Evaluation of Protein Structure Prediction Methods: Issues and Strategies

Tramontano, Anna; Cozzetto, Domenico

doi:10.1007/978-1-4419-6889-0_14

Cited by 3 publications

(2 citation statements)

References 95 publications

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“…We then investigated the stability of the final ranking under a wide range of conditions, which may reflect different assessment options—see Supporting Information Table S2. Although the conversion of raw scores—the Δ Q values in our case—into target‐based Z ‐scores is well‐established practice at CASP, the assessors made use of parametric statistics in CASP8 and of nonparametric statistics in CASP9. Here, we have adopted the same ranking procedure as last time, but we have also confirmed that using mean and standard deviation to compute the Z Q scores and to combine them has very limited effects on the evaluation results of the top ranked groups.…”

Section: Resultsmentioning

confidence: 99%

Evaluation of predictions in the CASP10 model refinement category

2014

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Here we report on the assessment results of the third experiment to evaluate the state of the art in protein model refinement, where participants were invited to improve the accuracy of initial protein models for 27 targets. Using an array of complementary evaluation measures, we find that five groups performed better than the naïve (null) method—a marked improvement over CASP9, although only three were significantly better. The leading groups also demonstrated the ability to consistently improve both backbone and side chain positioning, while other groups reliably enhanced other aspects of protein physicality. The top-ranked group succeeded in improving the backbone conformation in almost 90% of targets, suggesting a strategy that for the first time in CASP refinement is successful in a clear majority of cases. A number of issues remain unsolved: the majority of groups still fail to improve the quality of the starting models; even successful groups are only able to make modest improvements; and no prediction is more similar to the native structure than to the starting model. Successful refinement attempts also often go unrecognized, as suggested by the relatively larger improvements when predictions not submitted as model 1 are also considered. Proteins 2014; 82(Suppl 2):98–111.

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Section: Resultsmentioning

confidence: 99%

Evaluation of predictions in the CASP10 model refinement category

2014

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“…The best template(s) can be chosen according to different ways. These include (but they are not limited to) as described in [ 60 ]: (i) the selection of the template with the highest sequence similarity; (ii) the modeling of a theoretical template as average of other templates (ii) the unification of different templates for different regions to maximize the local similarity in each region; (iii) the derivation of constraints/restraints from templates and the successive construction of models that satisfy as many of these constraints as possible.…”

Section: Proteins Structural Predictionsmentioning

confidence: 99%

Designing the Sniper: Improving Targeted Human Cytolytic Fusion Proteins for Anti-Cancer Therapy via Molecular Simulation

et al. 2017

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Targeted human cytolytic fusion proteins (hCFPs) are humanized immunotoxins for selective treatment of different diseases including cancer. They are composed of a ligand specifically binding to target cells genetically linked to a human apoptosis-inducing enzyme. hCFPs target cancer cells via an antibody or derivative (scFv) specifically binding to e.g., tumor associated antigens (TAAs). After internalization and translocation of the enzyme from endocytosed endosomes, the human enzymes introduced into the cytosol are efficiently inducing apoptosis. Under in vivo conditions such enzymes are subject to tight regulation by native inhibitors in order to prevent inappropriate induction of cell death in healthy cells. Tumor cells are known to up-regulate these inhibitors as a survival mechanism resulting in escape of malignant cells from elimination by immune effector cells. Cytosolic inhibitors of Granzyme B and Angiogenin (Serpin P9 and RNH1, respectively), reduce the efficacy of hCFPs with these enzymes as effector domains, requiring detrimentally high doses in order to saturate inhibitor binding and rescue cytolytic activity. Variants of Granzyme B and Angiogenin might feature reduced affinity for their respective inhibitors, while retaining or even enhancing their catalytic activity. A powerful tool to design hCFPs mutants with improved potency is given by in silico methods. These include molecular dynamics (MD) simulations and enhanced sampling methods (ESM). MD and ESM allow predicting the enzyme-protein inhibitor binding stability and the associated conformational changes, provided that structural information is available. Such “high-resolution” detailed description enables the elucidation of interaction domains and the identification of sites where particular point mutations may modify those interactions. This review discusses recent advances in the use of MD and ESM for hCFP development from the viewpoints of scientists involved in both fields.

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