Additional file 1: Table S1. of The use of novel selectivity metrics in kinase research

Ranking of the different metrics computed for the Ambit dataset. Table S2. Ranking of the different metrics computed for the Reaction Biology dataset. Table S3. Ranking of the different metrics computed for the shared compounds between Ambit dataset (A) and Reaction Biology dataset (B). Table S4. Ranking of the different metrics computed for the compounds tested in the NCI-60 assay. (DOCX 184 kb

Prediction of Protein Kinase–Ligand Interactions through 2.5D Kinochemometrics

So far, 518 protein kinases have been identified in the human genome. They share a common mechanism of protein phosphorylation and are involved in many critical biological processes of eukaryotic cells. Deregulation of the kinase phosphorylation function induces severe illnesses such as cancer, diabetes, or inflammatory diseases. Many actors in the pharmaceutical domain have made significant efforts to design potent and selective protein kinase inhibitors as new potential drugs. Because the ATP binding site is highly conserved in the protein kinase family, the design of selective inhibitors remains a challenge and has negatively impacted the progression of drug candidates to late-stage clinical development. The work presented here adopts a 2.5D kinochemometrics (KCM) approach, derived from proteochemometrics (PCM), in which protein kinases are depicted by a novel 3D descriptor and the ligands by 2D fingerprints. We demonstrate in two examples that the protein descriptor successfully classified protein kinases based on their group membership and their Asp-Phe-Gly (DFG) conformation. We also compared the performance of our models with those obtained from a full 2D KCM model and QSAR models. In both cases, the internal validation of the models demonstrated good capabilities to distinguish “active” from “inactive” protein kinase–ligand pairs. However, the external validation performed on two independent data sets showed that the two statistical models tended to overestimate the number of “inactive” pairs

Ramachandran plots of the distribution of the (φ, ψ) backbone dihedrals of residues 1–15 for peptides WT, I, R and RI, calculated over of the 50 ns REMD trajectories.

<p>Ramachandran plots of the distribution of the (φ, ψ) backbone dihedrals of residues 1–15 for peptides WT, I, R and RI, calculated over of the 50 ns REMD trajectories.</p

Peptide transformations: (a) parent peptide, (b) its inverse, (c) its sequence reversed and (d) its retro-inverso analogue.

<p>Peptide transformations: (a) parent peptide, (b) its inverse, (c) its sequence reversed and (d) its retro-inverso analogue.</p

A Proteometric Analysis of Human Kinome: Insight into Discriminant Conformation-dependent Residues

Because of the success of imatinib, the first type-II kinase inhibitor approved by the FDA in 2001, sustained efforts have been made by the pharmaceutical industry to discover novel compounds stabilizing the inactive conformation of protein kinases. On the seven type-II inhibitors having reached the market, four were released in 2012, suggesting an acceleration of the research of such a class of compounds. Still, they represent less than a third of the protein kinase inhibitors available to patients today. The identification of key residues involved in the binding of this type of ligands in the kinase active site might ease the design of potent and selective type-II inhibitors. In order to identify those discriminant residues, we have developed a proteometric approach combining residue descriptors of protein kinase sequences and biological activities of various type-II kinase inhibitors. We applied Partial Least Squares (PLS) regression to identify 29 key residues that influence the binding of four type-II inhibitors to most proteins of the kinome. The gatekeeper residue was found to be the most relevant, confirming an essential role in ligand binding as well as in protein kinase conformational changes. Using the newly developed proteometric model, we predicted the propensity of each protein kinase to be inhibited by type-II ligands. The model was further validated using an external data set of protein/ligand activity pairs. Other residues present in the kinase domain, and more specifically in the binding site, have been highlighted by this approach, but their role in biological mechanisms is still unknown

Distribution of helicity (ordinate) as a function of amino acid residue for each of sequences WT, I, R and RI (abscissa), obtained from final 20 ns of REMD simulations with <i>ff99SB</i>.

<p>Residue numbering is from N- to C-terminal direction (solid line) for <b>WT</b>, <b>I</b>, <b>R</b> and <b>RI</b>. Additionally, helicity is shown for the reverse residue numbering ie. from C- to N-terminus for <b>R</b> and <b>RI</b> (dashed line).</p

Average interatomic distances <i>d₁</i> (Phe¹⁹-Trp²³), <i>d₂</i> (Trp²³-Leu²⁶) and <i>d₃</i> (Phe¹⁹-Leu²⁶) as defined by (<i>a</i>) α-carbons and (<i>b</i>) β-carbons from final 20 ns of REMD for sequences WT, I, R and RI.

<p>Standard deviations in parentheses. The <i>d₁</i>, <i>d₂</i> and <i>d₃</i> values from crystallographic structure of N-terminal sequence of p53 bound to MDM2 also given (PDB 1YCR <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0068723#pone.0068723-Kussie1" target="_blank">[11]</a>). All distances in Å. Population (%) of trajectory of <b>WT, I, R</b> and <b>RI</b> that satisfy <i>d₁</i>, <i>d₂</i> and <i>d₃</i> and their simultaneous combination, <i>[d₁-d₂-d₃]</i> over final 20 ns of REMD.</p

Fractional helical content (ordinate) for sequences WT, I, R and RI as a function of time (ns) (abscissa) obtained from (a) MD simulations and (b) REMD simulations: maximum helicity (dashed line) and average helicity (solid line) obtained starting from extended (E), right-handed (R) and left-handed (L) helical structures.

<p>Fractional helical content (ordinate) for sequences WT, I, R and RI as a function of time (ns) (abscissa) obtained from (a) MD simulations and (b) REMD simulations: maximum helicity (dashed line) and average helicity (solid line) obtained starting from extended (E), right-handed (R) and left-handed (L) helical structures.</p

Snapshots of the 300 K trajectory of RI taken at 0, 10, 20, 30, 40 and 50 ns starting from an extended (E), right-handed (R) and left-handed (L) helical structure.

<p>Each configuration is ordered from N- to C-terminus.</p

Intramolecular polar contacts.

<p>(a) A helical conformation of <b>WT</b> when Lys10 N<u>H</u>^…Ser6 <u>O</u>C and Lys10 Hζ^…Asp7 Oδ hydrogen bonds are present; (b) A helical conformation of <b>R</b> when Ser10 N<u>H</u>^…Lys6 <u>O</u>C and Ser10 Hγ^…Lys6 O hydrogen bonds are present.</p