Classification models for predicting the antimalarial activity against Plasmodium falciparum-Reference-Cited by-同舟云学术

Classification models for predicting the antimalarial activity against Plasmodium falciparum

Published:2020-03-19 Issue:4 Volume:31 Page:313-324
ISSN:1062-936X
Container-title:SAR and QSAR in Environmental Research
language:en
Short-container-title:SAR and QSAR in Environmental Research

Author:

Liu Q.¹^ORCID,Deng J.¹,Liu M.²^ORCID

Affiliation:

1. Hunan Provincial Key Laboratory of Environmental Catalysis & Waste Regeneration, College of Materials and Chemical Engineering, Hunan Institute of Engineering, Xiangtan, China

2. School of Chemistry and Materials Engineering, Huizhou University, Huizhou, PR China

Publisher

Informa UK Limited

Subject

Drug Discovery,Molecular Medicine,General Medicine,Bioengineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/1062936X.2020.1740890

Reference29 articles.

1. Substituted Aminoacetamides as Novel Leads for Malaria Treatment

2. Exploration and validation of diphosphate-based Plasmodium LytB inhibitors using computational approaches

3. Triazole derivatives and their antiplasmodial and antimalarial activities

4. Artemisia afra, a controversial herbal remedy or a treasure trove of new drugs?

5. Integrating GUSAR and QSAR analyses for antimalarial activity of synthetic prodiginines against multi drug resistant strain

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