On finding natural antibiotics based on TCM formulae
Copyright © 2023 Elsevier Inc. All rights reserved..
CONTEXT: Novel kinds of antibiotics are needed to combat the emergence of antibacterial resistance. Natural products (NPs) have shown potential as antibiotic candidates. Current experimental methods are not yet capable of exploring the massive, redundant, and noise-involved chemical space of NPs. In silico approaches are needed to select NPs as antibiotic candidates.
OBJECTIVE: This study screens out NPs with antibacterial efficacy guided by both TCM and modern medicine and constructed a dataset aiming to serve the new antibiotic design.
METHOD: A knowledge-based network is proposed in this study involving NPs, herbs, the concepts of TCM, and the treatment protocols (or etiologies) of infectious in modern medicine. Using this network, the NPs candidates are screened out and compose the dataset. Feature selection of machine learning approaches is conducted to evaluate the constructed dataset and statistically validate the im- portance of all NPs candidates for different antibiotics by a classification task.
RESULTS: The extensive experiments prove the constructed dataset reaches a convincing classification performance with a 0.9421 weighted accuracy, 0.9324 recall, and 0.9409 precision. The further visu- alizations of sample importance prove the comprehensive evaluation for model interpretation based on medical value considerations.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2023 |
|---|---|
| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:214 |
|---|---|
| Enthalten in: |
Methods (San Diego, Calif.) - 214(2023) vom: 01. Juni, Seite 35-45 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Gao, Pei [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Antibiotics |
|---|
| Anmerkungen: |
Date Completed 22.05.2023 Date Revised 23.05.2023 published: Print-Electronic Citation Status MEDLINE |
|---|
| doi: |
10.1016/j.ymeth.2023.04.001 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM355239973 |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM355239973 | ||
| 003 | DE-627 | ||
| 005 | 20231226063930.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231226s2023 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.ymeth.2023.04.001 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1184.xml |
| 035 | |a (DE-627)NLM355239973 | ||
| 035 | |a (NLM)37019293 | ||
| 035 | |a (PII)S1046-2023(23)00055-5 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Gao, Pei |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a On finding natural antibiotics based on TCM formulae |
| 264 | 1 | |c 2023 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 22.05.2023 | ||
| 500 | |a Date Revised 23.05.2023 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2023 Elsevier Inc. All rights reserved. | ||
| 520 | |a CONTEXT: Novel kinds of antibiotics are needed to combat the emergence of antibacterial resistance. Natural products (NPs) have shown potential as antibiotic candidates. Current experimental methods are not yet capable of exploring the massive, redundant, and noise-involved chemical space of NPs. In silico approaches are needed to select NPs as antibiotic candidates | ||
| 520 | |a OBJECTIVE: This study screens out NPs with antibacterial efficacy guided by both TCM and modern medicine and constructed a dataset aiming to serve the new antibiotic design | ||
| 520 | |a METHOD: A knowledge-based network is proposed in this study involving NPs, herbs, the concepts of TCM, and the treatment protocols (or etiologies) of infectious in modern medicine. Using this network, the NPs candidates are screened out and compose the dataset. Feature selection of machine learning approaches is conducted to evaluate the constructed dataset and statistically validate the im- portance of all NPs candidates for different antibiotics by a classification task | ||
| 520 | |a RESULTS: The extensive experiments prove the constructed dataset reaches a convincing classification performance with a 0.9421 weighted accuracy, 0.9324 recall, and 0.9409 precision. The further visu- alizations of sample importance prove the comprehensive evaluation for model interpretation based on medical value considerations | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a Antibiotics | |
| 650 | 4 | |a Natural products | |
| 650 | 4 | |a Traditional Chinese medicine | |
| 650 | 4 | |a Variational dropout feature ranking | |
| 650 | 7 | |a Biological Products |2 NLM | |
| 700 | 1 | |a Nasution, Ahmad Kamal |e verfasserin |4 aut | |
| 700 | 1 | |a Yang, Shuo |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Zheng |e verfasserin |4 aut | |
| 700 | 1 | |a Ono, Naoaki |e verfasserin |4 aut | |
| 700 | 1 | |a Kanaya, Shigehiko |e verfasserin |4 aut | |
| 700 | 1 | |a Altaf-Ul-Amin, M D |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Methods (San Diego, Calif.) |d 1990 |g 214(2023) vom: 01. Juni, Seite 35-45 |w (DE-627)NLM087818051 |x 1095-9130 |7 nnns |
| 773 | 1 | 8 | |g volume:214 |g year:2023 |g day:01 |g month:06 |g pages:35-45 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1016/j.ymeth.2023.04.001 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 214 |j 2023 |b 01 |c 06 |h 35-45 | ||