M. Natália D. S. Cordeiro

Universidade do Porto — Portugal

Computer Science · Physical Sciences

56h-index11.9kcitations469works4.72yr avg
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Research Topics

Computational Drug Discovery Methods(164), Ionic liquids properties and applications(39), Catalytic Processes in Materials Science(37), Electrochemical Analysis and Applications(34), Synthesis and biological activity(33)

Publications468 total

Computational Phenotypic Drug Discovery for Anticancer Chemotherapy: PTML Modeling of Multi-Cell Inhibitors of Colorectal Cancer Cell Lines
International Journal of Molecular Sciences·2025Open Access
Nanotechnology for the therapeutic use of biologics to treat metabolic disorders
Elsevier eBooks·2025
List of contributors
Elsevier eBooks·2025Open Access
Inverse ligand design: a generative data-driven model for optimizing vanadyl-based epoxidation catalysts
Journal of Catalysis·2025Open Access
Design de um RPG de Aventura para Educação Ambiental e Valorização das Lendas dos Povos Originários da Amazônia
2025Open Access
Analysis of the multiport beam splitter transfer matrix in photonic integrated devices
2025Open Access
Analysis of the multiport beam splitter transfer matrix in photonic integrated devices
2025
Computational and spectrofluorimetric validation on glyphosate interactions with zebrafish (Danio rerio) acetylcholinesterase: Mechanistic and ecotoxicological implications
Toxicology in Vitro·2025
Interactions of β-lactam antibiotics with bovine serum albumin: An experimental and convolutional multi-conformational model
Journal of Molecular Liquids·2025
Interactions of Protein with Grafted Poly(ethylene oxide) Layer in Two Setups: A Molecular Dynamics Simulation Study
Biomacromolecules·2025
In Silico Approach for Early Antimalarial Drug Discovery: De Novo Design of Virtual Multi-Strain Antiplasmodial Inhibitors
Microorganisms·2025· 3 citedOpen Access
Optimizing Vanadium-Catalyzed Epoxidation Reactions: Machine-Learning-Driven Yield Predictions and Data Augmentation
Journal of Chemical Information and Modeling·2025· 2 cited
Perturbation-Theory Machine Learning for Multi-Target Drug Discovery in Modern Anticancer Research
Current Issues in Molecular Biology·2025· 2 citedOpen Access
Machine Learning-Guided Prediction of Activation Energies for Catalyst Design in the Water Gas Shift Reaction
The Journal of Physical Chemistry C·2025· 6 cited
Properties and interactions of magnetic ionic Liquids: Focus on greenhouse gas capture from MD simulations
Separation and Purification Technology·2025Open Access
Predicting mito-target interactions for per-and poly-fluoroalkyl compounds: Mapping mitochondrial toxicity on zebrafish voltage-dependent anion channel 2
Aquatic Toxicology·2025· 3 citedOpen Access
In Silico Approach for Antibacterial Discovery: PTML Modeling of Virtual Multi-Strain Inhibitors Against Staphylococcus aureus
Pharmaceuticals·2025· 10 citedOpen Access
Influence of Deep Eutectic Solvent Composition on Micelle Properties: A Molecular Dynamics Study
Molecules·2025· 6 citedOpen Access
Predicting the Aquatic Toxicity of Pharmaceutical and Personal Care Products: A Multitasking Modeling Approach
Applied Sciences·2025· 3 citedOpen Access
Perturbation-Theory Machine Learning for Multi-Objective Antibacterial Discovery: Current Status and Future Perspectives
Applied Sciences·2025· 8 citedOpen Access
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Frequent Co-authors

Alejandro Speck‐Planche(14), Valeria V. Kleandrova(11), José L. C. Fajín(9), Feng Luan(8), José R. B. Gomes(7), Fernanda Borges(5), Juan M. Ruso(5), André Melo(5), Miguel Jorge(5), Aliuska Morales Helguera(4), Humberto González‐Díaz(4), Nuno Milhazes(3), Patrícia Rebelo(3), João G. Pacheco(3), Cristina Delerue‐Matos(3), Francesc Illas(3), Iuliia V. Voroshylova(3), M. Paula M. Marques(2), Amit Kumar Halder(2), Pravin Ambure(2)