ArticleJournal of structural biology2010
Prediction of protein crystallization outcome using a hybrid method.
Article in Journal of structural biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- High-Throughput Screening to Obtain Crystal Hits for Protein Crystallography.Journal of visualized experiments : JoVE · 2023Article
- Selection of Biophysical Methods for Characterisation of Membrane Proteins.International journal of molecular sciences · 2019Review
- Statistical analysis of crystallization database links protein physico-chemical features with crystallization mechanisms.PloS one · 2014Article
- PROSPERO: online prediction of crystallographic success from experimental results and sequence.Journal of applied crystallography · 2012Article
- Computational approaches to selecting and optimising targets for structural biology.Methods (San Diego, Calif.) · 2011Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
20 authors.
Funding
Abstract
The great power of protein crystallography to reveal biological structure is often limited by the tremendous effort required to produce suitable crystals. A hybrid crystal growth predictive model is presented that combines both experimental and sequence-derived data from target proteins, including novel variables derived from physico-chemical characterization such as R(30), the ratio between a protein's DSF intensity at 30°C and at T(m). This hybrid model is shown to be more powerful than sequence-based prediction alone - and more likely to be useful for prioritizing and directing the efforts of structural genomics and individual structural biology laboratories.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.