Read CatRange predictions returned as class ranges

src/gather_kcats/readOpenKineticsPredictorOutput.m

@@ -6,6 +6,10 @@
 % constructs a kcatList structure, that can be used by assignKcatValues() to
 % populate the ecModel with kcat values.
 %
+% CatRange predicts a class of kcat values, which OKP returns as its range
+% (for instance '10 to 100 s^-1'). It is read as the geometric midpoint of
+% the range, or half the upper bound for the class starting at 0.
+%
 % The per-entry `Source kcat` column (e.g. 'Prediction from CatPred',
 % 'BRENDA', 'Sabio-RK', 'UniProt') is preserved in kcatList.kcatSource so
 % that assignKcatValues() records the actual provenance of each value.
@@ -108,7 +112,7 @@
     if isnumeric(v)
         kcats(i) = v;
     elseif ischar(v) || isstring(v)
-        kcats(i) = str2double(v);
+        kcats(i) = kcatFromText(char(v));
     end
 end
 
@@ -255,3 +259,25 @@
     end
 end
 end
+
+function kcat = kcatFromText(v)
+% A number, or a CatRange class range '<low> to <high> s^-1' as its
+% geometric midpoint (half the upper bound when the class starts at 0).
+kcat = str2double(v);
+if ~isnan(kcat)
+    return
+end
+bounds = regexp(strtrim(v), '^([0-9.eE+-]+)\s+to\s+([0-9.eE+-]+)(\s*s\^-1)?$', 'tokens', 'once');
+if isempty(bounds)
+    return
+end
+low = str2double(bounds{1});
+high = str2double(bounds{2});
+if isnan(low) || isnan(high)
+    return
+elseif low > 0
+    kcat = sqrt(low * high);
+else
+    kcat = high / 2;
+end
+end

src/gather_kcats/submitOpenKineticsPredictor.m

@@ -7,8 +7,10 @@
 % job id is also stored in data/OKP_job.txt, so fetchOpenKineticsPredictor can
 % pick it up later.
 %
-% Predictors available via OKP: CataPro, CatPred, DLKcat, EITLEM, KinForm-H,
-% KinForm-L, UniKP (see GET /api/v1/methods/).
+% Predictors available via OKP: CataPro, CatPred, CatRange, DLKcat, EITLEM,
+% KinForm-H, KinForm-L, OmniESI, OmniESI-O2DENet, TurNuP, UniKP (see GET
+% /api/v1/methods/). CatRange predicts a class of kcat values;
+% readOpenKineticsPredictorOutput uses its geometric midpoint.
 %
 % Obtaining an API key:
 %   The OKP API requires a personal Bearer key (looks like 'ak_...'). Keys

test/VerificationMatrix.tsv

@@ -15,6 +15,7 @@ gather_kcats/readDLKcatOutput.m	tcm0001, tcm0002 - The test doesn't really check
 gather_kcats/runDLKcat.m	tcm0001, tcm0002 - The test doesn't really check the function, only that we get something
 gather_kcats/assignKcatValues.m	tc0011 - we did not test all possible parameterizations here
 gather_kcats/writeDLKcatInput.m	partly by tc0011
+gather_kcats/readOpenKineticsPredictorOutput.m	tc0030, tc0069	
 gather_kcats/reviewKcatAssignment.m	Has only been tested by running it manually, not tested by test cases
 gather_kcats/ecStatsFromBrenda.m	Not verified against real BRENDA data in this environment -- see its own TODO comment
 get_enzyme_data/calculateMW.m	Not explicitly tested - The code has existed for a long time	

test/unit_tests/geckoCoreFunctionTests.m

@@ -1163,6 +1163,35 @@ function testResolveOkpApiKeyResolutionOrder_tc0029(testCase)
 end
 
 
+function testReadOpenKineticsPredictorCatRange_tc0069(testCase)
+    % CatRange's prediction is a class range ('10 to 100 s^-1'), read as its
+    % geometric midpoint, or half the upper bound for the class from 0.
+    geckoPath = findGECKOroot;
+    adapter = ModelAdapterManager.getAdapter(fullfile(geckoPath,'test','unit_tests','ecTestGEM', 'TestGEMAdapter.m'));
+    model = getGeckoTestModel();
+    ecModel = makeEcModel(model, false, adapter);
+    ecModel = getECfromGEM(ecModel);
+    ecModel.metSmiles = repmat({''}, numel(ecModel.mets), 1);
+    ecModel.metSmiles(strcmp(ecModel.mets,'m1c')) = {'C(C1C)O'};
+
+    resultFile = [tempname '.csv'];
+    fid = fopen(resultFile,'w');
+    fprintf(fid,'Predicted kcat range: kcat (1/s),Source kcat,Extra Info kcat,Protein Sequence,Substrate\n');
+    fprintf(fid,'10 to 100 s^-1,Prediction from CatRange,Predicted range: 10 to 100 s^-1,MRAL,C(C1C)O\n');
+    fclose(fid);
+    cleanupFile = onCleanup(@() delete(resultFile));
+    kcatList = readOpenKineticsPredictorOutput(ecModel, 'outFile', resultFile, 'modelAdapter', adapter);
+    verifyEqual(testCase, kcatList.kcats, 10^1.5, 'RelTol', 1e-12)
+    verifyEqual(testCase, kcatList.kcatSource, {'OKP-CatRange'})
+
+    fid = fopen(resultFile,'w');
+    fprintf(fid,'Predicted kcat range: kcat (1/s),Source kcat,Extra Info kcat,Protein Sequence,Substrate\n');
+    fprintf(fid,'0 to 1e-08 s^-1,Prediction from CatRange,,MRAL,C(C1C)O\n');
+    fclose(fid);
+    kcatList = readOpenKineticsPredictorOutput(ecModel, 'outFile', resultFile, 'modelAdapter', adapter);
+    verifyEqual(testCase, kcatList.kcats, 5e-9, 'RelTol', 1e-12)
+end
+
 function testFetchOpenKineticsPredictorUseStoredMatchesReader_tc0030(testCase)
     % Verifies fetchOpenKineticsPredictor's 'useStored' path (parsing an
     % already-downloaded result file, the only path testable without a live