CASP: A Driving Force in Protein Structure Modeling

Kryshtafovych, Andriy; Fidelis, Krzysztof; Moult, John

doi:10.1002/9780470882207.ch2

Cited by 5 publications

(5 citation statements)

References 43 publications

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“…• John Moult of the University of Maryland, a molecular biophysicist who has been a sparkplug of the CASP protein structure prediction contests since the very beginning, i.e. the early 1990's [21,22,23,24,25,26,27].…”

Section: The Challenge Paradigmmentioning

confidence: 99%

50 Years of Data Science

Donoho

2017

Journal of Computational and Graphical Statistics

576

471

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We enjoyed re-reading this important article from Donoho and are pleased to see it discussed here in JCGS.For context, we both trained as statisticians and spent several years as regular professors of Statistics. We still have academic appointments. Yet today we work for RStudio, building tools to improve the workflows for data scientists and statisticians. This gives us an informed and unique perspective on Donoho's piece, which explores aspects of the academic statistical establishment that are deeply connected with this unusual career path.Overall, much of the paper resonated with us. Our comments deal with three main areas: academic statistics, the skills meme, and coupling of cognitive and computation tools.

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Section: The Challenge Paradigmmentioning

confidence: 99%

50 Years of Data Science

Donoho

2017

Journal of Computational and Graphical Statistics

576

471

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“…New prediction categories deemed attainable are regularly introduced, and those where the progress is believed to have been exhausted are discontinued. 12 Quaternary structure has a rather peculiar history within the experiment. While oligomeric protein targets were incidentally featured in CASP2 (1996), 13 CASP7 (2006), 14 and CASP9 (2010), 15 the experiment was mainly focused on tertiary structure prediction.…”

Section: Introductionmentioning

confidence: 99%

“…By introducing new assessment categories, the CASP experiment shapes and drives the development of methods necessary to excel in them. 12 Recent breakthroughs in both domain structure 18 and contact predictions 19 suggest that higher-order complexity targets, protein assemblies, are feasible. Here we present our analysis of the CASP13 assembly predictions, compare the results to those of CASP12 and discuss the status and outlook of the field.…”

Section: Introductionmentioning

confidence: 99%

Assessment of protein assembly prediction in CASP13

et al. 2019

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We present the assembly category assessment in the 13th edition of the CASP community‐wide experiment. For the second time, protein assemblies constitute an independent assessment category. Compared to the last edition we see a clear uptake in participation, more oligomeric targets released, and consistent, albeit modest, improvement of the predictions quality. Looking at the tertiary structure predictions, we observe that ignoring the oligomeric state of the targets hinders modeling success. We also note that some contact prediction groups successfully predicted homomeric interfacial contacts, though it appears that these predictions were not used for assembly modeling. Homology modeling with sizeable human intervention appears to form the basis of the assembly prediction techniques in this round of CASP. Future developments should see more integrated approaches where subunits are modeled in the context of the assemblies they form.

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“…Different proteins may present different levels of modeling difficulty 9,10 . As a result, most comparison of performance on different target structures is meaningless without some form of relationship to difficulty.…”

Section: Target Difficulty Analysismentioning

confidence: 99%

CASP9 results compared to those of previous casp experiments

2011

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The quality of structure models submitted to CASP9 is analyzed in the context of previous CASPs. Comparison methods are similar to those used in previous papers in this series, with the addition of new methods for looking at model quality in regions not covered by a single best structural template, alignment accuracy, and progress for template free models. Progress in this CASP was again modest, and statistically hard to validate. Nevertheless, there are several positive trends. There is an indication of improvement in overall model quality for the mid-range of template based modeling difficulty, methods for identifying the best model from a set generated have improved, and there are strong indications of progress in the quality of template free models of short proteins. In addition, the new examination of model quality in regions of model not covered by the best available template reveals better performance than had previously been apparent.

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CASP: A Driving Force in Protein Structure Modeling

Cited by 5 publications

References 43 publications

50 Years of Data Science

50 Years of Data Science

Assessment of protein assembly prediction in CASP13

CASP9 results compared to those of previous casp experiments

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