Structure-based derivation and optimization of YAP-like coactivator-derived peptides to selectively target TEAD family transcription factors by hydrocarbon stapling and cyclization.

Human transcriptional enhanced associate domain (TEAD) family consists of four paralogous transcription factors that function to modulate gene expression by interacting with YAP-like coactivators and have been recognized as potential therapeutic targets of diverse diseases including lung cancer and gastric tumor. Here, we attempt to explore the systematic interaction profile between the 4 TEAD proteins and the peptides derived from the binding sites of 8 known YAP-like coactivators, in order to analyze the binding affinity and recognition specificity of these peptides toward the TEAD family, and to design hydrocarbon-stapled/cyclized peptides that can target the specific interaction profile for each coactivator. Structural, energetic, and dynamic investigations of TEAD-coactivator interactions reveal that the coactivators adopt three independent secondary structure regions (ß-strand, α-helix, and Ω-loop) to surround on the surface of TEAD proteins, in which the α-helical and Ω-loop regions are primarily responsible for the interactions. Five α-helical peptides and four Ω-loop peptides are derived from the 8 YAP-like coactivators, and their systematic binding profile toward the 4 TEAD proteins is created, and hydrocarbon stapling and cyclization strategies are employed to constrain the free α-helical and Ω-loop peptides into their native conformations, respectively, thus effectively promoting peptide binding to TEADs. The all-hydrocarbon and disulfide bridges are designed to point out the TEAD-peptide complex interface, which would not disrupt the direct intermolecular interaction between the TEAD and peptide. Therefore, the stapling and cyclization only improve peptide binding affinity to these TEADs, but do not alter peptide recognition specificity over different TEADs.

TRPA1 deficiency alleviates inflammation of atopic dermatitis by reducing macrophage infiltration.

AIMS: The aim of this study was to investigate the role of TRPA1 in the pathogenesis of AD. MAIN METHODS: The experimental atopic dermatitis (AD)-like skin lesions were established using 2,4-dinitrochlorobenzene (DNCB). Mice were divided into three groups: TRPA1-/- and WT groups were treated with DNCB dissolved in a 3:1 mixture of acetone and olive oil; the negative control group was treated with 3:1 mixture of acetone and olive oil without DNCB. The treatment lasted for 21 days, after which the animals were sacrificed and their blood, ears and dorsal skin tissue samples were collected for analysis. KEY FINDINGS: Lower dermatitis score, ear thickness, pruritus score, and epidermal hyperplasia were observed in mice in TRPA1-/- mice compared to the WT group. Besides, lower dermal mast cell infiltration, proinflammatory cytokines, Th2 cytokines and the infiltration of macrophages were observed in the TRPA1-/- mice compared to the WT group. Furthermore, we demonstrated that TRPA1 antagonist HC-030031 could alleviate AD-like symptoms and reduce the degree of epidermal hyperplasia in mice. SIGNIFICANCE: TRPA1 has a crucial role during the AD pathogenesis in mice, thus may be used as a potential new target for treating patients with chronic skin inflammatory disease.

Histone deacetylase inhibitors suppress aggressiveness of head and neck squamous cell carcinoma via histone acetylation-independent blockade of the EGFR-Arf1 axis.

BACKGROUND: A promising arsenal of histone deacetylase (HDAC)-targeted treatment has emerged in the past decade, as the abnormal targeting or retention of HDACs to DNA regulatory regions often occurs in many cancers. Head and neck squamous cell carcinoma (HNSCC) is one of the most aggressive malignancies worldwide associated with poor overall survival in late-stage patients. HDAC inhibitors have great potential to treat this devastating disease; however, few has been studied regarding the beneficial role of HDAC inhibition in anti-HNSCC therapy and the underlying molecular mechanisms remain elusive. METHODS: Cell migration and invasion were examined by wound closure and Transwell assays. Protein levels and interactions were assessed by Western blotting and immunoprecipitation. HDAC activity was measured with the fluorometric HDAC Activity Assay. Phospho-receptor tyrosine kinase (RTK) profiling was determined by the Proteome Profiler Human Phospho-RTK Array. RESULTS: ADP-ribosylation factor 1 (Arf1), a small GTPase coordinating vesicle-mediated intracellular trafficking, can be inactivated by HDAC inhibitors through histone acetylation-independent degradation of epidermal growth factor receptor (EGFR) in HNSCC cells. Mechanistically, high levels of Arf1 activity are maintained by binding to phosphorylated EGFR which is localized on HNSCC cell plasma membrane. Decreased EGFR phosphorylation is associated with reduced EGFR protein levels in the presence of TSA, which inactivates Arf1 and eventually inhibits invasion in HNSCC cells. CONCLUSIONS: Our insights explore the critical role of EGFR-Arf1 complex in driving HNSCC progression, and demonstrate the selective action of HDAC inhibitors on this specific axis for suppressing HNSCC invasion. This novel finding represents the first example of modulating the EGFR-Arf1 complex in HNSCC by small molecule agents.

Genome-wide analysis of LXXLL-mediated DAX1/SHP-nuclear receptor interaction network and rational design of stapled LXXLL-based peptides to target the specific network profile.

The atypical orphan receptors DAX1 and SHP constitute the NR0B subgroup of human nuclear receptor (hNR) family; they play key roles in metabolism, reproduction, nutrition and steroidogenesis, and are involved in the pathogenesis of a variety of diseases such as cancer and adrenal hypoplasia. The two receptors lack the classical DNA-binding domain and act as the corepressors of other hNRs. The DAX1 and SHP contains three and two conserved LXXLL motifs, respectively, which can be recognized and bound by the activation function-2 (AF-2) domain of hNR proteins in agonist conformation. Here, we attempt to explore the systematic interaction profile between the five DAX1/SHP LXXLL motifs and all the 48 hNR AF-2 domains found in the human genome, to analyze the binding affinity and specificity of these motifs towards the complete domain array, and to design LXXLL-based, hydrocarbon-stapled peptides that can target the specific interaction profile for each motif. A weighted source-target network from motifs to domains is created based on the modeled domain-motif complex structures and calculated binding potencies, from which the specific interaction profile of each motif against the whole hNR array is depicted and clustered to measure the binding similarity and relationship among these motifs. Dynamics simulations reveal that the LXXLL-based peptides are highly flexible in free unbound state, thus unfavorable to be recognized and bound by AF-2 domains. Hydrocarbon-stapling technique is employed to help the constraint of these unstructured peptides to active helical conformation, thus largely improving their binding affinity to the hNR array. The hydrocarbon bridge is designed to point out of the domain's active pocket, which would not disrupt the direct interaction between the domain and peptide. Energetic decomposition imparts that the stapling has only a very modest influence on the interaction enthalpy and desolvation effect of domain-peptide binding, but can substantially reduce entropy penalty upon the binding. For a peptide ligand, the entropic reduction can be roughly regarded as a constant, which only improves (absolute) peptide binding affinity towards the whole domain array, but does not alter (relative) peptide binding specificity over different domains in the array. Overall, the stapled peptides can be considered as potent competitors to selectively target the specific interaction networks mediated by their parent LXXLL motifs in DAX1 and SHP proteins.

Aluminum (oxy) Hydroxide Nanorods Activate an Early Immune Response in Pseudomonas aeruginosa Vaccine.

Bacterial vaccines have been widely used to prevent infectious diseases, especially in veterinary medicine. Although there are many reports on bacterin adjuvants, only a few contain innovations in bacterin adjuvants. Taking this into consideration, in this study we designed and synthesized a new aluminum (oxy) hydroxide (AlOOH) nanorod (Al-NR) with a diameter of 200 ± 80 nm and a length of 1.1 ± 0.6 µm. Using whole- Pseudomonas aeruginosa PAO1 as antigens, we showed that the bacterial antigens of P. aeruginosa PAO1 adsorbed on the Al-NRs induced a quick and stronger antigen-specific antibody response than those of the other control groups, especially in the early stage of immunization. Furthermore, the level of antigen-specific IgG was approximately 4-fold higher than that of the no adjuvant group and 2.5-fold higher than those of other adjuvant groups in the first week after the initial immunization. The potent adjuvant activity of the Al-NRs was attributed to the rapid presentation of antigen adsorbed on them by APCs. Additionally, Al-NRs induced a milder local inflammation than the other adjuvants. In short, we confirmed that Al-NRs, enhancing both humoral and cellular immune responses, are a potentially promising vaccine adjuvant delivery system for inhibiting the whole- Pseudomonas aeruginosa infection.

Targeting oncogenic transcriptional corepressor Nac1 POZ domain with conformationally constrained peptides by cyclization and stapling.

The oncogenic transcriptional corepressor Nac1 contains a conserved POZ protein-protein interaction module that mediates homodimerization or heterodimerization with itself or other POZ proteins. The dimerization has been recognized as an attractive target for cancer therapy. Here, we attempted to (i) discover those potential binding partners of Nac1 in the human genome, (ii) derive key peptide segments from the complex interface of Nac1 with its putative partners, and (iii) improve the peptide binding affinity to Nac1 POZ domain. In the procedure, Nac1 POZ dimerization with 136 human POZ domains was modeled, simulated and analyzed at atomic level to elucidate structural basis, energetic property and dynamics behavior. Two hotspot regions, namely α1-helix and α2/α3-hairpin, at the dimerization interface were identified that are responsible for stabilizing the formed POZ-POZ dimer complexes. The α1-helix and α2/α3-hairpin were stripped from the interface to derive their respective isolated SIP peptides, which, however, exhibited a large flexibility and intrinsic disorder in free state, and thus would incur a considerable penalty upon rebinding to Nac1 POZ domain. By carefully examining the natively folded structures of α1-helix and α2/α3-hairpin in protein context and their interaction modes with the domain, we rationally designed a hydrocarbon bridge and a disulfide bond separately for the two peptides in order to constrain their conformational flexibility in free state, thus largely minimizing the flexibility penalty. Consequently, three α1-helix peptides derived from Nac1, Miz1 and Slx4 were stapled by all-hydrocarbon bridge, while four α2/α3-hairpin peptides derived from Nac1, Bacd1, Klh28 and Mynn were cyclized by disulfide bond. Binding affinity analysis revealed that, as designed, these peptides were converted from non- or weak binders to moderate or good binders of Nac1 POZ domain upon the stapling and cyclization.

Implications of FGF19 on sorafenib-mediated nitric oxide production in hepatocellular carcinoma cells - a short report.

BACKGROUND: Hepatocellular carcinoma (HCC), a primary neoplasm derived from hepatocytes, is the second leading cause of cancer mortality worldwide. Previous work has shown that fibroblast growth factor 19 (FGF19), an oncogenic driver, acts as a negative regulator of the therapeutic efficacy of the tyrosine kinase inhibitor sorafenib in HCC cells. The FGF19-mediated mechanism affecting sorafenib treatment, however, still remains to be resolved. Here, we hypothesize that the FGF19-FGFR4 axis may affect the effectiveness of sorafenib in the treatment of HCC. METHODS: FGF19 and FGFR4 cDNAs were cloned into a pcDNA3.1 vector and subsequently used for exogenous over-expression analyses. FGF19 knockdown cells were generated using a lentiviral-mediated short hairpin RNA (shRNA) methodology and FGFR4 knockout cells were generated using a CRISPR-Cas9 methodology. FGFR4 activation in HCC cells was inhibited by BLU9931. The effects of exogenous gene over-expression, expression knockdown and knockout, as well as drug efficacies in HCC cells, were validated using Western blotting. HCC cell proliferation was assessed using a CellTiter 96® AQueous One Solution Cell Proliferation Assay, whereas NO levels were assessed using DAF-FM DA staining in conjunction with electrochemical biosensors. RESULTS: We found that FGF19, when exogenously overexpressed, results in a reduced sorafenib-induced NO generation and a decreased proliferation of HCC cells. In contrast, we found that either FGF19 silencing or knockout of its receptor FGFR4 sensitized HCC cells to sorafenib through the induction of NO generation. Concordantly, we found that inactivation of FGFR4 by BLU9931 enhanced the sensitivity of HCC cells to sorafenib. CONCLUSION: From our data we conclude that the FGF19-FGFR4 axis may play a critical role in the effects elicited by sorafenib in HCC cells. Blocking the FGF19-FGFR4 axis may provide novel opportunities to improve the efficacy of sorafenib in the treatment of patients with HCC.

The potential regulatory mechanisms of the gonadotropin-releasing hormone in gonadotropin transcriptions identified with bioinformatics analyses.

BACKGROUND: The regulation of gonadotropin synthesis and release by gonadotropin-releasing hormone (GnRH) plays an essential role in the neuroendocrine control of reproduction. However, the mechanisms underlying gonadotropin regulation by GnRH pulse frequency and amplitude are still ambiguous. This study aimed to explore the molecular mechanisms and biological pathways associated with gonadotropin synthesis by GnRH pulse frequencies and amplitudes. METHODS: Using GSE63251 datasets downloaded from the Gene Expression Omnibus (GEO), differentially expressed genes (DEGs) were screened by comparing the RNA expression from the GnRH pulse group, the GnRH tonic group and the control group. Pathway enrichment analyses of DEGs was performed, followed by protein-protein interaction (PPI) network construction. Furthermore, sub-network modules were constructed by ClusterONE and GO function and pathways analysed by DAVID. In addition, the relationship between the metabolic pathways and the GnRH pathway was verified in vitro. RESULTS: In total, 531 common DEGs were identified in GnRH groups, including 290 up-regulated and 241 down-regulated genes. DEGs predominantly enriched in 16 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, including 11 up-regulated pathways (signallingsignallingmetabolic pathways, signallingand GnRH signalling pathway) and 5 down-regulated pathways (type II diabetes mellitus). Moreover, FBJ osteosarcoma oncogene (FOS) and jun proto-oncogene (JUN) had higher connectivity degrees in the PPI network. Three modules in the PPI were identified with ClusterONE. The genes in module 1 were significantly enriched in five pathways, including signallingthe insulin resistance and GnRH signalling pathway. The genes in modules 2 and 3 were mainly enriched in metabolic pathways and steroid hormone biosynthesis, respectively. Finally, knockdown leptin receptor (LEPR) and insulin receptor (INSR) reversed the GnRH-modulated metabolic related-gene expression. CONCLUSIONS: The present study revealed the involvement of GnRH in the regulation of gonadotropin biosynthesis and metabolism in the maintenance of reproduction, achieved by bioinformatics analyses. This, indicates that the GnRH signalling pathway played a central linkings role in reproductive function and metabolic balance. In addition, the present study identified the difference response between GnRH pulse and GnRH tone, indicated that abnormal GnRH pulse and amplitude may cause disease, which may provide an improved understanding of the GnRH pathway and a new insight for disease diagnosis and treatment.

Critical role of DEK and its regulation in tumorigenesis and metastasis of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality globally. Therefore, it is quite essential to identify novel HCC-related molecules for the discovery of new prognostic markers and therapeutic targets. As an oncogene, DEK plays an important role in cell processes and participates in a variety of cellular metabolic functions, and its altered expression is associated with several human malignancies. However, the functional significance of DEK and the involved complex biological events in HCC development and progression are poorly understood. Here, combing the results from clinical specimens and cultured cell lines, we uncover a critical oncogenic role of DEK, which is highly expressed in HCC cells. DEK protein encompasses two isoforms (isoforms 1 and 2) and isoform 1 is the most frequently expressed DEK isoform in HCC cells. DEK depletion by using shRNA inhibited the cell proliferation and migration in vitro and suppressed tumorigenesis and metastasis in mouse models. Consistently, DEK overexpression regardless of which isoform produced the opposite effects. Further studies showed that DEK induced cell proliferation through upregulating cell cycle related CDK signaling, and promoted cell migration and EMT, at least in part, through the repression of ß-catenin/E-cadherin axis. Interestingly, isoform 1 induced cell proliferation more efficiently than isoform 2, however, no functional differences existed between these two isoforms in cell migration. Together, our study indicates that DEK expression is required for tumorigenesis and metastasis of HCC, providing molecular insights for DEK-related pathogenesis and a basis for developing new strategies against HCC.

FGF19 promotes epithelial-mesenchymal transition in hepatocellular carcinoma cells by modulating the GSK3ß/ß- catenin signaling cascade via FGFR4 activation.

Compelling evidence suggests that the epithelial-mesenchymal transition (EMT) correlates with aggressiveness of tumors and poor survival. FGF19 has been shown to be involved in EMT in cholangiocarcinoma and colorectal cancer, however, molecular mechanisms underlying FGF19-induced EMT process in hepatocellular carcinoma (HCC) remain largely unknown. Here, we show the expression of FGF19 is significantly elevated and negatively associated with the expression of E-cadherin in HCC tissues and cell lines. Ectopic FGF19 expression promotes EMT and invasion in epithelial-like HCC cells through repression of E-cadherin expression, whereas FGF19 knockdown enhances E-cadherin expression and hence diminishes EMT traits in mesenchymal-like HCC cells, suggesting FGF19 exerts its tumor progressing functions as an EMT inducer. Interestingly, depletion of FGF19 cannot abrogate EMT traits in the presence of GSK3ß inhibitors. Furthermore, FGF19-induced EMT can be markedly attenuated when FGFR4 is knocked out. These observations clearly indicate that FGFR4/GSK3ß/ß-catenin axis may play a pivotal role in FGF19-induced EMT in HCC cells. As FGF19 and its specific receptor FGFR4 are frequently amplified in HCC cells, selective targeting this signaling node may lend insights into a potential effective therapeutic approach for blocking metastasis of HCC.

The Inhibitory Effects of RFamide-Related Peptide 3 on Luteinizing Hormone Release Involves an Estradiol-Dependent Manner in Prepubertal but Not in Adult Female Mice.

The mammalian gonadotropin-inhibitory hormone (GnIH) ortholog, RFamide-related peptide (RFRP), is considered to act on gonadotropin-releasing hormone (GnRH) neurons and the pituitary to inhibit gonadotropin synthesis and release. However, there is little evidence documenting whether RFamide-related peptide 3 (RFRP-3) plays a primary role in inhibition of the hypothalamo-pituitary-gonadal (HPG) axis prior to the onset of puberty. The present study aimed to understand the functional significance of the neuropeptide on pubertal development. The developmental changes in reproductive-related gene expression at the mRNA level were investigated in the hypothalamus of female mice. The results indicated that RFRP-3 may be an endogenous inhibitory factor for the activation of the HPG axis prior to the onset of puberty. In addition, centrally administered RFRP-3 significantly suppressed plasma luteinizing hormone (LH) levels in prepubertal female mice. Surprisingly, centrally administered RFRP-3 had no effects on plasma LH levels in ovariectomized (OVX) prepubescent female mice. In contrast, RFRP-3 also inhibited plasma LH levels in OVX prepubescent female mice that were treated with 17beta-estradiol replacement. Our study also examined the effects of RFRP-3 on plasma LH release in adult female mice that were ovariectomized at dioestrus, with or without estradiol (E2). Our results showed that the inhibitory effects of RFRP-3 were independent of E2 status. Quantitative real-time PCR and immunohistochemistry analyses showed that RFRP-3 inhibited GnRH expression at both the mRNA and protein levels in the hypothalamus. These data demonstrated that RFRP-3 could effectively suppress pituitary LH release, via the inhibition of GnRH transcription and translation in prepubescent female mice, which is associated with estrogen signaling pathway and developmental stages.

The auto-inhibitory state of Rho guanine nucleotide exchange factor ARHGEF5/TIM can be relieved by targeting its SH3 domain with rationally designed peptide aptamers.

The short isoform of Rho guanine nucleotide exchange factor ARHGEF5 is known as TIM, which plays diverse roles in, for example, tumorigenesis, neuronal development and Src-induced podosome formation through the activation of its substrates, the Rho family of GTPases. The activation is auto-inhibited by a putative helix N-terminal to the DH domain of TIM, which is stabilized by the intramolecular interaction of C-terminal SH3 domain with a poly-proline sequence between the putative helix and the DH domain. In this study, we systematically investigated the structural basis, energetic landscape and biological implication underlying TIM auto-inhibition by using atomistic molecular dynamics simulations and binding free energy analysis. The computational study revealed that the binding of SH3 domain to poly-proline sequence is the prerequisite for the stabilization of TIM auto-inhibition. Thus, it is suggested that targeting SH3 domain with competitors of the poly-proline sequence would be a promising strategy to relieve the auto-inhibitory state of TIM. In this consideration, we rationally designed a number of peptide aptamers for competitively inhibiting the SH3 domain based on modeled TIM structure and computationally generated data. Peptide binding test and guanine nucleotide exchange analysis solidified that these designed peptides can both bind to the SH3 domain potently and activate TIM-catalyzed RhoA exchange reaction effectively. Interestingly, a positive correlation between the peptide affinity and induced exchange activity was observed. In addition, separate mutation of three conserved residues Pro49, Pro52 and Lys54 - they are required for peptide recognition by SH3 domain -- in a designed peptide to Ala would completely abolish the capability of this peptide activating TIM. All these come together to suggest an intrinsic relationship between peptide binding to SH3 domain and the activation of TIM.

Polyinosinic-polycytidylic acid has therapeutic effects against cerebral ischemia/reperfusion injury through the downregulation of TLR4 signaling via TLR3.

Recent reports have shown that preconditioning with the TLR3 ligand polyinosinic-polycytidylic acid (poly(I:C)) protects against cerebral ischemia/reperfusion (I/R) injury. However, it is unclear whether poly(I:C) treatment after cerebral I/R injury is also effective. We used mouse/rat middle cerebral artery occlusion and cell oxygen-glucose deprivation models to evaluate the therapeutic effects and mechanisms of poly(I:C) treatment. Poly(I:C) was i.p. injected 3 h after ischemia (treatment group). Cerebral infarct volumes and brain edemas were significantly reduced, and neurologic scores were significantly increased. TNF-α and IL-1ß levels were markedly decreased, whereas IFN-ß levels were greatly increased, in the ischemic brain tissues, cerebral spinal fluid, and serum. Injuries to hippocampal neurons and mitochondria were greatly reduced. The numbers of TUNEL-positive and Fluoro-Jade B(+) cells also decreased significantly in the ischemic brain tissues. Poly(I:C) treatment increased the levels of Hsp27, Hsp70, and Bcl2 and decreased the level of Bax in the ischemic brain tissues. Moreover, poly(I:C) treatment attenuated the levels of TNF-α and IL-1ß in serum and cerebral spinal fluid of mice stimulated by LPS. However, the protective effects of poly(I:C) against cerebral ischemia were abolished in TLR3(-/-) and TLR4(-/-)mice. Poly(I:C) downregulated TLR4 signaling via TLR3. Poly(I:C) treatment exhibited obvious protective effects 14 d after ischemia and was also effective in the rat permanent middle cerebral artery occlusion model. The results suggest that poly(I:C) exerts therapeutic effects against cerebral I/R injury through the downregulation of TLR4 signaling via TLR3. Poly(I:C) is a promising new drug candidate for the treatment of cerebral infarcts.

Expression of the HPV18E2 gene in cervical cancer and premalignant lesions and its clinical significance.

This study aims to observe the expression of the HPV18E2 gene in cervical cancer and premalignant lesions and to investigate its clinical significance. The expression of the HPV18E2 gene in the cervical tissues obtained from 38 women with cervical lesions was detected using the RT-PCR method. The pathological changes were graded based on cervical intraepithelial neoplasia (CIN) criteria. The HPV18E2 gene was expressed mainly in cervical premalignant lesions, 60 % in Grade I CIN, 33.3 % in Grade II CIN, and 28.6 % in Grade III CIN. No expression was detected in cervical cancer and chronic cervical inflammation. This study suggests that peptides vaccine targeting the HPV18E2 protein may disrupt and prohibit the progress of diseases induced by HPV 18 infection (i.e., CIN and cervical cancer).

Why ligand cross-reactivity is high within peptide recognition domain families? A case study on human c-Src SH3 domain.

Many important protein-protein interactions in eukaryotic signaling networks are mediated by peptide recognition domains (PRDs), which bind short linear sequence motifs in other proteins. However, high ligand cross-reactivity is observed within most PRD families, rendering a broad specificity for the family members. In the present study, we attempt to explore the molecular mechanism and physicochemical origin of PRD cross-reactivity. In the procedure, a structure-based method called atomic cross-nonbonded interaction analysis (ACNIA) is described to extract atomic-level nonbonded interaction information at domain-peptide interface and to correlate the information with peptide affinity based on a set of structure-solved, affinity-known protein-peptide complex samples compiled from numerous literatures and databases. The ACNIA-derived affinity predictor is tested rigorously with statistical validation approach, which is also demonstrated to be capable of perceiving slight structural change in the interface using three distinct panels of SH3-binding peptide data. Subsequently, with help of the affinity predictor we adopt the human c-Src SH3 domain, one of the most sophisticated PRDs, as a paradigm to investigate the ligand cross-reactivity within SH3 family. It is found that most of the family members have only few non-essential residue differences in their peptide-binding pockets, and thus exhibit a similar peptide recognition profile and high cross-reactivity. The cross-reactivity is even shared by different subclasses of SH3 domains. The findings suggest that inherent binding specificity is not the only factor to select appropriate binders for specific SH3 domains, and other aspects such as cellular context and the rest of the SH3-containing proteins may play important roles in reducing their ligand cross-reactivity.

Development of QSAR-Improved Statistical Potential for the Structure-Based Analysis of ProteinPeptide Binding Affinities.

Proteinpeptide interactions have recently been found to play an essential role in constructing intracellular signaling networks. Understanding the molecular mechanism of such interactions and identification of the interacting partners would be of great value for developing peptide therapeutics against many severe diseases such as cancer. In this study, we describe a structure-based, general-purpose strategy for fast and reliably predicting proteinpeptide binding affinities. This strategy combines unsupervised knowledge-based statistical potential derived from 505 interfacially diverse, non-redundant proteinpeptide complex structures and supervised quantitative structure-activity relationship (QSAR) modeling trained by 250 proteinpeptide interactions with known structure and affinity data. The built partial least squares (PLS) model is confirmed to have high stability and predictive power by using internal 5-fold cross-validation and rigorous Monte Carlo cross-validation (MCCV). The model is further employed to analyze two large groups of HLA- and SH3-binding peptides based upon computationally modeled structures. Satisfactorily, although the PLS model is originally trained with dissociation constants (Kd ) of proteinpeptide binding, it shows a good correlation with other two affinity qualities, i.e. SPOT signal intensities (BLU) and half maximal competitive concentrations (IC50 ). Furthermore, we perform systematic comparisons of our method with several widely used, representative affinity predictors, including molecular mechanics-based MM-PB/SA, knowledge-based DFIRE and docking score HADDOCK, on a small panel of elaborately selected proteinpeptide systems. It is demonstrated that (i) the QSAR-improved statistical potential exhibits a comparable predictive performance with but can work faster than these traditional methods, and (ii) the crystal structure-derived statistical potential also supports the modeled and solution structures of proteinpeptide complexes. We expect that this hybrid method can be exploited as a new scoring tool to facilitate, for example, peptide docking and virtual screening.

Use of fast conformational sampling to improve the characterization of VEGF A-peptide interactions.

Protein-peptide interaction is fundamentally important for signal transduction, transcription regulation, protein degradation, cell regeneration, and immune response. Here, we report the use of a fast conformational sampling strategy to improve the prediction of protein-peptide binding affinity. This method generates hundreds of alternative conformers for a protein-peptide complex and then performs classical MM-PB/SA analysis over these conformers to derive a consistent binding energy expression for the complex. We show a proof-of-concept study on vascular endothelial growth factor A (VEGF A) interaction with its peptide ligands. The structures of VEGF A complexed with 13 peptides are modeled with a virtual mutagenesis protocol and their binding energies are subsequently calculated by using the conformational sampling-based method. A good linear correlation between the calculated and experimental values is observed, and we demonstrate that the correlation could be further improved by fitting the decomposed energy terms to experimentally measured affinity. Furthermore, the obtained results are discussed in detail in order to elucidate the structural basis and energetic implication underlying VEGF A-peptide recognition and association. We also give a detailed comparison between the proposed method and other widely used approaches, from which it is suggested that our method exhibits a good compromise between the effectiveness and efficiency in evaluating protein-peptide affinity.

Characterization of the binding profile of peptide to transporter associated with antigen processing (TAP) using Gaussian process regression.

Although MHC-peptide binding is the most selective event in epitope presentation process, the protein fragments generated by proteasomal cleavage require to be recognized by transporter associated with antigen processing (TAP) and translocated from cytosol to endoplasmic reticulum before they can be loaded into the ligand-binding groove of MHC. In this article, we report the use of a new and powerful machine learning tool called Gaussian process (GP) to model the linear and nonlinear relationships between the sequence pattern and binding affinity of peptide to TAP, and to explain the physicochemical properties and structural implications underlying the specific recognition and association of peptide with TAP. The resulting statistics are compared systematically with those obtained by sophisticated PLS, ANN and SVM. Results show that: (i) Nonlinear methods such as the ANN and GP perform much better than the linear PLS. (ii) GP is capable of handling both linearity- and nonlinearity-hybrid relationship and thus exhibits a good performance relative to other two nonlinear methods. (iii) Investigation of the GP model shows that the P1, P2, P3 and P9 of peptide are the most important positions that dominate TAP-peptide recognition, P5 contributes slightly to the peptide binding, whereas P4, P6, P7 and P8 can only exert very limited potency on the binding. (iv) Diverse properties cast remarkable effects on the interaction between TAP and peptide. In particular, hydrophobility, electronic property and hydrogen bond contribute most significantly to the binding affinity of TAP-peptide association.

Why OppA protein can bind sequence-independent peptides? A combination of QM/MM, PB/SA, and structure-based QSAR analyses.

Periplasmic oligopeptide-binding protein (OppA) is the initial receptor in the ATP-binding cassette (ABC) system of bacteria, which exhibits a broad specificity in binding oligopeptides without regard to sequence. Here, we present a computational study on the structural properties and energetic landscapes of OppA protein interacting with its cognate ligands on the basis of 28 structure/affinity-known OppA-tripeptide complexes. By employing a well-designed protocol that couples the hybrid quantum mechanical/molecular mechanical (QM/MM) scheme and the sophisticated Poisson-Boltzmann/surface area (PB/SA) solvent model together to analyze and decompose the energy components associated with the OppA-peptide binding, we demonstrate that the broad specificity of OppA-recognizing peptides is originated from a series of exquisite balances between the free energy contributions from, for example, the direct nonbonded interactions and indirect desolvation effects, the main chains and side chains, and the different residue positions of the tripeptide ligands. We also show that, in a framework of structure-based quantitative structure-activity relationship (SB-QSAR) methodology, the QM/MM-PB/SA-derived energy terms could be used as a good descriptor to characterize the interaction profile of OppA with peptides and correlate pretty well with the experimentally measured affinities of the binding.

Modeling and prediction of retention behavior of histidine-containing peptides in immobilized metal-affinity chromatography.

Two kinds of structural characterization method as local descriptors and global descriptors were used to parameterize peptide structures, and several quantitative structure-retention relationship models were then constructed using partial least square (PLS), least-squares support vector machine (LS-SVM) and Gaussian process (GP) coupled with genetic algorithm-variable selection. These models were validated rigorously and investigated systematically by Tropsha et al. criteria, Monte Carlo cross-validation and one-way analysis of variance. Results show that regression models constructed using nonlinear approaches such as LS-SVM and GP are more robust and predictable than those by linear PLS method. By including linear and nonlinear terms in the covariance function, the GP is capable of handling both linear and nonlinear-mixed relationship, and thus presents a better performance than LS-SVM. Investigation of the optimal GP model revealed that diversified properties contribute to the retention behavior of peptides in immobilized metal-affinity chromatography. Particularly, coordination interaction, electrostatic factor, sovlation effect and hydrogen bonding are correlated significantly with the peptide retention ability.