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Hatos A, Monzon AM, Tosatto SCE, Piovesan D, Fuxreiter M. FuzDB: a new phase in understanding fuzzy interactions. Nucleic Acids Res 2021; 50:D509-D517. [PMID: 34791357 PMCID: PMC8728163 DOI: 10.1093/nar/gkab1060] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 10/13/2021] [Accepted: 10/27/2021] [Indexed: 11/14/2022] Open
Abstract
Fuzzy interactions are specific, variable contacts between proteins and other biomolecules (proteins, DNA, RNA, small molecules) formed in accord to the cellular context. Fuzzy interactions have recently been demonstrated to regulate biomolecular condensates generated by liquid-liquid phase separation. The FuzDB v4.0 database (https://fuzdb.org) assembles experimentally identified examples of fuzzy interactions, where disordered regions mediate functionally important, context-dependent contacts between the partners in stoichiometric and higher-order assemblies. The new version of FuzDB establishes cross-links with databases on structure (PDB, BMRB, PED), function (ELM, UniProt) and biomolecular condensates (PhaSepDB, PhaSePro, LLPSDB). FuzDB v4.0 is a source to decipher molecular basis of complex cellular interaction behaviors, including those in protein droplets.
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Affiliation(s)
- Andras Hatos
- Department of Biomedical Sciences, University of Padova, via Ugo Bassi 58/B, 35131 Padova, Italy
| | - Alexander Miguel Monzon
- Department of Biomedical Sciences, University of Padova, via Ugo Bassi 58/B, 35131 Padova, Italy
| | - Silvio C E Tosatto
- Department of Biomedical Sciences, University of Padova, via Ugo Bassi 58/B, 35131 Padova, Italy
| | - Damiano Piovesan
- Department of Biomedical Sciences, University of Padova, via Ugo Bassi 58/B, 35131 Padova, Italy
| | - Monika Fuxreiter
- Department of Biomedical Sciences, University of Padova, via Ugo Bassi 58/B, 35131 Padova, Italy.,Department of Biochemistry and Molecular Biology, University of Debrecen, Nagyerdei krt 98, 4010 Debrecen, Hungary
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2
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Nussinov R, Zhang M, Maloney R, Tsai CJ, Yavuz BR, Tuncbag N, Jang H. Mechanism of activation and the rewired network: New drug design concepts. Med Res Rev 2021; 42:770-799. [PMID: 34693559 PMCID: PMC8837674 DOI: 10.1002/med.21863] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 07/06/2021] [Accepted: 10/07/2021] [Indexed: 12/13/2022]
Abstract
Precision oncology benefits from effective early phase drug discovery decisions. Recently, drugging inactive protein conformations has shown impressive successes, raising the cardinal questions of which targets can profit and what are the principles of the active/inactive protein pharmacology. Cancer driver mutations have been established to mimic the protein activation mechanism. We suggest that the decision whether to target an inactive (or active) conformation should largely rest on the protein mechanism of activation. We next discuss the recent identification of double (multiple) same-allele driver mutations and their impact on cell proliferation and suggest that like single driver mutations, double drivers also mimic the mechanism of activation. We further suggest that the structural perturbations of double (multiple) in cis mutations may reveal new surfaces/pockets for drug design. Finally, we underscore the preeminent role of the cellular network which is deregulated in cancer. Our structure-based review and outlook updates the traditional Mechanism of Action, informs decisions, and calls attention to the intrinsic activation mechanism of the target protein and the rewired tumor-specific network, ushering innovative considerations in precision medicine.
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Affiliation(s)
- Ruth Nussinov
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, Maryland, USA.,Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Mingzhen Zhang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, Maryland, USA
| | - Ryan Maloney
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, Maryland, USA
| | - Chung-Jung Tsai
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, Maryland, USA
| | - Bengi Ruken Yavuz
- Department of Health Informatics, Graduate School of Informatics, Middle East Technical University, Ankara, Turkey
| | - Nurcan Tuncbag
- Department of Health Informatics, Graduate School of Informatics, Middle East Technical University, Ankara, Turkey.,Department of Chemical and Biological Engineering, College of Engineering, Koc University, Istanbul, Turkey.,Koc University Research Center for Translational Medicine, School of Medicine, Koc University, Istanbul, Turkey
| | - Hyunbum Jang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, Maryland, USA
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3
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Vendruscolo M, Fuxreiter M. Sequence Determinants of the Aggregation of Proteins Within Condensates Generated by Liquid-liquid Phase Separation. J Mol Biol 2021; 434:167201. [PMID: 34391803 DOI: 10.1016/j.jmb.2021.167201] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 07/08/2021] [Accepted: 08/09/2021] [Indexed: 12/12/2022]
Abstract
The transition between the native and amyloid states of proteins can proceed via a deposition pathway via oligomeric intermediates or via a condensation pathway involving liquid droplet intermediates generated through liquid-liquid phase separation. While several computational methods are available to perform sequence-based predictions of the propensity of proteins to aggregate via the deposition pathway, much less is known about the physico-chemical principles that underlie aggregation within condensates. Here we investigate the sequence determinants of aggregation via the condensation pathway, and identify three relevant features: droplet-promoting propensity, aggregation-promoting propensity and multimodal interactions quantified by the binding mode entropy. By using this approach, we show that it is possible to predict aggregation-promoting mutations in droplet-forming proteins associated with amyotrophic lateral sclerosis (ALS). This analysis provides insights into the amino acid code for the conversion of proteins between liquid-like and solid-like condensates.
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Affiliation(s)
- Michele Vendruscolo
- Centre for Misfolding Diseases, Department of Chemistry, University of Cambridge, UK.
| | - Monika Fuxreiter
- Department of Biomedical Sciences, University of Padova, Italy; Department of Biochemistry and Molecular Biology, University of Debrecen, Hungary.
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4
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Whence Blobs? Phylogenetics of functional protein condensates. Biochem Soc Trans 2021; 48:2151-2158. [PMID: 32985656 DOI: 10.1042/bst20200355] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 09/04/2020] [Accepted: 09/07/2020] [Indexed: 12/15/2022]
Abstract
What do we know about the molecular evolution of functional protein condensation? The capacity of proteins to form biomolecular condensates (compact, protein-rich states, not bound by membranes, but still separated from the rest of the contents of the cell) appears in many cases to be bestowed by weak, transient interactions within one or between proteins. Natural selection is expected to remove or fix amino acid changes, insertions or deletions that preserve and change this condensation capacity when doing so is beneficial to the cell. A few recent studies have begun to explore this frontier of phylogenetics at the intersection of biophysics and cell biology.
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5
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Gao C, Ma C, Wang H, Zhong H, Zang J, Zhong R, He F, Yang D. Intrinsic disorder in protein domains contributes to both organism complexity and clade-specific functions. Sci Rep 2021; 11:2985. [PMID: 33542394 PMCID: PMC7862400 DOI: 10.1038/s41598-021-82656-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 01/22/2021] [Indexed: 11/09/2022] Open
Abstract
Interestingly, some protein domains are intrinsically disordered (abbreviated as IDD), and the disorder degree of same domains may differ in different contexts. However, the evolutionary causes and biological significance of these phenomena are unclear. Here, we address these issues by genome-wide analyses of the evolutionary and functional features of IDDs in 1,870 species across the three superkingdoms. As the result, there is a significant positive correlation between the proportion of IDDs and organism complexity with some interesting exceptions. These phenomena may be due to the high disorder of clade-specific domains and the different disorder degrees of the domains shared in different clades. The functions of IDDs are clade-specific and the higher proportion of post-translational modification sites may contribute to their complex functions. Compared with metazoans, fungi have more IDDs with a consecutive disorder region but a low disorder ratio, which reflects their different functional requirements. As for disorder variation, it’s greater for domains among different proteins than those within the same proteins. Some clade-specific ‘no-variation’ or ‘high-variation’ domains are involved in clade-specific functions. In sum, intrinsic domain disorder is related to both the organism complexity and clade-specific functions. These results deepen the understanding of the evolution and function of IDDs.
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Affiliation(s)
- Chao Gao
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, 38 Science Park Road, Changping District, Beijing, 102206, China
| | - Chong Ma
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, 38 Science Park Road, Changping District, Beijing, 102206, China.,Beijing Key Laboratory of Environmental and Viral Oncology, College of Life Science and Bioengineering, Beijing University of Technology, Beijing, 100124, China
| | - Huqiang Wang
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, 38 Science Park Road, Changping District, Beijing, 102206, China
| | - Haolin Zhong
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, 38 Science Park Road, Changping District, Beijing, 102206, China
| | - Jiayin Zang
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, 38 Science Park Road, Changping District, Beijing, 102206, China
| | - Rugang Zhong
- Beijing Key Laboratory of Environmental and Viral Oncology, College of Life Science and Bioengineering, Beijing University of Technology, Beijing, 100124, China
| | - Fuchu He
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, 38 Science Park Road, Changping District, Beijing, 102206, China.
| | - Dong Yang
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, 38 Science Park Road, Changping District, Beijing, 102206, China.
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Piovesan D, Necci M, Escobedo N, Monzon AM, Hatos A, Mičetić I, Quaglia F, Paladin L, Ramasamy P, Dosztányi Z, Vranken WF, Davey N, Parisi G, Fuxreiter M, Tosatto SE. MobiDB: intrinsically disordered proteins in 2021. Nucleic Acids Res 2021; 49:D361-D367. [PMID: 33237329 PMCID: PMC7779018 DOI: 10.1093/nar/gkaa1058] [Citation(s) in RCA: 130] [Impact Index Per Article: 43.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 10/16/2020] [Accepted: 11/19/2020] [Indexed: 12/13/2022] Open
Abstract
The MobiDB database (URL: https://mobidb.org/) provides predictions and annotations for intrinsically disordered proteins. Here, we report recent developments implemented in MobiDB version 4, regarding the database format, with novel types of annotations and an improved update process. The new website includes a re-designed user interface, a more effective search engine and advanced API for programmatic access. The new database schema gives more flexibility for the users, as well as simplifying the maintenance and updates. In addition, the new entry page provides more visualisation tools including customizable feature viewer and graphs of the residue contact maps. MobiDB v4 annotates the binding modes of disordered proteins, whether they undergo disorder-to-order transitions or remain disordered in the bound state. In addition, disordered regions undergoing liquid-liquid phase separation or post-translational modifications are defined. The integrated information is presented in a simplified interface, which enables faster searches and allows large customized datasets to be downloaded in TSV, Fasta or JSON formats. An alternative advanced interface allows users to drill deeper into features of interest. A new statistics page provides information at database and proteome levels. The new MobiDB version presents state-of-the-art knowledge on disordered proteins and improves data accessibility for both computational and experimental users.
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Affiliation(s)
- Damiano Piovesan
- Dept. of Biomedical Sciences, University of Padua, Via Ugo Bassi 58/B, Padua 35121, Italy
| | - Marco Necci
- Dept. of Biomedical Sciences, University of Padua, Via Ugo Bassi 58/B, Padua 35121, Italy
| | - Nahuel Escobedo
- Dept. of Science and Technology, Universidad Nacional de Quilmes, Buenos Aires, Argentina
| | | | - András Hatos
- Dept. of Biomedical Sciences, University of Padua, Via Ugo Bassi 58/B, Padua 35121, Italy
| | - Ivan Mičetić
- Dept. of Biomedical Sciences, University of Padua, Via Ugo Bassi 58/B, Padua 35121, Italy
| | - Federica Quaglia
- Dept. of Biomedical Sciences, University of Padua, Via Ugo Bassi 58/B, Padua 35121, Italy
| | - Lisanna Paladin
- Dept. of Biomedical Sciences, University of Padua, Via Ugo Bassi 58/B, Padua 35121, Italy
| | - Pathmanaban Ramasamy
- Interuniversity Institute of Bioinformatics in Brussels, ULB/VUB, Triomflaan, BC building, 6th floor, CP 263, 1050 Brussels, Belgium
- Structural Biology Brussels, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium
- Centre for Structural Biology, VIB, Pleinlaan 2, 1050 Brussels, Belgium
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent 9000, Belgium
- Department of Biomolecular Medicine, Faculty of Health Sciences and Medicine, Ghent University, Ghent 9000, Belgium
| | | | - Wim F Vranken
- Interuniversity Institute of Bioinformatics in Brussels, ULB/VUB, Triomflaan, BC building, 6th floor, CP 263, 1050 Brussels, Belgium
- Structural Biology Brussels, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium
- Centre for Structural Biology, VIB, Pleinlaan 2, 1050 Brussels, Belgium
| | - Norman E Davey
- Division of Cancer Biology, The Institute of Cancer Research, 237 Fulham Road, London, SW3 6JB, UK
| | - Gustavo Parisi
- Dept. of Science and Technology, Universidad Nacional de Quilmes, Buenos Aires, Argentina
| | - Monika Fuxreiter
- Dept. of Biomedical Sciences, University of Padua, Via Ugo Bassi 58/B, Padua 35121, Italy
| | - Silvio C E Tosatto
- Dept. of Biomedical Sciences, University of Padua, Via Ugo Bassi 58/B, Padua 35121, Italy
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7
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Wingert B, Krieger J, Li H, Bahar I. Adaptability and specificity: how do proteins balance opposing needs to achieve function? Curr Opin Struct Biol 2020; 67:25-32. [PMID: 33053463 DOI: 10.1016/j.sbi.2020.08.009] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2020] [Revised: 08/30/2020] [Accepted: 08/30/2020] [Indexed: 12/14/2022]
Abstract
Many proteins select from a small repertoire of 3-dimensional folds retained over evolutional timescales and recruited for different functions, with changes in local structure and sequence to enable specificity. Recent studies have revealed the evolutionary constraints on protein dynamics to achieve function. The significance of protein dynamics in simultaneously satisfying conformational flexibility/malleability and stability/precision requirements becomes clear upon dissecting the spectrum of equilibrium motions accessible to fold families. Accessibility to highly conserved global modes of motions shared by family members, to low-to-intermediate-frequency modes that distinguish subfamilies and confer specificity, and to conserved high-frequency modes ensuring chemical precision and core stability underlies functional specialization while exploiting highly versatile folds. These design principles are illustrated for the family of PDZ domains.
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Affiliation(s)
- Bentley Wingert
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA 15213 USA
| | - James Krieger
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA 15213 USA
| | - Hongchun Li
- Research Center for Computer-Aided Drug Discovery at Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA 15213 USA.
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