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23 <title>JABAWS Protein Disorder Prediction Services</title>
27 <strong>JABAWS Protein Disorder Prediction Services</strong> <br />
28 The <strong>Web Services→Disorder</strong> menu in the alignment
29 window allows access to protein disorder prediction services provided
30 by the configured <a href="http://www.compbio.dundee.ac.uk/jabaws">JABAWS
31 servers</a>. Each service operates on sequences in the alignment or
32 currently selected region (<em>since Jalview 2.8.0b1</em>) to identify
33 regions likely to be unstructured or flexible, or alternately, fold to
34 form globular domains.
37 Predictor results include both <a href="../features/seqfeatures.html">sequence
38 features</a> and sequence associated <a
39 href="../features/annotation.html">alignment annotation</a> rows.
40 Features display is controlled from the <a
41 href="../features/featureSettings.html">Feature Settings</a> dialog
42 box. Clicking on the ID for a disorder prediction annotation row will
43 highlight or select (if double clicked) the associated sequence for
44 that row. You can also use the <em>Sequence Associated</em> option in
45 the <a href="../colourSchemes/annotationColouring.html">Colour By
46 Annotation</a> dialog box to colour sequences according to the results of
47 predictors shown as annotation rows.
49 <p>JABAWS 2.0 provides four disorder predictors which are described
52 <li><a href="#disembl">DisEMBL</a></li>
53 <li><a href="#iupred">IUPred</a></li>
54 <li><a href="#ronn">RONN</a></li>
55 <li><a href="#globplot">GlobPlot</a></li>
58 <strong><a name="disembl"></a><a href="http://dis.embl.de/">DisEMBL
59 (Linding et al., 2003)</a> </strong> <br /> DisEMBL is a set of machine-learning
60 based predictors trained to recognise disorder-related annotation
61 found on PDB structures.
65 <td><strong>Name</strong></td>
66 <td><strong>Annotation type</strong></td>
67 <td><strong>Description</strong></td>
70 <td><strong>COILS</strong></td>
71 <td>Sequence Feature &<br />Annotation Row
73 <td>Predicts loops/coils according to DSSP definition<a
74 href="#dsspstates">[1]</a>.<br />Features mark range(s) of residues
75 predicted as loops/coils, and annotation row gives raw value for
76 each residue. Value over 0.516 indicates loop/coil.
80 <td><strong>HOTLOOPS</strong></td>
81 <td>Sequence Feature &<br />Annotation Row
83 <td>"Hot loops constitute a refined subset of <strong>COILS</strong>,
84 namely those loops with a high degree of mobility as determined from
85 Cα temperature factors (B factors). It follows that highly
86 dynamic loops should be considered protein disorder."<br />
87 Features mark range(s) of residues predicted to be hot loops and
88 annotation row gives raw value for each residue. Values over 0.6
93 <td><strong>REMARK465</strong></td>
94 <td>Sequence Feature &<br />Annotation Row
96 <td>"Missing coordinates in X-ray structure as defined by
97 remark465 entries in PDB. Nonassigned electron densities most often
98 reflect intrinsic disorder, and have been used early on in disorder
99 prediction."<br /> Features gives range(s) of residues
100 predicted as disordered, and annotation row gives raw value for each
101 residue. Value over 0.1204 indicates disorder.
107 <a name="dsspstates"></a>[1]. DSSP Classification: α-helix (H),
108 310-helix (G), β-strand (E) are ordered, and all other states
109 (β-bridge (B), β-turn (T), bend (S), π-helix (I), and
110 coil (C)) considered loops or coils.
115 <strong><a name="ronn"></a><a
116 href="http://www.strubi.ox.ac.uk/RONN">RONN</a></strong> <em>a.k.a.</em>
117 Regional Order Neural Network<br />This predictor employs an approach
118 known as the 'bio-basis' method to predict regions of disorder in
119 sequences based on their local similarity with a gold-standard set of
120 disordered protein sequences. It yields a set of disorder prediction
121 scores, which are shown as sequence annotation below the alignment.
125 <td><strong>Name</strong></td>
126 <td><strong>Annotation type</strong></td>
127 <td><strong>Description</strong></td>
130 <td><strong>JRonn</strong>[2]</td>
131 <td>Annotation Row</td>
132 <td>RONN score for each residue in the sequence. Scores above
133 0.5 identify regions of the protein likely to be disordered.</td>
137 <em>[2]. JRonn denotes the score for this server because JABAWS
138 runs a Java port of RONN developed by Peter Troshin and distributed
139 as part of <a href="http://www.biojava.org/">Biojava 3</a>
143 <strong><a name="iupred"></a><a
144 href="http://iupred.enzim.hu/Help.php">IUPred</a></strong><br /> IUPred
145 employs an empirical model to estimate likely regions of disorder.
146 There are three different prediction types offered, each using
147 different parameters optimized for slightly different applications. It
148 provides raw scores based on two models for predicting regions of
149 'long disorder' and 'short disorder'. A third predictor identifies
150 regions likely to form structured domains.
154 <td><strong>Name</strong></td>
155 <td><strong>Annotation type</strong></td>
156 <td><strong>Description</strong></td>
159 <td><strong>Long disorder</strong></td>
160 <td>Annotation Row</td>
161 <td>Prediction of context-independent global disorder that
162 encompasses at least 30 consecutive residues of predicted disorder.
163 Employs a 100 residue window for calculation.<br />Values above 0.5
164 indicates the residue is intrinsically disordered.
168 <td><strong>Short disorder</strong></td>
169 <td>Annotation Row</td>
170 <td>Predictor for short, (and probably) context-dependent,
171 disordered regions, such as missing residues in the X-ray structure
172 of an otherwise globular protein. Employs a 25 residue window for
173 calculation, and includes adjustment parameter for chain termini
174 which favors disorder prediction at the ends.<br />Values above 0.5
175 indicate short-range disorder.
179 <td><strong>Structured domains</strong></td>
180 <td>Sequence Feature</td>
181 <td>Features highlighting likely globular domains useful for
182 structure genomics investigation. <br />Post-analysis of disordered
183 region profile to find continuous regions confidently predicted to
184 be ordered. Neighbouring regions close to each other are merged,
185 while regions shorter than the minimal domain size of at least 30
186 residues are ignored.
191 <strong><a name="globplot"></a><a
192 href="http://globplot.embl.de/">GLOBPLOT</a></strong><br /> Defines regions
193 of globularity or natively unstructured regions based on a running sum
194 of the propensity of residues to be structured or unstructured. The
195 propensity is calculated based on the probability of each amino acid
196 being observed within well defined regions of secondary structure or
197 within regions of random coil. The initial signal is smoothed with a
198 Savitzky-Golay filter, and its first order derivative computed.
199 Residues for which the first order derivative is positive are
200 designated as natively unstructured, whereas those with negative
201 values are structured.<br />
204 <td><strong>Name</strong></td>
205 <td><strong>Annotation type</strong></td>
206 <td><strong>Description</strong></td>
209 <td><strong>Disordered Region</strong></td>
210 <td>Sequence Feature</td>
211 <td><br />Sequence features marking range(s) of residues with
212 positive dydx values (correspond to the #Disorder column from JABAWS
216 <td><strong>Globular Domain</strong>
217 <td>Sequence Feature</td>
218 <td>Putative globular domains</td>
221 <td><strong>Dydx</strong></td>
222 <td>Annotation row</td>
223 <td>First order derivative of smoothed score. Values above 0
224 indicates residue is disordered.</td>
227 <td><strong>Smoothed Score<br />Raw Score
229 <td>Annotation Row</td>
230 <td>The smoothed and raw scores used to create the differential
231 signal that indicates the presence of unstructured regions.<br /> <em>These
232 are hidden by default, but can be shown by right-clicking on the
233 alignment annotation panel and selecting <strong>Show
234 hidden annotation</strong>
240 <em>Documentation and thresholds for the JABAWS Disorder
241 predictors adapted from a personal communication by Nancy Giang,