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Background <p>The development of new drugs through structural bioinformatics plays a crucial role in the pharmaceutical industry, aiming to reduce both the cost and time required for drug development. Psoriasis is a chronic autoimmune skin disease with complex etiology for which new therapeutic options are needed. This study presents an in silico pipeline combining large-scale virtual screening and bioisosterism. This methodological integration allows not only the identification but also the chemical refinement of lead compounds, addressing both binding efficacy and predicted toxicity.</p> Methods <p>A comprehensive pipeline was developed for the identification of potential drug candidates targeting five key proteins (A2Ar, BTK, P38-MAPK, PAD-4 and TNF- α) involved in psoriatic symptomatology. Initially, a systematic review was conducted to identify studies that had employed drug repositioning for these target proteins in psoriasis. Subsequently, protein structures were retrieved from the Protein Data Bank, and 80,617 ligands derived from natural products were obtained from Zinc20. Virtual screening was applied by analyzing binding energies and molecular interactions with AutoDock Vina. Additionally, the evaluation of absorption, distribution, metabolism, excretion, and toxicity (ADME-Tox) properties was conducted using the pkCSM server to ensure drug-like behavior. When necessary, molecular optimization through bioisosterism was performed using MB-Isoster software.</p> Results <p>We identified eight potential compounds capable of targeting the A2Ar, BTK, P38-MAPK, PAD-4, and TNF-α receptors. These compounds exhibited binding energies superior to those of the respective controls for each receptor, interacting with the same amino acids and displaying ADME-Tox properties, making them promising candidates for further evaluation in the context of human therapeutic applications.</p> Discussion <p>This study aimed to identify safer and more effective treatments for psoriasis using a computational pipeline that combines virtual screening and bioisosterism. This pipeline is among the first to systematize this dual approach for psoriasis-related targets and offers potential for broader drug repurposing applications. The analysis revealed that the selected compounds exhibited adequate binding energies, favorable molecular interactions, and ADME-Tox profiles with a low risk of side effects. The study highlights the potential of bioisosterism in the development of new drugs, advancing knowledge in the search for therapeutic options for psoriasis and other diseases.</p>

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Virtual screening and bioisosterism of natural products for targeting A2Ar, BTK, P38-MAPK, PAD-4, and TNF-α in psoriatic symptomatology modulation

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月25日

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  • Leonardo Pereira de Araújo,
  • Evandro Neves Silva,
  • Patrícia Paiva Corsetti,
  • Carlos Alberto Tagliati,
  • Nelson José Freitas da Silveira,
  • Leonardo Augusto de Almeida

摘要

Background

The development of new drugs through structural bioinformatics plays a crucial role in the pharmaceutical industry, aiming to reduce both the cost and time required for drug development. Psoriasis is a chronic autoimmune skin disease with complex etiology for which new therapeutic options are needed. This study presents an in silico pipeline combining large-scale virtual screening and bioisosterism. This methodological integration allows not only the identification but also the chemical refinement of lead compounds, addressing both binding efficacy and predicted toxicity.

Methods

A comprehensive pipeline was developed for the identification of potential drug candidates targeting five key proteins (A2Ar, BTK, P38-MAPK, PAD-4 and TNF- α) involved in psoriatic symptomatology. Initially, a systematic review was conducted to identify studies that had employed drug repositioning for these target proteins in psoriasis. Subsequently, protein structures were retrieved from the Protein Data Bank, and 80,617 ligands derived from natural products were obtained from Zinc20. Virtual screening was applied by analyzing binding energies and molecular interactions with AutoDock Vina. Additionally, the evaluation of absorption, distribution, metabolism, excretion, and toxicity (ADME-Tox) properties was conducted using the pkCSM server to ensure drug-like behavior. When necessary, molecular optimization through bioisosterism was performed using MB-Isoster software.

Results

We identified eight potential compounds capable of targeting the A2Ar, BTK, P38-MAPK, PAD-4, and TNF-α receptors. These compounds exhibited binding energies superior to those of the respective controls for each receptor, interacting with the same amino acids and displaying ADME-Tox properties, making them promising candidates for further evaluation in the context of human therapeutic applications.

Discussion

This study aimed to identify safer and more effective treatments for psoriasis using a computational pipeline that combines virtual screening and bioisosterism. This pipeline is among the first to systematize this dual approach for psoriasis-related targets and offers potential for broader drug repurposing applications. The analysis revealed that the selected compounds exhibited adequate binding energies, favorable molecular interactions, and ADME-Tox profiles with a low risk of side effects. The study highlights the potential of bioisosterism in the development of new drugs, advancing knowledge in the search for therapeutic options for psoriasis and other diseases.