1
|
Cretin G, Périn C, Zimmermann N, Galochkina T, Gelly JC. ICARUS: flexible protein structural alignment based on Protein Units. Bioinformatics 2023; 39:btad459. [PMID: 37498544 PMCID: PMC10400377 DOI: 10.1093/bioinformatics/btad459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 07/04/2023] [Accepted: 07/26/2023] [Indexed: 07/28/2023] Open
Abstract
MOTIVATION Alignment of protein structures is a major problem in structural biology. The first approach commonly used is to consider proteins as rigid bodies. However, alignment of protein structures can be very complex due to conformational variability, or complex evolutionary relationships between proteins such as insertions, circular permutations or repetitions. In such cases, introducing flexibility becomes useful for two reasons: (i) it can help compare two protein chains which adopted two different conformational states, such as due to proteins/ligands interaction or post-translational modifications, and (ii) it aids in the identification of conserved regions in proteins that may have distant evolutionary relationships. RESULTS We propose ICARUS, a new approach for flexible structural alignment based on identification of Protein Units, evolutionarily preserved structural descriptors of intermediate size, between secondary structures and domains. ICARUS significantly outperforms reference methods on a dataset of very difficult structural alignments. AVAILABILITY AND IMPLEMENTATION Code is freely available online at https://github.com/DSIMB/ICARUS.
Collapse
Affiliation(s)
- Gabriel Cretin
- Université Paris Cité and Université des Antilles and Université de la Réunion, INSERM, BIGR, F-75015 Paris, France
- Laboratoire d’Excellence GR-Ex, 75015 Paris, France
| | - Charlotte Périn
- Université Paris Cité and Université des Antilles and Université de la Réunion, INSERM, BIGR, F-75015 Paris, France
- Laboratoire d’Excellence GR-Ex, 75015 Paris, France
- TBI, Université de Toulouse, CNRS, INRAE, INSA, 31077 Toulouse, France
| | - Nicolas Zimmermann
- Université Paris Cité and Université des Antilles and Université de la Réunion, INSERM, BIGR, F-75015 Paris, France
- Laboratoire d’Excellence GR-Ex, 75015 Paris, France
| | - Tatiana Galochkina
- Université Paris Cité and Université des Antilles and Université de la Réunion, INSERM, BIGR, F-75015 Paris, France
- Laboratoire d’Excellence GR-Ex, 75015 Paris, France
| | - Jean-Christophe Gelly
- Université Paris Cité and Université des Antilles and Université de la Réunion, INSERM, BIGR, F-75015 Paris, France
- Laboratoire d’Excellence GR-Ex, 75015 Paris, France
| |
Collapse
|
2
|
Daniluk P, Oleniecki T, Lesyng B. DAMA: a method for computing multiple alignments of protein structures using local structure descriptors. Bioinformatics 2021; 38:80-85. [PMID: 34396393 PMCID: PMC8696102 DOI: 10.1093/bioinformatics/btab571] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Revised: 05/31/2021] [Accepted: 08/12/2021] [Indexed: 02/03/2023] Open
Abstract
MOTIVATION The well-known fact that protein structures are more conserved than their sequences forms the basis of several areas of computational structural biology. Methods based on the structure analysis provide more complete information on residue conservation in evolutionary processes. This is crucial for the determination of evolutionary relationships between proteins and for the identification of recurrent structural patterns present in biomolecules involved in similar functions. However, algorithmic structural alignment is much more difficult than multiple sequence alignment. This study is devoted to the development and applications of DAMA-a novel effective environment capable to compute and analyze multiple structure alignments. RESULTS DAMA is based on local structural similarities, using local 3D structure descriptors and thus accounts for nearest-neighbor molecular environments of aligned residues. It is constrained neither by protein topology nor by its global structure. DAMA is an extension of our previous study (DEDAL) which demonstrated the applicability of local descriptors to pairwise alignment problems. Since the multiple alignment problem is NP-complete, an effective heuristic approach has been developed without imposing any artificial constraints. The alignment algorithm searches for the largest, consistent ensemble of similar descriptors. The new method is capable to capture most of the biologically significant similarities present in canonical test sets and is discriminatory enough to prevent the emergence of larger, but meaningless, solutions. Tests performed on the test sets, including protein kinases, demonstrate DAMA's capability of identifying equivalent residues, which should be very useful in discovering the biological nature of proteins similarity. Performance profiles show the advantage of DAMA over other methods, in particular when using a strict similarity measure QC, which is the ratio of correctly aligned columns, and when applying the methods to more difficult cases. AVAILABILITY AND IMPLEMENTATION DAMA is available online at http://dworkowa.imdik.pan.pl/EP/DAMA. Linux binaries of the software are available upon request. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Paweł Daniluk
- Bioinformatics Laboratory, Mossakowski Medical Research Centre, Polish Academy of Sciences, 02-106 Warsaw, Poland
| | - Tymoteusz Oleniecki
- College of Inter-Faculty Individual Studies in Mathematics and Natural Sciences, University of Warsaw, 02-089 Warsaw, Poland
| | | |
Collapse
|
3
|
Charzewski Ł, Krzyśko KA, Lesyng B. Exploring Covalent Docking Mechanisms of Boron-Based Inhibitors to Class A, C and D β-Lactamases Using Time-dependent Hybrid QM/MM Simulations. Front Mol Biosci 2021; 8:633181. [PMID: 34434961 PMCID: PMC8380965 DOI: 10.3389/fmolb.2021.633181] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Accepted: 07/19/2021] [Indexed: 11/13/2022] Open
Abstract
Recently, molecular covalent docking has been extensively developed to design new classes of inhibitors that form chemical bonds with their biological targets. This strategy for the design of such inhibitors, in particular boron-based inhibitors, holds great promise for the vast family of β-lactamases produced, inter alia, by Gram-negative antibiotic-resistant bacteria. However, the description of covalent docking processes requires a quantum-mechanical approach, and so far, only a few studies of this type have been presented. This study accurately describes the covalent docking process between two model inhibitors - representing two large families of inhibitors based on boronic-acid and bicyclic boronate scaffolds, and three β-lactamases which belong to the A, C, and D classes. Molecular fragments containing boron can be converted from a neutral, trigonal, planar state with sp2 hybridization to the anionic, tetrahedral sp3 state in a process sometimes referred to as morphing. This study applies multi-scale modeling methods, in particular, the hybrid QM/MM approach which has predictive power reaching well beyond conventional molecular modeling. Time-dependent QM/MM simulations indicated several structural changes and geometric preferences, ultimately leading to covalent docking processes. With current computing technologies, this approach is not computationally expensive, can be used in standard molecular modeling and molecular design works, and can effectively support experimental research which should allow for a detailed understanding of complex processes important to molecular medicine. In particular, it can support the rational design of covalent boron-based inhibitors for β-lactamases as well as for many other enzyme systems of clinical relevance, including SARS-CoV-2 proteins.
Collapse
Affiliation(s)
| | | | - Bogdan Lesyng
- Department of Biophysics, Faculty of Physics, University of Warsaw, Warsaw, Poland
| |
Collapse
|
4
|
Fallaize CJ, Green PJ, Mardia KV, Barber S. Bayesian protein sequence and structure alignment. J R Stat Soc Ser C Appl Stat 2020. [DOI: 10.1111/rssc.12394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
| | - Peter J. Green
- University of Bristol UK
- University of Technology Sydney Australia
| | | | | |
Collapse
|
5
|
RUPEE: A fast and accurate purely geometric protein structure search. PLoS One 2019; 14:e0213712. [PMID: 30875409 PMCID: PMC6420038 DOI: 10.1371/journal.pone.0213712] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Accepted: 02/27/2019] [Indexed: 11/19/2022] Open
Abstract
Given the close relationship between protein structure and function, protein structure searches have long played an established role in bioinformatics. Despite their maturity, existing protein structure searches either use simplifying assumptions or compromise between fast response times and quality of results. These limitations can prevent the easy and efficient exploration of relationships between protein structures, which is the norm in other areas of inquiry. To address these limitations we have developed RUPEE, a fast and accurate purely geometric structure search combining techniques from information retrieval and big data with a novel approach to encoding sequences of torsion angles. Comparing our results to the output of mTM, SSM, and the CATHEDRAL structural scan, it is clear that RUPEE has set a new bar for purely geometric big data approaches to protein structure searches. RUPEE in top-aligned mode produces equal or better results than the best available protein structure searches, and RUPEE in fast mode demonstrates the fastest response times coupled with high quality results. The RUPEE protein structure search is available at https://ayoubresearch.com. Code and data are available at https://github.com/rayoub/rupee.
Collapse
|
6
|
High-throughput and scalable protein function identification with Hadoop and Map-only pattern of the MapReduce processing model. Knowl Inf Syst 2018. [DOI: 10.1007/s10115-018-1245-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
|
7
|
Antczak M, Kasprzak M, Lukasiak P, Blazewicz J. Structural alignment of protein descriptors - a combinatorial model. BMC Bioinformatics 2016; 17:383. [PMID: 27639380 PMCID: PMC5027075 DOI: 10.1186/s12859-016-1237-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2016] [Accepted: 09/02/2016] [Indexed: 11/17/2022] Open
Abstract
Background Structural alignment of proteins is one of the most challenging problems in molecular biology. The tertiary structure of a protein strictly correlates with its function and computationally predicted structures are nowadays a main premise for understanding the latter. However, computationally derived 3D models often exhibit deviations from the native structure. A way to confirm a model is a comparison with other structures. The structural alignment of a pair of proteins can be defined with the use of a concept of protein descriptors. The protein descriptors are local substructures of protein molecules, which allow us to divide the original problem into a set of subproblems and, consequently, to propose a more efficient algorithmic solution. In the literature, one can find many applications of the descriptors concept that prove its usefulness for insight into protein 3D structures, but the proposed approaches are presented rather from the biological perspective than from the computational or algorithmic point of view. Efficient algorithms for identification and structural comparison of descriptors can become crucial components of methods for structural quality assessment as well as tertiary structure prediction. Results In this paper, we propose a new combinatorial model and new polynomial-time algorithms for the structural alignment of descriptors. The model is based on the maximum-size assignment problem, which we define here and prove that it can be solved in polynomial time. We demonstrate suitability of this approach by comparison with an exact backtracking algorithm. Besides a simplification coming from the combinatorial modeling, both on the conceptual and complexity level, we gain with this approach high quality of obtained results, in terms of 3D alignment accuracy and processing efficiency. Conclusions All the proposed algorithms were developed and integrated in a computationally efficient tool descs-standalone, which allows the user to identify and structurally compare descriptors of biological molecules, such as proteins and RNAs. Both PDB (Protein Data Bank) and mmCIF (macromolecular Crystallographic Information File) formats are supported. The proposed tool is available as an open source project stored on GitHub (https://github.com/mantczak/descs-standalone). Electronic supplementary material The online version of this article (doi:10.1186/s12859-016-1237-9) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Maciej Antczak
- Institute of Computing Science, Poznan University of Technology, Piotrowo 2, Poznan, 60-965, Poland.
| | - Marta Kasprzak
- Institute of Computing Science, Poznan University of Technology, Piotrowo 2, Poznan, 60-965, Poland.,Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, Poznan, 61-704, Poland
| | - Piotr Lukasiak
- Institute of Computing Science, Poznan University of Technology, Piotrowo 2, Poznan, 60-965, Poland.,Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, Poznan, 61-704, Poland
| | - Jacek Blazewicz
- Institute of Computing Science, Poznan University of Technology, Piotrowo 2, Poznan, 60-965, Poland.,Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, Poznan, 61-704, Poland
| |
Collapse
|
8
|
Dziubiński M, Daniluk P, Lesyng B. ResiCon: a method for the identification of dynamic domains, hinges and interfacial regions in proteins. Bioinformatics 2016; 32:25-34. [PMID: 26342233 DOI: 10.1093/bioinformatics/btv525] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2015] [Accepted: 08/21/2015] [Indexed: 11/12/2022] Open
Abstract
MOTIVATION Structure of most proteins is flexible. Identification and analysis of intramolecular motions is a complex problem. Breaking a structure into relatively rigid parts, the so-called dynamic domains, may help comprehend the complexity of protein's mobility. We propose a new approach called ResiCon (Residue Contacts analysis), which performs this task by applying a data-mining analysis of an ensemble of protein configurations and recognizes dynamic domains, hinges and interfacial regions, by considering contacts between residues. RESULTS Dynamic domains found by ResiCon are more compact than those identified by two other popular methods: PiSQRD and GeoStaS. The current analysis was carried out using a known reference set of 30 NMR protein structures, as well as molecular dynamics simulation data of flap opening events in HIV-1 protease. The more detailed analysis of HIV-1 protease dataset shows that ResiCon identified dynamic domains involved in structural changes of functional importance. AVAILABILITY AND IMPLEMENTATION The ResiCon server is available at URL: http://dworkowa.imdik.pan.pl/EP/ResiCon. CONTACT pawel@bioexploratorium.pl SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Maciej Dziubiński
- Department of Biophysics and CoE BioExploratorium, Faculty of Physics, University of Warsaw, 02-089 Warsaw, Poland and
| | - Paweł Daniluk
- Department of Biophysics and CoE BioExploratorium, Faculty of Physics, University of Warsaw, 02-089 Warsaw, Poland and Bioinformatics Laboratory, Mossakowski Medical Research Centre, Polish Academy of Sciences, 02-106 Warsaw, Poland
| | - Bogdan Lesyng
- Department of Biophysics and CoE BioExploratorium, Faculty of Physics, University of Warsaw, 02-089 Warsaw, Poland and Bioinformatics Laboratory, Mossakowski Medical Research Centre, Polish Academy of Sciences, 02-106 Warsaw, Poland
| |
Collapse
|
9
|
Daniluk P, Wilczyński B, Lesyng B. WeBIAS: a web server for publishing bioinformatics applications. BMC Res Notes 2015; 8:628. [PMID: 26526344 PMCID: PMC4629404 DOI: 10.1186/s13104-015-1622-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2015] [Accepted: 10/26/2015] [Indexed: 01/01/2023] Open
Abstract
Background One of the requirements for a successful scientific tool is its availability. Developing a functional web service, however, is usually considered a mundane and ungratifying task, and quite often neglected. When publishing bioinformatic applications, such attitude puts additional burden on the reviewers who have to cope with poorly designed interfaces in order to assess quality of presented methods, as well as impairs actual usefulness to the scientific community at large. Results In this note we present WeBIAS—a simple, self-contained solution to make command-line programs accessible through web forms. It comprises a web portal capable of serving several applications and backend schedulers which carry out computations. The server handles user registration and authentication, stores queries and results, and provides a convenient administrator interface. WeBIAS is implemented in Python and available under GNU Affero General Public License. It has been developed and tested on GNU/Linux compatible platforms covering a vast majority of operational WWW servers. Since it is written in pure Python, it should be easy to deploy also on all other platforms supporting Python (e.g. Windows, Mac OS X). Documentation and source code, as well as a demonstration site are available at http://bioinfo.imdik.pan.pl/webias. Conclusions WeBIAS has been designed specifically with ease of installation and deployment of services in mind. Setting up a simple application requires minimal effort, yet it is possible to create visually appealing, feature-rich interfaces for query submission and presentation of results.
Collapse
Affiliation(s)
- Paweł Daniluk
- Bioinformatics Laboratory, Mossakowski Medical Research Centre, Pawińskiego 5, 02-106, Warsaw, Poland. .,Department of Biophysics, Faculty of Physics, University of Warsaw, Warsaw, Poland.
| | | | - Bogdan Lesyng
- Bioinformatics Laboratory, Mossakowski Medical Research Centre, Pawińskiego 5, 02-106, Warsaw, Poland. .,Department of Biophysics, Faculty of Physics, University of Warsaw, Warsaw, Poland.
| |
Collapse
|
10
|
Mrozek D, Brożek M, Małysiak-Mrozek B. Parallel implementation of 3D protein structure similarity searches using a GPU and the CUDA. J Mol Model 2014; 20:2067. [PMID: 24481593 PMCID: PMC3936136 DOI: 10.1007/s00894-014-2067-1] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2013] [Accepted: 10/11/2013] [Indexed: 01/16/2023]
Abstract
Searching for similar 3D protein structures is one of the primary processes employed in the field of structural bioinformatics. However, the computational complexity of this process means that it is constantly necessary to search for new methods that can perform such a process faster and more efficiently. Finding molecular substructures that complex protein structures have in common is still a challenging task, especially when entire databases containing tens or even hundreds of thousands of protein structures must be scanned. Graphics processing units (GPUs) and general purpose graphics processing units (GPGPUs) can perform many time-consuming and computationally demanding processes much more quickly than a classical CPU can. In this paper, we describe the GPU-based implementation of the CASSERT algorithm for 3D protein structure similarity searching. This algorithm is based on the two-phase alignment of protein structures when matching fragments of the compared proteins. The GPU (GeForce GTX 560Ti: 384 cores, 2GB RAM) implementation of CASSERT (“GPU-CASSERT”) parallelizes both alignment phases and yields an average 180-fold increase in speed over its CPU-based, single-core implementation on an Intel Xeon E5620 (2.40GHz, 4 cores). In this paper, we show that massive parallelization of the 3D structure similarity search process on many-core GPU devices can reduce the execution time of the process, allowing it to be performed in real time. GPU-CASSERT is available at: http://zti.polsl.pl/dmrozek/science/gpucassert/cassert.htm.
Collapse
Affiliation(s)
- Dariusz Mrozek
- Institute of Informatics, Silesian University of Technology, Gliwice, Poland,
| | | | | |
Collapse
|
11
|
Ma J, Wang S. Algorithms, Applications, and Challenges of Protein Structure Alignment. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2014; 94:121-75. [DOI: 10.1016/b978-0-12-800168-4.00005-6] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
|
12
|
Binding Stoichiometry of a Recombinant Selenophosphate Synthetase with One Synonymic Substitution E197D to a Fluorescent Nucleotide Analog of ATP, TNP-ATP. JOURNAL OF AMINO ACIDS 2013; 2013:983565. [PMID: 24719756 PMCID: PMC3956282 DOI: 10.1155/2013/983565] [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: 09/30/2012] [Accepted: 12/07/2012] [Indexed: 11/17/2022]
Abstract
The transformation of the strain DH5αTM-T1R with plasmid vector pET11a containing the cloned gene of bacterial selenophosphate synthetase (SPS), selD, from the E. coli BL21-Gold (DE3) strain gives an overproducing strain of SPS with one synonymic substitution, E197D. The transformation efficiency was estimated as 8 × 108 CFU/μg plasmid DNA. 28 mg of highly purified preparation of recombinant SPS capable of binding TNP-ATP was eluted from DEAE-Sephadex column in amount of 15 % from the total soluble protein in crude extract. The fluorescent derivative of ATP, 2′(3′)-O-(2,4,6-trinitrophenyl)adenosine-5′-triphosphate (TNP-ATP), was used as a synthetic analog of the substrate for the monitoring and quantitative analysis of the functional activity of SPS. The non-linear regression analysis of the saturation curve of TNP-ATP binding to D197 SPS with GraphPad Prism software fits to a model with 2 distinct binding sites with KDs
different in order. The SPS existence in a form of tetramer in given reaction conditions, in accordance with the concentration stoichiometry of 4 moles of TNP-ATP to 1 mole of recombinant protein, is being discussed. The tetramer structure was predicted with molecular modelling software YASARA and modelled in vacuum using steepest descent minimization energy method. We hypothesize here the recombinant SPS exists as a dimer in solution with two active sites capable of ATP binding in each subunit.
Collapse
|
13
|
Minami S, Sawada K, Chikenji G. MICAN: a protein structure alignment algorithm that can handle Multiple-chains, Inverse alignments, C(α) only models, Alternative alignments, and Non-sequential alignments. BMC Bioinformatics 2013; 14:24. [PMID: 23331634 PMCID: PMC3637537 DOI: 10.1186/1471-2105-14-24] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2012] [Accepted: 01/08/2013] [Indexed: 11/10/2022] Open
Abstract
Background Protein pairs that have the same secondary structure packing arrangement but have different topologies have attracted much attention in terms of both evolution and physical chemistry of protein structures. Further investigation of such protein relationships would give us a hint as to how proteins can change their fold in the course of evolution, as well as a insight into physico-chemical properties of secondary structure packing. For this purpose, highly accurate sequence order independent structure comparison methods are needed. Results We have developed a novel protein structure alignment algorithm, MICAN (a structure alignment algorithm that can handle Multiple-chain complexes, Inverse direction of secondary structures, Cα only models, Alternative alignments, and Non-sequential alignments). The algorithm was designed so as to identify the best structural alignment between protein pairs by disregarding the connectivity between secondary structure elements (SSE). One of the key feature of the algorithm is utilizing the multiple vector representation for each SSE, which enables us to correctly treat bent or twisted nature of long SSE. We compared MICAN with other 9 publicly available structure alignment programs, using both reference-dependent and reference-independent evaluation methods on a variety of benchmark test sets which include both sequential and non-sequential alignments. We show that MICAN outperforms the other existing methods for reproducing reference alignments of non-sequential test sets. Further, although MICAN does not specialize in sequential structure alignment, it showed the top level performance on the sequential test sets. We also show that MICAN program is the fastest non-sequential structure alignment program among all the programs we examined here. Conclusions MICAN is the fastest and the most accurate program among non-sequential alignment programs we examined here. These results suggest that MICAN is a highly effective tool for automatically detecting non-trivial structural relationships of proteins, such as circular permutations and segment-swapping, many of which have been identified manually by human experts so far. The source code of MICAN is freely download-able at http://www.tbp.cse.nagoya-u.ac.jp/MICAN.
Collapse
Affiliation(s)
- Shintaro Minami
- Department of Computational Science and Engineering, Nagoya University, Nagoya 464-8603, Japan
| | | | | |
Collapse
|