Carlos Martínez Cortés

Carlos Martínez Cortés, PhD

Senior Researcher · BIO-HPC · UCAM HiTech Sport & Health Innovation Hub · UCAM Universidad Católica de Murcia

Computer scientist working on machine learning and AI for drug discovery and personalised medicine — co-developer of the group’s virtual-screening tooling and co-inventor on three Spanish patents.

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About

Carlos holds a PhD in Informatics from the University of Murcia (2019), an MSc in New Technologies in Informatics (UMU, 2016) and a BSc in Computer Engineering (UMU, 2015). During his undergraduate, master’s and doctoral training he developed several feature-selection and classification methods now available in the open-source Weka machine-learning platform.

He joined UCAM permanently in 2020 as Teaching and Research Staff at the BIO-HPC Research Group, based at the UCAM HiTech, Sport & Health Innovation Hub. His current work centres on applying machine learning and AI to drug discovery and personalised medicine, including within the EU-funded REVERT project.

Carlos is co-developer of several BIO-HPC software tools (Blind Docking Server, DIA-DB, MetaScreener, TOLEDO and ESSENCE-Dock) and co-inventor on three granted Spanish patents on antiviral and anti-obesity therapeutics.

Focus areas

Machine learning for drug discovery

Interpretable ML for activity prediction, ADMET, virtual-screening enrichment and personalised medicine within the REVERT project.

High-performance virtual screening

Co-developer of MetaScreener, Blind Docking Server, DIA-DB, TOLEDO and ESSENCE-Dock — the BIO-HPC virtual-screening stack on HPC.

Software methodology

Feature selection and classification contributions to the open-source Weka platform (University of Waikato).

Selected publications

  • Global and Local Interpretable Machine Learning Allow Early Prediction of Unscheduled Hospital Readmission. Morales Moreno I, Hernández Morante JJ, Pérez-Sánchez H, Martínez Cortés C, Banegas-Luna AJ, Segura Méndez FJ. Machine Learning and Knowledge Extraction, MDPI, 6:1653–1666, 2024.
  • Enhancing MD simulations: ASGARD’s automated analysis for GROMACS. Rodríguez Martínez A, Nelen J, Carmena Bargueño M, Martínez Cortés C, Luque I, Pérez-Sánchez H. Journal of Biomolecular Structure and Dynamics, 2024. DOI
  • ESSENCE-Dock: A Consensus-Based Approach to Enhance Virtual Screening Enrichment in Drug Discovery. Nelen J, Carmena Bargueño M, Martínez Cortés C, Rodríguez Martínez A, Villalgordo Soto JM, Pérez-Sánchez H. Journal of Chemical Information and Modeling, 2024. DOI
  • TOLEDO: Accelerated Maestro GUI molecular dynamics simulations. Carmena Bargueño M, Martínez Cortés C, Banegas-Luna AJ, Pérez-Sánchez H. Journal of Biomolecular Structure & Dynamics, Taylor & Francis, 2023. DOI
  • Identification of Kukoamine A, Zeaxanthin, and Clexane as New Furin Inhibitors. Zaragoza-Huesca D, Martínez Cortés C, Banegas-Luna AJ, et al, Martínez-Martínez I. International Journal of Molecular Sciences, MDPI, 23(5):2796–2812, 2022. DOI
  • Piperazine-derived small molecules as potential Flaviviridae NS3 protease inhibitors: in vitro antiviral evaluation against Zika and Dengue. García Lozano M, Pérez-Sánchez H, Martínez Cortés C, Rodríguez Martínez A, Iglesias Guerra F. Bioorganic Chemistry, 2023.

Patents

  • Zeaxanthin for the prevention and treatment of viral infection, preferably by coronavirus. Spanish patent ES2899697. Pérez-Sánchez H, Martínez-Martínez I, Zaragoza-Huesca D, Martínez Cortés C, Banegas-Luna AJ, Pérez-Garrido A, Vegara Meseguer J, Peñas Martínez J, Ródenas Bleda MdC, Espín García S. UCAM & FFIS. Granted 20 September 2022.
  • Kukoamine A for the prevention and treatment of viral infection, preferably by coronavirus. Spanish patent ES2899548. UCAM & FFIS. Granted 13 September 2022.
  • Treatment of obesity. Spanish patent ES2925124. Pérez-Sánchez H, Hernández Morante JJ, Del Castillo Santaella T, Maldonado Valderrama J, Martínez Cortés C. UCAM & UGR. Granted 1 April 2024.
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