1
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Hashemi ZS, Zarei M, Fath MK, Ganji M, Farahani MS, Afsharnouri F, Pourzardosht N, Khalesi B, Jahangiri A, Rahbar MR, Khalili S. In silico Approaches for the Design and Optimization of Interfering Peptides Against Protein-Protein Interactions. Front Mol Biosci 2021; 8:669431. [PMID: 33996914 PMCID: PMC8113820 DOI: 10.3389/fmolb.2021.669431] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 04/06/2021] [Indexed: 01/01/2023] Open
Abstract
Large contact surfaces of protein-protein interactions (PPIs) remain to be an ongoing issue in the discovery and design of small molecule modulators. Peptides are intrinsically capable of exploring larger surfaces, stable, and bioavailable, and therefore bear a high therapeutic value in the treatment of various diseases, including cancer, infectious diseases, and neurodegenerative diseases. Given these promising properties, a long way has been covered in the field of targeting PPIs via peptide design strategies. In silico tools have recently become an inevitable approach for the design and optimization of these interfering peptides. Various algorithms have been developed to scrutinize the PPI interfaces. Moreover, different databases and software tools have been created to predict the peptide structures and their interactions with target protein complexes. High-throughput screening of large peptide libraries against PPIs; "hotspot" identification; structure-based and off-structure approaches of peptide design; 3D peptide modeling; peptide optimization strategies like cyclization; and peptide binding energy evaluation are among the capabilities of in silico tools. In the present study, the most recent advances in the field of in silico approaches for the design of interfering peptides against PPIs will be reviewed. The future perspective of the field and its advantages and limitations will also be pinpointed.
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Affiliation(s)
- Zahra Sadat Hashemi
- ATMP Department, Breast Cancer Research Center, Motamed Cancer Institute, Academic Center for Education, Culture and Research, Tehran, Iran
| | - Mahboubeh Zarei
- Pharmaceutical Sciences Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Mohsen Karami Fath
- Department of Cellular and Molecular Biology, Faculty of Biological Sciences, Kharazmi University, Tehran, Iran
| | - Mahmoud Ganji
- Department of Medical Biotechnology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Mahboube Shahrabi Farahani
- Department of Medical Biotechnology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Fatemeh Afsharnouri
- Department of Medical Biotechnology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Navid Pourzardosht
- Cellular and Molecular Research Center, Faculty of Medicine, Guilan University of Medical Sciences, Rasht, Iran
- Department of Biochemistry, Guilan University of Medical Sciences, Rasht, Iran
| | - Bahman Khalesi
- Department of Research and Production of Poultry Viral Vaccine, Razi Vaccine and Serum Research Institute, Agricultural Research Education and Extension Organization, Karaj, Iran
| | - Abolfazl Jahangiri
- Applied Microbiology Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Mohammad Reza Rahbar
- Pharmaceutical Sciences Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Saeed Khalili
- Department of Biology Sciences, Shahid Rajaee Teacher Training University, Tehran, Iran
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2
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Yang Z, Deng X, Liu Y, Gong W, Li C. Analyses on clustering of the conserved residues at protein-RNA interfaces and its application in binding site identification. BMC Bioinformatics 2020; 21:57. [PMID: 32066366 PMCID: PMC7027071 DOI: 10.1186/s12859-020-3398-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Accepted: 02/07/2020] [Indexed: 12/26/2022] Open
Abstract
Background The maintenance of protein structural stability requires the cooperativity among spatially neighboring residues. Previous studies have shown that conserved residues tend to occur clustered together within enzyme active sites and protein-protein/DNA interfaces. It is possible that conserved residues form one or more local clusters in protein tertiary structures as it can facilitate the formation of functional motifs. In this work, we systematically investigate the spatial distributions of conserved residues as well as hot spot ones within protein-RNA interfaces. Results The analysis of 191 polypeptide chains from 160 complexes shows the polypeptides interacting with tRNAs evolve relatively rapidly. A statistical analysis of residues in different regions shows that the interface residues are often more conserved, while the most conserved ones are those occurring at protein interiors which maintain the stability of folded polypeptide chains. Additionally, we found that 77.8% of the interfaces have the conserved residues clustered within the entire interface regions. Appling the clustering characteristics to the identification of the real interface, there are 31.1% of cases where the real interfaces are ranked in top 10% of 1000 randomly generated surface patches. In the conserved clusters, the preferred residues are the hydrophobic (Leu, Ile, Met), aromatic (Tyr, Phe, Trp) and interestingly only one positively charged Arg residues. For the hot spot residues, 51.5% of them are situated in the conserved residue clusters, and they are largely consistent with the preferred residue types in the conserved clusters. Conclusions The protein-RNA interface residues are often more conserved than non-interface surface ones. The conserved interface residues occur more spatially clustered relative to the entire interface residues. The high consistence of hot spot residue types and the preferred residue types in the conserved clusters has important implications for the experimental alanine scanning mutagenesis study. This work deepens the understanding of the residual organization at protein-RNA interface and is of potential applications in the identification of binding site and hot spot residues.
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Affiliation(s)
- Zhen Yang
- College of Life Science and Bioengineering, Beijing University of Technology, Beijing, 100124, China
| | - Xueqing Deng
- College of Life Science and Bioengineering, Beijing University of Technology, Beijing, 100124, China
| | - Yang Liu
- College of Life Science and Bioengineering, Beijing University of Technology, Beijing, 100124, China
| | - Weikang Gong
- College of Life Science and Bioengineering, Beijing University of Technology, Beijing, 100124, China
| | - Chunhua Li
- College of Life Science and Bioengineering, Beijing University of Technology, Beijing, 100124, China.
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3
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Melo R, Fieldhouse R, Melo A, Correia JDG, Cordeiro MNDS, Gümüş ZH, Costa J, Bonvin AMJJ, Moreira IS. A Machine Learning Approach for Hot-Spot Detection at Protein-Protein Interfaces. Int J Mol Sci 2016; 17:E1215. [PMID: 27472327 PMCID: PMC5000613 DOI: 10.3390/ijms17081215] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2016] [Revised: 07/11/2016] [Accepted: 07/18/2016] [Indexed: 12/17/2022] Open
Abstract
Understanding protein-protein interactions is a key challenge in biochemistry. In this work, we describe a more accurate methodology to predict Hot-Spots (HS) in protein-protein interfaces from their native complex structure compared to previous published Machine Learning (ML) techniques. Our model is trained on a large number of complexes and on a significantly larger number of different structural- and evolutionary sequence-based features. In particular, we added interface size, type of interaction between residues at the interface of the complex, number of different types of residues at the interface and the Position-Specific Scoring Matrix (PSSM), for a total of 79 features. We used twenty-seven algorithms from a simple linear-based function to support-vector machine models with different cost functions. The best model was achieved by the use of the conditional inference random forest (c-forest) algorithm with a dataset pre-processed by the normalization of features and with up-sampling of the minor class. The method has an overall accuracy of 0.80, an F1-score of 0.73, a sensitivity of 0.76 and a specificity of 0.82 for the independent test set.
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Affiliation(s)
- Rita Melo
- Centro de Ciências e Tecnologias Nucleares, Instituto Superior Técnico, Universidade de Lisboa, Estrada Nacional 10 (ao km 139,7), 2695-066 Bobadela LRS, Portugal.
- CNC-Center for Neuroscience and Cell Biology; Rua Larga, Faculdade de Medicina, Polo I, 1ºandar, Universidade de Coimbra, 3004-504 Coimbra, Portugal.
| | - Robert Fieldhouse
- Department of Genetics and Genomics and Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| | - André Melo
- REQUIMTE (Rede de Química e Tecnologia), Faculdade de Ciências da Universidade do Porto, Departamento de Química e Bioquímica, Rua do Campo Alegre, 4169-007 Porto, Portugal.
| | - João D G Correia
- Centro de Ciências e Tecnologias Nucleares, Instituto Superior Técnico, Universidade de Lisboa, Estrada Nacional 10 (ao km 139,7), 2695-066 Bobadela LRS, Portugal.
| | - Maria Natália D S Cordeiro
- REQUIMTE (Rede de Química e Tecnologia), Faculdade de Ciências da Universidade do Porto, Departamento de Química e Bioquímica, Rua do Campo Alegre, 4169-007 Porto, Portugal.
| | - Zeynep H Gümüş
- Department of Genetics and Genomics and Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| | - Joaquim Costa
- CMUP/FCUP, Centro de Matemática da Universidade do Porto, Faculdade de Ciências, Rua do Campo Alegre, 4169-007 Porto, Portugal.
| | - Alexandre M J J Bonvin
- Bijvoet Center for Biomolecular Research, Faculty of Science-Chemistry, Utrecht University, Utrecht 3584CH, The Netherlands.
| | - Irina S Moreira
- CNC-Center for Neuroscience and Cell Biology; Rua Larga, Faculdade de Medicina, Polo I, 1ºandar, Universidade de Coimbra, 3004-504 Coimbra, Portugal.
- Bijvoet Center for Biomolecular Research, Faculty of Science-Chemistry, Utrecht University, Utrecht 3584CH, The Netherlands.
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4
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Mucić ID, Nikolić MR, Stojanović SĐ. Contribution of cation-π interactions to the stability of Sm/LSm oligomeric assemblies. PROTOPLASMA 2015; 252:947-958. [PMID: 25408427 DOI: 10.1007/s00709-014-0727-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2014] [Accepted: 10/30/2014] [Indexed: 06/04/2023]
Abstract
In this work, we have analyzed the influence of cation-π interactions to the stability of Sm/LSm assemblies and their environmental preferences. The number of interactions formed by arginine is higher than lysine in the cationic group, while histidine is comparatively higher than phenylalanine and tyrosine in the π group. Arg-Tyr interactions are predominant among the various pairs analyzed. The furcation level of multiple cation-π interactions is much higher than that of single cation-π interactions in Sm/LSm interfaces. We have found hot spot residues forming cation-π interactions, and hot spot composition is similar for all aromatic residues. The Arg-Phe pair has the strongest interaction energy of -8.81 kcal mol(-1) among all the possible pairs of amino acids. The extent of burial of the residue side-chain correlates with the ΔΔG of binding for residues in the core and also for hot spot residues cation-π bonded across the interface. Secondary structure of the cation-π residues shows that Arg and Lys preferred to be in strand. Among the π residues, His prefers to be in helix, Phe prefers to be in turn, and Tyr prefers to be in strand. Stabilization centers for these proteins showed that all the five residues found in cation-π interactions are important in locating one or more of such centers. More than 50 % of the cation-π interacting residues are highly conserved. It is likely that the cation-π interactions contribute significantly to the overall stability of Sm/LSm proteins.
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Affiliation(s)
- Ivana D Mucić
- Faculty of Chemistry, University of Belgrade, Belgrade, Serbia
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5
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Moal IH, Dapkūnas J, Fernández-Recio J. Inferring the microscopic surface energy of protein-protein interfaces from mutation data. Proteins 2015; 83:640-50. [PMID: 25586563 DOI: 10.1002/prot.24761] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2014] [Revised: 12/04/2014] [Accepted: 12/21/2014] [Indexed: 11/11/2022]
Abstract
Mutations at protein-protein recognition sites alter binding strength by altering the chemical nature of the interacting surfaces. We present a simple surface energy model, parameterized with empirical ΔΔG values, yielding mean energies of -48 cal mol(-1) Å(-2) for interactions between hydrophobic surfaces, -51 to -80 cal mol(-1) Å(-2) for surfaces of complementary charge, and 66-83 cal mol(-1) Å(-2) for electrostatically repelling surfaces, relative to the aqueous phase. This places the mean energy of hydrophobic surface burial at -24 cal mol(-1) Å(-2) . Despite neglecting configurational entropy and intramolecular changes, the model correlates with empirical binding free energies of a functionally diverse set of rigid-body interactions (r = 0.66). When used to rerank docking poses, it can place near-native solutions in the top 10 for 37% of the complexes evaluated, and 82% in the top 100. The method shows that hydrophobic burial is the driving force for protein association, accounting for 50-95% of the cohesive energy. The model is available open-source from http://life.bsc.es/pid/web/surface_energy/ and via the CCharpPPI web server http://life.bsc.es/pid/ccharppi/.
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Affiliation(s)
- Iain H Moal
- Joint BSC-IRB Research Program in Computational Biology, Life Science Department, Barcelona Supercomputing Center, Barcelona, 08034, Spain
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6
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Agrawal NJ, Helk B, Trout BL. A computational tool to predict the evolutionarily conserved protein-protein interaction hot-spot residues from the structure of the unbound protein. FEBS Lett 2013; 588:326-33. [PMID: 24239538 DOI: 10.1016/j.febslet.2013.11.004] [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: 09/23/2013] [Revised: 11/01/2013] [Accepted: 11/04/2013] [Indexed: 11/29/2022]
Abstract
Identifying hot-spot residues - residues that are critical to protein-protein binding - can help to elucidate a protein's function and assist in designing therapeutic molecules to target those residues. We present a novel computational tool, termed spatial-interaction-map (SIM), to predict the hot-spot residues of an evolutionarily conserved protein-protein interaction from the structure of an unbound protein alone. SIM can predict the protein hot-spot residues with an accuracy of 36-57%. Thus, the SIM tool can be used to predict the yet unknown hot-spot residues for many proteins for which the structure of the protein-protein complexes are not available, thereby providing a clue to their functions and an opportunity to design therapeutic molecules to target these proteins.
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Affiliation(s)
- Neeraj J Agrawal
- Chemical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, E19-502b, Cambridge, MA 02139, USA
| | | | - Bernhardt L Trout
- Chemical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, E19-502b, Cambridge, MA 02139, USA.
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7
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Frankiewicz L, Betti C, Guillemyn K, Tourwé D, Jacquot Y, Ballet S. Stabilisation of a short α
-helical VIP fragment by side chain to side chain cyclisation: a comparison of common cyclisation motifs by circular dichroism. J Pept Sci 2013; 19:423-32. [DOI: 10.1002/psc.2515] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2013] [Revised: 03/15/2013] [Accepted: 04/08/2013] [Indexed: 12/11/2022]
Affiliation(s)
- Lukasz Frankiewicz
- Department of Organic Chemistry; Vrije Universiteit Brussel; Pleinlaan 2 B-1050 Brussels Belgium
| | - Cecilia Betti
- Department of Organic Chemistry; Vrije Universiteit Brussel; Pleinlaan 2 B-1050 Brussels Belgium
| | - Karel Guillemyn
- Department of Organic Chemistry; Vrije Universiteit Brussel; Pleinlaan 2 B-1050 Brussels Belgium
| | - Dirk Tourwé
- Department of Organic Chemistry; Vrije Universiteit Brussel; Pleinlaan 2 B-1050 Brussels Belgium
| | - Yves Jacquot
- Laboratory of the BioMolécules (LBM), Department of Chemistry, CNRS - UMR 7203; Ecole Normale Supérieure/Université Pierre et Marie Curie Paris 6; 24, rue Lhomond 75231 Paris Cedex 05 France
| | - Steven Ballet
- Department of Organic Chemistry; Vrije Universiteit Brussel; Pleinlaan 2 B-1050 Brussels Belgium
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8
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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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9
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Kastritis PL, Bonvin AMJJ. On the binding affinity of macromolecular interactions: daring to ask why proteins interact. J R Soc Interface 2012; 10:20120835. [PMID: 23235262 PMCID: PMC3565702 DOI: 10.1098/rsif.2012.0835] [Citation(s) in RCA: 276] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
Interactions between proteins are orchestrated in a precise and time-dependent manner, underlying cellular function. The binding affinity, defined as the strength of these interactions, is translated into physico-chemical terms in the dissociation constant (Kd), the latter being an experimental measure that determines whether an interaction will be formed in solution or not. Predicting binding affinity from structural models has been a matter of active research for more than 40 years because of its fundamental role in drug development. However, all available approaches are incapable of predicting the binding affinity of protein–protein complexes from coordinates alone. Here, we examine both theoretical and experimental limitations that complicate the derivation of structure–affinity relationships. Most work so far has concentrated on binary interactions. Systems of increased complexity are far from being understood. The main physico-chemical measure that relates to binding affinity is the buried surface area, but it does not hold for flexible complexes. For the latter, there must be a significant entropic contribution that will have to be approximated in the future. We foresee that any theoretical modelling of these interactions will have to follow an integrative approach considering the biology, chemistry and physics that underlie protein–protein recognition.
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Affiliation(s)
- Panagiotis L Kastritis
- Bijvoet Center for Biomolecular Research, Faculty of Science, Chemistry, Utrecht University, , Padualaan 8, Utrecht, The Netherlands
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10
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Zhao Y, Wen X, Niu C, Xi Z. Arginine 26 and Aspartic Acid 69 of the Regulatory Subunit are Key Residues of Subunits Interaction of Acetohydroxyacid Synthase Isozyme III fromE. coli. Chembiochem 2012; 13:2445-54. [DOI: 10.1002/cbic.201200362] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2012] [Indexed: 11/08/2022]
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11
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Morrow JK, Zhang S. Computational prediction of protein hot spot residues. Curr Pharm Des 2012; 18:1255-65. [PMID: 22316154 DOI: 10.2174/138161212799436412] [Citation(s) in RCA: 67] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2011] [Accepted: 12/06/2011] [Indexed: 11/22/2022]
Abstract
Most biological processes involve multiple proteins interacting with each other. It has been recently discovered that certain residues in these protein-protein interactions, which are called hot spots, contribute more significantly to binding affinity than others. Hot spot residues have unique and diverse energetic properties that make them challenging yet important targets in the modulation of protein-protein complexes. Design of therapeutic agents that interact with hot spot residues has proven to be a valid methodology in disrupting unwanted protein-protein interactions. Using biological methods to determine which residues are hot spots can be costly and time consuming. Recent advances in computational approaches to predict hot spots have incorporated a myriad of features, and have shown increasing predictive successes. Here we review the state of knowledge around protein-protein interactions, hot spots, and give an overview of multiple in silico prediction techniques of hot spot residues.
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Affiliation(s)
- John Kenneth Morrow
- Department of Experimental Therapeutics, The University of Texas M.D. Anderson Cancer Center, Houston, Texas 77054, USA
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12
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Cukuroglu E, Gursoy A, Keskin O. HotRegion: a database of predicted hot spot clusters. Nucleic Acids Res 2011; 40:D829-33. [PMID: 22080558 PMCID: PMC3245113 DOI: 10.1093/nar/gkr929] [Citation(s) in RCA: 79] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Hot spots are energetically important residues at protein interfaces and they are not randomly distributed across the interface but rather clustered. These clustered hot spots form hot regions. Hot regions are important for the stability of protein complexes, as well as providing specificity to binding sites. We propose a database called HotRegion, which provides the hot region information of the interfaces by using predicted hot spot residues, and structural properties of these interface residues such as pair potentials of interface residues, accessible surface area (ASA) and relative ASA values of interface residues of both monomer and complex forms of proteins. Also, the 3D visualization of the interface and interactions among hot spot residues are provided. HotRegion is accessible at http://prism.ccbb.ku.edu.tr/hotregion.
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Affiliation(s)
- Engin Cukuroglu
- Center for Computational Biology and Bioinformatics and College of Engineering, Koc University, Rumelifeneri Yolu, 34450 Sariyer Istanbul, Turkey
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13
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Zhu X, Mitchell JC. KFC2: a knowledge-based hot spot prediction method based on interface solvation, atomic density, and plasticity features. Proteins 2011; 79:2671-83. [PMID: 21735484 DOI: 10.1002/prot.23094] [Citation(s) in RCA: 152] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2010] [Revised: 04/03/2011] [Accepted: 04/27/2011] [Indexed: 11/09/2022]
Abstract
Hot spots constitute a small fraction of protein-protein interface residues, yet they account for a large fraction of the binding affinity. Based on our previous method (KFC), we present two new methods (KFC2a and KFC2b) that outperform other methods at hot spot prediction. A number of improvements were made in developing these new methods. First, we created a training data set that contained a similar number of hot spot and non-hot spot residues. In addition, we generated 47 different features, and different numbers of features were used to train the models to avoid over-fitting. Finally, two feature combinations were selected: One (used in KFC2a) is composed of eight features that are mainly related to solvent accessible surface area and local plasticity; the other (KFC2b) is composed of seven features, only two of which are identical to those used in KFC2a. The two models were built using support vector machines (SVM). The two KFC2 models were then tested on a mixed independent test set, and compared with other methods such as Robetta, FOLDEF, HotPoint, MINERVA, and KFC. KFC2a showed the highest predictive accuracy for hot spot residues (True Positive Rate: TPR = 0.85); however, the false positive rate was somewhat higher than for other models. KFC2b showed the best predictive accuracy for hot spot residues (True Positive Rate: TPR = 0.62) among all methods other than KFC2a, and the False Positive Rate (FPR = 0.15) was comparable with other highly predictive methods.
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Affiliation(s)
- Xiaolei Zhu
- BACTER Institute, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
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14
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Guharoy M, Pal A, Dasgupta M, Chakrabarti P. PRICE (PRotein Interface Conservation and Energetics): a server for the analysis of protein-protein interfaces. ACTA ACUST UNITED AC 2011; 12:33-41. [PMID: 21519818 DOI: 10.1007/s10969-011-9108-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2010] [Accepted: 04/15/2011] [Indexed: 10/18/2022]
Abstract
Residues in a protein-protein interface that are important for forming and stabilizing the interaction can usually be identified by looking at patterns of evolutionary conservation in groups of homologous proteins and also by the computational identification of binding hotspots. The PRICE (PRotein Interface Conservation and Energetics) server takes the coordinates of a protein-protein complex, dissects the interface into core and rim regions, and calculates (1) the degree of conservation (measured as the sequence entropy), as well as (2) the change in free energy of binding (∆∆G, due to alanine scanning mutagenesis) of interface residues. Results are displayed as color-coded plots and also made available for download. This enables the computational identification of binding hot spots, based on which further experiments can be designed. The method will aid in protein functional prediction by correct assignment of hot regions involved in binding. Consideration of sequence entropies for residues with large ∆∆G values may provide an indication of the biological relevance of the interface. Finally, the results obtained on a test set of alanine mutants has been compared to those obtained using other servers/methods. The PRICE server is a web application available at http://www.boseinst.ernet.in/resources/bioinfo/stag.html.
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Affiliation(s)
- Mainak Guharoy
- Department of Biochemistry, Bose Institute, Kolkata, India
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15
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Guharoy M, Chakrabarti P. Conserved residue clusters at protein-protein interfaces and their use in binding site identification. BMC Bioinformatics 2010; 11:286. [PMID: 20507585 PMCID: PMC2894039 DOI: 10.1186/1471-2105-11-286] [Citation(s) in RCA: 68] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2010] [Accepted: 05/27/2010] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Biological evolution conserves protein residues that are important for structure and function. Both protein stability and function often require a certain degree of structural co-operativity between spatially neighboring residues and it has previously been shown that conserved residues occur clustered together in protein tertiary structures, enzyme active sites and protein-DNA interfaces. Residues comprising protein interfaces are often more conserved compared to those occurring elsewhere on the protein surface. We investigate the extent to which conserved residues within protein-protein interfaces are clustered together in three-dimensions. RESULTS Out of 121 and 392 interfaces in homodimers and heterocomplexes, 96.7 and 86.7%, respectively, have the conserved positions clustered within the overall interface region. The significance of this clustering was established in comparison to what is seen for the subsets of the same size of randomly selected residues from the interface. Conserved residues occurring in larger interfaces could often be sub-divided into two or more distinct sub-clusters. These structural cluster(s) comprising conserved residues indicate functionally important regions within the protein-protein interface that can be targeted for further structural and energetic analysis by experimental scanning mutagenesis. Almost 60% of experimental hot spot residues (with DeltaDeltaG > 2 kcal/mol) were localized to these conserved residue clusters. An analysis of the residue types that are enriched within these conserved subsets compared to the overall interface showed that hydrophobic and aromatic residues are favored, but charged residues (both positive and negative) are less common. The potential use of this method for discriminating binding sites (interfaces) versus random surface patches was explored by comparing the clustering of conserved residues within each of these regions--in about 50% cases the true interface is ranked among the top 10% of all surface patches. CONCLUSIONS Protein-protein interaction sites are much larger than small molecule biding sites, but still conserved residues are not randomly distributed over the whole interface and are distinctly clustered. The clustered nature of evolutionarily conserved residues within interfaces as compared to those within other surface patches not involved in binding has important implications for the identification of protein-protein binding sites and would have applications in docking studies.
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Affiliation(s)
- Mainak Guharoy
- Bioinformatics Centre, Bose Institute, P-1/12 CIT Scheme VIIM, Kolkata, India
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Tuncbag N, Keskin O, Gursoy A. HotPoint: hot spot prediction server for protein interfaces. Nucleic Acids Res 2010; 38:W402-6. [PMID: 20444871 PMCID: PMC2896123 DOI: 10.1093/nar/gkq323] [Citation(s) in RCA: 123] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The energy distribution along the protein–protein interface is not homogenous; certain residues contribute more to the binding free energy, called ‘hot spots’. Here, we present a web server, HotPoint, which predicts hot spots in protein interfaces using an empirical model. The empirical model incorporates a few simple rules consisting of occlusion from solvent and total knowledge-based pair potentials of residues. The prediction model is computationally efficient and achieves high accuracy of 70%. The input to the HotPoint server is a protein complex and two chain identifiers that form an interface. The server provides the hot spot prediction results, a table of residue properties and an interactive 3D visualization of the complex with hot spots highlighted. Results are also downloadable as text files. This web server can be used for analysis of any protein–protein interface which can be utilized by researchers working on binding sites characterization and rational design of small molecules for protein interactions. HotPoint is accessible at http://prism.ccbb.ku.edu.tr/hotpoint.
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Affiliation(s)
- Nurcan Tuncbag
- Center for Computational Biology and Bioinformatics, and College of Engineering, Koc University, Rumelifeneri Yolu, 34450 Sariyer Istanbul, Turkey
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