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Alejandro Speck-Planche

Alejandro Speck-Planche

D-Index & Metrics

Computer Science

D-Index
34
Citations
3122
World Ranking
12326
National Ranking
41

Overview

Alejandro Speck-Planche is affiliated with the University of Porto in Portugal. Their research spans multiple scientific disciplines, with a strong focus on computational approaches to drug discovery and related biomedical fields. The primary fields of study include Computer Science, Biochemistry, Genetics and Molecular Biology, and Medicine.

The subfields in which they are active include Computational Theory and Mathematics, Molecular Biology, Organic Chemistry, Pharmacology, and Oncology. Their research topics cover a broad range, notably in computational drug discovery methods, vaccines and immunoinformatics approaches, synthesis and biological activity, as well as genetics, bioinformatics, and biomedical research. Additionally, their work touches on cholinesterase and neurodegenerative diseases, bioinformatics and genomic networks, and machine learning in bioinformatics.

Recent publications authored or coauthored by Alejandro Speck-Planche include:

  • Artificial Intelligence, Big Data and Machine Learning Approaches in Precision Medicine & Drug Discovery (2021, Current Drug Targets)
  • Cell-based multi-target QSAR model for design of virtual versatile inhibitors of liver cancer cell lines (2020, SAR and QSAR in Environmental Research)
  • PTML Modeling for Alzheimer's Disease: Design and Prediction of Virtual Multi-Target Inhibitors of GSK3B, HDAC1, and HDAC6 (2020, Current Topics in Medicinal Chemistry)
  • PTML Modeling for Pancreatic Cancer Research: In Silico Design of Simultaneous Multi-Protein and Multi-Cell Inhibitors (2022, Biomedicines)
  • QSAR Modeling for Multi-Target Drug Discovery: Designing Simultaneous Inhibitors of Proteins in Diverse Pathogenic Parasites (2021, Frontiers in Chemistry)

Frequently appearing coauthors in their work are:

  • Valeria V. Kleandrova
  • M. Natália D. S. Cordeiro
  • Marcus Tullius Scotti
  • Luciana Scotti
  • Anuraj Nayarisseri

The most common publication venues where Alejandro Speck-Planche has contributed include:

  • Current Topics in Medicinal Chemistry
  • Frontiers in Chemistry
  • Expert Opinion on Drug Discovery
  • Applied Sciences
  • Future Medicinal Chemistry

Best Publications

  • Computational tool for risk assessment of nanomaterials: novel QSTR-perturbation model for simultaneous prediction of ecotoxicity and cytotoxicity of uncoated and coated nanoparticles under multiple experimental conditions.

    Valeria V. Kleandrova;Feng Luan;Feng Luan;Humberto González-Díaz;Humberto González-Díaz;Juan M. Ruso

  • Computer-aided nanotoxicology: Assessing cytotoxicity of nanoparticles under diverse experimental conditions by using a novel QSTR-perturbation approach

    Feng Luan;Feng Luan;Valeria V. Kleandrova;Humberto González-Díaz;Humberto González-Díaz;Juan M. Ruso

  • Computational ecotoxicology: simultaneous prediction of ecotoxic effects of nanoparticles under different experimental conditions.

    Valeria V. Kleandrova;Feng Luan;Humberto González-Díaz;Juan M. Ruso

  • Rational drug design for anti-cancer chemotherapy: multi-target QSAR models for the in silico discovery of anti-colorectal cancer agents.

    Alejandro Speck-Planche;Valeria V. Kleandrova;Feng Luan;Feng Luan;M. Natália D.S. Cordeiro

  • Chemoinformatics in anti-cancer chemotherapy: Multi-target QSAR model for the in silico discovery of anti-breast cancer agents

    Alejandro Speck-Planche;Valeria V. Kleandrova;Feng Luan;Feng Luan;M. Natália D.S. Cordeiro

  • Multi-target drug discovery in anti-cancer therapy: Fragment-based approach toward the design of potent and versatile anti-prostate cancer agents

    Alejandro Speck-Planche;Valeria V. Kleandrova;Feng Luan;M. Natália D.S. Cordeiro

  • Artificial Intelligence, Big Data and Machine Learning Approaches in Precision Medicine & Drug Discovery.

    Anuraj Nayarisseri;Ravina Khandelwal;Poonam Tanwar;Maddala Madhavi

  • Enabling the Discovery and Virtual Screening of Potent and Safe Antimicrobial Peptides. Simultaneous Prediction of Antibacterial Activity and Cytotoxicity

    Valeria V. Kleandrova;Juan M. Ruso;Alejandro Speck-Planche;Alejandro Speck-Planche;M. Natália Dias Soeiro Cordeiro

  • Speeding up Early Drug Discovery in Antiviral Research: A Fragment-Based in Silico Approach for the Design of Virtual Anti-Hepatitis C Leads

    Alejandro Speck-Planche;M. Natália Dias Soeiro Cordeiro

  • Multitasking models for quantitative structure-biological effect relationships: current status and future perspectives to speed up drug discovery.

    Alejandro Speck-Planche;Maria Natália Dias Soeiro Cordeiro

  • Chemoinformatics in multi-target drug discovery for anti-cancer therapy: in silico design of potent and versatile anti-brain tumor agents.

    Alejandro Speck-Planche;Valeria V. Kleandrova;Feng Luan;M. Natalia D. S. Cordeiro

  • Fragment-based approach for the in silico discovery of multi-target insecticides

    Alejandro Speck-Planche;Alejandro Speck-Planche;Valeria V. Kleandrova;Marcus T. Scotti

  • In silico discovery and virtual screening of multi-target inhibitors for proteins in Mycobacterium tuberculosis.

    Alejandro Speck-Planche;Valeria V. Kleandrova;Feng Luan;M. Natalia D.S. Cordeiro

  • New insights toward the discovery of antibacterial agents: multi-tasking QSBER model for the simultaneous prediction of anti-tuberculosis activity and toxicological profiles of drugs.

    Alejandro Speck-Planche;Valeria V. Kleandrova;Valeria V. Kleandrova;M. Natália D.S. Cordeiro

  • Simultaneous virtual prediction of anti-Escherichia coli activities and ADMET profiles: A chemoinformatic complementary approach for high-throughput screening.

    Alejandro Speck-Planche;M. N. D. S. Cordeiro

  • Fragment-based QSAR model toward the selection of versatile anti-sarcoma leads.

    Alejandro Speck-Planche;Valeria V. Kleandrova;Feng Luan;M. Natália D.S. Cordeiro

  • Computational modeling in nanomedicine: prediction of multiple antibacterial profiles of nanoparticles using a quantitative structure-activity relationship perturbation model

    Alejandro Speck-Planche;Valeria V Kleandrova;Feng Luan;Maria Natália D S Cordeiro

  • Unified multi-target approach for the rational in silico design of anti-bladder cancer agents.

    Alejandro Speck-Planche;Valeria V Kleandrova;Feng Luan;M N D S Cordeiro

  • First Multitarget Chemo-Bioinformatic Model To Enable the Discovery of Antibacterial Peptides against Multiple Gram-Positive Pathogens.

    Alejandro Speck-Planche;Alejandro Speck-Planche;Valeria V. Kleandrova;Juan M. Ruso;M. N. D. S. Cordeiro;M. N. D. S. Cordeiro;M. N. D. S. Cordeiro

  • Multi-Target Inhibitors for Proteins Associated with Alzheimer: In Silico Discovery using Fragment-Based Descriptors

    Alejandro Speck-Planche;Valeria V. Kleandrova;Feng Luan;M. Natalia D. S. Cordeiro

  • De novo computational design of compounds virtually displaying potent antibacterial activity and desirable in vitro ADMET profiles

    Alejandro Speck-Planche;M. Natália D. S. Cordeiro

Frequent Co-Authors

Humberto González-Díaz
Humberto González-Díaz University of the Basque Country
Eugene N. Muratov
Eugene N. Muratov University of North Carolina at Chapel Hill

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