Florbela Pereira

Secção de Química
(+351) 212948300
(+351) 212948550

Áreas de Investigação

Chemoinformatis; Machine Learning; Big Data; Marine Natural Products; Drug Discovery

Research scholarship for PhD student or person holding a master degree - 2020 Call for PhD Research Scholarships
It is open one (1) public competition for the assignment of one (1) Research Scholarship for PhD student or persons holding a Master in Chemoinformatics Lab, Chemistry Department, Faculty of Science and Technology, Nova.
1. Scientific Areas: i. Chemoinformatics; ii. Big Data; iii. Machine Learning; iv. Marine Natural Products (MNP); v. Nuclear Magnetic Resonance (NMR); vi. Drug Discovery.
2. Work Plan: i. A chemoinformatics exploration of spectral and quantum chemistry patterns for the discovery of new drug leads from marine natural products.
Superviser: Dr. Florbela Pereira (FCT-Nova, florbela.pereira@fct.unl.pt)
The selected candidate will be apply to the 2020 Call for PhD Research Scholarships (https://www.fct.pt/apoios/bolsas/concursos/individuais2020.phtml.en).

Interesses Científicos

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).

Publicações Representativas

- Tiago Dias; Susana Gaudêncio; Florbela Pereira*. 2019. "A Computer-Driven Approach to Discover Natural Product Leads for Methicillin-Resistant Staphylococcus aureus Infection Therapy". Marine Drugs 17: 16. https://doi.org/10.3390/md17010016.
- Sara Cruz; Sofia Gomes; Pedro Borralho; Cecília Rodrigues; Susana Gaudêncio; Florbela Pereira*. 2018. "In Silico HCT116 Human Colon Cancer Cell-Based Models En Route to the Discovery of Lead-Like Anticancer Drugs". Biomolecules 8: 56. https://doi.org/10.3390/biom8030056.
- Gilberto Pereira; Beatriz Szwarc; Miguel A. Mondragão; Pedro A. Lima;Florbela Pereira*. 2018. "A Ligand-Based Approach to the Discovery of Lead-Like Potassium Channel KV 1.3 Inhibitors". ChemistrySelect 3 (5): 1352-1364. http://dx.doi.org/10.1002/slct.201702977.

-Florbela Pereira; João Aires-de-Sousa*. 2018. "Machine learning for the prediction of molecular dipole moments obtained by density functional theory". Journal of Cheminformatics 10. https://jcheminf.biomedcentral.com/articles/10.1186/s13321-018-0296-5.
- Florbela Pereira; Kaixia Xiao; Diogo A. R. S. Latino; Chengcheng Wu; Qingyou Zhang*; João Aires-de-Sousa*. 2017. "Machine Learning Methods to Predict Density Functional Theory B3LYP Energies of HOMO and LUMO Orbitals". Journal of Chemical Information and Modeling 57 (1): 11-21. http://dx.doi.org/10.1021/acs.jcim.6b00340.

- Yuri Binev; Daniela Peixoto; Florbela Pereira; Ian Rodrigues; Sofia Cavaco; Ana M Lobo; João Aires-de-Sousa. 2018. "NavMol 3.0: enabling the representation of metabolic reactions by blind users". Bioinformatics 34 (1): 120-121. http://dx.doi.org/10.1093/bioinformatics/btx556.




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