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Comparative pharmacoinformatic and quantum descriptor insights from BFM/GBTLI guidelines to phase I/II compounds for acute lymphoblastic leukemia (ALL).

PubMed
Authors: Bahia IAF, da Silva MK, Sindi ER, Rodrigues-Neto JF, da Silva ED Jr, Alqahtani T, Tiruneh YK, Zaki MEA, Fulco UL, Oliveira JIN

Year

2026

Paper ID

9826

Status

Peer-reviewed

Abstract Read

~2 min

Abstract Words

311

Citations

1

Abstract

Acute lymphoblastic leukemia (ALL) remains the most common pediatric malignancy worldwide. Standard protocols such as BFM and GBTLI rely on long-established cytotoxic agents, yet novel targeted compounds have recently entered phase I/II trials. Despite these advances, no prior study has systematically compared the pharmacokinetic, ADMET, and quantum descriptor profiles of protocol-based drugs versus emerging clinical-phase agents. This study addresses that gap by integrating pharmacoinformatic and quantum-chemical approaches to highlight differences with potential clinical implications. We retrieved all small-molecule drugs from the BFM/GBTLI 2009 protocols and a representative set of phase I/II investigational compounds for pediatric ALL. In silico tools were used to assess physicochemical properties, ADMET (absorption, distribution, metabolism, excretion, and toxicity) profiles, and quantum chemical descriptors. We evaluated physicochemical and pharmacokinetic properties, including solubility, permeability, metabolic liabilities, and toxicity risks. Quantum chemical descriptors were calculated with density functional theory (DFT) to assess molecular reactivity (HOMO, LUMO, gap, dipole moment, electrophilicity). Multivariate analyses were applied to compare and cluster drug profiles. The comparative analysis revealed significant variability between guideline and clinical-phase compounds. Clinical-phase compounds generally exhibited higher molecular weight and lipophilicity, together with greater variability in permeability and solubility-related descriptors, indicating potential formulation and bioavailability challenges. Several investigational agents were identified as P-gp substrates and hERG inhibitors, suggesting increased risk of efflux-mediated resistance and cardiotoxicity. Quantum chemical analysis revealed that phase I/II compounds (e.g., Pelabresib, Molibresib) displayed smaller HOMO-LUMO gaps and higher electrophilicity, consistent with higher theoretical reactivity, whereas guideline drugs (e.g., Vincristine, Methotrexate) showed more stable electronic profiles. Cluster analysis confirmed distinct grouping between guideline and clinical-phase compounds. This in silico comparison integrates pharmacoinformatic and quantum descriptor analyses of established and emerging ALL therapeutics. By revealing key differences in drug-likeness, ADMET, and electronic reactivity, the study provides a comparative framework that may support the prioritization, optimization, and clinical translation of next-generation therapies for pediatric ALL.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2026 reference point for readers tracking recent quantum research.
  • Acute lymphoblastic leukemia (ALL) remains the most common pediatric malignancy worldwide.

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