molstar
Version:
A comprehensive macromolecular library.
140 lines (139 loc) • 6.83 kB
JavaScript
;
/**
* Copyright (c) 2018-2020 mol* contributors, licensed under MIT, See LICENSE file for more info.
*
* @author Michal Malý <michal.maly@ibt.cas.cz>
* @author Jiří Černý <jiri.cerny@ibt.cas.cz>
*/
Object.defineProperty(exports, "__esModule", { value: true });
exports.Dnatco = exports.DnatcoParams = void 0;
const db_1 = require("../../mol-data/db");
const schema_1 = require("../../mol-io/reader/cif/schema");
const wrapper_1 = require("../../mol-model-props/common/wrapper");
const mmcif_1 = require("../../mol-model-formats/structure/mmcif");
exports.DnatcoParams = {};
var Dnatco;
(function (Dnatco) {
Dnatco.Schema = {
ndb_struct_ntc_step: {
id: db_1.Column.Schema.int,
name: db_1.Column.Schema.str,
PDB_model_number: db_1.Column.Schema.int,
label_entity_id_1: db_1.Column.Schema.int,
label_asym_id_1: db_1.Column.Schema.str,
label_seq_id_1: db_1.Column.Schema.int,
label_comp_id_1: db_1.Column.Schema.str,
label_alt_id_1: db_1.Column.Schema.str,
label_entity_id_2: db_1.Column.Schema.int,
label_asym_id_2: db_1.Column.Schema.str,
label_seq_id_2: db_1.Column.Schema.int,
label_comp_id_2: db_1.Column.Schema.str,
label_alt_id_2: db_1.Column.Schema.str,
auth_asym_id_1: db_1.Column.Schema.str,
auth_seq_id_1: db_1.Column.Schema.int,
auth_asym_id_2: db_1.Column.Schema.str,
auth_seq_id_2: db_1.Column.Schema.int,
PDB_ins_code_1: db_1.Column.Schema.str,
PDB_ins_code_2: db_1.Column.Schema.str,
},
ndb_struct_ntc_step_summary: {
step_id: db_1.Column.Schema.int,
assigned_CANA: db_1.Column.Schema.str,
assigned_NtC: db_1.Column.Schema.str,
confal_score: db_1.Column.Schema.int,
euclidean_distance_NtC_ideal: db_1.Column.Schema.float,
cartesian_rmsd_closest_NtC_representative: db_1.Column.Schema.float,
closest_CANA: db_1.Column.Schema.str,
closest_NtC: db_1.Column.Schema.str,
closest_step_golden: db_1.Column.Schema.str
}
};
function getStepsFromCif(model, cifSteps, stepsSummary) {
var _a, _b;
const steps = new Array();
const mapping = new Array();
const { id, PDB_model_number, name, auth_asym_id_1, auth_seq_id_1, label_comp_id_1, label_alt_id_1, PDB_ins_code_1, auth_asym_id_2, auth_seq_id_2, label_comp_id_2, label_alt_id_2, PDB_ins_code_2, _rowCount } = cifSteps;
if (_rowCount !== stepsSummary._rowCount)
throw new Error('Inconsistent mmCIF data');
for (let i = 0; i < _rowCount; i++) {
const { NtC, confal_score, rmsd } = getSummaryData(id.value(i), i, stepsSummary);
const modelNum = PDB_model_number.value(i);
const chainId = auth_asym_id_1.value(i);
const seqId = auth_seq_id_1.value(i);
const modelIdx = modelNum - 1;
if (mapping.length <= modelIdx || !mapping[modelIdx])
mapping[modelIdx] = new Map();
const step = {
PDB_model_number: modelNum,
name: name.value(i),
auth_asym_id_1: chainId,
auth_seq_id_1: seqId,
label_comp_id_1: label_comp_id_1.value(i),
label_alt_id_1: label_alt_id_1.value(i),
PDB_ins_code_1: PDB_ins_code_1.value(i),
auth_asym_id_2: auth_asym_id_2.value(i),
auth_seq_id_2: auth_seq_id_2.value(i),
label_comp_id_2: label_comp_id_2.value(i),
label_alt_id_2: label_alt_id_2.value(i),
PDB_ins_code_2: PDB_ins_code_2.value(i),
confal_score,
NtC,
rmsd,
};
steps.push(step);
const mappedChains = mapping[modelIdx];
const residuesOnChain = (_a = mappedChains.get(chainId)) !== null && _a !== void 0 ? _a : new Map();
const stepsForResidue = (_b = residuesOnChain.get(seqId)) !== null && _b !== void 0 ? _b : [];
stepsForResidue.push(steps.length - 1);
residuesOnChain.set(seqId, stepsForResidue);
mappedChains.set(chainId, residuesOnChain);
mapping[modelIdx] = mappedChains;
}
return { steps, mapping };
}
Dnatco.getStepsFromCif = getStepsFromCif;
async function fromCif(ctx, model, props) {
const info = wrapper_1.PropertyWrapper.createInfo();
const data = getCifData(model);
if (data === undefined)
return { value: { info, data: undefined } };
const fromCif = getStepsFromCif(model, data.steps, data.stepsSummary);
return { value: { info, data: fromCif } };
}
Dnatco.fromCif = fromCif;
function getCifData(model) {
if (!mmcif_1.MmcifFormat.is(model.sourceData))
throw new Error('Data format must be mmCIF');
if (!hasNdbStructNtcCategories(model))
return undefined;
return {
steps: (0, schema_1.toTable)(Dnatco.Schema.ndb_struct_ntc_step, model.sourceData.data.frame.categories.ndb_struct_ntc_step),
stepsSummary: (0, schema_1.toTable)(Dnatco.Schema.ndb_struct_ntc_step_summary, model.sourceData.data.frame.categories.ndb_struct_ntc_step_summary)
};
}
Dnatco.getCifData = getCifData;
function hasNdbStructNtcCategories(model) {
if (!mmcif_1.MmcifFormat.is(model.sourceData))
return false;
const names = (model.sourceData).data.frame.categoryNames;
return names.includes('ndb_struct_ntc_step') && names.includes('ndb_struct_ntc_step_summary');
}
function isApplicable(model) {
return !!model && hasNdbStructNtcCategories(model);
}
Dnatco.isApplicable = isApplicable;
})(Dnatco || (exports.Dnatco = Dnatco = {}));
function getSummaryData(id, i, stepsSummary) {
const { step_id, confal_score, assigned_NtC, cartesian_rmsd_closest_NtC_representative, } = stepsSummary;
// Assume that step_ids in ntc_step_summary are in the same order as steps in ntc_step
for (let j = i; j < stepsSummary._rowCount; j++) {
if (id === step_id.value(j))
return { NtC: assigned_NtC.value(j), confal_score: confal_score.value(j), rmsd: cartesian_rmsd_closest_NtC_representative.value(j) };
}
// Safety net for cases where the previous assumption is not met
for (let j = 0; j < i; j++) {
if (id === step_id.value(j))
return { NtC: assigned_NtC.value(j), confal_score: confal_score.value(j), rmsd: cartesian_rmsd_closest_NtC_representative.value(j) };
}
throw new Error('Inconsistent mmCIF data');
}