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.

ReFOLD: a server for the refinement of 3D protein models guided by accurate quality estimates.

ReFOLD is a novel hybrid refinement server with integrated high performance global and local Accuracy Self Estimates (ASEs). The server attempts to identify and to fix likely errors in user supplied 3D models of proteins via successive rounds of refinement. The server is unique in providing output for multiple alternative refined models in a way that allows users to quickly visualize the key residue locations, which are likely to have been improved. This is important, as global refinement of a full chain model may not always be possible, whereas local regions, or individual domains, can often be much improved. Thus, users may easily compare the specific regions of the alternative refined models in which they are most interested e.g. key interaction sites or domains. ReFOLD was used to generate hundreds of alternative refined models for the CASP12 experiment, boosting our group's performance in the main tertiary structure prediction category. Our successful refinement of initial server models combined with our built-in ASEs were instrumental to our second place ranking on Template Based Modeling (TBM) and Free Modeling (FM)/TBM targets. The ReFOLD server is freely available at: http://www.reading.ac.uk/bioinf/ReFOLD/.

IntFOLD: an integrated server for modelling protein structures and functions from amino acid sequences.

IntFOLD is an independent web server that integrates our leading methods for structure and function prediction. The server provides a simple unified interface that aims to make complex protein modelling data more accessible to life scientists. The server web interface is designed to be intuitive and integrates a complex set of quantitative data, so that 3D modelling results can be viewed on a single page and interpreted by non-expert modellers at a glance. The only required input to the server is an amino acid sequence for the target protein. Here we describe major performance and user interface updates to the server, which comprises an integrated pipeline of methods for: tertiary structure prediction, global and local 3D model quality assessment, disorder prediction, structural domain prediction, function prediction and modelling of protein-ligand interactions. The server has been independently validated during numerous CASP (Critical Assessment of Techniques for Protein Structure Prediction) experiments, as well as being continuously evaluated by the CAMEO (Continuous Automated Model Evaluation) project. The IntFOLD server is available at: http://www.reading.ac.uk/bioinf/IntFOLD/.

Negative effects of nicotine on bone-resorbing cytokines and bone histomorphometric parameters in male rats.

The effects of nicotine administration on bone-resorbing cytokines, cotinine, and bone histomorphometric parameters were studied in 21 Sprague-Dawley male rats. Rats aged 3 months and weighing 250-300 g were divided into three groups. Group 1 was the baseline control (BC), which was killed without treatment. The other two groups were the control group (C) and the nicotine-treated group (N). The N group was treated with nicotine 7 mg/kg body weight and the C group was treated with normal saline only. Treatment was given by intraperitoneal injection for 6 days/week for 4 months. The rats were injected intraperitoneally with calcein 20 mg/kg body weight at day 9 and day 2 before they were killed. ELISA test kits were used to measure the serum interleukin-1 (IL-1), interleukin-6 (IL-6), and cotinine (a metabolite of nicotine) levels at the beginning of the study and upon completion of the study. Histomorphometric analysis was done on the metaphyseal region of the trabecular bone of the left femur by using an image analyzer. Biochemical analysis revealed that nicotine treatment for 4 months significantly increased the serum IL-1, IL-6, and cotinine levels as compared to pretreatment levels. In addition, the serum cotinine level was significantly higher in the N group than in the C group after 4 months treatment. Histomorphometric analysis showed that nicotine significantly decreased the trabecular bone volume (BV/TV), trabecular thickness (Tb.Th), double-labeled surface (dLS/BS), mineralizing surface (MS/BS), mineral appositional rate (MAR), and bone formation rate (BFR/BS), while causing an increase in the single-labeled surface (sLS/BS), osteoclast surface (Oc.S/BS), and eroded surface (ES/BS) as compared to the BC and C groups. In conclusion, treatment with nicotine 7 mg/kg for 4 months was detrimental to bone by causing an increase in the bone resorbing cytokines and cotinine levels. Nicotine also exerted negative effects on the dynamic trabecular histomorphometric parameters.