BMC Structural Biology | |
A simple method for finding a protein’s ligand-binding pockets | |
Jack A Tuszynski1  Seyed Majid Saberi Fathi2  | |
[1] Department of Physics, University of Alberta, Edmonton, Alberta, Canada;Department of Physics, Ferdowsi University of Mashhad, Mashhad, Iran | |
关键词: Computational methods; Ligand-binding pockets; Protein structure; | |
Others : 1090799 DOI : 10.1186/1472-6807-14-18 |
|
received in 2014-01-09, accepted in 2014-07-11, 发布年份 2014 | |
【 摘 要 】
Background
This paper provides a simple and rapid method for a protein-clustering strategy. The basic idea implemented here is to use computational geometry methods to predict and characterize ligand-binding pockets of a given protein structure. In addition to geometrical characteristics of the protein structure, we consider some simple biochemical properties that help recognize the best candidates for pockets in a protein’s active site.
Results
Our results are shown to produce good agreement with known empirical results.
Conclusions
The method presented in this paper is a low-cost rapid computational method that could be used to classify proteins and other biomolecules, and furthermore could be useful in reducing the cost and time of drug discovery.
【 授权许可】
2014 Saberi Fathi and Tuszynski; licensee BioMed Central Ltd.
【 预 览 】
Files | Size | Format | View |
---|---|---|---|
20150128163427535.pdf | 1287KB | download | |
Figure 9. | 21KB | Image | download |
Figure 8. | 21KB | Image | download |
Figure 7. | 20KB | Image | download |
Figure 6. | 60KB | Image | download |
Figure 5. | 72KB | Image | download |
Figure 4. | 39KB | Image | download |
Figure 3. | 96KB | Image | download |
Figure 2. | 58KB | Image | download |
Figure 1. | 57KB | Image | download |
【 图 表 】
Figure 1.
Figure 2.
Figure 3.
Figure 4.
Figure 5.
Figure 6.
Figure 7.
Figure 8.
Figure 9.
【 参考文献 】
- [1]Polgár L: The catalytic triad of serine peptidases. Cell Mol Life Sci CMLS 2005, 62:2161-2172.
- [2]Mooney SD, Liang MH-P, DeConde R, Altman RB: Structural characterization of proteins using residue environments. Proteins 2005, 61:741-747.
- [3]Shulman-Peleg A, Nussinov R, Wolfson HJ: Recognition of functional sites in protein structures. J Mol Biol 2004, 339:607-633.
- [4]Fetrow JS, Godzik A, Skolnick J: Functional analysis of the Escherichia coli genome using the sequence-to-structure-to-function paradigm: identification of proteins exhibiting the glutaredoxin/thioredoxin disulfide oxidoreductase activity. J Mol Biol 1998, 282:703-711.
- [5]Wallace AC, Borkakoti N, Thornton JM: TESS: a geometric hashing algorithm for deriving 3D coordinate templates for searching structural databases. Application to enzyme active sites. Protein Sci Publ Protein Soc 1997, 6:2308-2323.
- [6]Connolly ML: Solvent-accessible surfaces of proteins and nucleic acids. Science 1983, 221:709-713.
- [7]Goldman BB, Wipke WT: QSD quadratic shape descriptors. 2. Molecular docking using quadratic shape descriptors (QSDock). Proteins 2000, 38:79-94.
- [8]Duncan BS, Olson AJ: Approximation and characterization of molecular surfaces. Biopolymers 1993, 33:219-229.
- [9]Exner TE, Keil M, Brickmann J: Pattern recognition strategies for molecular surfaces. I. Pattern generation using fuzzy set theory. J Comput Chem 2002, 23:1176-1187.
- [10]Kinoshita K, Nakamura H: Identification of protein biochemical functions by similarity search using the molecular surface database eF-site. Protein Sci Publ Protein Soc 2003, 12:1589-1595.
- [11]Rupp B, Wang J: Predictive models for protein crystallization. Methods San Diego Calif 2004, 34:390-407.
- [12]Arnold K, Bordoli L, Kopp J, Schwede T: The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling. Bioinforma Oxf Engl 2006, 22:195-201.
- [13]An J, Totrov M, Abagyan R: Comprehensive identification of “druggable” protein ligand binding sites. Genome Inform Int Conf Genome Inform 2004, 15:31-41.
- [14]Huang B, Schroeder M: LIGSITEcsc: predicting ligand binding sites using the connolly surface and degree of conservation. BMC Struct Biol 2006, 6:19.
- [15]Laskowski RA: SURFNET: a program for visualizing molecular surfaces, cavities, and intermolecular interactions. J Mol Graph 1995, 13:323-330. 307–308
- [16]Laurie ATR, Jackson RM: Q-SiteFinder: an energy-based method for the prediction of protein-ligand binding sites. Bioinforma Oxf Engl 2005, 21:1908-1916.
- [17]Liang J, Edelsbrunner H, Woodward C: Anatomy of protein pockets and cavities: measurement of binding site geometry and implications for ligand design. Protein Sci Publ Protein Soc 1998, 7:1884-1897.
- [18]Peters KP, Fauck J, Frömmel C: The automatic search for ligand binding sites in proteins of known three-dimensional structure using only geometric criteria. J Mol Biol 1996, 256:201-213.
- [19]Brady GP Jr, Stouten PF: Fast prediction and visualization of protein binding pockets with PASS. J Comput Aided Mol Des 2000, 14:383-401.
- [20]Li B, Turuvekere S, Agrawal M, La D, Ramani K, Kihara D: Characterization of local geometry of protein surfaces with the visibility criterion. Proteins 2008, 71:670-683.
- [21]Hendlich M, Rippmann F, Barnickel G: LIGSITE: automatic and efficient detection of potential small molecule-binding sites in proteins. J Mol Graph Model 1997, 15:359-363.
- [22]Levitt DG, Banaszak LJ: POCKET: a computer graphics method for identifying and displaying protein cavities and their surrounding amino acids. J Mol Graph 1992, 10:229-234.
- [23]An J, Totrov M, Abagyan R: Pocketome via comprehensive identification and classification of ligand binding envelopes. Mol Cell Proteomics MCP 2005, 4:752-761.
- [24]Coleman RG, Sharp KA: Travel depth, a new shape descriptor for macromolecules: application to ligand binding. J Mol Biol 2006, 362:441-458.
- [25]Kleywegt GJ, Jones TA: Detection, delineation, measurement and display of cavities in macromolecular structures. Acta Crystallogr D Biol Crystallogr 1994, 50(Pt 2):178-185.
- [26]Ho CM, Marshall GR: Cavity search: an algorithm for the isolation and display of cavity-like binding regions. J Comput Aided Mol Des 1990, 4:337-354.
- [27]Dennis S, Kortvelyesi T, Vajda S: Computational mapping identifies the binding sites of organic solvents on proteins. Proc Natl Acad Sci U S A 2002, 99:4290-4295.
- [28]Kortvelyesi T, Silberstein M, Dennis S, Vajda S: Improved mapping of protein binding sites. J Comput Aided Mol Des 2003, 17:173-186.
- [29]Ruppert J, Welch W, Jain AN: Automatic identification and representation of protein binding sites for molecular docking. Protein Sci Publ Protein Soc 1997, 6:524-533.
- [30]Verdonk ML, Cole JC, Watson P, Gillet V, Willett P: SuperStar: improved knowledge-based interaction fields for protein binding sites. J Mol Biol 2001, 307:841-859.
- [31]Bliznyuk AA, Gready JE: Simple method for locating possible ligand binding sites on protein surfaces. J Comput Chem 1999, 20:983-988.
- [32]Campbell SJ, Gold ND, Jackson RM, Westhead DR: Ligand binding: functional site location, similarity and docking. Curr Opin Struct Biol 2003, 13:389-395.
- [33]Glick M, Robinson DD, Grant GH, Richards WG: Identification of ligand binding sites on proteins using a multi-scale approach. J Am Chem Soc 2002, 124:2337-2344.
- [34]Sotriffer C, Klebe G: Identification and mapping of small-molecule binding sites in proteins: computational tools for structure-based drug design. Farm Soc Chim Ital 1989 2002, 57:243-251.
- [35]Andricopulo AD, Salum LB, Abraham DJ: Structure-based drug design strategies in medicinal chemistry. Curr Top Med Chem 2009, 9:771-790.
- [36]Waszkowycz B, Clark DE, Gancia E: Outstanding challenges in protein-ligand docking and structure-based virtual screening. Wiley Interdiscip Rev Comput Mol Sci 2011, 1:229-259.
- [37]Cavasotto CN, Orry AJW: Ligand docking and structure-based virtual screening in drug discovery. Curr Top Med Chem 2007, 7:1006-1014.
- [38]Des Jarlais RL, Cummings MD, Gibbs AC: Virtual docking: how are we doing and how can we improve? Front Drug Des Discov Struct-Based Drug Des 21st Century 2007, 3:81-103.
- [39]Moitessier N, Englebienne P, Lee D, Lawandi J, Corbeil CR: Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go. Br J Pharmacol 2008, 153(Suppl 1):S7-S26.
- [40]Kontoyianni M, Madhav P, Suchanek E, Seibel W: Theoretical and practical considerations in virtual screening: a beaten field? Curr Med Chem 2008, 15:107-116.
- [41]Tuccinardi T: Docking-based virtual screening: recent developments. Comb Chem High Throughput Screen 2009, 12:303-314.
- [42]Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ: Basic local alignment search tool. J Mol Biol 1990, 215:403-410.
- [43]Pearson WR: Rapid and sensitive sequence comparison with FASTP and FASTA. Methods Enzymol 1990, 183:63-98.
- [44]Altschul SF, Madden TL, Schäffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ: Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 1997, 25:3389-3402.
- [45]Söding J, Biegert A, Lupas AN: The HHpred interactive server for protein homology detection and structure prediction. Nucleic Acids Res 2005, 33(Web Server issue):W244-W248.
- [46]Zhang Y: Template-based modeling and free modeling by I-TASSER in CASP7. Proteins 2007, 69(Suppl 8):108-117.
- [47]Roy A, Kucukural A, Zhang Y: I-TASSER: a unified platform for automated protein structure and function prediction. Nat Protoc 2010, 5:725-738.
- [48]Liu TW, Tang G, Capriotti E: Comparative modeling: the state of the art and protein drug target structure prediction. Comb Chem High Throughput Screen 2011, 14:532-547.
- [49]Nelson DL, Cox MM, Lehninger AL: Principles of Biochemistry. New York: Freeman; 2004.
- [50]Murray RK: Harper’s Illustrated Biochemistry. New York: McGraw-Hill; 2003.
- [51]Markley JL, Bax A, Arata Y, Hilbers CW, Kaptein R, Sykes BD, Wright PE, Wüthrich K: Recommendations for the presentation of NMR structures of proteins and nucleic acids (IUPAC Recommendations 1998). Pure Appl Chem 1998, 70:117-142.
- [52]Atomic coordinate entry format version 3.3 http://www.wwpdb.org/documentation/format33/v3.3.html webcite