New tight-binding BH3 peptides.

<p>Sequence logos and multiple-sequence alignments constructed using BH3 motifs from known BH3-only/pro-apoptotic effector Bcl-2 family proteins or tight binders (K_D<500 nM) from this study. Highly conserved positions 3a and 3e are colored red. The position of the first residue of the peptide in the full-length protein follows the protein name.</p

Structures of domains containing known and predicted BH3 peptides.

<p>The putative BH3 is shown in red. For Bak, Bax, Bid, POFUT2, TRPM7, PCNA, MINA, DDX4 (<i>Drosophila</i>), CASP3 and BCAR1, the structure shown is the structure of the predicted BH3-containing protein. Other BH3 motifs are highlighted in the structure of the closest CDD hit to the parent protein (domain in non-bold type). All PDB IDs are listed in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003693#pcbi.1003693.s007" target="_blank">Table S5</a>.</p

Predicting peptide binding to the 5 Bcl-2 receptors.

<p>The first benchmark (A) included 366 interactions (K_D<1 µM) and non-interactions (K_D>10 µM). Four models were evaluated with respect to their ability to correctly classify each example, as a function of the score cutoff used for prediction. The second benchmark (B) included 180 comparisons of one receptor binding a peptide (K_D<1 µM) and another receptor not binding that same peptide (K_D>10 µM). The difference in scores for a peptide binding to two receptors was used to predict the binding preference, and agreement with experiment was evaluated as a function of the score difference cutoff. The “PSSM_SPOT+STATIUM_SC” score is the average of the Z-scores of the two models for a given receptor. Values in parentheses report the area under the curve (AUC) for each method. For details, see the <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003693#s4" target="_blank">Methods</a> section.</p

Peptide Ligands for Pro-survival Protein Bfl‑1 from Computationally Guided Library Screening

Pro-survival members of the Bcl-2 protein family inhibit cell death by binding short helical BH3 motifs in pro-apoptotic proteins. Mammalian pro-survival proteins Bcl-x_L, Bcl-2, Bcl-w, Mcl-1, and Bfl-1 bind with varying affinities and specificities to native BH3 motifs, engineered peptides, and small molecules. Biophysical studies have determined interaction patterns for these proteins, particularly for the most-studied family members Bcl-x_L and Mcl-1. Bfl-1 is a pro-survival protein implicated in preventing apoptosis in leukemia, lymphoma, and melanoma. Although Bfl-1 is a promising therapeutic target, relatively little is known about its binding preferences. We explored the binding of Bfl-1 to BH3-like peptides by screening a peptide library that was designed to sample a high degree of relevant sequence diversity. Screening using yeast-surface display led to several novel high-affinity Bfl-1 binders and to thousands of putative binders identified through deep sequencing. Further screening for specificity led to identification of a peptide that bound to Bfl-1 with <i>K</i>_d < 1 nM and very slow dissociation from Bfl-1 compared to other pro-survival Bcl-2 family members. A point mutation in this sequence gave a peptide with ∼50 nM affinity for Bfl-1 that was selective for Bfl-1 in equilibrium binding assays. Analysis of engineered Bfl-1 binders deepens our understanding of how the binding profiles of pro-survival proteins differ and may guide the development of targeted Bfl-1 inhibitors

Prediction and validation of BH3-like peptides.

<p>Proteins from the Human Protein Reference Database were scanned in 23-residue windows, sequentially aligning each window with the [abcdefg]_n heptad definition of a BH3 motif, as defined in the figure. Sequences were then filtered for amino-acid composition to give ∼600,000 candidate peptide sequences to be evaluated <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003693#pcbi.1003693-KeshavaPrasad1" target="_blank">[46]</a>. Each sequence was scored with STATIUM, STATIUM_SC, and PSSM_SPOT models for binding to each of the 5 prosurvival proteins Bcl-x_L, Bcl-w, Bcl-2, Mcl-1 and Bfl-1 (15 scores in all, for each sequence), and candidate BH3-like sequences with good scores were selected for testing on SPOT arrays, as described in the <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003693#s4" target="_blank">Methods</a>. A subset of peptides with successful negative controls on the SPOT arrays was tested for binding in solution. PSSM_SPOT cartoon is for demonstration: See <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003693#s4" target="_blank">Methods</a> for the references to data used to derive the model.</p

Bcl-2 receptor binding profiles of 36 BH3-like peptides from human proteins.

<p>Binding profiles for known BH3 peptides interacting with Bcl-x_L, Bcl-w, Bcl-2, Mcl-1 and Bfl-1, measured by Certo et al., are in the left panel <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003693#pcbi.1003693-Certo1" target="_blank">[10]</a>. 34 peptides identified in this study with K_D<10⁴ nM for binding to at least one of five prosurvival proteins are in the right panel; these are ordered from left to right according to binding affinity, as indicated in the greyscale key. See <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003693#pcbi.1003693.s005" target="_blank">Table S3</a> for the K_D values used for binning and 95% confidence intervals.</p

Benchmark of existing methods for predicting coiled-coil specificity.

<p>Experimentally determined K_d values were compared to predicted scores using two tests: the Pearson correlation coefficient (R) and the area under the curve (AUC). The Pearson correlation coefficient is reported only for interactions with 1 nM < K_d < 5,000 nM. In the AUC test, the interactions were divided into two classes: strong interactions (K_d < 250 nM) and weak/non-interactions (K_d ≥ 5,000 nM). The number of interactions used in each test is given in parentheses at the top of each column.</p><p>^a Vinson and colleagues measured coupling energies for pairs of residues in <b>a_i</b>-<b>a<i>'</i>_i</b> and <b>g_i</b>-<b>e<i>'</i>_i+1</b> positions. An additional empirical coupling energy of -2 kcal/mol for Leu-Leu interaction at <b>d_i</b>-<b>d<i>'</i>_i</b> positions was added to account for these strongly stabilizing interactions, as in [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004046#pcbi.1004046.ref016" target="_blank">16</a>].</p><p>Benchmark of existing methods for predicting coiled-coil specificity.</p

Designed bZIP-binding peptides inhibit interactions of native bZIP dimers.

<p>(A) JUN-d1 inhibits the interaction of 10 nM JUN with 50 nM FOS with an IC₅₀ of 245 nM at 37°C. (B) XBP1-d1 inhibits the interaction of 10 nM XBP1 with 50 nM CREBZF with an IC₅₀ of 136 nM at 23°C. (C) ATF4-d1 inhibits the interaction of 10 nM ATF4 with 200 nM FOS with an IC₅₀ of 279 nM at 37°C. The dissociation constants at the indicated temperatures are K_d ≤ 1 nM for FOS-JUN, K_d ≤1 nM for XBP1-CREBZF, and K_d = 60 nM for ATF4-FOS, according to [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004046#pcbi.1004046.ref018" target="_blank">18</a>]. Fluorescence intensities were measured at both 37°C and 23°C, and the IC₅₀ value was fit and reported for the highest temperature that gave a well-defined lower baseline. The target bZIP in each complex was labeled with the FRET donor (fluorescein), the partner was labeled with the TAMRA FRET acceptor, and the design was unlabeled. Fluorescence emission was monitored at 525 nm and is reported in relative fluorescence units.</p

Specificity profiles of four designs tested at 37°C.

<p>The designed binders interact strongly with their targets as rhodamine-labeled peptides (bold red circles). Thin red circles show interactions with other bZIPs in the same family as the target. The ATF5-d1 design bound more tightly to ATF4 (thin red circle) than to ATF5. The designed proteins do not form strong homodimers (black bars), and there are large specificity gaps between the design/target interactions and design/off-target interactions (white and grey bars, colored according to target-off-target sequence identity at <b>a</b>, <b>d</b>, <b>e</b> and <b>g</b> positions). All K_d values are listed in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004046#pcbi.1004046.s011" target="_blank">S5</a>–<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004046#pcbi.1004046.s018" target="_blank">S12</a> Tables.</p

Performance of predictive models using different sets of residue interactions.

<p>The predictive models were optimized using the combined set of interactions and evaluated with nested cross-validation as described in the Methods. The residue interactions used to describe the coiled-coil interaction were varied as descried in the text. We also applied recursive feature elimination to find a smaller subset of key features that retained good prediction performance. The reduced number of features, and the model performance with this number of features, are given in parentheses.</p><p>Performance of predictive models using different sets of residue interactions.</p