Recent Advances on P-Glycoprotein (ABCB1) Transporter Modelling with In Silico Methods

Abstract

ABC transporters play a critical role in both drug bioavailability and toxicity, and with the discovery of the P-glycoprotein (P-gp), this became even more evident, as it plays an important role in preventing intracellular accumulation of toxic compounds. Over the past 30 years, intensive studies have been conducted to find new therapeutic molecules to reverse the phenomenon of multidrug resistance (MDR) ), that research has found is often associated with overexpression of P-gp, the most extensively studied drug efflux transporter; in MDR, therapeutic drugs are prevented from reaching their targets due to active efflux from the cell. The development of P-gp inhibitors is recognized as a good way to reverse this type of MDR, which has been the subject of extensive studies over the past few decades. Despite the progress made, no effective P-gp inhibitors to reverse multidrug resistance are yet on the market, mainly because of their toxic effects. Computational studies can accelerate this process, and in silico models such as QSAR models that predict the activity of compounds associated with P-gp (or analogous transporters) are of great value in the early stages of drug development, along with molecular modelling methods, which provide a way to explain how these molecules interact with the ABC transporter. This review highlights recent advances in computational P-gp research, spanning the last five years to 2022. Particular attention is given to the use of machine-learning approaches, drug–transporter interactions, and recent discoveries of potential P-gp inhibitors that could act as modulators of multidrug resistance.

Molecular Modeling Studies to Probe the Binding Hypothesis of Novel Lead Compounds against Multidrug Resistance Protein ABCB1

“…Comparatively small peaks were observed in the transmembrane regions as well as the Walker A and B regions (schematic presentation is provided is Supplementary Figure S10). The RMSF of the protein backbone showed similar behavior for all of the simulated complexes and the low movement of both nucleotide-binding domains (NBD1 and NBD2) around 3 Å that might suggest inhibition of the transport cycle [43,44], which can further be validated by ATPase assay. Thus, all four of the docked lead compounds 'A', 'D', 'E' and 'F' remained occluded in a stable binding pocket.…”

The Important Role of Transporter Structures in Drug Disposition, Efficacy, and Toxicity

“…These computational structures can be used as a complement to the experimental structures and greatly enrich the structural information of transporters. These computational structures provide an opportunity to clarify the mechanism of interaction between transporters and small molecules, reveal the pharmacophore region, binding affinity, selectively of ligands and study the mechanism of DDIs (Le et al, 2021;Namasivayam et al, 2021;Liu et al, 2022b;Mora Lagares and Novic, 2022). The ADMET properties can also be predicted based on the computational structure of ABC transporters and others to assess the pharmacokinetic properties of lead compounds or candidates (Demel et al, 2009;Yalcin-Ozkat, 2021;Yin et al, 2021).…”

Bioinformatic analysis of highly consumed phytochemicals as P-gp binders to overcome drug-resistance

“…Several researchers have focused on the in-silico modeling of phytochemicals as P-gp binders ( 4 15 ). In continuation of our previous study ( 16 ), molecular docking and functional B3LYP (Becke, 3-parameter, Lee-Yang-Parr) in association with the 6-31G (d, p) basis set have been exploited consecutively to evaluate the P-gp intermolecular interactions to a few dietary phytochemicals.…”