Maria Florbela Bento Martinho de Sá Pereira

PhD in Organic Chemistry

Accepting PhD Students

  • 297 Citations
  • 10 h-Index
20032020

Research output per year

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Personal profile

Research interests

Florbela Pereira is part of the Chemoinformatics lab of LAQV REQUIMTE- FCT-NOVA since 2007. Her main scientific interests include automatic learning of chemical reactivity, the use of machine learning techniques to model Spectra–Structure and Structure-Activity Relationships of natural products/marine natural products and software solutions for the processing of molecular structures and chemical data by blind users. More recently, FP is very interested in the structural elucidation of secondary metabolites from marine actinomycete bacteria and their biological activity evaluation both in real and in virtual screening en route to new drugs. Moreover, Florbela Pereira explores as well a big data approach to the ultra-fast prediction of DFT-calculated properties (e.g. the fast estimation of HOMO and LUMO orbital energies, dipole moments).

Keywords

  • QD Chemistry
  • chemoinformatics
  • Big Data
  • QSAR
  • Machine Learning
  • Marine Natural Products
  • Drug Discovery
  • DFT-calculated properties
  • Material Discovery

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Research Output at NOVA

Antifouling napyradiomycins from marine-derived actinomycetes streptomyces aculeolatus

Pereira, F., Almeida, J. R., Paulino, M., Grilo, I. R., Macedo, H., Cunha, I., Sobral, R. G., Vasconcelos, V. & Gaudêncio, S. P., 18 Jan 2020, In : Marine Drugs. 18, 1, 63.

Research output: Contribution to journalArticle

Open Access
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  • 2 Citations (Scopus)
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    5 Citations (Scopus)

    Intra-clade metabolomic profiling of MAR4 Streptomyces from the Macaronesia Atlantic region reveals a source of anti-biofilm metabolites

    Bauermeister, A., Pereira, F., Grilo, I. R., Godinho, C. C., Paulino, M., Almeida, V., Gobbo-Neto, L., Prieto-Davó, A., Sobral, R. G., Lopes, N. P. & Gaudêncio, S. P., 1 Mar 2019, In : Environmental Microbiology. 21, 3, p. 1099-1112 14 p.

    Research output: Contribution to journalArticle

  • 4 Citations (Scopus)

    A Ligand-Based Approach to the Discovery of Lead-Like Potassium Channel KV1.3 Inhibitors

    Pereira, G., Szwarc, B., Mondragão, M. A., Lima, P. A. & Pereira, F., 7 Feb 2018, In : ChemistrySelect. 3, 5, p. 1352-1364 13 p.

    Research output: Contribution to journalArticle

  • 1 Citation (Scopus)