View source for Physics:Relative accessible surface area

'''Relative accessible surface area''' or '''relative solvent accessibility (RSA)''' of a protein residue is a measure of [[Chemistry:Solvent exposure|residue solvent exposure]]. It can be calculated by formula:
<math> \text{RSA} = \text{ASA} / \text{MaxASA} </math> 
<ref name = "Tien_etal2013">
 {{cite journal
   | last1 = Tien | first1 = M. Z.
   | last2 = Meyer | first2 = A. G. 
   | last3 = Sydykova | first3 = D. K.
   | last4 = Spielman | first4 = S. J.
   | last5 = Wilke | first5 = C. O.
   | date = 2013
   | title = Maximum allowed solvent accessibilites of residues in proteins
   | journal = PLOS ONE
   | volume = 8
   | number = 11
   | pages = e80635
   | doi = 10.1371/journal.pone.0080635| pmid = 24278298 | pmc=3836772
   | bibcode = 2013PLoSO...880635T
 | arxiv = 1211.4251
 | doi-access = free
 }}
</ref>

where ASA is the [[Physics:Accessible surface area|solvent accessible surface area]] and MaxASA is the maximum possible [[Physics:Accessible surface area|solvent accessible surface area]] for the residue.<ref name="Tien_etal2013" />  Both ASA and MaxASA are commonly measured in <math> {\AA}^2 </math>.

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<ref name="Tien_etal2013" /><ref name="Miller_etal1987">
 {{cite journal
   | last1 = Miller | first1 = S.
   | last2 = Janin | first2 = J.
   | last3 = Lesk | first3 = A. M.
   | last4 = Chothia | first4 = C.
   | date = 1987
   | title = Interior and surface of monomeric proteins
   | journal = J. Mol. Biol.
   | volume = 196
   | issue = 3
 | pages = 641–656 | doi=10.1016/0022-2836(87)90038-6| pmid = 3681970
 }}
</ref><ref name="Rose_etal1985">
 {{ cite journal
   | last1 = Rose | first1 = G. D.
   | last2 = Geselowitz | first2 = A. R.
   | last3 = Lesser | first3 = G. J.
   | last4 = Lee | first4 = R. H.
   | last5 = Zehfus | first5 = M. H.
   | date = 1985
   | title = Hydrophobicity of amino acid residues in globular proteins
   | journal = Science
   | volume = 229
   | issue = 4716
 | pages = 834–838 | doi=10.1126/science.4023714| pmid = 4023714
 | bibcode = 1985Sci...229..834R
 | s2cid = 22227053
 }}
</ref>
and are commonly used (see Table).

{| class="wikitable sortable"
|-
! Residue !! Tien et al. 2013 (theor.)<ref name="Tien_etal2013" /> !! Tien et al. 2013 (emp.)<ref name="Tien_etal2013" /> !!  Miller et al. 1987<ref name="Miller_etal1987" /> !! Rose et al. 1985<ref name="Rose_etal1985" />
|-
| Alanine || 129.0 || 121.0 || 113.0 || 118.1
|-
| Arginine  || 274.0 || 265.0 || 241.0 || 256.0
|-
| Asparagine    || 195.0 || 187.0 || 158.0 || 165.5
|-
| Aspartate      || 193.0 || 187.0 || 151.0 || 158.7 
|-
| Cysteine        || 167.0 || 148.0 || 140.0 || 146.1
|-
| Glutamate     || 223.0 || 214.0 || 183.0 || 186.2
|-
| Glutamine      || 225.0 || 214.0 || 189.0 || 193.2 
|-
| Glycine          || 104.0 || 97.0 || 85.0 || 88.1 
|-
| Histidine        || 224.0 || 216.0 || 194.0 || 202.5 
|-
| Isoleucine     || 197.0 || 195.0 || 182.0 || 181.0
|-
| Leucine         || 201.0 || 191.0 || 180.0 || 193.1 
|-
| Lysine           || 236.0 || 230.0 || 211.0 || 225.8 
|-
| Methionine   || 224.0 || 203.0 || 204.0 || 203.4 
|-
| Phenylalanine  || 240.0 || 228.0 || 218.0 || 222.8 
|-
| Proline || 159.0 || 154.0|| 143.0 || 146.8 
|-
| Serine          || 155.0 || 143.0 || 122.0 || 129.8 
|-
| Threonine          || 172.0 || 163.0 || 146.0 || 152.5 
|-
| Tryptophan          || 285.0 || 264.0 || 259.0 || 266.3 
|-
| Tyrosine          || 263.0 || 255.0 || 229.0 || 236.8
|-
| Valine          || 174.0 || 165.0 || 160.0 || 164.5 
|}

In this table, the more recently published MaxASA values (from Tien et al. 2013<ref name="Tien_etal2013" />) are systematically larger than the older values (from Miller et al. 1987<ref name="Miller_etal1987" /> or Rose et al. 1985<ref name="Rose_etal1985" />). 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 [[Biology:Ramachandran plot|backbone angles]] of <math>\phi=-120^\circ</math> and <math>\psi=140^\circ</math>.<ref name="Miller_etal1987" /><ref name="Rose_etal1985" /> However, Tien et al. 2013<ref name="Tien_etal2013" /> 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 <math>\phi=-50^\circ</math> and <math>\psi=-45^\circ</math>. 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.<ref name="Tien_etal2013" />

ASA and hence RSA values are generally calculated from a protein structure, for example with the software DSSP.<ref name = "DSSP">
 {{cite journal
   | last1 = Kabsch | first1 = W.
   | last2 = Sander | first2 = C.
   | date = 1983
   | title = Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features
   | journal = Biopolymers
   | volume = 22
   | issue = 12
 | pages = 2577–2637
   | doi=10.1002/bip.360221211
   | pmid=6667333| s2cid = 29185760
 }}
</ref> However, there is also an extensive literature attempting to predict RSA values from sequence data, using machine-learning approaches.<ref name = "KimPark2003">
  {{cite web 
    | url = http://www.cc.gatech.edu/~hpark/papers/surface.pdf 
    | title = Prediction of Protein Relative Solvent Accessibility with Support Vector Machines and Long-range Interaction 3D Local Descriptor
    | date = 2003
    | accessdate = 10 April 2015
    | last1 = Hyunsoo | first1 = Kim
<ref name="RostSander1994">
 {{cite journal
   | last1 = Rost | first1 = Burkhard
   | last2 = Sander | first2 = Chris
   | title = Conservation and prediction of solvent accessibility in protein families
   | journal = Proteins
   | date = 1994
   | volume = 20
   | issue = 3
   | pages = 216–26
   | pmid = 7892171
   | url = https://www.researchgate.net/publication/15307400
   | accessdate = 10 April 2015
   | doi = 10.1002/prot.340200303| s2cid = 19285647
 }}</ref>

== Prediction tools ==
Experimentally predicting RSA is an expensive and time-consuming task. In recent decades, several computational methods have been introduced for RSA prediction.<ref>{{Cite journal|last1=Kaleel|first1=Manaz|last2=Torrisi|first2=Mirko|last3=Mooney|first3=Catherine|last4=Pollastri|first4=Gianluca|date=2019-09-01|title=PaleAle 5.0: prediction of protein relative solvent accessibility by deep learning|journal=Amino Acids|language=en|volume=51|issue=9|pages=1289–1296|doi=10.1007/s00726-019-02767-6|pmid=31388850|issn=1438-2199|hdl=10197/11324|s2cid=199469523|hdl-access=free}}</ref><ref>{{Cite journal|last1=Wang|first1=Sheng|last2=Li|first2=Wei|last3=Liu|first3=Shiwang|last4=Xu|first4=Jinbo|date=2016-07-08|title=RaptorX-Property: a web server for protein structure property prediction|url= |journal=Nucleic Acids Research|language=en|volume=44|issue=W1|pages=W430–W435|doi=10.1093/nar/gkw306|pmid=27112573|pmc=4987890|issn=0305-1048}}</ref><ref>{{Cite journal|last1=Magnan|first1=Christophe N.|last2=Baldi|first2=Pierre|date=2014-09-15|title=SSpro/ACCpro 5: almost perfect prediction of protein secondary structure and relative solvent accessibility using profiles, machine learning and structural similarity|url= |journal=Bioinformatics|language=en|volume=30|issue=18|pages=2592–2597|doi=10.1093/bioinformatics/btu352|pmid=24860169|pmc=4215083|issn=1367-4803}}</ref>

== References ==
{{Reflist}}

[[Category:Molecular modelling]]
[[Category:Protein structure]]

{{Sourceattribution|Relative accessible surface area}}