Peptide-HLA Molecule Modeling Benchmark.

<p>A set of 50 unique p-HLA complexes from the PDB was used to benchmark our modeling methodology. For each complex, the bound peptides were removed and then redocked back in to the HLA molecule. The RMSD between our solution and the experimental model is shown for the all-atom complex and the backbone-only atoms. Using each sequence, an <i>ab initio</i> three-dimensional model of each peptide was constructed. The <i>ab initio</i> peptide was then docked to the HLA molecule. The RMSD between our solution and the experimental model is shown for the all-atom and backbone-only complexes.</p

Predicting HLA Class I Non-Permissive Amino Acid Residues Substitutions

<div><p>Prediction of peptide binding to human leukocyte antigen (HLA) molecules is essential to a wide range of clinical entities from vaccine design to stem cell transplant compatibility. Here we present a new structure-based methodology that applies robust computational tools to model peptide-HLA (p-HLA) binding interactions. The method leverages the structural conservation observed in p-HLA complexes to significantly reduce the search space and calculate the system’s binding free energy. This approach is benchmarked against existing p-HLA complexes and the prediction performance is measured against a library of experimentally validated peptides. The effect on binding activity across a large set of high-affinity peptides is used to investigate amino acid mismatches reported as high-risk factors in hematopoietic stem cell transplantation.</p> </div

Peptide Binding Prediction Performance.

<p>The performance of our docking methodology to predict binding peptides is measured using a subset of nearly 6,000 peptides from the IEDB repository of HLA-A*02∶01 epitope binding affinity data. For our approach, the area under the ROC curve is 0.771 (A). The prediction accuracy is measured at varying cutoff thresholds of calculated ΔΔG values (B). The distribution densities of the calculated ΔΔG values for the positive (green) and negative (red) peptides are shown (C).</p

Structure of the HLA*A2∶01 Molecule.

<p>The structure of the HLA-A*02∶01 (PDB id = 1AKJ) molecule shown with bound peptide backbone (chain C, orange). The positions of the five high-risk residues on the HLA molecule are represented by a blue sphere and labeled. The molecular surface of the molecule is shown in gray.</p

Variability of Peptides Bound to HLA Molecules.

<p>The structural variability at each residue position for bound nonameric peptides in p-HLA complexes from the PDB. After a structural alignment of the HLA molecules, the peptide coordinates were extracted. The aligned peptides are depicted from the side view (b and d) and top (looking down into the binding groove) view (c and e), both with and without side chains. The backbone-only models are shown in B (side view) and C (top-down view). The alignments with the side chains are shown in D (side view) and E (top-down view). The Cα atoms are shown as black spheres. The pairwise RMSD was calculated between the backbone atoms at each residue position for each peptide. The peptides are colored uniquely and, for reference, the Cα atoms from a peptide (PDB id = 1AKJ, chain = C) are shown as black spheres. The results are summarized as a boxplot showing the median, quartiles, maximum and minimum distances, and outliers (circles) at each residue position.</p

Effect of High-Risk Amino Acid Substitutions on Binding Predictions.

<p>The distribution of calculated ΔΔG values for each of the 35 structural models from the five non-permissive substitutions are shown as violin plots. The plots are colored according to the Blosum62 amino acid substitution matrix, typically used for scoring evolutionary divergent protein sequences based on local alignment <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041710#pone.0041710-Luo1" target="_blank">[52]</a>. The colors are scaled according to the matrix’s log odds values, with green representing high frequency substitutions and red representing low frequency substitutions. Each plot highlights the percentage of peptides that are predicted to no longer bind as a result of the substitution in red. Those peptides predicted to retain their binding activity remain in gray.</p

Reported High-Risk Amino Acid Residue Substitutions.

<p>Non-permissive residues between patient and donor HLA antigens or alleles reported to have deleterious outcomes in HCT <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041710#pone.0041710-Ferrara1" target="_blank">[45]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041710#pone.0041710-Kawase1" target="_blank">[46]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041710#pone.0041710-Kawase2" target="_blank">[47]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041710#pone.0041710-Marino1" target="_blank">[48]</a>. The observed residues from all known HLA-A alleles at each position are listed as along with their relative orientation in the binding groove. The residue types were obtained from sequence alignments from the IMGHT using A*01∶01∶01∶01 as the reference sequence. The peptide residues in proximity for making contacts to HLA are listed for each residue.</p

Conservation of the HLA Peptide Binding Groove.

<p>The structural conservation of the peptide binding groove was measured by performing a superposition of 50 unique p-HLA complexes from the PDB. The pairwise RMSD was calculated between the backbone atoms at each solvent accessible residue comprising the binding groove <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041710#pone.0041710-Binkowski1" target="_blank">[4]</a>. The results are summarized as a boxplot showing the median, quartiles, maximum and minimum distances, and outliers (circles) at each residue position. The colors are scaled from green to red (lowest to highest RMSD) with minimum values of 0.28 Å (residue 9) and maximum of 0.83 Å (residue 58). For contrast, the non-binding groove residues are colored black. The average RMSDs are color mapped on to the HLA molecule shown as surface representation (b) and cartoon representation (c) from green (low RMSD) to red (high RMSD).</p

<i>Bacillus anthracis</i> Inosine 5′-Monophosphate Dehydrogenase in Action: The First Bacterial Series of Structures of Phosphate Ion‑, Substrate‑, and Product-Bound Complexes

Inosine 5′-monophosphate dehydrogenase (IMPDH) catalyzes the first unique step of the GMP branch of the purine nucleotide biosynthetic pathway. This enzyme is found in organisms of all three kingdoms. IMPDH inhibitors have broad clinical applications in cancer treatment, as antiviral drugs and as immunosuppressants, and have also displayed antibiotic activity. We have determined three crystal structures of <i>Bacillus anthracis</i> IMPDH, in a phosphate ion-bound (termed “apo”) form and in complex with its substrate, inosine 5′-monophosphate (IMP), and product, xanthosine 5′-monophosphate (XMP). This is the first example of a bacterial IMPDH in more than one state from the same organism. Furthermore, for the first time for a prokaryotic enzyme, the entire active site flap, containing the conserved Arg-Tyr dyad, is clearly visible in the structure of the apoenzyme. Kinetic parameters for the enzymatic reaction were also determined, and the inhibitory effect of XMP and mycophenolic acid (MPA) has been studied. In addition, the inhibitory potential of two known <i>Cryptosporidium parvum</i> IMPDH inhibitors was examined for the <i>B. anthracis</i> enzyme and compared with those of three bacterial IMPDHs from <i>Campylobacter jejuni</i>, <i>Clostridium perfringens</i>, and <i>Vibrio cholerae</i>. The structures contribute to the characterization of the active site and design of inhibitors that specifically target <i>B. anthracis</i> and other microbial IMPDH enzymes