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Mechanistic multiscale modeling identifies putative natural tri-target candidates of MAO-B, LRRK2 and A₂A for Parkinson's disease.

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Paper

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The authors' code

Python · 56 lines · 2.6 KB · no license

  1. #!/usr/bin/env python3
  2. # FEL_2D_only_G.py — Paysage d’énergie libre 2D (G), échelle 0–12 kJ/mol
  3. # Auteur: ChatGPT (corrigé pour libellé G au lieu de ΔG)
  5. import numpy as np
  6. import matplotlib.pyplot as plt
  7. import matplotlib as mpl
  8. from scipy.stats import gaussian_kde
  10. # ── Réglages utilisateur ────────────────────────────────────────
  11. INFILE = '2Dproj_PC1_PC2.xvg' # fichier PC1/PC2 (2 colonnes: PC1 PC2)
  12. TEMP = 300.0 # K
  13. kB = 0.008314 # kJ mol⁻1 K⁻1
  14. BINS = 100 # maillage XY (plus grand = plus fin)
  15. BWIDTH = 0.15 # bande KDE (plus petit = plus détaillé)
  16. Z_MAX = 12.0 # plafond G (kJ/mol)
  18. # ── Chargement ──────────────────────────────────────────────────
  19. pc1, pc2 = np.loadtxt(INFILE, comments=('#', '@')).T
  21. # ── Densité ρ(x,y) → G = −kT ln(ρ/ρmax) (énergie libre relative) ─
  22. kde = gaussian_kde([pc1, pc2], bw_method=BWIDTH)
  23. xi, yi = [np.linspace(v.min(), v.max(), BINS + 1) for v in (pc1, pc2)]
  24. xc, yc = [0.5 * (v[:-1] + v[1:]) for v in (xi, yi)]
  25. X, Y = np.meshgrid(xc, yc)
  26. rho = kde([X.ravel(), Y.ravel()]).reshape(X.shape)
  28. G = -kB * TEMP * np.log(rho / rho.max())
  29. G = np.clip(G, 0.0, Z_MAX) # bornes 0–12
  31. # ── Colormap & normalisation ───────────────────────────────────
  32. cmap = plt.get_cmap('jet')
  33. norm = mpl.colors.Normalize(vmin=0.0, vmax=Z_MAX)
  35. # ── Tracé 2D ───────────────────────────────────────────────────
  36. plt.rcParams.update({'font.size': 10})
  37. fig, ax = plt.subplots(figsize=(6.0, 5.6), dpi=300)
  39. pcm = ax.pcolormesh(xi, yi, G, cmap=cmap, norm=norm, shading='auto')
  40. # (Optionnel) isolignes toutes les 2 kJ/mol — commentez pour enlever
  41. ax.contour(X, Y, G, levels=np.arange(0, Z_MAX + 0.001, 2), colors='k', linewidths=0.35, alpha=0.6)
  43. ax.set_xlabel('PC1')
  44. ax.set_ylabel('PC2')
  45. ax.set_title('Free Energy Landscape (G)', pad=10)
  46. ax.set_aspect('equal', adjustable='box')
  48. # Échelle unique à droite, 0–12 kJ/mol
  49. cbar = fig.colorbar(pcm, ax=ax, pad=0.02, fraction=0.046, extend='max')
  50. cbar.set_label('G (kJ/mol)', weight='bold')
  51. cbar.set_ticks(np.arange(0, int(Z_MAX) + 1, 1))
  52. pcm.cmap.set_over('red') # valeurs >12 en rouge
  54. fig.tight_layout()
  55. fig.savefig('FEL_2D_only_G_0_12.png')
  56. # plt.show() # décommentez pour afficher interactivement

2D.py at commit fa6890d, no license · at the source

Overview

Authors: Oussama Khibech1, Salma Kadda2, Said Abadi1, Abdessamad Benabbou1, Mohamed Bouhrim3, Shehdeh Jodeh4, Diana Jodeh5, Belkheir Hammouti2, Allal Challioui1
ORCID iDs: Said Abadi
  1. Faculty of sciences, department of Chemistry, Laboratory of Applied and Environmental Chemistry (LCAE), Mohammed Premier University, Oujda, Morocco
  2. Euro-Mediterranean University of Fes, UEMF, 30000 Fez Oujda, Morocco
  3. Department of Pharmacy, UFR3S, TBC Laboratories, University of Lille, 3 rue du Professeur Laguesse, BP 83, Lille Cedex, 59006 France
  4. Department of Chemistry, An-Najah National University, P.O. Box 7, Nablus, Palestine
  5. Division of Pulmonary, Critical Care and Sleep Medicine, Detroit Medical Centre, Wayne State University School of Medicine, 3990 John R-3 Hudson, Detroit, MI 48201 USA
Institutions: Mohamed I University (Morocco); Euro-Mediterranean University of Fes (Morocco); Université de Lille (France); An-Najah National University (Palestinian Territories); Wayne State University (United States); Detroit Medical Center (United States)
Journal: Scientific reports, volume 16, issue 1, article 20657
Dates: received 13 January 2026; accepted 21 April 2026; published online 5 May 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1038/s41598-026-50523-0 · PMID 42086777 · PMCID PMC13333977 · OpenAlex W7160270765
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: computational modeling (no new data) (modality), human (organism), Parkinson's (population), cellular / molecular (subfield)
Methods: Machine learning
Keywords: Parkinson’s disease, ADMET-AI, MD, MM/GBSA, PCA, Good Health and Well-being, Chemistry, Computational biology and bioinformatics, Drug discovery, Neuroscience
MeSH: Leucine-Rich Repeat Serine-Threonine Protein Kinase-2*, Monoamine Oxidase*, Parkinson Disease*, Humans, Molecular Docking Simulation, Molecular Dynamics Simulation, Protein Binding (* major topic)
Topic: Parkinson's Disease Mechanisms and Treatments (Neurology, Medicine), according to OpenAlex
Citations: cited by 1 paper (Europe PMC); 51 references in the paper

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Repository

Its files are read in the Code ↔ Paper reader above.

khibech/Parkinson-s-Disease

License: none: the authors keep all their rights
State: the link answers, verified on 28 September 2026
Evidence: files inventoried
Commit: fa6890d9a93da19f7257744fcd8ae76cff2351c0, 26 November 2025
Languages: Python (2)
Size: 20 files, 2 scripts
Software Heritage: not archived
Found in: “Data availability”
Holds: README
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Matplotlib (2 files), NumPy (2 files), SciPy (2 files)
Availability: 1 check, the latest on 28 September 2026: the link answers
  • 28 September 2026: the link answers
3 files
At the source: github.com/khibech/Parkinson-s-Disease

The paper's code and data availability statement is in the Data section.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 2 scripts, each with its path and the digest of its content;
  • no match between paragraphs and code yet;
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Code and data availability statement

The paper has a code and data availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

Read it in the paper: doi.org/10.1038/s41598-026-50523-0.

Versions

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Version 1, 28 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 9 authors, 10 keywords, 7 MeSH terms, 48 references.

Cite

This paper

Khibech, O., Kadda, S., Abadi, S., Benabbou, A., Bouhrim, M., Jodeh, S., Jodeh, D., Hammouti, B., & Challioui, A. (2026). Mechanistic multiscale modeling identifies putative natural tri-target candidates of MAO-B, LRRK2 and A₂A for Parkinson's disease. Scientific reports, 16(1), 20657. https://doi.org/10.1038/s41598-026-50523-0

BibTeX

@article{khibech2026mechanistic,
author = {Khibech, Oussama and Kadda, Salma and Abadi, Said and Benabbou, Abdessamad and Bouhrim, Mohamed and Jodeh, Shehdeh and Jodeh, Diana and Hammouti, Belkheir and Challioui, Allal},
title = {{Mechanistic multiscale modeling identifies putative natural tri-target candidates of MAO-B, LRRK2 and A₂A for Parkinson's disease}},
journal = {Scientific reports},
year = {2026},
month = may,
volume = {16},
number = {1},
pages = {20657},
publisher = {Nature Publishing Group},
issn = {2045-2322},
doi = {10.1038/s41598-026-50523-0},
url = {https://doi.org/10.1038/s41598-026-50523-0},
pmid = {42086777},
pmcid = {PMC13333977}
}

RIS

TY - JOUR
AU - Khibech, Oussama
AU - Kadda, Salma
AU - Abadi, Said
AU - Benabbou, Abdessamad
AU - Bouhrim, Mohamed
AU - Jodeh, Shehdeh
AU - Jodeh, Diana
AU - Hammouti, Belkheir
AU - Challioui, Allal
TI - Mechanistic multiscale modeling identifies putative natural tri-target candidates of MAO-B, LRRK2 and A₂A for Parkinson's disease
T2 - Scientific reports
J2 - Sci Rep
PY - 2026
DA - 2026/05/05
VL - 16
IS - 1
SP - 20657
SN - 2045-2322
PB - Nature Publishing Group
DO - 10.1038/s41598-026-50523-0
UR - https://doi.org/10.1038/s41598-026-50523-0
LA - en
ER -

CSL-JSON

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"container-title": "Scientific reports",
"author": [
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