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Carlos Pintado-Grima

dblp:363/3595 · also Carlos Pintado · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2021
0000-0002-8544-959XORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › protein analysis › protein bioinformatics
protein aggregation prediction
0.512021
SolupHred: a server to predict the pH-dependent aggregation of intrinsically disordered proteins · Bioinform. 2021
Bioinformatics and computational biology › protein structure analysis › intrinsically disordered protein
intrinsically disordered protein analysis
0.112021
SolupHred: a server to predict the pH-dependent aggregation of intrinsically disordered proteins · Bioinform. 2021

Methods — techniques the papers use, named apart from their topics

phenomenological model · 0.5lipophilicity and charge modeling · 0.5
YearPublicationVenuePosition
2021 SolupHred: a server to predict the pH-dependent aggregation of intrinsically disordered proteins
abstract
SUMMARY: Polypeptides are exposed to changing environmental conditions that modulate their intrinsic aggregation propensities. Intrinsically disordered proteins (IDPs) constitutively expose their aggregation determinants to the solvent, thus being especially sensitive to its fluctuations. However, solvent conditions are often disregarded in computational aggregation predictors. We recently developed a phenomenological model to predict IDPs' solubility as a function of the solution pH, which is based on the assumption that both protein lipophilicity and charge depend on this parameter. The model anticipated solubility changes in different IDPs accurately. In this application note, we present SolupHred, a web-based interface that implements the aforementioned theoretical framework into a predictive tool able to compute IDPs aggregation propensities as a function of pH. SolupHred is the first dedicated software for the prediction of pH-dependent protein aggregation. AVAILABILITY AND IMPLEMENTATION: The SolupHred web server is freely available for academic users at: https://ppmclab.pythonanywhere.com/SolupHred. It is platform-independent and does not require previous registration. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Carlos Pintado-Grima, Jaime Santos, Valentín Iglesias, Salvador Ventura
Bioinform.1