Ontology type: schema:ScholarlyArticle
2012-10-11
AUTHORSAkhilesh K. Yadav, Jayprakash Thakur, Om Prakash, Feroz Khan, Dharmendra Saikia, Madan M. Gupta
ABSTRACTThe antitubercular activity of selected flavonoids and their structure–activity relationships were studied against Mycobacterium tuberculosisH37Rv strain radiometrically by BACTEC 460 assay. Present study led to the identification of five flavonoids, viz., luteolin, baicalein, quercetin, myricetin and hispidulin with MIC 25–100 μg ml−1, as new antitubercular templates. Rest flavonoids were found inactive against M. tuberculosis at a concentration of 100 μg ml−1. A possible structure–activity relationship (SAR) was also drawn to determine the specific structural requirements of flavonoids toward antitubercular activity. The hydroxyl substitution at position 5 and 7 provides no activity, whereas the hydroxyl substitutions at 5, 6, 7 (trihydroxy) or 3′, 4′ (dihydroxy) are of particular importance for antitubercular activity of a flavonoid. The O-methylation or glycosylation at any of di- or tri-hydroxyl substitutions inactivates the antitubercular potential of the flavonoids. We have also predicted the activity of studied flavonoids through QSAR model. A multiple linear regression QSAR mathematical model was developed for activity prediction that successfully and accurately (noting the corresponding experimental activities) predicted the antituberculosis activities of studied flavonoid compounds that had the basic pharmacophore, namely luteolin, baicalein, quercetin, myricetin, and hispidulin, with experimental and predicted n log MIC (μg ml−1) of 3.2189 & 2.583, 3.912 & 2.433, 3.912 & 2.433, 3.912 & 3.529, and 4.6052 & 2.703, respectively. The structure–activity relationship denoted by the QSAR model yielded a very high activity-descriptor relationship accuracy of 87 % referred by regression coefficient (r2 = 0.870533) and a high activity prediction accuracy of 81 % (rCV2 = 0.81423). These compounds may represent novel leads toward the development of pharmacologically acceptable antitubercular agent/agents. More... »
PAGES2706-2716
http://scigraph.springernature.com/pub.10.1007/s00044-012-0268-7
DOIhttp://dx.doi.org/10.1007/s00044-012-0268-7
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1047686868
JSON-LD is the canonical representation for SciGraph data.
TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT
[
{
"@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json",
"about": [
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Medical and Health Sciences",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1102",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Cardiorespiratory Medicine and Haematology",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "Analytical Chemistry Department, CSIR-Central Institute of Medicinal and Aromatic Plants, 226015, Lucknow, India",
"id": "http://www.grid.ac/institutes/grid.417631.6",
"name": [
"Analytical Chemistry Department, CSIR-Central Institute of Medicinal and Aromatic Plants, 226015, Lucknow, India"
],
"type": "Organization"
},
"familyName": "Yadav",
"givenName": "Akhilesh K.",
"id": "sg:person.0713640055.22",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0713640055.22"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Molecular Bio-Prospection Department, CSIR-Central Institute of Medicinal and Aromatic Plants, 226015, Lucknow, India",
"id": "http://www.grid.ac/institutes/grid.417631.6",
"name": [
"Molecular Bio-Prospection Department, CSIR-Central Institute of Medicinal and Aromatic Plants, 226015, Lucknow, India"
],
"type": "Organization"
},
"familyName": "Thakur",
"givenName": "Jayprakash",
"id": "sg:person.01015473463.30",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01015473463.30"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Metabolic and Structural Biology Department, CSIR-Central Institute of Medicinal and Aromatic Plants, 226015, Lucknow, India",
"id": "http://www.grid.ac/institutes/grid.417631.6",
"name": [
"Metabolic and Structural Biology Department, CSIR-Central Institute of Medicinal and Aromatic Plants, 226015, Lucknow, India"
],
"type": "Organization"
},
"familyName": "Prakash",
"givenName": "Om",
"id": "sg:person.010011077140.18",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010011077140.18"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Metabolic and Structural Biology Department, CSIR-Central Institute of Medicinal and Aromatic Plants, 226015, Lucknow, India",
"id": "http://www.grid.ac/institutes/grid.417631.6",
"name": [
"Metabolic and Structural Biology Department, CSIR-Central Institute of Medicinal and Aromatic Plants, 226015, Lucknow, India"
],
"type": "Organization"
},
"familyName": "Khan",
"givenName": "Feroz",
"id": "sg:person.01106430625.71",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01106430625.71"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Molecular Bio-Prospection Department, CSIR-Central Institute of Medicinal and Aromatic Plants, 226015, Lucknow, India",
"id": "http://www.grid.ac/institutes/grid.417631.6",
"name": [
"Molecular Bio-Prospection Department, CSIR-Central Institute of Medicinal and Aromatic Plants, 226015, Lucknow, India"
],
"type": "Organization"
},
"familyName": "Saikia",
"givenName": "Dharmendra",
"id": "sg:person.01001355751.65",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01001355751.65"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Analytical Chemistry Department, CSIR-Central Institute of Medicinal and Aromatic Plants, 226015, Lucknow, India",
"id": "http://www.grid.ac/institutes/grid.417631.6",
"name": [
"Analytical Chemistry Department, CSIR-Central Institute of Medicinal and Aromatic Plants, 226015, Lucknow, India"
],
"type": "Organization"
},
"familyName": "Gupta",
"givenName": "Madan M.",
"id": "sg:person.01242460441.07",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01242460441.07"
],
"type": "Person"
}
],
"citation": [
{
"id": "sg:pub.10.1007/s00210-004-0964-z",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1000475222",
"https://doi.org/10.1007/s00210-004-0964-z"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00894-011-1265-3",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1002126132",
"https://doi.org/10.1007/s00894-011-1265-3"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00894-011-1327-6",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1030330688",
"https://doi.org/10.1007/s00894-011-1327-6"
],
"type": "CreativeWork"
}
],
"datePublished": "2012-10-11",
"datePublishedReg": "2012-10-11",
"description": "The antitubercular activity of selected flavonoids and their structure\u2013activity relationships were studied against Mycobacterium tuberculosisH37Rv strain radiometrically by BACTEC 460 assay. Present study led to the identification of five flavonoids, viz., luteolin, baicalein, quercetin, myricetin and hispidulin with MIC 25\u2013100\u00a0\u03bcg\u00a0ml\u22121, as new antitubercular templates. Rest flavonoids were found inactive against M. tuberculosis at a concentration of 100\u00a0\u03bcg\u00a0ml\u22121. A possible structure\u2013activity relationship (SAR) was also drawn to determine the specific structural requirements of flavonoids toward antitubercular activity. The hydroxyl substitution at position 5 and 7 provides no activity, whereas the hydroxyl substitutions at 5, 6, 7 (trihydroxy) or 3\u2032, 4\u2032 (dihydroxy) are of particular importance for antitubercular activity of a flavonoid. The O-methylation or glycosylation at any of di- or tri-hydroxyl substitutions inactivates the antitubercular potential of the flavonoids. We have also predicted the activity of studied flavonoids through QSAR model. A multiple linear regression QSAR mathematical model was developed for activity prediction that successfully and accurately (noting the corresponding experimental activities) predicted the antituberculosis activities of studied flavonoid compounds that had the basic pharmacophore, namely luteolin, baicalein, quercetin, myricetin, and hispidulin, with experimental and predicted n\u00a0log\u00a0MIC (\u03bcg\u00a0ml\u22121) of 3.2189 & 2.583, 3.912 & 2.433, 3.912 & 2.433, 3.912 & 3.529, and 4.6052 & 2.703, respectively. The structure\u2013activity relationship denoted by the QSAR model yielded a very high activity-descriptor relationship accuracy of 87\u00a0% referred by regression coefficient (r2\u00a0=\u00a00.870533) and a high activity prediction accuracy of 81\u00a0% (rCV2\u00a0=\u00a00.81423). These compounds may represent novel leads toward the development of pharmacologically acceptable antitubercular agent/agents.",
"genre": "article",
"id": "sg:pub.10.1007/s00044-012-0268-7",
"inLanguage": "en",
"isAccessibleForFree": false,
"isPartOf": [
{
"id": "sg:journal.1102690",
"issn": [
"1054-2523",
"1554-8120"
],
"name": "Medicinal Chemistry Research",
"publisher": "Springer Nature",
"type": "Periodical"
},
{
"issueNumber": "6",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "22"
}
],
"keywords": [
"mathematical model",
"regression coefficients",
"QSAR models",
"prediction accuracy",
"multiple linear regression",
"model",
"linear regression",
"accuracy",
"particular importance",
"activity prediction",
"coefficient",
"prediction",
"basic pharmacophore",
"regression",
"requirements",
"logs",
"viz",
"substitution",
"lead",
"identification",
"potential",
"relationship",
"importance",
"antitubercular potential",
"template",
"structure-activity relationships",
"development",
"study",
"compounds",
"concentration",
"BACTEC 460",
"strains",
"present study",
"possible structure-activity relationships",
"structural requirements",
"specific structural requirements",
"antituberculosis activity",
"hydroxyl substitution",
"agents",
"activity",
"hispidulin",
"flavonoids",
"quercetin",
"glycosylation",
"antitubercular activity",
"myricetin",
"luteolin",
"position 5",
"flavonoid compounds",
"MIC",
"baicalein",
"methylation",
"novel leads",
"pharmacophore",
"tuberculosis"
],
"name": "Screening of flavonoids for antitubercular activity and their structure\u2013activity relationships",
"pagination": "2706-2716",
"productId": [
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1047686868"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/s00044-012-0268-7"
]
}
],
"sameAs": [
"https://doi.org/10.1007/s00044-012-0268-7",
"https://app.dimensions.ai/details/publication/pub.1047686868"
],
"sdDataset": "articles",
"sdDatePublished": "2022-05-20T07:27",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-springernature-scigraph/baseset/20220519/entities/gbq_results/article/article_576.jsonl",
"type": "ScholarlyArticle",
"url": "https://doi.org/10.1007/s00044-012-0268-7"
}
]
Download the RDF metadata as: json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s00044-012-0268-7'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s00044-012-0268-7'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00044-012-0268-7'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00044-012-0268-7'
This table displays all metadata directly associated to this object as RDF triples.
164 TRIPLES
22 PREDICATES
83 URIs
72 LITERALS
6 BLANK NODES
Subject | Predicate | Object | |
---|---|---|---|
1 | sg:pub.10.1007/s00044-012-0268-7 | schema:about | anzsrc-for:11 |
2 | ″ | ″ | anzsrc-for:1102 |
3 | ″ | schema:author | Na73cc1dc481348dca5e773878115bbd6 |
4 | ″ | schema:citation | sg:pub.10.1007/s00210-004-0964-z |
5 | ″ | ″ | sg:pub.10.1007/s00894-011-1265-3 |
6 | ″ | ″ | sg:pub.10.1007/s00894-011-1327-6 |
7 | ″ | schema:datePublished | 2012-10-11 |
8 | ″ | schema:datePublishedReg | 2012-10-11 |
9 | ″ | schema:description | The antitubercular activity of selected flavonoids and their structure–activity relationships were studied against Mycobacterium tuberculosisH37Rv strain radiometrically by BACTEC 460 assay. Present study led to the identification of five flavonoids, viz., luteolin, baicalein, quercetin, myricetin and hispidulin with MIC 25–100 μg ml−1, as new antitubercular templates. Rest flavonoids were found inactive against M. tuberculosis at a concentration of 100 μg ml−1. A possible structure–activity relationship (SAR) was also drawn to determine the specific structural requirements of flavonoids toward antitubercular activity. The hydroxyl substitution at position 5 and 7 provides no activity, whereas the hydroxyl substitutions at 5, 6, 7 (trihydroxy) or 3′, 4′ (dihydroxy) are of particular importance for antitubercular activity of a flavonoid. The O-methylation or glycosylation at any of di- or tri-hydroxyl substitutions inactivates the antitubercular potential of the flavonoids. We have also predicted the activity of studied flavonoids through QSAR model. A multiple linear regression QSAR mathematical model was developed for activity prediction that successfully and accurately (noting the corresponding experimental activities) predicted the antituberculosis activities of studied flavonoid compounds that had the basic pharmacophore, namely luteolin, baicalein, quercetin, myricetin, and hispidulin, with experimental and predicted n log MIC (μg ml−1) of 3.2189 & 2.583, 3.912 & 2.433, 3.912 & 2.433, 3.912 & 3.529, and 4.6052 & 2.703, respectively. The structure–activity relationship denoted by the QSAR model yielded a very high activity-descriptor relationship accuracy of 87 % referred by regression coefficient (r2 = 0.870533) and a high activity prediction accuracy of 81 % (rCV2 = 0.81423). These compounds may represent novel leads toward the development of pharmacologically acceptable antitubercular agent/agents. |
10 | ″ | schema:genre | article |
11 | ″ | schema:inLanguage | en |
12 | ″ | schema:isAccessibleForFree | false |
13 | ″ | schema:isPartOf | N29a21ec26ef144ad84faefa84cca79ef |
14 | ″ | ″ | N417b194f675248408866b796fb465907 |
15 | ″ | ″ | sg:journal.1102690 |
16 | ″ | schema:keywords | BACTEC 460 |
17 | ″ | ″ | MIC |
18 | ″ | ″ | QSAR models |
19 | ″ | ″ | accuracy |
20 | ″ | ″ | activity |
21 | ″ | ″ | activity prediction |
22 | ″ | ″ | agents |
23 | ″ | ″ | antitubercular activity |
24 | ″ | ″ | antitubercular potential |
25 | ″ | ″ | antituberculosis activity |
26 | ″ | ″ | baicalein |
27 | ″ | ″ | basic pharmacophore |
28 | ″ | ″ | coefficient |
29 | ″ | ″ | compounds |
30 | ″ | ″ | concentration |
31 | ″ | ″ | development |
32 | ″ | ″ | flavonoid compounds |
33 | ″ | ″ | flavonoids |
34 | ″ | ″ | glycosylation |
35 | ″ | ″ | hispidulin |
36 | ″ | ″ | hydroxyl substitution |
37 | ″ | ″ | identification |
38 | ″ | ″ | importance |
39 | ″ | ″ | lead |
40 | ″ | ″ | linear regression |
41 | ″ | ″ | logs |
42 | ″ | ″ | luteolin |
43 | ″ | ″ | mathematical model |
44 | ″ | ″ | methylation |
45 | ″ | ″ | model |
46 | ″ | ″ | multiple linear regression |
47 | ″ | ″ | myricetin |
48 | ″ | ″ | novel leads |
49 | ″ | ″ | particular importance |
50 | ″ | ″ | pharmacophore |
51 | ″ | ″ | position 5 |
52 | ″ | ″ | possible structure-activity relationships |
53 | ″ | ″ | potential |
54 | ″ | ″ | prediction |
55 | ″ | ″ | prediction accuracy |
56 | ″ | ″ | present study |
57 | ″ | ″ | quercetin |
58 | ″ | ″ | regression |
59 | ″ | ″ | regression coefficients |
60 | ″ | ″ | relationship |
61 | ″ | ″ | requirements |
62 | ″ | ″ | specific structural requirements |
63 | ″ | ″ | strains |
64 | ″ | ″ | structural requirements |
65 | ″ | ″ | structure-activity relationships |
66 | ″ | ″ | study |
67 | ″ | ″ | substitution |
68 | ″ | ″ | template |
69 | ″ | ″ | tuberculosis |
70 | ″ | ″ | viz |
71 | ″ | schema:name | Screening of flavonoids for antitubercular activity and their structure–activity relationships |
72 | ″ | schema:pagination | 2706-2716 |
73 | ″ | schema:productId | N4bd430b424ab4c6f91946f5ee9d23446 |
74 | ″ | ″ | N9681036a33ed412fb452d51963b8fe00 |
75 | ″ | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1047686868 |
76 | ″ | ″ | https://doi.org/10.1007/s00044-012-0268-7 |
77 | ″ | schema:sdDatePublished | 2022-05-20T07:27 |
78 | ″ | schema:sdLicense | https://scigraph.springernature.com/explorer/license/ |
79 | ″ | schema:sdPublisher | N9183e940edbe47e9b296939b7d342847 |
80 | ″ | schema:url | https://doi.org/10.1007/s00044-012-0268-7 |
81 | ″ | sgo:license | sg:explorer/license/ |
82 | ″ | sgo:sdDataset | articles |
83 | ″ | rdf:type | schema:ScholarlyArticle |
84 | N29a21ec26ef144ad84faefa84cca79ef | schema:issueNumber | 6 |
85 | ″ | rdf:type | schema:PublicationIssue |
86 | N417b194f675248408866b796fb465907 | schema:volumeNumber | 22 |
87 | ″ | rdf:type | schema:PublicationVolume |
88 | N4bd430b424ab4c6f91946f5ee9d23446 | schema:name | doi |
89 | ″ | schema:value | 10.1007/s00044-012-0268-7 |
90 | ″ | rdf:type | schema:PropertyValue |
91 | N9183e940edbe47e9b296939b7d342847 | schema:name | Springer Nature - SN SciGraph project |
92 | ″ | rdf:type | schema:Organization |
93 | N9681036a33ed412fb452d51963b8fe00 | schema:name | dimensions_id |
94 | ″ | schema:value | pub.1047686868 |
95 | ″ | rdf:type | schema:PropertyValue |
96 | Na73cc1dc481348dca5e773878115bbd6 | rdf:first | sg:person.0713640055.22 |
97 | ″ | rdf:rest | Nb162e6e27be7412e9e694a11538323f8 |
98 | Nb162e6e27be7412e9e694a11538323f8 | rdf:first | sg:person.01015473463.30 |
99 | ″ | rdf:rest | Ne79e9d35b5f345d79d9806277749d7a7 |
100 | Ne79e9d35b5f345d79d9806277749d7a7 | rdf:first | sg:person.010011077140.18 |
101 | ″ | rdf:rest | Nf4d6964fd58f4c73a0dfd6baf56254d4 |
102 | Nf0050a590c7243b496214e8151a6ff69 | rdf:first | sg:person.01242460441.07 |
103 | ″ | rdf:rest | rdf:nil |
104 | Nf4d6964fd58f4c73a0dfd6baf56254d4 | rdf:first | sg:person.01106430625.71 |
105 | ″ | rdf:rest | Nfd8cdd815f374d6ca1b03e9360f2f356 |
106 | Nfd8cdd815f374d6ca1b03e9360f2f356 | rdf:first | sg:person.01001355751.65 |
107 | ″ | rdf:rest | Nf0050a590c7243b496214e8151a6ff69 |
108 | anzsrc-for:11 | schema:inDefinedTermSet | anzsrc-for: |
109 | ″ | schema:name | Medical and Health Sciences |
110 | ″ | rdf:type | schema:DefinedTerm |
111 | anzsrc-for:1102 | schema:inDefinedTermSet | anzsrc-for: |
112 | ″ | schema:name | Cardiorespiratory Medicine and Haematology |
113 | ″ | rdf:type | schema:DefinedTerm |
114 | sg:journal.1102690 | schema:issn | 1054-2523 |
115 | ″ | ″ | 1554-8120 |
116 | ″ | schema:name | Medicinal Chemistry Research |
117 | ″ | schema:publisher | Springer Nature |
118 | ″ | rdf:type | schema:Periodical |
119 | sg:person.010011077140.18 | schema:affiliation | grid-institutes:grid.417631.6 |
120 | ″ | schema:familyName | Prakash |
121 | ″ | schema:givenName | Om |
122 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010011077140.18 |
123 | ″ | rdf:type | schema:Person |
124 | sg:person.01001355751.65 | schema:affiliation | grid-institutes:grid.417631.6 |
125 | ″ | schema:familyName | Saikia |
126 | ″ | schema:givenName | Dharmendra |
127 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01001355751.65 |
128 | ″ | rdf:type | schema:Person |
129 | sg:person.01015473463.30 | schema:affiliation | grid-institutes:grid.417631.6 |
130 | ″ | schema:familyName | Thakur |
131 | ″ | schema:givenName | Jayprakash |
132 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01015473463.30 |
133 | ″ | rdf:type | schema:Person |
134 | sg:person.01106430625.71 | schema:affiliation | grid-institutes:grid.417631.6 |
135 | ″ | schema:familyName | Khan |
136 | ″ | schema:givenName | Feroz |
137 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01106430625.71 |
138 | ″ | rdf:type | schema:Person |
139 | sg:person.01242460441.07 | schema:affiliation | grid-institutes:grid.417631.6 |
140 | ″ | schema:familyName | Gupta |
141 | ″ | schema:givenName | Madan M. |
142 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01242460441.07 |
143 | ″ | rdf:type | schema:Person |
144 | sg:person.0713640055.22 | schema:affiliation | grid-institutes:grid.417631.6 |
145 | ″ | schema:familyName | Yadav |
146 | ″ | schema:givenName | Akhilesh K. |
147 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0713640055.22 |
148 | ″ | rdf:type | schema:Person |
149 | sg:pub.10.1007/s00210-004-0964-z | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1000475222 |
150 | ″ | ″ | https://doi.org/10.1007/s00210-004-0964-z |
151 | ″ | rdf:type | schema:CreativeWork |
152 | sg:pub.10.1007/s00894-011-1265-3 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1002126132 |
153 | ″ | ″ | https://doi.org/10.1007/s00894-011-1265-3 |
154 | ″ | rdf:type | schema:CreativeWork |
155 | sg:pub.10.1007/s00894-011-1327-6 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1030330688 |
156 | ″ | ″ | https://doi.org/10.1007/s00894-011-1327-6 |
157 | ″ | rdf:type | schema:CreativeWork |
158 | grid-institutes:grid.417631.6 | schema:alternateName | Analytical Chemistry Department, CSIR-Central Institute of Medicinal and Aromatic Plants, 226015, Lucknow, India |
159 | ″ | ″ | Metabolic and Structural Biology Department, CSIR-Central Institute of Medicinal and Aromatic Plants, 226015, Lucknow, India |
160 | ″ | ″ | Molecular Bio-Prospection Department, CSIR-Central Institute of Medicinal and Aromatic Plants, 226015, Lucknow, India |
161 | ″ | schema:name | Analytical Chemistry Department, CSIR-Central Institute of Medicinal and Aromatic Plants, 226015, Lucknow, India |
162 | ″ | ″ | Metabolic and Structural Biology Department, CSIR-Central Institute of Medicinal and Aromatic Plants, 226015, Lucknow, India |
163 | ″ | ″ | Molecular Bio-Prospection Department, CSIR-Central Institute of Medicinal and Aromatic Plants, 226015, Lucknow, India |
164 | ″ | rdf:type | schema:Organization |