Relative accessible surface area

Relative accessible surface area or relative solvent accessibility (RSA) of a protein residue is a measure of residue solvent exposure. It can be calculated by formula:

[1]

where ASA is the solvent accessible surface area and MaxASA is the maximum possible solvent accessible surface area for the residue.[1] Both ASA and MaxASA are commonly measured in .

To measure the relative solvent accessibility of the residue side-chain only, one usually takes MaxASA values that have been obtained from Gly-X-Gly tripeptides, where X is the residue of interest. Several MaxASA scales have been published[1][2][3] and are commonly used (see Table).

ResidueTien et al. 2013 (theor.)[1]Tien et al. 2013 (emp.)[1]Miller et al. 1987[2]Rose et al. 1985[3]
Alanine129.0121.0113.0118.1
Arginine274.0265.0241.0256.0
Asparagine195.0187.0158.0165.5
Aspartate193.0187.0151.0158.7
Cysteine167.0148.0140.0146.1
Glutamate223.0214.0183.0186.2
Glutamine225.0214.0189.0193.2
Glycine104.097.085.088.1
Histidine224.0216.0194.0202.5
Isoleucine197.0195.0182.0181.0
Leucine201.0191.0180.0193.1
Lysine236.0230.0211.0225.8
Methionine224.0203.0204.0203.4
Phenylalanine240.0228.0218.0222.8
Proline159.0154.0143.0146.8
Serine155.0143.0122.0129.8
Threonine172.0163.0146.0152.5
Tryptophan285.0264.0259.0266.3
Tyrosine263.0255.0229.0236.8
Valine174.0165.0160.0164.5

In this table, the more recently published MaxASA values (from Tien et al. 2013[1]) are systematically larger than the older values (from Miller et al. 1987[2] or Rose et al. 1985[3]). This discrepancy can be traced back to the conformation in which the Gly-X-Gly tripeptides are evaluated to calculate MaxASA. The earlier works used the extended conformation, with backbone angles of and .[2][3] However, Tien et al. 2013[1] demonstrated that tripeptides in extended conformation fall among the least-exposed conformations. The largest ASA values are consistently observed in alpha helices, with backbone angles around and . Tien et al. 2013 recommend to use their theoretical MaxASA values (2nd column in Table), as they were obtained from a systematic enumeration of all possible conformations and likely represent a true upper bound to observable ASA.[1]

ASA and hence RSA values are generally calculated from a protein structure, for example with the software DSSP.[4] However, there is also an extensive literature attempting to predict RSA values from sequence data, using machine-learning approaches.[5] [6]


Prediction tools

Experimentally predicting RSA is an expensive and time consuming task. In recent decades, several computational methods have been introduced for RSA prediction.[7][8][9]

References

  1. Tien, M. Z.; Meyer, A. G.; Sydykova, D. K.; Spielman, S. J.; Wilke, C. O. (2013). "Maximum allowed solvent accessibilites of residues in proteins". PLOS ONE. 8 (11): e80635. arXiv:1211.4251. Bibcode:2013PLoSO...880635T. doi:10.1371/journal.pone.0080635. PMC 3836772. PMID 24278298.
  2. Miller, S.; Janin, J.; Lesk, A. M.; Chothia, C. (1987). "Interior and surface of monomeric proteins". J. Mol. Biol. 196 (3): 641–656. doi:10.1016/0022-2836(87)90038-6. PMID 3681970.
  3. Rose, G. D.; Geselowitz, A. R.; Lesser, G. J.; Lee, R. H.; Zehfus, M. H. (1985). "Hydrophobicity of amino acid residues in globular proteins". Science. 229 (4716): 834–838. Bibcode:1985Sci...229..834R. doi:10.1126/science.4023714. PMID 4023714.
  4. Kabsch, W.; Sander, C. (1983). "Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features". Biopolymers. 22 (12): 2577–2637. doi:10.1002/bip.360221211. PMID 6667333.
  5. Hyunsoo, Kim; Haesun, Park (2003). "Prediction of Protein Relative Solvent Accessibility with Support Vector Machines and Long-range Interaction 3D Local Descriptor" (PDF). Retrieved 10 April 2015.
  6. Rost, Burkhard; Sander, Chris (1994). "Conservation and prediction of solvent accessibility in protein families". Proteins. 20 (3): 216–26. doi:10.1002/prot.340200303. PMID 7892171. Retrieved 10 April 2015.
  7. Kaleel, Manaz; Torrisi, Mirko; Mooney, Catherine; Pollastri, Gianluca (2019-09-01). "PaleAle 5.0: prediction of protein relative solvent accessibility by deep learning". Amino Acids. 51 (9): 1289–1296. doi:10.1007/s00726-019-02767-6. hdl:10197/11324. ISSN 1438-2199. PMID 31388850.
  8. Wang, Sheng; Li, Wei; Liu, Shiwang; Xu, Jinbo (2016-07-08). "RaptorX-Property: a web server for protein structure property prediction". Nucleic Acids Research. 44 (W1): W430–W435. doi:10.1093/nar/gkw306. ISSN 0305-1048. PMC 4987890. PMID 27112573.
  9. Magnan, Christophe N.; Baldi, Pierre (2014-09-15). "SSpro/ACCpro 5: almost perfect prediction of protein secondary structure and relative solvent accessibility using profiles, machine learning and structural similarity". Bioinformatics. 30 (18): 2592–2597. doi:10.1093/bioinformatics/btu352. ISSN 1367-4803. PMC 4215083. PMID 24860169.
This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.