In silico model for P-glycoprotein substrate prediction: insights from molecular dynamics and in vitro studies

Prajapati, Rameshwar; Singh, Udghosh; Patil, Abhijeet; Khomane, Kailas S.; Bagul, Pravin; Bansal, Arvind K.; Sangamwar, Abhay T.

doi:10.1007/s10822-013-9650-x

Cited by 34 publications

(21 citation statements)

References 69 publications

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“…The crystal structure of C. elegans P-gp has been used to make homology models used in docking of anti-cancer compounds investigated by MD simulations and free energy calculations [38]. One of the compounds, NSC745689, did not show any stable interactions with the binding site, suggesting that it is not a substrate of P-gp and this was confirmed with in vitro experiments.…”

Section: Studies That Incorporated Dynamicsmentioning

confidence: 89%

Homology modelling of human P-glycoprotein

Domicevica

Biggin

2015

Biochemical Society Transactions

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P-glycoprotein (P-gp) is an ATP-binding cassette transporter that exports a huge range of compounds out of cells and is thus one of the key proteins in conferring multi-drug resistance in cancer. Understanding how it achieves such a broad specificity and the series of conformational changes that allow export to occur form major, on-going, research objectives around the world. Much of our knowledge to date has been derived from mutagenesis and assay data. However, in recent years, there has also been great progress in structural biology and although the structure of human P-gp has not yet been solved, there are now a handful of related structures on which homology models can be built to aid in the interpretation of the vast amount of experimental data that currently exists. Many models for P-gp have been built with this aim, but the situation is complicated by the apparent flexibility of the system and by the fact that although many potential templates exist, there is large variation in the conformational state in which they have been crystallized. In this review, we summarize how homology modelling has been used in the past, how models are typically selected and finally illustrate how MD simulations can be used as a means to give more confidence about models that have been generated via this approach.

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Section: Studies That Incorporated Dynamicsmentioning

confidence: 89%

Homology modelling of human P-glycoprotein

Domicevica

Biggin

2015

Biochemical Society Transactions

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“…Prajapati et al assessed molecular docking as a predictive model for P‐gp substrates using C . elegans P‐gp structure as template for a human homology model . Since the docking pose of the cocrystallized ligand showed a similar conformation and residue interactions, other molecules were docked in the active site (by choosing the active residues based on experimental data) and revealed that P‐gp interaction is mostly ruled by hydrophobic interactions with Phe343 (π–π stacking and hydrophobic) and Met949/Val981 (hydrophobic), although several HB were found with Gln347 and Tyr953.…”

Section: Structure‐based Drug Discovery In Mdrmentioning

confidence: 99%

“…Since the docking pose of the cocrystallized ligand showed a similar conformation and residue interactions, other molecules were docked in the active site (by choosing the active residues based on experimental data) and revealed that P‐gp interaction is mostly ruled by hydrophobic interactions with Phe343 (π–π stacking and hydrophobic) and Met949/Val981 (hydrophobic), although several HB were found with Gln347 and Tyr953. From this model, a new promising anticancer agent (NSC745689) is described as a possible nonsubstrate, thus circumventing P‐gp efflux. A potential binding site for phenytoin was also explored in the inward and outward‐facing conformations of a human P‐gp homology model .…”

Section: Structure‐based Drug Discovery In Mdrmentioning

confidence: 99%

Reversing cancer multidrug resistance: insights into the efflux by ABC transports from in silico studies

Ferreira

Santos

2014

WIREs Comput Mol Sci

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One of the greatest threats to cancer treatment is the development, by some tumors, of resistance to the pharmacological action of several structurally unrelated cytotoxic agents-multidrug resistance (MDR). As P-glycoprotein (P-gp) is one of the most studied ATP-dependent efflux pumps that are frequently involved in drug efflux from cancer cells, the development of MDR modulators with the ability to inhibit P-gp efflux is considered a promising approach for overcoming MDR. However, the development of P-gp modulators have been hampered due to the absence of knowledge on the intrinsic molecular aspects by which efflux occurs, namely the specific steps that correlates drug recognition, ATP binding and efflux-related conformational changes. Experimental evidences for these processes are also difficult to obtain and only provide small pieces of information that need to be assembled for better comprehension of a wider and complex process that is drug efflux. A promising alternative relies on cutting-edge computational techniques to provide new insights on key aspects that are determinant to understand how P-gp efflux can be effectively reversed. With the contribution of ligand-based or structure-based computational methods, P-gp drug efflux is slowly becoming a dynamic and reactive process rather than a simple response to drug binding, with the complex architecture of ABC transporters playing a determinant role not only in drug recognition but in the coordination of ATP-driven conformational changes that ultimately drives drug efflux. The major enlightenments that computational studies provided toward a better comprehension of MDR and P-gp efflux phenomena are hereby described.The demographic effect of this pathology on the general population, especially in the industrialized countries, is becoming severely affected by a rapid increase in the number of new cancers (Figure 1). It is estimated that by 2030 the number of new cases (excluding nonmelanoma skin cancer) will grow 32.8% (more than 21 million), with an estimated increase of 34.6% (1.3 million) in the total number of deaths. 2,3 Thus, new and improved chemotherapy regimens are needed to counterweight such predictions. However, cancer therapy evolution is directly related to a greater knowledge on the basic molecular mechanisms Volume 5, January/February 2015 Although the above structures contributed to a better comprehension of the ABC exporters' topology, a Volume 5, January/February 2015

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“…27,28 Furthermore, it was suggested that the crystal structure of C. elegans had more reliable orientation in those helices. 27 However, we suspected that the probable errors driven by some residue orientation incompatibilities in the mP-gp crystal structure were not large enough to disrupt the inhibitor docking simulations for following reasons; The identity and similarity between mP-gp and hP-gp are 87% and 94.2%, respectively, while those between C. elegans P-gp and hP-gp are 43.8% and 65.2%, respectively.…”

mentioning

confidence: 99%

In silico Study on the Interaction between P-glycoprotein and Its Inhibitors at the Drug Binding Pocket

Namseok

Shin

No³

2014

Bulletin of the Korean Chemical Society

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P-glycoprotein (P-gp) is a member of the ATP-Binding Cassette transporter superfamily and mediates transmembrane efflux of many drugs. Since it is involved in multi-drug resistance activity in various cancer cells, the development of P-gp inhibitor is one of the major concerns in anticancer therapy. Human P-gp protein has at least two "functional" drug binding sites that are called "H" site and "R" site, hence it has multi-bindingspecificities. Though the amino acid residues that constitute in drug binding pockets have been proposed by previous experimental evidences, the shapes and the binding poses are not revealed clearly yet. In this study, human P-gp structure was built by homology modeling with available crystal structure of mouse P-gp as a template and docking simulations were performed with inhibitors such as verapamil, hoechst33342, and rhodamine123 to construct the interaction between human P-gp and its inhibitors. The docking simulations were performed 500 times for each inhibitor, and then the interaction frequency of the amino acids at the binding poses was analyzed. With the analysis results, we proposed highly contributing residues that constitute binding pockets of the human P-gp for the inhibitors. Using the highly contributing residues, we proposed the locations and the shapes of verapamil binding site and "R" site, and suggested the possible position of "H" site.

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In silico model for P-glycoprotein substrate prediction: insights from molecular dynamics and in vitro studies

Cited by 34 publications

References 69 publications

Homology modelling of human P-glycoprotein

Homology modelling of human P-glycoprotein

Reversing cancer multidrug resistance: insights into the efflux by ABC transports from in silico studies

In silico Study on the Interaction between P-glycoprotein and Its Inhibitors at the Drug Binding Pocket

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