Rigorous Computational and Experimental Investigations on MDM2/MDMX-Targeted Linear and Macrocyclic Peptides

There is interest in peptide drug design, especially for targeting intracellular protein–protein interactions. Therefore, the experimental validation of a computational platform for enabling peptide drug design is of interest. Here, we describe our peptide drug design platform (CMDInventus) and demonstrate its use in modeling and predicting the structural and binding aspects of diverse peptides that interact with oncology targets MDM2/MDMX in comparison to both retrospective (pre-prediction) and prospective (post-prediction) data. In the retrospective study, CMDInventus modules (CMDpeptide, CMDboltzmann, CMDescore and CMDyscore) were used to accurately reproduce structural and binding data across multiple MDM2/MDMX data sets. In the prospective study, CMDescore, CMDyscore and CMDboltzmann were used to accurately predict binding affinities for an Ala-scan of the stapled α-helical peptide ATSP-7041. Remarkably, CMDboltzmann was used to accurately predict the results of a novel D-amino acid scan of ATSP-7041. Our investigations rigorously validate CMDInventus and support its utility for enabling peptide drug design

Volume-based solvation models out-perform area-based models in combined studies of wild-type and mutated protein-protein interfaces

<p>Abstract</p> <p>Background</p> <p>Empirical binding models have previously been investigated for the energetics of protein complexation (ΔG models) and for the influence of mutations on complexation (i.e. differences between wild-type and mutant complexes, ΔΔG models). We construct binding models to directly compare these processes, which have generally been studied separately.</p> <p>Results</p> <p>Although reasonable fit models were found for both ΔG and ΔΔG cases, they differ substantially. In a dataset curated for the absence of mainchain rearrangement upon binding, non-polar area burial is a major determinant of ΔG models. However this ΔG model does not fit well to the data for binding differences upon mutation. Burial of non-polar area is weighted down in fitting of ΔΔG models. These calculations were made with no repacking of sidechains upon complexation, and only minimal packing upon mutation. We investigated the consequences of more extensive packing changes with a modified mean-field packing scheme. Rather than emphasising solvent exposure with relatively extended sidechains, rotamers are selected that exhibit maximal packing with protein. This provides solvent accessible areas for proteins that are much closer to those of experimental structures than the more extended sidechain regime. The new packing scheme increases changes in non-polar burial for mutants compared to wild-type proteins, but does not substantially improve agreement between ΔG and ΔΔG binding models.</p> <p>Conclusion</p> <p>We conclude that solvent accessible area, based on modelled mutant structures, is a poor correlate for ΔΔG upon mutation. A simple volume-based, rather than solvent accessibility-based, model is constructed for ΔG and ΔΔG systems. This shows a more consistent behaviour. We discuss the efficacy of volume, as opposed to area, approaches to describe the energetic consequences of mutations at interfaces. This knowledge can be used to develop simple computational screens for binding in comparative modelled interfaces.</p

Rosetta FlexPepDock ab-initio: Simultaneous Folding, Docking and Refinement of Peptides onto Their Receptors

Flexible peptides that fold upon binding to another protein molecule mediate a large number of regulatory interactions in the living cell and may provide highly specific recognition modules. We present Rosetta FlexPepDock ab-initio, a protocol for simultaneous docking and de-novo folding of peptides, starting from an approximate specification of the peptide binding site. Using the Rosetta fragments library and a coarse-grained structural representation of the peptide and the receptor, FlexPepDock ab-initio samples efficiently and simultaneously the space of possible peptide backbone conformations and rigid-body orientations over the receptor surface of a given binding site. The subsequent all-atom refinement of the coarse-grained models includes full side-chain modeling of both the receptor and the peptide, resulting in high-resolution models in which key side-chain interactions are recapitulated. The protocol was applied to a benchmark in which peptides were modeled over receptors in either their bound backbone conformations or in their free, unbound form. Near-native peptide conformations were identified in 18/26 of the bound cases and 7/14 of the unbound cases. The protocol performs well on peptides from various classes of secondary structures, including coiled peptides with unusual turns and kinks. The results presented here significantly extend the scope of state-of-the-art methods for high-resolution peptide modeling, which can now be applied to a wide variety of peptide-protein interactions where no prior information about the peptide backbone conformation is available, enabling detailed structure-based studies and manipulation of those interactions

Differential expression of MUC genes in endometrial and cervical tissues and tumors

BACKGROUND: Mucin glycoprotein's are major components of mucus and are considered an important class of tumor associated antigens. The objective of this study was to investigate the expression of human MUC genes (MUC1, MUC2, MUC5B, MUC5AC and MUC8) in human endometrium and cervix, and to compare and quantitate the expression of MUC genes in normal and cancerous tissues. METHODS: Slot blot techniques were used to study the MUC gene expression and quantitation. RESULTS: Of the five-mucin genes studied, MUC1, MUC5B and MUC8 showed high expression levels in the normal and cancerous endometrial and cervical tissues, MUC2 and MUC5AC showed considerably lower expression. Statistically, higher levels of MUC1, MUC5B and MUC8 were observed in endometrial adenocarcinomas compared to normal tissues. In contrast, only MUC1 levels increased with no significant changes in expression of MUC5B and MUC8 in cervical tumors over normal cervical tissues. CONCLUSION: Endometrial tumors showed increased expression of MUC1, MUC5B and MUC8 over normal tissues. Only MUC1 appears to be increase, in cervical tumors. All the studied tissues showed high and consistent expression of MUC8 mRNA. Low to neglible levels of MUC2 and MUC5AC were observed in all studied endometrial and cervical tissues

Humoral immune response to MUC5AC in patients with colorectal polyps and colorectal carcinoma

BACKGROUND: MUC5AC is a secreted mucin aberrantly expressed by colorectal polyps and carcinoma. It has been hypothesized that aberrant expression of MUC5AC in colorectal carcinoma tissues increased the overall survival of patients with colorectal carcinoma. The present study investigates the incidence of naturally occurring MUC5AC antibodies in the sera of normal individuals, patients with colonic polyps and patients with advanced colorectal carcinoma. A second aim was to determine the relationship of MUC5AC antibody with the prognosis of colorectal carcinoma. METHODS: Free circulating MUC5AC antibodies were measured using an enzyme-linked immunosorbent assay with a synthetic peptide corresponding to an 8 aa. segment of MUC5AC tandem repeat region. Immunohistochemical analysis was completed to demonstrate MUC5AC expression in the polyp specimens. RESULTS: MUC5AC antibodies were detected in 6 of 22 (27.3%) healthy subjects, 9 of 20 (45%) polyp patients, 18 of 30 (60%) patients with colorectal cancer. The presence of circulating free MUC5AC antibody levels was significantly correlated with expression of MUC5AC in polyp sections. Serum MUC5AC antibody positivity was higher in patients with colon located tumors, advanced stage and poorly differentiated tumors were found negatively affecting patient survival in our study. MUC5AC antibody positivity was higher in patients with poor prognostic parameters. Disease free survival and overall survival were shorter in this group of patients. In the multivariate analysis MUC5AC antibody positivity didn't find an independent prognostic factor on prognosis. CONCLUSION: Decreased survival in colorectal carcinoma patients with MUC5AC antibody positivity may be due to a decrease in the MUC5AC expression in tumor tissues of surviving carcinoma patients

Solvent accessible surface area approximations for rapid and accurate protein structure prediction

The burial of hydrophobic amino acids in the protein core is a driving force in protein folding. The extent to which an amino acid interacts with the solvent and the protein core is naturally proportional to the surface area exposed to these environments. However, an accurate calculation of the solvent-accessible surface area (SASA), a geometric measure of this exposure, is numerically demanding as it is not pair-wise decomposable. Furthermore, it depends on a full-atom representation of the molecule. This manuscript introduces a series of four SASA approximations of increasing computational complexity and accuracy as well as knowledge-based environment free energy potentials based on these SASA approximations. Their ability to distinguish correctly from incorrectly folded protein models is assessed to balance speed and accuracy for protein structure prediction. We find the newly developed “Neighbor Vector” algorithm provides the most optimal balance of accurate yet rapid exposure measures

Four Distances between Pairs of Amino Acids Provide a Precise Description of their Interaction

The three-dimensional structures of proteins are stabilized by the interactions between amino acid residues. Here we report a method where four distances are calculated between any two side chains to provide an exact spatial definition of their bonds. The data were binned into a four-dimensional grid and compared to a random model, from which the preference for specific four-distances was calculated. A clear relation between the quality of the experimental data and the tightness of the distance distribution was observed, with crystal structure data providing far tighter distance distributions than NMR data. Since the four-distance data have higher information content than classical bond descriptions, we were able to identify many unique inter-residue features not found previously in proteins. For example, we found that the side chains of Arg, Glu, Val and Leu are not symmetrical in respect to the interactions of their head groups. The described method may be developed into a function, which computationally models accurately protein structures

Deciphering the Arginine-Binding Preferences at the Substrate-Binding Groove of Ser/Thr Kinases by Computational Surface Mapping

Protein kinases are key signaling enzymes that catalyze the transfer of γ-phosphate from an ATP molecule to a phospho-accepting residue in the substrate. Unraveling the molecular features that govern the preference of kinases for particular residues flanking the phosphoacceptor is important for understanding kinase specificities toward their substrates and for designing substrate-like peptidic inhibitors. We applied ANCHORSmap, a new fragment-based computational approach for mapping amino acid side chains on protein surfaces, to predict and characterize the preference of kinases toward Arginine binding. We focus on positions P−2 and P−5, commonly occupied by Arginine (Arg) in substrates of basophilic Ser/Thr kinases. The method accurately identified all the P−2/P−5 Arg binding sites previously determined by X-ray crystallography and produced Arg preferences that corresponded to those experimentally found by peptide arrays. The predicted Arg-binding positions and their associated pockets were analyzed in terms of shape, physicochemical properties, amino acid composition, and in-silico mutagenesis, providing structural rationalization for previously unexplained trends in kinase preferences toward Arg moieties. This methodology sheds light on several kinases that were described in the literature as having non-trivial preferences for Arg, and provides some surprising departures from the prevailing views regarding residues that determine kinase specificity toward Arg. In particular, we found that the preference for a P−5 Arg is not necessarily governed by the 170/230 acidic pair, as was previously assumed, but by several different pairs of acidic residues, selected from positions 133, 169, and 230 (PKA numbering). The acidic residue at position 230 serves as a pivotal element in recognizing Arg from both the P−2 and P−5 positions

Differential Muc2 and Muc5ac secretion by stimulated guinea pig tracheal epithelial cells in vitro

BACKGROUND: Mucus overproduction is a characteristic of inflammatory pulmonary diseases including asthma, chronic bronchitis, and cystic fibrosis. Expression of two mucin genes, MUC2 and MUC5AC, and their protein products (mucins), is modulated in certain disease states. Understanding the signaling mechanisms that regulate the production and secretion of these major mucus components may contribute significantly to development of effective therapies to modify their expression in inflamed airways. METHODS: To study the differential expression of Muc2 and Muc5ac, a novel monoclonal antibody recognizing guinea pig Muc2 and a commercially-available antibody against human MUC5AC were optimized for recognition of specific guinea pig mucins by enzyme-linked immunosorbent assay (ELISA), Western blot, and immunohistochemistry (IHC). These antibodies were then used to analyze expression of Muc2 and another mucin subtype (likely Muc5ac) in guinea pig tracheal epithelial (GPTE) cells stimulated with a mixture of pro-inflammatory cytokines [tumor necrosis factor-α (TNF-α), interleukin 1β (IL-1β), and interferon- γ (IFN-γ)]. RESULTS: The anti-Muc2 (C4) and anti-MUC5AC (45M1) monoclonal antibodies specifically recognized proteins located in Muc2-dominant small intestinal and Muc5ac-dominant stomach mucosae, respectively, in both Western and ELISA experimental protocols. IHC protocols confirmed that C4 recognizes murine small intestine mucosal proteins while 45M1 does not react. C4 and 45M1 also stained specific epithelial cells in guinea pig lung sections. In the resting state, Muc2 was recognized as a highly expressed intracellular mucin in GPTE cells in vitro. Following cytokine exposure, secretion of Muc2, but not the mucin recognized by the 45M1 antibody (likely Muc5ac), was increased from the GPTE cells, with a concomitant increase in intracellular expression of both mucins. CONCLUSION: Given the tissue specificity in IHC and the differential hybridization to high molecular weight proteins by Western blot, we conclude that the antibodies used in this study can recognize specific mucin subtypes in guinea pig airway epithelium and in proteins from GPTE cells. In addition, Muc2 is highly expressed constitutively, modulated by inflammation, and secreted differentially (as compared to Muc5ac) in GPTE cells. This finding contrasts with expression patterns in the airway epithelium of a variety of mammalian species in which only Muc5ac predominates