A
Andrea Cavalli
Researcher at University of Lugano
Publications - 89
Citations - 4931
Andrea Cavalli is an academic researcher from University of Lugano. The author has contributed to research in topics: Chemical shift & Protein structure. The author has an hindex of 34, co-authored 89 publications receiving 4197 citations. Previous affiliations of Andrea Cavalli include European Bioinformatics Institute & University of Cambridge.
Papers
More filters
Journal ArticleDOI
Protein structure determination from NMR chemical shifts.
TL;DR: It is shown that it is possible to use chemical shifts as structural restraints in combination with a conventional molecular mechanics force field to determine the conformations of proteins at a resolution of 2 Å or better.
Journal ArticleDOI
Androgen-deprivation therapies for prostate cancer and risk of infection by SARS-CoV-2: a population-based study (N = 4532).
Monica Montopoli,Sara Zumerle,Roberto Vettor,Massimo Rugge,Manuel Zorzi,Carlo V. Catapano,Giuseppina M. Carbone,Andrea Cavalli,Francesco Pagano,Eugenio Ragazzi,Tommaso Prayer-Galetti,Andrea Alimonti +11 more
TL;DR: It is suggested that cancer patients have an increased risk of SARS-CoV-2 infections than non-cancer patients, however, prostate cancer patients receiving androgen-deprivation therapy (ADT) appear to be partially protected from Sars- CoV- 2 infections.
Journal ArticleDOI
Structure of an Intermediate State in Protein Folding and Aggregation
Philipp Neudecker,Paul Robustelli,Andrea Cavalli,Patrick Walsh,Patrik Lundström,Arash Zarrine-Afsar,Simon Sharpe,Michele Vendruscolo,Lewis E. Kay +8 more
TL;DR: The structure provides a detailed characterization of the non-native interactions stabilizing an aggregation-prone intermediate under native conditions and insight into how such an intermediate can derail folding and initiate fibrillation.
Journal ArticleDOI
Fast and accurate predictions of protein NMR chemical shifts from interatomic distances.
TL;DR: The calculations performed by CamShift are based on an approximate expression of the chemical shifts in terms of polynomial functions of interatomic distances, which can be utilized in standard protein structure calculation protocols.
Journal ArticleDOI
Prediction of aggregation rate and aggregation-prone segments in polypeptide sequences.
TL;DR: A model based on physicochemical properties and computational design of β‐aggregating peptide sequences is shown to be able to predict the aggregation rate over a large set of natural polypeptide sequences.