Rafael F. Lameiro

ORCID: 0000-0003-4466-2682
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About
Contact & Profiles
Research Areas
  • Trypanosoma species research and implications
  • Computational Drug Discovery Methods
  • Machine Learning in Materials Science
  • Carbohydrate Chemistry and Synthesis
  • Lysosomal Storage Disorders Research
  • Various Chemistry Research Topics
  • Trace Elements in Health
  • Research on Leishmaniasis Studies
  • Synthesis and Biological Evaluation
  • Bone Metabolism and Diseases
  • Plant Stress Responses and Tolerance
  • Click Chemistry and Applications
  • History and advancements in chemistry
  • Plant Molecular Biology Research
  • Peptidase Inhibition and Analysis
  • Plant nutrient uptake and metabolism
  • Protease and Inhibitor Mechanisms
  • Malaria Research and Control
  • Chemical Synthesis and Analysis

Universidade de São Paulo
2019-2023

Universidade Federal de São Carlos
2020

Chagas disease is a neglected tropical caused by the protozoa Trypanosoma cruzi. Cruzain, its main cysteine protease, commonly targeted in drug discovery efforts to find new treatments for this disease. Even though essentiality of enzyme parasite has been established, many cruzain inhibitors fail as trypanocidal agents. This lack translation from biochemical biological assays can involve several factors, including suboptimal physicochemical properties. In work, we aim rationalize phenomenon...

10.1002/cmdc.202200434 article EN ChemMedChem 2023-01-24

Aim: Compounds that block enzyme activity can kill pathogens and help develop effective safe drugs for Chagas disease leishmaniasis. Materials & methods: A library of nonpeptidic nitrile-based compounds was synthesized had their inhibitory affinity tested against cruzain, Leishmania mexicana cysteine protease B cathepsin L. Isothermal titration calorimetry experiments molecular simulations were performed selected to obtain thermodynamic fingerprints identify main interactions putative modes...

10.4155/fmc-2020-0057 article EN Future Medicinal Chemistry 2020-12-08

Artificial intelligence (AI) and machine learning (ML) are expanding in popularity for broad applications to challenging tasks chemistry materials science. Examples include the prediction of properties, discovery new reaction pathways, or design molecules. The needs read write fluently a chemical language each these tasks. Strings common tool represent molecular graphs, most popular string representation, SMILES, has powered cheminformatics since late 1980s. However, context AI ML chemistry,...

10.48550/arxiv.2204.00056 preprint EN cc-by arXiv (Cornell University) 2022-01-01
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