1
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Zhao K, Zhao P, Wang S, Xia Y, Zhang G. FoldPAthreader: predicting protein folding pathway using a novel folding force field model derived from known protein universe. Genome Biol 2024; 25:152. [PMID: 38862984 PMCID: PMC11167914 DOI: 10.1186/s13059-024-03291-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 05/29/2024] [Indexed: 06/13/2024] Open
Abstract
Protein folding has become a tractable problem with the significant advances in deep learning-driven protein structure prediction. Here we propose FoldPAthreader, a protein folding pathway prediction method that uses a novel folding force field model by exploring the intrinsic relationship between protein evolution and folding from the known protein universe. Further, the folding force field is used to guide Monte Carlo conformational sampling, driving the protein chain fold into its native state by exploring potential intermediates. On 30 example targets, FoldPAthreader successfully predicts 70% of the proteins whose folding pathway is consistent with biological experimental data.
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Affiliation(s)
- Kailong Zhao
- College of Information Engineering, Zhejiang University of Technology, HangZhou, 310023, China
| | - Pengxin Zhao
- College of Information Engineering, Zhejiang University of Technology, HangZhou, 310023, China
| | - Suhui Wang
- College of Information Engineering, Zhejiang University of Technology, HangZhou, 310023, China
| | - Yuhao Xia
- College of Information Engineering, Zhejiang University of Technology, HangZhou, 310023, China
| | - Guijun Zhang
- College of Information Engineering, Zhejiang University of Technology, HangZhou, 310023, China.
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2
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Rosenberg AA, Yehishalom N, Marx A, Bronstein AM. An amino-domino model described by a cross-peptide-bond Ramachandran plot defines amino acid pairs as local structural units. Proc Natl Acad Sci U S A 2023; 120:e2301064120. [PMID: 37878722 PMCID: PMC10623034 DOI: 10.1073/pnas.2301064120] [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: 01/20/2023] [Accepted: 08/24/2023] [Indexed: 10/27/2023] Open
Abstract
Protein structure, both at the global and local level, dictates function. Proteins fold from chains of amino acids, forming secondary structures, α-helices and β-strands, that, at least for globular proteins, subsequently fold into a three-dimensional structure. Here, we show that a Ramachandran-type plot focusing on the two dihedral angles separated by the peptide bond, and entirely contained within an amino acid pair, defines a local structural unit. We further demonstrate the usefulness of this cross-peptide-bond Ramachandran plot by showing that it captures β-turn conformations in coil regions, that traditional Ramachandran plot outliers fall into occupied regions of our plot, and that thermophilic proteins prefer specific amino acid pair conformations. Further, we demonstrate experimentally that the effect of a point mutation on backbone conformation and protein stability depends on the amino acid pair context, i.e., the identity of the adjacent amino acid, in a manner predictable by our method.
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Affiliation(s)
- Aviv A. Rosenberg
- Department of Computer Science, Technion–Israel Institute of Technology, Haifa32000, Israel
| | - Nitsan Yehishalom
- Faculty of Biology, Technion–Israel Institute of Technology, Haifa32000, Israel
| | - Ailie Marx
- Department of Computer Science, Technion–Israel Institute of Technology, Haifa32000, Israel
| | - Alex M. Bronstein
- Department of Computer Science, Technion–Israel Institute of Technology, Haifa32000, Israel
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3
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Milchevskiy YV, Milchevskaya VY, Nikitin AM, Kravatsky YV. Effective Local and Secondary Protein Structure Prediction by Combining a Neural Network-Based Approach with Extensive Feature Design and Selection without Reliance on Evolutionary Information. Int J Mol Sci 2023; 24:15656. [PMID: 37958639 PMCID: PMC10648199 DOI: 10.3390/ijms242115656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 10/24/2023] [Accepted: 10/25/2023] [Indexed: 11/15/2023] Open
Abstract
Protein structure prediction continues to pose multiple challenges despite outstanding progress that is largely attributable to the use of novel machine learning techniques. One of the widely used representations of local 3D structure-protein blocks (PBs)-can be treated in a similar way to secondary structure classes. Here, we present a new approach for predicting local conformation in terms of PB classes solely from amino acid sequences. We apply the RMSD metric to ensure unambiguous future 3D protein structure recovery. The selection of statistically assessed features is a key component of the proposed method. We suggest that ML input features should be created from the statistically significant predictors that are derived from the amino acids' physicochemical properties and the resolved structures' statistics. The statistical significance of the suggested features was assessed using a stepwise regression analysis that permitted the evaluation of the contribution and statistical significance of each predictor. We used the set of 380 statistically significant predictors as a learning model for the regression neural network that was trained using the PISCES30 dataset. When using the same dataset and metrics for benchmarking, our method outperformed all other methods reported in the literature for the CB513 nonredundant dataset (for the PBs, Q16 = 81.01%, and for the DSSP, Q3 = 85.99% and Q8 = 79.35%).
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Affiliation(s)
- Yury V. Milchevskiy
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Vavilov Str., 32, 119991 Moscow, Russia (Y.V.K.)
| | - Vladislava Y. Milchevskaya
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Vavilov Str., 32, 119991 Moscow, Russia (Y.V.K.)
- Institute of Medical Statistics and Bioinformatics, University of Cologne, 50931 Cologne, Germany
| | - Alexei M. Nikitin
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Vavilov Str., 32, 119991 Moscow, Russia (Y.V.K.)
| | - Yury V. Kravatsky
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Vavilov Str., 32, 119991 Moscow, Russia (Y.V.K.)
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia
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4
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Kazmirchuk TDD, Bradbury-Jost C, Withey TA, Gessese T, Azad T, Samanfar B, Dehne F, Golshani A. Peptides of a Feather: How Computation Is Taking Peptide Therapeutics under Its Wing. Genes (Basel) 2023; 14:1194. [PMID: 37372372 DOI: 10.3390/genes14061194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 05/24/2023] [Accepted: 05/26/2023] [Indexed: 06/29/2023] Open
Abstract
Leveraging computation in the development of peptide therapeutics has garnered increasing recognition as a valuable tool to generate novel therapeutics for disease-related targets. To this end, computation has transformed the field of peptide design through identifying novel therapeutics that exhibit enhanced pharmacokinetic properties and reduced toxicity. The process of in-silico peptide design involves the application of molecular docking, molecular dynamics simulations, and machine learning algorithms. Three primary approaches for peptide therapeutic design including structural-based, protein mimicry, and short motif design have been predominantly adopted. Despite the ongoing progress made in this field, there are still significant challenges pertaining to peptide design including: enhancing the accuracy of computational methods; improving the success rate of preclinical and clinical trials; and developing better strategies to predict pharmacokinetics and toxicity. In this review, we discuss past and present research pertaining to the design and development of in-silico peptide therapeutics in addition to highlighting the potential of computation and artificial intelligence in the future of disease therapeutics.
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Affiliation(s)
- Thomas David Daniel Kazmirchuk
- Department of Biology, and the Ottawa Institute of Systems Biology (OISB), Carleton University, Ottawa, ON K1S 5B6, Canada
| | - Calvin Bradbury-Jost
- Department of Biology, and the Ottawa Institute of Systems Biology (OISB), Carleton University, Ottawa, ON K1S 5B6, Canada
| | - Taylor Ann Withey
- Department of Biology, and the Ottawa Institute of Systems Biology (OISB), Carleton University, Ottawa, ON K1S 5B6, Canada
| | - Tadesse Gessese
- Department of Biology, and the Ottawa Institute of Systems Biology (OISB), Carleton University, Ottawa, ON K1S 5B6, Canada
| | - Taha Azad
- Department of Microbiology and Infectious Diseases, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada
- Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke (CHUS), Sherbrooke, QC J1H 5N4, Canada
| | - Bahram Samanfar
- Department of Biology, and the Ottawa Institute of Systems Biology (OISB), Carleton University, Ottawa, ON K1S 5B6, Canada
- Agriculture and Agri-Food Canada, Ottawa Research and Development Centre (ORDC), Ottawa, ON K1A 0C6, Canada
| | - Frank Dehne
- School of Computer Science, Carleton University, Ottawa, ON K1S 5B6, Canada
| | - Ashkan Golshani
- Department of Biology, and the Ottawa Institute of Systems Biology (OISB), Carleton University, Ottawa, ON K1S 5B6, Canada
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5
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Das JK, Heryakusuma C, Susanti D, Choudhury PP, Mukhopadhyay B. Reduced Protein Sequence Patterns in Identifying Key Structural Elements of Dissimilatory Sulfite Reductase Homologs. Comput Biol Chem 2022; 98:107691. [DOI: 10.1016/j.compbiolchem.2022.107691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2022] [Revised: 04/26/2022] [Accepted: 04/26/2022] [Indexed: 11/03/2022]
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6
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Maljković MM, Mitić NS, de Brevern AG. Prediction of structural alphabet protein blocks using data mining. Biochimie 2022; 197:74-85. [PMID: 35143919 DOI: 10.1016/j.biochi.2022.01.019] [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: 09/20/2021] [Revised: 01/22/2022] [Accepted: 01/31/2022] [Indexed: 11/17/2022]
Abstract
3D protein structures determine proteins' biological functions. The 3D structure of the protein backbone can be approximated using the prototypes of local protein conformations. Sets of these prototypes are called structural alphabets (SAs). Amongst several approaches to the prediction of 3D structures from amino acid sequences, one approach is based on the prediction of SA prototypes for a given amino acid sequence. Protein Blocks (PBs) is the most known SA, and it is composed of 16 prototypes of five consecutive amino acids which were identified as optimal prototypes considering the ability to correctly approximate the local structure and the prediction accuracy of prototypes from an amino acid sequence. We developed models for PBs prediction from sequence information using different data mining approaches and machine learning algorithms. Besides the amino acid sequences, the results of the following tools were used to train the models: the Spider3 predictor of protein structure properties, several predictors of the protein's intrinsically disordered regions, and a tool for finding repeats in amino acid sequences. The highest accuracy of the constructed models is 80%, which is a significant improvement compared to the previous best available prediction, whose accuracy was 61%. Analyzing the models constructed by applying different algorithms, it was noticed that the significance of input attributes differs among the models constructed by algorithms. Using the information about amino acids belonging to intrinsically disordered regions and repeats improves the precision of prediction for some PBs using the CART classification algorithm, while this is not the case with the C5.0 classification algorithm. Improved prediction approaches can have interesting applications in protein structural model approaches or computational protein design.
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Affiliation(s)
- Mirjana M Maljković
- Faculty of Mathematics, University of Belgrade, Studentski Trg 16, 11000, Belgrade, Serbia.
| | - Nenad S Mitić
- Faculty of Mathematics, University of Belgrade, Studentski Trg 16, 11000, Belgrade, Serbia
| | - Alexandre G de Brevern
- Université de Paris, INSERM UMR_S 1134, DSIMB, Université de la Réunion, INTS6, Rue Alexandre Cabanel, 75015, Paris, France
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7
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de Brevern AG, Rebehmed J. Current status of PTMs structural databases: applications, limitations and prospects. Amino Acids 2022; 54:575-590. [PMID: 35020020 DOI: 10.1007/s00726-021-03119-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Accepted: 12/20/2021] [Indexed: 12/11/2022]
Abstract
Protein 3D structures, determined by their amino acid sequences, are the support of major crucial biological functions. Post-translational modifications (PTMs) play an essential role in regulating these functions by altering the physicochemical properties of proteins. By virtue of their importance, several PTM databases have been developed and released in decades, but very few of these databases incorporate real 3D structural data. Since PTMs influence the function of the protein and their aberrant states are frequently implicated in human diseases, providing structural insights to understand the influence and dynamics of PTMs is crucial for unraveling the underlying processes. This review is dedicated to the current status of databases providing 3D structural data on PTM sites in proteins. Some of these databases are general, covering multiple types of PTMs in different organisms, while others are specific to one particular type of PTM, class of proteins or organism. The importance of these databases is illustrated with two major types of in silico applications: predicting PTM sites in proteins using machine learning approaches and investigating protein structure-function relationships involving PTMs. Finally, these databases suffer from multiple problems and care must be taken when analyzing the PTMs data.
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Affiliation(s)
- Alexandre G de Brevern
- Université de Paris, INSERM, UMR_S 1134, DSIMB, 75739, Paris, France.,Université de la Réunion, INSERM, UMR_S 1134, DSIMB, 97715, Saint-Denis de La Réunion, France.,Laboratoire d'Excellence GR-Ex, 75739, Paris, France
| | - Joseph Rebehmed
- Department of Computer Science and Mathematics, Lebanese American University, Beirut, Lebanon.
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8
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Cretin G, Galochkina T, de Brevern AG, Gelly JC. PYTHIA: Deep Learning Approach for Local Protein Conformation Prediction. Int J Mol Sci 2021; 22:ijms22168831. [PMID: 34445537 PMCID: PMC8396346 DOI: 10.3390/ijms22168831] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 08/09/2021] [Accepted: 08/10/2021] [Indexed: 02/07/2023] Open
Abstract
Protein Blocks (PBs) are a widely used structural alphabet describing local protein backbone conformation in terms of 16 possible conformational states, adopted by five consecutive amino acids. The representation of complex protein 3D structures as 1D PB sequences was previously successfully applied to protein structure alignment and protein structure prediction. In the current study, we present a new model, PYTHIA (predicting any conformation at high accuracy), for the prediction of the protein local conformations in terms of PBs directly from the amino acid sequence. PYTHIA is based on a deep residual inception-inside-inception neural network with convolutional block attention modules, predicting 1 of 16 PB classes from evolutionary information combined to physicochemical properties of individual amino acids. PYTHIA clearly outperforms the LOCUSTRA reference method for all PB classes and demonstrates great performance for PB prediction on particularly challenging proteins from the CASP14 free modelling category.
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Affiliation(s)
- Gabriel Cretin
- Biologie Intégrée du Globule Rouge, Université de Paris, UMR_S1134, BIGR, INSERM, 75015 Paris, France; (G.C.); (T.G.); (A.G.d.B.)
- Laboratoire d’Excellence GR-Ex, 75015 Paris, France
| | - Tatiana Galochkina
- Biologie Intégrée du Globule Rouge, Université de Paris, UMR_S1134, BIGR, INSERM, 75015 Paris, France; (G.C.); (T.G.); (A.G.d.B.)
- Laboratoire d’Excellence GR-Ex, 75015 Paris, France
| | - Alexandre G. de Brevern
- Biologie Intégrée du Globule Rouge, Université de Paris, UMR_S1134, BIGR, INSERM, 75015 Paris, France; (G.C.); (T.G.); (A.G.d.B.)
- Laboratoire d’Excellence GR-Ex, 75015 Paris, France
| | - Jean-Christophe Gelly
- Biologie Intégrée du Globule Rouge, Université de Paris, UMR_S1134, BIGR, INSERM, 75015 Paris, France; (G.C.); (T.G.); (A.G.d.B.)
- Laboratoire d’Excellence GR-Ex, 75015 Paris, France
- Correspondence:
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9
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Hashemi ZS, Zarei M, Fath MK, Ganji M, Farahani MS, Afsharnouri F, Pourzardosht N, Khalesi B, Jahangiri A, Rahbar MR, Khalili S. In silico Approaches for the Design and Optimization of Interfering Peptides Against Protein-Protein Interactions. Front Mol Biosci 2021; 8:669431. [PMID: 33996914 PMCID: PMC8113820 DOI: 10.3389/fmolb.2021.669431] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 04/06/2021] [Indexed: 01/01/2023] Open
Abstract
Large contact surfaces of protein-protein interactions (PPIs) remain to be an ongoing issue in the discovery and design of small molecule modulators. Peptides are intrinsically capable of exploring larger surfaces, stable, and bioavailable, and therefore bear a high therapeutic value in the treatment of various diseases, including cancer, infectious diseases, and neurodegenerative diseases. Given these promising properties, a long way has been covered in the field of targeting PPIs via peptide design strategies. In silico tools have recently become an inevitable approach for the design and optimization of these interfering peptides. Various algorithms have been developed to scrutinize the PPI interfaces. Moreover, different databases and software tools have been created to predict the peptide structures and their interactions with target protein complexes. High-throughput screening of large peptide libraries against PPIs; "hotspot" identification; structure-based and off-structure approaches of peptide design; 3D peptide modeling; peptide optimization strategies like cyclization; and peptide binding energy evaluation are among the capabilities of in silico tools. In the present study, the most recent advances in the field of in silico approaches for the design of interfering peptides against PPIs will be reviewed. The future perspective of the field and its advantages and limitations will also be pinpointed.
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Affiliation(s)
- Zahra Sadat Hashemi
- ATMP Department, Breast Cancer Research Center, Motamed Cancer Institute, Academic Center for Education, Culture and Research, Tehran, Iran
| | - Mahboubeh Zarei
- Pharmaceutical Sciences Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Mohsen Karami Fath
- Department of Cellular and Molecular Biology, Faculty of Biological Sciences, Kharazmi University, Tehran, Iran
| | - Mahmoud Ganji
- Department of Medical Biotechnology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Mahboube Shahrabi Farahani
- Department of Medical Biotechnology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Fatemeh Afsharnouri
- Department of Medical Biotechnology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Navid Pourzardosht
- Cellular and Molecular Research Center, Faculty of Medicine, Guilan University of Medical Sciences, Rasht, Iran
- Department of Biochemistry, Guilan University of Medical Sciences, Rasht, Iran
| | - Bahman Khalesi
- Department of Research and Production of Poultry Viral Vaccine, Razi Vaccine and Serum Research Institute, Agricultural Research Education and Extension Organization, Karaj, Iran
| | - Abolfazl Jahangiri
- Applied Microbiology Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Mohammad Reza Rahbar
- Pharmaceutical Sciences Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Saeed Khalili
- Department of Biology Sciences, Shahid Rajaee Teacher Training University, Tehran, Iran
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10
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Sun Z, Huang S, Zheng L, Liang P, Yang W, Zuo Y. ICTC-RAAC: An improved web predictor for identifying the types of ion channel-targeted conotoxins by using reduced amino acid cluster descriptors. Comput Biol Chem 2020; 89:107371. [PMID: 32950852 DOI: 10.1016/j.compbiolchem.2020.107371] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 09/01/2020] [Accepted: 09/02/2020] [Indexed: 12/27/2022]
Abstract
Conotoxins are small peptide toxins which are rich in disulfide and have the unique diversity of sequences. It is significant to correctly identify the types of ion channel-targeted conotoxins because that they are considered as the optimal pharmacological candidate medicine in drug design owing to their ability specifically binding to ion channels and interfering with neural transmission. Comparing with other feature extracting methods, the reduced amino acid cluster (RAAC) better resolved in simplifying protein complexity and identifying functional conserved regions. Thus, in our study, 673 RAACs generated from 74 types of reduced amino acid alphabet were comprehensively assessed to establish a state-of-the-art predictor for predicting ion channel-targeted conotoxins. The results showed Type 20, Cluster 9 (T = 20, C = 9) in the tripeptide composition (N = 3) achieved the best accuracy, 89.3%, which was based on the algorithm of amino acids reduction of variance maximization. Further, the ANOVA with incremental feature selection (IFS) was used for feature selection to improve prediction performance. Finally, the cross-validation results showed that the best overall accuracy we calculated was 96.4% and 1.8% higher than the best accuracy of previous studies. Based on the predictor we proposed, a user-friendly webserver was established and can be friendly accessed at http://bioinfor.imu.edu.cn/ictcraac.
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Affiliation(s)
- Zijie Sun
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, College of Life Sciences, Inner Mongolia University, Hohhot, 010070, China; School of Mathematical Sciences, Inner Mongolia University, Hohhot, 010021, China
| | - Shenghui Huang
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, College of Life Sciences, Inner Mongolia University, Hohhot, 010070, China
| | - Lei Zheng
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, College of Life Sciences, Inner Mongolia University, Hohhot, 010070, China
| | - Pengfei Liang
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, College of Life Sciences, Inner Mongolia University, Hohhot, 010070, China
| | - Wuritu Yang
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, College of Life Sciences, Inner Mongolia University, Hohhot, 010070, China.
| | - Yongchun Zuo
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, College of Life Sciences, Inner Mongolia University, Hohhot, 010070, China.
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11
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Badaczewska-Dawid AE, Kolinski A, Kmiecik S. Computational reconstruction of atomistic protein structures from coarse-grained models. Comput Struct Biotechnol J 2019; 18:162-176. [PMID: 31969975 PMCID: PMC6961067 DOI: 10.1016/j.csbj.2019.12.007] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Accepted: 12/10/2019] [Indexed: 01/02/2023] Open
Abstract
Three-dimensional protein structures, whether determined experimentally or theoretically, are often too low resolution. In this mini-review, we outline the computational methods for protein structure reconstruction from incomplete coarse-grained to all atomistic models. Typical reconstruction schemes can be divided into four major steps. Usually, the first step is reconstruction of the protein backbone chain starting from the C-alpha trace. This is followed by side-chains rebuilding based on protein backbone geometry. Subsequently, hydrogen atoms can be reconstructed. Finally, the resulting all-atom models may require structure optimization. Many methods are available to perform each of these tasks. We discuss the available tools and their potential applications in integrative modeling pipelines that can transfer coarse-grained information from computational predictions, or experiment, to all atomistic structures.
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Affiliation(s)
| | | | - Sebastian Kmiecik
- Faculty of Chemistry, Biological and Chemical Research Center, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
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12
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Narwani TJ, Craveur P, Shinada NK, Floch A, Santuz H, Vattekatte AM, Srinivasan N, Rebehmed J, Gelly JC, Etchebest C, de Brevern AG. Discrete analyses of protein dynamics. J Biomol Struct Dyn 2019; 38:2988-3002. [PMID: 31361191 DOI: 10.1080/07391102.2019.1650112] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Protein structures are highly dynamic macromolecules. This dynamics is often analysed through experimental and/or computational methods only for an isolated or a limited number of proteins. Here, we explore large-scale protein dynamics simulation to observe dynamics of local protein conformations using different perspectives. We analysed molecular dynamics to investigate protein flexibility locally, using classical approaches such as RMSf, solvent accessibility, but also innovative approaches such as local entropy. First, we focussed on classical secondary structures and analysed specifically how β-strand, β-turns, and bends evolve during molecular simulations. We underlined interesting specific bias between β-turns and bends, which are considered as the same category, while their dynamics show differences. Second, we used a structural alphabet that is able to approximate every part of the protein structures conformations, namely protein blocks (PBs) to analyse (i) how each initial local protein conformations evolve during dynamics and (ii) if some exchange can exist among these PBs. Interestingly, the results are largely complex than simple regular/rigid and coil/flexible exchange. AbbreviationsNeqnumber of equivalentPBProtein BlocksPDBProtein DataBankRMSfroot mean square fluctuationsCommunicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Tarun Jairaj Narwani
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire D'Excellence GR-Ex, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France
| | - Pierrick Craveur
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire D'Excellence GR-Ex, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA
| | - Nicolas K Shinada
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire D'Excellence GR-Ex, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Discngine, SAS, Paris, France
| | - Aline Floch
- Laboratoire D'Excellence GR-Ex, Paris, France.,Etablissement Français du Sang Ile de France, Créteil, France.,IMRB - INSERM U955 Team 2 « Transfusion et Maladies du Globule Rouge », Paris Est- Créteil Univ, Créteil, France.,UPEC, Université Paris Est-Créteil, Créteil, France
| | - Hubert Santuz
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire D'Excellence GR-Ex, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France
| | - Akhila Melarkode Vattekatte
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire D'Excellence GR-Ex, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Faculté Des Sciences et Technologies, Saint Denis Messag, La Réunion, France
| | | | - Joseph Rebehmed
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire D'Excellence GR-Ex, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Department of Computer Science and Mathematics, Lebanese American University, Byblos, Lebanon
| | - Jean-Christophe Gelly
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire D'Excellence GR-Ex, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Faculté Des Sciences et Technologies, Saint Denis Messag, La Réunion, France.,IBL, Paris, France
| | - Catherine Etchebest
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire D'Excellence GR-Ex, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Faculté Des Sciences et Technologies, Saint Denis Messag, La Réunion, France
| | - Alexandre G de Brevern
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire D'Excellence GR-Ex, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Faculté Des Sciences et Technologies, Saint Denis Messag, La Réunion, France.,IBL, Paris, France
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13
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Craveur P, Narwani TJ, Rebehmed J, de Brevern AG. Investigation of the impact of PTMs on the protein backbone conformation. Amino Acids 2019; 51:1065-1079. [DOI: 10.1007/s00726-019-02747-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2018] [Accepted: 05/18/2019] [Indexed: 12/17/2022]
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14
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A minimum set of stable blocks for rational design of polypeptide chains. Biochimie 2019; 160:88-92. [DOI: 10.1016/j.biochi.2019.02.006] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2018] [Accepted: 02/13/2019] [Indexed: 12/30/2022]
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15
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Vetrivel I, Mahajan S, Tyagi M, Hoffmann L, Sanejouand YH, Srinivasan N, de Brevern AG, Cadet F, Offmann B. Knowledge-based prediction of protein backbone conformation using a structural alphabet. PLoS One 2017; 12:e0186215. [PMID: 29161266 PMCID: PMC5697859 DOI: 10.1371/journal.pone.0186215] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2017] [Accepted: 09/27/2017] [Indexed: 01/19/2023] Open
Abstract
Libraries of structural prototypes that abstract protein local structures are known as structural alphabets and have proven to be very useful in various aspects of protein structure analyses and predictions. One such library, Protein Blocks, is composed of 16 standard 5-residues long structural prototypes. This form of analyzing proteins involves drafting its structure as a string of Protein Blocks. Predicting the local structure of a protein in terms of protein blocks is the general objective of this work. A new approach, PB-kPRED is proposed towards this aim. It involves (i) organizing the structural knowledge in the form of a database of pentapeptide fragments extracted from all protein structures in the PDB and (ii) applying a knowledge-based algorithm that does not rely on any secondary structure predictions and/or sequence alignment profiles, to scan this database and predict most probable backbone conformations for the protein local structures. Though PB-kPRED uses the structural information from homologues in preference, if available. The predictions were evaluated rigorously on 15,544 query proteins representing a non-redundant subset of the PDB filtered at 30% sequence identity cut-off. We have shown that the kPRED method was able to achieve mean accuracies ranging from 40.8% to 66.3% depending on the availability of homologues. The impact of the different strategies for scanning the database on the prediction was evaluated and is discussed. Our results highlight the usefulness of the method in the context of proteins without any known structural homologues. A scoring function that gives a good estimate of the accuracy of prediction was further developed. This score estimates very well the accuracy of the algorithm (R2 of 0.82). An online version of the tool is provided freely for non-commercial usage at http://www.bo-protscience.fr/kpred/.
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Affiliation(s)
- Iyanar Vetrivel
- Université de Nantes, Unité Fonctionnalité et Ingénierie des Protéines (UFIP), UMR 6286 CNRS, UFR Sciences et Techniques, 2, chemin de la Houssinière, France
| | - Swapnil Mahajan
- Université de Nantes, Unité Fonctionnalité et Ingénierie des Protéines (UFIP), UMR 6286 CNRS, UFR Sciences et Techniques, 2, chemin de la Houssinière, France
- DSIMB, INSERM, UMR S-1134, Laboratory of Excellence, GR-Ex, Université de La Réunion, Faculty of Sciences and Technology, Saint Denis Cedex, La Réunion, France
| | - Manoj Tyagi
- Université de La Réunion, Saint Denis Cedex, La Réunion, France
| | - Lionel Hoffmann
- Université de Nantes, Unité Fonctionnalité et Ingénierie des Protéines (UFIP), UMR 6286 CNRS, UFR Sciences et Techniques, 2, chemin de la Houssinière, France
| | - Yves-Henri Sanejouand
- Université de Nantes, Unité Fonctionnalité et Ingénierie des Protéines (UFIP), UMR 6286 CNRS, UFR Sciences et Techniques, 2, chemin de la Houssinière, France
| | | | - Alexandre G. de Brevern
- INSERM UMR_S 1134, DSIMB team, Laboratory of Excellence, GR-Ex, Univ Paris Diderot, Univ Sorbonne Paris Cité, INTS, rue Alexandre Cabanel, Paris, France
| | - Frédéric Cadet
- DSIMB, INSERM, UMR S-1134, Laboratory of Excellence, GR-Ex, Université de La Réunion, Faculty of Sciences and Technology, Saint Denis Cedex, La Réunion, France
- PEACCEL SAS, Paris, France
| | - Bernard Offmann
- Université de Nantes, Unité Fonctionnalité et Ingénierie des Protéines (UFIP), UMR 6286 CNRS, UFR Sciences et Techniques, 2, chemin de la Houssinière, France
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16
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Barnoud J, Santuz H, Craveur P, Joseph AP, Jallu V, de Brevern AG, Poulain P. PBxplore: a tool to analyze local protein structure and deformability with Protein Blocks. PeerJ 2017; 5:e4013. [PMID: 29177113 PMCID: PMC5700758 DOI: 10.7717/peerj.4013] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2017] [Accepted: 10/19/2017] [Indexed: 11/20/2022] Open
Abstract
This paper describes the development and application of a suite of tools, called PBxplore, to analyze the dynamics and deformability of protein structures using Protein Blocks (PBs). Proteins are highly dynamic macromolecules, and a classical way to analyze their inherent flexibility is to perform molecular dynamics simulations. The advantage of using small structural prototypes such as PBs is to give a good approximation of the local structure of the protein backbone. More importantly, by reducing the conformational complexity of protein structures, PBs allow analysis of local protein deformability which cannot be done with other methods and had been used efficiently in different applications. PBxplore is able to process large amounts of data such as those produced by molecular dynamics simulations. It produces frequencies, entropy and information logo outputs as text and graphics. PBxplore is available at https://github.com/pierrepo/PBxplore and is released under the open-source MIT license.
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Affiliation(s)
- Jonathan Barnoud
- INSERM, U 1134, DSIMB, Paris, France.,Univ. Paris Diderot, Sorbonne Paris Cité, Univ de la Réunion, Univ des Antilles, UMR-S 1134, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Laboratoire d'Excellence GR-Ex, Paris, France.,Current affiliation: Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials, University of Groningen, Groningen, The Netherlands
| | - Hubert Santuz
- INSERM, U 1134, DSIMB, Paris, France.,Univ. Paris Diderot, Sorbonne Paris Cité, Univ de la Réunion, Univ des Antilles, UMR-S 1134, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Laboratoire d'Excellence GR-Ex, Paris, France.,Current affiliation: Laboratoire de Biochimie Théorique, CNRS UPR 9080, Institut de Biologie Physico-Chimique, Paris, France
| | - Pierrick Craveur
- INSERM, U 1134, DSIMB, Paris, France.,Univ. Paris Diderot, Sorbonne Paris Cité, Univ de la Réunion, Univ des Antilles, UMR-S 1134, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Laboratoire d'Excellence GR-Ex, Paris, France.,Current affiliation: Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, United States of America
| | - Agnel Praveen Joseph
- INSERM, U 1134, DSIMB, Paris, France.,Univ. Paris Diderot, Sorbonne Paris Cité, Univ de la Réunion, Univ des Antilles, UMR-S 1134, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Laboratoire d'Excellence GR-Ex, Paris, France.,Current affiliation: Birkbeck College, University of London, London, UK
| | | | - Alexandre G de Brevern
- INSERM, U 1134, DSIMB, Paris, France.,Univ. Paris Diderot, Sorbonne Paris Cité, Univ de la Réunion, Univ des Antilles, UMR-S 1134, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Laboratoire d'Excellence GR-Ex, Paris, France
| | - Pierre Poulain
- INSERM, U 1134, DSIMB, Paris, France.,Univ. Paris Diderot, Sorbonne Paris Cité, Univ de la Réunion, Univ des Antilles, UMR-S 1134, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Laboratoire d'Excellence GR-Ex, Paris, France.,Current affiliation: Mitochondria, Metals and Oxidative Stress Group, Institut Jacques Monod, UMR 7592, Univ. Paris Diderot, CNRS, Sorbonne Paris Cité, Paris, France
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17
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Noël F, Malpertuy A, de Brevern AG. Global analysis of VHHs framework regions with a structural alphabet. Biochimie 2016; 131:11-19. [PMID: 27613403 DOI: 10.1016/j.biochi.2016.09.005] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2016] [Revised: 09/05/2016] [Accepted: 09/05/2016] [Indexed: 02/08/2023]
Abstract
The VHHs are antigen-binding region/domain of camelid heavy chain antibodies (HCAb). They have many interesting biotechnological and biomedical properties due to their small size, high solubility and stability, and high affinity and specificity for their antigens. HCAb and classical IgGs are evolutionary related and share a common fold. VHHs are composed of regions considered as constant, called the frameworks (FRs) connected by Complementarity Determining Regions (CDRs), a highly variable region that provide interaction with the epitope. Actually, no systematic structural analyses had been performed on VHH structures despite a significant number of structures. This work is the first study to analyse the structural diversity of FRs of VHHs. Using a structural alphabet that allows approximating the local conformation, we show that each of the four FRs do not have a unique structure but exhibit many structural variant patterns. Moreover, no direct simple link between the local conformational change and amino acid composition can be detected. These results indicate that long-range interactions affect the local conformation of FRs and impact the building of structural models.
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Affiliation(s)
- Floriane Noël
- INSERM, U 1134, DSIMB, F-75739 Paris, France; Univ Paris Diderot, Sorbonne Paris Cité, UMR_S 1134, F-75739 Paris, France; Institut National de la Transfusion Sanguine (INTS), F-75739 Paris, France; Laboratoire d'Excellence GR-Ex, F-75739 Paris, France
| | | | - Alexandre G de Brevern
- INSERM, U 1134, DSIMB, F-75739 Paris, France; Univ Paris Diderot, Sorbonne Paris Cité, UMR_S 1134, F-75739 Paris, France; Institut National de la Transfusion Sanguine (INTS), F-75739 Paris, France; Laboratoire d'Excellence GR-Ex, F-75739 Paris, France.
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18
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McHugh SM, Rogers JR, Solomon SA, Yu H, Lin YS. Computational methods to design cyclic peptides. Curr Opin Chem Biol 2016; 34:95-102. [PMID: 27592259 DOI: 10.1016/j.cbpa.2016.08.004] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2016] [Revised: 08/08/2016] [Accepted: 08/10/2016] [Indexed: 10/21/2022]
Abstract
Cyclic peptides (CPs) are promising modulators of protein-protein interactions (PPIs), but their application remains challenging. It is currently difficult to predict the structures and bioavailability of CPs. The ability to design CPs using computer modeling would greatly facilitate the development of CPs as potent PPI modulators for fundamental studies and as potential therapeutics. Herein, we describe computational methods to generate CP libraries for virtual screening, as well as current efforts to accurately predict the conformations adopted by CPs. These advances are making it possible to envision robust computational design of active CPs. However, unique properties of CPs pose significant challenges associated with sampling CP conformational space and accurately describing CP energetics. These major obstacles to structure prediction likely must be solved before robust design of active CPs can be reliably achieved.
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Affiliation(s)
- Sean M McHugh
- Department of Chemistry, Tufts University, Medford, MA 02155, United States
| | - Julia R Rogers
- Department of Chemistry, Tufts University, Medford, MA 02155, United States
| | - Sarah A Solomon
- Department of Chemistry, Tufts University, Medford, MA 02155, United States
| | - Hongtao Yu
- Department of Chemistry, Tufts University, Medford, MA 02155, United States
| | - Yu-Shan Lin
- Department of Chemistry, Tufts University, Medford, MA 02155, United States.
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19
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Characterization and Prediction of Protein Flexibility Based on Structural Alphabets. BIOMED RESEARCH INTERNATIONAL 2016; 2016:4628025. [PMID: 27660756 PMCID: PMC5021887 DOI: 10.1155/2016/4628025] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/13/2016] [Accepted: 08/02/2016] [Indexed: 11/25/2022]
Abstract
Motivation. To assist efforts in determining and exploring the functional properties of proteins, it is desirable to characterize and predict protein flexibilities. Results. In this study, the conformational entropy is used as an indicator of the protein flexibility. We first explore whether the conformational change can capture the protein flexibility. The well-defined decoy structures are converted into one-dimensional series of letters from a structural alphabet. Four different structure alphabets, including the secondary structure in 3-class and 8-class, the PB structure alphabet (16-letter), and the DW structure alphabet (28-letter), are investigated. The conformational entropy is then calculated from the structure alphabet letters. Some of the proteins show high correlation between the conformation entropy and the protein flexibility. We then predict the protein flexibility from basic amino acid sequence. The local structures are predicted by the dual-layer model and the conformational entropy of the predicted class distribution is then calculated. The results show that the conformational entropy is a good indicator of the protein flexibility, but false positives remain a problem. The DW structure alphabet performs the best, which means that more subtle local structures can be captured by large number of structure alphabet letters. Overall this study provides a simple and efficient method for the characterization and prediction of the protein flexibility.
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20
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Galiez C, Coste F. Amplitude spectrum distance: measuring the global shape divergence of protein fragments. BMC Bioinformatics 2015; 16:256. [PMID: 26268224 PMCID: PMC4535829 DOI: 10.1186/s12859-015-0693-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2015] [Accepted: 07/31/2015] [Indexed: 12/02/2022] Open
Abstract
Background In structural bioinformatics, there is an increasing interest in identifying and understanding the evolution of local protein structures regarded as key structural or functional protein building blocks. A central need is then to compare these, possibly short, fragments by measuring efficiently and accurately their (dis)similarity. Progress towards this goal has given rise to scores enabling to assess the strong similarity of fragments. Yet, there is still a lack of more progressive scores, with meaningful intermediate values, for the comparison, retrieval or clustering of distantly related fragments. Results We introduce here the Amplitude Spectrum Distance (ASD), a novel way of comparing protein fragments based on the discrete Fourier transform of their Cα distance matrix. Defined as the distance between their amplitude spectra, ASD can be computed efficiently and provides a parameter-free measure of the global shape dissimilarity of two fragments. ASD inherits from nice theoretical properties, making it tolerant to shifts, insertions, deletions, circular permutations or sequence reversals while satisfying the triangle inequality. The practical interest of ASD with respect to RMSD, RMSDd, BC and TM scores is illustrated through zinc finger retrieval experiments and concrete structure examples. The benefits of ASD are also illustrated by two additional clustering experiments: domain linkers fragments and complementarity-determining regions of antibodies. Conclusions Taking advantage of the Fourier transform to compare fragments at a global shape level, ASD is an objective and progressive measure taking into account the whole fragments. Its practical computation time and its properties make ASD particularly relevant for applications requiring meaningful measures on distantly related protein fragments, such as similar fragments retrieval asking for high recalls as shown in the experiments, or for any application taking also advantage of triangle inequality, such as fragments clustering. ASD program and source code are freely available at: http://www.irisa.fr/dyliss/public/ASD/. Electronic supplementary material The online version of this article (doi:10.1186/s12859-015-0693-y) contains supplementary material, which is available to authorized users.
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21
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Craveur P, Joseph AP, Esque J, Narwani TJ, Noël F, Shinada N, Goguet M, Leonard S, Poulain P, Bertrand O, Faure G, Rebehmed J, Ghozlane A, Swapna LS, Bhaskara RM, Barnoud J, Téletchéa S, Jallu V, Cerny J, Schneider B, Etchebest C, Srinivasan N, Gelly JC, de Brevern AG. Protein flexibility in the light of structural alphabets. Front Mol Biosci 2015; 2:20. [PMID: 26075209 PMCID: PMC4445325 DOI: 10.3389/fmolb.2015.00020] [Citation(s) in RCA: 59] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2015] [Accepted: 04/30/2015] [Indexed: 01/01/2023] Open
Abstract
Protein structures are valuable tools to understand protein function. Nonetheless, proteins are often considered as rigid macromolecules while their structures exhibit specific flexibility, which is essential to complete their functions. Analyses of protein structures and dynamics are often performed with a simplified three-state description, i.e., the classical secondary structures. More precise and complete description of protein backbone conformation can be obtained using libraries of small protein fragments that are able to approximate every part of protein structures. These libraries, called structural alphabets (SAs), have been widely used in structure analysis field, from definition of ligand binding sites to superimposition of protein structures. SAs are also well suited to analyze the dynamics of protein structures. Here, we review innovative approaches that investigate protein flexibility based on SAs description. Coupled to various sources of experimental data (e.g., B-factor) and computational methodology (e.g., Molecular Dynamic simulation), SAs turn out to be powerful tools to analyze protein dynamics, e.g., to examine allosteric mechanisms in large set of structures in complexes, to identify order/disorder transition. SAs were also shown to be quite efficient to predict protein flexibility from amino-acid sequence. Finally, in this review, we exemplify the interest of SAs for studying flexibility with different cases of proteins implicated in pathologies and diseases.
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Affiliation(s)
- Pierrick Craveur
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France
| | - Agnel P Joseph
- Rutherford Appleton Laboratory, Science and Technology Facilities Council Didcot, UK
| | - Jeremy Esque
- Institut National de la Santé et de la Recherche Médicale U964,7 UMR Centre National de la Recherche Scientifique 7104, IGBMC, Université de Strasbourg Illkirch, France
| | - Tarun J Narwani
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France
| | - Floriane Noël
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France
| | - Nicolas Shinada
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France
| | - Matthieu Goguet
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France
| | - Sylvain Leonard
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France
| | - Pierre Poulain
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France ; Ets Poulain Pointe-Noire, Congo
| | - Olivier Bertrand
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France
| | - Guilhem Faure
- National Library of Medicine, National Center for Biotechnology Information, National Institutes of Health Bethesda, MD, USA
| | - Joseph Rebehmed
- Centre National de la Recherche Scientifique UMR7590, Sorbonne Universités, Université Pierre et Marie Curie - MNHN - IRD - IUC Paris, France
| | | | - Lakshmipuram S Swapna
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore Bangalore, India ; Hospital for Sick Children, and Departments of Biochemistry and Molecular Genetics, University of Toronto Toronto, ON, Canada
| | - Ramachandra M Bhaskara
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore Bangalore, India ; Department of Theoretical Biophysics, Max Planck Institute of Biophysics Frankfurt, Germany
| | - Jonathan Barnoud
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France ; Laboratoire de Physique, École Normale Supérieure de Lyon, Université de Lyon, Centre National de la Recherche Scientifique UMR 5672 Lyon, France
| | - Stéphane Téletchéa
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France ; Faculté des Sciences et Techniques, Université de Nantes, Unité Fonctionnalité et Ingénierie des Protéines, Centre National de la Recherche Scientifique UMR 6286, Université Nantes Nantes, France
| | - Vincent Jallu
- Platelet Unit, Institut National de la Transfusion Sanguine Paris, France
| | - Jiri Cerny
- Institute of Biotechnology, The Czech Academy of Sciences Prague, Czech Republic
| | - Bohdan Schneider
- Institute of Biotechnology, The Czech Academy of Sciences Prague, Czech Republic
| | - Catherine Etchebest
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France
| | | | - Jean-Christophe Gelly
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France
| | - Alexandre G de Brevern
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France
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22
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Thévenet P, Rey J, Moroy G, Tuffery P. De novo peptide structure prediction: an overview. Methods Mol Biol 2015; 1268:1-13. [PMID: 25555718 DOI: 10.1007/978-1-4939-2285-7_1] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Peptide structure identification is an important contribution to the further characterization of the residues involved in functional interactions. De novo structure peptide prediction has, in the past few years, made significant progresses that make reasonable, for peptides up to 50 amino acids, its use for the fast identification of their structural topologies. Here, we introduce some of the concepts underlying approaches of the field, together with their limits.
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Affiliation(s)
- Pierre Thévenet
- Molécules Thérapeutiques In Silico, Inserm UMR-S 973, Université Paris Diderot, Sorbonne Paris Cité, 35 rue Helene Brion, 75013, Paris, France
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23
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Topham CM, Smith JC. Tri-peptide reference structures for the calculation of relative solvent accessible surface area in protein amino acid residues. Comput Biol Chem 2014; 54:33-43. [PMID: 25544680 DOI: 10.1016/j.compbiolchem.2014.11.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2014] [Revised: 11/23/2014] [Accepted: 11/30/2014] [Indexed: 10/24/2022]
Abstract
Relative amino acid residue solvent accessibility values allow the quantitative comparison of atomic solvent-accessible surface areas in different residue types and physical environments in proteins and in protein structural alignments. Geometry-optimised tri-peptide structures in extended solvent-exposed reference conformations have been obtained for 43 amino acid residue types at a high level of quantum chemical theory. Significant increases in side-chain solvent accessibility, offset by reductions in main-chain atom solvent exposure, were observed for standard residue types in partially geometry-optimised structures when compared to non-minimised models built from identical sets of proper dihedral angles abstracted from the literature. Optimisation of proper dihedral angles led most notably to marked increases of up to 54% in proline main-chain atom solvent accessibility compared to literature values. Similar effects were observed for fully-optimised tri-peptides in implicit solvent. The relief of internal strain energy was associated with systematic variation in N, C(α) and C(β) atom solvent accessibility across all standard residue types. The results underline the importance of optimisation of 'hard' degrees of freedom (bond lengths and valence bond angles) and improper dihedral angle values from force field or other context-independent reference values, and impact on the use of standardised fixed internal co-ordinate geometry in sampling approaches to the determination of absolute values of protein amino acid residue solvent accessibility. Quantum chemical methods provide a useful and accurate alternative to molecular mechanics methods to perform energy minimisation of peptides containing non-standard (chemically modified) amino acid residues frequently present in experimental protein structure data sets, for which force field parameters may not be available. Reference tri-peptide atomic co-ordinate sets including hydrogen atoms are made freely available.
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Affiliation(s)
- Christopher M Topham
- Molecular Forces Consulting, 40 Rue Boyssonne, Toulouse 31400, France; Computational Molecular Biophysics, IWR der Universität Heidelberg, Im Neuenheimer Feld 368, Heidelberg D-69120, Germany; University of Tennessee/Oak Ridge National Laboratory, Center for Molecular Biophysics, P.O. Box 2008, Oak Ridge, TN 37831-6309, USA; Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, M407 Walters Life Sciences, 1414 Cumberland Avenue, Knoxville, TN 37996, USA.
| | - Jeremy C Smith
- Computational Molecular Biophysics, IWR der Universität Heidelberg, Im Neuenheimer Feld 368, Heidelberg D-69120, Germany; University of Tennessee/Oak Ridge National Laboratory, Center for Molecular Biophysics, P.O. Box 2008, Oak Ridge, TN 37831-6309, USA; Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, M407 Walters Life Sciences, 1414 Cumberland Avenue, Knoxville, TN 37996, USA
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Modeling and molecular dynamics simulations of the V33 variant of the integrin subunit β3: Structural comparison with the L33 (HPA-1a) and P33 (HPA-1b) variants. Biochimie 2014; 105:84-90. [DOI: 10.1016/j.biochi.2014.06.017] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2014] [Accepted: 06/21/2014] [Indexed: 11/21/2022]
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25
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Joseph AP, de Brevern AG. From local structure to a global framework: recognition of protein folds. J R Soc Interface 2014; 11:20131147. [PMID: 24740960 DOI: 10.1098/rsif.2013.1147] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Protein folding has been a major area of research for many years. Nonetheless, the mechanisms leading to the formation of an active biological fold are still not fully apprehended. The huge amount of available sequence and structural information provides hints to identify the putative fold for a given sequence. Indeed, protein structures prefer a limited number of local backbone conformations, some being characterized by preferences for certain amino acids. These preferences largely depend on the local structural environment. The prediction of local backbone conformations has become an important factor to correctly identifying the global protein fold. Here, we review the developments in the field of local structure prediction and especially their implication in protein fold recognition.
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Affiliation(s)
- Agnel Praveen Joseph
- Science and Technology Facilities Council, Rutherford Appleton Laboratory, Harwell Oxford, , Didcot OX11 0QX, UK
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26
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Verma S, Kumar S, Gupta VP, Gourinath S, Bhatnagar S, Bhatnagar R. Structural basis of Bacillus anthracis MoxXT disruption and the modulation of MoxT ribonuclease activity by rationally designed peptides. J Biomol Struct Dyn 2014; 33:606-24. [PMID: 24650157 DOI: 10.1080/07391102.2014.899924] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
Bacillus anthracis MoxXT is a Type II proteic Toxin-Antitoxin (TA) module wherein MoxT is a ribonuclease that cleaves RNA specifically while MoxX interacts with MoxT and inhibits its activity. Disruption of the TA interaction has been proposed as a novel antibacterial strategy. Peptides, either based on antitoxin sequence or rationally designed, have previously been reported to disrupt the MoxXT interaction but cause a decrease in MoxT ribonuclease activity. In the present study, we report the crystal structure of MoxT, and the effect of several peptides in disrupting the MoxXT interaction as well as augmentation of MoxT ribonuclease activity by binding to MoxT in vitro. Docking studies on the peptides were carried out in order to explain the observed structure activity relationships. The peptides with ribonuclease augmentation activity possess a distinct structure and are proposed to bind to a distinct site on MoxT. The docking of the active peptides with MoxT showed that they possess an aromatic group that occupies a conserved hydrophobic pocket. Additionally, the peptides inducing high ribonuclease activity were anchored by a negatively charged group near a cluster of positively charged residues present near the pocket. Our study provides a structural basis and rationale for the observed properties of the peptides and may aid the development of small molecules to disrupt the TA interaction.
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Affiliation(s)
- Shashikala Verma
- a Laboratory of Genetic Engineering and Molecular Biology, School of Biotechnology , Jawaharlal Nehru University , Room No. 102, New Delhi 110067 , India
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27
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Shen Y, Picord G, Guyon F, Tuffery P. Detecting protein candidate fragments using a structural alphabet profile comparison approach. PLoS One 2013; 8:e80493. [PMID: 24303019 PMCID: PMC3841190 DOI: 10.1371/journal.pone.0080493] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2013] [Accepted: 10/03/2013] [Indexed: 01/28/2023] Open
Abstract
Predicting accurate fragments from sequence has recently become a critical step for protein structure modeling, as protein fragment assembly techniques are presently among the most efficient approaches for de novo prediction. A key step in these approaches is, given the sequence of a protein to model, the identification of relevant fragments - candidate fragments - from a collection of the available 3D structures. These fragments can then be assembled to produce a model of the complete structure of the protein of interest. The search for candidate fragments is classically achieved by considering local sequence similarity using profile comparison, or threading approaches. In the present study, we introduce a new profile comparison approach that, instead of using amino acid profiles, is based on the use of predicted structural alphabet profiles, where structural alphabet profiles contain information related to the 3D local shapes associated with the sequences. We show that structural alphabet profile-profile comparison can be used efficiently to retrieve accurate structural fragments, and we introduce a fully new protocol for the detection of candidate fragments. It identifies fragments specific of each position of the sequence and of size varying between 6 and 27 amino-acids. We find it outperforms present state of the art approaches in terms (i) of the accuracy of the fragments identified, (ii) the rate of true positives identified, while having a high coverage score. We illustrate the relevance of the approach on complete target sets of the two previous Critical Assessment of Techniques for Protein Structure Prediction (CASP) rounds 9 and 10. A web server for the approach is freely available at http://bioserv.rpbs.univ-paris-diderot.fr/SAFrag.
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Affiliation(s)
- Yimin Shen
- INSERM, U973, MTi, Paris, France
- Univ Paris Diderot, Sorbonne Paris Cité, Paris, France
| | - Géraldine Picord
- INSERM, U973, MTi, Paris, France
- Univ Paris Diderot, Sorbonne Paris Cité, Paris, France
| | - Frédéric Guyon
- INSERM, U973, MTi, Paris, France
- Univ Paris Diderot, Sorbonne Paris Cité, Paris, France
| | - Pierre Tuffery
- INSERM, U973, MTi, Paris, France
- Univ Paris Diderot, Sorbonne Paris Cité, Paris, France
- RPBS, Paris, France
- * E-mail:
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28
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Mahajan S, de Brevern AG, Offmann B, Srinivasan N. Correlation between local structural dynamics of proteins inferred from NMR ensembles and evolutionary dynamics of homologues of known structure. J Biomol Struct Dyn 2013; 32:751-8. [PMID: 23730714 DOI: 10.1080/07391102.2013.789989] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
Conformational changes in proteins are extremely important for their biochemical functions. Correlation between inherent conformational variations in a protein and conformational differences in its homologues of known structure is still unclear. In this study, we have used a structural alphabet called Protein Blocks (PBs). PBs are used to perform abstraction of protein 3-D structures into a 1-D strings of 16 alphabets (a-p) based on dihedral angles of overlapping pentapeptides. We have analyzed the variations in local conformations in terms of PBs represented in the ensembles of 801 protein structures determined using NMR spectroscopy. In the analysis of concatenated data over all the residues in all the NMR ensembles, we observe that the overall nature of inherent local structural variations in NMR ensembles is similar to the nature of local structural differences in homologous proteins with a high correlation coefficient of .94. High correlation at the alignment positions corresponding to helical and β-sheet regions is only expected. However, the correlation coefficient by considering only the loop regions is also quite high (.91). Surprisingly, segregated position-wise analysis shows that this high correlation does not hold true to loop regions at the structurally equivalent positions in NMR ensembles and their homologues of known structure. This suggests that the general nature of local structural changes is unique; however most of the local structural variations in loop regions of NMR ensembles do not correlate to their local structural differences at structurally equivalent positions in homologues.
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Affiliation(s)
- Swapnil Mahajan
- a Faculté des Sciences et Technologies, Université de La Réunion , F-97715 Saint Denis Messag Cedex 09, La Réunion , France
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29
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Craveur P, Joseph AP, Poulain P, de Brevern AG, Rebehmed J. Cis-trans isomerization of omega dihedrals in proteins. Amino Acids 2013; 45:279-89. [PMID: 23728840 DOI: 10.1007/s00726-013-1511-3] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2013] [Accepted: 05/09/2013] [Indexed: 01/24/2023]
Abstract
Peptide bonds in protein structures are mainly found in trans conformation with a torsion angle ω close to 180°. Only a very low proportion is observed in cis conformation with ω angle around 0°. Cis-trans isomerization leads to local conformation changes which play an important role in many biological processes. In this paper, we reviewed the recent discoveries and research achievements in this field. First, we presented some interesting cases of biological processes in which cis-trans isomerization is directly implicated. It is involved in protein folding and various aspect of protein function like dimerization interfaces, autoinhibition control, channel gating, membrane binding. Then we reviewed conservation studies of cis peptide bonds which emphasized evolution constraints in term of sequence and local conformation. Finally we made an overview of the numerous molecular dynamics studies and prediction methodologies already developed to take into account this structural feature in the research area of protein modeling. Many cis peptide bonds have not been recognized as such due to the limited resolution of the data and to the refinement protocol used. Cis-trans proline isomerization reactions represents a vast and promising research area that still needs to be further explored for a better understanding of isomerization mechanism and improvement of cis peptide bond predictions.
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Affiliation(s)
- Pierrick Craveur
- INSERM UMR-S 665, Dynamique des Structures et Interactions des Macromolécules Biologiques, Université Denis Diderot-Paris 7, INTS, 6, rue Alexandre Cabanel, 75739 Paris cedex 15, France
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30
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Moore BL, Kelley LA, Barber J, Murray JW, MacDonald JT. High-quality protein backbone reconstruction from alpha carbons using Gaussian mixture models. J Comput Chem 2013; 34:1881-9. [PMID: 23703289 DOI: 10.1002/jcc.23330] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2013] [Revised: 04/01/2013] [Accepted: 04/21/2013] [Indexed: 11/08/2022]
Abstract
Coarse-grained protein structure models offer increased efficiency in structural modeling, but these must be coupled with fast and accurate methods to revert to a full-atom structure. Here, we present a novel algorithm to reconstruct mainchain models from C traces. This has been parameterized by fitting Gaussian mixture models (GMMs) to short backbone fragments centered on idealized peptide bonds. The method we have developed is statistically significantly more accurate than several competing methods, both in terms of RMSD values and dihedral angle differences. The method produced Ramachandran dihedral angle distributions that are closer to that observed in real proteins and better Phaser molecular replacement log-likelihood gains. Amino acid residue sidechain reconstruction accuracy using SCWRL4 was found to be statistically significantly correlated to backbone reconstruction accuracy. Finally, the PD2 method was found to produce significantly lower energy full-atom models using Rosetta which has implications for multiscale protein modeling using coarse-grained models. A webserver and C++ source code is freely available for noncommercial use from: http://www.sbg.bio.ic.ac.uk/phyre2/PD2_ca2main/.
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Affiliation(s)
- Benjamin L Moore
- Division of Molecular Biosciences, Imperial College, South Kensington Campus, London, United Kingdom
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31
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Sunami T, Kono H. Local conformational changes in the DNA interfaces of proteins. PLoS One 2013; 8:e56080. [PMID: 23418514 PMCID: PMC3571985 DOI: 10.1371/journal.pone.0056080] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2012] [Accepted: 01/03/2013] [Indexed: 11/18/2022] Open
Abstract
When a protein binds to DNA, a conformational change is often induced so that the protein will fit into the DNA structure. Therefore, quantitative analyses were conducted to understand the conformational changes in proteins. The results showed that conformational changes in DNA interfaces are more frequent than in non-interfaces, and DNA interfaces have more conformational variations in the DNA-free form. As expected, the former indicates that interaction with DNA has some influence on protein structure. The latter suggests that the intrinsic conformational flexibility of DNA interfaces is important for adjusting their conformation for DNA. The amino acid propensities of the conformationally changed regions in DNA interfaces indicate that hydrophilic residues are preferred over the amino acids that appear in the conformationally unchanged regions. This trend is true for disordered regions, suggesting again that intrinsic flexibility is of importance not only for DNA binding but also for interactions with other molecules. These results demonstrate that fragments destined to be DNA interfaces have an intrinsic flexibility and are composed of amino acids with the capability of binding to DNA. This information suggests that the prediction of DNA binding sites may be improved by the integration of amino acid preference for DNA and one for disordered regions.
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Affiliation(s)
- Tomoko Sunami
- Molecular Modeling and Simulation Group, Quantum Beam Science Directorate, Japan Atomic Energy Agency, Kizugawa, Kyoto, Japan
| | - Hidetoshi Kono
- Molecular Modeling and Simulation Group, Quantum Beam Science Directorate, Japan Atomic Energy Agency, Kizugawa, Kyoto, Japan
- * E-mail:
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32
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Principles for designing ideal protein structures. Nature 2013; 491:222-7. [PMID: 23135467 DOI: 10.1038/nature11600] [Citation(s) in RCA: 408] [Impact Index Per Article: 37.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2012] [Accepted: 09/19/2012] [Indexed: 02/03/2023]
Abstract
Unlike random heteropolymers, natural proteins fold into unique ordered structures. Understanding how these are encoded in amino-acid sequences is complicated by energetically unfavourable non-ideal features--for example kinked α-helices, bulged β-strands, strained loops and buried polar groups--that arise in proteins from evolutionary selection for biological function or from neutral drift. Here we describe an approach to designing ideal protein structures stabilized by completely consistent local and non-local interactions. The approach is based on a set of rules relating secondary structure patterns to protein tertiary motifs, which make possible the design of funnel-shaped protein folding energy landscapes leading into the target folded state. Guided by these rules, we designed sequences predicted to fold into ideal protein structures consisting of α-helices, β-strands and minimal loops. Designs for five different topologies were found to be monomeric and very stable and to adopt structures in solution nearly identical to the computational models. These results illuminate how the folding funnels of natural proteins arise and provide the foundation for engineering a new generation of functional proteins free from natural evolution.
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33
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Chellapa GD, Rose GD. Reducing the dimensionality of the protein-folding search problem. Protein Sci 2012; 21:1231-40. [PMID: 22692765 DOI: 10.1002/pro.2106] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2012] [Revised: 06/04/2012] [Accepted: 06/05/2012] [Indexed: 11/10/2022]
Abstract
How does a folding protein negotiate a vast, featureless conformational landscape and adopt its native structure in biological real time? Motivated by this search problem, we developed a novel algorithm to compare protein structures. Procedures to identify structural analogs are typically conducted in three-dimensional space: the tertiary structure of a target protein is matched against each candidate in a database of structures, and goodness of fit is evaluated by a distance-based measure, such as the root-mean-square distance between target and candidate. This is an expensive approach because three-dimensional space is complex. Here, we transform the problem into a simpler one-dimensional procedure. Specifically, we identify and label the 11 most populated residue basins in a database of high-resolution protein structures. Using this 11-letter alphabet, any protein's three-dimensional structure can be transformed into a one-dimensional string by mapping each residue onto its corresponding basin. Similarity between the resultant basin strings can then be evaluated by conventional sequence-based comparison. The disorder → order folding transition is abridged on both sides. At the onset, folding conditions necessitate formation of hydrogen-bonded scaffold elements on which proteins are assembled, severely restricting the magnitude of accessible conformational space. Near the end, chain topology is established prior to emergence of the close-packed native state. At this latter stage of folding, the chain remains molten, and residues populate natural basins that are approximated by the 11 basins derived here. In essence, our algorithm reduces the protein-folding search problem to mapping the amino acid sequence onto a restricted basin string.
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Affiliation(s)
- George D Chellapa
- TC Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, Maryland 21218, USA
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34
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Joseph AP, Valadié H, Srinivasan N, de Brevern AG. Local structural differences in homologous proteins: specificities in different SCOP classes. PLoS One 2012; 7:e38805. [PMID: 22745680 PMCID: PMC3382195 DOI: 10.1371/journal.pone.0038805] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2011] [Accepted: 05/10/2012] [Indexed: 11/19/2022] Open
Abstract
The constant increase in the number of solved protein structures is of great help in understanding the basic principles behind protein folding and evolution. 3-D structural knowledge is valuable in designing and developing methods for comparison, modelling and prediction of protein structures. These approaches for structure analysis can be directly implicated in studying protein function and for drug design. The backbone of a protein structure favours certain local conformations which include α-helices, β-strands and turns. Libraries of limited number of local conformations (Structural Alphabets) were developed in the past to obtain a useful categorization of backbone conformation. Protein Block (PB) is one such Structural Alphabet that gave a reasonable structure approximation of 0.42 Å. In this study, we use PB description of local structures to analyse conformations that are preferred sites for structural variations and insertions, among group of related folds. This knowledge can be utilized in improving tools for structure comparison that work by analysing local structure similarities. Conformational differences between homologous proteins are known to occur often in the regions comprising turns and loops. Interestingly, these differences are found to have specific preferences depending upon the structural classes of proteins. Such class-specific preferences are mainly seen in the all-β class with changes involving short helical conformations and hairpin turns. A test carried out on a benchmark dataset also indicates that the use of knowledge on the class specific variations can improve the performance of a PB based structure comparison approach. The preference for the indel sites also seem to be confined to a few backbone conformations involving β-turns and helix C-caps. These are mainly associated with short loops joining the regular secondary structures that mediate a reversal in the chain direction. Rare β-turns of type I’ and II’ are also identified as preferred sites for insertions.
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Affiliation(s)
- Agnel Praveen Joseph
- INSERM, UMR-S 665, Dynamique des Structures et Interactions des Macromolécules Biologiques (DSIMB), Paris, France
- Univ Paris Diderot, Sorbonne Paris Cité, UMR 665, Paris, France
- Institut National de la Transfusion Sanguine (INTS), Paris, France
| | - Hélène Valadié
- INSERM UMR-S 726, DSIMB, Université Paris Diderot - Paris 7, Paris, France
| | | | - Alexandre G. de Brevern
- INSERM, UMR-S 665, Dynamique des Structures et Interactions des Macromolécules Biologiques (DSIMB), Paris, France
- Univ Paris Diderot, Sorbonne Paris Cité, UMR 665, Paris, France
- Institut National de la Transfusion Sanguine (INTS), Paris, France
- * E-mail:
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35
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Astakhova TV, Lobanov MN, Poverennaya IV, Roytberg MA, Yacovlev VV. Verification of the PREFAB alignment database. Biophysics (Nagoya-shi) 2012. [DOI: 10.1134/s0006350912020030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
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36
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Joseph AP, Srinivasan N, de Brevern AG. Cis-trans peptide variations in structurally similar proteins. Amino Acids 2012; 43:1369-81. [PMID: 22227866 DOI: 10.1007/s00726-011-1211-9] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2011] [Accepted: 12/22/2011] [Indexed: 12/30/2022]
Abstract
The presence of energetically less favourable cis peptides in protein structures has been observed to be strongly associated with its structural integrity and function. Inter-conversion between the cis and trans conformations also has an important role in the folding process. In this study, we analyse the extent of conservation of cis peptides among similar folds. We look at both the amino acid preferences and local structural changes associated with such variations. Nearly 34% of the Xaa-Proline cis bonds are not conserved in structural relatives; Proline also has a high tendency to get replaced by another amino acid in the trans conformer. At both positions bounding the peptide bond, Glycine has a higher tendency to lose the cis conformation. The cis conformation of more than 30% of β turns of type VIb and IV are not found to be conserved in similar structures. A different view using Protein Block-based description of backbone conformation, suggests that many of the local conformational changes are highly different from the general local structural variations observed among structurally similar proteins. Changes between cis and trans conformations are found to be associated with the evolution of new functions facilitated by local structural changes. This is most frequent in enzymes where new catalytic activity emerges with local changes in the active site. Cis-trans changes are also seen to facilitate inter-domain and inter-protein interactions. As in the case of folding, cis-trans conversions have been used as an important driving factor in evolution.
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Affiliation(s)
- Agnel Praveen Joseph
- INSERM UMR-S 665, Dynamique des Structures et Interactions des Macromolécules Biologiques, Université Denis Diderot-Paris 7, INTS, 6 rue Alexandre Cabanel, Paris Cedex 15, France
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Beaufays J, Lins L, Thomas A, Brasseur R. In silico predictions of 3D structures of linear and cyclic peptides with natural and non-proteinogenic residues. J Pept Sci 2011; 18:17-24. [PMID: 22033979 DOI: 10.1002/psc.1410] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2011] [Revised: 06/14/2011] [Accepted: 07/01/2011] [Indexed: 11/08/2022]
Abstract
We extended the use of Peplook, an in silico procedure for the prediction of three-dimensional (3D) models of linear peptides to the prediction of 3D models of cyclic peptides and thanks to the ab initio calculation procedure, to the calculation of peptides with non-proteinogenic amino acids. Indeed, such peptides cannot be predicted by homology or threading. We compare the calculated models with NMR and X-ray models and for the cyclic peptides, with models predicted by other in silico procedures (Pep-Fold and I-Tasser). For cyclic peptides, on a set of 38 peptides, average root mean square deviation of backbone atoms (BB-RMSD) was 3.8 and 4.1 Å for Peplook and Pep-Fold, respectively. The best results are obtained with I-Tasser (2.5 Å) although evaluations were biased by the fact that the resolved Protein Data Bank models could be used as template by the server. Peplook and Pep-Fold give similar results, better for short (up to 20 residues) than for longer peptides. For peptides with non-proteinogenic residues, performances of Peplook are sound with an average BB-RMSD of 3.6 Å for 'non-natural peptides' and 3.4 Å for peptides combining non-proteinogenic residues and cyclic structure. These results open interesting possibilities for the design of peptidic drugs.
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Affiliation(s)
- Jérôme Beaufays
- Centre de Biophysique Moléculaire Numérique, ULg, Gembloux Agro Bio Tech, Passage des Déportés, 2, 5030, Gembloux, Belgium
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38
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Charlois Y, Lins L, Brasseur R. A new in-silico method for determination of helical transmembrane domains based on the PepLook scan: application to IL-2Rβ and IL-2Rγc receptor chains. BMC STRUCTURAL BIOLOGY 2011; 11:26. [PMID: 21605471 PMCID: PMC3123172 DOI: 10.1186/1472-6807-11-26] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/11/2010] [Accepted: 05/24/2011] [Indexed: 11/10/2022]
Abstract
BACKGROUND Modeling of transmembrane domains (TMDs) requires correct prediction of interfacial residues for in-silico modeling and membrane insertion studies. This implies the defining of a target sequence long enough to contain interfacial residues. However, too long sequences induce artifactual polymorphism: within tested modeling methods, the longer the target sequence, the more variable the secondary structure, as though the procedure were stopped before the end of the calculation (which may in fact be unreachable). Moreover, delimitation of these TMDs can produce variable results with sequence based two-dimensional prediction methods, especially for sequences showing polymorphism. To solve this problem, we developed a new modeling procedure using the PepLook method. We scanned the sequences by modeling peptides from the target sequence with a window of 19 residues. RESULTS Using sequences whose NMR-structures are already known (GpA, EphA1 and Erb2-HER2), we first determined that the hydrophobic to hydrophilic accessible surface area ratio (ASAr) was the best criterion for delimiting the TMD sequence. The length of the helical structure and the Impala method further supported the determination of the TMD limits. This method was applied to the IL-2Rβ and IL-2Rγ TMD sequences of Homo sapiens, Rattus norvegicus, Mus musculus and Bos taurus. CONCLUSIONS We succeeded in reducing the variation in the TMD limits to only 2 residues and in gaining structural information.
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Affiliation(s)
- Yan Charlois
- Centre de Biophysique Moleculaire Numerique, Gembloux Agro Bio-tech, 5030 Gembloux, Belgium
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39
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Gelly JC, Joseph AP, Srinivasan N, de Brevern AG. iPBA: a tool for protein structure comparison using sequence alignment strategies. Nucleic Acids Res 2011; 39:W18-23. [PMID: 21586582 PMCID: PMC3125758 DOI: 10.1093/nar/gkr333] [Citation(s) in RCA: 68] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
With the immense growth in the number of available protein structures, fast and accurate structure comparison has been essential. We propose an efficient method for structure comparison, based on a structural alphabet. Protein Blocks (PBs) is a widely used structural alphabet with 16 pentapeptide conformations that can fairly approximate a complete protein chain. Thus a 3D structure can be translated into a 1D sequence of PBs. With a simple Needleman–Wunsch approach and a raw PB substitution matrix, PB-based structural alignments were better than many popular methods. iPBA web server presents an improved alignment approach using (i) specialized PB Substitution Matrices (SM) and (ii) anchor-based alignment methodology. With these developments, the quality of ∼88% of alignments was improved. iPBA alignments were also better than DALI, MUSTANG and GANGSTA+ in >80% of the cases. The webserver is designed to for both pairwise comparisons and database searches. Outputs are given as sequence alignment and superposed 3D structures displayed using PyMol and Jmol. A local alignment option for detecting subs-structural similarity is also embedded. As a fast and efficient ‘sequence-based’ structure comparison tool, we believe that it will be quite useful to the scientific community. iPBA can be accessed at http://www.dsimb.inserm.fr/dsimb_tools/ipba/.
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Affiliation(s)
- Jean-Christophe Gelly
- INSERM, UMR-S 665, Dynamique des Structures et Interactions des Macromolécules Biologiques, Université Paris Diderot-Paris 7, Institut National de la Transfusion Sanguine, 6, rue Alexandre Cabanel, 75739 Paris cedex 15, France
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Joseph AP, Srinivasan N, de Brevern AG. Improvement of protein structure comparison using a structural alphabet. Biochimie 2011; 93:1434-45. [PMID: 21569819 DOI: 10.1016/j.biochi.2011.04.010] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2010] [Accepted: 04/12/2011] [Indexed: 12/29/2022]
Abstract
The three dimensional structure of a protein provides major insights into its function. Protein structure comparison has implications in functional and evolutionary studies. A structural alphabet (SA) is a library of local protein structure prototypes that can abstract every part of protein main chain conformation. Protein Blocks (PBs) is a widely used SA, composed of 16 prototypes, each representing a pentapeptide backbone conformation defined in terms of dihedral angles. Through this description, the 3D structural information can be translated into a 1D sequence of PBs. In a previous study, we have used this approach to compare protein structures encoded in terms of PBs. A classical sequence alignment procedure based on dynamic programming was used, with a dedicated PB Substitution Matrix (SM). PB-based pairwise structural alignment method gave an excellent performance, when compared to other established methods for mining. In this study, we have (i) refined the SMs and (ii) improved the Protein Block Alignment methodology (named as iPBA). The SM was normalized in regards to sequence and structural similarity. Alignment of protein structures often involves similar structural regions separated by dissimilar stretches. A dynamic programming algorithm that weighs these local similar stretches has been designed. Amino acid substitutions scores were also coupled linearly with the PB substitutions. iPBA improves (i) the mining efficiency rate by 6.8% and (ii) more than 82% of the alignments have a better quality. A higher efficiency in aligning multi-domain proteins could be also demonstrated. The quality of alignment is better than DALI and MUSTANG in 81.3% of the cases. Thus our study has resulted in an impressive improvement in the quality of protein structural alignment.
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Affiliation(s)
- Agnel Praveen Joseph
- INSERM UMR-S 665, Dynamique des Structures et Interactions des Macromolécules Biologiques, 6, rue Alexandre Cabanel, 75739 Paris Cedex 15, France.
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Mansiaux Y, Joseph AP, Gelly JC, de Brevern AG. Assignment of PolyProline II conformation and analysis of sequence--structure relationship. PLoS One 2011; 6:e18401. [PMID: 21483785 PMCID: PMC3069088 DOI: 10.1371/journal.pone.0018401] [Citation(s) in RCA: 77] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2010] [Accepted: 03/07/2011] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Secondary structures are elements of great importance in structural biology, biochemistry and bioinformatics. They are broadly composed of two repetitive structures namely α-helices and β-sheets, apart from turns, and the rest is associated to coil. These repetitive secondary structures have specific and conserved biophysical and geometric properties. PolyProline II (PPII) helix is yet another interesting repetitive structure which is less frequent and not usually associated with stabilizing interactions. Recent studies have shown that PPII frequency is higher than expected, and they could have an important role in protein-protein interactions. METHODOLOGY/PRINCIPAL FINDINGS A major factor that limits the study of PPII is that its assignment cannot be carried out with the most commonly used secondary structure assignment methods (SSAMs). The purpose of this work is to propose a PPII assignment methodology that can be defined in the frame of DSSP secondary structure assignment. Considering the ambiguity in PPII assignments by different methods, a consensus assignment strategy was utilized. To define the most consensual rule of PPII assignment, three SSAMs that can assign PPII, were compared and analyzed. The assignment rule was defined to have a maximum coverage of all assignments made by these SSAMs. Not many constraints were added to the assignment and only PPII helices of at least 2 residues length are defined. CONCLUSIONS/SIGNIFICANCE The simple rules designed in this study for characterizing PPII conformation, lead to the assignment of 5% of all amino as PPII. Sequence-structure relationships associated with PPII, defined by the different SSAMs, underline few striking differences. A specific study of amino acid preferences in their N and C-cap regions was carried out as their solvent accessibility and contact patterns. Thus the assignment of PPII can be coupled with DSSP and thus opens a simple way for further analysis in this field.
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Affiliation(s)
- Yohann Mansiaux
- INSERM, UMR-S 665, Dynamique des Structures et Interactions des Macromolécules Biologiques (DSIMB), Paris, France
- Université Paris Diderot - Paris 7, Paris, France
- Institut National de la Transfusion Sanguine (INTS), Paris, France
| | - Agnel Praveen Joseph
- INSERM, UMR-S 665, Dynamique des Structures et Interactions des Macromolécules Biologiques (DSIMB), Paris, France
- Université Paris Diderot - Paris 7, Paris, France
- Institut National de la Transfusion Sanguine (INTS), Paris, France
| | - Jean-Christophe Gelly
- INSERM, UMR-S 665, Dynamique des Structures et Interactions des Macromolécules Biologiques (DSIMB), Paris, France
- Université Paris Diderot - Paris 7, Paris, France
- Institut National de la Transfusion Sanguine (INTS), Paris, France
| | - Alexandre G. de Brevern
- INSERM, UMR-S 665, Dynamique des Structures et Interactions des Macromolécules Biologiques (DSIMB), Paris, France
- Université Paris Diderot - Paris 7, Paris, France
- Institut National de la Transfusion Sanguine (INTS), Paris, France
- * E-mail:
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Esque J, Oguey C, de Brevern AG. Comparative Analysis of Threshold and Tessellation Methods for Determining Protein Contacts. J Chem Inf Model 2011; 51:493-507. [DOI: 10.1021/ci100195t] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Jeremy Esque
- LPTM, CNRS UMR 8089, Université de Cergy Pontoise, 2 av. Adolphe Chauvin, 95302 Cergy-Pontoise, France
- INSERM UMR-S 665, Dynamique des Structures et Interactions des Macromolécules Biologiques (DSIMB), Université Paris Diderot, Paris 7, INTS, 6, rue Alexandre Cabanel, 75739 Paris Cedex 15, France
| | - Christophe Oguey
- LPTM, CNRS UMR 8089, Université de Cergy Pontoise, 2 av. Adolphe Chauvin, 95302 Cergy-Pontoise, France
| | - Alexandre G. de Brevern
- INSERM UMR-S 665, Dynamique des Structures et Interactions des Macromolécules Biologiques (DSIMB), Université Paris Diderot, Paris 7, INTS, 6, rue Alexandre Cabanel, 75739 Paris Cedex 15, France
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de Sousa MM, Munteanu CR, Pazos A, Fonseca NA, Camacho R, Magalhães AL. Amino acid pair- and triplet-wise groupings in the interior of α-helical segments in proteins. J Theor Biol 2010; 271:136-44. [PMID: 21130100 DOI: 10.1016/j.jtbi.2010.11.028] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2010] [Revised: 11/03/2010] [Accepted: 11/23/2010] [Indexed: 10/18/2022]
Abstract
A statistical approach has been applied to analyse primary structure patterns at inner positions of α-helices in proteins. A systematic survey was carried out in a recent sample of non-redundant proteins selected from the Protein Data Bank, which were used to analyse α-helix structures for amino acid pairing patterns. Only residues more than three positions apart from both termini of the α-helix were considered as inner. Amino acid pairings i, i+k (k=1, 2, 3, 4, 5), were analysed and the corresponding 20×20 matrices of relative global propensities were constructed. An analysis of (i, i+4, i+8) and (i, i+3, i+4) triplet patterns was also performed. These analysis yielded information on a series of amino acid patterns (pairings and triplets) showing either high or low preference for α-helical motifs and suggested a novel approach to protein alphabet reduction. In addition, it has been shown that the individual amino acid propensities are not enough to define the statistical distribution of these patterns. Global pair propensities also depend on the type of pattern, its composition and orientation in the protein sequence. The data presented should prove useful to obtain and refine useful predictive rules which can further the development and fine-tuning of protein structure prediction algorithms and tools.
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Affiliation(s)
- Miguel M de Sousa
- REQUIMTE/University of Porto, Faculty of Sciences, R. Campo Alegre 687, 4169-007 Porto, Portugal
| | - Cristian R Munteanu
- REQUIMTE/University of Porto, Faculty of Sciences, R. Campo Alegre 687, 4169-007 Porto, Portugal; Computer Science Faculty, University of A Coruña, Campus de Elviña S/N, 15071A Coruña, Spain
| | - Alejandro Pazos
- Computer Science Faculty, University of A Coruña, Campus de Elviña S/N, 15071A Coruña, Spain
| | - Nuno A Fonseca
- CRACS-INESC Porto L.A., R. Campo Alegre 1021/1055, 4169-007 Porto, Portugal
| | - Rui Camacho
- LIAAD-INESC-Porto, DEI and FEUP, R. Dr. Roberto Frias s/n, 4200-465 Porto, Portugal
| | - A L Magalhães
- REQUIMTE/University of Porto, Faculty of Sciences, R. Campo Alegre 687, 4169-007 Porto, Portugal
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Realistic modeling approaches of structure–function properties of CPPs in non-covalent complexes. BIOCHIMICA ET BIOPHYSICA ACTA-BIOMEMBRANES 2010; 1798:2217-22. [DOI: 10.1016/j.bbamem.2010.02.020] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2009] [Revised: 02/15/2010] [Accepted: 02/16/2010] [Indexed: 11/23/2022]
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Joseph AP, Agarwal G, Mahajan S, Gelly JC, Swapna LS, Offmann B, Cadet F, Bornot A, Tyagi M, Valadié H, Schneider B, Etchebest C, Srinivasan N, De Brevern AG. A short survey on protein blocks. Biophys Rev 2010; 2:137-147. [PMID: 21731588 DOI: 10.1007/s12551-010-0036-1] [Citation(s) in RCA: 97] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Protein structures are classically described in terms of secondary structures. Even if the regular secondary structures have relevant physical meaning, their recognition from atomic coordinates has some important limitations such as uncertainties in the assignment of boundaries of helical and β-strand regions. Further, on an average about 50% of all residues are assigned to an irregular state, i.e., the coil. Thus different research teams have focused on abstracting conformation of protein backbone in the localized short stretches. Using different geometric measures, local stretches in protein structures are clustered in a chosen number of states. A prototype representative of the local structures in each cluster is generally defined. These libraries of local structures prototypes are named as "structural alphabets". We have developed a structural alphabet, named Protein Blocks, not only to approximate the protein structure, but also to predict them from sequence. Since its development, we and other teams have explored numerous new research fields using this structural alphabet. We review here some of the most interesting applications.
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Affiliation(s)
- Agnel Praveen Joseph
- DSIMB, Dynamique des Structures et Interactions des Macromolécules Biologiques Université Paris-Diderot - Paris VII INTS INSERM : U665 INTS, 6 rue Alexandre Cabanel, 75739 Paris Cedex 15 FRANCE,FR
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Smolarek D, Bertrand O, Czerwinski M, Colin Y, Etchebest C, de Brevern AG. Multiple interests in structural models of DARC transmembrane protein. Transfus Clin Biol 2010; 17:184-96. [PMID: 20655787 DOI: 10.1016/j.tracli.2010.05.003] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2010] [Accepted: 05/21/2010] [Indexed: 12/23/2022]
Abstract
Duffy Antigen Receptor for Chemokines (DARC) is an unusual transmembrane chemokine receptor which (i) binds the two main chemokine families and (ii) does not transduct any signal as it lacks the DRY consensus sequence. It is considered as silent chemokine receptor, a tank useful for chemiotactism. DARC had been particularly studied as a major actor of malaria infection by Plasmodium vivax. It is also implicated in multiple chemokine inflammation, inflammatory diseases, in cancer and might play a role in HIV infection and AIDS. In this review, we focus on the interest to build structural model of DARC to understand more precisely its abilities to bind its physiological ligand CXCL8 and its malaria ligand. We also present innovative development on VHHs able to bind DARC protein. We underline difficulties and limitations of such bioinformatics approaches and highlight the crucial importance of biological data to conduct these kinds of researches.
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Affiliation(s)
- D Smolarek
- Inserm UMR-S 665, dynamique des structures et interactions des macromolecules biologiques (DSIMB), 6, rue Alexandre-Cabanel, 75739 Paris cedex 15, France
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Influence of assignment on the prediction of transmembrane helices in protein structures. Amino Acids 2010; 39:1241-54. [DOI: 10.1007/s00726-010-0559-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2009] [Accepted: 03/08/2010] [Indexed: 02/01/2023]
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Pandini A, Fornili A, Kleinjung J. Structural alphabets derived from attractors in conformational space. BMC Bioinformatics 2010; 11:97. [PMID: 20170534 PMCID: PMC2838871 DOI: 10.1186/1471-2105-11-97] [Citation(s) in RCA: 45] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2009] [Accepted: 02/20/2010] [Indexed: 11/20/2022] Open
Abstract
Background The hierarchical and partially redundant nature of protein structures justifies the definition of frequently occurring conformations of short fragments as 'states'. Collections of selected representatives for these states define Structural Alphabets, describing the most typical local conformations within protein structures. These alphabets form a bridge between the string-oriented methods of sequence analysis and the coordinate-oriented methods of protein structure analysis. Results A Structural Alphabet has been derived by clustering all four-residue fragments of a high-resolution subset of the protein data bank and extracting the high-density states as representative conformational states. Each fragment is uniquely defined by a set of three independent angles corresponding to its degrees of freedom, capturing in simple and intuitive terms the properties of the conformational space. The fragments of the Structural Alphabet are equivalent to the conformational attractors and therefore yield a most informative encoding of proteins. Proteins can be reconstructed within the experimental uncertainty in structure determination and ensembles of structures can be encoded with accuracy and robustness. Conclusions The density-based Structural Alphabet provides a novel tool to describe local conformations and it is specifically suitable for application in studies of protein dynamics.
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Affiliation(s)
- Alessandro Pandini
- Division of Mathematical Biology, MRC National Institute for Medical Research, London, UK
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Abstract
Multiple protein sequence alignment methods are central to many applications in molecular biology. These methods are typically assessed on benchmark datasets including BALIBASE, OXBENCH, PREFAB and SABMARK, which are important to biologists in making informed choices between programs. In this article, annotations of domain homology and secondary structure are used to define new measures of alignment quality and are used to make the first systematic, independent evaluation of these benchmarks. These measures indicate sensitivity and specificity while avoiding the ambiguous residue correspondences and arbitrary distance cutoffs inherent to structural superpositions. Alignments by selected methods that indicate high-confidence columns (ALIGN-M, DIALIGN-T, FSA and MUSCLE) are also assessed. Fold space coverage and effective benchmark database sizes are estimated by reference to domain annotations, and significant redundancy is found in all benchmarks except SABMARK. Questionable alignments are found in all benchmarks, especially in BALIBASE where 87% of sequences have unknown structure, 20% of columns contain different folds according to SUPERFAMILY and 30% of ‘core block’ columns have conflicting secondary structure according to DSSP. A careful analysis of current protein multiple alignment benchmarks calls into question their ability to determine reliable algorithm rankings.
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Rangwala H, Kauffman C, Karypis G. svmPRAT: SVM-based protein residue annotation toolkit. BMC Bioinformatics 2009; 10:439. [PMID: 20028521 PMCID: PMC2805646 DOI: 10.1186/1471-2105-10-439] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2009] [Accepted: 12/22/2009] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Over the last decade several prediction methods have been developed for determining the structural and functional properties of individual protein residues using sequence and sequence-derived information. Most of these methods are based on support vector machines as they provide accurate and generalizable prediction models. RESULTS We present a general purpose protein residue annotation toolkit (svmPRAT) to allow biologists to formulate residue-wise prediction problems. svmPRAT formulates the annotation problem as a classification or regression problem using support vector machines. One of the key features of svmPRAT is its ease of use in incorporating any user-provided information in the form of feature matrices. For every residue svmPRAT captures local information around the reside to create fixed length feature vectors. svmPRAT implements accurate and fast kernel functions, and also introduces a flexible window-based encoding scheme that accurately captures signals and pattern for training effective predictive models. CONCLUSIONS In this work we evaluate svmPRAT on several classification and regression problems including disorder prediction, residue-wise contact order estimation, DNA-binding site prediction, and local structure alphabet prediction. svmPRAT has also been used for the development of state-of-the-art transmembrane helix prediction method called TOPTMH, and secondary structure prediction method called YASSPP. This toolkit developed provides practitioners an efficient and easy-to-use tool for a wide variety of annotation problems. AVAILABILITY http://www.cs.gmu.edu/~mlbio/svmprat.
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Affiliation(s)
- Huzefa Rangwala
- Computer Science Department, George Mason University, Fairfax, VA, USA.
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