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Combining empirical knowledge, in silico molecular docking and ADMET profiling to identify therapeut...

Combining empirical knowledge, in silico molecular docking and ADMET profiling to identify therapeut...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_2695455558

Combining empirical knowledge, in silico molecular docking and ADMET profiling to identify therapeutic phytochemicals from Brucea antidysentrica for acute myeloid leukemia

About this item

Full title

Combining empirical knowledge, in silico molecular docking and ADMET profiling to identify therapeutic phytochemicals from Brucea antidysentrica for acute myeloid leukemia

Publisher

San Francisco: Public Library of Science

Journal title

PloS one, 2022-07, Vol.17 (7), p.e0270050-e0270050

Language

English

Formats

Publication information

Publisher

San Francisco: Public Library of Science

More information

Scope and Contents

Contents

Acute myeloid leukemia (AML) is one of the deadly cancers. Chemotherapy is the first-line treatment and the only curative intervention is stem cell transplantation which are intolerable for aged and comorbid patients. Therefore, finding complementary treatment is still an active research area. For this, empirical knowledge driven search for therape...

Alternative Titles

Full title

Combining empirical knowledge, in silico molecular docking and ADMET profiling to identify therapeutic phytochemicals from Brucea antidysentrica for acute myeloid leukemia

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_plos_journals_2695455558

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_2695455558

Other Identifiers

ISSN

1932-6203

E-ISSN

1932-6203

DOI

10.1371/journal.pone.0270050

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