ArticleScientific reports2024
Py-CoMFA, docking, and molecular dynamics simulations of Leishmania (L.) amazonensis arginase inhibitors.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- 7-Prenyloxycoumarins as Promising Antileishmanial Agents: In Vitro, In Vivo, and In Silico Evaluation AgainstPharmaceuticals (Basel, Switzerland) · 2026Article
- Machine Learning and Molecular Modeling for Drug Repurposing Targeting Potential PI3Kα Inhibitors in Post-CoViD-19 Pulmonary Fibrosis.ACS omega · 2026Article
- In silico evaluation of N-aryl-1,10-phenanthroline-2-amines as potential inhibitors of T. cruzi GP63 zinc-metalloprotease by docking and molecular dynamics simulations.Scientific reports · 2025Article
- Exploring the Potential of Malvidin and Echiodinin as Probable Antileishmanial Agents Through In Silico Analysis and In Vitro Efficacy.Molecules (Basel, Switzerland) · 2025Article
- In vitro assays identified thiohydantoins with anti-trypanosomatid activity and molecular modelling studies indicated possible selective CYP51 inhibition.Scientific reports · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Leishmaniasis is a disease caused by a protozoan of the genus Leishmania, affecting millions of people, mainly in tropical countries, due to poor social conditions and low economic development. First-line chemotherapeutic agents involve highly toxic pentavalent antimonials, while treatment failure is mainly due to the emergence of drug-resistant strains. Leishmania arginase (ARG) enzyme is vital in pathogenicity and contributes to a higher infection rate, thus representing a potential drug target. This study helps in designing ARG inhibitors for the treatment of leishmaniasis. Py-CoMFA (3D-QSAR) models were constructed using 34 inhibitors from different chemical classes against ARG from L. (L.) amazonensis (LaARG). The 3D-QSAR predictions showed an excellent correlation between experimental and calculated pIC
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Registered trials
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