<b>NANO.PTML Model for read-across prediction of nanosystems in neurosciences.</b>

  1. He, Shan
  2. Nader, Karam
  3. Segura Abarrategi, Julen
  4. Bediaga, Harbil
  5. Nocedo-Mena, Deyani
  6. Ascencio, Estefania
  7. Casanola-Martin, Gerardo M.
  8. Castellanos-Rubio, Idoia
  9. Insausti, Maite
  10. Rasulev, Bakhtiyor
  11. Arrasate, Sonia
  12. González-Díaz, Humberto

Verleger: figshare

Datum der Publikation: 2024

Art: Dataset

CC BY 4.0

Zusammenfassung

<b>Abstract. </b>Neurodegenerative diseases involve progressive neuronal death. Traditional treatments often struggle due to solubility, bioavailability, and crossing the Blood-Brain Barrier (BBB). Nanoparticles (NPs) in biomedical field are garnering growing attention as neurodegenerative disease drugs (NDDs) carrier to the central nervous system. Here, IFPTML technique was used, which combined Information Fusion (IF) + Perturbation Theory (PT) + Machine Learning (ML) to select the most promising NDDS and NP candidates and to address the few data in the literature. IF-process was carried out between 4403 NDDS assays and 260 cytotoxicity NP assays conducting a dataset of 500000 cases. The optimal IFPTML identified was the DT algorithm, demonstrating satisfactory performance with specificity values of 96.4% and 96.2%, and sensitivity values of 79.3% and 75.7% in the training (375k/75%) and validation (125k/25%) set. Moreover, the DT model obtained AUROC scores of 0.97 and 0.96 in the training and validation series, highlighting its effectiveness in classification tasks. On the other hand, two samples of NPs (Fe<sub>3</sub>O<sub>4</sub>_A and Fe<sub>3</sub>O<sub>4</sub>_B) were synthesized and structurally characterized by different methods. Additionally, in order to make the as-synthesized hydrophobic NPs (Fe<sub>3</sub>O<sub>4</sub>_A and Fe<sub>3</sub>O<sub>4</sub>_B) soluble in water the amphiphilic CTAB (hexadecyltrimethylammonium bromide) molecule was employed. Therefore, to conduct a study with a wider range of NP system variants, an experimental illustrative simulation experiment was performed using the IFPTML-DT model. For this, a set of 500000 prediction dataset was created involving n(NP cores)=5 vs. n(cell lines) =53 vs. n(NP shapes) =5 vs. n(NP coats) =16 vs. n(drugs) =123. The outcome of this experiment highlighted certain NANO.PTML systems as promising candidates for further investigation. Specifically, the experiment revealed that the cell line <i>Lycopersicon esculentum</i> showed promise for ecotoxicity studies across various coating systems. In contrast, <i>Danio rerio</i> cell lines (embryos, juveniles, and adults) showed lower predictive values, suggesting less favorable candidates. MacGowan volume was notably relevant for CTAB, PS, and PEG as coating agents, excluding PVA. The NANO.PTML approach holds potential to accelerate experimental investigations and offer initial insights into various NP and NDDS compounds, serving as an efficient alternative to time-consuming trial-and-error procedures.