRF-GIF protein partnership began to be established in pteridophytes and is highly conserved across different terrestrial plants. CONCLUSIONS These results provide a foundation for further exploration of the molecular evolution and biological functions of GRF and GIF genes.
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Affiliation(s)
- Xinghao Chen
- Forest Department, Forestry College, Hebei Agricultural University, Baoding, China
- Hebei Key Laboratory for Tree Genetic Resources and Forest Protection, 071000, Baoding, People's Republic of China
| | - Jun Zhang
- Forest Department, Forestry College, Hebei Agricultural University, Baoding, China
- Hebei Key Laboratory for Tree Genetic Resources and Forest Protection, 071000, Baoding, People's Republic of China
| | - Shijie Wang
- Forest Department, Forestry College, Hebei Agricultural University, Baoding, China
- Hebei Key Laboratory for Tree Genetic Resources and Forest Protection, 071000, Baoding, People's Republic of China
| | - Hongyu Cai
- Forest Department, Forestry College, Hebei Agricultural University, Baoding, China
- Hebei Key Laboratory for Tree Genetic Resources and Forest Protection, 071000, Baoding, People's Republic of China
| | - Minsheng Yang
- Forest Department, Forestry College, Hebei Agricultural University, Baoding, China.
- Hebei Key Laboratory for Tree Genetic Resources and Forest Protection, 071000, Baoding, People's Republic of China.
| | - Yan Dong
- Forest Department, Forestry College, Hebei Agricultural University, Baoding, China.
- Hebei Key Laboratory for Tree Genetic Resources and Forest Protection, 071000, Baoding, People's Republic of China.
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11
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Kumar V, Chunchagatta Lakshman PK, Prasad TK, Manjunath K, Bairy S, Vasu AS, Ganavi B, Jasti S, Kamariah N. Target-based drug discovery: Applications of fluorescence techniques in high throughput and fragment-based screening. Heliyon 2024; 10:e23864. [PMID: 38226204 PMCID: PMC10788520 DOI: 10.1016/j.heliyon.2023.e23864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 12/14/2023] [Accepted: 12/14/2023] [Indexed: 01/17/2024] Open
Abstract
Target-based discovery of first-in-class therapeutics demands an in-depth understanding of the molecular mechanisms underlying human diseases. Precise measurements of cellular and biochemical activities are critical to gain mechanistic knowledge of biomolecules and their altered function in disease conditions. Such measurements enable the development of intervention strategies for preventing or treating diseases by modulation of desired molecular processes. Fluorescence-based techniques are routinely employed for accurate and robust measurements of in-vitro activity of molecular targets and for discovering novel chemical molecules that modulate the activity of molecular targets. In the current review, the authors focus on the applications of fluorescence-based high throughput screening (HTS) and fragment-based ligand discovery (FBLD) techniques such as fluorescence polarization (FP), Förster resonance energy transfer (FRET), fluorescence thermal shift assay (FTSA) and microscale thermophoresis (MST) for the discovery of chemical probe to exploring target's role in disease biology and ultimately, serve as a foundation for drug discovery. Some recent advancements in these techniques for compound library screening against important classes of drug targets, such as G-protein-coupled receptors (GPCRs) and GTPases, as well as phosphorylation- and acetylation-mediated protein-protein interactions, are discussed. Overall, this review presents a landscape of how these techniques paved the way for the discovery of small-molecule modulators and biologics against these targets for therapeutic benefits.
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Affiliation(s)
| | | | - Thazhe Kootteri Prasad
- Centre for Chemical Biology & Therapeutics, inStem & NCBS, Bellary Road, Bangalore, 560065, India
| | - Kavyashree Manjunath
- Centre for Chemical Biology & Therapeutics, inStem & NCBS, Bellary Road, Bangalore, 560065, India
| | - Sneha Bairy
- Centre for Chemical Biology & Therapeutics, inStem & NCBS, Bellary Road, Bangalore, 560065, India
| | - Akshaya S. Vasu
- Centre for Chemical Biology & Therapeutics, inStem & NCBS, Bellary Road, Bangalore, 560065, India
| | - B. Ganavi
- Centre for Chemical Biology & Therapeutics, inStem & NCBS, Bellary Road, Bangalore, 560065, India
| | - Subbarao Jasti
- Centre for Chemical Biology & Therapeutics, inStem & NCBS, Bellary Road, Bangalore, 560065, India
| | - Neelagandan Kamariah
- Centre for Chemical Biology & Therapeutics, inStem & NCBS, Bellary Road, Bangalore, 560065, India
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12
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Ayub U, Naveed H. GSLAlign: community detection and local PPI network alignment. J Biomol Struct Dyn 2024:1-9. [PMID: 38214492 DOI: 10.1080/07391102.2024.2301757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Accepted: 12/29/2023] [Indexed: 01/13/2024]
Abstract
High throughput protein-protein interaction (PPI) profiling and computational techniques have resulted in generating a large amount of PPI network data. The study of PPI networks helps in understanding the biological processes of the proteins. The comparative study of the PPI networks helps in identifying the conserved interactions across the species. This article presents a novel local PPI network aligner 'GSLAlign' that consists of two stages. It first detects the communities from the PPI networks by applying the GraphSAGE algorithm using gene expression data. In the second stage, the detected communities are aligned using a community aligner that is based on protein sequence similarity. The community detection algorithm produces more separable and biologically accurate communities as compared to previous community detection algorithms. Moreover, the proposed community alignment algorithm achieves 3-8% better results in terms of semantic similarity as compared to previous local aligners. The average connectivity and coverage of the proposed algorithm are also better than the existing aligners.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Umair Ayub
- Department of Computer Science, Bahria University, Lahore, Pakistan
| | - Hammad Naveed
- National University of Computer and Emerging Sciences, Lahore, Pakistan and Computational Biology Research Lab, National University of Computer and Emerging Sciences, Lahore, Pakistan
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13
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Viala JPM, Bouveret E. Protein-Protein Interaction: Tandem Affinity Purification in Bacteria. Methods Mol Biol 2024; 2715:285-297. [PMID: 37930536 DOI: 10.1007/978-1-0716-3445-5_19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2023]
Abstract
The discovery of protein-protein interaction networks can lead to the unveiling of protein complex(es) forming cellular machinerie(s) or reveal component proteins of a specific cellular pathway. Deciphering protein-protein interaction networks therefore contributes to a deeper understanding of how cells function. Here we describe the protocol to perform tandem affinity purification (TAP) in bacteria, which enables the identification of the partners of a bait protein under native conditions. This method consists in two sequential steps of affinity purification using two different tags. For that purpose, the bait protein is translationally fused to the TAP tag, which consists of a calmodulin-binding peptide (CBP) and two immunoglobulin G (IgG)-binding domains of Staphylococcus aureus protein A (ProtA) that are separated by the tobacco etch virus (TEV) protease cleavage site. After the first round of purification based on the binding of ProtA to IgG-coated beads, TEV protease cleavage releases CBP-tagged bait protein along with its partners for a second round of purification on calmodulin affinity resin and leaves behind protein contaminants bound to IgG. Creating the TAP-tag translational fusion at the chromosomal locus allows detection of protein interactions occurring in physiological conditions.
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Affiliation(s)
- Julie P M Viala
- Laboratoire d'Ingénierie des Systèmes Macromoléculaires (UMR 7255), Institut de Microbiologie de la Méditerranée, Aix-Marseille Univ., CNRS, Marseille, France.
| | - Emmanuelle Bouveret
- Institut Pasteur, Department of Microbiology, Unit Stress, Adaptation and Metabolism in enterobacteria, Université Paris Cité, UMR CNRS 6047, Paris, France
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14
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Abuta'a YA, Caumont-Sarcos A, Albenne C, Ieva R. In Vivo Site-Directed and Time-Resolved Photocrosslinking of Envelope Proteins. Methods Mol Biol 2024; 2715:299-320. [PMID: 37930537 DOI: 10.1007/978-1-0716-3445-5_20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2023]
Abstract
In vivo site-directed photocrosslinking provides a means to probe the vicinity of proteins in their native cellular environment. Because this method relies on the incorporation of unnatural amino acid analogs that are similar in size to natural amino acids, crosslink products are indicative of direct protein-protein interactions. Here, we present the use of this approach to monitor both transient and stable interactions of two proteins of the envelope of Escherichia coli. First, we describe a protocol to characterize the interactions of a secretory protein as it transverses the bacterial envelope with temporal and spatial resolution. We combine site-directed photocrosslinking with radiolabeling of proteins and lipids. Second, we describe a method to purify a photocrosslinked partner protein and to analyze it by mass spectrometry. We use in-gel protein digestion and peptide fragmentation by MALDI-TOF/TOF tandem mass spectrometry to determine the site of interaction on the photocrosslinked partner.
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Affiliation(s)
- Yassin A Abuta'a
- Laboratoire de Microbiologie et Génétique Moléculaires (LMGM), Centre de Biologie Intégrative (CBI), Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Anne Caumont-Sarcos
- Laboratoire de Microbiologie et Génétique Moléculaires (LMGM), Centre de Biologie Intégrative (CBI), Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Cécile Albenne
- Laboratoire de Microbiologie et Génétique Moléculaires (LMGM), Centre de Biologie Intégrative (CBI), Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Raffaele Ieva
- Laboratoire de Microbiologie et Génétique Moléculaires (LMGM), Centre de Biologie Intégrative (CBI), Université de Toulouse, CNRS, UPS, Toulouse, France.
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15
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Douzi B. Surface Plasmon Resonance: A Sensitive Tool to Study Protein-Protein Interactions. Methods Mol Biol 2024; 2715:363-382. [PMID: 37930540 DOI: 10.1007/978-1-0716-3445-5_23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2023]
Abstract
Surface plasmon resonance (SPR) is one of the most commonly used techniques to study protein-protein interactions. The main advantage of SPR is the ability of measuring binding affinities and association/dissociation kinetics of complexes in real time, in a label-free environment, and using relatively small quantities of materials. The method is based on the immobilization of one of the binding partners, called the "ligand," on a dedicated sensor surface. Immobilization is followed by the injection of the other partner, called the "analyte," over the surface containing the ligand. The binding is monitored by following changes in the refractive index of the medium close to the sensor surface upon injection of the analyte. During the last 15 years, SPR has been intensively used in the study of bacterial secretion systems due to its ability of detecting highly dynamic complexes, which are difficult to investigate by other techniques. This chapter will guide users in setting up SPR experiments in order to identify protein complexes and to assess their binding affinity and/or kinetics. It will include detailed protocols for (i) immobilization of proteins with the amine coupling capture method, (ii) analyte-binding analysis, (iii) affinity/kinetics measurements, and (iv) data analysis.
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16
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Yazaki J, Dal-Bianco M. In Situ Protein Microarray for Identifying the Geminivirus-Arabidopsis Interactome. Methods Mol Biol 2024; 2724:307-314. [PMID: 37987915 DOI: 10.1007/978-1-0716-3485-1_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
The protein-protein interactions (PPI) by protein array technology complement other PPI assay technologies such as AP-MS and Y2H. The in situ protein array technology (NAPPA) enables low-cost, rapid, and comprehensive protein detection. It allows standardized and simultaneous assay of a wide range of proteins with a broad range of expression in cells. This technology facilitates the detection of protein-protein interactions within species and between heterologous species such as host-microbe. Here, we described the technique that identified a syntaxin-6 protein-mediated begomovirus infection using an array containing 4600 Arabidopsis genes. The protein microarray assay also identified several other viral protein-host protein interactions.
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Affiliation(s)
- Junshi Yazaki
- RIKEN Center for Integrative Medical Sciences, Yokohama City, Kanagawa, Japan.
| | - Maximiller Dal-Bianco
- Plant Genetics and Biochemistry Laboratory, BIOAGRO, Universidade Federal de Vicosa, Vicosa, Minas Gerais, Brazil.
- Department of Biochemistry and Molecular Biology, Universidade Federal de Vicosa, Vicosa, Minas Gerais, Brazil.
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17
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Lin JS, Lai EM. Protein-Protein Interactions: Yeast Two Hybrid. Methods Mol Biol 2024; 2715:235-246. [PMID: 37930532 DOI: 10.1007/978-1-0716-3445-5_15] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2023]
Abstract
The yeast two-hybrid system is a powerful and commonly used genetic tool to investigate the interaction between artificial fusion proteins inside the nucleus of yeast. Here, we describe how to use the Matchmaker GAL4-based yeast two-hybrid system to detect the interaction of the Agrobacterium type VI secretion system (T6SS) sheath components TssB and TssC41. The bait and prey gene are expressed as a fusion to the GAL4 DNA-binding domain (DNA-BD) and GAL4 activation domain (AD, prey/library fusion protein), respectively. When bait and prey fusion proteins interact in yeast nucleus, the DNA-BD and AD are brought into proximity, thus activating transcription of reporter genes. This technology can be widely used to identify interacting partners, confirm suspected interactions, and define interacting domains.
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Affiliation(s)
- Jer-Sheng Lin
- Institute of Plant and Microbial Biology, Academia Sinica, Taipei, Taiwan
| | - Erh-Min Lai
- Institute of Plant and Microbial Biology, Academia Sinica, Taipei, Taiwan.
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18
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de Amorim GC, Bardiaux B, Izadi-Pruneyre N. Structural Analysis of Proteins from Bacterial Secretion Systems and Their Assemblies by NMR Spectroscopy. Methods Mol Biol 2024; 2715:503-517. [PMID: 37930547 DOI: 10.1007/978-1-0716-3445-5_30] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2023]
Abstract
Bacterial secretion systems are built up from proteins with different physicochemical characteristics, such as highly hydrophobic transmembrane polypeptides, and soluble periplasmic or intracellular domains. A single complex can be composed of more than ten proteins with distinct features, spreading through different cellular compartments. The membrane and multicompartment nature of the proteins, and their large molecular weight make their study challenging. However, information on their structure and assemblies is required to understand their mechanisms and interfere with them. An alternative strategy is to work with soluble domains and peptides corresponding to the regions of interest of the proteins.Here, we describe a simple and fast protocol to evaluate the stability, folding, and interaction of protein sub-complexes by using solution-state Nuclear Magnetic Resonance (NMR) spectroscopy. This technique is widely used for protein structure and protein-ligand interaction analysis in solution.
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Affiliation(s)
- Gisele Cardoso de Amorim
- Núcleo Multidisciplinar de Pesquisa em Biologia, Campus Duque de Caxias, Universidade Federal do Rio de Janeiro, Duque de Caxias, RJ, Brazil
| | - Benjamin Bardiaux
- Institut Pasteur, Université Paris Cité, CNRS UMR 3528, Bacterial Transmembrane Systems Unit, Paris, France
| | - Nadia Izadi-Pruneyre
- Institut Pasteur, Université Paris Cité, CNRS UMR 3528, Bacterial Transmembrane Systems Unit, Paris, France.
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19
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Lin JS, Ali J, Lai EM. Protein-Protein Interactions: Co-immunoprecipitation. Methods Mol Biol 2024; 2715:273-283. [PMID: 37930535 DOI: 10.1007/978-1-0716-3445-5_18] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2023]
Abstract
Proteins often do not function as single substances but rather as team players in a dynamic network. Growing evidences show that protein-protein interactions are crucial in many biological processes in living cells. Genetic (such as yeast two hybrid, Y2H) and biochemical (such as co-immunoprecipitation, co-IP) methods are the commonly used methods to identify the interacting proteins. Immunoprecipitation (IP), a method using a target protein-specific antibody in conjunction with Protein A/G affinity beads, is a powerful tool to identify the molecules interacting with specific proteins. Therefore, co-IP is considered to be one of the standard methods to identify and/or confirm the occurrence of the protein-protein interaction events in vivo. The co-IP experiments can identify proteins via direct or indirect interactions or in a protein complex. Here, we use two different co-Ip protocols as an example to describe the principle, procedure, and experimental problems of co-IP. First, we show the interaction of two Agrobacterium type VI secretion system (T6SS) sheath components TssB and TssC41, and secondly, we show the protocol we used for determining the interaction of an epitope-tagged T6SS effector, Tde1 expressed in Agrobacterium with endogenously expressing adaptor/chaperone protein Tap1.
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Affiliation(s)
- Jer-Sheng Lin
- Institute of Plant and Microbial Biology, Academia Sinica, Taipei, Taiwan
| | - Jemal Ali
- Institute of Plant and Microbial Biology, Academia Sinica, Taipei, Taiwan
- Molecular and Biological Agricultural Sciences Program, Taiwan International Graduate Program, National Chung-Hsing University and Academia Sinica, Taipei, Taiwan
- Graduate Institute of Biotechnology, National Chung-Hsing University, Taichung, Taiwan
| | - Erh-Min Lai
- Institute of Plant and Microbial Biology, Academia Sinica, Taipei, Taiwan.
- Molecular and Biological Agricultural Sciences Program, Taiwan International Graduate Program, National Chung-Hsing University and Academia Sinica, Taipei, Taiwan.
- Biotechnology Center, National Chung-Hsing University, Taichung, Taiwan.
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20
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Calandra F, Siciliano V. Engineered Protease-Responsive RNA-Binding Proteins (RBPs) to Expand the Toolbox of Synthetic Circuits in Mammalian Cells. Methods Mol Biol 2024; 2774:59-69. [PMID: 38441758 DOI: 10.1007/978-1-0716-3718-0_5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/07/2024]
Abstract
Genetically encoded sensor-actuator circuits aim at reprogramming cellular functions and are inspired by intracellular networks: from the input signal (sensor) to the desired output response (actuator). In the last years, circuits with posttranscriptional regulation of gene expression have aroused great interest for their potential in the biomedical space. Posttranscriptional modulation can be achieved with ribozymes, riboswitches (simple regulatory elements based on RNA secondary structures), noncoding RNAs, and RNA-binding proteins (RBPs). RBPs are proteins that recognize specific motifs on the mRNA target inducing mRNA decay or translation inhibition. The use of RBPs deriving from different species in mammalian cells has allowed to create sophisticated and multilayered regulatory networks, addressing the previous limitation of regulatory orthogonal parts that can be assembled in synthetic devices. In this chapter, we describe the engineering and tests of protease-responsive RNA-binding proteins (L7Ae and MS2-cNOT7) to expand the toolbox of synthetic circuits in mammalian cells.
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Affiliation(s)
- Fabiana Calandra
- Synthetic and Systems Biology lab for Biomedicine, Istituto Italiano di Tecnologia-IIT, Naples, Italy
| | - Velia Siciliano
- Synthetic and Systems Biology lab for Biomedicine, Istituto Italiano di Tecnologia-IIT, Naples, Italy.
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21
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Zoued A, Duneau JP, Cascales E. Bacterial One- and Two-Hybrid Assays to Monitor Transmembrane Helix Interactions. Methods Mol Biol 2024; 2715:259-271. [PMID: 37930534 DOI: 10.1007/978-1-0716-3445-5_17] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2023]
Abstract
In transenvelope multiprotein machines such as bacterial secretion systems, protein-protein interactions not only occur between soluble domains but might also be mediated by helix-helix contacts in the inner membrane. Several assays have been therefore developed to test homotypic and heterotypic interactions between transmembrane α-helices in their native membrane environment. Here, we provide detailed protocols for two genetic assays, TOXCAT and GALLEX, which are based on the reconstitution of dimeric regulators allowing the control of expression of reporter genes.
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Affiliation(s)
- Abdelrahim Zoued
- Laboratoire d'Ingénierie des Systèmes Macromoléculaires, UMR7255, Institut de Microbiologie de la Méditerranée, Aix-Marseille Univ, CNRS, Marseille, France
- Centre International de Recherche en Infectiologie, UMR5308, Université Claude Bernard Lyon 1 - INSERM - CNRS, Lyon, France
| | - Jean-Pierre Duneau
- Laboratoire d'Ingénierie des Systèmes Macromoléculaires, UMR7255, Institut de Microbiologie de la Méditerranée, Aix-Marseille Univ, CNRS, Marseille, France
| | - Eric Cascales
- Laboratoire d'Ingénierie des Systèmes Macromoléculaires, UMR7255, Institut de Microbiologie de la Méditerranée, Aix-Marseille Univ, CNRS, Marseille, France.
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Wu J, Liu B, Zhang J, Wang Z, Li J. DL-PPI: a method on prediction of sequenced protein-protein interaction based on deep learning. BMC Bioinformatics 2023; 24:473. [PMID: 38097937 PMCID: PMC10722729 DOI: 10.1186/s12859-023-05594-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 12/01/2023] [Indexed: 12/17/2023] Open
Abstract
PURPOSE Sequenced Protein-Protein Interaction (PPI) prediction represents a pivotal area of study in biology, playing a crucial role in elucidating the mechanistic underpinnings of diseases and facilitating the design of novel therapeutic interventions. Conventional methods for extracting features through experimental processes have proven to be both costly and exceedingly complex. In light of these challenges, the scientific community has turned to computational approaches, particularly those grounded in deep learning methodologies. Despite the progress achieved by current deep learning technologies, their effectiveness diminishes when applied to larger, unfamiliar datasets. RESULTS In this study, the paper introduces a novel deep learning framework, termed DL-PPI, for predicting PPIs based on sequence data. The proposed framework comprises two key components aimed at improving the accuracy of feature extraction from individual protein sequences and capturing relationships between proteins in unfamiliar datasets. 1. Protein Node Feature Extraction Module: To enhance the accuracy of feature extraction from individual protein sequences and facilitate the understanding of relationships between proteins in unknown datasets, the paper devised a novel protein node feature extraction module utilizing the Inception method. This module efficiently captures relevant patterns and representations within protein sequences, enabling more informative feature extraction. 2. Feature-Relational Reasoning Network (FRN): In the Global Feature Extraction module of our model, the paper developed a novel FRN that leveraged Graph Neural Networks to determine interactions between pairs of input proteins. The FRN effectively captures the underlying relational information between proteins, contributing to improved PPI predictions. DL-PPI framework demonstrates state-of-the-art performance in the realm of sequence-based PPI prediction.
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Affiliation(s)
- Jiahui Wu
- Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
| | - Bo Liu
- School of Mathematical and Computational Sciences, Massey University, Auckland, 0745, New Zealand.
| | - Jidong Zhang
- Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
| | - Zhihan Wang
- Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
| | - Jianqiang Li
- Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
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23
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Akenroye A, Nopsopon T, Cho L, Moll M, Weiss ST. Lower myostatin and higher MUC1 levels are associated with better response to mepolizumab and omalizumab in asthma: a protein-protein interaction analyses. Respir Res 2023; 24:305. [PMID: 38057814 PMCID: PMC10698971 DOI: 10.1186/s12931-023-02620-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 11/28/2023] [Indexed: 12/08/2023] Open
Abstract
INTRODUCTION Biomarkers are needed to inform the choice of biologic therapy in patients with asthma given the increasing number of biologics. We aimed to identify proteins associated with response to omalizumab and mepolizumab. METHODS Aptamer-based proteomic profiling (SomaScan) was used to assess 1437 proteins from 51 patients with moderate to severe asthma who received omalizumab (n = 29) or mepolizumab (n = 22). Response was defined as the change in asthma-related exacerbations in the 12 months following therapy initiation. All models were adjusted for age, sex, and pre-treatment exacerbation rate. Additionally, body mass index was included in the omalizumab model and eosinophil count in the mepolizumab model. We evaluated the association between molecular signatures and response using negative binomial regression correcting for the false discovery rate (FDR) and gene set enrichment analyses (GSEA) to identify associated pathways. RESULTS Over two-thirds of patients were female. The average age for omalizumab patients was 42 years and 57 years for mepolizumab. At baseline, the average exacerbation rate was 1.5/year for omalizumab and 2.4/year for mepolizumab. Lower levels of LOXL2 (unadjusted p: 1.93 × 10E-05, FDR-corrected: 0.028) and myostatin (unadjusted: 3.87 × 10E-05, FDR-corrected: 0.028) were associated with better response to mepolizumab. Higher levels of CD9 antigen (unadjusted: 5.30 × 10E-07, FDR-corrected: 0.0006) and MUC1 (unadjusted: 1.15 × 10E-06, FDR-corrected: 0.0006) were associated with better response to omalizumab, and LTB4R (unadjusted: 1.12 × 10E-06, FDR-corrected: 0.0006) with worse response. Protein-protein interaction network modeling showed an enrichment of the TNF- and NF-kB signaling pathways for patients treated with mepolizumab and multiple pathways involving MAPK, including the FcER1 pathway, for patients treated with omalizumab. CONCLUSIONS This study provides novel fundamental data on proteins associated with response to mepolizumab or omalizumab in severe asthma and warrants further validation as potential biomarkers for therapy selection.
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Affiliation(s)
- Ayobami Akenroye
- Division of Allergy and Clinical Immunology, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA.
- Channing Division of Network Medicine, Brigham and Women's Hospital, 60 Fenwood Road, BostonBoston, MA, 02115, USA.
| | - Tanawin Nopsopon
- Division of Allergy and Clinical Immunology, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA
| | - Laura Cho
- Division of Allergy and Clinical Immunology, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA
| | - Matthew Moll
- Channing Division of Network Medicine, Brigham and Women's Hospital, 60 Fenwood Road, BostonBoston, MA, 02115, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA
| | - Scott T Weiss
- Channing Division of Network Medicine, Brigham and Women's Hospital, 60 Fenwood Road, BostonBoston, MA, 02115, USA
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24
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Cong H, Liu H, Cao Y, Liang C, Chen Y. Protein-protein interaction site prediction by model ensembling with hybrid feature and self-attention. BMC Bioinformatics 2023; 24:456. [PMID: 38053020 DOI: 10.1186/s12859-023-05592-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Accepted: 11/30/2023] [Indexed: 12/07/2023] Open
Abstract
BACKGROUND Protein-protein interactions (PPIs) are crucial in various biological functions and cellular processes. Thus, many computational approaches have been proposed to predict PPI sites. Although significant progress has been made, these methods still have limitations in encoding the characteristics of each amino acid in sequences. Many feature extraction methods rely on the sliding window technique, which simply merges all the features of residues into a vector. The importance of some key residues may be weakened in the feature vector, leading to poor performance. RESULTS We propose a novel sequence-based method for PPI sites prediction. The new network model, PPINet, contains multiple feature processing paths. For a residue, the PPINet extracts the features of the targeted residue and its context separately. These two types of features are processed by two paths in the network and combined to form a protein representation, where the two types of features are of relatively equal importance. The model ensembling technique is applied to make use of more features. The base models are trained with different features and then ensembled via stacking. In addition, a data balancing strategy is presented, by which our model can get significant improvement on highly unbalanced data. CONCLUSION The proposed method is evaluated on a fused dataset constructed from Dset186, Dset_72, and PDBset_164, as well as the public Dset_448 dataset. Compared with current state-of-the-art methods, the performance of our method is better than the others. In the most important metrics, such as AUPRC and recall, it surpasses the second-best programmer on the latter dataset by 6.9% and 4.7%, respectively. We also demonstrated that the improvement is essentially due to using the ensemble model, especially, the hybrid feature. We share our code for reproducibility and future research at https://github.com/CandiceCong/StackingPPINet .
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Affiliation(s)
- Hanhan Cong
- School of Information Science and Engineering, Shandong Normal University, Jinan, China
- Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology, Jinan, China
| | - Hong Liu
- School of Information Science and Engineering, Shandong Normal University, Jinan, China.
- Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology, Jinan, China.
| | - Yi Cao
- School of Information Science and Engineering, University of Jinan, Jinan, China
- Shandong Provincial Key Laboratory of Network Based Intelligent Computing, Jinan, China
| | - Cheng Liang
- School of Information Science and Engineering, Shandong Normal University, Jinan, China
| | - Yuehui Chen
- School of Information Science and Engineering, University of Jinan, Jinan, China
- Shandong Provincial Key Laboratory of Network Based Intelligent Computing, Jinan, China
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Li G, Luo X, Hu Z, Wu J, Peng W, Liu J, Zhu X. Essential proteins discovery based on dominance relationship and neighborhood similarity centrality. Health Inf Sci Syst 2023; 11:55. [PMID: 37981988 PMCID: PMC10654316 DOI: 10.1007/s13755-023-00252-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 10/13/2023] [Indexed: 11/21/2023] Open
Abstract
Essential proteins play a vital role in development and reproduction of cells. The identification of essential proteins helps to understand the basic survival of cells. Due to time-consuming, costly and inefficient with biological experimental methods for discovering essential proteins, computational methods have gained increasing attention. In the initial stage, essential proteins are mainly identified by the centralities based on protein-protein interaction (PPI) networks, which limit their identification rate due to many false positives in PPI networks. In this study, a purified PPI network is firstly introduced to reduce the impact of false positives in the PPI network. Secondly, by analyzing the similarity relationship between a protein and its neighbors in the PPI network, a new centrality called neighborhood similarity centrality (NSC) is proposed. Thirdly, based on the subcellular localization and orthologous data, the protein subcellular localization score and ortholog score are calculated, respectively. Fourthly, by analyzing a large number of methods based on multi-feature fusion, it is found that there is a special relationship among features, which is called dominance relationship, then, a novel model based on dominance relationship is proposed. Finally, NSC, subcellular localization score, and ortholog score are fused by the dominance relationship model, and a new method called NSO is proposed. In order to verify the performance of NSO, the seven representative methods (ION, NCCO, E_POC, SON, JDC, PeC, WDC) are compared on yeast datasets. The experimental results show that the NSO method has higher identification rate than other methods.
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Affiliation(s)
- Gaoshi Li
- Key Lab of Education Blockchain and Intelligent Technology, Ministry of Education, Guangxi Normal University, Guilin, 541004 China
- Guangxi Key Lab of Multi-source Information Mining & Security, Guangxi Normal University, Guilin, 541004 Guangxi China
- College of Computer Science and Engineering, Guangxi Normal University, Guilin, 541004 Guangxi China
| | - Xinlong Luo
- Key Lab of Education Blockchain and Intelligent Technology, Ministry of Education, Guangxi Normal University, Guilin, 541004 China
- Guangxi Key Lab of Multi-source Information Mining & Security, Guangxi Normal University, Guilin, 541004 Guangxi China
- College of Computer Science and Engineering, Guangxi Normal University, Guilin, 541004 Guangxi China
| | - Zhipeng Hu
- Key Lab of Education Blockchain and Intelligent Technology, Ministry of Education, Guangxi Normal University, Guilin, 541004 China
- Guangxi Key Lab of Multi-source Information Mining & Security, Guangxi Normal University, Guilin, 541004 Guangxi China
- College of Computer Science and Engineering, Guangxi Normal University, Guilin, 541004 Guangxi China
| | - Jingli Wu
- Key Lab of Education Blockchain and Intelligent Technology, Ministry of Education, Guangxi Normal University, Guilin, 541004 China
- Guangxi Key Lab of Multi-source Information Mining & Security, Guangxi Normal University, Guilin, 541004 Guangxi China
- College of Computer Science and Engineering, Guangxi Normal University, Guilin, 541004 Guangxi China
| | - Wei Peng
- Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, 650500 Yunnan China
| | - Jiafei Liu
- Key Lab of Education Blockchain and Intelligent Technology, Ministry of Education, Guangxi Normal University, Guilin, 541004 China
- Guangxi Key Lab of Multi-source Information Mining & Security, Guangxi Normal University, Guilin, 541004 Guangxi China
- College of Computer Science and Engineering, Guangxi Normal University, Guilin, 541004 Guangxi China
| | - Xiaoshu Zhu
- Key Lab of Education Blockchain and Intelligent Technology, Ministry of Education, Guangxi Normal University, Guilin, 541004 China
- Guangxi Key Lab of Multi-source Information Mining & Security, Guangxi Normal University, Guilin, 541004 Guangxi China
- College of Computer Science and Engineering, Guangxi Normal University, Guilin, 541004 Guangxi China
- School of Computer and Information Security & School of Software Engineering, Guilin University of Electronic Science and Technology, Guilin, China
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Wu W, Zheng J, Wang R, Wang Y. Ion channels regulate energy homeostasis and the progression of metabolic disorders: Novel mechanisms and pharmacology of their modulators. Biochem Pharmacol 2023; 218:115863. [PMID: 37863328 DOI: 10.1016/j.bcp.2023.115863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 10/13/2023] [Accepted: 10/16/2023] [Indexed: 10/22/2023]
Abstract
The progression of metabolic diseases, featured by dysregulated metabolic signaling pathways, is orchestrated by numerous signaling networks. Among the regulators, ion channels transport ions across the membranes and trigger downstream signaling transduction. They critically regulate energy homeostasis and pathogenesis of metabolic diseases and are potential therapeutic targets for treating metabolic disorders. Ion channel blockers have been used to treat diabetes for decades by stimulating insulin secretion, yet with hypoglycemia and other adverse effects. It calls for deeper understanding of the largely elusive regulatory mechanisms, which facilitates the identification of new therapeutic targets and safe drugs against ion channels. In the article, we critically assess the two principal regulatory mechanisms, protein-channel interaction and post-translational modification on the activities of ion channels to modulate energy homeostasis and metabolic disorders through multiple novel mechanisms. Moreover, we discuss the multidisciplinary methods that provide the tools for elucidation of the regulatory mechanisms mediating metabolic disorders by ion channels. In terms of translational perspective, the mechanistic analysis of recently validated ion channels that regulate insulin resistance, body weight control, and adverse effects of current ion channel antagonists are discussed in details. Their small molecule modulators serve as promising new drug candidates to combat metabolic disorders.
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Affiliation(s)
- Wenyi Wu
- School of Kinesiology, Shanghai University of Sport, Shanghai 200438, China
| | - Jianan Zheng
- School of Kinesiology, Shanghai University of Sport, Shanghai 200438, China
| | - Ru Wang
- School of Kinesiology, Shanghai University of Sport, Shanghai 200438, China; Shanghai Frontiers Science Research Base of Exercise and Metabolic Health, China
| | - Yibing Wang
- School of Kinesiology, Shanghai University of Sport, Shanghai 200438, China; Shanghai Frontiers Science Research Base of Exercise and Metabolic Health, China.
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Modanwal S, Mishra A, Mishra N. An integrative analysis of GEO data to identify possible therapeutic biomarkers of prostate cancer and targeting potential protein through Zea mays phytochemicals by virtual screening approaches. J Biomol Struct Dyn 2023:1-21. [PMID: 38217083 DOI: 10.1080/07391102.2023.2283163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 11/08/2023] [Indexed: 01/14/2024]
Abstract
Prostate cancer (PC) is a prevalent type of cancer among men. Delaying the treatment of patients with upgraded or upstaged cancer may lead to unmanageable circumstances. The aim of this study is to contribute to the finding of biomarkers that are specific to PC and identify drug candidates derived from plants. The information about cancer is critical for clinicians to make decisions about patient treatment in the era of precision medicine. Advances in genomics technology have opened up new possibilities for identifying genes that are associated with cancer, including PC. This study identifies novel differentially expressed genes for PC. The seven PC microarray datasets were selected from the National Center for Biotechnology Information (NCBI)/Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) were found based on a fold change of |logFC| ≥ 1 and an adjusted p-value of <0.05. The DEGs were further studied using several bioinformatics tools, including STRING, CytoHubba, SRplot, Coremine Medical database, FunRich and GeneMANIA, cBioPortal. The six new potential biomarkers, GAGE2A, GAGE12G, GAGE2E, GAGE13, GAGE12F and CSAG1 were identified. These biomarkers are associated with biological processes (BPs) such as cell division, and gene expression regulation, so these genes may have a crucial role in PC progression and may serve as potential biomarkers for PC. A total of 497 phytochemicals from corn plants have been screened against the target protein and found LTS0176591 as the best lead molecule with docking score of -6.31 kcal/mol. Further, molecular mechanics-generalized born surface area (MM-GBSA), molecular dynamics simulation, principal component analysis (PCA), free energy landscape (FEL) and molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) were carried out to validate the findings.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Shristi Modanwal
- Department of Applied Science, Indian Institute of Information Technology Allahabad, Prayagraj, India
| | - Ashutosh Mishra
- Department of Applied Science, Indian Institute of Information Technology Allahabad, Prayagraj, India
| | - Nidhi Mishra
- Department of Applied Science, Indian Institute of Information Technology Allahabad, Prayagraj, India
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Lampart A, Krowarsch D, Biadun M, Sorensen V, Szymczyk J, Sluzalska K, Wiedlocha A, Otlewski J, Zakrzewska M. Intracellular FGF1 protects cells from apoptosis through direct interaction with p53. Cell Mol Life Sci 2023; 80:311. [PMID: 37783936 PMCID: PMC10545594 DOI: 10.1007/s00018-023-04964-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Revised: 08/28/2023] [Accepted: 09/12/2023] [Indexed: 10/04/2023]
Abstract
Fibroblast growth factor 1 (FGF1) acts by activating specific tyrosine kinase receptors on the cell surface. In addition to this classical mode of action, FGF1 also exhibits intracellular activity. Recently, we found that FGF1 translocated into the cell interior exhibits anti-apoptotic activity independent of receptor activation and downstream signaling. Here, we show that expression of FGF1 increases the survival of cells treated with various apoptosis inducers, but only when wild-type p53 is present. The p53-negative cells were not protected by either ectopically expressed or translocated FGF1. We also confirmed the requirement of p53 for the anti-apoptotic intracellular activity of FGF1 by silencing p53, resulting in loss of the protective effect of FGF1. In contrast, in p53-negative cells, intracellular FGF1 regained its anti-apoptotic properties after transfection with wild-type p53. We also found that FGF1 directly interacts with p53 in cells and that the binding region is located in the DBD domain of p53. We therefore postulate that intracellular FGF1 protects cells from apoptosis by directly interacting with p53.
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Affiliation(s)
- Agata Lampart
- Department of Protein Engineering, Faculty of Biotechnology, University of Wroclaw, Wroclaw, Poland
| | - Daniel Krowarsch
- Department of Protein Biotechnology, Faculty of Biotechnology, University of Wroclaw, Wroclaw, Poland
| | - Martyna Biadun
- Department of Protein Engineering, Faculty of Biotechnology, University of Wroclaw, Wroclaw, Poland
- Department of Protein Biotechnology, Faculty of Biotechnology, University of Wroclaw, Wroclaw, Poland
| | - Vigdis Sorensen
- Advanced Light Microscopy Core Facility, Dept. Core Facilities, Institute for Cancer Research, The Norwegian Radium Hospital, Oslo University Hospital, Montebello, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Montebello, Oslo, Norway
| | - Jakub Szymczyk
- Department of Protein Engineering, Faculty of Biotechnology, University of Wroclaw, Wroclaw, Poland
| | - Katarzyna Sluzalska
- Department of Protein Engineering, Faculty of Biotechnology, University of Wroclaw, Wroclaw, Poland
| | - Antoni Wiedlocha
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Montebello, Oslo, Norway
- Department of Molecular Cell Biology, Institute for Cancer Research, Oslo University Hospital, Montebello, Oslo, Norway
| | - Jacek Otlewski
- Department of Protein Engineering, Faculty of Biotechnology, University of Wroclaw, Wroclaw, Poland
| | - Malgorzata Zakrzewska
- Department of Protein Engineering, Faculty of Biotechnology, University of Wroclaw, Wroclaw, Poland.
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Hoque RA, Yadav M, Yadava U, Rai N, Negi S, Yadav HS. Active site determination of novel plant versatile peroxidase extracted from Citrus sinensis and bioconversion of β-naphthol. 3 Biotech 2023; 13:345. [PMID: 37719748 PMCID: PMC10501043 DOI: 10.1007/s13205-023-03758-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 08/20/2023] [Indexed: 09/19/2023] Open
Abstract
A ligninolytic peroxidase called versatile peroxidase, VP, (EC 1.11.1.16) is an iron-containing metalloenzyme. The most distinctive feature of this enzyme is its composite molecular framework, which combines lignin peroxidase's capacity to oxidize compounds with high-redox potential with manganese peroxidase's capacity to oxidize Mn2+ to Mn3+. In this study, we have extracted amino acid sequences from the Citrus sinensis source and subjected them to various computation tools to visualize the insight secondary and 3D structure, physicochemical properties, and validation of the structure which have not been studied so far to further investigate the catalytic efficiency and effectiveness of VP. The binding energies of HEME and HEME C (HEC) ligands with produced PDB (6rqf.1. A) have been also assessed, analyzed, and confirmed utilizing AutoDock. Binding energies were calculated using the AutoDock and validated by MD simulation using SCHRODINGER DESMOND. Most stable confirmation was achieved through a protein-ligand interaction study. Bio-technological use of VP in the biotransformation of β-naphthol has also been studied. The findings in the current study will have a substantial impact on proteomics, biochemistry, biotechnology, and possible uses of versatile peroxidase in the bio-remediation of different toxic organic compounds. Supplementary Information The online version contains supplementary material available at 10.1007/s13205-023-03758-x.
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Affiliation(s)
- Rohida Amin Hoque
- Department of Chemistry, North Eastern Regional Institute of Science and Technology, Nirjuli, Itanagar, AP 791109 India
| | - Meera Yadav
- Department of Chemistry, North Eastern Regional Institute of Science and Technology, Nirjuli, Itanagar, AP 791109 India
| | - Umesh Yadava
- Department of Physics, Deen Dayal Upadhyaya Gorakhpur University, Gorakhpur, 273009 India
| | - Nivedita Rai
- Department of Chemistry, North Eastern Regional Institute of Science and Technology, Nirjuli, Itanagar, AP 791109 India
| | - Shivani Negi
- Department of Physics, Deen Dayal Upadhyaya Gorakhpur University, Gorakhpur, 273009 India
| | - Hardeo Singh Yadav
- Department of Chemistry, North Eastern Regional Institute of Science and Technology, Nirjuli, Itanagar, AP 791109 India
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30
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Yu C, Huang L. New advances in cross-linking mass spectrometry toward structural systems biology. Curr Opin Chem Biol 2023; 76:102357. [PMID: 37406423 DOI: 10.1016/j.cbpa.2023.102357] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 06/02/2023] [Accepted: 06/04/2023] [Indexed: 07/07/2023]
Abstract
Elucidating protein-protein interaction (PPI) networks and their structural features within cells is central to understanding fundamental biology and associations of cell phenotypes with human pathologies. Owing to technological advancements during the last decade, cross-linking mass spectrometry (XL-MS) has become an enabling technology for delineating interaction landscapes of proteomes as they exist in living systems. XL-MS is unique due to its capability to simultaneously capture PPIs from native environments and uncover interaction contacts though identification of cross-linked peptides, thereby permitting the determination of both identity and connectivity of PPIs in cells. In combination with high resolution structural tools such as cryo-electron microscopy and AI-assisted prediction, XL-MS has contributed significantly to elucidating architectures of large protein assemblies. This review highlights the latest developments in XL-MS technologies and their applications in proteome-wide analysis to advance structural systems biology.
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Affiliation(s)
- Clinton Yu
- Department of Physiology & Biophysics, University of California, Irvine, Irvine, CA 92697, USA
| | - Lan Huang
- Department of Physiology & Biophysics, University of California, Irvine, Irvine, CA 92697, USA.
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Li P, Tian Y, Shang Q, Tang C, Hou Z, Li Y, Cao L, Xue S, Bian J, Luo C, Wu D, Li Z, Ding H. Discovery of a highly potent NPAS3 heterodimer inhibitor by covalently modifying ARNT. Bioorg Chem 2023; 139:106676. [PMID: 37352720 DOI: 10.1016/j.bioorg.2023.106676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 06/01/2023] [Accepted: 06/09/2023] [Indexed: 06/25/2023]
Abstract
Neuronal PAS domain protein 3 (NPAS3), a basic helix-loop-helix PER-ARNT-SIM (bHLH-PAS) family member, is a pivotal transcription factor in neuronal regeneration, development, and related diseases, regulating the expression of downstream genes. Despite several modulators of certain bHLH-PAS family proteins being identified, the NPAS3-targeted compound has yet to be reported. Herein, we discovered a hit compound BI-78D3 that directly blocks the NPAS3-ARNT heterodimer formation by covalently binding to the aryl hydrocarbon receptor nuclear translocator (ARNT) subunit. Further optimization based on the hit scaffold yielded a highly potent Compound 6 with a biochemical EC50 value of 282 ± 61 nM and uncovered the 5-nitrothiazole-2-sulfydryl as a cysteine-targeting covalent warhead. Compound 6 effectively down-regulated NPAS3's transcriptional function by disrupting the interface of NPAS3-ARNT complexes at cellular level. In conclusion, our study identifies the 5-nitrothiazole-2-sulfydryl as a cysteine-modified warhead and provides a strategy that blocks the NPAS3-ARNT heterodimerization by covalently conjugating ARNT Cys336 residue. Compound 6 may serve as a promising chemical probe for exploring NPAS3-related physiological functions.
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Affiliation(s)
- Peizhuo Li
- School of Chinese Materia Medica, Nanjing University of Chinese Medicine, Nanjing 210023, China; State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China
| | - Yucheng Tian
- Jiangsu Key Laboratory of Drug Design and Optimization, Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Qinghong Shang
- Helmholtz International Lab, State Key Laboratory of Microbial Technology, Shandong University, Qingdao 266237, China
| | - Cailing Tang
- School of Chinese Materia Medica, Nanjing University of Chinese Medicine, Nanjing 210023, China; State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China
| | - Zeng Hou
- School of Pharmaceutical Science and Technology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310053, China
| | - Yuanqing Li
- School of Chinese Materia Medica, Nanjing University of Chinese Medicine, Nanjing 210023, China; State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China
| | - Liyuan Cao
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Shengyu Xue
- School of Chinese Materia Medica, Nanjing University of Chinese Medicine, Nanjing 210023, China; State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China
| | - Jinlei Bian
- Jiangsu Key Laboratory of Drug Design and Optimization, Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Cheng Luo
- School of Chinese Materia Medica, Nanjing University of Chinese Medicine, Nanjing 210023, China; State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China
| | - Dalei Wu
- Helmholtz International Lab, State Key Laboratory of Microbial Technology, Shandong University, Qingdao 266237, China.
| | - Zhiyu Li
- Jiangsu Key Laboratory of Drug Design and Optimization, Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China.
| | - Hong Ding
- State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China.
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Yang D, Han F, Cai J, Sun H, Wang F, Jiang M, Zhang M, Yuan M, Zhou W, Li H, Yang L, Bai Y, Xiao L, Dong H, Cheng Q, Mao H, Zhou L, Wang R, Li Y, Nie H. N-glycosylation by N-acetylglucosaminyltransferase IVa enhances the interaction of integrin β1 with vimentin and promotes hepatocellular carcinoma cell motility. Biochim Biophys Acta Mol Cell Res 2023; 1870:119513. [PMID: 37295747 DOI: 10.1016/j.bbamcr.2023.119513] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 06/02/2023] [Accepted: 06/05/2023] [Indexed: 06/12/2023]
Abstract
N-glycosylation has been revealed to be tightly associated with cancer metastasis. As a key transferase that catalyzes the formation of β1,4 N-acetylglucosamine (β1,4GlcNAc) branches on the mannose core of N-glycans, N-acetylglucosaminyltransferase IVa (GnT-IVa) has been reported to be involved in hepatocellular carcinoma (HCC) metastasis by forming N-glycans; however, the underlying mechanisms are largely unknown. In the current study, we found that GnT-IVa was upregulated in HCC tissues and positively correlated with worse outcomes in HCC patients. We found that GnT-IVa could promote tumor growth in mice; notably, this effect was attenuated after mutating the enzymatic site (D445A) of GnT-IVa, suggesting that GnT-IVa regulated HCC progression by forming β1,4GlcNAc branches. To mechanistically investigate the role of GnT-IVa in HCC, we conducted GSEA and GO functional analysis as well as in vitro experiments. The results showed that GnT-IVa could enhance HCC cell migration, invasion and adhesion ability and increase β1,4GlcNAc branch glycans on integrin β1 (ITGB1), a tumor-associated glycoprotein that is closely involved in cell motility by interacting with vimentin. Interruption of β1,4GlcNAc branch glycan modification on ITGB1 could suppress the interaction of ITGB1 with vimentin and inhibit cell motility. These results revealed that GnT-IVa could promote HCC cell motility by affecting the biological functions of ITGB1 through N-glycosylation. In summary, our results revealed that GnT-IVa is highly expressed in HCC and can form β1,4GlcNAc branches on ITGB1, which are essential for interactions with vimentin to promote HCC cell motility. These findings not only proposed a novel mechanism for GnT-IVa in HCC progression but also revealed the significance of N-glycosylation on ITGB1 during the process, which may provide a novel target for future HCC therapy.
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Affiliation(s)
- Depeng Yang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Fang Han
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Jialing Cai
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Handi Sun
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Fengyou Wang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Meiyi Jiang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Mengmeng Zhang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Mengfan Yuan
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Wenyang Zhou
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Huaxin Li
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Lijun Yang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Yan Bai
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Lixing Xiao
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Haiyang Dong
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Qixiang Cheng
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Haoyu Mao
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Lu Zhou
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Ruonan Wang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Yu Li
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China.
| | - Huan Nie
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China.
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Shi Z, Gao X, Zhang W, Chen B, Wang M, Liao K, Wang Z, Ren L, Zhai Y, Qiu Y, Wang X, Lin Y. Novel Bimolecular Fluorescence Complementation (BiFC) Assay for Visualization of the Protein-Protein Interactions and Cellular Protein Complex Localizations. Mol Biotechnol 2023:10.1007/s12033-023-00860-6. [PMID: 37751129 DOI: 10.1007/s12033-023-00860-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Accepted: 08/16/2023] [Indexed: 09/27/2023]
Abstract
Investigations of protein-protein interactions (PPIs) are of paramount importance for comprehending cellular processes within biological systems. The bimolecular fluorescence complementation (BiFC) assay presents a convenient methodology for visualizing PPIs within live cells. While a range of fluorescent proteins have been introduced into the BiFC system, there is a growing demand for new fluorescent proteins to accommodate the expanding requirements of researchers. This study describes the introduction of Tagged blue fluorescent protein 2 (TagBFP2) into the BiFC assay to verify the interaction between two proteins, with Enhanced yellow fluorescent protein (EYFP) employed as a positive control. Both fluorescent proteins demonstrated optimal performance in this study. Compared to EYFP, the BiFC system utilizing TagBFP2 yielded a higher signal-to-noise ratio, which facilitated differentiation of the signal of PPIs from noise and enabled employment of other fluorescent proteins within the BiFC assay. Notably, the utilization of a fluorescent secondary antibody in immunofluorescence applications or the tagging of an interest protein with a fluorescent protein occupied the green or yellow channel. Overall, the present article introduces a BiFC assay that is highly straightforward, reliable, and replicable, with the ability to be completed within 1 week. This method requires neither expensive instrumentation nor technical skills of a high order.
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Affiliation(s)
- Zhonggang Shi
- Brain Injury Center, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, No. 160 Pujian Road, Pudong District, Shanghai, 200127, People's Republic of China
- Shanghai Cancer Institute, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, No. 160 Pujian Road, Pudong District, Shanghai, 200127, People's Republic of China
| | - Xing Gao
- Department of Medical Oncology, Guangxi Medical University Cancer Hospital, Nanning, 530021, Guangxi, People's Republic of China
| | - Wenrui Zhang
- Brain Injury Center, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, No. 160 Pujian Road, Pudong District, Shanghai, 200127, People's Republic of China
- Shanghai Cancer Institute, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, No. 160 Pujian Road, Pudong District, Shanghai, 200127, People's Republic of China
| | - Binghong Chen
- Brain Injury Center, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, No. 160 Pujian Road, Pudong District, Shanghai, 200127, People's Republic of China
| | - Mengying Wang
- Brain Injury Center, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, No. 160 Pujian Road, Pudong District, Shanghai, 200127, People's Republic of China
- Shanghai Cancer Institute, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, No. 160 Pujian Road, Pudong District, Shanghai, 200127, People's Republic of China
| | - Keman Liao
- Brain Injury Center, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, No. 160 Pujian Road, Pudong District, Shanghai, 200127, People's Republic of China
| | - Zhihan Wang
- Department of Neurosurgery, Shanghai Pudong Hospital, Fudan University, Shanghai, 201399, People's Republic of China
| | - Li Ren
- Department of Neurosurgery, Shanghai Pudong Hospital, Fudan University, Shanghai, 201399, People's Republic of China
| | - Yujia Zhai
- Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Yueyang Road 320, Shanghai, 200031, China
| | - Yongming Qiu
- Brain Injury Center, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, No. 160 Pujian Road, Pudong District, Shanghai, 200127, People's Republic of China
| | - Xuhui Wang
- Department of Neurosurgery, Xinhua Hospital Affiliated to Shanghai JiaoTong University School of Medicine, No. 1665 Kongjiang Road, Shanghai, 200092, People's Republic of China.
- Department of Neurosurgery, Chongming Hospital Affiliated to Shanghai University of Medicine and Health Sciences, Shanghai, 202150, People's Republic of China.
| | - Yingying Lin
- Brain Injury Center, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, No. 160 Pujian Road, Pudong District, Shanghai, 200127, People's Republic of China.
- Shanghai Cancer Institute, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, No. 160 Pujian Road, Pudong District, Shanghai, 200127, People's Republic of China.
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Kailasam Natesan V, Balaraman S, KuppannaGounder Pitchaimuthu E. Insilico design of an allosteric modulator targeting the protein-protein interaction site of 3 Phosphoinositide dependent Kinase-1: design, synthesis and biological activity. In Silico Pharmacol 2023; 11:26. [PMID: 37767119 PMCID: PMC10519888 DOI: 10.1007/s40203-023-00160-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 08/24/2023] [Indexed: 09/29/2023] Open
Abstract
The signalling pathways in human cells mostly rely on protein-protein interactions (PPI) for their function. Such a PPI site in 3 Phosphoinositide dependent Kinase-1 (PDK1) is targeted to design the small molecule modulators. Based on the hotspot residues in its PPI site, a pharmacophore with seven different features was developed and screened against 2.9 million lead like compounds in Zinc database. A phthalazine derivative was identified as a potent allosteric inhibitor through virtual screening, molecular docking and 100 ns dynamics simulations. The modified hit possessed hydrogen bonds with Lys115, Arg131, Thr148, Glu150 as well as pi-pi stacking interactions with Phe157 which are the key residues in the PIF pocket of PDK1. Comparison between the free energy profiles by metadynamics simulation with the presence and absence of the modified ligand (MH) in the binding pocket indicates that the binding of MH enhances the hinge motion making PDK1 to adopt open conformation also and stabilizes the fluctuation of the end-to-end distance in αB helix of PDK1. The modified hit compound was synthesized, characterized and found to be cytotoxic to cancerous cells that are rich in PDK1 expression. These results propose that MH can serve as a new scaffold template for the design of novel drugs targeting PDK1 as well as promising allosteric regulator of PDK1 targeting its protein-protein interface. Supplementary Information The online version contains supplementary material available at 10.1007/s40203-023-00160-6.
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Ohue M. MEGADOCK-on-Colab: an easy-to-use protein-protein docking tool on Google Colaboratory. BMC Res Notes 2023; 16:229. [PMID: 37737185 PMCID: PMC10515421 DOI: 10.1186/s13104-023-06505-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 09/06/2023] [Indexed: 09/23/2023] Open
Abstract
MOTIVATION Since the advent of ColabFold, numerous software packages have been provided with Google Colaboratory-compatible ipynb files, allowing users to effortlessly test and reproduce results without the need for local installation or configuration. MEGADOCK, a protein-protein docking tool, is particularly well-suited for Google Colaboratory due to its lightweight computations and GPU acceleration capabilities. To increase accessibility and promote widespread use, it is crucial to provide a computing environment compatible with Google Colaboratory. RESULTS In this study, we report the development of a Google Colaboratory environment for running our protein-protein docking software, MEGADOCK. We provide a comprehensive ipynb file, including the compilation of MEGADOCK with the FFTW library installation on Colaboratory, the introduction of related tools using PyPI/apt, and the execution and visualization of docking structures. This streamlined environment enables users to visualize docking structures with just one click. The code is available under a CC-BY NC 4.0 license from https://github.com/ohuelab/MEGADOCK-on-Colab .
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Affiliation(s)
- Masahito Ohue
- Department of Computer Science, School of Computing, Tokyo Institute of Technology, 4259-G3-56 Nagatsutacho, Midori-ku, Yokohama, Kanagawa, 226-8501, Japan.
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Vennila KN, Elango KP. Insilico molecular modelling to identify PDK-1 targeting agents based on its protein-protein docking interaction. J Biomol Struct Dyn 2023:1-12. [PMID: 37646644 DOI: 10.1080/07391102.2023.2252080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 08/18/2023] [Indexed: 09/01/2023]
Abstract
PDK1, an attractive cancer target that downstreams 23 other kinases towards cell growth, survival and metabolism has gaining attention due to allosteric effect of ligands bound to it. Generally, the drug design strategy using pharmacophores is either a single protein structure or ensemble or ligand-based. Apart from these methods, yet another new approach of protein-protein docking with state of art computational tool like Schrodinger Suite to generate pharmacophores based on the interacting partners of the protein is proposed in this work. The structure-based pharmacophoric features were picked up from docking the ten interacting partners of PDK1 and screened against the Enamine libraries containing protein-protein interacting compound collection, advanced, protein mimetic and allosteric compounds. High throughput virtual screening against the PIF pocket of PDK1 yields an indole scaffold. The identified indole derivative is proposed to be a strong activator that binds in the protein-protein interaction site of PDK1 which was further confirmed by molecular metadynamics simulations, free energy surface analysis and MM-GBSA calculations. Thus, the pharmacophores generated by the interacting proteins for PPI can facilitate the virtual screening in structure-based drug discovery of similar therapeutic targets.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Kailasam N Vennila
- The Gandhigram Rural Institute-Deemed to be University, Gandhigram, Tamil Nadu, India
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Manyilov VD, Ilyinsky NS, Nesterov SV, Saqr BMGA, Dayhoff GW, Zinovev EV, Matrenok SS, Fonin AV, Kuznetsova IM, Turoverov KK, Ivanovich V, Uversky VN. Chaotic aging: intrinsically disordered proteins in aging-related processes. Cell Mol Life Sci 2023; 80:269. [PMID: 37634152 DOI: 10.1007/s00018-023-04897-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Revised: 07/03/2023] [Accepted: 07/24/2023] [Indexed: 08/29/2023]
Abstract
The development of aging is associated with the disruption of key cellular processes manifested as well-established hallmarks of aging. Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) have no stable tertiary structure that provide them a power to be configurable hubs in signaling cascades and regulate many processes, potentially including those related to aging. There is a need to clarify the roles of IDPs/IDRs in aging. The dataset of 1702 aging-related proteins was collected from established aging databases and experimental studies. There is a noticeable presence of IDPs/IDRs, accounting for about 36% of the aging-related dataset, which is however less than the disorder content of the whole human proteome (about 40%). A Gene Ontology analysis of the used here aging proteome reveals an abundance of IDPs/IDRs in one-third of aging-associated processes, especially in genome regulation. Signaling pathways associated with aging also contain IDPs/IDRs on different hierarchical levels, revealing the importance of "structure-function continuum" in aging. Protein-protein interaction network analysis showed that IDPs present in different clusters associated with different aging hallmarks. Protein cluster with IDPs enrichment has simultaneously high liquid-liquid phase separation (LLPS) probability, "nuclear" localization and DNA-associated functions, related to aging hallmarks: genomic instability, telomere attrition, epigenetic alterations, and stem cells exhaustion. Intrinsic disorder, LLPS, and aggregation propensity should be considered as features that could be markers of pathogenic proteins. Overall, our analyses indicate that IDPs/IDRs play significant roles in aging-associated processes, particularly in the regulation of DNA functioning. IDP aggregation, which can lead to loss of function and toxicity, could be critically harmful to the cell. A structure-based analysis of aging and the identification of proteins that are particularly susceptible to disturbances can enhance our understanding of the molecular mechanisms of aging and open up new avenues for slowing it down.
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Affiliation(s)
- Vladimir D Manyilov
- Research Center for Molecular Mechanisms of Aging and Age-Related Diseases, Moscow Institute of Physics and Technology, Institutskiy Pereulok, 9, Dolgoprudny, 141700, Russia
| | - Nikolay S Ilyinsky
- Research Center for Molecular Mechanisms of Aging and Age-Related Diseases, Moscow Institute of Physics and Technology, Institutskiy Pereulok, 9, Dolgoprudny, 141700, Russia.
| | - Semen V Nesterov
- Research Center for Molecular Mechanisms of Aging and Age-Related Diseases, Moscow Institute of Physics and Technology, Institutskiy Pereulok, 9, Dolgoprudny, 141700, Russia
- Institute of Cytology, Russian Academy of Sciences, Saint Petersburg, 194064, Russia
| | - Baraa M G A Saqr
- Research Center for Molecular Mechanisms of Aging and Age-Related Diseases, Moscow Institute of Physics and Technology, Institutskiy Pereulok, 9, Dolgoprudny, 141700, Russia
| | - Guy W Dayhoff
- Department of Chemistry, University of South Florida, Tampa, FL, USA
| | - Egor V Zinovev
- Research Center for Molecular Mechanisms of Aging and Age-Related Diseases, Moscow Institute of Physics and Technology, Institutskiy Pereulok, 9, Dolgoprudny, 141700, Russia
| | - Simon S Matrenok
- Research Center for Molecular Mechanisms of Aging and Age-Related Diseases, Moscow Institute of Physics and Technology, Institutskiy Pereulok, 9, Dolgoprudny, 141700, Russia
| | - Alexander V Fonin
- Institute of Cytology, Russian Academy of Sciences, Saint Petersburg, 194064, Russia
| | - Irina M Kuznetsova
- Institute of Cytology, Russian Academy of Sciences, Saint Petersburg, 194064, Russia
| | | | - Valentin Ivanovich
- Research Center for Molecular Mechanisms of Aging and Age-Related Diseases, Moscow Institute of Physics and Technology, Institutskiy Pereulok, 9, Dolgoprudny, 141700, Russia
| | - Vladimir N Uversky
- Research Center for Molecular Mechanisms of Aging and Age-Related Diseases, Moscow Institute of Physics and Technology, Institutskiy Pereulok, 9, Dolgoprudny, 141700, Russia.
- Department of Molecular Medicine and USF Health Byrd Alzheimer's Research Institute, Morsani College of Medicine, University of South Florida, 12901 Bruce B. Downs Blvd., MDC07, Tampa, FL, 33612, USA.
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Ozger ZB. A robust protein language model for SARS-CoV-2 protein-protein interaction network prediction. Artif Intell Med 2023; 142:102574. [PMID: 37316102 DOI: 10.1016/j.artmed.2023.102574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 04/17/2023] [Accepted: 04/27/2023] [Indexed: 06/16/2023]
Abstract
Protein-protein interaction is one of the ways viruses interact with their hosts. Therefore, identifying protein interactions between viruses and hosts helps explain how virus proteins work, how they replicate, and how they cause disease. SARS-CoV-2 is a new type of virus that emerged from the coronavirus family in 2019 and caused a worldwide pandemic. Detection of human proteins interacting with this novel virus strain plays an important role in monitoring the cellular process of virus-associated infection. Within the scope of the study, a natural language processing-based collective learning method is proposed for the prediction of potential SARS-CoV-2-human PPIs. Protein language models were obtained with the prediction-based word2Vec and doc2Vec embedding methods and the frequency-based tf-idf method. Known interactions were represented by proposed language models and traditional feature extraction methods (conjoint triad and repeat pattern), and their performances were compared. The interaction data were trained with support vector machine, artificial neural network (ANN), k-nearest neighbor (KNN), naive Bayes (NB), decision tree (DT), and ensemble algorithms. Experimental results show that protein language models are a promising protein representation method for protein-protein interaction prediction. The term frequency-inverse document frequency-based language model performed the SARS-CoV-2 protein-protein interaction estimation with an error of 1.4%. Additionally, the decisions of high-performing learning models for different feature extraction methods were combined with a collective voting approach to make new interaction predictions. For 10,000 human proteins, 285 new potential interactions were predicted, with models combining decisions.
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Affiliation(s)
- Zeynep Banu Ozger
- Department of Computer Engineering, Sutcu Imam University, 46040, Kahramanmaras, Turkey.
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Inoue S, Ikeda Y, Fujiyama S, Ueda T, Abe Y. Oligomeric state of the N-terminal domain of DnaT for replication restart in Escherichia coli. Biochim Biophys Acta Proteins Proteom 2023:140929. [PMID: 37328019 DOI: 10.1016/j.bbapap.2023.140929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 06/09/2023] [Accepted: 06/12/2023] [Indexed: 06/18/2023]
Abstract
DNA replication stops when chemical or physical damage occurs to the DNA. Repairing genomic DNA and reloading the replication helicase are crucial steps for restarting DNA replication. The Escherichia coli primosome is a complex of proteins and DNA responsible for reloading the replication helicase DnaB. DnaT, a protein found in the primosome complex, contains two functional domains. The C-terminal domain (89-179) forms an oligomeric complex with single-stranded DNA. Although the N-terminal domain (1-88) forms an oligomer, the specific residues responsible for this oligomeric structure have not yet been identified. In this study, we proposed that the N-terminal domain of DnaT has a dimeric antitoxin structure based on its primary sequence. Based on the proposed model, we confirmed the site of oligomerization in the N-terminal domain of DnaT through site-directed mutagenesis. The molecular masses and thermodynamic stabilities of the site-directed mutants located at the dimer interface, namely Phe42, Tyr43, Leu50, Leu53, and Leu54, were found to be lower than those of the wild-type. Moreover, we observed a decrease in the molecular masses of the V10S and F35S mutants compared to the wild-type DnaT. NMR analysis of the V10S mutant revealed that the secondary structure of the N-terminal domain of DnaT was consistent with the proposed model. Additionally, we have demonstrated that the stability of the oligomer formed by the N-terminal domain of DnaT is crucial for its function. Based on these findings, we propose that the DnaT oligomer plays a role in replication restart in Escherichia coli.
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Affiliation(s)
- Shogo Inoue
- Department of Protein Structure, Function and Design, Graduate School of Pharmaceutical Sciences, Kyushu University, Fukuoka 812-8582, Japan
| | - Yohei Ikeda
- Department of Protein Structure, Function and Design, Graduate School of Pharmaceutical Sciences, Kyushu University, Fukuoka 812-8582, Japan
| | - Saki Fujiyama
- Department of Protein Structure, Function and Design, Graduate School of Pharmaceutical Sciences, Kyushu University, Fukuoka 812-8582, Japan
| | - Tadashi Ueda
- Department of Protein Structure, Function and Design, Graduate School of Pharmaceutical Sciences, Kyushu University, Fukuoka 812-8582, Japan
| | - Yoshito Abe
- Department of Protein Structure, Function and Design, Graduate School of Pharmaceutical Sciences, Kyushu University, Fukuoka 812-8582, Japan; Department of Pharmaceutical Sciences, School of Pharmacy at Fukuoka, International University of Health and Welfare, Okawa 831-8501, Japan.
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40
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Bhatnagar P, Bajpai P, Shrinet J, Kaja MK, Chandele A, Sitaraman R. Prediction of human protein interactome of dengue virus non-structural protein 5 (NS5) and its downstream immunological implications. 3 Biotech 2023; 13:180. [PMID: 37193327 PMCID: PMC10182223 DOI: 10.1007/s13205-023-03569-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 04/19/2023] [Indexed: 05/18/2023] Open
Abstract
The non-structural protein 5 (NS5) is the most conserved protein among flaviviruses, a family that includes the dengue virus. It functions both as an RNA-dependent RNA polymerase and an RNA-methyltransferase and is therefore essential for the replication of viral RNA. The discovery that dengue virus NS5 protein (DENV-NS5) can also localize to the nucleus has resulted in renewed interest in its potential roles at the host-virus interface. In this study, we have used two complementary computational approaches in parallel - one based on linear motifs (ELM) and another based on tertiary structure of the protein (DALI) - to predict the host proteins that DENV-NS5 might interact with. Of the 42 human proteins predicted by both these methods, 34 are novel. Pathway analysis of these 42 human proteins shows that they are involved in key host cellular processes related to cell cycle regulation, proliferation, protein degradation, apoptosis, and immune responses. A focused analysis of transcription factors that directly interact with the predicted DENV-NS5 interacting proteins was performed, followed by the identification of downstream genes that are differentially expressed after dengue infection using previously published RNA-seq data. Our study provides unique insights into the DENV-NS5 interaction network and delineates mechanisms whereby DENV-NS5 could impact the host-virus interface. The novel interactors identified in this study could be potentially targeted by NS5 to modulate the host cellular environment in general, and the immune response in particular, thereby extending the role of DENV-NS5 beyond its known enzymatic functions. Supplementary Information The online version contains supplementary material available at 10.1007/s13205-023-03569-0.
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Affiliation(s)
- Priya Bhatnagar
- Department of Biotechnology, TERI School of Advanced Studies, New Delhi, India
- ICGEB-Emory Vaccine Centre, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India
| | - Prashant Bajpai
- ICGEB-Emory Vaccine Centre, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India
| | - Jatin Shrinet
- Department of Biological Science, Florida State University, Tallahassee, FL 32306 USA
| | - Murali Krishna Kaja
- ICGEB-Emory Vaccine Centre, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India
- Department of Pediatrics and Emory Vaccine Centre, Emory University School of Medicine, Atlanta, GA USA
| | - Anmol Chandele
- ICGEB-Emory Vaccine Centre, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India
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Leblanc S, Brunet MA, Jacques JF, Lekehal AM, Duclos A, Tremblay A, Bruggeman-Gascon A, Samandi S, Brunelle M, Cohen AA, Scott MS, Roucou X. Newfound Coding Potential of Transcripts Unveils Missing Members of Human Protein Communities. Genomics Proteomics Bioinformatics 2023; 21:515-534. [PMID: 36183975 PMCID: PMC10787177 DOI: 10.1016/j.gpb.2022.09.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 08/10/2022] [Accepted: 09/26/2022] [Indexed: 06/16/2023]
Abstract
Recent proteogenomic approaches have led to the discovery that regions of the transcriptome previously annotated as non-coding regions [i.e., untranslated regions (UTRs), open reading frames overlapping annotated coding sequences in a different reading frame, and non-coding RNAs] frequently encode proteins, termed alternative proteins (altProts). This suggests that previously identified protein-protein interaction (PPI) networks are partially incomplete because altProts are not present in conventional protein databases. Here, we used the proteogenomic resource OpenProt and a combined spectrum- and peptide-centric analysis for the re-analysis of a high-throughput human network proteomics dataset, thereby revealing the presence of 261 altProts in the network. We found 19 genes encoding both an annotated (reference) and an alternative protein interacting with each other. Of the 117 altProts encoded by pseudogenes, 38 are direct interactors of reference proteins encoded by their respective parental genes. Finally, we experimentally validate several interactions involving altProts. These data improve the blueprints of the human PPI network and suggest functional roles for hundreds of altProts.
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Affiliation(s)
- Sébastien Leblanc
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada; PROTEO, Quebec Network for Research on Protein Function, Structure, and Engineering, Quebec City, QC G1V 0A6, Canada
| | - Marie A Brunet
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada; PROTEO, Quebec Network for Research on Protein Function, Structure, and Engineering, Quebec City, QC G1V 0A6, Canada
| | - Jean-François Jacques
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada; PROTEO, Quebec Network for Research on Protein Function, Structure, and Engineering, Quebec City, QC G1V 0A6, Canada
| | - Amina M Lekehal
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada; PROTEO, Quebec Network for Research on Protein Function, Structure, and Engineering, Quebec City, QC G1V 0A6, Canada
| | - Andréa Duclos
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada
| | - Alexia Tremblay
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada
| | - Alexis Bruggeman-Gascon
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada
| | - Sondos Samandi
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada; PROTEO, Quebec Network for Research on Protein Function, Structure, and Engineering, Quebec City, QC G1V 0A6, Canada
| | - Mylène Brunelle
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada; PROTEO, Quebec Network for Research on Protein Function, Structure, and Engineering, Quebec City, QC G1V 0A6, Canada
| | - Alan A Cohen
- Department of Family Medicine, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
| | - Michelle S Scott
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada
| | - Xavier Roucou
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada; PROTEO, Quebec Network for Research on Protein Function, Structure, and Engineering, Quebec City, QC G1V 0A6, Canada.
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42
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Sunny S, Prakash PB, Gopakumar G, Jayaraj PB. DeepBindPPI: Protein-Protein Binding Site Prediction Using Attention Based Graph Convolutional Network. Protein J 2023:10.1007/s10930-023-10121-9. [PMID: 37198346 DOI: 10.1007/s10930-023-10121-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/25/2023] [Indexed: 05/19/2023]
Abstract
Due to the importance of protein-protein interactions in defence mechanism of living body, attempts were made to investigate its attributes, including, but not limited to, binding affinity, and binding region. Contemporary strategies for binding site prediction largely resort to deep learning techniques but turned out to be low precision models. As laboratory experiments for drug discovery tasks utilize this information, increased false positives devalue the computational methods. This emphasize the need to develop enhanced strategies. DeepBindPPI employs deep learning technique to predict the binding regions of proteins, particularly antigen-antibody interaction sites. The results obtained are applied in a docking environment to confirm their correctness. An integration of graph convolutional network with attention mechanism predicts interacting amino acids with improved precision. The model learns the determining factors in interaction from a general pool of proteins and is then fine-tuned using antigen-antibody data. Comparison of the proposed method with existing techniques shows that the developed model has comparable performance. The use of a separate spatial network clearly improved the precision of the proposed method from 0.4 to 0.5. An attempt to utilize the interface information for docking using the HDOCK server gives promising results, with high-quality structures appearing in the top10 ranks.
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Affiliation(s)
- Sharon Sunny
- Department of CSE, National Institute of Technology, Calicut, Kerala, 673601, India.
| | | | - G Gopakumar
- Department of CSE, National Institute of Technology, Calicut, Kerala, 673601, India
| | - P B Jayaraj
- Department of CSE, National Institute of Technology, Calicut, Kerala, 673601, India
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Koch J, Scheps D, Gunne M, Boscheinen O, Frech C. Effect of salt modulators on the elution behavior of insulin and the separation of product-related impurities in reversed-phase chromatography. J Chromatogr B Analyt Technol Biomed Life Sci 2023; 1224:123735. [PMID: 37182410 DOI: 10.1016/j.jchromb.2023.123735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 04/25/2023] [Accepted: 04/28/2023] [Indexed: 05/16/2023]
Abstract
In this work, the effect of the salt modulators potassium chloride, ammonium chloride, ammonium sulfate, and potassium sulfate on the elution behavior of insulin in reversed-phase chromatography with ethanol as the organic modifier was investigated. Without the addition of salt modulators, insulin shows the formation of multiple peaks under non-linear loading conditions, presumably due to an aggregate formation equilibrium. Flow rate and temperature did not influence the appearance of multiple peaks. The addition of chloride and sulfate salt modulators changed the monomer-multimer equilibrium, and multi-peak formation no longer occurred. Chloride salts induce a Langmuirian elution behavior, whereas sulfate salts induce additional insulin-insulin interactions resulting in an anti-Langmuirian elution behavior. The elution behavior can be influenced by the combination of both chloride and sulfate salts and by varying the concentration ratio. The separation with respect to two product-related impurities also showed significant differences under Langmuirian and anti-Langmuirian elution conditions and the purification of insulin could be optimized. Induced anti-Langmuirian elution by lowering the chloride/sulfate ratio suppresses an observed tag-along effect of one variant resulting in a slightly smaller pool volume with increased insulin concentration and a significantly increased insulin recovery.
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Affiliation(s)
- Jonas Koch
- Institute for Biochemistry, University of Applied Sciences, 68163 Mannheim, Germany; IA MSAT M&I DS, Sanofi-Aventis Deutschland GmbH, 65929 Frankfurt am Main, Germany
| | - Daniel Scheps
- CMC Microbial Platform, Sanofi-Aventis Deutschland GmbH, 65929 Frankfurt am Main, Germany
| | - Matthias Gunne
- IA MSAT M&I DS, Sanofi-Aventis Deutschland GmbH, 65929 Frankfurt am Main, Germany
| | - Oliver Boscheinen
- CMC Microbial Platform, Sanofi-Aventis Deutschland GmbH, 65929 Frankfurt am Main, Germany
| | - Christian Frech
- Institute for Biochemistry, University of Applied Sciences, 68163 Mannheim, Germany.
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Zhan Y, Liu J, Wu M, Tan CSH, Li X, Ou-Yang L. A partially shared joint clustering framework for detecting protein complexes from multiple state-specific signed interaction networks. Comput Biol Med 2023; 159:106936. [PMID: 37105110 DOI: 10.1016/j.compbiomed.2023.106936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 03/27/2023] [Accepted: 04/13/2023] [Indexed: 04/29/2023]
Abstract
Detecting protein complexes is critical for studying cellular organizations and functions. The accumulation of protein-protein interaction (PPI) data enables the identification of protein complexes computationally. Although a great number of computational methods have been proposed to identify protein complexes from PPI networks, most of them ignore the signs of PPIs that reflect the ways proteins interact (activation or inhibition). As not all PPIs imply co-complex relationships, taking into account the signs of PPIs can benefit the identification of protein complexes. Moreover, PPI networks are not static, but vary with the change of cell states or environments. However, existing methods are primarily designed for single-network clustering, and rarely consider joint clustering of multiple PPI networks. In this study, we propose a novel partially shared signed network clustering (PS-SNC) model for identifying protein complexes from multiple state-specific signed PPI networks jointly. PS-SNC can not only consider the signs of PPIs, but also identify the common and unique protein complexes in different states. Experimental results on synthetic and real datasets show that our PS-SNC model can achieve better performance than other state-of-the-art protein complex detection methods. Extensive analysis on real datasets demonstrate the effectiveness of PS-SNC in revealing novel insights about the underlying patterns of different cell lines.
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Affiliation(s)
- Youlin Zhan
- Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen Key Laboratory of Media Security, and Guangdong Laboratory of Artificial Intelligence and Digital Economy(SZ), College of Electronics and Information Engineering, Shenzhen University, Shenzhen, 518060, China
| | - Jiahan Liu
- Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen Key Laboratory of Media Security, and Guangdong Laboratory of Artificial Intelligence and Digital Economy(SZ), College of Electronics and Information Engineering, Shenzhen University, Shenzhen, 518060, China
| | - Min Wu
- Institute for Infocomm Research (I2R), Agency of Science, Technology, and Research (A*STAR), 138632, Singapore
| | - Chris Soon Heng Tan
- Department of Chemistry, College of Science, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Xiaoli Li
- Institute for Infocomm Research (I2R), Agency of Science, Technology, and Research (A*STAR), 138632, Singapore
| | - Le Ou-Yang
- Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen Key Laboratory of Media Security, and Guangdong Laboratory of Artificial Intelligence and Digital Economy(SZ), College of Electronics and Information Engineering, Shenzhen University, Shenzhen, 518060, China; Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, 518129, China.
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He H, Chen R, Wang Z, Qing L, Zhang Y, Liu Y, Pan W, Fang H, Zhang S. Design of Orally-bioavailable Tetra-cyclic phthalazine SOS1 inhibitors with high selectivity against EGFR. Bioorg Chem 2023; 136:106536. [PMID: 37054529 DOI: 10.1016/j.bioorg.2023.106536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 02/28/2023] [Accepted: 04/07/2023] [Indexed: 04/15/2023]
Abstract
KRAS mutations (G12C, G12D, etc.) are implicated in the oncogenesis and progression of many deadliest cancers. Son of sevenless homolog 1 (SOS1) is a crucial regulator of KRAS to modulate KRAS from inactive to active states. We previously discovered tetra-cyclic quinazolines as an improved scaffold for inhibiting SOS1-KRAS interaction. In this work, we report the design of tetra-cyclic phthalazine derivatives for selectively inhibiting SOS1 against EGFR. The lead compound 6c displayed remarkable activity to inhibit the proliferation of KRAS(G12C)-mutant pancreas cells. 6c showed a favorable pharmacokinetic profile in vivo, with a bioavailability of 65.8% and exhibited potent tumor suppression in pancreas tumor xenograft models. These intriguing results suggested that 6c has the potential to be developed as a drug candidate for KRAS-driven tumors.
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Affiliation(s)
- Huan He
- School of Pharmaceutical Sciences, Guizhou University, Guiyang 550025, PR China; Key Laboratory of Coal Conversion and New Carbon Materials of Hubei Province, College of Chemistry and Chemical Engineering, Wuhan University of Science and Technology, Wuhan 430081, PR China; Wuhan Yuxiang Pharmaceutical Technology Co., Ltd., Wuhan 430200, PR China
| | - Ruiqi Chen
- Key Laboratory of Coal Conversion and New Carbon Materials of Hubei Province, College of Chemistry and Chemical Engineering, Wuhan University of Science and Technology, Wuhan 430081, PR China
| | - Ziwei Wang
- Key Laboratory of Coal Conversion and New Carbon Materials of Hubei Province, College of Chemistry and Chemical Engineering, Wuhan University of Science and Technology, Wuhan 430081, PR China
| | - Luolong Qing
- Key Laboratory of Coal Conversion and New Carbon Materials of Hubei Province, College of Chemistry and Chemical Engineering, Wuhan University of Science and Technology, Wuhan 430081, PR China
| | - Yu Zhang
- Key Laboratory of Coal Conversion and New Carbon Materials of Hubei Province, College of Chemistry and Chemical Engineering, Wuhan University of Science and Technology, Wuhan 430081, PR China
| | - Yi Liu
- Key Laboratory of Coal Conversion and New Carbon Materials of Hubei Province, College of Chemistry and Chemical Engineering, Wuhan University of Science and Technology, Wuhan 430081, PR China; School of Chemical and Environmental Engineering, Wuhan Polytechnic University, Wuhan 430023, PR China; Hubei Key Laboratory of Radiation Chemistry and Functional Materials, Hubei University of Science and Technology, Xianning 437100, PR China
| | - Weidong Pan
- School of Pharmaceutical Sciences, Guizhou University, Guiyang 550025, PR China.
| | - Huaxiang Fang
- Key Laboratory of Coal Conversion and New Carbon Materials of Hubei Province, College of Chemistry and Chemical Engineering, Wuhan University of Science and Technology, Wuhan 430081, PR China.
| | - Silong Zhang
- School of Pharmaceutical Sciences, Guizhou University, Guiyang 550025, PR China; Key Laboratory of Coal Conversion and New Carbon Materials of Hubei Province, College of Chemistry and Chemical Engineering, Wuhan University of Science and Technology, Wuhan 430081, PR China; Wuhan Yuxiang Pharmaceutical Technology Co., Ltd., Wuhan 430200, PR China.
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An MJ, Lee HM, Kim CH, Shin GS, Jo AR, Kim JY, Kim MJ, Kim J, Park J, Hwangbo Y, Kim J, Kim JW. c-Jun N-terminal kinase 1 (JNK1) phosphorylates OTX2 transcription factor that regulates early retinal development. Genes Genomics 2023; 45:429-435. [PMID: 36434388 DOI: 10.1007/s13258-022-01342-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Accepted: 10/27/2022] [Indexed: 11/27/2022]
Abstract
BACKGROUND The transcription factor orthodenticle homeobox 2 (OTX2) has critical functions in brain and eye development, and its mutations in humans are related to retinal diseases, such as ocular coloboma and microphthalmia. However, the regulatory mechanisms of OTX2 are poorly identified. OBJECTIVE The identification of JNK1 as an OTX2 regulatory protein through the protein interaction and phosphorylation. METHODS To identify the binding partner of OTX2, we performed co-immunoprecipitation and detected with a pooled antibody that targeted effective kinases. The protein interaction between JNK1 and OTX2 was identified with the co-immunoprecipitation and immunocytochemistry. In vivo and in vitro kinase assay of JNK1 was performed to detect the phosphorylation of OTX2 by JNK1. RESULTS JNK1 directly interacted with OTX2 through the transactivation domain at the c-terminal region. The protein-protein interaction and co-localization between JNK1 and OTX2 were further validated in the developing P0 mouse retina. In addition, we confirmed that the inactivation of JNK1 K55N mutant significantly reduced the JNK1-mediated phosphorylation of OTX2 by performing an immune complex protein kinase assay. CONCLUSION c-Jun N-terminal kinase 1 (JNK1) phosphorylates OTX2 transcription factor through the protein-protein interaction.
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Affiliation(s)
- Mi-Jin An
- Department of Life Science, Chung-Ang University, Seoul, 06974, South Korea
| | - Hyun-Min Lee
- Department of Life Science, Chung-Ang University, Seoul, 06974, South Korea
| | - Chul-Hong Kim
- Department of Life Science, Chung-Ang University, Seoul, 06974, South Korea
| | - Geun-Seup Shin
- Department of Life Science, Chung-Ang University, Seoul, 06974, South Korea
| | - Ah-Ra Jo
- Department of Life Science, Chung-Ang University, Seoul, 06974, South Korea
| | - Ji-Young Kim
- Department of Life Science, Chung-Ang University, Seoul, 06974, South Korea
| | - Mi Jin Kim
- Department of Life Science, Chung-Ang University, Seoul, 06974, South Korea
| | - Jinho Kim
- Department of Life Science, Chung-Ang University, Seoul, 06974, South Korea
| | - Jinhong Park
- Department of Life Science, Chung-Ang University, Seoul, 06974, South Korea
| | - Yujeong Hwangbo
- Department of Life Science, Chung-Ang University, Seoul, 06974, South Korea
| | - Jeongkyu Kim
- Department of Life Science, Chung-Ang University, Seoul, 06974, South Korea
| | - Jung-Woong Kim
- Department of Life Science, Chung-Ang University, Seoul, 06974, South Korea.
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Yazdani M, Jafari A, Mahdian S, Namazi M, Gharaghani S. Rational approaches to discover SARS-CoV-2/ACE2 interaction inhibitors: Pharmacophore-based virtual screening, molecular docking, molecular dynamics and binding free energy studies. J Mol Liq 2023; 375:121345. [PMID: 36747970 PMCID: PMC9889117 DOI: 10.1016/j.molliq.2023.121345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Revised: 01/20/2023] [Accepted: 01/26/2023] [Indexed: 02/03/2023]
Abstract
The lack of effective treatment remains a bottleneck in combating the current coronavirus family pandemic, particularly coronavirus 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The infection of host cells by SARS-CoV-2 is mediated by the binding of its receptor-binding domain (RBD) on the spike (S) glycoprotein to the host angiotensin-converting enzyme (ACE2) receptor. As all developed and available vaccines against COVID-19 do not provide long-term immunity, the creation of an effective drug for the treatment of COVID-19 is necessary and cannot be ignored. Therefore, the aim of this study is to present a computational screening method to identify potential inhibitor candidates with a high probability of blocking the binding of RBD to the ACE2 receptor. Pharmacophore mapping, molecular docking, molecular dynamics (MD) simulations, and binding free-energy analyses were performed to identify potential inhibitor candidates against ACE2/SARS-CoV-2. In conclusion, we propose the compound PubChem-84280085 as a potential inhibitor of protein-protein interactions to disrupt the binding of the SARS-CoV-2-RBD to the ACE2 receptor.
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Affiliation(s)
- Mohsen Yazdani
- Laboratory of Bioinformatics and Drug Design, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
| | - Ameneh Jafari
- ATMP Department, Breast Cancer Research Center, Motamed Cancer Institute, ACECR, P.O. Box: 15179/64311, Tehran, Iran
- Proteomics Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Soodeh Mahdian
- Department of Cellular and Molecular Biology, Faculty of Biological Science, North Tehran Branch, Islamic Azad University, Tehran, Iran
| | - Mohsen Namazi
- Department of Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
| | - Sajjad Gharaghani
- Laboratory of Bioinformatics and Drug Design, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
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Fujita M, Tsuchiya K, Kurohara T, Fukuhara K, Misawa T, Demizu Y. In silico optimization of peptides that inhibit Wnt/β-catenin signaling. Bioorg Med Chem 2023; 84:117264. [PMID: 37003158 DOI: 10.1016/j.bmc.2023.117264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 03/23/2023] [Accepted: 03/24/2023] [Indexed: 04/03/2023]
Abstract
The Wnt/β-catenin signaling pathway causes transcriptional activation through the interaction between β-catenin and T cell-specific transcription factor (TCF) and regulates a wide variety of cellular responses, including proliferation, differentiation and cell motility. Excessive transcriptional activation of the Wnt/β-catenin pathway is implicated in developing or exacerbating various cancers. We have recently reported that liver receptor homolog-1 (LRH-1)-derived peptides inhibit the β-catenin/TCF interaction. In addition, we developed a cell-penetrating peptide (CPP)-conjugated LRH-1-derived peptide that inhibits the growth of colon cancer cells and specifically inhibits the Wnt/β-catenin pathway. Nonetheless, the inhibitory activity of the CPP-conjugated LRH-1-derived peptide was unsatisfactory (ca. 20 μM), and improving the bioactivity of peptide inhibitors is required for their in vivo applications. In this study, we optimized the LRH-1-derived peptide using in silico design to enhance its activity further. The newly designed peptides showed binding affinity toward β-catenin comparable to the parent peptide. In addition, the CPP-conjugated stapled peptide, Penetratin-st6, showed excellent inhibition (ca. 5 μM). Thus, the combination of in silico design by MOE and MD calculations has revealed that logical molecular design of PPI inhibitory peptides targeting β-catenin is possible. This method can be also applied to the rational design of peptide-based inhibitors targeting other proteins.
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Affiliation(s)
- Minami Fujita
- Graduate School of Medical Life Science, Yokohama City University, 1-7-29 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan; Division of Organic Chemistry, National Institute of Health Sciences, Kanagawa 210-9501, Japan
| | - Keisuke Tsuchiya
- Division of Organic Chemistry, National Institute of Health Sciences, Kanagawa 210-9501, Japan; Graduate School of Pharmacy, Showa University, 1-5-8 Hatanodai, Shinagawa-ku, Tokyo 142-8555, Japan.
| | - Takashi Kurohara
- Division of Organic Chemistry, National Institute of Health Sciences, Kanagawa 210-9501, Japan
| | - Kiyoshi Fukuhara
- Graduate School of Pharmacy, Showa University, 1-5-8 Hatanodai, Shinagawa-ku, Tokyo 142-8555, Japan
| | - Takashi Misawa
- Division of Organic Chemistry, National Institute of Health Sciences, Kanagawa 210-9501, Japan
| | - Yosuke Demizu
- Graduate School of Medical Life Science, Yokohama City University, 1-7-29 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan; Division of Organic Chemistry, National Institute of Health Sciences, Kanagawa 210-9501, Japan; Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, 1-1-1 Tsushimanaka, Kita-ku, Okayama 700-8530, Japan.
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Han S, Hong J, Yun SJ, Koo HJ, Kim TY. PWN: enhanced random walk on a warped network for disease target prioritization. BMC Bioinformatics 2023; 24:105. [PMID: 36944912 PMCID: PMC10031933 DOI: 10.1186/s12859-023-05227-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 03/13/2023] [Indexed: 03/23/2023] Open
Abstract
BACKGROUND Extracting meaningful information from unbiased high-throughput data has been a challenge in diverse areas. Specifically, in the early stages of drug discovery, a considerable amount of data was generated to understand disease biology when identifying disease targets. Several random walk-based approaches have been applied to solve this problem, but they still have limitations. Therefore, we suggest a new method that enhances the effectiveness of high-throughput data analysis with random walks. RESULTS We developed a new random walk-based algorithm named prioritization with a warped network (PWN), which employs a warped network to achieve enhanced performance. Network warping is based on both internal and external features: graph curvature and prior knowledge. CONCLUSIONS We showed that these compositive features synergistically increased the resulting performance when applied to random walk algorithms, which led to PWN consistently achieving the best performance among several other known methods. Furthermore, we performed subsequent experiments to analyze the characteristics of PWN.
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Affiliation(s)
- Seokjin Han
- Standigm Inc., 70, Nonhyeon-ro 85-gil, Gangnam-gu, Seoul, 06234, Republic of Korea
| | - Jinhee Hong
- Standigm Inc., 70, Nonhyeon-ro 85-gil, Gangnam-gu, Seoul, 06234, Republic of Korea
| | - So Jeong Yun
- Standigm Inc., 70, Nonhyeon-ro 85-gil, Gangnam-gu, Seoul, 06234, Republic of Korea
| | - Hee Jung Koo
- Standigm UK Co., Ltd, 50-60 Station Road, Cambridge, CB1 2JH, UK.
| | - Tae Yong Kim
- Standigm Inc., 70, Nonhyeon-ro 85-gil, Gangnam-gu, Seoul, 06234, Republic of Korea.
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50
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Mostaffa NH, Suhaimi AH, Al-Idrus A. Interactomics in plant defence: progress and opportunities. Mol Biol Rep 2023; 50:4605-4618. [PMID: 36920596 DOI: 10.1007/s11033-023-08345-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 02/15/2023] [Indexed: 03/16/2023]
Abstract
Interactomics is a branch of systems biology that deals with the study of protein-protein interactions and how these interactions influence phenotypes. Identifying the interactomes involved during host-pathogen interaction events may bring us a step closer to deciphering the molecular mechanisms underlying plant defence. Here, we conducted a systematic review of plant interactomics studies over the last two decades and found that while a substantial progress has been made in the field, plant-pathogen interactomics remains a less-travelled route. As an effort to facilitate the progress in this field, we provide here a comprehensive research pipeline for an in planta plant-pathogen interactomics study that encompasses the in silico prediction step to the validation step, unconfined to model plants. We also highlight four challenges in plant-pathogen interactomics with plausible solution(s) for each.
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Affiliation(s)
- Nur Hikmah Mostaffa
- Programme of Genetics, Institute of Biological Sciences, Faculty of Science, Universiti Malaya, 50603, Kuala Lumpur, Malaysia
| | - Ahmad Husaini Suhaimi
- Programme of Genetics, Institute of Biological Sciences, Faculty of Science, Universiti Malaya, 50603, Kuala Lumpur, Malaysia
| | - Aisyafaznim Al-Idrus
- Programme of Genetics, Institute of Biological Sciences, Faculty of Science, Universiti Malaya, 50603, Kuala Lumpur, Malaysia.
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