1
|
Chen Q, Fan X. Potential role of the protein interactome in translating TCM theory and clinical practice into modern biomedical knowledge. Chin J Nat Med 2024; 22:385-386. [PMID: 38796212 DOI: 10.1016/s1875-5364(24)60635-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Indexed: 05/28/2024]
Affiliation(s)
- Qian Chen
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing 314100, China
| | - Xiaohui Fan
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing 314100, China.
| |
Collapse
|
2
|
Czerczak-Kwiatkowska K, Kaminska M, Fraczyk J, Majsterek I, Kolesinska B. Searching for EGF Fragments Recreating the Outer Sphere of the Growth Factor Involved in Receptor Interactions. Int J Mol Sci 2024; 25:1470. [PMID: 38338748 PMCID: PMC10855902 DOI: 10.3390/ijms25031470] [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: 12/12/2023] [Revised: 01/21/2024] [Accepted: 01/22/2024] [Indexed: 02/12/2024] Open
Abstract
The aims of this study were to determine whether it is possible to use peptide microarrays obtained using the SPOT technique (immobilized on cellulose) and specific polyclonal antibodies to select fragments that reconstruct the outer sphere of proteins and to ascertain whether the selected peptide fragments can be useful in the study of their protein-protein and/or peptide-protein interactions. Using this approach, epidermal growth factor (EGF) fragments responsible for the interaction with the EGF receptor were searched. A library of EGF fragments immobilized on cellulose was obtained using triazine condensing reagents. Experiments on the interactions with EGFR confirmed the high affinity of the selected peptide fragments. Biological tests on cells showed the lack of cytotoxicity of the EGF fragments. Selected EGF fragments can be used in various areas of medicine.
Collapse
Affiliation(s)
- Katarzyna Czerczak-Kwiatkowska
- Faculty of Chemistry, Institute of Organic Chemistry, Lodz University of Technology, Zeromskiego 116, 90-924 Lodz, Poland; (K.C.-K.); (J.F.)
| | - Marta Kaminska
- Division of Biophysics, Institute of Materials Science and Engineering, Lodz University of Technology, Stefanowskiego 1/15, 90-924 Lodz, Poland;
| | - Justyna Fraczyk
- Faculty of Chemistry, Institute of Organic Chemistry, Lodz University of Technology, Zeromskiego 116, 90-924 Lodz, Poland; (K.C.-K.); (J.F.)
| | - Ireneusz Majsterek
- Department of Clinical Chemistry and Biochemistry, Medical University of Lodz, Narutowicza 60, 90-136 Lodz, Poland;
| | - Beata Kolesinska
- Faculty of Chemistry, Institute of Organic Chemistry, Lodz University of Technology, Zeromskiego 116, 90-924 Lodz, Poland; (K.C.-K.); (J.F.)
| |
Collapse
|
3
|
Bret H, Gao J, Zea DJ, Andreani J, Guerois R. From interaction networks to interfaces, scanning intrinsically disordered regions using AlphaFold2. Nat Commun 2024; 15:597. [PMID: 38238291 PMCID: PMC10796318 DOI: 10.1038/s41467-023-44288-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 12/07/2023] [Indexed: 01/22/2024] Open
Abstract
The revolution brought about by AlphaFold2 opens promising perspectives to unravel the complexity of protein-protein interaction networks. The analysis of interaction networks obtained from proteomics experiments does not systematically provide the delimitations of the interaction regions. This is of particular concern in the case of interactions mediated by intrinsically disordered regions, in which the interaction site is generally small. Using a dataset of protein-peptide complexes involving intrinsically disordered regions that are non-redundant with the structures used in AlphaFold2 training, we show that when using the full sequences of the proteins, AlphaFold2-Multimer only achieves 40% success rate in identifying the correct site and structure of the interface. By delineating the interaction region into fragments of decreasing size and combining different strategies for integrating evolutionary information, we manage to raise this success rate up to 90%. We obtain similar success rates using a much larger dataset of protein complexes taken from the ELM database. Beyond the correct identification of the interaction site, our study also explores specificity issues. We show the advantages and limitations of using the AlphaFold2 confidence score to discriminate between alternative binding partners, a task that can be particularly challenging in the case of small interaction motifs.
Collapse
Affiliation(s)
- Hélène Bret
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198, Gif-sur-Yvette, France
| | - Jinmei Gao
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198, Gif-sur-Yvette, France
| | - Diego Javier Zea
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198, Gif-sur-Yvette, France
| | - Jessica Andreani
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198, Gif-sur-Yvette, France.
| | - Raphaël Guerois
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198, Gif-sur-Yvette, France.
| |
Collapse
|
4
|
Na D, Lim DH, Hong JS, Lee HM, Cho D, Yu MS, Shaker B, Ren J, Lee B, Song JG, Oh Y, Lee K, Oh KS, Lee MY, Choi MS, Choi HS, Kim YH, Bui JM, Lee K, Kim HW, Lee YS, Gsponer J. A multi-layered network model identifies Akt1 as a common modulator of neurodegeneration. Mol Syst Biol 2023; 19:e11801. [PMID: 37984409 DOI: 10.15252/msb.202311801] [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: 06/05/2023] [Revised: 10/25/2023] [Accepted: 10/27/2023] [Indexed: 11/22/2023] Open
Abstract
The accumulation of misfolded and aggregated proteins is a hallmark of neurodegenerative proteinopathies. Although multiple genetic loci have been associated with specific neurodegenerative diseases (NDs), molecular mechanisms that may have a broader relevance for most or all proteinopathies remain poorly resolved. In this study, we developed a multi-layered network expansion (MLnet) model to predict protein modifiers that are common to a group of diseases and, therefore, may have broader pathophysiological relevance for that group. When applied to the four NDs Alzheimer's disease (AD), Huntington's disease, and spinocerebellar ataxia types 1 and 3, we predicted multiple members of the insulin pathway, including PDK1, Akt1, InR, and sgg (GSK-3β), as common modifiers. We validated these modifiers with the help of four Drosophila ND models. Further evaluation of Akt1 in human cell-based ND models revealed that activation of Akt1 signaling by the small molecule SC79 increased cell viability in all models. Moreover, treatment of AD model mice with SC79 enhanced their long-term memory and ameliorated dysregulated anxiety levels, which are commonly affected in AD patients. These findings validate MLnet as a valuable tool to uncover molecular pathways and proteins involved in the pathophysiology of entire disease groups and identify potential therapeutic targets that have relevance across disease boundaries. MLnet can be used for any group of diseases and is available as a web tool at http://ssbio.cau.ac.kr/software/mlnet.
Collapse
Affiliation(s)
- Dokyun Na
- Department of Biomedical Engineering, Chung-Ang University, Seoul, Republic of Korea
| | - Do-Hwan Lim
- College of Life Sciences and Biotechnology, Korea University, Seoul, Republic of Korea
- School of Systems Biomedical Science, Soongsil University, Seoul, Republic of Korea
| | - Jae-Sang Hong
- College of Life Sciences and Biotechnology, Korea University, Seoul, Republic of Korea
- Center for Systems Biology, Massachusetts General Hospital, Boston, MA, USA
| | - Hyang-Mi Lee
- Department of Biomedical Engineering, Chung-Ang University, Seoul, Republic of Korea
| | - Daeahn Cho
- Department of Biomedical Engineering, Chung-Ang University, Seoul, Republic of Korea
| | - Myeong-Sang Yu
- Department of Biomedical Engineering, Chung-Ang University, Seoul, Republic of Korea
| | - Bilal Shaker
- Department of Biomedical Engineering, Chung-Ang University, Seoul, Republic of Korea
| | - Jun Ren
- Department of Biomedical Engineering, Chung-Ang University, Seoul, Republic of Korea
| | - Bomi Lee
- College of Life Sciences, Sejong University, Seoul, Republic of Korea
| | - Jae Gwang Song
- College of Life Sciences, Sejong University, Seoul, Republic of Korea
| | - Yuna Oh
- Korea Institute of Science and Technology, Seoul, Republic of Korea
| | - Kyungeun Lee
- Korea Institute of Science and Technology, Seoul, Republic of Korea
| | - Kwang-Seok Oh
- Information-based Drug Research Center, Korea Research Institute of Chemical Technology, Deajeon, Republic of Korea
| | - Mi Young Lee
- Information-based Drug Research Center, Korea Research Institute of Chemical Technology, Deajeon, Republic of Korea
| | - Min-Seok Choi
- College of Life Sciences and Biotechnology, Korea University, Seoul, Republic of Korea
| | - Han Saem Choi
- College of Life Sciences, Sejong University, Seoul, Republic of Korea
| | - Yang-Hee Kim
- College of Life Sciences, Sejong University, Seoul, Republic of Korea
| | - Jennifer M Bui
- Department of Biochemistry and Molecular Biology, Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada
| | - Kangseok Lee
- Department of Life Science, Chung-Ang University, Seoul, Republic of Korea
| | - Hyung Wook Kim
- College of Life Sciences, Sejong University, Seoul, Republic of Korea
| | - Young Sik Lee
- College of Life Sciences and Biotechnology, Korea University, Seoul, Republic of Korea
| | - Jörg Gsponer
- Department of Biochemistry and Molecular Biology, Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada
| |
Collapse
|
5
|
Meng Y, Hong C, Yang S, Qin Z, Yang L, Huang Y. Roles of USP9X in cellular functions and tumorigenesis (Review). Oncol Lett 2023; 26:506. [PMID: 37920433 PMCID: PMC10618932 DOI: 10.3892/ol.2023.14093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 09/12/2023] [Indexed: 11/04/2023] Open
Abstract
Ubiquitin-specific peptidase 9X (USP9X) is involved in certain human diseases, including malignancies, atherosclerosis and certain diseases of the nervous system. USP9X promotes the deubiquitination and stabilization of diverse substrates, thereby exerting a versatile range of effects on pathological and physiological processes. USP9X serves vital roles in the processes of cell survival, invasion and migration in various types of cancer. The present review aims to highlight the current knowledge of USP9X in terms of its structure and the possible mediatory mechanisms involved in certain types of cancer, providing a thorough introduction to its biological functions in carcinogenesis and further outlining its oncogenic or suppressive properties in a diverse range of cancer types. Finally, several perspectives regarding USP9X-targeted pharmacological therapeutics in cancer development are discussed.
Collapse
Affiliation(s)
- Yimei Meng
- Cancer Center, Department of Medical Oncology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang 310014, P.R. China
| | - Chaojin Hong
- Cancer Center, Department of Medical Oncology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang 310014, P.R. China
| | - Sifu Yang
- Cancer Center, Department of Medical Oncology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang 310014, P.R. China
| | - Zhiquan Qin
- Cancer Center, Department of Medical Oncology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang 310014, P.R. China
| | - Liu Yang
- Cancer Center, Department of Medical Oncology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang 310014, P.R. China
| | - Yumei Huang
- Cancer Center, Department of Medical Oncology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang 310014, P.R. China
| |
Collapse
|
6
|
Basu S, Hegedűs T, Kurgan L. CoMemMoRFPred: Sequence-based Prediction of MemMoRFs by Combining Predictors of Intrinsic Disorder, MoRFs and Disordered Lipid-binding Regions. J Mol Biol 2023; 435:168272. [PMID: 37709009 DOI: 10.1016/j.jmb.2023.168272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 09/01/2023] [Accepted: 09/07/2023] [Indexed: 09/16/2023]
Abstract
Molecular recognition features (MoRFs) are a commonly occurring type of intrinsically disordered regions (IDRs) that undergo disorder-to-order transition upon binding to partner molecules. We focus on recently characterized and functionally important membrane-binding MoRFs (MemMoRFs). Motivated by the lack of computational tools that predict MemMoRFs, we use a dataset of experimentally annotated MemMoRFs to conceptualize, design, evaluate and release an accurate sequence-based predictor. We rely on state-of-the-art tools that predict residues that possess key characteristics of MemMoRFs, such as intrinsic disorder, disorder-to-order transition and lipid-binding. We identify and combine results from three tools that include flDPnn for the disorder prediction, DisoLipPred for the prediction of disordered lipid-binding regions, and MoRFCHiBiLight for the prediction of disorder-to-order transitioning protein binding regions. Our empirical analysis demonstrates that combining results produced by these three methods generates accurate predictions of MemMoRFs. We also show that use of a smoothing operator produces predictions that closely mimic the number and sizes of the native MemMoRF regions. The resulting CoMemMoRFPred method is available as an easy-to-use webserver at http://biomine.cs.vcu.edu/servers/CoMemMoRFPred. This tool will aid future studies of MemMoRFs in the context of exploring their abundance, cellular functions, and roles in pathologic phenomena.
Collapse
Affiliation(s)
- Sushmita Basu
- Department of Computer Science, Virginia Commonwealth University, USA
| | - Tamás Hegedűs
- Department of Biophysics and Radiation Biology, Semmelweis University, Budapest, Hungary; ELKH-SE Biophysical Virology Research Group, Eötvös Loránd Research Network, Budapest, Hungary
| | - Lukasz Kurgan
- Department of Computer Science, Virginia Commonwealth University, USA.
| |
Collapse
|
7
|
Kurgan L, Hu G, Wang K, Ghadermarzi S, Zhao B, Malhis N, Erdős G, Gsponer J, Uversky VN, Dosztányi Z. Tutorial: a guide for the selection of fast and accurate computational tools for the prediction of intrinsic disorder in proteins. Nat Protoc 2023; 18:3157-3172. [PMID: 37740110 DOI: 10.1038/s41596-023-00876-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 06/21/2023] [Indexed: 09/24/2023]
Abstract
Intrinsic disorder is instrumental for a wide range of protein functions, and its analysis, using computational predictions from primary structures, complements secondary and tertiary structure-based approaches. In this Tutorial, we provide an overview and comparison of 23 publicly available computational tools with complementary parameters useful for intrinsic disorder prediction, partly relying on results from the Critical Assessment of protein Intrinsic Disorder prediction experiment. We consider factors such as accuracy, runtime, availability and the need for functional insights. The selected tools are available as web servers and downloadable programs, offer state-of-the-art predictions and can be used in a high-throughput manner. We provide examples and instructions for the selected tools to illustrate practical aspects related to the submission, collection and interpretation of predictions, as well as the timing and their limitations. We highlight two predictors for intrinsically disordered proteins, flDPnn as accurate and fast and IUPred as very fast and moderately accurate, while suggesting ANCHOR2 and MoRFchibi as two of the best-performing predictors for intrinsically disordered region binding. We link these tools to additional resources, including databases of predictions and web servers that integrate multiple predictive methods. Altogether, this Tutorial provides a hands-on guide to comparatively evaluating multiple predictors, submitting and collecting their own predictions, and reading and interpreting results. It is suitable for experimentalists and computational biologists interested in accurately and conveniently identifying intrinsic disorder, facilitating the functional characterization of the rapidly growing collections of protein sequences.
Collapse
Affiliation(s)
- Lukasz Kurgan
- Department of Computer Science, Virginia Commonwealth University, Richmond, VA, USA.
| | - Gang Hu
- School of Statistics and Data Science, LPMC and KLMDASR, Nankai University, Tianjin, China
| | - Kui Wang
- School of Statistics and Data Science, LPMC and KLMDASR, Nankai University, Tianjin, China
| | - Sina Ghadermarzi
- Department of Computer Science, Virginia Commonwealth University, Richmond, VA, USA
| | - Bi Zhao
- Department of Computer Science, Virginia Commonwealth University, Richmond, VA, USA
| | - Nawar Malhis
- Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia, Canada
| | - Gábor Erdős
- MTA-ELTE Momentum Bioinformatics Research Group, Department of Biochemistry, Eötvös Loránd University, Budapest, Hungary
| | - Jörg Gsponer
- Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia, Canada.
| | - Vladimir N Uversky
- Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA.
- Byrd Alzheimer's Center and Research Institute, Morsani College of Medicine, University of South Florida, Tampa, FL, USA.
| | - Zsuzsanna Dosztányi
- MTA-ELTE Momentum Bioinformatics Research Group, Department of Biochemistry, Eötvös Loránd University, Budapest, Hungary.
| |
Collapse
|
8
|
Yoodee S, Thongboonkerd V. Bioinformatics and computational analyses of kidney stone modulatory proteins lead to solid experimental evidence and therapeutic potential. Biomed Pharmacother 2023; 159:114217. [PMID: 36623450 DOI: 10.1016/j.biopha.2023.114217] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Revised: 12/26/2022] [Accepted: 01/04/2023] [Indexed: 01/09/2023] Open
Abstract
In recent biomedical research, bioinformatics and computational analyses have played essential roles for examining experimental findings and database information. Several bioinformatic tools have been developed and made publicly available for analyzing protein sequence, structure, functional motif/domain, and interactions network. Such properties are very helpful to define biochemical and functional roles of the protein(s) of interest. During the past few decades, bioinformatics and computational biotechnology have been widely applied to kidney stone research. This review summarizes commonly used tools and evidence of bioinformatics and computational biotechnology applied to kidney stone disease (KSD) with special emphasis on analyses of the stone modulatory proteins that play critical roles in kidney stone formation. Such analyses lead to solid experimental evidence to demonstrate mechanisms underlying their stone modulatory activities. The findings obtained from such analyses may also lead to better understanding of KSD pathogenesis and to further development of new therapeutic and preventive strategies.
Collapse
Affiliation(s)
- Sunisa Yoodee
- Medical Proteomics Unit, Research Department, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Visith Thongboonkerd
- Medical Proteomics Unit, Research Department, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand.
| |
Collapse
|
9
|
Fenton M, Borcherds W, Chen L, Anbanandam A, Levy R, Chen J, Daughdrill G. The MDMX Acidic Domain Uses Allovalency to Bind Both p53 and MDMX. J Mol Biol 2022; 434:167844. [PMID: 36181774 PMCID: PMC9644833 DOI: 10.1016/j.jmb.2022.167844] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 09/05/2022] [Accepted: 09/22/2022] [Indexed: 01/10/2023]
Abstract
Autoinhibition of p53 binding to MDMX requires two short-linear motifs (SLiMs) containing adjacent tryptophan (WW) and tryptophan-phenylalanine (WF) residues. NMR spectroscopy was used to show the WW and WF motifs directly compete for the p53 binding site on MDMX and circular dichroism spectroscopy was used to show the WW motif becomes helical when it is bound to the p53 binding domain (p53BD) of MDMX. Binding studies using isothermal titration calorimetry showed the WW motif is a stronger inhibitor of p53 binding than the WF motif when they are both tethered to p53BD by the natural disordered linker. We also investigated how the WW and WF motifs interact with the DNA binding domain (DBD) of p53. Both motifs bind independently to similar sites on DBD that overlap the DNA binding site. Taken together our work defines a model for complex formation between MDMX and p53 where a pair of disordered SLiMs bind overlapping sites on both proteins.
Collapse
Affiliation(s)
- Malissa Fenton
- Department of Cell Biology, Microbiology, and Molecular Biology, University of South Florida, Tampa, FL 33620, United States
| | - Wade Borcherds
- Department of Cell Biology, Microbiology, and Molecular Biology, University of South Florida, Tampa, FL 33620, United States
| | - Lihong Chen
- Molecular Oncology Department, Moffitt Cancer Center, Tampa, FL 33612, United States
| | - Asokan Anbanandam
- Department of Cell Biology, Microbiology, and Molecular Biology, University of South Florida, Tampa, FL 33620, United States
| | - Robin Levy
- Department of Cell Biology, Microbiology, and Molecular Biology, University of South Florida, Tampa, FL 33620, United States
| | - Jiandong Chen
- Molecular Oncology Department, Moffitt Cancer Center, Tampa, FL 33612, United States
| | - Gary Daughdrill
- Department of Cell Biology, Microbiology, and Molecular Biology, University of South Florida, Tampa, FL 33620, United States.
| |
Collapse
|