Acoplamiento de Grandes Bibliotecas para Polifarmacología

Área de la Ciencia:

• Computational chemistry
• Pharmacology
• Drug discovery

Sus antecedentes:

• Polypharmacology, the simultaneous targeting of multiple biological targets, offers a promising strategy for treating complex diseases.
• Identifying molecules with joint activity against specific target pairs is crucial for developing effective multi-target therapies.

Objetivo del estudio:

• To explore the utility of large library docking for discovering dual-activity molecules against selected target pairs.
• To identify potential analgesic compounds through prospective docking against alpha2A/SERT, MOR/SERT, and alpha2A/MOR targets.

Principales métodos:

• Retrospective analysis of library growth and dual-activity molecule identification.
• Prospective virtual screening of a 900-million molecule library using docking against three target pairs.
• Confirmation of docking-predicted poses using cryo-electron microscopy (cryo-EM) structures.
• In vivo evaluation of compound efficacy in mouse behavioral assays.

Principales resultados:

• Docking campaigns identified dual binders with low μM to high nM activities and high hit rates for alpha2A/SERT and SERT/MOR targets.
• Tetrahydropyridine compounds from the alpha2A/SERT campaign also exhibited activity against 5-HT2A.
• Cryo-EM confirmed docking-predicted poses, but subsequent optimization faced challenges in improving potency.
• The lead alpha2A/SERT compound (z7149) demonstrated efficacy in pain assays without conditioned place preference, and exhibited antidepressant and anxiolytic-like behavior.

Conclusiones:

• Large library docking is a viable strategy for discovering polypharmacological agents, yielding promising hits for complex conditions.
• Despite structural validation, optimizing the potency of identified dual-activity molecules presents significant challenges.
• The study highlights both the potential and limitations of computational docking in advancing polypharmacology for therapeutic benefit.