1
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Recoulat Angelini AA, Roman EA, González Flecha FL. The Structural Stability of Membrane Proteins Revisited: Combined Thermodynamic and Spectral Phasor Analysis of SDS-induced Denaturation of a Thermophilic Cu(I)-transport ATPase. J Mol Biol 2024; 436:168689. [PMID: 38936696 DOI: 10.1016/j.jmb.2024.168689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Revised: 06/20/2024] [Accepted: 06/21/2024] [Indexed: 06/29/2024]
Abstract
Assessing membrane protein stability is among the major challenges in protein science due to their inherent complexity, which complicates the application of conventional biophysical tools. In this work, sodium dodecyl sulfate-induced denaturation of AfCopA, a Cu(I)-transport ATPase from Archaeoglobus fulgidus, was explored using a combined model-free spectral phasor analysis and a model-dependent thermodynamic analysis. Decrease in tryptophan and 1-anilino-naphthalene-8-sulfonate fluorescence intensity, displacements in the spectral phasor space, and the loss of ATPase activity were reversibly induced by this detergent. Refolding from the SDS-induced denatured state yields an active enzyme that is functionally and spectroscopically indistinguishable from the native state of the protein. Phasor analysis of Trp spectra allowed us to identify two intermediate states in the SDS-induced denaturation of AfCopA, a result further supported by principal component analysis. In contrast, traditional thermodynamic analysis detected only one intermediate state, and including the second one led to overparameterization. Additionally, ANS fluorescence spectral analysis detected one more intermediate and a gradual change at the level of the hydrophobic transmembrane surface of the protein. Based on this evidence, a model for acquiring the native structure of AfCopA in a membrane-like environment is proposed.
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Affiliation(s)
- Alvaro A Recoulat Angelini
- Universidad de Buenos Aires - CONICET, Laboratorio de Biofísica Molecular, Instituto de Química y Fisicoquímica Biológicas, Junín 956, Buenos Aires, Argentina
| | - Ernesto A Roman
- Universidad de Buenos Aires - CONICET, Laboratorio de Biofísica Molecular, Instituto de Química y Fisicoquímica Biológicas, Junín 956, Buenos Aires, Argentina
| | - F Luis González Flecha
- Universidad de Buenos Aires - CONICET, Laboratorio de Biofísica Molecular, Instituto de Química y Fisicoquímica Biológicas, Junín 956, Buenos Aires, Argentina.
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2
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Kumar R, Jayaraman M, Ramadas K, Chandrasekaran A. Computational identification and analysis of deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) in the human POR gene: a structural and functional impact. J Biomol Struct Dyn 2024; 42:1518-1532. [PMID: 37173831 DOI: 10.1080/07391102.2023.2211674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 04/02/2023] [Indexed: 05/15/2023]
Abstract
Cytochrome P450 oxidoreductase (POR) protein is essential for steroidogenesis, and POR gene mutations are frequently associated with P450 Oxidoreductase Deficiency (PORD), a disorder of hormone production. To our knowledge, no previous attempt has been made to identify and analyze the deleterious/pathogenic non-synonymous single nucleotide polymorphisms (nsSNPs) in the human POR gene through an extensive computational approach. Computational algorithms and tools were employed to identify, characterize, and validate the pathogenic SNPs associated with certain diseases. To begin with, all the high-confidence SNPs were collected, and their structural and functional impacts on the protein structures were explored. The results of various in silico analyses affirm that the A287P and R457H variants of POR could destabilize the interactions between the amino acids and the hydrogen bond networks, resulting in functional deviations of POR. The literature study further confirms that the pathogenic mutations (A287P and R457H) are associated with the onset of PORD. Molecular dynamics simulations (MDS) and essential dynamics (ED) studies characterized the structural consequences of prioritized deleterious mutations, representing the structural destabilization that might disrupt POR biological function. The identified deleterious mutations at the cofactor's binding domains might interfere with the essential interactions between the protein and cofactors, thus inhibiting POR catalytic activity. The consolidated insights from the computational analyses can be used to predict potential deleterious mutants and understand the disease's pathological basis and the molecular mechanism of drug metabolism for the application of personalized medication. HIGHLIGHTSNADPH cytochrome P450 oxidoreductase (POR) mutations are associated with a broad spectrum of human diseasesIdentified and analyzed the most deleterious nsSNPs of POR through the sequence and structure-based prediction toolsInvestigated the structural and functional impacts of the most significant mutations (A287P and R457H) associated with PORDMolecular dynamics and PCA-based FEL analysis were utilized to probe the mutation-induced structural alterations in PORCommunicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Rajalakshmi Kumar
- Central Inter-Disciplinary Research Facility, Sri Balaji Vidyapeeth (Deemed to be University), Pillayarkuppam, Puducherry, India
| | - Manikandan Jayaraman
- Department of Bioinformatics, School of Life Sciences, Pondicherry University, Kalapet, Puducherry, India
| | - Krishna Ramadas
- Department of Bioinformatics, School of Life Sciences, Pondicherry University, Kalapet, Puducherry, India
| | - Adithan Chandrasekaran
- Central Inter-Disciplinary Research Facility, Sri Balaji Vidyapeeth (Deemed to be University), Pillayarkuppam, Puducherry, India
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3
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Liu B, Jiang Y, Yang Y, Chen JX. OmeDDG: Improved Protein Mutation Stability Prediction Based on Predicted 3D Structures. J Phys Chem B 2024; 128:67-76. [PMID: 38130113 DOI: 10.1021/acs.jpcb.3c05601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
Determining changes in the protein's thermal stability following mutations is critical in protein engineering and understanding pathogenic missense mutations. Despite the development of various computational methods to predict the effects of single-point mutations, their accuracy remains limited. In this study, we propose a new computational method, OmeDDG, that more accurately predicts mutation-induced Gibbs free energy changes in protein folding (ΔΔG). OmeDDG takes the sequences of wild-type and mutant proteins as input, utilizes OmegaFold to obtain the 3D structure, employs a convolutional neural network to extract structural features, and combines them with protein mutation features and pretraining features to predict the stability of single-point mutations in proteins. We performed a comprehensive comparison between OmeDDG and other available prediction methods on four blind test datasets, confirming that OmeDDG can effectively enhance protein mutation prediction performance. Notably, on the antisymmetric dataset Ssym, OmeDDG achieves the best performance, demonstrating favorable antisymmetry with PCC = 0.79 and RMSE = 0.96 for forward mutations and PCC = 0.77 and RMSE = 0.97 for reverse mutant types.
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Affiliation(s)
- Baoying Liu
- School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu 611756, Sichuan, China
| | - Yongquan Jiang
- School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu 611756, Sichuan, China
- Artificial Intelligence Research Institute, Southwest Jiaotong University, Chengdu 611756, Sichuan, China
| | - Yan Yang
- School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu 611756, Sichuan, China
- Artificial Intelligence Research Institute, Southwest Jiaotong University, Chengdu 611756, Sichuan, China
| | - Jim X Chen
- Department of Computer Science, George Mason University, Fairfax, Virginia 22030-4444, United States
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4
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Pandey P, Panday SK, Rimal P, Ancona N, Alexov E. Predicting the Effect of Single Mutations on Protein Stability and Binding with Respect to Types of Mutations. Int J Mol Sci 2023; 24:12073. [PMID: 37569449 PMCID: PMC10418460 DOI: 10.3390/ijms241512073] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 07/24/2023] [Accepted: 07/26/2023] [Indexed: 08/13/2023] Open
Abstract
The development of methods and algorithms to predict the effect of mutations on protein stability, protein-protein interaction, and protein-DNA/RNA binding is necessitated by the needs of protein engineering and for understanding the molecular mechanism of disease-causing variants. The vast majority of the leading methods require a database of experimentally measured folding and binding free energy changes for training. These databases are collections of experimental data taken from scientific investigations typically aimed at probing the role of particular residues on the above-mentioned thermodynamic characteristics, i.e., the mutations are not introduced at random and do not necessarily represent mutations originating from single nucleotide variants (SNV). Thus, the reported performance of the leading algorithms assessed on these databases or other limited cases may not be applicable for predicting the effect of SNVs seen in the human population. Indeed, we demonstrate that the SNVs and non-SNVs are not equally presented in the corresponding databases, and the distribution of the free energy changes is not the same. It is shown that the Pearson correlation coefficients (PCCs) of folding and binding free energy changes obtained in cases involving SNVs are smaller than for non-SNVs, indicating that caution should be used in applying them to reveal the effect of human SNVs. Furthermore, it is demonstrated that some methods are sensitive to the chemical nature of the mutations, resulting in PCCs that differ by a factor of four across chemically different mutations. All methods are found to underestimate the energy changes by roughly a factor of 2.
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Affiliation(s)
- Preeti Pandey
- Department of Physics and Astronomy, Clemson University, Clemson, SC 29634, USA; (P.P.); (S.K.P.); (P.R.)
| | - Shailesh Kumar Panday
- Department of Physics and Astronomy, Clemson University, Clemson, SC 29634, USA; (P.P.); (S.K.P.); (P.R.)
| | - Prawin Rimal
- Department of Physics and Astronomy, Clemson University, Clemson, SC 29634, USA; (P.P.); (S.K.P.); (P.R.)
| | - Nicolas Ancona
- Department of Biological Sciences, Clemson University, Clemson, SC 29634, USA;
| | - Emil Alexov
- Department of Physics and Astronomy, Clemson University, Clemson, SC 29634, USA; (P.P.); (S.K.P.); (P.R.)
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5
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Rosace A, Bennett A, Oeller M, Mortensen MM, Sakhnini L, Lorenzen N, Poulsen C, Sormanni P. Automated optimisation of solubility and conformational stability of antibodies and proteins. Nat Commun 2023; 14:1937. [PMID: 37024501 PMCID: PMC10079162 DOI: 10.1038/s41467-023-37668-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Accepted: 03/24/2023] [Indexed: 04/08/2023] Open
Abstract
Biologics, such as antibodies and enzymes, are crucial in research, biotechnology, diagnostics, and therapeutics. Often, biologics with suitable functionality are discovered, but their development is impeded by developability issues. Stability and solubility are key biophysical traits underpinning developability potential, as they determine aggregation, correlate with production yield and poly-specificity, and are essential to access parenteral and oral delivery. While advances for the optimisation of individual traits have been made, the co-optimization of multiple traits remains highly problematic and time-consuming, as mutations that improve one property often negatively impact others. In this work, we introduce a fully automated computational strategy for the simultaneous optimisation of conformational stability and solubility, which we experimentally validate on six antibodies, including two approved therapeutics. Our results on 42 designs demonstrate that the computational procedure is highly effective at improving developability potential, while not affecting antigen-binding. We make the method available as a webserver at www-cohsoftware.ch.cam.ac.uk.
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Affiliation(s)
- Angelo Rosace
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield road, CB2 1EW, Cambridge, UK
- Master in Bioinformatics for Health Sciences, Universitat Pompeu Fabra, Barcelona, Catalonia, Spain
- Institute for Research in Biomedicine (IRB), The Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain
| | - Anja Bennett
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield road, CB2 1EW, Cambridge, UK
- Department of Mammalian Expression, Global Research Technologies, Novo Nordisk A/S, Novo Nordisk Park 1, 2760, Måløv, Denmark
- BRIC, Faculty of Health and Medical Sciences, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark
| | - Marc Oeller
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield road, CB2 1EW, Cambridge, UK
| | - Mie M Mortensen
- Department of Purification Technologies, Global Research Technologies, Novo Nordisk A/S, Novo Nordisk Park 1, 2760, Måløv, Denmark
- Faculty of Engineering and Science, Department of Biotechnology, Chemistry and Environmental Engineering, University of Aalborg, Fredrik Bajers Vej 7H, 9220, Aalborg, Denmark
| | - Laila Sakhnini
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield road, CB2 1EW, Cambridge, UK
- Department of Biophysics and Injectable Formulation 2, Global Research Technologies, Novo Nordisk A/S, Måløv, 2760, Denmark
| | - Nikolai Lorenzen
- Department of Biophysics and Injectable Formulation 2, Global Research Technologies, Novo Nordisk A/S, Måløv, 2760, Denmark
| | - Christian Poulsen
- Department of Mammalian Expression, Global Research Technologies, Novo Nordisk A/S, Novo Nordisk Park 1, 2760, Måløv, Denmark
| | - Pietro Sormanni
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield road, CB2 1EW, Cambridge, UK.
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6
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Hervis YP, Valle A, Canet L, Rodríguez A, Lanio ME, Alvarez C, Steinhoff HJ, Pazos IF. Cys mutants as tools to study the oligomerization of the pore-forming toxin sticholysin I. Toxicon 2023; 222:106994. [PMID: 36529153 DOI: 10.1016/j.toxicon.2022.106994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 12/08/2022] [Accepted: 12/09/2022] [Indexed: 12/23/2022]
Abstract
Sticholysin I (StI) is a water-soluble protein with the ability to bind membranes where it oligomerizes and forms pores leading to cell death. Understanding the assembly property of this protein may be valuable for designing potential biotechnological tools, such as stable or structurally defined nanopores. In order to get insights into the stabilization of StI oligomers by disulfide bonds, we designed and characterized single and double cysteine mutants at the oligomerization interface. The oligomer formation was induced in the presence of lipid membranes and visualized by SDS-PAGE. The contribution of the oligomeric structures to the membrane binding and pore-forming capacities of StI was assessed. Single and double cysteine introduction at the protein-protein oligomerization interface does not considerably affect the conformation and function of the monomeric protein. In the presence of membranes, a cysteine double mutation at positions 15 and 59 favored formation of different size oligomers stabilized by disulfide bonds. The results of this work highlight the relevance of these positions (15 and 59) to be considered for developing biosensors based on nanopores from StI.
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Affiliation(s)
- Yadira P Hervis
- Center for Protein Studies/Department of Biochemistry, Faculty of Biology, University of Havana, Havana, ZIP 10400, Cuba.
| | - Aisel Valle
- Center for Protein Studies/Department of Biochemistry, Faculty of Biology, University of Havana, Havana, ZIP 10400, Cuba.
| | - Liem Canet
- Center for Protein Studies/Department of Biochemistry, Faculty of Biology, University of Havana, Havana, ZIP 10400, Cuba.
| | | | - Maria E Lanio
- Center for Protein Studies/Department of Biochemistry, Faculty of Biology, University of Havana, Havana, ZIP 10400, Cuba.
| | - Carlos Alvarez
- Center for Protein Studies/Department of Biochemistry, Faculty of Biology, University of Havana, Havana, ZIP 10400, Cuba.
| | - Heinz J Steinhoff
- Department of Physics, University of Osnabrueck, Osnabrueck, 49069, Germany.
| | - Isabel F Pazos
- Center for Protein Studies/Department of Biochemistry, Faculty of Biology, University of Havana, Havana, ZIP 10400, Cuba.
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7
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Lim H, No KT. Prediction of polyreactive and nonspecific single-chain fragment variables through structural biochemical features and protein language-based descriptors. BMC Bioinformatics 2022; 23:520. [PMID: 36471239 PMCID: PMC9720949 DOI: 10.1186/s12859-022-05010-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 10/26/2022] [Indexed: 12/09/2022] Open
Abstract
BACKGROUND Monoclonal antibodies (mAbs) have been used as therapeutic agents, which must overcome many developability issues after the discovery from in vitro display libraries. Especially, polyreactive mAbs can strongly bind to a specific target and weakly bind to off-target proteins, which leads to poor antibody pharmacokinetics in clinical development. Although early assessment of polyreactive mAbs is important in the early discovery stage, experimental assessments are usually time-consuming and expensive. Therefore, computational approaches for predicting the polyreactivity of single-chain fragment variables (scFvs) in the early discovery stage would be promising for reducing experimental efforts. RESULTS Here, we made prediction models for the polyreactivity of scFvs with the known polyreactive antibody features and natural language model descriptors. We predicted 19,426 protein structures of scFvs with trRosetta to calculate the polyreactive antibody features and investigated the classifying performance of each factor for polyreactivity. In the known polyreactive features, the net charge of the CDR2 loop, the tryptophan and glycine residues in CDR-H3, and the lengths of the CDR1 and CDR2 loops, importantly contributed to the performance of the models. Additionally, the hydrodynamic features, such as partial specific volume, gyration radius, and isoelectric points of CDR loops and scFvs, were newly added to improve model performance. Finally, we made the prediction model with a robust performance ([Formula: see text]) with an ensemble learning of the top 3 best models. CONCLUSION The prediction models for polyreactivity would help assess polyreactive scFvs in the early discovery stage and our approaches would be promising to develop machine learning models with quantitative data from high throughput assays for antibody screening.
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Affiliation(s)
- Hocheol Lim
- grid.15444.300000 0004 0470 5454The Interdisciplinary Graduate Program in Integrative Biotechnology and Translational Medicine, Yonsei University, Incheon, 21983 Republic of Korea ,Bioinformatics and Molecular Design Research Center (BMDRC), Incheon, 21983 Republic of Korea
| | - Kyoung Tai No
- grid.15444.300000 0004 0470 5454The Interdisciplinary Graduate Program in Integrative Biotechnology and Translational Medicine, Yonsei University, Incheon, 21983 Republic of Korea ,Bioinformatics and Molecular Design Research Center (BMDRC), Incheon, 21983 Republic of Korea ,Baobab AiBIO Co., Ltd., Incheon, 21983 Republic of Korea
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8
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Singh S, Sharma S, Baranwal M. Identification of SNPs in hMSH3/MSH6 interaction domain affecting the structure and function of MSH2 protein. Biotechnol Appl Biochem 2022; 69:2454-2465. [PMID: 34837403 DOI: 10.1002/bab.2295] [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: 05/24/2021] [Accepted: 11/23/2021] [Indexed: 12/27/2022]
Abstract
MutS homolog 2 (MSH2) is a mismatch repair gene that plays a critical role in DNA repair pathways, and its mutations are associated with different cancers. The present study aimed to find out the single nucleotide polymorphisms (SNPs) of MSH2 protein associated with causing structural and functional changes leading to the development of cancer with the help of computational tools. Four different tools for predicting deleterious SNPs (SIFT, PROVEAN, PANTHER, and PolyPhen), two tools each for identifying disease association (PhD-SNP and SNP&GO) and estimating stability (I-mutant and MUPro) were employed. Homology modeling, energy minimization, and root mean square deviation calculation were used to estimate structural variations. Twenty-seven SNPs and five SNPs (double amino acid change) were identified based on a consensus approach that might be associated with the structural and functional change in MSH2 protein. Molecular docking reveals that six SNPs affect the interaction of MSH2 and MSH6. Twelve identified SNPs were reported to be linked with hereditary nonpolyposis, colorectal cancer, and Lynch syndrome. Further, selected SNPs need to be validated in an in vitro system for their precise association with cancer predisposition.
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Affiliation(s)
- Sidhartha Singh
- Department of Biotechnology, Thapar Institute of Engineering & Technology, Patiala, Punjab, India
| | - Siddharth Sharma
- Department of Biotechnology, Thapar Institute of Engineering & Technology, Patiala, Punjab, India
| | - Manoj Baranwal
- Department of Biotechnology, Thapar Institute of Engineering & Technology, Patiala, Punjab, India
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9
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Valanciute A, Nygaard L, Zschach H, Maglegaard Jepsen M, Lindorff-Larsen K, Stein A. Accurate protein stability predictions from homology models. Comput Struct Biotechnol J 2022; 21:66-73. [PMID: 36514339 PMCID: PMC9729920 DOI: 10.1016/j.csbj.2022.11.048] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 11/22/2022] [Accepted: 11/23/2022] [Indexed: 11/27/2022] Open
Abstract
Calculating changes in protein stability (ΔΔG) has been shown to be central for predicting the consequences of single amino acid substitutions in protein engineering as well as interpretation of genomic variants for disease risk. Structure-based calculations are considered most accurate, however the tools used to calculate ΔΔGs have been developed on experimentally resolved structures. Extending those calculations to homology models based on related proteins would greatly extend their applicability as large parts of e.g. the human proteome are not structurally resolved. In this study we aim to investigate the accuracy of ΔΔG values predicted on homology models compared to crystal structures. Specifically, we identified four proteins with a large number of experimentally tested ΔΔGs and templates for homology modeling across a broad range of sequence identities, and selected three methods for ΔΔG calculations to test. We find that ΔΔG-values predicted from homology models compare equally well to experimental ΔΔGs as those predicted on experimentally established crystal structures, as long as the sequence identity of the model template to the target protein is at least 40%. In particular, the Rosetta cartesian_ddg protocol is robust against the small perturbations in the structure which homology modeling introduces. In an independent assessment, we observe a similar trend when using ΔΔGs to categorize variants as low or wild-type-like abundance. Overall, our results show that stability calculations performed on homology models can substitute for those on crystal structures with acceptable accuracy as long as the model is built on a template with sequence identity of at least 40% to the target protein.
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Affiliation(s)
- Audrone Valanciute
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Lasse Nygaard
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Henrike Zschach
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Michael Maglegaard Jepsen
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Kresten Lindorff-Larsen
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark,Corresponding authors.
| | - Amelie Stein
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark,Corresponding authors.
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10
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Qing R, Hao S, Smorodina E, Jin D, Zalevsky A, Zhang S. Protein Design: From the Aspect of Water Solubility and Stability. Chem Rev 2022; 122:14085-14179. [PMID: 35921495 PMCID: PMC9523718 DOI: 10.1021/acs.chemrev.1c00757] [Citation(s) in RCA: 54] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Indexed: 12/13/2022]
Abstract
Water solubility and structural stability are key merits for proteins defined by the primary sequence and 3D-conformation. Their manipulation represents important aspects of the protein design field that relies on the accurate placement of amino acids and molecular interactions, guided by underlying physiochemical principles. Emulated designer proteins with well-defined properties both fuel the knowledge-base for more precise computational design models and are used in various biomedical and nanotechnological applications. The continuous developments in protein science, increasing computing power, new algorithms, and characterization techniques provide sophisticated toolkits for solubility design beyond guess work. In this review, we summarize recent advances in the protein design field with respect to water solubility and structural stability. After introducing fundamental design rules, we discuss the transmembrane protein solubilization and de novo transmembrane protein design. Traditional strategies to enhance protein solubility and structural stability are introduced. The designs of stable protein complexes and high-order assemblies are covered. Computational methodologies behind these endeavors, including structure prediction programs, machine learning algorithms, and specialty software dedicated to the evaluation of protein solubility and aggregation, are discussed. The findings and opportunities for Cryo-EM are presented. This review provides an overview of significant progress and prospects in accurate protein design for solubility and stability.
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Affiliation(s)
- Rui Qing
- State
Key Laboratory of Microbial Metabolism, School of Life Sciences and
Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
- Media
Lab, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
- The
David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
| | - Shilei Hao
- Media
Lab, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
- Key
Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing 400030, China
| | - Eva Smorodina
- Department
of Immunology, University of Oslo and Oslo
University Hospital, Oslo 0424, Norway
| | - David Jin
- Avalon GloboCare
Corp., Freehold, New Jersey 07728, United States
| | - Arthur Zalevsky
- Laboratory
of Bioinformatics Approaches in Combinatorial Chemistry and Biology, Shemyakin−Ovchinnikov Institute of Bioorganic
Chemistry RAS, Moscow 117997, Russia
| | - Shuguang Zhang
- Media
Lab, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
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11
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PSP-GNM: Predicting Protein Stability Changes upon Point Mutations with a Gaussian Network Model. Int J Mol Sci 2022; 23:ijms231810711. [PMID: 36142614 PMCID: PMC9505940 DOI: 10.3390/ijms231810711] [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: 08/14/2022] [Revised: 09/05/2022] [Accepted: 09/09/2022] [Indexed: 11/26/2022] Open
Abstract
Understanding the effects of missense mutations on protein stability is a widely acknowledged significant biological problem. Genomic missense mutations may alter one or more amino acids, leading to increased or decreased stability of the encoded proteins. In this study, we describe a novel approach—Protein Stability Prediction with a Gaussian Network Model (PSP-GNM)—to measure the unfolding Gibbs free energy change (ΔΔG) and evaluate the effects of single amino acid substitutions on protein stability. Specifically, PSP-GNM employs a coarse-grained Gaussian Network Model (GNM) that has interactions between amino acids weighted by the Miyazawa–Jernigan statistical potential. We used PSP-GNM to simulate partial unfolding of the wildtype and mutant protein structures, and then used the difference in the energies and entropies of the unfolded wildtype and mutant proteins to calculate ΔΔG. The extent of the agreement between the ΔΔG calculated by PSP-GNM and the experimental ΔΔG was evaluated on three benchmark datasets: 350 forward mutations (S350 dataset), 669 forward and reverse mutations (S669 dataset) and 611 forward and reverse mutations (S611 dataset). We observed a Pearson correlation coefficient as high as 0.61, which is comparable to many of the existing state-of-the-art methods. The agreement with experimental ΔΔG further increased when we considered only those measurements made close to 25 °C and neutral pH, suggesting dependence on experimental conditions. We also assessed for the antisymmetry (ΔΔGreverse = −ΔΔGforward) between the forward and reverse mutations on the Ssym+ dataset, which has 352 forward and reverse mutations. While most available methods do not display significant antisymmetry, PSP-GNM demonstrated near-perfect antisymmetry, with a Pearson correlation of −0.97. PSP-GNM is written in Python and can be downloaded as a stand-alone code.
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12
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Kulandaisamy A, Nikam R, Harini K, Sharma D, Gromiha MM. Illustrative Tutorials for ProThermDB: Thermodynamic Database for Proteins and Mutants. Curr Protoc 2021; 1:e306. [PMID: 34826364 DOI: 10.1002/cpz1.306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
ProThermDB (https://web.iitm.ac.in/bioinfo2/prothermdb/index.html) is a primary resource for protein stability, which contains experimentally determined thermodynamic data for proteins and their mutants. The most recent version of ProThermDB accumulates the data obtained from both high- and low-throughput experimental biophysical methods. It includes comprehensive information at four different levels, i.e.: (i) protein sequence and structure; (ii) experimental conditions; (iii) thermodynamic parameters such as Gibbs free energy, melting temperature, enthalpy, etc.; and (iv) literature. In the following protocols, we present detailed tutorials for retrieving data using different search, display and sorting options, interpretation of search results, description of each entry-level information category, data upload and download, cross-links with other databases, and visualization options. This protocol consists of six pictorial exercises, which are useful for biologists/users to understand the contents and organization of data in ProThermDB. Further, potential applications of ProThermDB in protein engineering are discussed. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Retrieval of experimental thermodynamic data for wild-type and mutants of a specific protein using a simple query Basic Protocol 2: Retrieval of stabilizing point mutations, which are located at the interior of α-helical regions, and obtaining data by thermal denaturation methods Basic Protocol 3: Retrieval of destabilizing point mutations, which are in β-sheets of exposed regions, and obtaining data by chemical denaturation methods (urea and GdnHCl) Basic Protocol 4: Retrieval of stabilizing and destabilizing point mutations in a range of physiological conditions (pH: 6-9 and T: 20°C-25°C) and publication years (2010-2020) Support Protocol: Downloading the entire data of the database for academic research purposes and submission of new data in ProThermDB.
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Affiliation(s)
- A Kulandaisamy
- Department of Biotechnology, Bhupat and Jyoti Mehta School of BioSciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India
| | - Rahul Nikam
- Department of Biotechnology, Bhupat and Jyoti Mehta School of BioSciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India
| | - K Harini
- Department of Biotechnology, Bhupat and Jyoti Mehta School of BioSciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India
| | - Divya Sharma
- Department of Biotechnology, Bhupat and Jyoti Mehta School of BioSciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India
| | - M Michael Gromiha
- Department of Biotechnology, Bhupat and Jyoti Mehta School of BioSciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India
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Hoxha M, Kamberaj H. Automation of some macromolecular properties using a machine learning approach. MACHINE LEARNING: SCIENCE AND TECHNOLOGY 2021. [DOI: 10.1088/2632-2153/abe7b6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
Abstract
In this study, we employed a newly developed method to predict macromolecular properties using a swarm artificial neural network (ANN) method as a machine learning approach. In this method, the molecular structures are represented by the feature description vectors used as training input data for a neural network. This study aims to develop an efficient approach for training an ANN using either experimental or quantum mechanics data. We aim to introduce an error model controlling the reliability of the prediction confidence interval using a bootstrapping swarm approach. We created different datasets of selected experimental or quantum mechanics results. Using this optimized ANN, we hope to predict properties and their statistical errors for new molecules. There are four datasets used in this study. That includes the dataset of 642 small organic molecules with known experimental hydration free energies, the dataset of 1475 experimental pKa values of ionizable groups in 192 proteins, the dataset of 2693 mutants in 14 proteins with given experimental values of changes in the Gibbs free energy, and a dataset of 7101 quantum mechanics heat of formation calculations. All the data are prepared and optimized using the AMBER force field in the CHARMM macromolecular computer simulation program. The bootstrapping swarm ANN code for performing the optimization and prediction is written in Python computer programming language. The descriptor vectors of the small molecules are based on the Coulomb matrix and sum over bond properties. For the macromolecular systems, they consider the chemical-physical fingerprints of the region in the vicinity of each amino acid.
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Atsavapranee B, Stark CD, Sunden F, Thompson S, Fordyce PM. Fundamentals to function: Quantitative and scalable approaches for measuring protein stability. Cell Syst 2021; 12:547-560. [PMID: 34139165 DOI: 10.1016/j.cels.2021.05.009] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 04/16/2021] [Accepted: 05/07/2021] [Indexed: 12/11/2022]
Abstract
Folding a linear chain of amino acids into a three-dimensional protein is a complex physical process that ultimately confers an impressive range of diverse functions. Although recent advances have driven significant progress in predicting three-dimensional protein structures from sequence, proteins are not static molecules. Rather, they exist as complex conformational ensembles defined by energy landscapes spanning the space of sequence and conditions. Quantitatively mapping the physical parameters that dictate these landscapes and protein stability is therefore critical to develop models that are capable of predicting how mutations alter function of proteins in disease and informing the design of proteins with desired functions. Here, we review the approaches that are used to quantify protein stability at a variety of scales, from returning multiple thermodynamic and kinetic measurements for a single protein sequence to yielding indirect insights into folding across a vast sequence space. The physical parameters derived from these approaches will provide a foundation for models that extend beyond the structural prediction to capture the complexity of conformational ensembles and, ultimately, their function.
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Affiliation(s)
| | - Catherine D Stark
- Department of Biochemistry, Stanford University, Stanford, CA 94305, USA; ChEM-H, Stanford University, Stanford, CA 94305, USA
| | - Fanny Sunden
- Department of Biochemistry, Stanford University, Stanford, CA 94305, USA
| | - Samuel Thompson
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
| | - Polly M Fordyce
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; ChEM-H, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA; Chan Zuckerberg Biohub, San Francisco, CA 94110, USA.
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15
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Sequeiros-Borja CE, Surpeta B, Brezovsky J. Recent advances in user-friendly computational tools to engineer protein function. Brief Bioinform 2021; 22:bbaa150. [PMID: 32743637 PMCID: PMC8138880 DOI: 10.1093/bib/bbaa150] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 06/03/2020] [Accepted: 06/16/2020] [Indexed: 12/14/2022] Open
Abstract
Progress in technology and algorithms throughout the past decade has transformed the field of protein design and engineering. Computational approaches have become well-engrained in the processes of tailoring proteins for various biotechnological applications. Many tools and methods are developed and upgraded each year to satisfy the increasing demands and challenges of protein engineering. To help protein engineers and bioinformaticians navigate this emerging wave of dedicated software, we have critically evaluated recent additions to the toolbox regarding their application for semi-rational and rational protein engineering. These newly developed tools identify and prioritize hotspots and analyze the effects of mutations for a variety of properties, comprising ligand binding, protein-protein and protein-nucleic acid interactions, and electrostatic potential. We also discuss notable progress to target elusive protein dynamics and associated properties like ligand-transport processes and allosteric communication. Finally, we discuss several challenges these tools face and provide our perspectives on the further development of readily applicable methods to guide protein engineering efforts.
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Affiliation(s)
- Carlos Eduardo Sequeiros-Borja
- Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University and the International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Bartłomiej Surpeta
- Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University and the International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Jan Brezovsky
- Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University and the International Institute of Molecular and Cell Biology in Warsaw
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16
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Xavier JS, Nguyen TB, Karmarkar M, Portelli S, Rezende PM, Velloso JPL, Ascher DB, Pires DEV. ThermoMutDB: a thermodynamic database for missense mutations. Nucleic Acids Res 2021; 49:D475-D479. [PMID: 33095862 PMCID: PMC7778973 DOI: 10.1093/nar/gkaa925] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2020] [Revised: 09/21/2020] [Accepted: 10/12/2020] [Indexed: 01/17/2023] Open
Abstract
Proteins are intricate, dynamic structures, and small changes in their amino acid sequences can lead to large effects on their folding, stability and dynamics. To facilitate the further development and evaluation of methods to predict these changes, we have developed ThermoMutDB, a manually curated database containing >14,669 experimental data of thermodynamic parameters for wild type and mutant proteins. This represents an increase of 83% in unique mutations over previous databases and includes thermodynamic information on 204 new proteins. During manual curation we have also corrected annotation errors in previously curated entries. Associated with each entry, we have included information on the unfolding Gibbs free energy and melting temperature change, and have associated entries with available experimental structural information. ThermoMutDB supports users to contribute to new data points and programmatic access to the database via a RESTful API. ThermoMutDB is freely available at: http://biosig.unimelb.edu.au/thermomutdb.
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Affiliation(s)
- Joicymara S Xavier
- Institute of Agricultural Sciences, Universidade Federal dos Vales do Jequitinhonha e Mucuri.,Instituto René Rachou, Fundação Oswaldo Cruz
| | | | - Malancha Karmarkar
- Bio 21 Institute, University of Melbourne.,Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute
| | - Stephanie Portelli
- Bio 21 Institute, University of Melbourne.,Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute
| | | | | | - David B Ascher
- Bio 21 Institute, University of Melbourne.,Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute.,Department of Biochemistry, University of Cambridge
| | - Douglas E V Pires
- Bio 21 Institute, University of Melbourne.,Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute.,School of Computing and Information Systems, University of Melbourne
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17
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Nikam R, Kulandaisamy A, Harini K, Sharma D, Gromiha MM. ProThermDB: thermodynamic database for proteins and mutants revisited after 15 years. Nucleic Acids Res 2021; 49:D420-D424. [PMID: 33196841 PMCID: PMC7778892 DOI: 10.1093/nar/gkaa1035] [Citation(s) in RCA: 90] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 10/14/2020] [Accepted: 10/26/2020] [Indexed: 11/12/2022] Open
Abstract
ProThermDB is an updated version of the thermodynamic database for proteins and mutants (ProTherm), which has ∼31 500 data on protein stability, an increase of 84% from the previous version. It contains several thermodynamic parameters such as melting temperature, free energy obtained with thermal and denaturant denaturation, enthalpy change and heat capacity change along with experimental methods and conditions, sequence, structure and literature information. Besides, the current version of the database includes about 120 000 thermodynamic data obtained for different organisms and cell lines, which are determined by recent high throughput proteomics techniques using whole-cell approaches. In addition, we provided a graphical interface for visualization of mutations at sequence and structure levels. ProThermDB is cross-linked with other relevant databases, PDB, UniProt, PubMed etc. It is freely available at https://web.iitm.ac.in/bioinfo2/prothermdb/index.html without any login requirements. It is implemented in Python, HTML and JavaScript, and supports the latest versions of major browsers, such as Firefox, Chrome and Safari.
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Affiliation(s)
- Rahul Nikam
- Department of Biotechnology, Bhupat and Jyoti Mehta School of BioSciences, Indian Institute of Technology Madras, Chennai 600 036, Tamilnadu, India
| | - A Kulandaisamy
- Department of Biotechnology, Bhupat and Jyoti Mehta School of BioSciences, Indian Institute of Technology Madras, Chennai 600 036, Tamilnadu, India
| | - K Harini
- Department of Biotechnology, Bhupat and Jyoti Mehta School of BioSciences, Indian Institute of Technology Madras, Chennai 600 036, Tamilnadu, India
| | - Divya Sharma
- Department of Biotechnology, Bhupat and Jyoti Mehta School of BioSciences, Indian Institute of Technology Madras, Chennai 600 036, Tamilnadu, India
| | - M Michael Gromiha
- Department of Biotechnology, Bhupat and Jyoti Mehta School of BioSciences, Indian Institute of Technology Madras, Chennai 600 036, Tamilnadu, India
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18
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Yazar M, Özbek P. In Silico Tools and Approaches for the Prediction of Functional and Structural Effects of Single-Nucleotide Polymorphisms on Proteins: An Expert Review. OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY 2020; 25:23-37. [PMID: 33058752 DOI: 10.1089/omi.2020.0141] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Single-nucleotide polymorphisms (SNPs) are single-base variants that contribute to human biological variation and pathogenesis of many human diseases. Among all SNP types, nonsynonymous single-nucleotide polymorphisms (nsSNPs) can alter many structural, biochemical, and functional features of a protein such as folding characteristics, charge distribution, stability, dynamics, and interactions with other proteins/nucleotides. These modifications in the protein structure can lead nsSNPs to be closely associated with many multifactorial diseases such as cancer, diabetes, and neurodegenerative diseases. Predicting structural and functional effects of nsSNPs with experimental approaches can be time-consuming and costly; hence, computational prediction tools and algorithms are being widely and increasingly utilized in biology and medical research. This expert review examines the in silico tools and algorithms for the prediction of functional or structural effects of SNP variants, in addition to the description of the phenotypic effects of nsSNPs on protein structure, association between pathogenicity of variants, and functional or structural features of disease-associated variants. Finally, case studies investigating the functional and structural effects of nsSNPs on selected protein structures are highlighted. We conclude that creating a consistent workflow with a combination of in silico approaches or tools should be considered to increase the performance, accuracy, and precision of the biological and clinical predictions made in silico.
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Affiliation(s)
- Metin Yazar
- Department of Bioengineering, Marmara University, Göztepe, İstanbul, Turkey.,Department of Genetics and Bioengineering, Istanbul Okan University, Tuzla, Istanbul, Turkey
| | - Pemra Özbek
- Department of Bioengineering, Marmara University, Göztepe, İstanbul, Turkey
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19
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Mazurenko S. Predicting protein stability and solubility changes upon mutations: data perspective. ChemCatChem 2020. [DOI: 10.1002/cctc.202000933] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Affiliation(s)
- Stanislav Mazurenko
- Loschmidt Laboratories Department of Experimental Biology and RECETOX Faculty of Science Masaryk University Zerotinovo nam. 617/9 601 77 Brno Czech Republic
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20
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Bharmoria P, Correia SFH, Martins M, Hernández-Rodríguez MA, Ventura SPM, Ferreira RAS, Carlos LD, Coutinho JAP. Protein Cohabitation: Improving the Photochemical Stability of R-Phycoerythrin in the Solid State. J Phys Chem Lett 2020; 11:6249-6255. [PMID: 32643938 DOI: 10.1021/acs.jpclett.0c01491] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
The poor photochemical stability of R-phycoerythrin (R-PE) has been a bottleneck for its broad-spectrum applications. Inspired by nature, we studied a sustainable strategy of protein cohabitation to enhance R-PE stability by embedding it in a solid matrix of gelatin. Both pure R-PE and fresh phycobiliprotein (PBP) extracts recovered from Gracilaria gracilis were studied. The incorporation of R-PE in the gelatin-based films (gelatin-RPE and gelatin-PBPs) has improved its photochemical stability for at least 8 months, the longest time period reported so far. These results were evidenced by not only absorption but also emission quantum yield measurements (Φ). Moreover, the photostability of gelatin-RPE films upon continuous excitation with an AM1.5G solar simulator was tested and found to remain stable for 23 h after initial decreasing up to 250 min. In the end, another approach was established to allow 100% photostability for a 3 h exposure to an AM1.5G solar simulator by doping the gelatin-based film including R-Phycoerythrin with n-propyl gallate stabilized with Tween 80, allowing their use as naturally based optically active centers in photovoltaic applications.
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Affiliation(s)
- Pankaj Bharmoria
- CICECO-Aveiro Institute of Materials, Department of Chemistry, University of Aveiro, 3810-193 Aveiro, Portugal
| | - Sandra F H Correia
- Phantom-g, CICECO-Aveiro Institute of Materials, Department of Physics, University of Aveiro, 3810-193 Aveiro, Portugal
| | - Margarida Martins
- CICECO-Aveiro Institute of Materials, Department of Chemistry, University of Aveiro, 3810-193 Aveiro, Portugal
| | - Miguel A Hernández-Rodríguez
- Phantom-g, CICECO-Aveiro Institute of Materials, Department of Physics, University of Aveiro, 3810-193 Aveiro, Portugal
| | - Sónia P M Ventura
- CICECO-Aveiro Institute of Materials, Department of Chemistry, University of Aveiro, 3810-193 Aveiro, Portugal
| | - Rute A S Ferreira
- Phantom-g, CICECO-Aveiro Institute of Materials, Department of Physics, University of Aveiro, 3810-193 Aveiro, Portugal
| | - Luís D Carlos
- Phantom-g, CICECO-Aveiro Institute of Materials, Department of Physics, University of Aveiro, 3810-193 Aveiro, Portugal
| | - João A P Coutinho
- CICECO-Aveiro Institute of Materials, Department of Chemistry, University of Aveiro, 3810-193 Aveiro, Portugal
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21
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Narayan A, Gopi S, Lukose B, Naganathan AN. Electrostatic Frustration Shapes Folding Mechanistic Differences in Paralogous Bacterial Stress Response Proteins. J Mol Biol 2020; 432:4830-4839. [DOI: 10.1016/j.jmb.2020.06.026] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 06/30/2020] [Accepted: 06/30/2020] [Indexed: 01/06/2023]
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22
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Sternke M, Tripp KW, Barrick D. The use of consensus sequence information to engineer stability and activity in proteins. Methods Enzymol 2020; 643:149-179. [PMID: 32896279 DOI: 10.1016/bs.mie.2020.06.001] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
The goal of protein design is to create proteins that are stable, soluble, and active. Here we focus on one approach to protein design in which sequence information is used to create a "consensus" sequence. Such consensus sequences comprise the most common residue at each position in a multiple sequence alignment (MSA). After describing some general ideas that relate MSA and consensus sequences and presenting a statistical thermodynamic framework that relates consensus and non-consensus sequences to stability, we detail the process of designing a consensus sequence and survey reports of consensus design and characterization from the literature. Many of these consensus proteins retain native biological activities including ligand binding and enzyme activity. Remarkably, in most cases the consensus protein shows significantly higher stability than extant versions of the protein, as measured by thermal or chemical denaturation, consistent with the statistical thermodynamic model. To understand this stability increase, we compare various features of consensus sequences with the extant MSA sequences from which they were derived. Consensus sequences show enrichment in charged residues (most notably glutamate and lysine) and depletion of uncharged polar residues (glutamine, serine, and asparagine). Surprisingly, a survey of stability changes resulting from point substitutions show little correlation with residue frequencies at the corresponding positions within the MSA, suggesting that the high stability of consensus proteins may result from interactions among residue pairs or higher-order clusters. Whatever the source, the large number of reported successes demonstrates that consensus design is a viable route to generating active and in many cases highly stabilized proteins.
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Affiliation(s)
- Matt Sternke
- T.C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, MD, United States; Program in Molecular Biophysics, Johns Hopkins University, Baltimore, MD, United States
| | - Katherine W Tripp
- T.C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, MD, United States
| | - Doug Barrick
- T.C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, MD, United States.
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23
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Proteus: An algorithm for proposing stabilizing mutation pairs based on interactions observed in known protein 3D structures. BMC Bioinformatics 2020; 21:275. [PMID: 32611389 PMCID: PMC7330979 DOI: 10.1186/s12859-020-03575-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 05/28/2020] [Indexed: 11/10/2022] Open
Abstract
Background Protein engineering has many applications for industry, such as the development of new drugs, vaccines, treatment therapies, food, and biofuel production. A common way to engineer a protein is to perform mutations in functionally essential residues to optimize their function. However, the discovery of beneficial mutations for proteins is a complex task, with a time-consuming and high cost for experimental validation. Hence, computational approaches have been used to propose new insights for experiments narrowing the search space and reducing the costs. Results In this study, we developed Proteus (an acronym for Protein Engineering Supporter), a new algorithm for proposing mutation pairs in a target 3D structure. These suggestions are based on contacts observed in other known structures from Protein Data Bank (PDB). Proteus’ basic assumption is that if a non-interacting pair of amino acid residues in the target structure is exchanged to an interacting pair, this could enhance protein stability. This trade is only allowed if the main-chain conformation of the residues involved in the contact is conserved. Furthermore, no steric impediment is expected between the proposed mutations and the surrounding protein atoms. To evaluate Proteus, we performed two case studies with proteins of industrial interests. In the first case study, we evaluated if the mutations suggested by Proteus for four protein structures enhance the number of inter-residue contacts. Our results suggest that most mutations proposed by Proteus increase the number of interactions into the protein. In the second case study, we used Proteus to suggest mutations for a lysozyme protein. Then, we compared Proteus’ outcomes to mutations with available experimental evidence reported in the ProTherm database. Four mutations, in which our results agree with the experimental data, were found. This could be initial evidence that changes in the side-chain of some residues do not cause disturbances that harm protein structure stability. Conclusion We believe that Proteus could be used combined with other methods to give new insights into the rational development of engineered proteins. Proteus user-friendly web-based tool is available at <http://proteus.dcc.ufmg.br>.
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Kulandaisamy A, Sakthivel R, Gromiha MM. MPTherm: database for membrane protein thermodynamics for understanding folding and stability. Brief Bioinform 2020; 22:2119-2125. [PMID: 32337573 DOI: 10.1093/bib/bbaa064] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 03/19/2020] [Indexed: 12/21/2022] Open
Abstract
The functions of membrane proteins (MPs) are attributed to their structure and stability. Factors influencing the stability of MPs differ from globular proteins due to the presence of membrane spanning regions. Thermodynamic data of MPs aid to understand the relationship among their structure, stability and function. Although a wealth of experimental data on thermodynamics of MPs are reported in the literature, there is no database available explicitly for MPs. In this work, we have developed a database for MP thermodynamics, MPTherm, which contains more than 7000 thermodynamic data from about 320 MPs. Each entry contains protein sequence and structural information, membrane topology, experimental conditions, thermodynamic parameters such as melting temperature, free energy, enthalpy etc. and literature information. MPTherm assists users to retrieve the data by using different search and display options. We have also provided the sequence and structure visualization as well as cross-links to UniProt and PDB databases. MPTherm database is freely available at http://www.iitm.ac.in/bioinfo/mptherm/. It is implemented in HTML, PHP, MySQL and JavaScript, and supports the latest versions of major browsers, such as Firefox, Chrome and Opera. MPTherm would serve as an effective resource for understanding the stability of MPs, development of prediction tools and identifying drug targets for diseases associated with MPs.
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Affiliation(s)
| | - R Sakthivel
- Medical Biochemistry from University of Madras, India
| | - M Michael Gromiha
- Indian Institute of Technology Madras, Chennai 600036, Tamil Nadu, India
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25
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Hassan MO, Gassim DA, Albakrye AM, Elnasri HA, Khaier MA. In silico analysis of likely pathogenic variants in human GGCX gene. INFORMATICS IN MEDICINE UNLOCKED 2020. [DOI: 10.1016/j.imu.2020.100337] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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26
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Jespers W, Isaksen GV, Andberg TA, Vasile S, van Veen A, Åqvist J, Brandsdal BO, Gutiérrez-de-Terán H. QresFEP: An Automated Protocol for Free Energy Calculations of Protein Mutations in Q. J Chem Theory Comput 2019; 15:5461-5473. [DOI: 10.1021/acs.jctc.9b00538] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Willem Jespers
- Department of Cell and Molecular Biology, Biomedical Center, Uppsala University, Box 590, S-75124 Uppsala, Sweden
| | - Geir V. Isaksen
- Department of Cell and Molecular Biology, Biomedical Center, Uppsala University, Box 590, S-75124 Uppsala, Sweden
- Hylleraas Centre for Quantum Molecular Sciences, Department of Chemistry, University of Tromsø−The Arctic University of Norway, N9037 Tromsø, Norway
| | - Tor A.H. Andberg
- Hylleraas Centre for Quantum Molecular Sciences, Department of Chemistry, University of Tromsø−The Arctic University of Norway, N9037 Tromsø, Norway
| | - Silvana Vasile
- Department of Cell and Molecular Biology, Biomedical Center, Uppsala University, Box 590, S-75124 Uppsala, Sweden
| | - Amber van Veen
- Department of Cell and Molecular Biology, Biomedical Center, Uppsala University, Box 590, S-75124 Uppsala, Sweden
| | - Johan Åqvist
- Department of Cell and Molecular Biology, Biomedical Center, Uppsala University, Box 590, S-75124 Uppsala, Sweden
| | - Bjørn Olav Brandsdal
- Hylleraas Centre for Quantum Molecular Sciences, Department of Chemistry, University of Tromsø−The Arctic University of Norway, N9037 Tromsø, Norway
| | - Hugo Gutiérrez-de-Terán
- Department of Cell and Molecular Biology, Biomedical Center, Uppsala University, Box 590, S-75124 Uppsala, Sweden
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27
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Hervis YP, Valle A, Dunkel S, Klare JP, Canet L, Lanio ME, Alvarez C, Pazos IF, Steinhoff HJ. Architecture of the pore forming toxin sticholysin I in membranes. J Struct Biol 2019; 208:30-42. [PMID: 31330179 DOI: 10.1016/j.jsb.2019.07.008] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Revised: 07/02/2019] [Accepted: 07/17/2019] [Indexed: 12/28/2022]
Abstract
Sticholysin I (StI) is a toxin produced by the sea anemone Stichodactyla helianthus and belonging to the actinoporins family. Upon binding to sphingomyelin-containing membranes StI forms oligomeric pores, thereby leading to cell death. According to recent controversial experimental evidences, the pore architecture of actinoporins is a debated topic. Here, we investigated the StI topology in membranes by site-directed spin labeling and electron paramagnetic resonance spectroscopy. The results reveal that StI in membrane exhibits an oligomeric architecture with heterogeneous stoichiometry of predominantly eight or nine protomers, according to the available structural models. The StI topology resembles the conic pore structure reported for the actinoporin fragaceatoxin C. Our data show that StI coexists in two membrane-associated conformations, with the N-terminal segment either attached to the protein core or inserted in the membrane forming the pore. This finding suggests a 'pre-pore' to 'pore' transition determined by a conformational change that detaches the N-terminal segment.
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Affiliation(s)
- Yadira P Hervis
- Center for Protein Studies/Department of Biochemistry, University of Havana, Calle 25 #455 e/I y J, Vedado, Plaza de la Revolución, ZIP 10400, Havana, Cuba.
| | - Aisel Valle
- Center for Protein Studies/Department of Biochemistry, University of Havana, Calle 25 #455 e/I y J, Vedado, Plaza de la Revolución, ZIP 10400, Havana, Cuba.
| | - Sabrina Dunkel
- Department of Physics, University of Osnabrueck, Barbarastr. 7, 49076 Osnabrueck, Germany.
| | - Johann P Klare
- Department of Physics, University of Osnabrueck, Barbarastr. 7, 49076 Osnabrueck, Germany.
| | - Liem Canet
- Center for Protein Studies/Department of Biochemistry, University of Havana, Calle 25 #455 e/I y J, Vedado, Plaza de la Revolución, ZIP 10400, Havana, Cuba.
| | - Maria E Lanio
- Center for Protein Studies/Department of Biochemistry, University of Havana, Calle 25 #455 e/I y J, Vedado, Plaza de la Revolución, ZIP 10400, Havana, Cuba.
| | - Carlos Alvarez
- Center for Protein Studies/Department of Biochemistry, University of Havana, Calle 25 #455 e/I y J, Vedado, Plaza de la Revolución, ZIP 10400, Havana, Cuba.
| | - Isabel F Pazos
- Center for Protein Studies/Department of Biochemistry, University of Havana, Calle 25 #455 e/I y J, Vedado, Plaza de la Revolución, ZIP 10400, Havana, Cuba.
| | - Heinz-J Steinhoff
- Department of Physics, University of Osnabrueck, Barbarastr. 7, 49076 Osnabrueck, Germany.
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28
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Parasuraman P, Selvin JFA, Gromiha MM, Fukui K, Veluraja K. Investigation on the binding specificity of Agrocybe cylindracea galectin towards α(2,6)-linked sialyllactose by molecular modeling and molecular dynamics simulations. J Carbohydr Chem 2019. [DOI: 10.1080/07328303.2019.1631323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Affiliation(s)
| | | | - M. Michael Gromiha
- Department of Biotechnology, Indian Institute of Technology Madras, Chennai, India
| | - Kazuhiko Fukui
- National Institute of Advanced Industrial Science and Technology (AIST), Molecular Profiling Research Center for Drug Discovery (molprof), Tokyo, Japan
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29
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Abstract
In this review, we take a survey of bioinformatics databases and quantitative structure-activity relationship studies reported in published literature. Databases from the most general to special cancer-related ones have been included. Most commonly used methods of structure-based analysis of molecules have been reviewed, along with some case studies where they have been used in cancer research. This article is expected to be of use for general bioinformatics researchers interested in cancer and will also provide an update to those who have been actively pursuing this field of research.
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Affiliation(s)
- Adeel Malik
- Department of Biosciences, Jamia Millia Islamia University, New Delhi-110025, India
| | - Hemajit Singh
- Department of Biosciences, Jamia Millia Islamia University, New Delhi-110025, India
| | - Munazah Andrabi
- Department of Biosciences, Jamia Millia Islamia University, New Delhi-110025, India
| | - Syed Akhtar Husain
- Department of Biosciences, Jamia Millia Islamia University, New Delhi-110025, India
| | - Shandar Ahmad
- Department of Biosciences, Jamia Millia Islamia University, New Delhi-110025, India
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30
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Ford MC, Babaoglu K. Examining the Feasibility of Using Free Energy Perturbation (FEP+) in Predicting Protein Stability. J Chem Inf Model 2017; 57:1276-1285. [PMID: 28520421 DOI: 10.1021/acs.jcim.7b00002] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Melissa Coates Ford
- Department of Modeling & Informatics, MRL, Merck & Co., Inc., 770 Sumneytown Pike, West Point, Pennsylvania 19486, United States
| | - Kerim Babaoglu
- Department of Modeling & Informatics, MRL, Merck & Co., Inc., 770 Sumneytown Pike, West Point, Pennsylvania 19486, United States
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31
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Chitranshi N, Dheer Y, Wall RV, Gupta V, Abbasi M, Graham SL, Gupta V. Computational analysis unravels novel destructive single nucleotide polymorphisms in the non-synonymous region of human caveolin gene. GENE REPORTS 2017. [DOI: 10.1016/j.genrep.2016.08.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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32
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Gopi S, Rajasekaran N, Singh A, Ranu S, Naganathan AN. Energetic and topological determinants of a phosphorylation-induced disorder-to-order protein conformational switch. Phys Chem Chem Phys 2016; 17:27264-9. [PMID: 26421497 DOI: 10.1039/c5cp04765j] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
We show that the phosphorylation of 4E-BP2 acts as a triggering event to shape its folding-function landscape that is delicately balanced between conflicting favorable energetics and intrinsically unfavorable topological connectivity. We further provide first evidence that the fitness landscapes of proteins at the threshold of disorder can differ considerably from ordered domains.
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Affiliation(s)
- Soundhararajan Gopi
- Department of Biotechnology, Bhupat & Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600036, India.
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33
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Magyar C, Gromiha MM, Sávoly Z, Simon I. The role of stabilization centers in protein thermal stability. Biochem Biophys Res Commun 2016; 471:57-62. [DOI: 10.1016/j.bbrc.2016.01.181] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2016] [Accepted: 01/30/2016] [Indexed: 11/25/2022]
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34
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Gromiha MM, Anoosha P, Huang LT. Applications of Protein Thermodynamic Database for Understanding Protein Mutant Stability and Designing Stable Mutants. Methods Mol Biol 2016; 1415:71-89. [PMID: 27115628 DOI: 10.1007/978-1-4939-3572-7_4] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Protein stability is the free energy difference between unfolded and folded states of a protein, which lies in the range of 5-25 kcal/mol. Experimentally, protein stability is measured with circular dichroism, differential scanning calorimetry, and fluorescence spectroscopy using thermal and denaturant denaturation methods. These experimental data have been accumulated in the form of a database, ProTherm, thermodynamic database for proteins and mutants. It also contains sequence and structure information of a protein, experimental methods and conditions, and literature information. Different features such as search, display, and sorting options and visualization tools have been incorporated in the database. ProTherm is a valuable resource for understanding/predicting the stability of proteins and it can be accessed at http://www.abren.net/protherm/ . ProTherm has been effectively used to examine the relationship among thermodynamics, structure, and function of proteins. We describe the recent progress on the development of methods for understanding/predicting protein stability, such as (1) general trends on mutational effects on stability, (2) relationship between the stability of protein mutants and amino acid properties, (3) applications of protein three-dimensional structures for predicting their stability upon point mutations, (4) prediction of protein stability upon single mutations from amino acid sequence, and (5) prediction methods for addressing double mutants. A list of online resources for predicting has also been provided.
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Affiliation(s)
- M Michael Gromiha
- Department of Biotechnology, Bhupat & Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, 600 036, India.
| | - P Anoosha
- Department of Biotechnology, Bhupat & Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, 600 036, India
| | - Liang-Tsung Huang
- Department of Medical Informatics, Tzu Chi University, Hualien, 970, Taiwan
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35
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Structure Based Thermostability Prediction Models for Protein Single Point Mutations with Machine Learning Tools. PLoS One 2015; 10:e0138022. [PMID: 26361227 PMCID: PMC4567301 DOI: 10.1371/journal.pone.0138022] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2015] [Accepted: 08/24/2015] [Indexed: 11/19/2022] Open
Abstract
Thermostability issue of protein point mutations is a common occurrence in protein engineering. An application which predicts the thermostability of mutants can be helpful for guiding decision making process in protein design via mutagenesis. An in silico point mutation scanning method is frequently used to find “hot spots” in proteins for focused mutagenesis. ProTherm (http://gibk26.bio.kyutech.ac.jp/jouhou/Protherm/protherm.html) is a public database that consists of thousands of protein mutants’ experimentally measured thermostability. Two data sets based on two differently measured thermostability properties of protein single point mutations, namely the unfolding free energy change (ddG) and melting temperature change (dTm) were obtained from this database. Folding free energy change calculation from Rosetta, structural information of the point mutations as well as amino acid physical properties were obtained for building thermostability prediction models with informatics modeling tools. Five supervised machine learning methods (support vector machine, random forests, artificial neural network, naïve Bayes classifier, K nearest neighbor) and partial least squares regression are used for building the prediction models. Binary and ternary classifications as well as regression models were built and evaluated. Data set redundancy and balancing, the reverse mutations technique, feature selection, and comparison to other published methods were discussed. Rosetta calculated folding free energy change ranked as the most influential features in all prediction models. Other descriptors also made significant contributions to increasing the accuracy of the prediction models.
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36
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An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions. Int J Mol Sci 2015. [PMID: 26198229 PMCID: PMC4519904 DOI: 10.3390/ijms160715384] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Protein disordered regions are segments of a protein chain that do not adopt a stable structure. Thus far, a variety of protein disorder prediction methods have been developed and have been widely used, not only in traditional bioinformatics domains, including protein structure prediction, protein structure determination and function annotation, but also in many other biomedical fields. The relationship between intrinsically-disordered proteins and some human diseases has played a significant role in disorder prediction in disease identification and epidemiological investigations. Disordered proteins can also serve as potential targets for drug discovery with an emphasis on the disordered-to-ordered transition in the disordered binding regions, and this has led to substantial research in drug discovery or design based on protein disordered region prediction. Furthermore, protein disorder prediction has also been applied to healthcare by predicting the disease risk of mutations in patients and studying the mechanistic basis of diseases. As the applications of disorder prediction increase, so too does the need to make quick and accurate predictions. To fill this need, we also present a new approach to predict protein residue disorder using wide sequence windows that is applicable on the genomic scale.
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37
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Saranya N, Saravanan KM, Michael Gromiha M, Selvaraj S. Analysis of secondary structural and physicochemical changes in protein-protein complexes. J Biomol Struct Dyn 2015; 34:508-16. [PMID: 25990569 DOI: 10.1080/07391102.2015.1050695] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
Conformation switching in protein-protein complexes is considered important for the molecular recognition process. Overall analysis of 123 protein-protein complexes in a benchmark data-set showed that 6.8% of residues switched over their secondary structure conformation upon complex formation. Amino acid residue-wise preference for conformation change has been analyzed in binding and non-binding site residues separately. In this analysis, residues such as Ser, Leu, Glu, and Lys had higher frequency of secondary structural conformation change. The change of helix to coil and sheet to coil conformation and vice versa has been observed frequently, whereas the conformation change of helix to extended sheet occurred rarely in the studied complexes. Influence of conformation change toward the N and C terminal on either side of the binding site residues has been analyzed. Further, analysis on φ and ψ angle variation, conservation, stability, and solvent accessibility have been performed on binding site residues. Knowledge obtained from the present study could be effectively employed in the protein-protein modeling and docking studies.
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Affiliation(s)
- N Saranya
- a Department of Bioinformatics , School of Life Sciences, Bharathidasan University , Tiruchirappalli 620024 , India.,b Department of Plant Molecular Biology and Bioinformatics , Tamil Nadu Agricultural University , Coimbatore , Tamil Nadu 641003 , India
| | - K M Saravanan
- a Department of Bioinformatics , School of Life Sciences, Bharathidasan University , Tiruchirappalli 620024 , India.,c Center of Excellence in Bioinformatics, School of Biotechnology , Madurai Kamaraj University , Madurai , Tamil Nadu 625 021 , India
| | - M Michael Gromiha
- d Department of Biotechnology , Indian Institute of Technology Madras , Chennai , Tamil Nadu 600036 , India
| | - S Selvaraj
- a Department of Bioinformatics , School of Life Sciences, Bharathidasan University , Tiruchirappalli 620024 , India
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38
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Parasuraman P, Murugan V, Selvin JFA, Gromiha MM, Fukui K, Veluraja K. Theoretical investigation on the glycan-binding specificity ofAgrocybe cylindraceagalectin using molecular modeling and molecular dynamics simulation studies. J Mol Recognit 2015; 28:528-38. [DOI: 10.1002/jmr.2468] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2014] [Revised: 01/23/2015] [Accepted: 01/23/2015] [Indexed: 11/06/2022]
Affiliation(s)
- Ponnusamy Parasuraman
- Department of Physics; Manonmaniam Sundaranar University; Tirunelveli Tamil Nadu 627012 India
| | - Veeramani Murugan
- Department of Physics; Manonmaniam Sundaranar University; Tirunelveli Tamil Nadu 627012 India
| | | | - M Michael Gromiha
- Department of Biotechnology; Indian Institute of Technology Madras; Chennai Tamil Nadu 600036 India
| | - Kazuhiko Fukui
- Molecular Profiling Research Center for Drug Discovery (molprof); National Institute of Advanced Industrial Science and Technology (AIST); 2-4-7 Aomi Koto-ku Tokyo 135-0064 Japan
| | - Kasinadar Veluraja
- School of Advanced Sciences; VIT University; Vellore Tamil Nadu 632014 India
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39
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Parasuraman P, Murugan V, Selvin JFA, Gromiha MM, Fukui K, Veluraja K. Insights into the binding specificity of wild type and mutated wheat germ agglutinin towards Neu5Acα(2-3)Gal: a study by in silico mutations and molecular dynamics simulations. J Mol Recognit 2015; 27:482-92. [PMID: 24984865 DOI: 10.1002/jmr.2369] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2013] [Revised: 02/02/2014] [Accepted: 02/02/2014] [Indexed: 02/06/2023]
Abstract
Wheat germ agglutinin (WGA) is a plant lectin, which specifically recognizes the sugars NeuNAc and GlcNAc. Mutated WGA with enhanced binding specificity can be used as biomarkers for cancer. In silico mutations are performed at the active site of WGA to enhance the binding specificity towards sialylglycans, and molecular dynamics simulations of 20 ns are carried out for wild type and mutated WGAs (WGA1, WGA2, and WGA3) in complex with sialylgalactose to examine the change in binding specificity. MD simulations reveal the change in binding specificity of wild type and mutated WGAs towards sialylgalactose and bound conformational flexibility of sialylgalactose. The mutated polar amino acid residues Asn114 (S114N), Lys118 (G118K), and Arg118 (G118R) make direct and water mediated hydrogen bonds and hydrophobic interactions with sialylgalactose. An analysis of possible hydrogen bonds, hydrophobic interactions, total pair wise interaction energy between active site residues and sialylgalactose and MM-PBSA free energy calculation reveals the plausible binding modes and the role of water in stabilizing different binding modes. An interesting observation is that the binding specificity of mutated WGAs (cyborg lectin) towards sialylgalactose is found to be higher in double point mutation (WGA3). One of the substituted residues Arg118 plays a crucial role in sugar binding. Based on the interactions and energy calculations, it is concluded that the order of binding specificity of WGAs towards sialylgalactose is WGA3 > WGA1 > WGA2 > WGA. On comparing with the wild type, double point mutated WGA (WGA3) exhibits increased specificity towards sialylgalactose, and thus, it can be effectively used in targeted drug delivery and as biological cell marker in cancer therapeutics.
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Affiliation(s)
- Ponnusamy Parasuraman
- Department of Physics, Manonmaniam Sundaranar University, Tirunelveli, 627 012, India
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40
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Carter JW, Baker CM, Best RB, De Sancho D. Engineering folding dynamics from two-state to downhill: application to λ-repressor. J Phys Chem B 2013; 117:13435-43. [PMID: 24079652 PMCID: PMC3840902 DOI: 10.1021/jp405904g] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
![]()
One
strategy for reaching the downhill folding regime, primarily
exploited for the λ6–85 protein fragment,
consists of cumulatively introducing mutations that speed up folding.
This is an experimentally demanding process where chemical intuition
usually serves as a guide for the choice of amino acid residues to
mutate. Such an approach can be aided by computational methods that
screen for protein engineering hot spots. Here we present one such
method that involves sampling the energy landscape of the pseudo-wild-type
protein and investigating the effect of point mutations on this landscape.
Using a novel metric for the cooperativity, we identify those residues
leading to the least cooperative folding. The folding dynamics of
the selected mutants are then directly characterized and the differences
in the kinetics are analyzed within a Markov-state model framework.
Although the method is general, here we present results for a coarse-grained
topology-based simulation model of λ-repressor, whose barrier
is reduced from an initial value of ∼4kBT at the midpoint to ∼1kBT, thereby reaching the downhill folding
regime.
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Affiliation(s)
- James W Carter
- Department of Chemistry, University of Cambridge , Lensfield Road, Cambridge CB2 1EW, United Kingdom
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41
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Gromiha MM, Pathak MC, Saraboji K, Ortlund EA, Gaucher EA. Hydrophobic environment is a key factor for the stability of thermophilic proteins. Proteins 2013; 81:715-21. [PMID: 23319168 DOI: 10.1002/prot.24232] [Citation(s) in RCA: 85] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2012] [Revised: 11/16/2012] [Accepted: 11/28/2012] [Indexed: 11/07/2022]
Affiliation(s)
- M Michael Gromiha
- Department of Biotechnology, Indian Institute of Technology Madras, Chennai 600036, Tamilnadu, India.
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42
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Lu CT, Huang KY, Su MG, Lee TY, Bretaña NA, Chang WC, Chen YJ, Chen YJ, Huang HD. DbPTM 3.0: an informative resource for investigating substrate site specificity and functional association of protein post-translational modifications. Nucleic Acids Res 2012. [PMID: 23193290 PMCID: PMC3531199 DOI: 10.1093/nar/gks1229] [Citation(s) in RCA: 165] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
Protein modification is an extremely important post-translational regulation that adjusts the physical and chemical properties, conformation, stability and activity of a protein; thus altering protein function. Due to the high throughput of mass spectrometry (MS)-based methods in identifying site-specific post-translational modifications (PTMs), dbPTM (http://dbPTM.mbc.nctu.edu.tw/) is updated to integrate experimental PTMs obtained from public resources as well as manually curated MS/MS peptides associated with PTMs from research articles. Version 3.0 of dbPTM aims to be an informative resource for investigating the substrate specificity of PTM sites and functional association of PTMs between substrates and their interacting proteins. In order to investigate the substrate specificity for modification sites, a newly developed statistical method has been applied to identify the significant substrate motifs for each type of PTMs containing sufficient experimental data. According to the data statistics in dbPTM, >60% of PTM sites are located in the functional domains of proteins. It is known that most PTMs can create binding sites for specific protein-interaction domains that work together for cellular function. Thus, this update integrates protein–protein interaction and domain–domain interaction to determine the functional association of PTM sites located in protein-interacting domains. Additionally, the information of structural topologies on transmembrane (TM) proteins is integrated in dbPTM in order to delineate the structural correlation between the reported PTM sites and TM topologies. To facilitate the investigation of PTMs on TM proteins, the PTM substrate sites and the structural topology are graphically represented. Also, literature information related to PTMs, orthologous conservations and substrate motifs of PTMs are also provided in the resource. Finally, this version features an improved web interface to facilitate convenient access to the resource.
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Affiliation(s)
- Cheng-Tsung Lu
- Department of Computer Science and Engineering, Yuan Ze University, Chung-Li 320, Taiwan
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43
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Xu D. Protein databases on the internet. CURRENT PROTOCOLS IN PROTEIN SCIENCE 2012; Chapter 2:2.6.1-2.6.17. [PMID: 23151744 DOI: 10.1002/0471140864.ps0206s70] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Protein databases have become a crucial part of modern biology. Huge amounts of data for protein structures, functions, and particularly sequences are being generated. Searching databases is often the first step in the study of a new protein. Comparison between proteins or between protein families provides information about the relationship between proteins within a genome or across different species, and hence offers much more information than can be obtained by studying only an isolated protein. In addition, secondary databases derived from experimental databases are also widely available. These databases reorganize and annotate the data or provide predictions. The use of multiple databases often helps researchers understand the structure and function of a protein. Although some protein databases are widely known, they are far from being fully utilized in the protein science community. This unit provides a starting point for readers to explore the potential of protein databases on the Internet.
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Affiliation(s)
- Dong Xu
- Department of Computer Science and Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, Missouri
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44
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Huang H, Sarai A. Analysis of the relationships between evolvability, thermodynamics, and the functions of intrinsically disordered proteins/regions. Comput Biol Chem 2012; 41:51-7. [PMID: 23153654 DOI: 10.1016/j.compbiolchem.2012.10.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2012] [Revised: 08/23/2012] [Accepted: 10/11/2012] [Indexed: 01/08/2023]
Abstract
The evolvability of proteins is not only restricted by functional and structural importance, but also by other factors such as gene duplication, protein stability, and an organism's robustness. Recently, intrinsically disordered proteins (IDPs)/regions (IDRs) have been suggested to play a role in facilitating protein evolution. However, the mechanisms by which this occurs remain largely unknown. To address this, we have systematically analyzed the relationship between the evolvability, stability, and function of IDPs/IDRs. Evolutionary analysis shows that more recently emerged IDRs have higher evolutionary rates with more functional constraints relaxed (or experiencing more positive selection), and that this may have caused accelerated evolution in the flanking regions and in the whole protein. A systematic analysis of observed stability changes due to single amino acid mutations in IDRs and ordered regions shows that while most mutations induce a destabilizing effect in proteins, mutations in IDRs cause smaller stability changes than in ordered regions. The weaker impact of mutations in IDRs on protein stability may have advantages for protein evolvability in the gain of new functions. Interestingly, however, an analysis of functional motifs in the PROSITE and ELM databases showed that motifs in IDRs are more conserved, characterized by smaller entropy and lower evolutionary rate, than in ordered regions. This apparently opposing evolutionary effect may be partly due to the flexible nature of motifs in IDRs, which require some key amino acid residues to engage in tighter interactions with other molecules. Our study suggests that the unique conformational and thermodynamic characteristics of IDPs/IDRs play an important role in the evolvability of proteins to gain new functions.
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Affiliation(s)
- He Huang
- Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka 820-8502, Japan.
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45
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Juritz E, Fornasari MS, Martelli PL, Fariselli P, Casadio R, Parisi G. On the effect of protein conformation diversity in discriminating among neutral and disease related single amino acid substitutions. BMC Genomics 2012; 13 Suppl 4:S5. [PMID: 22759653 PMCID: PMC3303731 DOI: 10.1186/1471-2164-13-s4-s5] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Non-synonymous coding SNPs (nsSNPs) that are associated to disease can also be related with alterations in protein stability. Computational methods are available to predict the effect of single amino acid substitutions (SASs) on protein stability based on a single folded structure. However, the native state of a protein is not unique and it is better represented by the ensemble of its conformers in dynamic equilibrium. The maintenance of the ensemble is essential for protein function. In this work we investigated how protein conformational diversity can affect the discrimination of neutral and disease related SASs based on protein stability estimations. For this purpose, we used 119 proteins with 803 associated SASs, 60% of which are disease related. Each protein was associated with its corresponding set of available conformers as found in the Protein Conformational Database (PCDB). Our dataset contains proteins with different extensions of conformational diversity summing up a total number of 1023 conformers. RESULTS The existence of different conformers for a given protein introduces great variability in the estimation of the protein stability (ΔΔG) after a single amino acid substitution (SAS) as computed with FoldX. Indeed, in 35% of our protein set at least one SAS can be described as stabilizing, destabilizing or neutral when a cutoff value of ±2 kcal/mol is adopted for discriminating neutral from perturbing SASs. However, when the ΔΔG variability among conformers is taken into account, the correlation among the perturbation of protein stability and the corresponding disease or neutral phenotype increases as compared with the same analysis on single protein structures. At the conformer level, we also found that the different conformers correlate in a different way to the corresponding phenotype. CONCLUSIONS Our results suggest that the consideration of conformational diversity can improve the discrimination of neutral and disease related protein SASs based on the evaluation of the corresponding Gibbs free energy change.
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Affiliation(s)
- Ezequiel Juritz
- Departamento de Ciencia y Tecnología, Universidad Nacional de Quilmes, Buenos Aires, Argentina
| | - Maria Silvina Fornasari
- Departamento de Ciencia y Tecnología, Universidad Nacional de Quilmes, Buenos Aires, Argentina
| | | | - Piero Fariselli
- Biocomputing Group, Department of Computer Science, University of Bologna, Italy
| | - Rita Casadio
- Biocomputing Group, Department of Biology, University of Bologna, Italy
| | - Gustavo Parisi
- Departamento de Ciencia y Tecnología, Universidad Nacional de Quilmes, Buenos Aires, Argentina
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46
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Real value prediction of protein folding rate change upon point mutation. J Comput Aided Mol Des 2012; 26:339-47. [DOI: 10.1007/s10822-012-9560-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2011] [Accepted: 03/02/2012] [Indexed: 10/28/2022]
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47
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Affiliation(s)
- Dong Xu
- Department of Computer Science and Christopher S. Bond Life Sciences Center, University of Missouri Columbia Missouri
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48
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Valle A, López-Castilla A, Pedrera L, Martínez D, Tejuca M, Campos J, Fando R, Lissi E, Álvarez C, Lanio M, Pazos F, Schreier S. Cys mutants in functional regions of Sticholysin I clarify the participation of these residues in pore formation. Toxicon 2011; 58:8-17. [DOI: 10.1016/j.toxicon.2011.04.005] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2010] [Revised: 04/01/2011] [Accepted: 04/05/2011] [Indexed: 10/18/2022]
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49
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Gong S, Worth CL, Cheng TMK, Blundell TL. Meet Me Halfway: When Genomics Meets Structural Bioinformatics. J Cardiovasc Transl Res 2011; 4:281-303. [DOI: 10.1007/s12265-011-9259-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2010] [Accepted: 02/08/2011] [Indexed: 01/08/2023]
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50
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Huang LT, Lai LF, Gromiha MM. Human-readable rule generator for integrating amino scid sequence information and stability of mutant proteins. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2010; 7:681-687. [PMID: 21030735 DOI: 10.1109/tcbb.2008.128] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Most of the bioinformatics tools developed for predicting mutant protein stability appear as a black box and the relationship between amino acid sequence/structure and stability is hidden to the users. We have addressed this problem and developed a human-readable rule generator for integrating the knowledge of amino acid sequence and experimental stability change upon single mutation. Using information about the original residue, substituted residue, and three neighboring residues, classification rules have been generated to discriminate the stabilizing and destabilizing mutants and explore the basis for experimental data. These rules are human readable, and hence, the method enhances the synergy between expert knowledge and computational system. Furthermore, the performance of the rules has been assessed on a nonredundant data set of 1,859 mutants and we obtained an accuracy of 80 percent using cross validation. The results showed that the method could be effectively used as a tool for both knowledge discovery and predicting mutant protein stability. We have developed a Web for classification rule generator and it is freely available at http://bioinformatics.myweb.hinet.net/irobot.htm.
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Affiliation(s)
- Liang-Tsung Huang
- Department of Information Communication, Mingdao University, Changhua, Taiwan.
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