Alejandro Planche-Speck

Porto, 4169007, Portugal

Last Updated: 09/26/2026

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Found 82 publications

Computational Phenotypic Drug Discovery for Anticancer Chemotherapy: PTML Modeling of Multi-Cell Inhibitors of Colorectal Cancer Cell Lines.

Computational Phenotypic Drug Discovery for Anticancer Chemotherapy: PTML Modeling of Multi-Cell Inhibitors of Colorectal Cancer Cell Lines.

Journal: International journal of molecular sciences

Published: November 03, 2025

In Silico Approach for Early Antimalarial Drug Discovery: De Novo Design of Virtual Multi-Strain Antiplasmodial Inhibitors.

In Silico Approach for Early Antimalarial Drug Discovery: De Novo Design of Virtual Multi-Strain Antiplasmodial Inhibitors.

Journal: Microorganisms

Published: May 15, 2025

Perturbation-Theory Machine Learning for Multi-Target Drug Discovery in Modern Anticancer Research.

Perturbation-Theory Machine Learning for Multi-Target Drug Discovery in Modern Anticancer Research.

Journal: Current issues in molecular biology

Published: March 26, 2025

In Silico Approach for Antibacterial Discovery: PTML Modeling of Virtual Multi-Strain Inhibitors Against Staphylococcus aureus.

In Silico Approach for Antibacterial Discovery: PTML Modeling of Virtual Multi-Strain Inhibitors Against Staphylococcus aureus.

Journal: Pharmaceuticals (Basel, Switzerland)

Published: December 13, 2024

Perturbation-theory machine learning for mood disorders: virtual design of dual inhibitors of NET and SERT proteins.

Perturbation-theory machine learning for mood disorders: virtual design of dual inhibitors of NET and SERT proteins.

Journal: BMC chemistry

Published: October 04, 2024

Ligand-Based Approach for Multi-Target Drug Discovery: PTML Modeling of Triple-Target Inhibitors.

Ligand-Based Approach for Multi-Target Drug Discovery: PTML Modeling of Triple-Target Inhibitors.

Journal: Current topics in medicinal chemistry

Published: April 24, 2024

Current in silico methods for multi-target drug discovery in early anticancer research: the rise of the perturbation-theory machine learning approach.

Current in silico methods for multi-target drug discovery in early anticancer research: the rise of the perturbation-theory machine learning approach.

Journal: Future medicinal chemistry

Published: September 20, 2023

Optimizing drug discovery using multitasking models for quantitative structure-biological effect relationships: an update of the literature.

Optimizing drug discovery using multitasking models for quantitative structure-biological effect relationships: an update of the literature.

Journal: Expert opinion on drug discovery

Published: August 28, 2023

The latest guidance on the simultaneous design of virtually active and non-hemolytic peptides.

The latest guidance on the simultaneous design of virtually active and non-hemolytic peptides.

Journal: Expert opinion on drug discovery

Published: September 23, 2022

PTML Modeling for Pancreatic Cancer Research: In Silico Design of Simultaneous Multi-Protein and Multi-Cell Inhibitors.

PTML Modeling for Pancreatic Cancer Research: In Silico Design of Simultaneous Multi-Protein and Multi-Cell Inhibitors.

Journal: Biomedicines

Published: January 29, 2022

In Silico Drug Repurposing for Anti-Inflammatory Therapy: Virtual Search for Dual Inhibitors of Caspase-1 and TNF-Alpha.

In Silico Drug Repurposing for Anti-Inflammatory Therapy: Virtual Search for Dual Inhibitors of Caspase-1 and TNF-Alpha.

Journal: Biomolecules

Published: November 01, 2021

PTML modeling for peptide discovery: in silico design of non-hemolytic peptides with antihypertensive activity.

PTML modeling for peptide discovery: in silico design of non-hemolytic peptides with antihypertensive activity.

Journal: Molecular diversity

Published: September 14, 2021

Showing 1-12 of 82

Last Updated: 09/26/2026