Structure-Based Virtual Screening Identifies Novobiocin, Montelukast, and Cinnarizine as TRPV1 Modulators with Anticonvulsant Activity In Vivo

Abstract

The transient receptor potential vanilloid 1 (TRPV1) receptor is a nonselective cation channel, known to be involved in the regulation of many important physiological and pathological processes. In the last few years, it has been proposed as a promising target to develop novel anticonvulsant compounds. However, thermoregulatory effects associated with the channel inhibition have hampered the path for TRPV1 antagonists to become marketed drugs. In this regard, we conducted a structure-based virtual screening campaign to find potential TRPV1 modulators among approved drugs, which are known to be safe and thermally neutral. To this end, different docking models were developed and validated by assessing their pose and score prediction powers. Novobiocin, montelukast, and cinnarizine were selected from the screening as promising candidates for experimental testing and all of them exhibited nanomolar inhibitory activity. Moreover, the in vivo profiles showed promising results in at least one of the three models of seizures tested.

Comprehensive Survey of Consensus Docking for High-Throughput Virtual Screening

“…Even though different approaches have been developed to obtain the consensus results from individual docking programs, there is currently no consensus procedure that stands out from the rest of methods. Nevertheless, from the quantitative viewpoint, the analyzed studies strongly support that VS consensus docking can be efficiently used for discovering new hit compounds [112][113][114][115][116][117][118][119][120]122]. The main objection to the consensus approach is probably the computational time, as the compound libraries must be calculated with all docking procedures.…”

“…In addition, the performance of VS was shown to greatly vary for the different structural conformations of the proteins, which implies the selection and elimination of structures with the worst performance in the ensemble [112,113]. In the last two decades, several studies have been conducted to evaluate and compare the performance of different docking software on the same systems using known databases of binders and non-binders and using structure ensembles when available [112][113][114][115][116][117][118][119][120][121][122].…”

“…Recently, Llanos et al performed a structure-based VS on TRPV1 to find potential modulators among approved drugs without thermoregulatory side-effects. Using several TRPV1 structures, they assessed the pose and scoring prediction power to discover three promising candidates for experimental testing [120]. Nonetheless, the worst-performing structure these authors obtained was the capsaicin-derived one, similar to that used in the example.…”

Multidisciplinary Advances Address the Challenges in Developing Drugs against Transient Receptor Potential Channels to Treat Metabolic Disorders

“…It has identified Novobiocin, montelukast, and cinnarizine that potently antagonized TRPV1 activity and exhibited anticonvul-sant activity in vivo. [92] The first step of the strategy included the validation of different constructed and refined homology models of TRPV1. Therefore, the optimal docking conditions for virtual screening was established.…”

Descubrimiento de nuevos anticonvulsivos que actúan mediante interacciones con canales iónicos

“…Analizando conjuntamente las validaciones de docking power, scoring power y screening power, se decidió que el mejor modelo consiste el dockear los compuestos con el programa QVina2, utilizando el modelo por homología derivado del molde apo (5IRZ), y luego como post-procesamiento el re-scoring con Smina utilizando la función de puntuación ad4, considerando las cadenas laterales a menos de 3 Å de cada ligando como flexibles. Las coordenadas atómicas de este modelo en formato PDB se encuentran disponibles en la sección suplementaria de la publicación correspondiente (Llanos et al 2022).…”