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<p>Alpha-synuclein (α-syn) is a 140 amino acid neuronal protein linked to different neurodegenerative disorders. A point mutation in its gene has been related to a rare family type of Parkinson's disease (PD), and more alterations have been discovered in familial PD cases. Abnormal processing of α-syn can cause pathological alterations, altering its binding characteristics and functionality. Clinical trials aimed at reducing α-syn aggregation have faced obstacles due to challenges in identifying effective drugs during preclinical studies. Method To address this issue, we present computational methods that combines pharmacophore modeling, molecular docking, molecular dynamics, free energy calculations, and similarity index investigations to find possible hit compounds for preventing α-syn aggregation. Results A validated pharmacophore model was used to screen the ZINC natural product library, followed by established computational pipeline, yielding four novel inhibitors (ZINC000150351590, ZINC000299817386, ZINC000085509805, ZINC000095911811) with strong binding affinities (− 9.43 to − 9.06&#xa0;kcal/mol). Molecular dynamics simulations confirmed stable protein–ligand complexes (average RMSD &lt; 2.5&#xa0;Å), while MM/PBSA analysis showed favorable binding free energies (− 56.7 to − 49.2&#xa0;kcal/mol). Conclusion Evaluation of docking performance, stability, and binding energetics using MM/PBSA enabled the identification of four natural inhibitors of α-syn aggregation. These compounds represent promising leads for further investigation in Parkinson’s disease drug discovery.</p>

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Targeting the alpha-synuclein protein to treat Parkinson's disease using novel inhibitors identified using an integrated computational drug development approaches

  • 期刊论文

  • 发表日期：

    2025年11月6日

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  • Arif Jamal Siddiqui,
  • Sadaf Jahan,
  • Juhi Saxena,
  • Manojkumar Sachidanandan,
  • Riadh Badraoui,
  • Mohd Adnan

摘要

Alpha-synuclein (α-syn) is a 140 amino acid neuronal protein linked to different neurodegenerative disorders. A point mutation in its gene has been related to a rare family type of Parkinson's disease (PD), and more alterations have been discovered in familial PD cases. Abnormal processing of α-syn can cause pathological alterations, altering its binding characteristics and functionality. Clinical trials aimed at reducing α-syn aggregation have faced obstacles due to challenges in identifying effective drugs during preclinical studies. Method To address this issue, we present computational methods that combines pharmacophore modeling, molecular docking, molecular dynamics, free energy calculations, and similarity index investigations to find possible hit compounds for preventing α-syn aggregation. Results A validated pharmacophore model was used to screen the ZINC natural product library, followed by established computational pipeline, yielding four novel inhibitors (ZINC000150351590, ZINC000299817386, ZINC000085509805, ZINC000095911811) with strong binding affinities (− 9.43 to − 9.06 kcal/mol). Molecular dynamics simulations confirmed stable protein–ligand complexes (average RMSD < 2.5 Å), while MM/PBSA analysis showed favorable binding free energies (− 56.7 to − 49.2 kcal/mol). Conclusion Evaluation of docking performance, stability, and binding energetics using MM/PBSA enabled the identification of four natural inhibitors of α-syn aggregation. These compounds represent promising leads for further investigation in Parkinson’s disease drug discovery.