Different binding modes for ErbB2 bound to lapatinib.

<p>Two dimensional χ-angle plot for Arg849 (χ4) and the dihedral angle in lapatinib comprising the rotation along C5 and the sulphure atom at the methylsulfonyl group for the binder and looser conformations explored in the triplicate simulations for the system. Conformations are color-coded with respect to these two different populations and following the scheme in previous figures. Representative structures of Arg849 and Ser728 sidechains and their interactions with lapatinib are shown inside the plot, with hydrogen bonds indicated by dark blue dashed lines. Different conformers observed along the dihedral angle in lapatinib are shown on top of the plot; they are the equivalent to the so called gauche-, trans and gauche+ conformations; they correspond to the clusters near −60°, 180° and 60° in the main plot.</p

Literature reported mutations confering resistance towards lapatinib in EGFR and ErbB2.

<p>Genomic location of these mutations in the tyrosine kinase (TK) domain of EGFR (A) and ErbB2 (B). The list of mutations have been extracted from literature for both EGFR <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0077054#pone.0077054-Gilmer1" target="_blank">[16]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0077054#pone.0077054-Avizienyte1" target="_blank">[17]</a> and for ErbB2 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0077054#pone.0077054-Kancha1" target="_blank">[18]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0077054#pone.0077054-Trowe1" target="_blank">[19]</a>. These mutations have been mapped on the three-dimensional structures of EGFR (C) and ErbB2 (D).</p

Residue-wise contribution estimated by <i>in silico</i> alanine scanning for the systems analysed in this study (Table S1).

<p>The coloured boxes on the top part of the plots represent key secondary structure elements in the kinase architecture (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0077054#pone-0077054-g004" target="_blank">Figure 4A</a>). The graphs in red correspond to the tighter binding mode while the blue ones are for the identified subpopulations with a lesser interaction or looser binding mode. The regions showing a distinct binding energy for these two modes have been marked with boxes.</p

<i>In silico</i> predicted resistance mutations.

<p>The normalized values of the residuewise contribution to the binding energy are shown for EGFR and ErbB2 (A). Those residues to the left of the 0 line are involved in the binding of ATP, while the ones to the right contribute to the binding of lapatinib. The colored boxes follows the same color scheme than in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0077054#pone-0077054-g004" target="_blank">Figure 4</a>, with the exception of the hinge region that here is combined with the regions that make up the adenine pocket. The position of those residues on the three-dimensional structures of EGFR (B) and ErbB2 (C) have been mapped. The residues important in the binding of ATP are colored in red, while the ones involved in the binding of lapatinib are colored in blue. For reference, the experimental-based resistance mutations are shown in red stars in (A), and with spheres in (B) and (C).</p

Molecular interactions monitored during the simulations of EGFR and ErbB2 bound to ATP and lapatinib.

<p>Molecular interactions monitored during the simulations of EGFR and ErbB2 bound to ATP and lapatinib.</p

Time series for the total binding energy for EGFR in association with ATP (A) and lapatinib (C), and the same inhibitor-protein systems for ErbB2, panels B for the interaction with ATP and D for the lapatinib one.

<p>Time series for the total binding energy for EGFR in association with ATP (A) and lapatinib (C), and the same inhibitor-protein systems for ErbB2, panels B for the interaction with ATP and D for the lapatinib one.</p

Pharmacophore architecture and description of the ATP binding pocket.

<p>ATP binds to a deep cleft situated between the N- and C-lobes of the protein kinase (A). In general, the ATP binding pocket can be divided into several regions that they form a continuos space with residues that belong to the hinge region (in green), P-loop (in orange), αC-helix (in pink) and activation loop (in brown). The selectivity pocket (in blue) and hydrophobic pockets I (in gray) and II (in yellow) are highlighted. Schematic 2D representation of the binding modes of lapatinib with EGFR (B) and ErbB2 (C) are depicted.</p

Different binding modes for ErbB2 bound to ATP.

<p>(A) Global kinase conformation for the looser (picture on the left) and the tighter (picture of right) binding modes. The color scheme is the same that described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0077054#pone-0077054-g004" target="_blank">Figure 4A</a>) Two dimensional plot of the Φ and ω3 angles of ATP, where isolines represent the 2D kernel density estimation as calculated using an axis-aligned bivariate normal kernel evaluated on a square grid. Different rotameric states of ATP lead to a different interaction profile with neighbouring residues in the pocket.</p

Individual energy components for the estimated binding energies for the interaction of ATP and lapatinib with EGFR and ErbB2 calculated with MM-GBSA method.

<p>The values represent the average and standard deviation for the different populations observed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0077054#pone-0077054-g002" target="_blank">Figure 2</a>. The values are given in kcal/mol.</p

Macrostate Identification from Biomolecular Simulations through Time Series Analysis

This paper builds upon the need for a more descriptive and accurate understanding of the landscape of intermolecular interactions, particularly those involving macromolecules such as proteins. For this, we need methods that move away from the single conformation description of binding events, toward a descriptive free energy landscape where different macrostates can coexist. Molecular dynamics simulations and molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) methods provide an excellent approach for such a dynamic description of the binding events. An alternative to the standard method of the statistical reporting of such results is proposed