Disordered Structural Ensembles of Vasopressin and Oxytocin and Their Mutants

Vasopressin and oxytocin are intrinsically disordered cyclic nonapeptides belonging to a family of neurohypophysial hormones. Although unique in their functions, these peptides differ only by two residues and both feature a tocin ring formed by the disulfide bridge between first and sixth cysteine residues. This sequence and structural similarity are experimentally linked to oxytocin agonism at vasopressin receptors and vasopressin antagonism at oxytocin receptors. Yet single- or double-residue mutations in both peptides have been shown to have drastic impacts on their activities at either receptor, and possibly the ability to bind to their neurophysin carrier protein. In this study we perform molecular dynamics simulations of the unbound native and mutant sequences of the oxytocin and vasopressin hormones to characterize their structural ensembles. We classify the subpopulations of these structural ensembles on the basis of the distributions of radius of gyration and secondary structure and hydrogen-bonding features of the canonical tocin ring and disordered tail region. We then relate the structural changes observed in the unbound form of the different hormone sequences to experimental information about peptide receptor binding, and more indirectly, carrier protein binding affinity, receptor activity, and protease degradation. This study supports the hypothesis that the structural characteristics of the unbound form of an IDP can be used to predict structural or functional preferences of its functional bound form

Sustained proliferation in cancer: mechanisms and novel therapeutic targets

Proliferation is an important part of cancer development and progression. This is manifest by altered expression and/or activity of cell cycle related proteins. Constitutive activation of many signal transduction pathways also stimulates cell growth. Early steps in tumor development are associated with a fibrogenic response and the development of a hypoxic environment which favors the survival and proliferation of cancer stem cells. Part of the survival strategy of cancer stem cells may manifested by alterations in cell metabolism. Once tumors appear, growth and metastasis may be supported by overproduction of appropriate hormones (in hormonally dependent cancers), by promoting angiogenesis, by undergoing epithelial to mesenchymal transition, by triggering autophagy, and by taking cues from surrounding stromal cells. A number of natural compounds (e.g., curcumin, resveratrol, indole-3-carbinol, brassinin, sulforaphane, epigallocatechin-3-gallate, genistein, ellagitannins, lycopene and quercetin) have been found to inhibit one or more pathways that contribute to proliferation (e.g., hypoxia inducible factor 1, nuclear factor kappa B, phosphoinositide 3 kinase/Akt, insulin-like growth factor receptor 1, Wnt, cell cycle associated proteins, as well as androgen and estrogen receptor signaling). These data, in combination with bioinformatics analyses, will be very important for identifying signaling pathways and molecular targets that may provide early diagnostic markers and/or critical targets for the development of new drugs or drug combinations that block tumor formation and progression

Resveratrol Enhances Antitumor Activity of TRAIL in Prostate Cancer Xenografts through Activation of FOXO Transcription Factor

Resveratrol (3, 4', 5 tri-hydroxystilbene), a naturally occurring polyphenol, exhibits anti-inflammatory, antioxidant, cardioprotective and antitumor activities. We have recently shown that resveratrol can enhance the apoptosis-inducing potential of TRAIL in prostate cancer cells through multiple mechanisms in vitro. Therefore, the present study was designed to validate whether resveratrol can enhance the apoptosis-inducing potential of TRAIL in a xenograft model of prostate cancer.Resveratrol and TRAIL alone inhibited growth of PC-3 xenografts in nude mice by inhibiting tumor cell proliferation (PCNA and Ki67 staining) and inducing apoptosis (TUNEL staining). The combination of resveratrol and TRAIL was more effective in inhibiting tumor growth than single agent alone. In xenografted tumors, resveratrol upregulated the expressions of TRAIL-R1/DR4, TRAIL-R2/DR5, Bax and p27(/KIP1), and inhibited the expression of Bcl-2 and cyclin D1. Treatment of mice with resveratrol and TRAIL alone inhibited angiogenesis (as demonstrated by reduced number of blood vessels, and VEGF and VEGFR2 positive cells) and markers of metastasis (MMP-2 and MMP-9). The combination of resveratrol with TRAIL further inhibited number of blood vessels in tumors, and circulating endothelial growth factor receptor 2-positive endothelial cells than single agent alone. Furthermore, resveratrol inhibited the cytoplasmic phosphorylation of FKHRL1 resulting in its enhanced activation as demonstrated by increased DNA binding activity.These data suggest that resveratrol can enhance the apoptosis-inducing potential of TRAIL by activating FKHRL1 and its target genes. The ability of resveratrol to inhibit tumor growth, metastasis and angiogenesis, and enhance the therapeutic potential of TRAIL suggests that resveratrol alone or in combination with TRAIL can be used for the management of prostate cancer

Resveratrol Induces Growth Arrest and Apoptosis through Activation of FOXO Transcription Factors in Prostate Cancer Cells

Resveratrol, a naturally occurring phytopolyphenol compound, has attracted extensive interest in recent years because of its diverse pharmacological characteristics. Although resveratrol possesses chemopreventive properties against several cancers, the molecular mechanisms by which it inhibits cell growth and induces apoptosis have not been clearly understood. The present study was carried out to examine whether PI3K/AKT/FOXO pathway mediates the biological effects of resveratrol.Resveratrol inhibited the phosphorylation of PI3K, AKT and mTOR. Resveratrol, PI3K inhibitors (LY294002 and Wortmannin) and AKT inhibitor alone slightly induced apoptosis in LNCaP cells. These inhibitors further enhanced the apoptosis-inducing potential of resveratrol. Overexpression of wild-type PTEN slightly induced apoptosis. Wild type PTEN and PTEN-G129E enhanced resveratrol-induced apoptosis, whereas PTEN-G129R had no effect on proapoptotic effects of resveratrol. Furthermore, apoptosis-inducing potential of resveratrol was enhanced by dominant negative AKT, and inhibited by wild-type AKT and constitutively active AKT. Resveratrol has no effect on the expression of FKHR, FKHRL1 and AFX genes. The inhibition of FOXO phosphorylation by resveratrol resulted in its nuclear translocation, DNA binding and transcriptional activity. The inhibition of PI3K/AKT pathway induced FOXO transcriptional activity resulting in induction of Bim, TRAIL, p27/KIP1, DR4 and DR5, and inhibition of cyclin D1. Similarly, resveratrol-induced FOXO transcriptional activity was further enhanced when activation of PI3K/AKT pathway was blocked. Over-expression of phosphorylation deficient mutants of FOXO proteins (FOXO1-TM, FOXO3A-TM and FOXO4-TM) induced FOXO transcriptional activity, which was further enhanced by resveratrol. Inhibition of FOXO transcription factors by shRNA blocked resveratrol-induced upregulation of Bim, TRAIL, DR4, DR5, p27/KIP1 and apoptosis, and inhibition of cyclin D1 by resveratrol.These data suggest that FOXO transcription factors mediate anti-proliferative and pro-apoptotic effects of resveratrol, in part due to activation of extrinsic apoptosis pathway

Toxicity profile of bevacizumab in the UK Neurofibromatosis Type 2 cohort

Bevacizumab is considered an established part of the treatment strategies available for schwannomas in patients with Neurofibromatosis Type 2(NF2). In the UK, it is available through NHS National Specialized Commissioning to NF2 patients with a rapidly growing target schwannoma. Regrowth of the tumour on suspension of treatment is often observed resulting in prolonged periods of exposure to bevacizumab to control the disease. Hypertension and proteinuria are common events with bevacizumab use and there are concerns with regards to the long-term risks of prolonged treatment. Dosing, demographic and adverse event(CTCAE 4.03) data from the UK NF2 bevacizumab cohort are reviewed with particular consideration of renal and cardiovascular complications. Eighty patients (48 male:32female), median age 24.5 years (range 11-66years), were followed for a median of 32.7 months (range 12.0–60.2months). The most common adverse events were fatigue, hypertension and infection. A total of 19/80 patients (24%) had either a grade 2 or grade 3 hypertension event and 14/80 patients (17.5%) had proteinuria. Of 36 patients followed for 36 months, 78% were free from hypertension and 86% were free of proteinuria. Logistic regression modeling identified age and induction dosing regime to be predictors of development of hypertension with dose of 7.5mg/kg three weekly and age >30years having higher rates of hypertension. Proteinuria persisted in one of three patients after cessation of bevacizumab. One patient developed congestive heart failure and the details of this case are described. Further work is needed to determine optimal dosing regimes to limit toxicity without impacting on efficacy

Impact of AlphaFold on structure prediction of protein complexes: The CASP15-CAPRI experiment

We present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody-antigen complexes, and 7 large assemblies. On average ~70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21 941 models submitted by these groups and by 15 CAPRI scorer groups were evaluated using the CAPRI model quality measures and the DockQ score consolidating these measures. The prediction performance was quantified by a weighted score based on the number of models of acceptable quality or higher submitted by each group among their five best models. Results show substantial progress achieved across a significant fraction of the 60+ participating groups. High-quality models were produced for about 40% of the targets compared to 8% two years earlier. This remarkable improvement is due to the wide use of the AlphaFold2 and AlphaFold2-Multimer software and the confidence metrics they provide. Notably, expanded sampling of candidate solutions by manipulating these deep learning inference engines, enriching multiple sequence alignments, or integration of advanced modeling tools, enabled top performing groups to exceed the performance of a standard AlphaFold2-Multimer version used as a yard stick. This notwithstanding, performance remained poor for complexes with antibodies and nanobodies, where evolutionary relationships between the binding partners are lacking, and for complexes featuring conformational flexibility, clearly indicating that the prediction of protein complexes remains a challenging problem

Impact of AlphaFold on Structure Prediction of Protein Complexes: The CASP15-CAPRI Experiment

We present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homo-dimers, 3 homo-trimers, 13 hetero-dimers including 3 antibody-antigen complexes, and 7 large assemblies. On average ~70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21941 models submitted by these groups and by 15 CAPRI scorer groups were evaluated using the CAPRI model quality measures and the DockQ score consolidating these measures. The prediction performance was quantified by a weighted score based on the number of models of acceptable quality or higher submitted by each group among their 5 best models. Results show substantial progress achieved across a significant fraction of the 60+ participating groups. High-quality models were produced for about 40% for the targets compared to 8% two years earlier, a remarkable improvement resulting from the wide use of the AlphaFold2 and AlphaFold-Multimer software. Creative use was made of the deep learning inference engines affording the sampling of a much larger number of models and enriching the multiple sequence alignments with sequences from various sources. Wide use was also made of the AlphaFold confidence metrics to rank models, permitting top performing groups to exceed the results of the public AlphaFold-Multimer version used as a yard stick. This notwithstanding, performance remained poor for complexes with antibodies and nanobodies, where evolutionary relationships between the binding partners are lacking, and for complexes featuring conformational flexibility, clearly indicating that the prediction of protein complexes remains a challenging problem