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Fuentes-Mateos R, García-Navas R, Fernández-Infante C, Hernández-Cano L, Calzada-Nieto N, Juan AOS, Guerrero C, Santos E, Fernández-Medarde A. Combined HRAS and NRAS ablation induces a RASopathy phenotype in mice. Cell Commun Signal 2024; 22:332. [PMID: 38886790 PMCID: PMC11184836 DOI: 10.1186/s12964-024-01717-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 06/14/2024] [Indexed: 06/20/2024] Open
Abstract
BACKGROUND HRASKO/NRASKO double knockout mice exhibit exceedingly high rates of perinatal lethality due to respiratory failure caused by a significant lung maturation delay. The few animals that reach adulthood have a normal lifespan, but present areas of atelectasis mixed with patches of emphysema and normal tissue in the lung. METHODS Eight double knockout and eight control mice were analyzed using micro-X-ray computerized tomography and a Small Animal Physiological Monitoring system. Tissues and samples from these mice were analyzed using standard histological and Molecular Biology methods and the significance of the results analyzed using a Student´s T-test. RESULTS The very few double knockout mice surviving up to adulthood display clear craniofacial abnormalities reminiscent of those seen in RASopathy mouse models, as well as thrombocytopenia, bleeding anomalies, and reduced platelet activation induced by thrombin. These surviving mice also present heart and spleen hyperplasia, and elevated numbers of myeloid-derived suppressor cells in the spleen. Mechanistically, we observed that these phenotypic alterations are accompanied by increased KRAS-GTP levels in heart, platelets and primary mouse embryonic fibroblasts from these animals. CONCLUSIONS Our data uncovers a new, previously unidentified mechanism capable of triggering a RASopathy phenotype in mice as a result of the combined removal of HRAS and NRAS.
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Affiliation(s)
- Rocío Fuentes-Mateos
- Centro de Investigación del Cáncer-Instituto de Biología Molecular y Celular del Cáncer (CSIC-Universidad de Salamanca) and CIBERONC, Campus Unamuno, University of Salamanca, 37007, Salamanca, Spain
- Present address: Department of Molecular Pharmacology, Groningen Research Institute for Asthma and COPD, University of Groningen, Groningen, Netherlands
| | - Rósula García-Navas
- Centro de Investigación del Cáncer-Instituto de Biología Molecular y Celular del Cáncer (CSIC-Universidad de Salamanca) and CIBERONC, Campus Unamuno, University of Salamanca, 37007, Salamanca, Spain
| | - Cristina Fernández-Infante
- Instituto de Biología Molecular y Celular del Cáncer (IMBCC), USAL-CSIC. Instituto de Investigación Biomédica de Salamanca (IBSAL), Salamanca, Spain
- Departamento de Medicina, Universidad de Salamanca, Salamanca, Spain
| | - Luis Hernández-Cano
- Instituto de Biología Molecular y Celular del Cáncer (IMBCC), USAL-CSIC. Instituto de Investigación Biomédica de Salamanca (IBSAL), Salamanca, Spain
- Departamento de Medicina, Universidad de Salamanca, Salamanca, Spain
- Present address: Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Groningen, Netherlands
| | - Nuria Calzada-Nieto
- Centro de Investigación del Cáncer-Instituto de Biología Molecular y Celular del Cáncer (CSIC-Universidad de Salamanca) and CIBERONC, Campus Unamuno, University of Salamanca, 37007, Salamanca, Spain
| | - Andrea Olarte-San Juan
- Centro de Investigación del Cáncer-Instituto de Biología Molecular y Celular del Cáncer (CSIC-Universidad de Salamanca) and CIBERONC, Campus Unamuno, University of Salamanca, 37007, Salamanca, Spain
| | - Carmen Guerrero
- Instituto de Biología Molecular y Celular del Cáncer (IMBCC), USAL-CSIC. Instituto de Investigación Biomédica de Salamanca (IBSAL), Salamanca, Spain
- Departamento de Medicina, Universidad de Salamanca, Salamanca, Spain
| | - Eugenio Santos
- Centro de Investigación del Cáncer-Instituto de Biología Molecular y Celular del Cáncer (CSIC-Universidad de Salamanca) and CIBERONC, Campus Unamuno, University of Salamanca, 37007, Salamanca, Spain.
| | - Alberto Fernández-Medarde
- Centro de Investigación del Cáncer-Instituto de Biología Molecular y Celular del Cáncer (CSIC-Universidad de Salamanca) and CIBERONC, Campus Unamuno, University of Salamanca, 37007, Salamanca, Spain.
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Hong X, Lv J, Li Z, Xiong Y, Zhang J, Chen HF. Sequence-based machine learning method for predicting the effects of phosphorylation on protein-protein interactions. Int J Biol Macromol 2023; 243:125233. [PMID: 37290543 DOI: 10.1016/j.ijbiomac.2023.125233] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 06/02/2023] [Accepted: 06/03/2023] [Indexed: 06/10/2023]
Abstract
Protein phosphorylation, catalyzed by kinases, is an important biochemical process, which plays an essential role in multiple cell signaling pathways. Meanwhile, protein-protein interactions (PPI) constitute the signaling pathways. Abnormal phosphorylation status on protein can regulate protein functions through PPI to evoke severe diseases, such as Cancer and Alzheimer's disease. Due to the limited experimental evidence and high costs to experimentally identify novel evidence of phosphorylation regulation on PPI, it is necessary to develop a high-accuracy and user-friendly artificial intelligence method to predict phosphorylation effect on PPI. Here, we proposed a novel sequence-based machine learning method named PhosPPI, which achieved better identification performance (Accuracy and AUC) than other competing predictive methods of Betts, HawkDock and FoldX. PhosPPI is now freely available in web server (https://phosppi.sjtu.edu.cn/). This tool can help the user to identify functional phosphorylation sites affecting PPI and explore phosphorylation-associated disease mechanism and drug development.
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Affiliation(s)
- Xiaokun Hong
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Jiyang Lv
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Zhengxin Li
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Yi Xiong
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Jian Zhang
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao-Tong University School of Medicine (SJTU-SM), Shanghai 200025, China.
| | - Hai-Feng Chen
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, China.
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3
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Hong X, Li N, Lv J, Zhang Y, Li J, Zhang J, Chen HF. PTMint database of experimentally verified PTM regulation on protein-protein interaction. Bioinformatics 2022; 39:6957085. [PMID: 36548389 PMCID: PMC9848059 DOI: 10.1093/bioinformatics/btac823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 12/18/2022] [Accepted: 12/21/2022] [Indexed: 12/24/2022] Open
Abstract
MOTIVATION Post-translational modification (PTM) is an important biochemical process. which includes six most well-studied types: phosphorylation, acetylation, methylation, sumoylation, ubiquitylation and glycosylation. PTM is involved in various cell signaling pathways and biological processes. Abnormal PTM status is closely associated with severe diseases (such as cancer and neurologic diseases) by regulating protein functions, such as protein-protein interactions (PPIs). A set of databases was constructed separately for PTM sites and PPI; however, the resource of regulation for PTM on PPI is still unsolved. RESULTS Here, we firstly constructed a public accessible database of PTMint (PTMs that are associated with PPIs) (https://ptmint.sjtu.edu.cn/) that contains manually curated complete experimental evidence of the PTM regulation on PPIs in multiple organisms, including Homo sapiens, Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Saccharomyces cerevisiae and Schizosaccharomyces pombe. Currently, the first version of PTMint encompassed 2477 non-redundant PTM sites in 1169 proteins affecting 2371 protein-protein pairs involving 357 diseases. Various annotations were systematically integrated, such as protein sequence, structure properties and protein complex analysis. PTMint database can help to insight into disease mechanism, disease diagnosis and drug discovery associated with PTM and PPI. AVAILABILITY AND IMPLEMENTATION PTMint is freely available at: https://ptmint.sjtu.edu.cn/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Xiaokun Hong
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Ningshan Li
- Department of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics and Data Science, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Jiyang Lv
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Yan Zhang
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Jing Li
- To whom correspondence should be addressed. or or
| | - Jian Zhang
- To whom correspondence should be addressed. or or
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Tam J, Palumbo T, Miwa JM, Chen BY. DiffBond: A Method for Predicting Intermolecular Bond Formation. PROCEEDINGS. IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE 2021; 2021:2574-2586. [PMID: 35378834 DOI: 10.1109/bibm52615.2021.9669850] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Many tools that explore models of protein complexes are also able to analyze interactions between specific residues and atoms. A comprehensive exploration of these interactions can often uncover aspects of protein-protein recognition that are not obvious using other protein analysis techniques. This paper describes DiffBond, a novel method for searching for intermolecular interactions between protein complexes while differentiating between three different types of interaction: hydrogen bonds, ionic bonds, and salt bridges. DiffBond incorporates textbook definitions of these three interactions while contending with uncertainties that are inherent in computational models of interacting proteins. We used it to examine the barnase-barstar, Rap1a-raf, and Smad2-Smad4 complexes, as well as a subset of protein complexes formed between three-finger toxins and nAChRs. Based on electrostatic interactions established by previous experimental studies, DiffBond was able to identify ionic and hydrogen bonds with high precision and recall, and identify salt bridges with high precision. In combination with other electrostatic analysis methods, DiffBond can be a useful tool in helping predict influential amino acids in protein-protein interactions and characterizing the type of interaction.
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Affiliation(s)
- Justin Tam
- Dept. Computer Science and Engineering, Lehigh University, Bethlehem, PA 18015, USA
| | - Talulla Palumbo
- Dept. Biological Sciences, Lehigh University, Bethlehem, PA 18015, USA
| | - Julie M Miwa
- Dept. Biological Sciences, Lehigh University, Bethlehem, PA 18015, USA
| | - Brian Y Chen
- Dept. Computer Science and Engineering, Lehigh University, Bethlehem, PA 18015, USA
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Qiu Y, Wang Y, Chai Z, Ni D, Li X, Pu J, Chen J, Zhang J, Lu S, Lv C, Ji M. Targeting RAS phosphorylation in cancer therapy: Mechanisms and modulators. Acta Pharm Sin B 2021; 11:3433-3446. [PMID: 34900528 PMCID: PMC8642438 DOI: 10.1016/j.apsb.2021.02.014] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 01/26/2021] [Accepted: 02/16/2021] [Indexed: 12/17/2022] Open
Abstract
RAS, a member of the small GTPase family, functions as a binary switch by shifting between inactive GDP-loaded and active GTP-loaded state. RAS gain-of-function mutations are one of the leading causes in human oncogenesis, accounting for ∼19% of the global cancer burden. As a well-recognized target in malignancy, RAS has been intensively studied in the past decades. Despite the sustained efforts, many failures occurred in the earlier exploration and resulted in an ‘undruggable’ feature of RAS proteins. Phosphorylation at several residues has been recently determined as regulators for wild-type and mutated RAS proteins. Therefore, the development of RAS inhibitors directly targeting the RAS mutants or towards upstream regulatory kinases supplies a novel direction for tackling the anti-RAS difficulties. A better understanding of RAS phosphorylation can contribute to future therapeutic strategies. In this review, we comprehensively summarized the current advances in RAS phosphorylation and provided mechanistic insights into the signaling transduction of associated pathways. Importantly, the preclinical and clinical success in developing anti-RAS drugs targeting the upstream kinases and potential directions of harnessing allostery to target RAS phosphorylation sites were also discussed.
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Key Words
- ABL, Abelson
- APC, adenomatous polyposis coli
- Allostery
- CK1, casein kinase 1
- CML, chronic myeloid leukemia
- ER, endoplasmic reticulum
- GAPs, GTPase-activating proteins
- GEFs, guanine nucleotide exchange-factors
- GSK3, glycogen synthase kinase 3
- HVR, hypervariable region
- IP3R, inositol trisphosphate receptors
- LRP6, lipoprotein-receptor-related protein 6
- OMM, outer mitochondrial membrane
- PI3K, phosphatidylinositol 3-kinase
- PKC, protein kinase C
- PPIs, protein−protein interactions
- Phosphorylation
- Protein kinases
- RAS
- RIN1, RAB-interacting protein 1
- SHP2, SRC homology 2 domain containing phosphatase 2
- SOS, Son of Sevenless
- STK19, serine/threonine-protein kinase 19
- TKIs, tyrosine kinase inhibitors
- Undruggable
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Affiliation(s)
- Yuran Qiu
- Department of Urology, Changzheng Hospital, Naval Military Medical University, Shanghai 200003, China
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Yuanhao Wang
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Zongtao Chai
- Department of Hepatic Surgery VI, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai 200438, China
| | - Duan Ni
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Xinyi Li
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Jun Pu
- Department of Cardiology, Renji Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai 200120, China
| | - Jie Chen
- Department of Urology, Changzheng Hospital, Naval Military Medical University, Shanghai 200003, China
| | - Jian Zhang
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
- Corresponding authors.
| | - Shaoyong Lu
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
- Corresponding authors.
| | - Chuan Lv
- Department of Plastic Surgery, Changhai Hospital, Naval Military Medical University, Shanghai 200438, China
- Corresponding authors.
| | - Mingfei Ji
- Department of Urology, Changzheng Hospital, Naval Military Medical University, Shanghai 200003, China
- Corresponding authors.
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Rezaei Adariani S, Kazemein Jasemi NS, Bazgir F, Wittich C, Amin E, Seidel CAM, Dvorsky R, Ahmadian MR. A comprehensive analysis of RAS-effector interactions reveals interaction hotspots and new binding partners. J Biol Chem 2021; 296:100626. [PMID: 33930461 PMCID: PMC8163975 DOI: 10.1016/j.jbc.2021.100626] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 03/25/2021] [Accepted: 03/31/2021] [Indexed: 02/07/2023] Open
Abstract
RAS effectors specifically interact with GTP-bound RAS proteins to link extracellular signals to downstream signaling pathways. These interactions rely on two types of domains, called RAS-binding (RB) and RAS association (RA) domains, which share common structural characteristics. Although the molecular nature of RAS-effector interactions is well-studied for some proteins, most of the RA/RB-domain-containing proteins remain largely uncharacterized. Here, we searched through human proteome databases, extracting 41 RA domains in 39 proteins and 16 RB domains in 14 proteins, each of which can specifically select at least one of the 25 members in the RAS family. We next comprehensively investigated the sequence–structure–function relationship between different representatives of the RAS family, including HRAS, RRAS, RALA, RAP1B, RAP2A, RHEB1, and RIT1, with all members of RA domain family proteins (RASSFs) and the RB-domain-containing CRAF. The binding affinity for RAS-effector interactions, determined using fluorescence polarization, broadly ranged between high (0.3 μM) and very low (500 μM) affinities, raising interesting questions about the consequence of these variable binding affinities in the regulation of signaling events. Sequence and structural alignments pointed to two interaction hotspots in the RA/RB domains, consisting of an average of 19 RAS-binding residues. Moreover, we found novel interactions between RRAS1, RIT1, and RALA and RASSF7, RASSF9, and RASSF1, respectively, which were systematically explored in sequence–structure–property relationship analysis, and validated by mutational analysis. These data provide a set of distinct functional properties and putative biological roles that should now be investigated in the cellular context.
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Affiliation(s)
- Soheila Rezaei Adariani
- Medical Faculty, Institute of Biochemistry and Molecular Biology II, Heinrich Heine University, Düsseldorf, Germany
| | - Neda S Kazemein Jasemi
- Medical Faculty, Institute of Biochemistry and Molecular Biology II, Heinrich Heine University, Düsseldorf, Germany
| | - Farhad Bazgir
- Medical Faculty, Institute of Biochemistry and Molecular Biology II, Heinrich Heine University, Düsseldorf, Germany
| | - Christoph Wittich
- Medical Faculty, Institute of Biochemistry and Molecular Biology II, Heinrich Heine University, Düsseldorf, Germany
| | - Ehsan Amin
- Medical Faculty, Institute of Biochemistry and Molecular Biology II, Heinrich Heine University, Düsseldorf, Germany; Medical Faculty, Institute of Neural and Sensory Physiology, Heinrich Heine University, Düsseldorf, Germany
| | - Claus A M Seidel
- Chair of Molecular Physical Chemistry, Heinrich Heine University, Düsseldorf, Germany
| | - Radovan Dvorsky
- Medical Faculty, Institute of Biochemistry and Molecular Biology II, Heinrich Heine University, Düsseldorf, Germany
| | - Mohammad R Ahmadian
- Medical Faculty, Institute of Biochemistry and Molecular Biology II, Heinrich Heine University, Düsseldorf, Germany.
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