In silico research to assist the investigation of carboxamide derivatives as potent TRPV1 antagonists

Abstract

The transient receptor potential vanilloid type 1 (TRPV1), a non-selective cation channel, is known for its essential role in the pathogenesis of various pain conditions such as nerve damage induced hyperalgesia, diabetic neuropathy and cancer pain. Therefore, TRPV1 is considered as a promising target for the development of new anti-inflammatory and analgesic drugs. In the present study, a theoretical study on the functionalities of the molecular interactions between 236 active ligands and TRPV1 was carried out, using three-dimensional quantitative structure-activity relationships (3D-QSAR), molecular docking and molecular dynamics (MD) simulation approaches. The ligand-based CoMSIA model (obtained by use of a random division method for splitting the training and test sets) exhibits optimum predictivity (Q(2) = 0.522, R(ncv)(2) = 0.935, R(pred)(2) = 0.839). The results show that the models are useful tools for the prediction of the test sets as well as newly designed structures against TRPV1 activity. In addition, to verify the rationality of the random division method for splitting the dataset, we also used a self-organizing map (SOM) division approach for establishing the QSAR models. Interestingly, the obtained optimal CoMSIA model based on the SOM division exhibits almost the same proper statistical results (Q(2) = 0.521, R(ncv)(2) = 0.929, R(pred)(2) = 0.829) as the random division-derived model, proving the reasonability of both division methods for building the models. The contour plots of molecular fields along with docking and MD simulation have identified several key structural requirements responsible for the activity. The present work provides extremely useful guidelines for future structural modifications of this class of compounds towards the development of superior TRPV1 antagonists. The new computational insights presented in this study are expected to be valuable for the guideline and development of new potent TRPV1 antagonists.

Identification of Novel and Potent Indole-Based Benzenesulfonamides as Selective Human Carbonic Anhydrase II Inhibitors: Design, Synthesis, In Vitro, and In Silico Studies

“…The ability to estimate the impact of specific amino acid mutations on the ligand’s activity profile is another utility of molecular docking studies [ 24 ]. Additionally, visualizing the docking study’s resulting interactions aids future ligand modification, resulting in molecules with better affinity properties [ 25 ]. Accordingly, a molecular docking study for synthesized hybrid compounds was performed for hCA isozymes I, II and IX to correlate the structural characteristics with the inhibitory activity and investigate the binding modes of the synthesized hybrids.…”

Computational Study Exploring the Interaction Mechanism of Benzimidazole Derivatives as Potent Cattle Bovine Viral Diarrhea Virus Inhibitors

“…For exploring the positional conformational variations in the ligand of the binding pocket, hydrogen-bonding interactions with the main native contacts in both MD and docking simulations were compared (Figure ). As seen from Figure , a total of three H-bonds appeared in both simulation systems for the protein–ligand complex. In docking simulation, a backbone H-bond is observed with Tyr553, whereas in MD simulation, a side chain H-bond is noted with the same residue.…”

Mechanism Exploration of Arylpiperazine Derivatives Targeting the 5-HT2A Receptor by In Silico Methods

“…Unlike molecular docking, which regards proteins as relatively rigid structures and neglects their conformational flexibility, MD simulations computationally probe the dynamics and structure of biological macromolecules and seem more reliable with a view to the protein flexibility, providing the atomic-level changes of the docked complex structure [ 57 , 58 ]. In this work, the docked complex of 5-HT 2A receptor as starting molecular structure was further used to undertake a 50,000 ps MD simulation in a DOPC lipid bilayer to explore the dynamical image of the conformational diversity of the ligand binding to the receptor.…”