1
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Kremling V, Loll B, Pach S, Dahmani I, Weise C, Wolber G, Chiantia S, Wahl MC, Osterrieder N, Azab W. Crystal structures of glycoprotein D of equine alphaherpesviruses reveal potential binding sites to the entry receptor MHC-I. Front Microbiol 2023; 14:1197120. [PMID: 37250020 PMCID: PMC10213783 DOI: 10.3389/fmicb.2023.1197120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 04/18/2023] [Indexed: 05/31/2023] Open
Abstract
Cell entry of most alphaherpesviruses is mediated by the binding of glycoprotein D (gD) to different cell surface receptors. Equine herpesvirus type 1 (EHV-1) and EHV-4 gDs interact with equine major histocompatibility complex I (MHC-I) to initiate entry into equine cells. We have characterized the gD-MHC-I interaction by solving the crystal structures of EHV-1 and EHV-4 gDs (gD1, gD4), performing protein-protein docking simulations, surface plasmon resonance (SPR) analysis, and biological assays. The structures of gD1 and gD4 revealed the existence of a common V-set immunoglobulin-like (IgV-like) core comparable to those of other gD homologs. Molecular modeling yielded plausible binding hypotheses and identified key residues (F213 and D261) that are important for virus binding. Altering the key residues resulted in impaired virus growth in cells, which highlights the important role of these residues in the gD-MHC-I interaction. Taken together, our results add to our understanding of the initial herpesvirus-cell interactions and will contribute to the targeted design of antiviral drugs and vaccine development.
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Affiliation(s)
- Viviane Kremling
- Institut für Virologie, Robert von Ostertag-Haus, Zentrum für Infektionsmedizin, Freie Universität Berlin, Berlin, Germany
| | - Bernhard Loll
- Laboratory of Structural Biochemistry, Freie Universität Berlin, Berlin, Germany
| | - Szymon Pach
- Institute of Pharmacy (Pharmaceutical Chemistry), Freie Universität Berlin, Berlin, Germany
| | - Ismail Dahmani
- Universität Potsdam, Institut für Biochemie und Biologie, Potsdam, Brandenburg, Germany
| | - Christoph Weise
- BioSupraMol Core Facility, Bio-Mass Spectrometry, Freie Universität Berlin, Berlin, Germany
| | - Gerhard Wolber
- Institute of Pharmacy (Pharmaceutical Chemistry), Freie Universität Berlin, Berlin, Germany
| | - Salvatore Chiantia
- Universität Potsdam, Institut für Biochemie und Biologie, Potsdam, Brandenburg, Germany
| | - Markus C. Wahl
- Laboratory of Structural Biochemistry, Freie Universität Berlin, Berlin, Germany
- Helmholtz-Zentrum Berlin für Materialien und Energie, Macromolecular Crystallography, Berlin, Germany
| | - Nikolaus Osterrieder
- Institut für Virologie, Robert von Ostertag-Haus, Zentrum für Infektionsmedizin, Freie Universität Berlin, Berlin, Germany
- Department of Infectious Diseases and Public Health, City University of Hong Kong, Kowloon, Hong Kong SAR, China
| | - Walid Azab
- Institut für Virologie, Robert von Ostertag-Haus, Zentrum für Infektionsmedizin, Freie Universität Berlin, Berlin, Germany
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2
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Gurusinghe SN, Oppenheimer B, Shifman JM. Cold spots are universal in protein–protein interactions. Protein Sci 2022; 31:e4435. [PMID: 36173158 PMCID: PMC9490803 DOI: 10.1002/pro.4435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 07/22/2022] [Accepted: 08/26/2022] [Indexed: 12/02/2022]
Abstract
Proteins interact with each other through binding interfaces that differ greatly in size and physico‐chemical properties. Within the binding interface, a few residues called hot spots contribute the majority of the binding free energy and are hence irreplaceable. In contrast, cold spots are occupied by suboptimal amino acids, providing possibility for affinity enhancement through mutations. In this study, we identify cold spots due to cavities and unfavorable charge interactions in multiple protein–protein interactions (PPIs). For our cold spot analysis, we first use a small affinity database of PPIs with known structures and affinities and then expand our search to nearly 4000 homo‐ and heterodimers in the Protein Data Bank (PDB). We observe that cold spots due to cavities are present in nearly all PPIs unrelated to their binding affinity, while unfavorable charge interactions are relatively rare. We also find that most cold spots are located in the periphery of the binding interface, with high‐affinity complexes showing fewer centrally located colds spots than low‐affinity complexes. A larger number of cold spots is also found in non‐cognate interactions compared to their cognate counterparts. Furthermore, our analysis reveals that cold spots are more frequent in homo‐dimeric complexes compared to hetero‐complexes, likely due to symmetry constraints imposed on sequences of homodimers. Finally, we find that glycines, glutamates, and arginines are the most frequent amino acids appearing at cold spot positions. Our analysis emphasizes the importance of cold spot positions to protein evolution and facilitates protein engineering studies directed at enhancing binding affinity and specificity in a wide range of applications.
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Affiliation(s)
- Sagara N.S. Gurusinghe
- Department of Biological Chemistry The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem Jerusalem Israel
| | - Ben Oppenheimer
- Department of Biological Chemistry The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem Jerusalem Israel
| | - Julia M. Shifman
- Department of Biological Chemistry The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem Jerusalem Israel
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3
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Trisciuzzi D, Siragusa L, Baroni M, Autiero I, Nicolotti O, Cruciani G. Getting Insights into Structural and Energetic Properties of Reciprocal Peptide-Protein Interactions. J Chem Inf Model 2022; 62:1113-1125. [PMID: 35148095 DOI: 10.1021/acs.jcim.1c01343] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Peptide-protein interactions play a key role for many cellular and metabolic processes involved in the onset of largely spread diseases such as cancer and neurodegenerative pathologies. Despite the progress in the structural characterization of peptide-protein interfaces, the in-depth knowledge of the molecular details behind their interactions is still a daunting task. Here, we present the first comprehensive in silico morphological and energetic study of peptide binding sites by focusing on both peptide and protein standpoints. Starting from the PixelDB database, a nonredundant benchmark collection of high-quality 3D crystallographic structures of peptide-protein complexes, a classification analysis of the most representative categories based on the nature of each cocrystallized peptide has been carried out. Several interpretable geometrical and energetic descriptors have been computed both from peptide and target protein sides in the attempt to unveil physicochemical and structural causative correlations. Finally, we investigated the most frequent peptide-protein residue pairs at the binding interface and made extensive energetic analyses, based on GRID MIFs, with the aim to study the peptide affinity-enhancing interactions to be further exploited in rational drug design strategies.
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Affiliation(s)
- Daniela Trisciuzzi
- Department of Pharmacy, Pharmaceutical Sciences, Università degli Studi di Bari "Aldo Moro", 70125 Bari, Italy.,Molecular Horizon s.r.l., Via Montelino, 30, 06084 Bettona (PG), Italy
| | - Lydia Siragusa
- Molecular Horizon s.r.l., Via Montelino, 30, 06084 Bettona (PG), Italy.,Molecular Discovery Ltd., Kinetic Business Centre, Theobald Street, Elstree, Borehamwood, Hertfordshire WD6 4PJ, United Kingdom
| | - Massimo Baroni
- Molecular Discovery Ltd., Kinetic Business Centre, Theobald Street, Elstree, Borehamwood, Hertfordshire WD6 4PJ, United Kingdom
| | - Ida Autiero
- Molecular Horizon s.r.l., Via Montelino, 30, 06084 Bettona (PG), Italy.,National Research Council, Institute of Biostructures and Bioimaging, 80138 Naples, Italy
| | - Orazio Nicolotti
- Department of Pharmacy, Pharmaceutical Sciences, Università degli Studi di Bari "Aldo Moro", 70125 Bari, Italy
| | - Gabriele Cruciani
- Department of Chemistry, Biology and Biotechnology, Università degli Studi di Perugia, via Elce di Sotto, 8, 06123 Perugia (PG), Italy
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4
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Qiu L, Yan Y, Sun Z, Song J, Zhang JZ. Interaction entropy for computational alanine scanning in protein-protein binding. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2017. [DOI: 10.1002/wcms.1342] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Affiliation(s)
- Linqiong Qiu
- Shanghai Key Laboratory of Green Chemistry and Chemical Processes, School of Chemistry and Molecular Engineering; State Key Laboratory of Precision Spectroscopy, East China Normal University; Shanghai China
| | - Yuna Yan
- Shanghai Key Laboratory of Green Chemistry and Chemical Processes, School of Chemistry and Molecular Engineering; State Key Laboratory of Precision Spectroscopy, East China Normal University; Shanghai China
| | - Zhaoxi Sun
- Shanghai Key Laboratory of Green Chemistry and Chemical Processes, School of Chemistry and Molecular Engineering; State Key Laboratory of Precision Spectroscopy, East China Normal University; Shanghai China
| | - Jianing Song
- Shanghai Key Laboratory of Green Chemistry and Chemical Processes, School of Chemistry and Molecular Engineering; State Key Laboratory of Precision Spectroscopy, East China Normal University; Shanghai China
- NYU-ECNU Center for Computational Chemistry; NYU Shanghai; Shanghai China
| | - John Z.H. Zhang
- Shanghai Key Laboratory of Green Chemistry and Chemical Processes, School of Chemistry and Molecular Engineering; State Key Laboratory of Precision Spectroscopy, East China Normal University; Shanghai China
- NYU-ECNU Center for Computational Chemistry; NYU Shanghai; Shanghai China
- Department of Chemistry; New York University; New York NY USA
- Collaborative Innovation Center of Extreme Optics; Shanxi University; Taiyuan Shanxi China
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5
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Yan Y, Yang M, Ji CG, Zhang JZ. Interaction Entropy for Computational Alanine Scanning. J Chem Inf Model 2017; 57:1112-1122. [DOI: 10.1021/acs.jcim.6b00734] [Citation(s) in RCA: 63] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Affiliation(s)
- Yuna Yan
- State
Key Laboratory for Precision Spectroscopy, School of Chemistry and
Molecular Engineering, East China Normal University, Shanghai 200062, China
| | - Maoyou Yang
- College of Mathematics & Physics, Shandong Institute of Light Industry, Jinan, Shandong 250353, China
| | - Chang G. Ji
- State
Key Laboratory for Precision Spectroscopy, School of Chemistry and
Molecular Engineering, East China Normal University, Shanghai 200062, China
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
| | - John Z.H. Zhang
- State
Key Laboratory for Precision Spectroscopy, School of Chemistry and
Molecular Engineering, East China Normal University, Shanghai 200062, China
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
- Department
of Chemistry, New York University, New York, New York 10003, United States
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6
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Ren J, Liu Q, Ellis J, Li J. Positive-unlabeled learning for the prediction of conformational B-cell epitopes. BMC Bioinformatics 2015; 16 Suppl 18:S12. [PMID: 26681157 PMCID: PMC4682424 DOI: 10.1186/1471-2105-16-s18-s12] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
Background The incomplete ground truth of training data of B-cell epitopes is a demanding issue in computational epitope prediction. The challenge is that only a small fraction of the surface residues of an antigen are confirmed as antigenic residues (positive training data); the remaining residues are unlabeled. As some of these uncertain residues can possibly be grouped to form novel but currently unknown epitopes, it is misguided to unanimously classify all the unlabeled residues as negative training data following the traditional supervised learning scheme. Results We propose a positive-unlabeled learning algorithm to address this problem. The key idea is to distinguish between epitope-likely residues and reliable negative residues in unlabeled data. The method has two steps: (1) identify reliable negative residues using a weighted SVM with a high recall; and (2) construct a classification model on the positive residues and the reliable negative residues. Complex-based 10-fold cross-validation was conducted to show that this method outperforms those commonly used predictors DiscoTope 2.0, ElliPro and SEPPA 2.0 in every aspect. We conducted four case studies, in which the approach was tested on antigens of West Nile virus, dihydrofolate reductase, beta-lactamase, and two Ebola antigens whose epitopes are currently unknown. All the results were assessed on a newly-established data set of antigen structures not bound by antibodies, instead of on antibody-bound antigen structures. These bound structures may contain unfair binding information such as bound-state B-factors and protrusion index which could exaggerate the epitope prediction performance. Source codes are available on request.
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7
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Alsop JD, Mitchell JC. Interolog interfaces in protein-protein docking. Proteins 2015; 83:1940-6. [PMID: 25740680 PMCID: PMC5054918 DOI: 10.1002/prot.24788] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2014] [Revised: 02/17/2015] [Accepted: 02/24/2015] [Indexed: 12/26/2022]
Abstract
Proteins are essential elements of biological systems, and their function typically relies on their ability to successfully bind to specific partners. Recently, an emphasis of study into protein interactions has been on hot spots, or residues in the binding interface that make a significant contribution to the binding energetics. In this study, we investigate how conservation of hot spots can be used to guide docking prediction. We show that the use of evolutionary data combined with hot spot prediction highlights near‐native structures across a range of benchmark examples. Our approach explores various strategies for using hot spots and evolutionary data to score protein complexes, using both absolute and chemical definitions of conservation along with refinements to these strategies that look at windowed conservation and filtering to ensure a minimum number of hot spots in each binding partner. Finally, structure‐based models of orthologs were generated for comparison with sequence‐based scoring. Using two data sets of 22 and 85 examples, a high rate of top 10 and top 1 predictions are observed, with up to 82% of examples returning a top 10 hit and 35% returning top 1 hit depending on the data set and strategy applied; upon inclusion of the native structure among the decoys, up to 55% of examples yielded a top 1 hit. The 20 common examples between data sets show that more carefully curated interolog data yields better predictions, particularly in achieving top 1 hits. Proteins 2015; 83:1940–1946. © 2015 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.
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Affiliation(s)
- James D Alsop
- Department of Biochemistry, University of Wisconsin, Madison, Wisconsin
| | - Julie C Mitchell
- Department of Biochemistry, University of Wisconsin, Madison, Wisconsin.,Department of Mathematics, University of Wisconsin, Madison, Wisconsin
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8
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Luchini A, Espina V, Liotta LA. Protein painting reveals solvent-excluded drug targets hidden within native protein-protein interfaces. Nat Commun 2014; 5:4413. [PMID: 25048602 PMCID: PMC4109009 DOI: 10.1038/ncomms5413] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2013] [Accepted: 06/16/2014] [Indexed: 01/26/2023] Open
Abstract
Identifying the contact regions between a protein and its binding partners is essential for creating therapies that block the interaction. Unfortunately, such contact regions are extremely difficult to characterize because they are hidden inside the binding interface. Here we introduce protein painting as a new tool that employs small molecules as molecular paints to tightly coat the surface of protein–protein complexes. The molecular paints, which block trypsin cleavage sites, are excluded from the binding interface. Following mass spectrometry, only peptides hidden in the interface emerge as positive hits, revealing the functional contact regions that are drug targets. We use protein painting to discover contact regions between the three-way interaction of IL1β ligand, the receptor IL1RI and the accessory protein IL1RAcP. We then use this information to create peptides and monoclonal antibodies that block the interaction and abolish IL1β cell signalling. The technology is broadly applicable to discover protein interaction drug targets. Identifying the site where a protein binds to another molecule is an important factor for the design of therapeutics intended to prevent this interaction. Here, the authors coat protein–receptor complexes with surface-binding molecules, and determine their interacting regions using mass spectrometry.
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Affiliation(s)
- Alessandra Luchini
- Center for Applied Proteomics and Molecular Medicine, George Mason University, 10900 University Boulevard, Manassas, Virginia 20110, USA
| | - Virginia Espina
- Center for Applied Proteomics and Molecular Medicine, George Mason University, 10900 University Boulevard, Manassas, Virginia 20110, USA
| | - Lance A Liotta
- Center for Applied Proteomics and Molecular Medicine, George Mason University, 10900 University Boulevard, Manassas, Virginia 20110, USA
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9
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Jakobi S, Nguyen TXP, Debaene F, Metz A, Sanglier-Cianférani S, Reuter K, Klebe G. Hot-spot analysis to dissect the functional protein-protein interface of a tRNA-modifying enzyme. Proteins 2014; 82:2713-32. [DOI: 10.1002/prot.24637] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2014] [Revised: 05/24/2014] [Accepted: 06/18/2014] [Indexed: 12/22/2022]
Affiliation(s)
- Stephan Jakobi
- Institut für Pharmazeutische Chemie, Philipps-Universität Marburg; Marbacher Weg 6 D-35032 Marburg Germany
| | - Tran Xuan Phong Nguyen
- Institut für Pharmazeutische Chemie, Philipps-Universität Marburg; Marbacher Weg 6 D-35032 Marburg Germany
| | - François Debaene
- Laboratoire de Spectrométrie de Masse BioOrganique (LSMBO), IPHC-DSA, Université de Strasbourg; CNRS UMR7178; 25 rue Becquerel 67087 Strasbourg France
| | - Alexander Metz
- Institut für Pharmazeutische Chemie, Philipps-Universität Marburg; Marbacher Weg 6 D-35032 Marburg Germany
| | - Sarah Sanglier-Cianférani
- Laboratoire de Spectrométrie de Masse BioOrganique (LSMBO), IPHC-DSA, Université de Strasbourg; CNRS UMR7178; 25 rue Becquerel 67087 Strasbourg France
| | - Klaus Reuter
- Institut für Pharmazeutische Chemie, Philipps-Universität Marburg; Marbacher Weg 6 D-35032 Marburg Germany
| | - Gerhard Klebe
- Institut für Pharmazeutische Chemie, Philipps-Universität Marburg; Marbacher Weg 6 D-35032 Marburg Germany
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10
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Guo W, Wisniewski JA, Ji H. Hot spot-based design of small-molecule inhibitors for protein-protein interactions. Bioorg Med Chem Lett 2014; 24:2546-54. [PMID: 24751445 DOI: 10.1016/j.bmcl.2014.03.095] [Citation(s) in RCA: 107] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2014] [Revised: 03/26/2014] [Accepted: 03/28/2014] [Indexed: 12/27/2022]
Abstract
Protein-protein interactions (PPIs) are important targets for the development of chemical probes and therapeutic agents. From the initial discovery of the existence of hot spots at PPI interfaces, it has been proposed that hot spots might provide the key for developing small-molecule PPI inhibitors. However, there has been no review on the ways in which the knowledge of hot spots can be used to achieve inhibitor design, nor critical examination of successful examples. This Digest discusses the characteristics of hot spots and the identification of druggable hot spot pockets. An analysis of four examples of hot spot-based design reveals the importance of this strategy in discovering potent and selective PPI inhibitors. A general procedure for hot spot-based design of PPI inhibitors is outlined.
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Affiliation(s)
- Wenxing Guo
- Department of Chemistry, Center for Cell and Genome Science, University of Utah, 315 South 1400 East, Salt Lake City, UT 84112-0850, USA
| | - John A Wisniewski
- Department of Chemistry, Center for Cell and Genome Science, University of Utah, 315 South 1400 East, Salt Lake City, UT 84112-0850, USA
| | - Haitao Ji
- Department of Chemistry, Center for Cell and Genome Science, University of Utah, 315 South 1400 East, Salt Lake City, UT 84112-0850, USA.
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11
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Martins JM, Ramos RM, Pimenta AC, Moreira IS. Solvent-accessible surface area: How well can be applied to hot-spot detection? Proteins 2013; 82:479-90. [PMID: 24105801 DOI: 10.1002/prot.24413] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2013] [Revised: 08/25/2013] [Accepted: 09/02/2013] [Indexed: 11/08/2022]
Abstract
A detailed comprehension of protein-based interfaces is essential for the rational drug development. One of the key features of these interfaces is their solvent accessible surface area profile. With that in mind, we tested a group of 12 SASA-based features for their ability to correlate and differentiate hot- and null-spots. These were tested in three different data sets, explicit water MD, implicit water MD, and static PDB structure. We found no discernible improvement with the use of more comprehensive data sets obtained from molecular dynamics. The features tested were shown to be capable of discerning between hot- and null-spots, while presenting low correlations. Residue standardization such as rel SASAi or rel/res SASAi , improved the features as a tool to predict ΔΔGbinding values. A new method using support machine learning algorithms was developed: SBHD (Sasa-Based Hot-spot Detection). This method presents a precision, recall, and F1 score of 0.72, 0.81, and 0.76 for the training set and 0.91, 0.73, and 0.81 for an independent test set.
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Affiliation(s)
- João M Martins
- REQUIMTE/Departamento de Química e Bioquímica, Faculdade de Ciências da Universidade do Porto, Rua do Campo Alegre s/n, 4169-007, Porto, Portugal
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12
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Chen P, Li J, Wong L, Kuwahara H, Huang JZ, Gao X. Accurate prediction of hot spot residues through physicochemical characteristics of amino acid sequences. Proteins 2013; 81:1351-62. [DOI: 10.1002/prot.24278] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2012] [Revised: 02/07/2013] [Accepted: 02/23/2013] [Indexed: 11/11/2022]
Affiliation(s)
- Peng Chen
- Computer, Electrical and Mathematical Sciences and Engineering Division; King Abdullah University of Science and Technology (KAUST); Thuwal 23955-6900 Saudi Arabia
| | - Jinyan Li
- Advanced Analytics Institute; University of Technology; Sydney New South Wales Australia
| | - Limsoon Wong
- School of Computing; National University of Singapore; Singapore 117417
| | - Hiroyuki Kuwahara
- Computer, Electrical and Mathematical Sciences and Engineering Division; King Abdullah University of Science and Technology (KAUST); Thuwal 23955-6900 Saudi Arabia
| | - Jianhua Z. Huang
- Department of Statistics; Texas A&M University; College Station Texas 77843-3143
| | - Xin Gao
- Computer, Electrical and Mathematical Sciences and Engineering Division; King Abdullah University of Science and Technology (KAUST); Thuwal 23955-6900 Saudi Arabia
- Computational Bioscience Research Center; King Abdullah University of Science and Technology (KAUST); Thuwal 23955-6900 Saudi Arabia
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13
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Ramamoorthy D, Turos E, Guida WC. Identification of a New Binding Site in E. coli FabH using Molecular Dynamics Simulations: Validation by Computational Alanine Mutagenesis and Docking Studies. J Chem Inf Model 2013; 53:1138-56. [DOI: 10.1021/ci3003528] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Divya Ramamoorthy
- Department of Chemistry, University of South Florida, 4202 E. Fowler Avenue,
Tampa, Florida 33620, United States
| | - Edward Turos
- Department of Chemistry, University of South Florida, 4202 E. Fowler Avenue,
Tampa, Florida 33620, United States
- Center for Molecular Diversity in Drug Design, Discovery and Delivery, 4202
E. Fowler Avenue, Tampa, Florida 33620, United States
- Center for Drug Discovery and Innovation, 4202 E. Fowler Avenue, Tampa,
Florida 33620, United States
| | - Wayne C. Guida
- Department of Chemistry, University of South Florida, 4202 E. Fowler Avenue,
Tampa, Florida 33620, United States
- Drug Discovery Department, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, Tampa,
Florida 33612, United States
- Center for Molecular Diversity in Drug Design, Discovery and Delivery, 4202
E. Fowler Avenue, Tampa, Florida 33620, United States
- Center for Drug Discovery and Innovation, 4202 E. Fowler Avenue, Tampa,
Florida 33620, United States
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14
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Martins SA, Perez MAS, Moreira IS, Sousa SF, Ramos MJ, Fernandes PA. Computational Alanine Scanning Mutagenesis: MM-PBSA vs TI. J Chem Theory Comput 2013; 9:1311-9. [PMID: 26587593 DOI: 10.1021/ct4000372] [Citation(s) in RCA: 60] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Understanding protein-protein association and being able to determine the crucial residues responsible for their association (hot-spots) is a key issue with huge practical applications such as rational drug design and protein engineering. A variety of computational methods exist to detect hot-spots residues, but the development of a fast and accurate quantitative alanine scanning mutagenesis (ASM) continues to be crucial. Using four protein-protein complexes, we have compared a variation of the standard computational ASM protocol developed at our group, based on the Molecular Mechanics/Poisson-Boltzmann Surface Area (MM-PBSA) approach, against Thermodynamic Integration (TI), a well-known and accurate but computationally expensive method. To compare the efficiency and the accuracy of the two methods, we have calculated the protein-protein binding free energy differences upon alanine mutation of interfacial residues (ΔΔGbind). In relation to the experimental ΔΔGbind values, the average error obtained with TI was 1.53 kcal/mol, while the ASM protocol resulted in an average error of 1.18 kcal/mol. The results demonstrate that the much faster ASM protocol gives results at the same level of accuracy as the TI method but at a fraction of the computational time required to run TI. This ASM protocol is therefore a strong and efficient alternative to the systematic evaluation of protein-protein interfaces, involving hundreds of amino acid residues in search of hot-spots.
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Affiliation(s)
- Sílvia A Martins
- REQUIMTE/Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade do Porto , Rua do Campo Alegre s/n, 4169-007 Porto, Portugal
| | - Marta A S Perez
- REQUIMTE/Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade do Porto , Rua do Campo Alegre s/n, 4169-007 Porto, Portugal
| | - Irina S Moreira
- REQUIMTE/Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade do Porto , Rua do Campo Alegre s/n, 4169-007 Porto, Portugal
| | - Sérgio F Sousa
- REQUIMTE/Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade do Porto , Rua do Campo Alegre s/n, 4169-007 Porto, Portugal
| | - M J Ramos
- REQUIMTE/Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade do Porto , Rua do Campo Alegre s/n, 4169-007 Porto, Portugal
| | - P A Fernandes
- REQUIMTE/Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade do Porto , Rua do Campo Alegre s/n, 4169-007 Porto, Portugal
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15
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Moreira IS, Ramos RM, Martins JM, Fernandes PA, Ramos MJ. Are hot-spots occluded from water? J Biomol Struct Dyn 2013; 32:186-97. [DOI: 10.1080/07391102.2012.758598] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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Zawaira A, Shibayama Y. A simple recipe for the non-expert bioinformaticist for building experimentally-testable hypotheses for proteins with no known homologs. JOURNAL OF STRUCTURAL AND FUNCTIONAL GENOMICS 2012; 13:185-200. [PMID: 22956349 DOI: 10.1007/s10969-012-9141-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/29/2012] [Accepted: 08/08/2012] [Indexed: 06/01/2023]
Abstract
The study of the protein-protein interactions (PPIs) of unique ORFs is a strategy for deciphering the biological roles of unique ORFs of interest. For uniform reference, we define unique ORFs as those for which no matching protein is found after PDB-BLAST search with default parameters. The uniqueness of the ORFs generally precludes the straightforward use of structure-based approaches in the design of experiments to explore PPIs. Many open-source bioinformatics tools, from the commonly-used to the relatively esoteric, have been built and validated to perform analyses and/or predictions of sorts on proteins. How can these available tools be combined into a protocol that helps the non-expert bioinformaticist researcher to design experiments to explore the PPIs of their unique ORF? Here we define a pragmatic protocol based on accessibility of software to achieve this and we make it concrete by applying it on two proteins-the ImuB and ImuA' proteins from Mycobacterium tuberculosis. The protocol is pragmatic in that decisions are made largely based on the availability of easy-to-use freeware. We define the following basic and user-friendly software pathway to build testable PPI hypotheses for a query protein sequence: PSI-PRED → MUSTER → metaPPISP → ASAView and ConSurf. Where possible, other analytical and/or predictive tools may be included. Our protocol combines the software predictions and analyses with general bioinformatics principles to arrive at consensus, prioritised and testable PPI hypotheses.
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Affiliation(s)
- Alexander Zawaira
- Gene Expression and Biophysics Group, Synthetic Biology, ERA, CSIR Biosciences, Brummeria, Pretoria, South Africa.
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Liu Q, Wong L, Li J. Z-score biological significance of binding hot spots of protein interfaces by using crystal packing as the reference state. BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS 2012; 1824:1457-67. [PMID: 22728649 DOI: 10.1016/j.bbapap.2012.05.014] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2012] [Revised: 05/12/2012] [Accepted: 05/31/2012] [Indexed: 11/19/2022]
Abstract
Characterization of binding hot spots of protein interfaces is a fundamental study in molecular biology. Many computational methods have been proposed to identify binding hot spots. However, there are few studies to assess the biological significance of binding hot spots. We introduce the notion of biological significance of a contact residue for capturing the probability of the residue occurring in or contributing to protein binding interfaces. We take a statistical Z-score approach to the assessment of the biological significance. The method has three main steps. First, the potential score of a residue is defined by using a knowledge-based potential function with relative accessible surface area calculations. A null distribution of this potential score is then generated from artifact crystal packing contacts. Finally, the Z-score significance of a contact residue with a specific potential score is determined according to this null distribution. We hypothesize that residues at binding hot spots have big absolute values of Z-score as they contribute greatly to binding free energy. Thus, we propose to use Z-score to predict whether a contact residue is a hot spot residue. Comparison with previously reported methods on two benchmark datasets shows that this Z-score method is mostly superior to earlier methods. This article is part of a Special Issue entitled: Computational Methods for Protein Interaction and Structural Prediction.
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Affiliation(s)
- Qian Liu
- BIRC, SCE, Nanyang Technological University, Singapore 639798, Singapore
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Khan SH, Ahmad F, Ahmad N, Flynn DC, Kumar R. Protein-protein interactions: principles, techniques, and their potential role in new drug development. J Biomol Struct Dyn 2011; 28:929-38. [PMID: 21469753 DOI: 10.1080/07391102.2011.10508619] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Abstract
A vast network of genes is inter-linked through protein-protein interactions and is critical component of almost every biological process under physiological conditions. Any disruption of the biologically essential network leads to pathological conditions resulting into related diseases. Therefore, proper understanding of biological functions warrants a comprehensive knowledge of protein-protein interactions and the molecular mechanisms that govern such processes. The importance of protein-protein interaction process is highlighted by the fact that a number of powerful techniques/methods have been developed to understand how such interactions take place under various physiological and pathological conditions. Many of the key protein-protein interactions are known to participate in disease-associated signaling pathways, and represent novel targets for therapeutic intervention. Thus, controlling protein-protein interactions offers a rich dividend for the discovery of new drug targets. Availability of various tools to study and the knowledge of human genome have put us in a unique position to understand highly complex biological network, and the mechanisms involved therein. In this review article, we have summarized protein-protein interaction networks, techniques/methods of their binding/kinetic parameters, and the role of these interactions in the development of potential tools for drug designing.
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Affiliation(s)
- Shagufta H Khan
- Department of Basic Sciences, The Commonwealth Medical College, 501 Madison Avenue, Scranton, PA 18510, USA
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Bojja RS, Andrake MD, Weigand S, Merkel G, Yarychkivska O, Henderson A, Kummerling M, Skalka AM. Architecture of a full-length retroviral integrase monomer and dimer, revealed by small angle X-ray scattering and chemical cross-linking. J Biol Chem 2011; 286:17047-59. [PMID: 21454648 PMCID: PMC3089549 DOI: 10.1074/jbc.m110.212571] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2010] [Revised: 02/28/2011] [Indexed: 01/25/2023] Open
Abstract
We determined the size and shape of full-length avian sarcoma virus (ASV) integrase (IN) monomers and dimers in solution using small angle x-ray scattering. The low resolution data obtained establish constraints for the relative arrangements of the three component domains in both forms. Domain organization within the small angle x-ray envelopes was determined by combining available atomic resolution data for individual domains with results from cross-linking coupled with mass spectrometry. The full-length dimer architecture so revealed is unequivocally different from that proposed from x-ray crystallographic analyses of two-domain fragments, in which interactions between the catalytic core domains play a prominent role. Core-core interactions are detected only in cross-linked IN tetramers and are required for concerted integration. The solution dimer is stabilized by C-terminal domain (CTD-CTD) interactions and by interactions of the N-terminal domain in one subunit with the core and CTD in the second subunit. These results suggest a pathway for formation of functional IN-DNA complexes that has not previously been considered and possible strategies for preventing such assembly.
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Affiliation(s)
- Ravi S. Bojja
- From the Institute for Cancer Research, Fox Chase Cancer Center, Philadelphia, Pennsylvania 19111 and
| | - Mark D. Andrake
- From the Institute for Cancer Research, Fox Chase Cancer Center, Philadelphia, Pennsylvania 19111 and
| | - Steven Weigand
- the Dupont Northwestern Dow Collaborative Access Team Synchrotron Research Center, Northwestern University, Argonne, Illinois 60439
| | - George Merkel
- From the Institute for Cancer Research, Fox Chase Cancer Center, Philadelphia, Pennsylvania 19111 and
| | - Olya Yarychkivska
- From the Institute for Cancer Research, Fox Chase Cancer Center, Philadelphia, Pennsylvania 19111 and
| | - Adam Henderson
- From the Institute for Cancer Research, Fox Chase Cancer Center, Philadelphia, Pennsylvania 19111 and
| | - Marissa Kummerling
- From the Institute for Cancer Research, Fox Chase Cancer Center, Philadelphia, Pennsylvania 19111 and
| | - Anna Marie Skalka
- From the Institute for Cancer Research, Fox Chase Cancer Center, Philadelphia, Pennsylvania 19111 and
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