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Identificação

Identificação pessoal

Nome completo
Riccardo Concu

Nomes de citação

  • Concu, Riccardo

Identificadores de autor

Ciência ID
DE10-7770-3918
ORCID iD
0000-0002-0301-9407
Formação
Grau Classificação
2007/12/01 - 2010/12/21
Concluído
 Chimica e Tecnologie Farmaceutiche (Doctor of Philosophy)
Especialização em Computational Chemistry
Università degli Studi di Cagliari, Itália
"New QSAR models based on Markov Chains to predict protein functions" (TESE/DISSERTAÇÃO)
Percurso profissional

Ciência

Categoria Profissional
Instituição de acolhimento 		Empregador
2019/11/01 - 2025/11/01 Investigador Contratado (Investigação) Universidade do Porto Faculdade de Ciências, Portugal
Universidade do Porto Faculdade de Ciências, Portugal
Projetos

Bolsa

Designação Financiadores
2012/01 - 2015/01 Mitigation of risk and control of exposure in nanotechnology based inks and pigments - NANOMICEX -
280713
 European Commission
2011/12 - 2014/11 Development of a best practices guide for the safe handling and use of nanoparticles in packaging industries-NANOSAFEPACK
286362
 European Commission

Projeto

Designação Financiadores
2012/06 - 2018/06 Toward the design of molecularly imprinted materials: A molecular simulation study of the sol-gel synthesis of silica nanoparticles
SFRH/BPD/80605/2011
 Governo da República Portuguesa Ministério da Ciência Tecnologia e Ensino Superior
Produções

Publicações

Artigo em conferência
  1. Concu, Riccardo. "A novel QSAR model to predict epidermial growth factor inhibitors". 2018.
    10.3390/mol2net-04-05261
  2. Concu, Riccardo. "Nanodesk project: development of a web platform for the selection of the nanoparticles of interest for the plastic industry". 2017.
    10.3390/mol2net-03-05064
  3. Riccardo Concu; Maria Natalia Dias Soeiro Cordeiro. "Building a New High-Selective Molecular Imprinted Polymer". 2015.
    10.3390/mol2net-1-c013
Artigo em revista
  1. Concu, Riccardo. "New Mechanistic Insights on Carbon Nanotubes’ Nanotoxicity Using Isolated Submitochondrial Particles, Molecular Docking, and Nano-QSTR Approaches". Biology (2021): https://www.mdpi.com/2079-7737/10/3/171.
    https://doi.org/10.3390/biology10030171
  2. Michael González-Durruthy; Riccardo Concu; Laura F. Osmari Vendrame; Ivana Zanella; Juan M. Ruso; M. Natália D. S. Cordeiro. "Targeting Beta-Blocker Drug–Drug Interactions with Fibrinogen Blood Plasma Protein: A Computational and Experimental Study". Molecules (2020): https://doi.org/10.3390/molecules25225425.
    10.3390/molecules25225425
  3. Michael González-Durruthy; Amal Kanta Giri; Irina Moreira; Riccardo Concu; André Melo; Juan M. Ruso; M. Natália D.S. Cordeiro. "Computational modeling on mitochondrial channel nanotoxicity". Nano Today 34 (2020): 100913-100913. https://doi.org/10.1016/j.nantod.2020.100913.
    10.1016/j.nantod.2020.100913
  4. Concu, Riccardo. "New Computational Approaches Aimed at the Prediction of More Selective and Active Drugs". Current Topics in Medicinal Chemistry (2020): http://dx.doi.org/10.2174/156802662018200630150100.
    10.2174/156802662018200630150100
  5. Concu, Riccardo. "Developing a Multi-target Model to Predict the Activity of Monoamine Oxidase A and B Drugs". Current Topics in Medicinal Chemistry (2020): http://dx.doi.org/10.2174/1568026620666200603121224.
    10.2174/1568026620666200603121224
  6. Concu, Riccardo. "Alignment-Free Method to Predict Enzyme Classes and Subclasses". International Journal of Molecular Sciences (2019): http://dx.doi.org/10.3390/ijms20215389.
    10.3390/ijms20215389
  7. Concu, Riccardo. "PTML Model of Enzyme Subclasses for Mining the Proteome of Biofuel Producing Microorganisms". Journal of Proteome Research (2019): http://dx.doi.org/10.1021/acs.jproteome.8b00949.
    10.1021/acs.jproteome.8b00949
  8. Michael González-Durruthy; José M. Monserrat; Patricia Viera de Oliveira; Solange Binotto Fagan; Adriano V. Werhli; Karina Machado; André Melo; et al. "Computational MitoTarget Scanning Based on Topological Vacancies of Single-Walled Carbon Nanotubes with the Human Mitochondrial Voltage-Dependent Anion Channel (hVDAC1)". Chemical Research in Toxicology 32 4 (2019): 566-577. https://doi.org/10.1021/acs.chemrestox.8b00266.
    10.1021/acs.chemrestox.8b00266
  9. Concu, Riccardo. "MitoTarget Modeling Using ANN-Classification Models Based on Fractal SEM Nano-Descriptors: Carbon Nanotubes as Mitochondrial F0F1-ATPase Inhibitors". Journal of Chemical Information and Modelling (2018): https://pubs.acs.org/doi/10.1021/acs.jcim.8b00631.
    10.1021/acs.jcim.8b00631
  10. Concu, Riccardo. "Cetuximab And The Head And Neck Squamous Cell Cancer". (2018):
    10.2174/1568026618666180112162412
  11. Concu R; Cordeiro MND. "Looking for new inhibitors for the Epidermial Growth Factor Receptor.". Current topics in medicinal chemistry (2018): http://europepmc.org/abstract/med/29595111.
    10.2174/1568026618666180329123023
  12. Ardito F; Muzio L; Soeiro Cordeiro MND; Concu R. "Editorial: Head and Neck Cancer: Recent Findings and New Targets.". Current topics in medicinal chemistry (2018): http://europepmc.org/abstract/med/29788865.
    10.2174/156802661803180514122453
  13. Concu, Riccardo. "Probing the toxicity of nanoparticles: a unified in silico machine learning model based on perturbation theory.". Nanotoxicology (2017): http://europepmc.org/abstract/med/28937298.
    10.1080/17435390.2017.1379567
  14. Concu R; Cordeiro MN. "Molecular Dynamics Simulation Study of the Selectivity of a Silica Polymer for Ibuprofen.". International Journal of Molecular Sciences (2016): http://europepmc.org/abstract/med/27399685.
    10.3390/ijms17071083
  15. Perez M; Concu R; Ornelas M; Cordeiro MN; Azenha M; Silva AF. "Measurement artifacts identified in the UV-vis spectroscopic study of adduct formation within the context of molecular imprinting of naproxen.". Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy (2016): http://europepmc.org/abstract/med/26458249.
    10.1016/j.saa.2015.10.005
  16. Concu, Riccardo. "Molecularly imprinted sol-gel materials for medical applications.". Current Topics in Medicinal Chemistry (2015): http://www.eurekaselect.com/127189/article.
    10.2174/1568026614666141229112246
  17. Concu R; Perez M; Cordeiro MN; Azenha M. "Molecular dynamics simulations of complex mixtures aimed at the preparation of naproxen-imprinted xerogels.". Journal of chemical information and modeling (2014): http://europepmc.org/abstract/med/25382432.
    10.1021/ci5004575
  18. Chis Oana; Opris Dumitru; Concu Riccardo. "Review of Stochastic Stability and Analysis Tumor-Immune Systems". Current Bioinformatics 8 4 (2013): 390-400. https://doi.org/10.2174%2F1574893611308040002.
    10.2174/1574893611308040002
  19. Prado-Prado F; Garcia-Mera X; Rodriguez-Borges JE; Concu R; Perez-Montoto LG; Gonzalez-Diaz H; Duardo-Sanchez A. "Patents of bio-active compounds based on computer-aided drug discovery techniques.". (2013): http://europepmc.org/abstract/med/23276997.
    10.2741/E623
  20. Concu, Riccardo. "Generalized String Pseudo-Folding Lattices in Bioinformatics: State-of-Art Review, New Model for Enzyme Sub-Classes, and Study of ESTs on Trichinella spiralis". (2012):
    10.2174/157489312799304459
  21. Concu, Riccardo. "From QSAR models of Drugs to Complex Networks: State-of-Art Review and Introduction of New Markov-Spectral Moments Indices". Current Topics in Medicinal Chemistry 12 8 (2012): 927-960. http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000302767900011&KeyUID=WOS:000302767900011.
    10.2174/156802612800166819
  22. Concu R; Podda G; Gonzalez-Diaz H; Shen B. "Review of computer-aided models for predicting collagen stability.". (2011): http://europepmc.org/abstract/med/22050685.
    10.2174/157340911798260269
  23. Concu, Riccardo. "Yeast Network and Report of New Stochastic-Credibility Cell Cycle Models". Current Bioinformatics 6 1 (2011): 35-43. http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000292191700005&KeyUID=WOS:000292191700005.
    10.2174/157489311795222419
  24. Concu, Riccardo. "Review of MARCH-INSIDE & Complex Networks Prediction of Drugs: ADMET, Anti-parasite Activity, Metabolizing Enzymes and Cardiotoxicity Proteome Biomarkers". Current Drug Metabolism 11 4 (2010): 379-406. http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000279877800009&KeyUID=WOS:000279877800009.
    10.2174/138920010791514225
  25. Concu, Riccardo. "Review of QSAR Models for Enzyme Classes of Drug Targets: Theoretical Background and Applications in Parasites, Hosts and Other Organisms". Current Pharmaceutical Design 16 24 (2010): 2710-2723. http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000281444600008&KeyUID=WOS:000281444600008.
    10.2174/138161210792389207
  26. Concu R; Dea-Ayuela MA; Perez-Montoto LG; Bolas-Fernández F; Prado-Prado FJ; Podda G; Uriarte E; Ubeira FM; González-Díaz H. "Prediction of enzyme classes from 3D structure: a general model and examples of experimental-theoretic scoring of peptide mass fingerprints of Leishmania proteins.". (2009): http://europepmc.org/abstract/med/19603824.
    10.1021/pr9003163
  27. Concu R; Podda G; Uriarte E; González-Díaz H. "Computational chemistry study of 3D-structure-function relationships for enzymes based on Markov models for protein electrostatic, HINT, and van der Waals potentials.". (2009): http://europepmc.org/abstract/med/19086060.
    10.1002/jcc.21170
  28. Concu, R.; Dea-Ayuela, M. A.; Perez-Montoto, L. G.; Prado-Prado, F. J.; Uriarte, E.; Bolas-Fernandez, F.; Podda, G.; et al. "3D entropy and moments prediction of enzyme classes and experimental-theoretic study of peptide fingerprints in Leishmania parasites". Biochimica Et Biophysica Acta-Proteins and Proteomics 1794 12 (2009): 1784-1794. http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000271293700008&KeyUID=WOS:000271293700008.
    10.1016/j.bbapap.2009.08.020
Capítulo de livro
  1. Concu, Riccardo. "On the Relevance of Feature Selection Algorithms While Developing Non-linear QSARs". In Ecotoxicological QSARs. 2020.
    https://doi.org/10.1007/978-1-0716-0150-1
  2. Concu, Riccardo. "A model based on Markov Entropy to predict the stability of collagen peptides". 2009.
Edição de número de revista
  1. Concu, Riccardo. "Sol-Gel Chemistry Applied to Medicinal Science". Current Topics in Medicinal Chemistry (2015):
    10.2174/1568026615666141229115050
Livro
  1. Concu, Riccardo. Recent Trends on QSAR in the Pharmaceutical Perceptions. 2012.
    10.2174/97816080537971120101
Poster em conferência
  1. Concu, Riccardo. "From All Atom to Coarse Grain: Molecular Dynamic Simulation of Imprinting Process on a Silica Xerogel". 2018.
    10.3390/mol2net-04-06006

Outros

Outra produção
  1. Machine Learning Approach to Predict Enzyme Subclasses. 2017. R. Concu; H. González-Díaz; M.N.D.S. Cordeiro. https://doi.org/10.1016%2Fb978-0-08-101129-4.00002-3.
    10.1016/b978-0-08-101129-4.00002-3
  2. Molecular Dynamics Simulations and Comparison of Two New and High Selective Imprinted Xerogels. 2016. Riccardo Concu; Manuel Azenha; M Cordeiro. https://doi.org/10.1201%2F9781315368863-15.
    10.1201/9781315368863-15