Articolo in rivista, 2022, ENG, 10.3390/ijms23126793

A Drug Discovery Approach for an Effective Pain Therapy through Selective Inhibition of Nav1.7

Gabriele A. Trombetti, Alessandra Mezzelani and Alessandro Orro

Institute for Biomedical Technologies, National Research Council (ITB-CNR), 20054 Segrate, Italy; Institute for Biomedical Technologies, National Research Council (ITB-CNR), 20054 Segrate, Italy; Institute for Biomedical Technologies, National Research Council (ITB-CNR), 20054 Segrate, Italy

Chronic pain is a widespread disorder affecting millions of people and is insufficiently addressed by current classes of analgesics due to significant long-term or high dosage side effects. A promising approach that was recently proposed involves the systemic inhibition of the voltage-gated sodium channel Nav1.7, capable of cancelling pain perception completely. Notwithstanding numerous attempts, currently no drugs have been approved for the inhibition of Nav1.7. The task is complicated by the difficulty of creating a selective drug for Nav1.7, and avoiding binding to the many human paralogs performing fundamental physiological functions. In our work, we obtained a promising set of ligands with up to 5-40-fold selectivity and reaching 5.2 nanomolar binding affinity by employing a proper treatment of the problem and an innovative differential in silico screening procedure to discriminate for affinity and selectivity against the Nav paralogs. The absorption, distribution, metabolism, and excretion (ADME) properties of our top-scoring ligands were also evaluated, with good to excellent results. Additionally, our study revealed that the top-scoring ligand is a stereoisomer of an already-approved drug. These facts could reduce the time required to bring a new effective and selective Nav1.7 inhibitor to the market.

International journal of molecular sciences (Online) 23 (12), pp. 6793–?

Keywords

in silico drug discovery, analgesia, voltage-gated sodium channel, selectivity, paralogs, pore blocking, ADME, chronic pain, monogenic pain disorders

CNR authors

Mezzelani Alessandra Maria, Orro Alessandro, Trombetti Gabriele Antonio

CNR institutes

ITB – Istituto di tecnologie biomediche

ID: 473639

Year: 2022

Type: Articolo in rivista

Creation: 2022-11-18 14:58:57.000

Last update: 2023-07-02 09:16:32.000

External IDs

CNR OAI-PMH: oai:it.cnr:prodotti:473639

DOI: 10.3390/ijms23126793