Homology Modeling of the Human P-glycoprotein (ABCB1) and Insights into Ligand Binding through Molecular Docking Studies

Abstract

The ABCB1 transporter also known as P-glycoprotein (P-gp) is a transmembrane protein belonging to the ATP binding cassette super-family of transporters; it is a xenobiotic efflux pump that limits intracellular drug accumulation by pumping the compounds out of cells. P-gp contributes to a decrease of toxicity and possesses broad substrate specificity. It is involved in the failure of numerous anticancer and antiviral chemotherapies due to the multidrug resistance (MDR) phenomenon, where it removes the chemotherapeutics out of the targeted cells. Understanding the details of the ligand–P-gp interaction is therefore crucial for the development of drugs that might overcome the MRD phenomenon and for obtaining a more effective prediction of the toxicity of certain compounds. In this work, an in silico modeling was performed using homology modeling and molecular docking methods with the aim of better understanding the ligand–P-gp interactions. Based on different mouse P-gp structural templates from the PDB repository, a 3D model of the human P-gp (hP-gp) was constructed by means of protein homology modeling. The homology model was then used to perform molecular docking calculations on a set of thirteen compounds, including some well-known compounds that interact with P-gp as substrates, inhibitors, or both. The sum of ranking differences (SRD) was employed for the comparison of the different scoring functions used in the docking calculations. A consensus-ranking scheme was employed for the selection of the top-ranked pose for each docked ligand. The docking results showed that a high number of π interactions, mainly π–sigma, π–alkyl, and π–π type of interactions, together with the simultaneous presence of hydrogen bond interactions contribute to the stability of the ligand–protein complex in the binding site. It was also observed that some interacting residues in hP-gp are the same when compared to those observed in a co-crystallized ligand (PBDE-100) with mouse P-gp (PDB ID: 4XWK). Our in silico approach is consistent with available experimental results regarding P-gp efflux transport assay; therefore it could be useful in the prediction of the role of new compounds in systemic toxicity.

Structure–Function Relationships in the Human P-Glycoprotein (ABCB1): Insights from Molecular Dynamics Simulations

“…Only the interactions observed in more than 50% of the production snapshots were considered in the analysis. The observed ligand–P-gp interactions mainly involved residues in TM1, TM4, TM5, TM6, TM12, and to a lesser extent in TM3, TM7, TM10, and TM11 (see Supplementary Materials, Figure S2 ), which is consistent with our recent docking study showing the interactions with the same TMDs [ 19 ]. Some regions that interact exclusively with the active compounds have also been identified, namely the residues near the breaking loops in TM4 (Ala229, Trp232, Leu236) and TM10 (Met876, Leu879).…”

“…The diversity of conformations in which the P-gp structure has been solved demonstrates the flexibility of the transporter [ 11 , 12 ], a property associated with its polyspecificity, i.e., the ability to bind a large number of chemically diverse compounds. Over time, numerous ligand-based models have been developed to predict the P-gp activity, such as quantitative structure–activity relationship (QSAR) models [ 13 , 14 , 15 , 16 ] and structure-based models based on molecular docking and the use of the mouse P-gp ( m P-gp) 3D structure [ 17 , 18 ], or homology models of the human P-gp ( h P-gp) [ 19 ], in which the binding modes of substrates and inhibitors have been well characterized. Nonetheless, the molecular details of the effects of these molecules on the conformational dynamics of P-gp are not well known.…”

Computational-approach understanding the structure-function prophecy of Fibrinolytic Protease RFEA1 from Bacillus cereus RSA1

“…In Mycobacterium tuberculosis H 37 Rv, Rv3906c gene was testified to exhibit glycine (17.8%) and aspartate (23.7%) rich residues using SAPS server (Beg, Thakur & Meena, 2018). The use of multiple structural modeling servers is preferred for prediction of high-quality 3D protein models (Guleria et al, 2016;Lagares et al, 2020). We have used I-TASSER, SWISS-MODEL, RaptorX and Phyre2 to model RFEA1, wherein Phyre2 server predicted superior model with 99% identity and 100% confidence with template '3whiA'.…”

Molecular Docking Simulation Studies Identifies Potential Natural Product Derived-Antiwolbachial Compounds as Filaricides against Onchocerciasis

“…Although all the top three models did not have a VERIFY score of 80% or higher, ROB2 and ITAS 1 had relatively closer values. Additionally, a previous study has shown that this quality indicator (VERIFY) performed poorly on a crystallized structure [105]. The ERRAT plot of ROB2 showed that amino acid residues 147-150, 170, 172-178, 192-194, 205 and 209 were the most erroneous parts (Figure S2).…”