Multitask learning-driven identification of novel antitrypanosomal compounds
Background: Chagas disease and human African trypanosomiasis cause substantial death and morbidity, particularly in low- and middle-income countries, making the need for novel drugs urgent. Methodology & results: Therefore, an explainable multitask pipeline to profile the activity of compounds against three trypanosomes (Trypanosoma brucei brucei, Trypanosoma brucei rhodesiense and Trypanosoma cruzi) were created. These models successfully discovered four new experimental hits (LC-3, LC-4, LC-6 and LC-15). Among them, LC-6 showed promising results, with IC50 values ranging 0.01-0.072 μM and selectivity indices >10,000. Conclusion: These results demonstrate that the multitask protocol offers predictivity and interpretability in the virtual screening of new antitrypanosomal compounds and has the potential to improve hit rates in Chagas and human African trypanosomiasis projects.
Medienart: |
E-Artikel |
---|
Erscheinungsjahr: |
2023 |
---|---|
Erschienen: |
2023 |
Enthalten in: |
Zur Gesamtaufnahme - volume:15 |
---|---|
Enthalten in: |
Future medicinal chemistry - 15(2023), 16 vom: 13. Aug., Seite 1449-1467 |
Sprache: |
Englisch |
---|
Beteiligte Personen: |
Lemos, Jade Milhomem [VerfasserIn] |
---|
Links: |
---|
Themen: |
Deep learning |
---|
Anmerkungen: |
Date Completed 11.10.2023 Date Revised 12.10.2023 published: Print-Electronic Citation Status MEDLINE |
---|
doi: |
10.4155/fmc-2023-0074 |
---|
funding: |
|
---|---|
Förderinstitution / Projekttitel: |
|
PPN (Katalog-ID): |
NLM361993196 |
---|
LEADER | 01000naa a22002652 4500 | ||
---|---|---|---|
001 | NLM361993196 | ||
003 | DE-627 | ||
005 | 20231226090318.0 | ||
007 | cr uuu---uuuuu | ||
008 | 231226s2023 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.4155/fmc-2023-0074 |2 doi | |
028 | 5 | 2 | |a pubmed24n1206.xml |
035 | |a (DE-627)NLM361993196 | ||
035 | |a (NLM)37701989 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
100 | 1 | |a Lemos, Jade Milhomem |e verfasserin |4 aut | |
245 | 1 | 0 | |a Multitask learning-driven identification of novel antitrypanosomal compounds |
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 11.10.2023 | ||
500 | |a Date Revised 12.10.2023 | ||
500 | |a published: Print-Electronic | ||
500 | |a Citation Status MEDLINE | ||
520 | |a Background: Chagas disease and human African trypanosomiasis cause substantial death and morbidity, particularly in low- and middle-income countries, making the need for novel drugs urgent. Methodology & results: Therefore, an explainable multitask pipeline to profile the activity of compounds against three trypanosomes (Trypanosoma brucei brucei, Trypanosoma brucei rhodesiense and Trypanosoma cruzi) were created. These models successfully discovered four new experimental hits (LC-3, LC-4, LC-6 and LC-15). Among them, LC-6 showed promising results, with IC50 values ranging 0.01-0.072 μM and selectivity indices >10,000. Conclusion: These results demonstrate that the multitask protocol offers predictivity and interpretability in the virtual screening of new antitrypanosomal compounds and has the potential to improve hit rates in Chagas and human African trypanosomiasis projects | ||
650 | 4 | |a Journal Article | |
650 | 4 | |a Research Support, Non-U.S. Gov't | |
650 | 4 | |a QSAR | |
650 | 4 | |a deep learning | |
650 | 4 | |a low-data regimes | |
650 | 4 | |a model explainability | |
650 | 4 | |a neglected tropical diseases | |
650 | 4 | |a trypanosomatids | |
650 | 4 | |a virtual screening | |
650 | 7 | |a Trypanocidal Agents |2 NLM | |
700 | 1 | |a Brito da Silva, Meryck Felipe |e verfasserin |4 aut | |
700 | 1 | |a Dos Santos Carvalho, Alexandra Maria |e verfasserin |4 aut | |
700 | 1 | |a Vicente Gil, Henric Pietro |e verfasserin |4 aut | |
700 | 1 | |a Fiaia Costa, Vinícius Alexandre |e verfasserin |4 aut | |
700 | 1 | |a Andrade, Carolina Horta |e verfasserin |4 aut | |
700 | 1 | |a Braga, Rodolpho Campos |e verfasserin |4 aut | |
700 | 1 | |a Grellier, Philippe |e verfasserin |4 aut | |
700 | 1 | |a Muratov, Eugene N |e verfasserin |4 aut | |
700 | 1 | |a Charneau, Sébastien |e verfasserin |4 aut | |
700 | 1 | |a Moreira-Filho, José Teófilo |e verfasserin |4 aut | |
700 | 1 | |a Dourado Bastos, Izabela Marques |e verfasserin |4 aut | |
700 | 1 | |a Neves, Bruno Junior |e verfasserin |4 aut | |
773 | 0 | 8 | |i Enthalten in |t Future medicinal chemistry |d 2009 |g 15(2023), 16 vom: 13. Aug., Seite 1449-1467 |w (DE-627)NLM194822109 |x 1756-8927 |7 nnns |
773 | 1 | 8 | |g volume:15 |g year:2023 |g number:16 |g day:13 |g month:08 |g pages:1449-1467 |
856 | 4 | 0 | |u http://dx.doi.org/10.4155/fmc-2023-0074 |3 Volltext |
912 | |a GBV_USEFLAG_A | ||
912 | |a GBV_NLM | ||
951 | |a AR | ||
952 | |d 15 |j 2023 |e 16 |b 13 |c 08 |h 1449-1467 |