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Gianni S, Jemth P. Allostery Frustrates the Experimentalist. J Mol Biol 2023; 435:167934. [PMID: 36586463 DOI: 10.1016/j.jmb.2022.167934] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 12/20/2022] [Accepted: 12/22/2022] [Indexed: 12/29/2022]
Abstract
Proteins interact with other proteins, with nucleic acids, lipids, carbohydrates and various small molecules in the living cell. These interactions have been quantified and structurally characterized in numerous studies such that we today have a comprehensive picture of protein structure and function. However, proteins are dynamic and even folded proteins are likely more heterogeneous than they appear in most descriptions. One property of proteins that relies on dynamics and heterogeneity is allostery, the ability of a protein to change structure and function upon ligand binding to an allosteric site. Over the last decades the concept of allostery was broadened to embrace all types of long-range interactions across a protein including purely entropic changes without a conformational change in single protein domains. But with this re-definition came a problem: How do we measure allostery? In this opinion, we discuss some caveats arising from the quantitative description of single-domain allostery from an experimental perspective and how the limitations cannot be separated from the definition of allostery per se. Furthermore, we attempt to tie together allostery with the concept of frustration in an effort to investigate the links between these two complex, and yet general, properties of proteins. We arrive at the conclusion that the sensitivity to perturbation of allosteric networks in single protein domains is too large for the networks to be of significant biological relevance.
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Affiliation(s)
- Stefano Gianni
- Istituto Pasteur-Fondazione Cenci Bolognetti and Istituto di Biologia e Patologia Molecolari del CNR, Dipartimento di Scienze Biochimiche "A. Rossi Fanelli," Sapienza Università di Roma, 00185 Rome, Italy.
| | - Per Jemth
- Department of Medical Biochemistry and Microbiology, Uppsala University, BMC Box 582, SE-75123 Uppsala, Sweden.
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2
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Stevens AO, Kazan IC, Ozkan B, He Y. Investigating the allosteric response of the PICK1 PDZ domain to different ligands with all-atom simulations. Protein Sci 2022; 31:e4474. [PMID: 36251217 PMCID: PMC9667829 DOI: 10.1002/pro.4474] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 09/27/2022] [Accepted: 10/11/2022] [Indexed: 12/13/2022]
Abstract
The PDZ family is comprised of small modular domains that play critical roles in the allosteric modulation of many cellular signaling processes by binding to the C-terminal tail of different proteins. As dominant modular proteins that interact with a diverse set of peptides, it is of particular interest to explore how different binding partners induce different allosteric effects on the same PDZ domain. Because the PICK1 PDZ domain can bind different types of ligands, it is an ideal test case to answer this question and explore the network of interactions that give rise to dynamic allostery. Here, we use all-atom molecular dynamics simulations to explore dynamic allostery in the PICK1 PDZ domain by modeling two PICK1 PDZ systems: PICK1 PDZ-DAT and PICK1 PDZ-GluR2. Our results suggest that ligand binding to the PICK1 PDZ domain induces dynamic allostery at the αA helix that is similar to what has been observed in other PDZ domains. We found that the PICK1 PDZ-ligand distance is directly correlated with both dynamic changes of the αA helix and the distance between the αA helix and βB strand. Furthermore, our work identifies a hydrophobic core between DAT/GluR2 and I35 as a key interaction in inducing such dynamic allostery. Finally, the unique interaction patterns between different binding partners and the PICK1 PDZ domain can induce unique dynamic changes to the PICK1 PDZ domain. We suspect that unique allosteric coupling patterns with different ligands may play a critical role in how PICK1 performs its biological functions in various signaling networks.
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Affiliation(s)
- Amy O. Stevens
- Department of Chemistry and Chemical BiologyThe University of New MexicoAlbuquerqueNew MexicoUSA
| | - I. Can Kazan
- Department of Physics, Center for Biological PhysicsArizona State UniversityTempeArizonaUSA
| | - Banu Ozkan
- Department of Physics, Center for Biological PhysicsArizona State UniversityTempeArizonaUSA
| | - Yi He
- Department of Chemistry and Chemical BiologyThe University of New MexicoAlbuquerqueNew MexicoUSA
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3
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Stevens AO, Luo S, He Y. Three Binding Conformations of BIO124 in the Pocket of the PICK1 PDZ Domain. Cells 2022; 11:cells11152451. [PMID: 35954295 PMCID: PMC9368557 DOI: 10.3390/cells11152451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 07/29/2022] [Accepted: 08/04/2022] [Indexed: 11/30/2022] Open
Abstract
The PDZ family has drawn attention as possible drug targets because of the domains’ wide ranges of function and highly conserved binding pockets. The PICK1 PDZ domain has been proposed as a possible drug target because the interactions between the PICK1 PDZ domain and the GluA2 subunit of the AMPA receptor have been shown to progress neurodegenerative diseases. BIO124 has been identified as a sub µM inhibitor of the PICK1–GluA2 interaction. Here, we use all-atom molecular dynamics simulations to reveal the atomic-level interaction pattern between the PICK1 PDZ domain and BIO124. Our simulations reveal three unique binding conformations of BIO124 in the PICK1 PDZ binding pocket, referred to here as state 0, state 1, and state 2. Each conformation is defined by a unique hydrogen bonding network and a unique pattern of hydrophobic interactions between BIO124 and the PICK1 PDZ domain. Interestingly, each conformation of BIO124 results in different dynamic changes to the PICK1 PDZ domain. Unlike states 1 and 2, state 0 induces dynamic coupling between BIO124 and the αA helix. Notably, this dynamic coupling with the αA helix is similar to what has been observed in other PDZ–ligand complexes. Our analysis indicates that the interactions formed between BIO124 and I35 may be the key to inducing dynamic coupling with the αA helix. Lastly, we suspect that the conformational shifts observed in our simulations may affect the stability and thus the overall effectiveness of BIO124. We propose that a physically larger inhibitor may be necessary to ensure sufficient interactions that permit stable binding between a drug and the PICK1 PDZ domain.
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Affiliation(s)
- Amy O. Stevens
- Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, NM 87131, USA
| | - Samuel Luo
- Albuquerque Academy, Albuquerque, NM 87131, USA
| | - Yi He
- Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, NM 87131, USA
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico, Albuquerque, NM 87131, USA
- Correspondence:
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4
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Stevens AO, He Y. Allosterism in the PDZ Family. Int J Mol Sci 2022; 23:1454. [PMID: 35163402 PMCID: PMC8836106 DOI: 10.3390/ijms23031454] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 01/14/2022] [Accepted: 01/25/2022] [Indexed: 02/05/2023] Open
Abstract
Dynamic allosterism allows the propagation of signal throughout a protein. The PDZ (PSD-95/Dlg1/ZO-1) family has been named as a classic example of dynamic allostery in small modular domains. While the PDZ family consists of more than 200 domains, previous efforts have primarily focused on a few well-studied PDZ domains, including PTP-BL PDZ2, PSD-95 PDZ3, and Par6 PDZ. Taken together, experimental and computational studies have identified regions of these domains that are dynamically coupled to ligand binding. These regions include the αA helix, the αB lower-loop, and the αC helix. In this review, we summarize the specific residues on the αA helix, the αB lower-loop, and the αC helix of PTP-BL PDZ2, PSD-95 PDZ3, and Par6 PDZ that have been identified as participants in dynamic allostery by either experimental or computational approaches. This review can serve as an index for researchers to look back on the previously identified allostery in the PDZ family. Interestingly, our summary of previous work reveals clear consistencies between the domains. While the PDZ family has a low sequence identity, we show that some of the most consistently identified allosteric residues within PTP-BL PDZ2 and PSD-95 PDZ3 domains are evolutionarily conserved. These residues include A46/A347, V61/V362, and L66/L367 on PTP-BL PDZ2 and PSD-95 PDZ3, respectively. Finally, we expose a need for future work to explore dynamic allostery within (1) PDZ domains with multiple binding partners and (2) multidomain constructs containing a PDZ domain.
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Affiliation(s)
| | - Yi He
- Department of Chemistry and Chemical Biology, The University of New Mexico, Albuquerque, NM 87131, USA;
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5
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Dudola D, Hinsenkamp A, Gáspári Z. Ensemble-Based Analysis of the Dynamic Allostery in the PSD-95 PDZ3 Domain in Relation to the General Variability of PDZ Structures. Int J Mol Sci 2020; 21:ijms21218348. [PMID: 33172212 PMCID: PMC7672539 DOI: 10.3390/ijms21218348] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 10/28/2020] [Accepted: 10/30/2020] [Indexed: 11/16/2022] Open
Abstract
PDZ domains are abundant interaction hubs found in a number of different proteins and they exhibit characteristic differences in their structure and ligand specificity. Their internal dynamics have been proposed to contribute to their biological activity via changes in conformational entropy upon ligand binding and allosteric modulation. Here we investigate dynamic structural ensembles of PDZ3 of the postsynaptic protein PSD-95, calculated based on previously published backbone and side-chain S2 order parameters. We show that there are distinct but interdependent structural rearrangements in PDZ3 upon ligand binding and the presence of the intramolecular allosteric modulator helix α3. We have also compared these rearrangements in PDZ1-2 of PSD-95 and the conformational diversity of an extended set of PDZ domains available in the PDB database. We conclude that although the opening-closing rearrangement, occurring upon ligand binding, is likely a general feature for all PDZ domains, the conformer redistribution upon ligand binding along this mode is domain-dependent. Our findings suggest that the structural and functional diversity of PDZ domains is accompanied by a diversity of internal motional modes and their interdependence.
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Affiliation(s)
- Dániel Dudola
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter u. 50/A, 1083 Budapest, Hungary; (D.D.); (A.H.)
| | - Anett Hinsenkamp
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter u. 50/A, 1083 Budapest, Hungary; (D.D.); (A.H.)
- 3in-PPCU Research Group, 2500 Esztergom, Hungary
| | - Zoltán Gáspári
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter u. 50/A, 1083 Budapest, Hungary; (D.D.); (A.H.)
- Correspondence:
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Gautier C, Laursen L, Jemth P, Gianni S. Seeking allosteric networks in PDZ domains. Protein Eng Des Sel 2018; 31:367-373. [PMID: 30690500 PMCID: PMC6508479 DOI: 10.1093/protein/gzy033] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Accepted: 12/20/2018] [Indexed: 12/21/2022] Open
Abstract
Ever since Ranganathan and coworkers subjected the covariation of amino acid residues in the postsynaptic density-95/Discs large/Zonula occludens 1 (PDZ) domain family to a statistical correlation analysis, PDZ domains have represented a paradigmatic family to explore single domain protein allostery. Nevertheless, several theoretical and experimental studies in the past two decades have contributed contradicting results with regard to structural localization of the allosteric networks, or even questioned their actual existence in PDZ domains. In this review, we first describe theoretical and experimental approaches that were used to probe the energetic network(s) in PDZ domains. We then compare the proposed networks for two well-studied PDZ domains namely the third PDZ domain from PSD-95 and the second PDZ domain from PTP-BL. Our analysis highlights the contradiction between the different methods and calls for additional work to better understand these allosteric phenomena.
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Affiliation(s)
- Candice Gautier
- Istituto Pasteur—Fondazione Cenci Bolognetti, Dipartimento di Scienze Biochimiche ‘A. Rossi Fanelli’ and Istituto di Biologia e Patologia Molecolari del CNR, Sapienza Università di Roma, Rome, Italy
| | - Louise Laursen
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Per Jemth
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Stefano Gianni
- Istituto Pasteur—Fondazione Cenci Bolognetti, Dipartimento di Scienze Biochimiche ‘A. Rossi Fanelli’ and Istituto di Biologia e Patologia Molecolari del CNR, Sapienza Università di Roma, Rome, Italy
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Liu J, Duan X, Sun J, Yin Y, Li G, Wang L, Liu B. Bi-factor analysis based on noise-reduction (BIFANR): a new algorithm for detecting coevolving amino acid sites in proteins. PLoS One 2013; 8:e79764. [PMID: 24278175 PMCID: PMC3835919 DOI: 10.1371/journal.pone.0079764] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2013] [Accepted: 09/29/2013] [Indexed: 11/23/2022] Open
Abstract
Previous statistical analyses have shown that amino acid sites in a protein evolve in a correlated way instead of independently. Even though located distantly in the linear sequence, the coevolved amino acids could be spatially adjacent in the tertiary structure, and constitute specific protein sectors. Moreover, these protein sectors are independent of one another in structure, function, and even evolution. Thus, systematic studies on protein sectors inside a protein will contribute to the clarification of protein function. In this paper, we propose a new algorithm BIFANR (Bi-factor Analysis Based on Noise-reduction) for detecting protein sectors in amino acid sequences. After applying BIFANR on S1A family and PDZ family, we carried out internal correlation test, statistical independence test, evolutionary rate analysis, evolutionary independence analysis, and function analysis to assess the prediction. The results showed that the amino acids in certain predicted protein sector are closely correlated in structure, function, and evolution, while protein sectors are nearly statistically independent. The results also indicated that the protein sectors have distinct evolutionary directions. In addition, compared with other algorithms, BIFANR has higher accuracy and robustness under the influence of noise sites.
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Affiliation(s)
- Juntao Liu
- School of Mathematics, Shandong University, Jinan, China
| | - Xiaoyun Duan
- School of Life Science, Shandong University, Jinan, China
| | - Jianyang Sun
- School of Mathematics, Shandong University, Jinan, China
| | - Yanbin Yin
- Department of Biological Sciences, Northern Illinois University, DeKalb, Illinois, United States of America
| | - Guojun Li
- School of Mathematics, Shandong University, Jinan, China
| | - Lushan Wang
- School of Life Science, Shandong University, Jinan, China
| | - Bingqiang Liu
- School of Mathematics, Shandong University, Jinan, China
- * E-mail: Bingqiang Liu:
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Du QS, Meng JZ, Wang CH, Long SY, Huang RB. Structural position correlation analysis (SPCA) for protein family. PLoS One 2011; 6:e28206. [PMID: 22163002 PMCID: PMC3230615 DOI: 10.1371/journal.pone.0028206] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2011] [Accepted: 11/03/2011] [Indexed: 11/18/2022] Open
Abstract
Background The proteins in a family, which perform the similar biological functions, may have very different amino acid composition, but they must share the similar 3D structures, and keep a stable central region. In the conservative structure region similar biological functions are performed by two or three catalytic residues with the collaboration of several functional residues at key positions. Communication signals are conducted in a position network, adjusting the biological functions in the protein family. Methodology A computational approach, namely structural position correlation analysis (SPCA), is developed to analyze the correlation relationship between structural segments (or positions). The basic hypothesis of SPCA is that in a protein family the structural conservation is more important than the sequence conservation, and the local structural changes may contain information of biology functional evolution. A standard protein P(0) is defined in a protein family, which consists of the most-frequent amino acids and takes the average structure of the protein family. The foundational variables of SPCA is the structural position displacements between the standard protein P(0) and individual proteins Pi of the family. The structural positions are organized as segments, which are the stable units in structural displacements of the protein family. The biological function differences of protein members are determined by the position structural displacements of individual protein Pi to the standard protein P(0). Correlation analysis is used to analyze the communication network among segments. Conclusions The structural position correlation analysis (SPCA) is able to find the correlation relationship among the structural segments (or positions) in a protein family, which cannot be detected by the amino acid sequence and frequency-based methods. The functional communication network among the structural segments (or positions) in protein family, revealed by SPCA approach, well illustrate the distantly allosteric interactions, and contains valuable information for protein engineering study.
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Affiliation(s)
- Qi-Shi Du
- State Key Laboratory of Non-food Biomass Energy and Enzyme Technology, National Engineering Research Center for Non-food Biorefinery, Guangxi Academy of Sciences, Nanning, Guangxi, China.
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