IntFOLD: an integrated web resource for high performance protein structure and function prediction.

The IntFOLD server provides a unified resource for the automated prediction of: protein tertiary structures with built-in estimates of model accuracy (EMA), protein structural domain boundaries, natively unstructured or disordered regions in proteins, and protein-ligand interactions. The component methods have been independently evaluated via the successive blind CASP experiments and the continual CAMEO benchmarking project. The IntFOLD server has established its ranking as one of the best performing publicly available servers, based on independent official evaluation metrics. Here, we describe significant updates to the server back end, where we have focused on performance improvements in tertiary structure predictions, in terms of global 3D model quality and accuracy self-estimates (ASE), which we achieve using our newly improved ModFOLD7_rank algorithm. We also report on various upgrades to the front end including: a streamlined submission process, enhanced visualization of models, new confidence scores for ranking, and links for accessing all annotated model data. Furthermore, we now include an option for users to submit selected models for further refinement via convenient push buttons. The IntFOLD server is freely available at: http://www.reading.ac.uk/bioinf/IntFOLD/.

Accurate template-based modeling in CASP12 using the IntFOLD4-TS, ModFOLD6, and ReFOLD methods.

Our aim in CASP12 was to improve our Template-Based Modeling (TBM) methods through better model selection, accuracy self-estimate (ASE) scores and refinement. To meet this aim, we developed two new automated methods, which we used to score, rank, and improve upon the provided server models. Firstly, the ModFOLD6_rank method, for improved global Quality Assessment (QA), model ranking and the detection of local errors. Secondly, the ReFOLD method for fixing errors through iterative QA guided refinement. For our automated predictions we developed the IntFOLD4-TS protocol, which integrates the ModFOLD6_rank method for scoring the multiple-template models that were generated using a number of alternative sequence-structure alignments. Overall, our selection of top models and ASE scores using ModFOLD6_rank was an improvement on our previous approaches. In addition, it was worthwhile attempting to repair the detected errors in the top selected models using ReFOLD, which gave us an overall gain in performance. According to the assessors' formula, the IntFOLD4 server ranked 3rd/5th (average Z-score > 0.0/-2.0) on the server only targets, and our manual predictions (McGuffin group) ranked 1st/2nd (average Z-score > -2.0/0.0) compared to all other groups.

Predictive and Experimental Approaches for Elucidating Protein-Protein Interactions and Quaternary Structures.

The elucidation of protein-protein interactions is vital for determining the function and action of quaternary protein structures. Here, we discuss the difficulty and importance of establishing protein quaternary structure and review in vitro and in silico methods for doing so. Determining the interacting partner proteins of predicted protein structures is very time-consuming when using in vitro methods, this can be somewhat alleviated by use of predictive methods. However, developing reliably accurate predictive tools has proved to be difficult. We review the current state of the art in predictive protein interaction software and discuss the problem of scoring and therefore ranking predictions. Current community-based predictive exercises are discussed in relation to the growth of protein interaction prediction as an area within these exercises. We suggest a fusion of experimental and predictive methods that make use of sparse experimental data to determine higher resolution predicted protein interactions as being necessary to drive forward development.

A novel therapeutic with two SNAP-25 inactivating proteases shows long-lasting anti-hyperalgesic activity in a rat model of neuropathic pain.

A pressing need exists for long-acting, non-addictive medicines to treat chronic pain, a major societal burden. Botulinum neurotoxin type A (BoNT/A) complex - a potent, specific and prolonged inhibitor of neuro-exocytosis - gives some relief in several pain disorders, but not for all patients. Our study objective was to modify BoNT/A to overcome its inability to block transmitter release elicited by high [Ca2+]i and increase its limited analgesic effects. This was achieved by fusing a BoNT/A gene to that for the light chain (LC) of type/E. The resultant purified protein, LC/E-BoNT/A, entered cultured sensory neurons and, unlike BoNT/A, inhibited release of calcitonin gene-related peptide evoked by capsaicin. Western blotting revealed that this improvement could be due to a more extensive truncation by LC/E of synaptosomal-associated protein of Mr = 25 k, essential for neuro-exocytosis. When tested in a rat spared nerve injury (SNI) model, a single intra-plantar (IPL) injection of LC/E-BoNT/A alleviated for ∼2 weeks mechanical and cold hyper-sensitivities, in a dose-dependent manner. The highest non-paralytic dose (75 U/Kg, IPL) proved significantly more efficacious than BoNT/A (15 U/Kg, IPL) or repeated systemic pregabalin (10 mg/Kg, intraperitoneal), a clinically-used pain modulator. Effects of repeated or delayed injections of this fusion protein highlighted its analgesic potential. Attenuation of mechanical hyperalgesia was extended by a second administration when the effect of the first had diminished. When injected 5 weeks after injury, LC/E-BoNT/A also reversed fully-established mechanical and cold hyper-sensitivity. Thus, combining advantageous features of BoNT/E and/A yields an efficacious, locally-applied and long-acting anti-hyperalgesic.