کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1257239 971552 2006 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Computational models for the prediction of polypeptide aggregation propensity
موضوعات مرتبط
مهندسی و علوم پایه شیمی شیمی (عمومی)
پیش نمایش صفحه اول مقاله
Computational models for the prediction of polypeptide aggregation propensity
چکیده انگلیسی

In amyloid fibrils, β-strand conformations of polypeptide chains, or segments thereof, are perpendicular to the fibril axis, but knowledge of their three dimensional structure at atomic level of detail is scarce. Two types of computational approaches have been developed recently for investigating the aggregation propensity of peptides and proteins and identifying the segments most prone to form fibrils (hot spots). The physicochemical properties of the natural amino acids (e.g. β-propensity, hydrophobicity, aromatic content and charge) have been used to derive phenomenological models able to predict changes in aggregation rate upon mutation, as well as absolute rates and hot spots. Applications of these models to entire proteomes have provided evidence that intrinsically disordered proteins are less amyloidogenic than globular proteins. In the second type of approach, amyloidogenic polypeptides have been decomposed into overlapping segments, and atomistic simulations of three or more copies of each segment have been performed to obtain insights into aggregation propensity and structural details of the ordered aggregates (e.g. turn regions).

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Current Opinion in Chemical Biology - Volume 10, Issue 5, October 2006, Pages 437–444
نویسندگان
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