A conservation and rigidity based method for detecting critical protein residues

Background

Certain amino acids in proteins play a critical role in determining their structural stability and function. Examples include flexible regions such as hinges which allow domain motion, and highly conserved residues on functional interfaces which allow interactions with other proteins. Detecting these regions can aid in the analysis and simulation of protein rigidity and conformational changes, and helps characterizing protein binding and docking. We present an analysis of critical residues in proteins using a combination of two complementary techniques. One method performs in-silico mutations and analyzes the protein's rigidity to infer the role of a point substitution to Glycine or Alanine. The other method uses evolutionary conservation to find functional interfaces in proteins.

Results

We applied the two methods to a dataset of proteins, including biomolecules with experimentally known critical residues as determined by the free energy of unfolding. Our results show that the combination of the two methods can detect the vast majority of critical residues in tested proteins.

Conclusions

Our results show that the combination of the two methods has the potential to detect more information than each method separately. Future work will provide a confidence level for the criticalness of a residue to improve the accuracy of our method and eliminate false positives. Once the combined methods are integrated into one scoring function, it can be applied to other domains such as estimating functional interfaces.

     

Inhibition of Fatty Acid Amidohydrolase,the Enzyme Responsible for the Metabolism of the Endocannabinoid Anandamide,by Analogues of Arachidonoyl-serotonin

Arachidonoyl-serotonin inhibits in a mixed-type manner the metabolism of the endocannabinoid anandamide by the enzyme fatty acid amidohydrolase. In the present study, compounds related to arachidonoyl-serotonin have been synthesised and investigated for their ability to inhibit anandamide hydrolysis by this enzyme in rat brain homogenates. Removal of the 5-hydroxy from the serotonin head group of arachidonoyl-serotonin produced a compound (N-arachidonoyltryptamine) that was a 2.3-fold weaker inhibitor of anandamide hydrolysis, but which also produced its inhibition by a mixed-type manner (K_i(slope) 1.3 µM; K_i(intercept) 44 µM). Replacement of the amide linkage in this compound by an ester group further reduced the potency. In contrast, replacement of the arachidonoyl side chain by a linolenoyl side chain did not affect the observed potency. N-(Fur-3-ylmethyl) arachidonamide (UCM707), N-(fur-3-ylmethyl)linolenamide and N-(fur-3-ylmethyl)oleamide inhibited anandamide hydrolysis with pI50 values of 4.53, 5.36 and 5.25, respectively. The linolenamide derivative was also found to be a mixed-type inhibitor. It is concluded that the 5-hydroxy group of arachidonoyl-serotonin contributes to, but is not essential for, inhibitory potency at fatty acid amidohydrolase.     

Increased dosage of Ink4/Arf protects against glucose intolerance and insulin resistance associated with aging

Recent genome‐wide association studies have linked type‐2 diabetes mellitus to a genomic region in chromosome 9p21 near the Ink4/Arf locus, which encodes tumor suppressors that are up‐regulated in a variety of mammalian organs during aging. However, it is unclear whether the susceptibility to type‐2 diabetes is associated with altered expression of the Ink4/Arf locus. In the present study, we investigated the role of Ink4/Arf in age‐dependent alterations of insulin and glucose homeostasis using Super‐Ink4/Arf mice which bear an extra copy of the entire Ink4/Arf locus. We find that, in contrast to age‐matched wild‐type controls, Super‐Ink4/Arf mice do not develop glucose intolerance with aging. Insulin tolerance tests demonstrated increased insulin sensitivity in Super‐Ink4/Arf compared with wild‐type mice, which was accompanied by higher activation of the insulin receptor substrate (IRS)‐PI3K‐AKT pathway in liver, skeletal muscle and heart. Glucose uptake studies in Super‐Ink4/Arf mice showed a tendency toward increased ¹⁸F‐fluorodeoxyglucose uptake in skeletal muscle compared with wild‐type mice (P = 0.079). Furthermore, a positive correlation between glucose uptake and baseline glucose levels was observed in Super‐Ink4/Arf mice (P < 0.008) but not in wild‐type mice. Our studies reveal a protective role of the Ink4/Arf locus against the development of age‐dependent insulin resistance and glucose intolerance.     

Predicting beta-turns in proteins using support vector machines with fractional polynomials

Background

β-turns are secondary structure type that have essential role in molecular recognition, protein folding, and stability. They are found to be the most common type of non-repetitive structures since 25% of amino acids in protein structures are situated on them. Their prediction is considered to be one of the crucial problems in bioinformatics and molecular biology, which can provide valuable insights and inputs for the fold recognition and drug design.

Results

We propose an approach that combines support vector machines (SVMs) and logistic regression (LR) in a hybrid prediction method, which we call (H-SVM-LR) to predict β-turns in proteins. Fractional polynomials are used for LR modeling. We utilize position specific scoring matrices (PSSMs) and predicted secondary structure (PSS) as features. Our simulation studies show that H-SVM-LR achieves Qtotal of 82.87%, 82.84%, and 82.32% on the BT426, BT547, and BT823 datasets respectively. These values are the highest among other β-turns prediction methods that are based on PSSMs and secondary structure information. H-SVM-LR also achieves favorable performance in predicting β-turns as measured by the Matthew's correlation coefficient (MCC) on these datasets. Furthermore, H-SVM-LR shows good performance when considering shape strings as additional features.

Conclusions

In this paper, we present a comprehensive approach for β-turns prediction. Experiments show that our proposed approach achieves better performance compared to other competing prediction methods.

     

Integrating domain similarity to improve protein complexes identification in TAP-MS data

Background

Detecting protein complexes in protein-protein interaction (PPI) networks plays an important role in improving our understanding of the dynamic of cellular organisation. However, protein interaction data generated by high-throughput experiments such as yeast-two-hybrid (Y2H) and tandem affinity-purification/mass-spectrometry (TAP-MS) are characterised by the presence of a significant number of false positives and false negatives. In recent years there has been a growing trend to incorporate diverse domain knowledge to support large-scale analysis of PPI networks.

Methods

This paper presents a new algorithm, by incorporating Gene Ontology (GO) based semantic similarities, to detect protein complexes from PPI networks generated by TAP-MS. By taking co-complex relations in TAP-MS data into account, TAP-MS PPI networks are modelled as bipartite graph, where bait proteins consist of one set of nodes and prey proteins are on the other. Similarities between pairs of bait proteins are computed by considering both the topological features and GO-driven semantic similarities. Bait proteins are then grouped in to sets of clusters based on their pair-wise similarities to produce a set of 'seed' clusters. An expansion process is applied to each 'seed' cluster to recruit prey proteins which are significantly associated with the same set of bait proteins. Thus, completely identified protein complexes are then obtained.

Results

The proposed algorithm has been applied to real TAP-MS PPI networks. Fifteen quality measures have been employed to evaluate the quality of generated protein complexes. Experimental results show that the proposed algorithm has greatly improved the accuracy of identifying complexes and outperformed several state-of-the-art clustering algorithms. Moreover, by incorporating semantic similarity, the proposed algorithm is more robust to noises in the networks.

     

Rapid sampling of local minima in protein energy surface and effective reduction through a multi-objective filter

Background

Many problems in protein modeling require obtaining a discrete representation of the protein conformational space as an ensemble of conformations. In ab-initio structure prediction, in particular, where the goal is to predict the native structure of a protein chain given its amino-acid sequence, the ensemble needs to satisfy energetic constraints. Given the thermodynamic hypothesis, an effective ensemble contains low-energy conformations which are similar to the native structure. The high-dimensionality of the conformational space and the ruggedness of the underlying energy surface currently make it very difficult to obtain such an ensemble. Recent studies have proposed that Basin Hopping is a promising probabilistic search framework to obtain a discrete representation of the protein energy surface in terms of local minima. Basin Hopping performs a series of structural perturbations followed by energy minimizations with the goal of hopping between nearby energy minima. This approach has been shown to be effective in obtaining conformations near the native structure for small systems. Recent work by us has extended this framework to larger systems through employment of the molecular fragment replacement technique, resulting in rapid sampling of large ensembles.

Methods

This paper investigates the algorithmic components in Basin Hopping to both understand and control their effect on the sampling of near-native minima. Realizing that such an ensemble is reduced before further refinement in full ab-initio protocols, we take an additional step and analyze the quality of the ensemble retained by ensemble reduction techniques. We propose a novel multi-objective technique based on the Pareto front to filter the ensemble of sampled local minima.

Results and conclusions

We show that controlling the magnitude of the perturbation allows directly controlling the distance between consecutively-sampled local minima and, in turn, steering the exploration towards conformations near the native structure. For the minimization step, we show that the addition of Metropolis Monte Carlo-based minimization is no more effective than a simple greedy search. Finally, we show that the size of the ensemble of sampled local minima can be effectively and efficiently reduced by a multi-objective filter to obtain a simpler representation of the probed energy surface.

     

B-cell depletion in SLE: clinical and trial experience with rituximab and ocrelizumaband implications for study design

B cells are believed to be central to the disease process in systemic lupuserythematosus (SLE), making them a target for new therapeutic intervention. In recentyears there have been many publications regarding the experience in SLE of B-celldepletion utilising rituximab, an anti-CD20 mAb that temporarily depletes B cells,reporting promising results in uncontrolled open studies and in routine clinical use.However, the two large randomised controlled trials in extra-renal lupus (EXPLORERstudy) and lupus nephritis (LUNAR study) failed to achieve their primary endpoints.Based on the clinical experience with rituximab this failure was somewhat unexpectedand raised a number of questions and concerns, not only into the true level ofbenefit of B-cell depletion in a broad population but also how to test the true levelof effectiveness of an investigational agent as we seek to improve the design oftherapeutic trials in SLE. A better understanding of what went wrong in these trialsis essential to elucidate the underlying reasons for the disparate observations notedin open studies and controlled trials. In this review, we focus on various factorsthat may affect the ability to accurately and confidently establish the level oftreatment effect of the investigational agent, in this case rituximab, in the twostudies and explore hurdles faced in the randomised controlled trials investigatingthe efficacy of ocrelizumab, the humanised anti-CD20 mAb, in SLE. Further, based onthe lessons learned from the clinical trials, we make suggestions that could beimplemented in future clinical trial design to overcome the hurdles faced.     

The use of H2 antagonists in treating and preventing NSAID-induced mucosal damage

Pain affects the quality of life for millions of individuals and is a major reason for healthcare utilization. As populations age, medical personnel will need to manage more and more patients suffering from pain associated with degenerative and inflammatory musculoskeletal disorders. Nonsteroidal anti-inflammatory drugs (NSAIDs) are an effective treatment for both acute and chronic musculoskeletal pain; however, their use is associated with potentially significant gastrointestinal (GI) toxicity. Guidelines suggest various strategies to prevent problems in those at risk for NSAID-associated GI complications. In this article, we review the data supporting one such strategy - the use of histamine type-2 receptor antagonists (H2RAs) - for the prevention of GI adverse events in NSAID users. Older studies suggest that high-dose H2RAs are effective in preventing upper GI ulcers and dyspepsia. This suggestion was recently confirmed during clinical trials with a new ibuprofen/famotidine combination that reduced the risk of ulcers by 50% compared with ibuprofen alone.     

Novel Series of [ddN]-[TSAO-T] Heterodimers as Potential Bi-Functional Inhibitors of HIV-1 RT. Studies in the Linker and ddN Region

Abstract

Novel series of [ddN]-(CH₂)_n-[TSAO-T] heterodimers have been prepared and tested for their anti-HIV-1 and HIV-2 activity. The most active compound of this series was the [d4T]-(CH₂)₃-[TSAO-T] heterodimer (EC₅₀ = 0.018 ± 0.03 μM).     

A New Synthesis of 2′,3′-Didehydro-3′-deoxy-3-Alkylthymidine

Abstract

The preparation of 3-alkyl D4T derivatives has been carried out starting from the corresponding 5′-O-t-butyldimethylsilyl-3′-O-methanesulfonylthymidine 2 by way of deprotection-elimination and succesive alkylation reactions.