1
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Viral subversion of the cell polarity regulator Scribble. Biochem Soc Trans 2023; 51:415-426. [PMID: 36606695 PMCID: PMC9987997 DOI: 10.1042/bst20221067] [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: 10/19/2022] [Revised: 12/08/2022] [Accepted: 12/12/2022] [Indexed: 01/07/2023]
Abstract
Scribble is a scaffolding protein that regulates key events such as cell polarity, tumorigenesis and neuronal signalling. Scribble belongs to the LAP family which comprise of 16 Leucine Rich Repeats (LRR) at the N-terminus, two LAP Specific Domains (LAPSD) and four PSD-95/Discs-large/ZO-1 (PDZ) domains at the C-terminus. The four PDZ domains have been shown to be key for a range of protein-protein interactions and have been identified to be crucial mediators for the vast majority of Scribble interactions, particularly via PDZ Binding Motifs (PBMs) often found at the C-terminus of interacting proteins. Dysregulation of Scribble is associated with poor prognosis in viral infections due to subversion of multiple cell signalling pathways by viral effector proteins. Here, we review the molecular details of the interplay between Scribble and viral effector proteins that provide insight into the potential modes of regulation of Scribble mediated polarity signalling.
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2
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Campitelli P, Swint-Kruse L, Ozkan SB. Substitutions at Nonconserved Rheostat Positions Modulate Function by Rewiring Long-Range, Dynamic Interactions. Mol Biol Evol 2021; 38:201-214. [PMID: 32780837 PMCID: PMC7783170 DOI: 10.1093/molbev/msaa202] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Amino acid substitutions at nonconserved protein positions can have noncanonical and "long-distance" outcomes on protein function. Such outcomes might arise from changes in the internal protein communication network, which is often accompanied by changes in structural flexibility. To test this, we calculated flexibilities and dynamic coupling for positions in the linker region of the lactose repressor protein. This region contains nonconserved positions for which substitutions alter DNA-binding affinity. We first chose to study 11 substitutions at position 52. In computations, substitutions showed long-range effects on flexibilities of DNA-binding positions, and the degree of flexibility change correlated with experimentally measured changes in DNA binding. Substitutions also altered dynamic coupling to DNA-binding positions in a manner that captured other experimentally determined functional changes. Next, we broadened calculations to consider the dynamic coupling between 17 linker positions and the DNA-binding domain. Experimentally, these linker positions exhibited a wide range of substitution outcomes: Four conserved positions tolerated hardly any substitutions ("toggle"), ten nonconserved positions showed progressive changes from a range of substitutions ("rheostat"), and three nonconserved positions tolerated almost all substitutions ("neutral"). In computations with wild-type lactose repressor protein, the dynamic couplings between the DNA-binding domain and these linker positions showed varied degrees of asymmetry that correlated with the observed toggle/rheostat/neutral substitution outcomes. Thus, we propose that long-range and noncanonical substitutions outcomes at nonconserved positions arise from rewiring long-range communication among functionally important positions. Such calculations might enable predictions for substitution outcomes at a range of nonconserved positions.
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Affiliation(s)
- Paul Campitelli
- Department of Physics, Center for Biological Physics, Arizona State University, Tempe, AZ
| | - Liskin Swint-Kruse
- Department of Biochemistry and Molecular Biology, The University of Kansas Medical Center, Kansas City, KS
| | - S Banu Ozkan
- Department of Physics, Center for Biological Physics, Arizona State University, Tempe, AZ
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3
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Modi T, Risso VA, Martinez-Rodriguez S, Gavira JA, Mebrat MD, Van Horn WD, Sanchez-Ruiz JM, Banu Ozkan S. Hinge-shift mechanism as a protein design principle for the evolution of β-lactamases from substrate promiscuity to specificity. Nat Commun 2021; 12:1852. [PMID: 33767175 PMCID: PMC7994827 DOI: 10.1038/s41467-021-22089-0] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 02/01/2021] [Indexed: 01/31/2023] Open
Abstract
TEM-1 β-lactamase degrades β-lactam antibiotics with a strong preference for penicillins. Sequence reconstruction studies indicate that it evolved from ancestral enzymes that degraded a variety of β-lactam antibiotics with moderate efficiency. This generalist to specialist conversion involved more than 100 mutational changes, but conserved fold and catalytic residues, suggesting a role for dynamics in enzyme evolution. Here, we develop a conformational dynamics computational approach to rationally mold a protein flexibility profile on the basis of a hinge-shift mechanism. By deliberately weighting and altering the conformational dynamics of a putative Precambrian β-lactamase, we engineer enzyme specificity that mimics the modern TEM-1 β-lactamase with only 21 amino acid replacements. Our conformational dynamics design thus re-enacts the evolutionary process and provides a rational allosteric approach for manipulating function while conserving the enzyme active site.
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Affiliation(s)
- Tushar Modi
- Department of Physics and Center for Biological Physics, Arizona State University, Tempe, AZ, USA
| | - Valeria A Risso
- Departamento de Quimica Fisica, Facultad de Ciencias, Universidad de Granada, Granada, Spain
- Unidad de Excelencia de Quimica Aplicada a Biomedicina y Medioambiente (UEQ), Universidad de Granada, Granada, Spain
| | - Sergio Martinez-Rodriguez
- Departamento de Quimica Fisica, Facultad de Ciencias, Universidad de Granada, Granada, Spain
- Departamento de Bioquimica, Biologia Molecular III e Inmunologia, Universidad de Granada, Granada, Spain
| | - Jose A Gavira
- Unidad de Excelencia de Quimica Aplicada a Biomedicina y Medioambiente (UEQ), Universidad de Granada, Granada, Spain
- Laboratorio de Estudios Cristalograficos, Instituto Andaluz de Ciencias de la Tierra, CSIC, Universidad de Granada, Granada, Armilla, Spain
| | - Mubark D Mebrat
- The Biodesign Institute Virginia G. Piper Center for Personalized Diagnostics, Arizona State University, Tempe, AZ, USA
- School of Molecular Sciences, Arizona State University, Tempe, AZ, USA
| | - Wade D Van Horn
- The Biodesign Institute Virginia G. Piper Center for Personalized Diagnostics, Arizona State University, Tempe, AZ, USA
- School of Molecular Sciences, Arizona State University, Tempe, AZ, USA
| | - Jose M Sanchez-Ruiz
- Departamento de Quimica Fisica, Facultad de Ciencias, Universidad de Granada, Granada, Spain.
- Unidad de Excelencia de Quimica Aplicada a Biomedicina y Medioambiente (UEQ), Universidad de Granada, Granada, Spain.
| | - S Banu Ozkan
- Department of Physics and Center for Biological Physics, Arizona State University, Tempe, AZ, USA.
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4
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Amacher JF, Brooks L, Hampton TH, Madden DR. Specificity in PDZ-peptide interaction networks: Computational analysis and review. JOURNAL OF STRUCTURAL BIOLOGY-X 2020; 4:100022. [PMID: 32289118 PMCID: PMC7138185 DOI: 10.1016/j.yjsbx.2020.100022] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Revised: 02/26/2020] [Accepted: 02/29/2020] [Indexed: 01/03/2023]
Abstract
Globular PDZ domains typically serve as protein-protein interaction modules that regulate a wide variety of cellular functions via recognition of short linear motifs (SLiMs). Often, PDZ mediated-interactions are essential components of macromolecular complexes, and disruption affects the entire scaffold. Due to their roles as linchpins in trafficking and signaling pathways, PDZ domains are attractive targets: both for controlling viral pathogens, which bind PDZ domains and hijack cellular machinery, as well as for developing therapies to combat human disease. However, successful therapeutic interventions that avoid off-target effects are a challenge, because each PDZ domain interacts with a number of cellular targets, and specific binding preferences can be difficult to decipher. Over twenty-five years of research has produced a wealth of data on the stereochemical preferences of individual PDZ proteins and their binding partners. Currently the field lacks a central repository for this information. Here, we provide this important resource and provide a manually curated, comprehensive list of the 271 human PDZ domains. We use individual domain, as well as recent genomic and proteomic, data in order to gain a holistic view of PDZ domains and interaction networks, arguing this knowledge is critical to optimize targeting selectivity and to benefit human health.
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Affiliation(s)
- Jeanine F Amacher
- Department of Biochemistry and Cell Biology, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA.,Department of Chemistry, Western Washington University, Bellingham, WA 98225, USA
| | - Lionel Brooks
- Department of Biology, Western Washington University, Bellingham, WA 98225, USA
| | - Thomas H Hampton
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA
| | - Dean R Madden
- Department of Biochemistry and Cell Biology, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA
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5
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Campitelli P, Modi T, Kumar S, Ozkan SB. The Role of Conformational Dynamics and Allostery in Modulating Protein Evolution. Annu Rev Biophys 2020; 49:267-288. [PMID: 32075411 DOI: 10.1146/annurev-biophys-052118-115517] [Citation(s) in RCA: 73] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Advances in sequencing techniques and statistical methods have made it possible not only to predict sequences of ancestral proteins but also to identify thousands of mutations in the human exome, some of which are disease associated. These developments have motivated numerous theories and raised many questions regarding the fundamental principles behind protein evolution, which have been traditionally investigated horizontally using the tip of the phylogenetic tree through comparative studies of extant proteins within a family. In this article, we review a vertical comparison of the modern and resurrected ancestral proteins. We focus mainly on the dynamical properties responsible for a protein's ability to adapt new functions in response to environmental changes. Using the Dynamic Flexibility Index and the Dynamic Coupling Index to quantify the relative flexibility and dynamic coupling at a site-specific, single-amino-acid level, we provide evidence that the migration of hinges, which are often functionally critical rigid sites, is a mechanism through which proteins can rapidly evolve. Additionally, we show that disease-associated mutations in proteins often result in flexibility changes even at positions distal from mutational sites, particularly in the modulation of active site dynamics.
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Affiliation(s)
- Paul Campitelli
- Center for Biological Physics, Department of Physics, Arizona State University, Tempe, Arizona 85281, USA; , ,
| | - Tushar Modi
- Center for Biological Physics, Department of Physics, Arizona State University, Tempe, Arizona 85281, USA; , ,
| | - Sudhir Kumar
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, Pennsylvania 19122, USA; .,Department of Biology, Temple University, Philadelphia, Pennsylvania 19122, USA.,Center for Excellence in Genome Medicine and Research, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - S Banu Ozkan
- Center for Biological Physics, Department of Physics, Arizona State University, Tempe, Arizona 85281, USA; , ,
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6
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Bramer D, Wei GW. Multiscale weighted colored graphs for protein flexibility and rigidity analysis. J Chem Phys 2018; 148:054103. [PMID: 29421884 DOI: 10.1063/1.5016562] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Protein structural fluctuation, measured by Debye-Waller factors or B-factors, is known to correlate to protein flexibility and function. A variety of methods has been developed for protein Debye-Waller factor prediction and related applications to domain separation, docking pose ranking, entropy calculation, hinge detection, stability analysis, etc. Nevertheless, none of the current methodologies are able to deliver an accuracy of 0.7 in terms of the Pearson correlation coefficients averaged over a large set of proteins. In this work, we introduce a paradigm-shifting geometric graph model, multiscale weighted colored graph (MWCG), to provide a new generation of computational algorithms to significantly change the current status of protein structural fluctuation analysis. Our MWCG model divides a protein graph into multiple subgraphs based on interaction types between graph nodes and represents the protein rigidity by generalized centralities of subgraphs. MWCGs not only predict the B-factors of protein residues but also accurately analyze the flexibility of all atoms in a protein. The MWCG model is validated over a number of protein test sets and compared with many standard methods. An extensive numerical study indicates that the proposed MWCG offers an accuracy of over 0.8 and thus provides perhaps the first reliable method for estimating protein flexibility and B-factors. It also simultaneously predicts all-atom flexibility in a molecule.
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Affiliation(s)
- David Bramer
- Department of Mathematics, Michigan State University, East Lansing, Michigan 48824, USA
| | - Guo-Wei Wei
- Department of Mathematics, Michigan State University, East Lansing, Michigan 48824, USA
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7
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Modi T, Huihui J, Ghosh K, Ozkan SB. Ancient thioredoxins evolved to modern-day stability-function requirement by altering native state ensemble. Philos Trans R Soc Lond B Biol Sci 2018; 373:20170184. [PMID: 29735738 PMCID: PMC5941179 DOI: 10.1098/rstb.2017.0184] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/20/2018] [Indexed: 02/06/2023] Open
Abstract
Thioredoxins (THRXs)-small globular proteins that reduce other proteins-are ubiquitous in all forms of life, from Archaea to mammals. Although ancestral thioredoxins share sequential and structural similarity with the modern-day (extant) homologues, they exhibit significantly different functional activity and stability. We investigate this puzzle by comparative studies of their (ancient and modern-day THRXs') native state ensemble, as quantified by the dynamic flexibility index (DFI), a metric for the relative resilience of an amino acid to perturbations in the rest of the protein. Clustering proteins using DFI profiles strongly resemble an alternative classification scheme based on their activity and stability. The DFI profiles of the extant proteins are substantially different around the α3, α4 helices and catalytic regions. Likewise, allosteric coupling of the active site with the rest of the protein is different between ancient and extant THRXs, possibly explaining the decreased catalytic activity at low pH with evolution. At a global level, we note that the population of low-flexibility (called hinges) and high-flexibility sites increases with evolution. The heterogeneity (quantified by the variance) in DFI distribution increases with the decrease in the melting temperature typically associated with the evolution of ancient proteins to their modern-day counterparts.This article is part of a discussion meeting issue 'Allostery and molecular machines'.
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Affiliation(s)
- Tushar Modi
- Department of Physics and Center for Biological Physics, Arizona State University, Tempe, AZ 85281, USA
| | - Jonathan Huihui
- Department of Physics and Astronomy, University of Denver, Denver, CO 80209, USA
| | - Kingshuk Ghosh
- Department of Physics and Astronomy, University of Denver, Denver, CO 80209, USA
| | - S Banu Ozkan
- Department of Physics and Center for Biological Physics, Arizona State University, Tempe, AZ 85281, USA
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8
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Manjunath GP, Ramanujam PL, Galande S. Structure function relations in PDZ-domain-containing proteins: Implications for protein networks in cellular signalling. J Biosci 2018; 43:155-171. [PMID: 29485124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Protein scaffolds as essential backbones for organization of supramolecular signalling complexes are a recurrent theme in several model systems. Scaffold proteins preferentially employ linear peptide binding motifs for recruiting their interaction partners. PDZ domains are one of the more commonly encountered peptide binding domains in several proteins including those involved in scaffolding functions. This domain is known for its promiscuity both in terms of ligand selection, mode of interaction with its ligands as well as its association with other protein interaction domains. PDZ domains are subject to several means of regulations by virtue of their functional diversity. Additionally, the PDZ domains are refractive to the effect of mutations and maintain their three-dimensional architecture under extreme mutational load. The biochemical and biophysical basis for this selectivity as well as promiscuity has been investigated and reviewed extensively. The present review focuses on the plasticity inherent in PDZ domains and its implications for modular organization as well as evolution of cellular signalling pathways in higher eukaryotes.
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Affiliation(s)
- G P Manjunath
- Indian Institute of Science Education and Research, Pune 411 008, India
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9
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Structure function relations in PDZ-domain-containing proteins: Implications for protein networks in cellular signalling. J Biosci 2017. [DOI: 10.1007/s12038-017-9727-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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10
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Incorporation of side chain flexibility into protein binding pockets using MTflex. Bioorg Med Chem 2016; 24:4978-4987. [DOI: 10.1016/j.bmc.2016.08.030] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2016] [Revised: 08/16/2016] [Accepted: 08/18/2016] [Indexed: 01/15/2023]
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11
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Xia K, Opron K, Wei GW. Multiscale Gaussian network model (mGNM) and multiscale anisotropic network model (mANM). J Chem Phys 2016; 143:204106. [PMID: 26627949 DOI: 10.1063/1.4936132] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Gaussian network model (GNM) and anisotropic network model (ANM) are some of the most popular methods for the study of protein flexibility and related functions. In this work, we propose generalized GNM (gGNM) and ANM methods and show that the GNM Kirchhoff matrix can be built from the ideal low-pass filter, which is a special case of a wide class of correlation functions underpinning the linear scaling flexibility-rigidity index (FRI) method. Based on the mathematical structure of correlation functions, we propose a unified framework to construct generalized Kirchhoff matrices whose matrix inverse leads to gGNMs, whereas, the direct inverse of its diagonal elements gives rise to FRI method. With this connection, we further introduce two multiscale elastic network models, namely, multiscale GNM (mGNM) and multiscale ANM (mANM), which are able to incorporate different scales into the generalized Kirchhoff matrices or generalized Hessian matrices. We validate our new multiscale methods with extensive numerical experiments. We illustrate that gGNMs outperform the original GNM method in the B-factor prediction of a set of 364 proteins. We demonstrate that for a given correlation function, FRI and gGNM methods provide essentially identical B-factor predictions when the scale value in the correlation function is sufficiently large. More importantly, we reveal intrinsic multiscale behavior in protein structures. The proposed mGNM and mANM are able to capture this multiscale behavior and thus give rise to a significant improvement of more than 11% in B-factor predictions over the original GNM and ANM methods. We further demonstrate the benefits of our mGNM through the B-factor predictions of many proteins that fail the original GNM method. We show that the proposed mGNM can also be used to analyze protein domain separations. Finally, we showcase the ability of our mANM for the analysis of protein collective motions.
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Affiliation(s)
- Kelin Xia
- Department of Mathematics, Michigan State University, East Lansing, Michigan 48824, USA
| | - Kristopher Opron
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 48824, USA
| | - Guo-Wei Wei
- Mathematical Biosciences Institute, The Ohio State University, Columbus, Ohio 43210, USA
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12
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Anselmi M, Pisabarro MT. Exploring Multiple Binding Modes Using Confined Replica Exchange Molecular Dynamics. J Chem Theory Comput 2016; 11:3906-18. [PMID: 26574471 DOI: 10.1021/acs.jctc.5b00253] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Molecular docking is extensively applied to determine the position of a ligand on its receptor despite the rather poor correspondence between docking scores and experimental binding affinities found in several studies, especially for systems structurally unrelated with those used in the scoring functions' training sets. Here, we present a method for the prediction of binding modes and binding free energies, which uses replica exchange molecular dynamics in combination with a receptor-shaped piecewise potential, confining the ligand in the proximity of the receptor surface and limiting the accessible conformational space of interest. We assess our methodology with a set of protein receptor-ligand test cases. In every case studied, the method is able to locate the ligand on the experimentally known receptor binding site, and it gives as output the binding free energy. The added value of our approach with respect to other available methods is that it quickly performs a conformational space search, providing a set of bound (or unbound) configurations, which can be used to determine phenomenological structural and energetic properties of an experimental binding state as a result of contributions provided by diversified multiple binding poses.
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Affiliation(s)
- Massimiliano Anselmi
- Structural Bioinformatics, BIOTEC TU Dresden , Tatzberg 47-51, 01307 Dresden, Germany.,Dipartimento di Scienze e Tecnologie Chimiche, Università di Roma "Tor Vergata" , Via della Ricerca Scientifica, 00133 Rome, Italy
| | - M Teresa Pisabarro
- Structural Bioinformatics, BIOTEC TU Dresden , Tatzberg 47-51, 01307 Dresden, Germany
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13
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Opron K, Xia K, Burton Z, Wei GW. Flexibility-rigidity index for protein-nucleic acid flexibility and fluctuation analysis. J Comput Chem 2016; 37:1283-95. [PMID: 26927815 PMCID: PMC5844491 DOI: 10.1002/jcc.24320] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2015] [Revised: 12/02/2015] [Accepted: 01/17/2016] [Indexed: 12/29/2022]
Abstract
Protein-nucleic acid complexes are important for many cellular processes including the most essential functions such as transcription and translation. For many protein-nucleic acid complexes, flexibility of both macromolecules has been shown to be critical for specificity and/or function. The flexibility-rigidity index (FRI) has been proposed as an accurate and efficient approach for protein flexibility analysis. In this article, we introduce FRI for the flexibility analysis of protein-nucleic acid complexes. We demonstrate that a multiscale strategy, which incorporates multiple kernels to capture various length scales in biomolecular collective motions, is able to significantly improve the state of art in the flexibility analysis of protein-nucleic acid complexes. We take the advantage of the high accuracy and O(N) computational complexity of our multiscale FRI method to investigate the flexibility of ribosomal subunits, which are difficult to analyze by alternative approaches. An anisotropic FRI approach, which involves localized Hessian matrices, is utilized to study the translocation dynamics in an RNA polymerase.
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Affiliation(s)
- Kristopher Opron
- Department of Biochemistry and Molecular Biology, Michigan State University, MI 48824, USA
| | - Kelin Xia
- Department of Mathematics Michigan State University, MI 48824, USA
| | - Zach Burton
- Department of Biochemistry and Molecular Biology, Michigan State University, MI 48824, USA
| | - Guo-Wei Wei
- Mathematical Biosciences Institute The Ohio State University, Columbus, Ohio 43210, USA
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14
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Bolia A, Ozkan SB. Adaptive BP-Dock: An Induced Fit Docking Approach for Full Receptor Flexibility. J Chem Inf Model 2016; 56:734-46. [PMID: 26971620 DOI: 10.1021/acs.jcim.5b00587] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
We present an induced fit docking approach called Adaptive BP-Dock that integrates perturbation response scanning (PRS) with the flexible docking protocol of RosettaLigand in an adaptive manner. We first perturb the binding pocket residues of a receptor and obtain a new conformation based on the residue response fluctuation profile using PRS. Next, we dock a ligand to this new conformation by RosettaLigand, where we repeat these steps for several iterations. We test this approach on several protein test sets including difficult unbound docking cases such as HIV-1 reverse transcriptase and HIV-1 protease. Adaptive BP-Dock results show better correlation with experimental binding affinities compared to other docking protocols. Overall, the results imply that Adaptive BP-Dock can easily capture binding induced conformational changes by simultaneous sampling of protein and ligand conformations. This can provide faster and efficient docking of novel targets for rational drug design.
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Affiliation(s)
- Ashini Bolia
- Department of Chemistry and Biochemistry, Arizona State University , Tempe, Arizona 85287, United States
| | - S Banu Ozkan
- Department of Physics, Center for Biological Physics, Arizona State University , Tempe, Arizona 85287, United States
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15
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Li Z, Bolia A, Maxwell JD, Bobkov AA, Ghirlanda G, Ozkan SB, Margulis CJ. A Rigid Hinge Region Is Necessary for High-Affinity Binding of Dimannose to Cyanovirin and Associated Constructs. Biochemistry 2015; 54:6951-60. [PMID: 26507789 DOI: 10.1021/acs.biochem.5b00635] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Mutations in the hinge region of cyanovirin-N (CVN) dictate its preferential oligomerization state. Constructs with the Pro51Gly mutation preferentially exist as monomers, whereas wild-type cyanovirin can form domain-swapped dimers under certain conditions. Because the hinge region is an integral part of the high-affinity binding site of CVN, we investigated whether this mutation affects the shape, flexibility, and binding affinity of domain B for dimannose. Our studies indicate that the capability of monomeric wild-type CVN to resist mechanical perturbations is enhanced when compared to that of constructs in which the hinge region is more flexible. Our computational results also show that enhanced flexibility leads to blocking of the binding site by allowing different rotational isomeric states of Asn53. Moreover, at higher temperatures, this observed flexibility leads to an interaction between Asn53 and Asn42, further hindering access to the binding site. On the basis of these results, we predicted that binding affinity for dimannose would be more favorable for cyanovirin constructs containing a wild-type hinge region, whereas affinity would be impaired in the case of mutants containing Pro51Gly. Experimental characterization by isothermal titration calorimetry of a set of cyanovirin mutants confirms this hypothesis. Those possessing the Pro51Gly mutation are consistently inferior binders.
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Affiliation(s)
- Zhen Li
- Department of Chemistry, University of Iowa , Iowa City, Iowa 52242, United States
| | - Ashini Bolia
- Department of Chemistry and Biochemistry, Arizona State University , Tempe, Arizona 85287-1604, United States
| | - Jason D Maxwell
- Department of Chemistry and Biochemistry, Arizona State University , Tempe, Arizona 85287-1604, United States
| | - Andrey A Bobkov
- Sanford Burnham Medical Research Institute , 10901 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Giovanna Ghirlanda
- Department of Chemistry and Biochemistry, Arizona State University , Tempe, Arizona 85287-1604, United States
| | - S Banu Ozkan
- Center for Biological Physics, Department of Physics, Arizona State University , Tempe, Arizona 85287, United States
| | - Claudio J Margulis
- Department of Chemistry, University of Iowa , Iowa City, Iowa 52242, United States
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16
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Grosso M, Kalstein A, Parisi G, Roitberg AE, Fernandez-Alberti S. On the analysis and comparison of conformer-specific essential dynamics upon ligand binding to a protein. J Chem Phys 2015; 142:245101. [DOI: 10.1063/1.4922925] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Affiliation(s)
- Marcos Grosso
- Universidad Nacional de Quilmes, Roque Saenz Peña 352, B1876BXD Bernal, Argentina
| | - Adrian Kalstein
- Universidad Nacional de Quilmes, Roque Saenz Peña 352, B1876BXD Bernal, Argentina
| | - Gustavo Parisi
- Universidad Nacional de Quilmes, Roque Saenz Peña 352, B1876BXD Bernal, Argentina
| | - Adrian E. Roitberg
- Departments of Physics and Chemistry, University of Florida, Gainesville, Florida 32611, USA
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17
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Opron K, Xia K, Wei GW. Fast and anisotropic flexibility-rigidity index for protein flexibility and fluctuation analysis. J Chem Phys 2015; 140:234105. [PMID: 24952521 DOI: 10.1063/1.4882258] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Protein structural fluctuation, typically measured by Debye-Waller factors, or B-factors, is a manifestation of protein flexibility, which strongly correlates to protein function. The flexibility-rigidity index (FRI) is a newly proposed method for the construction of atomic rigidity functions required in the theory of continuum elasticity with atomic rigidity, which is a new multiscale formalism for describing excessively large biomolecular systems. The FRI method analyzes protein rigidity and flexibility and is capable of predicting protein B-factors without resorting to matrix diagonalization. A fundamental assumption used in the FRI is that protein structures are uniquely determined by various internal and external interactions, while the protein functions, such as stability and flexibility, are solely determined by the structure. As such, one can predict protein flexibility without resorting to the protein interaction Hamiltonian. Consequently, bypassing the matrix diagonalization, the original FRI has a computational complexity of O(N(2)). This work introduces a fast FRI (fFRI) algorithm for the flexibility analysis of large macromolecules. The proposed fFRI further reduces the computational complexity to O(N). Additionally, we propose anisotropic FRI (aFRI) algorithms for the analysis of protein collective dynamics. The aFRI algorithms permit adaptive Hessian matrices, from a completely global 3N × 3N matrix to completely local 3 × 3 matrices. These 3 × 3 matrices, despite being calculated locally, also contain non-local correlation information. Eigenvectors obtained from the proposed aFRI algorithms are able to demonstrate collective motions. Moreover, we investigate the performance of FRI by employing four families of radial basis correlation functions. Both parameter optimized and parameter-free FRI methods are explored. Furthermore, we compare the accuracy and efficiency of FRI with some established approaches to flexibility analysis, namely, normal mode analysis and Gaussian network model (GNM). The accuracy of the FRI method is tested using four sets of proteins, three sets of relatively small-, medium-, and large-sized structures and an extended set of 365 proteins. A fifth set of proteins is used to compare the efficiency of the FRI, fFRI, aFRI, and GNM methods. Intensive validation and comparison indicate that the FRI, particularly the fFRI, is orders of magnitude more efficient and about 10% more accurate overall than some of the most popular methods in the field. The proposed fFRI is able to predict B-factors for α-carbons of the HIV virus capsid (313 236 residues) in less than 30 seconds on a single processor using only one core. Finally, we demonstrate the application of FRI and aFRI to protein domain analysis.
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Affiliation(s)
- Kristopher Opron
- Department of Biochemistry and Molecular Biology, Michigan State University, Michigan 48824, USA
| | - Kelin Xia
- Department of Mathematics, Michigan State University, Michigan 48824, USA
| | - Guo-Wei Wei
- Department of Biochemistry and Molecular Biology, Michigan State University, Michigan 48824, USA
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18
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Bolia A, Woodrum BW, Cereda A, Ruben MA, Wang X, Ozkan SB, Ghirlanda G. A flexible docking scheme efficiently captures the energetics of glycan-cyanovirin binding. Biophys J 2014; 106:1142-51. [PMID: 24606938 DOI: 10.1016/j.bpj.2014.01.040] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2013] [Revised: 01/08/2014] [Accepted: 01/10/2014] [Indexed: 01/10/2023] Open
Abstract
Cyanovirin-N (CVN), a cyanobacterial lectin, exemplifies a class of antiviral agents that inhibit HIV by binding to the highly glycosylated envelope protein gp120. Here, we investigate the energetics of glycan recognition using a computationally inexpensive flexible docking approach, backbone perturbation docking (BP-Dock). We benchmarked our method using two mutants of CVN: P51G-m4-CVN, which binds dimannose with high affinity through domain B, and CVN((mutDB)), in which binding to domain B has been abolished through mutation of five polar residues to small nonpolar side chains. We investigated the energetic contribution of these polar residues along with the additional position 53 by docking dimannose to single-point CVN mutant models. Analysis of the docking simulations indicated that the E41A/G and T57A mutations led to a significant decrease in binding energy scores due to rearrangements of the hydrogen-bond network that reverberated throughout the binding cavity. N42A decreased the binding score to a level comparable to that of CVN((mutDB)) by affecting the integrity of the local protein structure. In contrast, N53S resulted in a high binding energy score, similar to P51G-m4-CVN. Experimental characterization of the five mutants by NMR spectroscopy confirmed the binding affinity pattern predicted by BP-Dock. Despite their mostly conserved fold and stability, E41A, E41G, and T57A displayed dissociation constants in the millimolar range. N53S showed a binding constant in the low micromolar range, similar to that observed for P51G-m4-CVN. No binding was observed for N42A. Our results show that BP-Dock is a useful tool for rapidly screening the relative binding affinity pattern of in silico-designed mutants compared with wild-type, supporting its use to design novel mutants with enhanced binding properties.
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Affiliation(s)
- Ashini Bolia
- Department of Chemistry and Biochemistry, Arizona State University, Tempe, Arizona
| | - Brian W Woodrum
- Department of Chemistry and Biochemistry, Arizona State University, Tempe, Arizona
| | - Angelo Cereda
- Department of Chemistry and Biochemistry, Arizona State University, Tempe, Arizona
| | - Melissa A Ruben
- Department of Chemistry and Biochemistry, Arizona State University, Tempe, Arizona
| | - Xu Wang
- Department of Chemistry and Biochemistry, Arizona State University, Tempe, Arizona
| | - S Banu Ozkan
- Center for Biological Physics, Department of Physics, Arizona State University, Tempe, Arizona.
| | - Giovanna Ghirlanda
- Center for Biological Physics, Department of Physics, Arizona State University, Tempe, Arizona.
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19
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Zou T, Risso VA, Gavira JA, Sanchez-Ruiz JM, Ozkan SB. Evolution of conformational dynamics determines the conversion of a promiscuous generalist into a specialist enzyme. Mol Biol Evol 2014; 32:132-43. [PMID: 25312912 DOI: 10.1093/molbev/msu281] [Citation(s) in RCA: 101] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
β-Lactamases are produced by many modern bacteria as a mechanism of resistance toward β-lactam antibiotics, the most common antibiotics in use. β-Lactamases, however, are ancient enzymes that originated billions of years ago. Recently, proteins corresponding to 2- to 3-Gy-old Precambrian nodes in the evolution of Class A β-lactamases have been prepared and shown to be moderately efficient promiscuous catalysts, able to degrade a variety of antibiotics with catalytic efficiency levels similar to those of an average modern enzyme. Remarkably, there are few structural differences (in particular at the active-site regions) between the resurrected enzymes and a penicillin-specialist modern β-lactamase. Here, we propose that the ancestral promiscuity originates from conformational dynamics. We investigate the differences in conformational dynamics of the ancient and extant β-lactamases through MD simulations and quantify the contribution of each position to functionally related dynamics through Dynamic Flexibility Index. The modern TEM-1 lactamase shows a comparatively rigid active-site region, likely reflecting adaptation for efficient degradation of a specific substrate (penicillin), whereas enhanced deformability at the active-site neighborhood in the ancestral resurrected proteins likely accounts for the binding and subsequent degradation of antibiotic molecules of different size and shape. Clustering of the conformational dynamics on the basis of Principal Component Analysis is in agreement with the functional divergence, as the ancient β-lactamases cluster together, separated from their modern descendant. Finally, our analysis leads to testable predictions, as sites of potential relevance for the evolution of dynamics are identified and mutations at those sites are expected to alter substrate-specificity.
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Affiliation(s)
- Taisong Zou
- Center for Biological Physics, Department of Physics, Arizona State University
| | - Valeria A Risso
- Departamento de Química Física, Facultad de Ciencias, Universidad de Granada, Granada, Spain
| | - Jose A Gavira
- Laboratorio de Estudios Cristalográficos, Instituto Andaluz de Ciencias de la Tierra (Consejo Superior de Investigaciones Científicas-Universidad de Granada), Granada, Spain
| | - Jose M Sanchez-Ruiz
- Departamento de Química Física, Facultad de Ciencias, Universidad de Granada, Granada, Spain
| | - S Banu Ozkan
- Center for Biological Physics, Department of Physics, Arizona State University
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20
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Ostermeir K, Zacharias M. Hamiltonian replica exchange combined with elastic network analysis to enhance global domain motions in atomistic molecular dynamics simulations. Proteins 2014; 82:3410-9. [DOI: 10.1002/prot.24695] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2014] [Revised: 09/10/2014] [Accepted: 09/11/2014] [Indexed: 12/20/2022]
Affiliation(s)
- Katja Ostermeir
- Physik-Department T38; Technische Universität München; 85748 Garching Germany
| | - Martin Zacharias
- Physik-Department T38; Technische Universität München; 85748 Garching Germany
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21
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Campbell AJ, Lamb ML, Joseph-McCarthy D. Ensemble-based docking using biased molecular dynamics. J Chem Inf Model 2014; 54:2127-38. [PMID: 24881672 DOI: 10.1021/ci400729j] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
Proteins are dynamic molecules, and understanding their movements, especially as they relate to molecular recognition and protein-ligand interactions, poses a significant challenge to structure-based drug discovery. In most instances, protein flexibility is underrepresented in computer-aided drug design due to uncertainties on how it should be accurately modeled as well as the computational cost associated with attempting to incorporate flexibility in the calculations. One approach that aims to address these issues is ensemble-based docking. With this technique, ligands are docked to an ensemble of rigid protein conformations. Molecular dynamics (MD) simulations can be used to generate the ensemble of protein conformations for the subsequent docking. Here we present a novel approach that uses biased-MD simulations to generate the docking ensemble. The MD simulations are biased toward an initial protein-ligand X-ray complex structure. The biasing maintains some of the original crystallographic pocket-ligand information and thereby enhances sampling of the more relevant conformational space of the protein. Resulting trajectories are clustered to select a representative set of protein conformations, and ligands are docked to that reduced set of conformations. Cross-docking to this ensemble and then selecting the lowest scoring pose enables reliable identification of the correct binding mode. Various levels of biasing are investigated, and the method is validated for cyclin-dependent kinase 2 and factor Xa.
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Affiliation(s)
- Arthur J Campbell
- AstraZeneca , R&D Boston, 35 Gatehouse Drive, Waltham, Massachusetts 02451, United States
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22
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Zimmermann MT, Jernigan RL. Elastic network models capture the motions apparent within ensembles of RNA structures. RNA (NEW YORK, N.Y.) 2014; 20:792-804. [PMID: 24759093 PMCID: PMC4024634 DOI: 10.1261/rna.041269.113] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
The role of structure and dynamics in mechanisms for RNA becomes increasingly important. Computational approaches using simple dynamics models have been successful at predicting the motions of proteins and are often applied to ribonucleo-protein complexes but have not been thoroughly tested for well-packed nucleic acid structures. In order to characterize a true set of motions, we investigate the apparent motions from 16 ensembles of experimentally determined RNA structures. These indicate a relatively limited set of motions that are captured by a small set of principal components (PCs). These limited motions closely resemble the motions computed from low frequency normal modes from elastic network models (ENMs), either at atomic or coarse-grained resolution. Various ENM model types, parameters, and structure representations are tested here against the experimental RNA structural ensembles, exposing differences between models for proteins and for folded RNAs. Differences in performance are seen, depending on the structure alignment algorithm used to generate PCs, modulating the apparent utility of ENMs but not significantly impacting their ability to generate functional motions. The loss of dynamical information upon coarse-graining is somewhat larger for RNAs than for globular proteins, indicating, perhaps, the lower cooperativity of the less densely packed RNA. However, the RNA structures show less sensitivity to the elastic network model parameters than do proteins. These findings further demonstrate the utility of ENMs and the appropriateness of their application to well-packed RNA-only structures, justifying their use for studying the dynamics of ribonucleo-proteins, such as the ribosome and regulatory RNAs.
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Affiliation(s)
- Michael T. Zimmermann
- Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, Iowa 50011, USA
- Bioinformatics and Computational Biology Interdepartmental Graduate Program, Iowa State University, Ames, Iowa 50011, USA
| | - Robert L. Jernigan
- Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, Iowa 50011, USA
- Bioinformatics and Computational Biology Interdepartmental Graduate Program, Iowa State University, Ames, Iowa 50011, USA
- Corresponding authorE-mail
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23
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The antiviral lectin cyanovirin-N: probing multivalency and glycan recognition through experimental and computational approaches. Biochem Soc Trans 2014; 41:1170-6. [PMID: 24059504 DOI: 10.1042/bst20130154] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
CVN (cyanovirin-N), a small lectin isolated from cyanobacteria, exemplifies a novel class of anti-HIV agents that act by binding to the highly glycosylated envelope protein gp120 (glycoprotein 120), resulting in inhibition of the crucial viral entry step. In the present review, we summarize recent work in our laboratory and others towards determining the crucial role of multivalency in the antiviral activity, and we discuss features that contribute to the high specificity and affinity for the glycan ligand observed in CVN. An integrated approach that encompasses structural determination, mutagenesis analysis and computational work holds particular promise to clarify aspects of the interactions between CVN and glycans.
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24
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Bolia A, Gerek ZN, Ozkan SB. BP-Dock: a flexible docking scheme for exploring protein-ligand interactions based on unbound structures. J Chem Inf Model 2014; 54:913-25. [PMID: 24380381 DOI: 10.1021/ci4004927] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Molecular docking serves as an important tool in modeling protein-ligand interactions. However, it is still challenging to incorporate overall receptor flexibility, especially backbone flexibility, in docking due to the large conformational space that needs to be sampled. To overcome this problem, we developed a novel flexible docking approach, BP-Dock (Backbone Perturbation-Dock) that can integrate both backbone and side chain conformational changes induced by ligand binding through a multi-scale approach. In the BP-Dock method, we mimic the nature of binding-induced events as a first-order approximation by perturbing the residues along the protein chain with a small Brownian kick one at a time. The response fluctuation profile of the chain upon these perturbations is computed using the perturbation response scanning method. These response fluctuation profiles are then used to generate binding-induced multiple receptor conformations for ensemble docking. To evaluate the performance of BP-Dock, we applied our approach on a large and diverse data set using unbound structures as receptors. We also compared the BP-Dock results with bound and unbound docking, where overall receptor flexibility was not taken into account. Our results highlight the importance of modeling backbone flexibility in docking for recapitulating the experimental binding affinities, especially when an unbound structure is used. With BP-Dock, we can generate a wide range of binding site conformations realized in nature even in the absence of a ligand that can help us to improve the accuracy of unbound docking. We expect that our fast and efficient flexible docking approach may further aid in our understanding of protein-ligand interactions as well as virtual screening of novel targets for rational drug design.
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Affiliation(s)
- Ashini Bolia
- Center for Biological Physics, Department of Physics, Arizona State University , Tempe, Arizona 85287, United States
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25
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Jiang Y, Lu G, Trescott LR, Hou Y, Guan X, Wang S, Stamenkovich A, Brunzelle J, Sirinupong N, Li C, Yang Z. New conformational state of NHERF1-CXCR2 signaling complex captured by crystal lattice trapping. PLoS One 2013; 8:e81904. [PMID: 24339979 PMCID: PMC3858284 DOI: 10.1371/journal.pone.0081904] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2013] [Accepted: 10/18/2013] [Indexed: 11/18/2022] Open
Abstract
NHERF1 is a PDZ adaptor protein that scaffolds the assembly of diverse signaling complexes and has been implicated in many cancers. However, little is known about the mechanism responsible for its scaffolding promiscuity or its ability to bind to multiple targets. Computational studies have indicated that PDZ promiscuity may be attributed to its conformational dynamics, but experimental evidence for this relationship remains very limited. Here we examine the conformational flexibility of the NHERF1 PDZ1 domain using crystal lattice trapping via solving PDZ1 structure of a new crystal form. The structure, together with prior PDZ1 structures of a different space group, reveals that 4 of 11 ligand-interacting residues undergo significant crystal packing-induced structural changes. Most of these residues correspond to the residues involved in allosteric transition when a peptide ligand binds. In addition, a subtle difference in ligand conformations causes the same peptide to bind in slightly different modes in different crystal forms. These findings indicate that substantial structural flexibility is present in the PDZ1 peptide-binding pocket, and the structural substate trapped in the present crystal form can be utilized to represent the conformational space accessible to the protein. Such knowledge will be critical for drug design against the NHERF1 PDZ1 domain, highlighting the continued need for experimentally determined PDZ1-ligand complexes.
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Affiliation(s)
- Yuanyuan Jiang
- Department of Biochemistry and Molecular Biology, Wayne State University School of Medicine, Detroit, Michigan, United States of America
| | - Guorong Lu
- Department of Biochemistry and Molecular Biology, Wayne State University School of Medicine, Detroit, Michigan, United States of America
| | - Laura R. Trescott
- Department of Biochemistry and Molecular Biology, Wayne State University School of Medicine, Detroit, Michigan, United States of America
| | - Yuning Hou
- Department of Biochemistry and Molecular Biology, Wayne State University School of Medicine, Detroit, Michigan, United States of America
| | - Xiaoqing Guan
- Department of Biochemistry and Molecular Biology, Wayne State University School of Medicine, Detroit, Michigan, United States of America
| | - Shuo Wang
- Department of Biochemistry and Molecular Biology, Wayne State University School of Medicine, Detroit, Michigan, United States of America
| | - Angelique Stamenkovich
- Department of Biochemistry and Molecular Biology, Wayne State University School of Medicine, Detroit, Michigan, United States of America
| | - Joseph Brunzelle
- Advance Photon Source, Argonne National Lab, Argonne, Illinois, United States of America
| | - Nualpun Sirinupong
- Nutraceuticals and Functional Food Research and Development Center, Prince of Songkla University, Hat-Yai, Songkhla, Thailand
| | - Chunying Li
- Department of Biochemistry and Molecular Biology, Wayne State University School of Medicine, Detroit, Michigan, United States of America
- * E-mail: (ZY); (CL)
| | - Zhe Yang
- Department of Biochemistry and Molecular Biology, Wayne State University School of Medicine, Detroit, Michigan, United States of America
- * E-mail: (ZY); (CL)
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26
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The role of flexibility and conformational selection in the binding promiscuity of PDZ domains. PLoS Comput Biol 2012; 8:e1002749. [PMID: 23133356 PMCID: PMC3486844 DOI: 10.1371/journal.pcbi.1002749] [Citation(s) in RCA: 59] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2012] [Accepted: 09/02/2012] [Indexed: 11/23/2022] Open
Abstract
In molecular recognition, it is often the case that ligand binding is coupled to conformational change in one or both of the binding partners. Two hypotheses describe the limiting cases involved; the first is the induced fit and the second is the conformational selection model. The conformational selection model requires that the protein adopts conformations that are similar to the ligand-bound conformation in the absence of ligand, whilst the induced-fit model predicts that the ligand-bound conformation of the protein is only accessible when the ligand is actually bound. The flexibility of the apo protein clearly plays a major role in these interpretations. For many proteins involved in signaling pathways there is the added complication that they are often promiscuous in that they are capable of binding to different ligand partners. The relationship between protein flexibility and promiscuity is an area of active research and is perhaps best exemplified by the PDZ domain family of proteins. In this study we use molecular dynamics simulations to examine the relationship between flexibility and promiscuity in five PDZ domains: the human Dvl2 (Dishevelled-2) PDZ domain, the human Erbin PDZ domain, the PDZ1 domain of InaD (inactivation no after-potential D protein) from fruit fly, the PDZ7 domain of GRIP1 (glutamate receptor interacting protein 1) from rat and the PDZ2 domain of PTP-BL (protein tyrosine phosphatase) from mouse. We show that despite their high structural similarity, the PDZ binding sites have significantly different dynamics. Importantly, the degree of binding pocket flexibility was found to be closely related to the various characteristics of peptide binding specificity and promiscuity of the five PDZ domains. Our findings suggest that the intrinsic motions of the apo structures play a key role in distinguishing functional properties of different PDZ domains and allow us to make predictions that can be experimentally tested. Proteins that are capable of binding to many different ligands are said to have broad specificity. This is sometimes also referred to as promiscuity. Whether a protein is promiscuous or not can sometimes be readily explained by the structure of the protein and the ligand in terms of electrostatic and steric effects. Sometimes however, this simple interpretation can struggle to explain the experimentally observed data. A prominent case in point is the PDZ domains. These small protein domains bind to unstructured regions of other proteins and are involved in many signaling pathways. Some PDZ domains appear to be more promiscuous than others, but this has been difficult to explain purely on the basis of the composition of residues in the binding groove. In this work we examine the dynamics and conformational flexibility of five key PDZ domains and demonstrate that despite similar folds, these proteins can exhibit quite different dynamics. Furthermore the difference in the dynamic behavior appears to correlate with the observed promiscuity. Our findings suggest that knowledge of the dynamic behavior of the PDZs can be used to rationalize the extent of expected promiscuity. Such knowledge will be critical for drug design against PDZ domains.
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27
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Hawkins JC, Zhu H, Teyra J, Pisabarro MT. Reduced false positives in PDZ binding prediction using sequence and structural descriptors. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2012; 9:1492-1503. [PMID: 22508908 DOI: 10.1109/tcbb.2012.54] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
Abstract—Identifying the binding partners of proteins is a problem of fundamental importance in computational biology. The PDZ is one of the most common and well-studied protein binding domains, hence it is a perfect model system for designing protein binding predictors. The standard approach to identifying the binding partners of PDZ domains uses multiple sequence alignments to infer the set of contact residues that are used in a predictive model. We expand on the sequence alignment approach by incorporating structural information to generate descriptors of the binding site geometry. Furthermore, we generate a real-value score for binary predictions by applying a filter based on models that predict the probability distributions of contact residues at each of the canonical PDZ ligand binding positions. Under training cross validation, our model produced an order of magnitude more predictions at a false positive proportion (FPP) of 10 percent than our benchmark model chosen from the literature. Evaluated using an independent cross validation, with computationally predicted structures, our model was able to make five times as many predictions as the benchmark model, with a Matthews' correlation coefficient (MCC) of 0.33. In addition, our model achieved a false positive proportion of 0.14, while the benchmark model had a 0.25 false positive proportion.
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Affiliation(s)
- John C Hawkins
- Structural Bioinformatics, BIOTEC TU Dresden, Dresden, Germany.
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28
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Ho BK, Perahia D, Buckle AM. Hybrid approaches to molecular simulation. Curr Opin Struct Biol 2012; 22:386-93. [PMID: 22633678 DOI: 10.1016/j.sbi.2012.05.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2012] [Revised: 05/07/2012] [Accepted: 05/08/2012] [Indexed: 10/28/2022]
Abstract
Molecular dynamics (MD) simulation is an established method for studying the conformational changes that are important for protein function. Recent advances in hardware and software have allowed MD simulations over the same timescales as experiment, improving the agreement between theory and experiment to a large extent. However, running such simulations are costly, in terms of resources, storage, and trajectory analysis. There is still a place for techniques that involve short MD simulations. In order to overcome the sampling paucity of short time-scales, hybrid methods that include some form of MD simulation can exploit certain features of the system of interest, often combining experimental information in surprising ways. Here, we review some recent hybrid approaches to the simulation of proteins.
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Affiliation(s)
- Bosco K Ho
- Department of Biochemistry and Molecular Biology, Monash University, Clayton, Victoria 3800, Australia
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29
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Luck K, Charbonnier S, Travé G. The emerging contribution of sequence context to the specificity of protein interactions mediated by PDZ domains. FEBS Lett 2012; 586:2648-61. [PMID: 22709956 DOI: 10.1016/j.febslet.2012.03.056] [Citation(s) in RCA: 94] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2012] [Revised: 03/26/2012] [Accepted: 03/27/2012] [Indexed: 12/18/2022]
Abstract
The canonical binding mode of PDZ domains to target motifs involves a small interface, unlikely to fully account for PDZ-target interaction specificities. Here, we review recent work on sequence context, defined as the regions surrounding not only the PDZ domains but also their target motifs. We also address the theoretical problem of defining the core of PDZ domains and the practical issue of designing PDZ constructs. Sequence context is found to introduce structural diversity, to impact the stability and solubility of constructs, and to deeply influence binding affinity and specificity, thereby increasing the difficulty of predicting PDZ-motif interactions. We expect that sequence context will have similar importance for other protein interactions mediated by globular domains binding to short linear motifs.
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Affiliation(s)
- Katja Luck
- UMR 7242, Institut de Recherche de l'Ecole de Biotechnologie de Strasbourg, Bd Sébastien Brant, BP 10413, 67412 Illkirch, Cedex, France.
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30
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Bolia A, Gerek ZN, Keskin O, Banu Ozkan S, Dev KK. The binding affinities of proteins interacting with the PDZ domain of PICK1. Proteins 2012; 80:1393-408. [PMID: 22275068 DOI: 10.1002/prot.24034] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2011] [Revised: 12/30/2011] [Accepted: 01/03/2012] [Indexed: 11/09/2022]
Abstract
Protein interacting with C kinase (PICK1) is well conserved throughout evolution and plays a critical role in synaptic plasticity by regulating the trafficking and posttranslational modification of its interacting proteins. PICK1 contains a single PSD95/DlgA/Zo-1 (PDZ) protein-protein interaction domain, which is promiscuous and shown to interact with over 60 proteins, most of which play roles in neuronal function. Several reports have suggested the role of PICK1 in disorders such as epilepsy, pain, brain trauma and stroke, drug abuse and dependence, schizophrenia and psychosis. Importantly, lead compounds that block PICK1 interactions are also now becoming available. Here, a new modeling approach was developed to investigate binding affinities of PDZ interactions. Using these methods, the binding affinities of all major PICK1 interacting proteins are reported and the effects of PICK1 mutations on these interactions are described. These modeling methods have important implications in defining the binding properties of proteins interacting with PICK1 as well as the general structural requirements of PDZ interactions. The study also provides modeling methods to support in the drug design of ligands for PDZ domains, which may further aid in development of the family of PDZ domains as a drug target.
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Affiliation(s)
- Ashini Bolia
- Department of Physics, Center for Biological Physics, Arizona State University Tempe, Arizona, USA
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31
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Abstract
Explicitly accounting for target flexibility in docking still constitutes a difficult challenge due to the high dimensionality of the conformational space to be sampled. This especially applies to the high-throughput scenario, where the screening of hundreds of thousands compounds takes place. The use of multiple receptor conformations (MRCs) to perform ensemble docking in a sequential fashion is a simple but powerful approach that allows to incorporate binding site structural diversity in the docking process. Whenever enough experimental structures to build a diverse ensemble are not available, normal mode analysis provides an appealing and efficient approach to in silico generate MRCs by distortion along few low-frequency modes that represent collective mid- and large-scale displacements. In this way, the dimension of the conformational space to be sampled is heavily reduced. This methodology is especially suited to incorporate target flexibility at the backbone level. In this chapter, the main components of normal mode-based approaches in the context of ensemble docking are presented and explained, including the theoretical and practical considerations needed for the successful development and implementation of this methodology.
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Affiliation(s)
- Claudio N Cavasotto
- School of Biomedical Informatics, The University of Texas Health Center, Houston, TX, USA.
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Luck K, Fournane S, Kieffer B, Masson M, Nominé Y, Travé G. Putting into practice domain-linear motif interaction predictions for exploration of protein networks. PLoS One 2011; 6:e25376. [PMID: 22069443 PMCID: PMC3206016 DOI: 10.1371/journal.pone.0025376] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2011] [Accepted: 09/02/2011] [Indexed: 12/22/2022] Open
Abstract
PDZ domains recognise short sequence motifs at the extreme C-termini of proteins. A model based on microarray data has been recently published for predicting the binding preferences of PDZ domains to five residue long C-terminal sequences. Here we investigated the potential of this predictor for discovering novel protein interactions that involve PDZ domains. When tested on real negative data assembled from published literature, the predictor displayed a high false positive rate (FPR). We predicted and experimentally validated interactions between four PDZ domains derived from the human proteins MAGI1 and SCRIB and 19 peptides derived from human and viral C-termini of proteins. Measured binding intensities did not correlate with prediction scores, and the high FPR of the predictor was confirmed. Results indicate that limitations of the predictor may arise from an incomplete model definition and improper training of the model. Taking into account these limitations, we identified several novel putative interactions between PDZ domains of MAGI1 and SCRIB and the C-termini of the proteins FZD4, ARHGAP6, NET1, TANC1, GLUT7, MARCH3, MAS, ABC1, DLL1, TMEM215 and CYSLTR2. These proteins are localised to the membrane or suggested to act close to it and are often involved in G protein signalling. Furthermore, we showed that, while extension of minimal interacting domains or peptides toward tandem constructs or longer peptides never suppressed their ability to interact, the measured affinities and inferred specificity patterns often changed significantly. This suggests that if protein fragments interact, the full length proteins are also likely to interact, albeit possibly with altered affinities and specificities. Therefore, predictors dealing with protein fragments are promising tools for discovering protein interaction networks but their application to predict binding preferences within networks may be limited.
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Affiliation(s)
- Katja Luck
- Group Onco-Proteins, Institut de Recherche de l'Ecole de Biotechnologie de Strasbourg, 1, BP 10413, Illkirch, France
| | - Sadek Fournane
- Group Onco-Proteins, Institut de Recherche de l'Ecole de Biotechnologie de Strasbourg, 1, BP 10413, Illkirch, France
| | - Bruno Kieffer
- Biomolecular NMR group, Institut de Génétique et de Biologie Moléculaire et Cellulaire, 1, BP 10413, Illkirch, France
| | - Murielle Masson
- Group Onco-Proteins, Institut de Recherche de l'Ecole de Biotechnologie de Strasbourg, 1, BP 10413, Illkirch, France
| | - Yves Nominé
- Group Onco-Proteins, Institut de Recherche de l'Ecole de Biotechnologie de Strasbourg, 1, BP 10413, Illkirch, France
| | - Gilles Travé
- Group Onco-Proteins, Institut de Recherche de l'Ecole de Biotechnologie de Strasbourg, 1, BP 10413, Illkirch, France
- * E-mail:
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Ganjiwale AD, Rao GS, Cowsik SM. Molecular Modeling of Neurokinin B and Tachykinin NK3 Receptor Complex. J Chem Inf Model 2011; 51:2932-8. [DOI: 10.1021/ci2000264] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Affiliation(s)
- Anjali D. Ganjiwale
- School of Life Sciences, Jawaharlal Nehru University, New Delhi − 110 067, India
| | - Gita Subba Rao
- Department of Biophysics, All India Institute of Medical Sciences, New Delhi, India
| | - Sudha M. Cowsik
- School of Life Sciences, Jawaharlal Nehru University, New Delhi − 110 067, India
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Gerek ZN, Ozkan SB. Change in allosteric network affects binding affinities of PDZ domains: analysis through perturbation response scanning. PLoS Comput Biol 2011; 7:e1002154. [PMID: 21998559 PMCID: PMC3188487 DOI: 10.1371/journal.pcbi.1002154] [Citation(s) in RCA: 132] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2011] [Accepted: 06/22/2011] [Indexed: 01/27/2023] Open
Abstract
The allosteric mechanism plays a key role in cellular functions of several PDZ domain proteins (PDZs) and is directly linked to pharmaceutical applications; however, it is a challenge to elaborate the nature and extent of these allosteric interactions. One solution to this problem is to explore the dynamics of PDZs, which may provide insights about how intramolecular communication occurs within a single domain. Here, we develop an advancement of perturbation response scanning (PRS) that couples elastic network models with linear response theory (LRT) to predict key residues in allosteric transitions of the two most studied PDZs (PSD-95 PDZ3 domain and hPTP1E PDZ2 domain). With PRS, we first identify the residues that give the highest mean square fluctuation response upon perturbing the binding sites. Strikingly, we observe that the residues with the highest mean square fluctuation response agree with experimentally determined residues involved in allosteric transitions. Second, we construct the allosteric pathways by linking the residues giving the same directional response upon perturbation of the binding sites. The predicted intramolecular communication pathways reveal that PSD-95 and hPTP1E have different pathways through the dynamic coupling of different residue pairs. Moreover, our analysis provides a molecular understanding of experimentally observed hidden allostery of PSD-95. We show that removing the distal third alpha helix from the binding site alters the allosteric pathway and decreases the binding affinity. Overall, these results indicate that (i) dynamics plays a key role in allosteric regulations of PDZs, (ii) the local changes in the residue interactions can lead to significant changes in the dynamics of allosteric regulations, and (iii) this might be the mechanism that each PDZ uses to tailor their binding specificities regulation. PDZ domain proteins (PDZs) act as adapters in organizing functional protein complexes. Through dynamic interactions, PDZs play a key role in mediating key cellular functions in the cell, and they are linked to currently challenging diseases including Alzheimer's, Parkinson's and cancer. Moreover, they are associated with allosteric regulations in mediating signaling. Therefore, it is critical to have knowledge of how the allosteric transition occurs in PDZs. We investigate the allosteric response of the two most studied PDZs, PSD-95 and hPTP1E, using the perturbation response scanning (PRS) approach. The method treats the protein as an elastic network and uses linear response theory (LRT) to obtain residue fluctuations upon exerting directed random forces on selected residues. With this efficient and fast approach, we identify the key residues that mediate long-range communication and find the allosteric pathways. Although the structures of PSD-95 and hPTP1E are very similar, our analysis predicts that their allosteric pathways are different. We also observe a significant change in allosteric pathways and a decrease in binding affinity upon removal of the distal α3 helix of PSD-95. This approach enables us to understand how dynamic interactions play an important role in allosteric regulations.
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Affiliation(s)
- Z. Nevin Gerek
- Center for Biological Physics, Arizona State University, Tempe, Arizona, United States of America
- Department of Physics, Arizona State University, Tempe, Arizona, United States of America
| | - S. Banu Ozkan
- Center for Biological Physics, Arizona State University, Tempe, Arizona, United States of America
- Department of Physics, Arizona State University, Tempe, Arizona, United States of America
- * E-mail:
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Yuan P, Liang K, Ma B, Zheng N, Nussinov R, Huang J. Multiple-targeting and conformational selection in the estrogen receptor: computation and experiment. Chem Biol Drug Des 2011; 78:137-49. [PMID: 21443691 PMCID: PMC3115459 DOI: 10.1111/j.1747-0285.2011.01119.x] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Conformational selection is a primary mechanism in biomolecular recognition. The conformational ensemble may determine the ability of a drug to compete with a native ligand for a receptor target. Traditional docking procedures which use one or few protein structures are limited and may not be able to represent a complex competition among closely related protein receptors in agonist and antagonist ensembles. Here, we test a protocol aimed at selecting a drug candidate based on its ability to synergistically bind to distinct conformational states. We demonstrate, for the case of estrogen receptor α (ERα) and estrogen receptor β (ERβ), that the functional outcome of ligand binding can be inferred from its ability to simultaneously bind both ERα and ERβ in agonist and antagonist conformations as calculated docking scores. Combining a conformational selection method with an experimental reporter gene system in yeast, we propose that several phytoestrogens can be novel estrogen receptor β selective agonists. Our work proposes a computational protocol to select estrogen receptor subtype selective agonists. Compared with other models, present method gives the best prediction in ligands' function.
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Affiliation(s)
- Peng Yuan
- State Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan 430072, Hubei, China
| | - Kaiwei Liang
- State Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan 430072, Hubei, China
| | - Buyong Ma
- Center for Cancer Research Nanobiology Program, SAIC-Frederick, National Cancer Institute, Frederick, MD 21702,USA
| | - Nan Zheng
- State Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan 430072, Hubei, China
| | - Ruth Nussinov
- Center for Cancer Research Nanobiology Program, SAIC-Frederick, National Cancer Institute, Frederick, MD 21702,USA
- Department of Human Genetics and Molecular Medicine, Sackler Institute of Molecular Medicine, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel
| | - Jian Huang
- State Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan 430072, Hubei, China
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Nichols SE, Baron R, Ivetac A, McCammon JA. Predictive power of molecular dynamics receptor structures in virtual screening. J Chem Inf Model 2011; 51:1439-46. [PMID: 21534609 PMCID: PMC3124922 DOI: 10.1021/ci200117n] [Citation(s) in RCA: 70] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
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Molecular dynamics (MD) simulation is a well-established method for understanding protein dynamics. Conformations from unrestrained MD simulations have yet to be assessed for blind virtual screening (VS) by docking. This study presents a critical analysis of the predictive power of MD snapshots to this regard, evaluating two well-characterized systems of varying flexibility in ligand-bound and unbound configurations. Results from such VS predictions are discussed with respect to experimentally determined structures. In all cases, MD simulations provide snapshots that improve VS predictive power over known crystal structures, possibly due to sampling more relevant receptor conformations. Additionally, MD can move conformations previously not amenable to docking into the predictive range.
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Affiliation(s)
- Sara E Nichols
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093-0365, United States.
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Physics-based scoring of protein–ligand interactions: explicit polarizability, quantum mechanics and free energies. Future Med Chem 2011; 3:683-98. [DOI: 10.4155/fmc.11.30] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
The ability to accurately predict the interaction of a ligand with its receptor is a key limitation in computer-aided drug design approaches such as virtual screening and de novo design. In this article, we examine current strategies for a physics-based approach to scoring of protein–ligand affinity, as well as outlining recent developments in force fields and quantum chemical techniques. We also consider advances in the development and application of simulation-based free energy methods to study protein–ligand interactions. Fuelled by recent advances in computational algorithms and hardware, there is the opportunity for increased integration of physics-based scoring approaches at earlier stages in computationally guided drug discovery. Specifically, we envisage increased use of implicit solvent models and simulation-based scoring methods as tools for computing the affinities of large virtual ligand libraries. Approaches based on end point simulations and reference potentials allow the application of more advanced potential energy functions to prediction of protein–ligand binding affinities. Comprehensive evaluation of polarizable force fields and quantum mechanical (QM)/molecular mechanical and QM methods in scoring of protein–ligand interactions is required, particularly in their ability to address challenging targets such as metalloproteins and other proteins that make highly polar interactions. Finally, we anticipate increasingly quantitative free energy perturbation and thermodynamic integration methods that are practical for optimization of hits obtained from screened ligand libraries
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Abstract
Peptide-protein interactions are prevalent in the living cell and form a key component of the overall protein-protein interaction network. These interactions are drawing increasing interest due to their part in signaling and regulation, and are thus attractive targets for computational structural modeling. Here we report an overview of current techniques for the high resolution modeling of peptide-protein complexes. We dissect this complicated challenge into several smaller subproblems, namely: modeling the receptor protein, predicting the peptide binding site, sampling an initial peptide backbone conformation and the final refinement of the peptide within the receptor binding site. For each of these conceptual stages, we present available tools, approaches, and their reported performance. We summarize with an illustrative example of this process, highlighting the success and current challenges still facing the automated blind modeling of peptide-protein interactions. We believe that the upcoming years will see considerable progress in our ability to create accurate models of peptide-protein interactions, with applications in binding-specificity prediction, rational design of peptide-mediated interactions and the usage of peptides as therapeutic agents.
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Affiliation(s)
- Nir London
- Department of Microbiology and Molecular Genetics, Institute for Medical Research Israel-Canada, Hadassah Medical School, The Hebrew University, Jerusalem, Israel
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Zhang J, Sapienza PJ, Ke H, Chang A, Hengel SR, Wang H, Phillips GN, Lee AL. Crystallographic and nuclear magnetic resonance evaluation of the impact of peptide binding to the second PDZ domain of protein tyrosine phosphatase 1E. Biochemistry 2010; 49:9280-91. [PMID: 20839809 DOI: 10.1021/bi101131f] [Citation(s) in RCA: 61] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
PDZ (PSD95/Discs large/ZO-1) domains are ubiquitous protein interaction motifs found in scaffolding proteins involved in signal transduction. Despite the fact that many PDZ domains show a limited tendency to undergo structural change, the PDZ family has been associated with long-range communication and allostery. One of the PDZ domains studied most in terms of structure and biophysical properties is the second PDZ ("PDZ2") domain from protein tyrosine phosphatase 1E (PTP1E, also known as PTPL1). Previously, we showed through NMR relaxation studies that binding of the RA-GEF2 C-terminal peptide substrate results in long-range propagation of side-chain dynamic changes in human PDZ2 [Fuentes, E. J., et al. (2004) J. Mol. Biol. 335, 1105-1115]. Here, we present the first X-ray crystal structures of PDZ2 in the absence and presence of RA-GEF2 ligand, determined to resolutions of 1.65 and 1.3 Å, respectively. These structures deviate somewhat from previously determined NMR structures and indicate that very minor structural changes in PDZ2 accompany peptide binding. NMR residual dipolar couplings confirm the crystal structures to be accurate models of the time-averaged atomic coordinates of PDZ2. The impact on side-chain dynamics was further tested with a C-terminal peptide from APC, which showed results nearly identical to those of RA-GEF2. Thus, allosteric transmission in PDZ2 induced by peptide binding is conveyed purely and robustly by dynamics. (15)N relaxation dispersion measurements did not detect appreciable populations of a kinetic structural intermediate. Collectively, for ligand binding to PDZ2, these data support a lock-and-key binding model from a structural perspective and an allosteric model from a dynamical perspective, which together suggest a complex energy landscape for functional transitions within the ensemble.
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Affiliation(s)
- Jun Zhang
- Department of Biochemistry and Biophysics, School of Medicine, University of North Carolina, Chapel Hill, NC 27599, USA
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41
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Bahar I. On the functional significance of soft modes predicted by coarse-grained models for membrane proteins. ACTA ACUST UNITED AC 2010; 135:563-73. [PMID: 20513758 PMCID: PMC2888054 DOI: 10.1085/jgp.200910368] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Affiliation(s)
- Ivet Bahar
- Department of Computational Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.
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Kalyoncu S, Keskin O, Gursoy A. Interaction prediction and classification of PDZ domains. BMC Bioinformatics 2010; 11:357. [PMID: 20591147 PMCID: PMC2909223 DOI: 10.1186/1471-2105-11-357] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2010] [Accepted: 06/30/2010] [Indexed: 11/10/2022] Open
Abstract
Background PDZ domain is a well-conserved, structural protein domain found in hundreds of signaling proteins that are otherwise unrelated. PDZ domains can bind to the C-terminal peptides of different proteins and act as glue, clustering different protein complexes together, targeting specific proteins and routing these proteins in signaling pathways. These domains are classified into classes I, II and III, depending on their binding partners and the nature of bonds formed. Binding specificities of PDZ domains are very crucial in order to understand the complexity of signaling pathways. It is still an open question how these domains recognize and bind their partners. Results The focus of the current study is two folds: 1) predicting to which peptides a PDZ domain will bind and 2) classification of PDZ domains, as Class I, II or I-II, given the primary sequences of the PDZ domains. Trigram and bigram amino acid frequencies are used as features in machine learning methods. Using 85 PDZ domains and 181 peptides, our model reaches high prediction accuracy (91.4%) for binary interaction prediction which outperforms previously investigated similar methods. Also, we can predict classes of PDZ domains with an accuracy of 90.7%. We propose three critical amino acid sequence motifs that could have important roles on specificity pattern of PDZ domains. Conclusions Our model on PDZ interaction dataset shows that our approach produces encouraging results. The method can be further used as a virtual screening technique to reduce the search space for putative candidate target proteins and drug-like molecules of PDZ domains.
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Affiliation(s)
- Sibel Kalyoncu
- Center for Computational Biology and Bioinformatics, College of Engineering, Koc University, Rumelifeneri Yolu 34450 Sariyer, Istanbul, Turkey
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