scholarly journals Characterization of Transiently Stable Structural Motifs in Intrinsically Disordered Proteins using Free Energy Simulations

2015 ◽  
Vol 108 (2) ◽  
pp. 317a-318a ◽  
Author(s):  
Rainer Bomblies ◽  
Manuel Luitz ◽  
Martin Zacharias
2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Song-Ho Chong ◽  
Sihyun Ham

Abstract Folding funnel is the essential concept of the free energy landscape for ordered proteins. How does this concept apply to intrinsically disordered proteins (IDPs)? Here, we address this fundamental question through the explicit characterization of the free energy landscapes of the representative α-helical (HP-35) and β-sheet (WW domain) proteins and of an IDP (pKID) that folds upon binding to its partner (KIX). We demonstrate that HP-35 and WW domain indeed exhibit the steep folding funnel: the landscape slope for these proteins is ca. −50 kcal/mol, meaning that the free energy decreases by ~5 kcal/mol upon the formation of 10% native contacts. On the other hand, the landscape of pKID is funneled but considerably shallower (slope of −24 kcal/mol), which explains why pKID is disordered in free environments. Upon binding to KIX, the landscape of pKID now becomes significantly steep (slope of −54 kcal/mol), which enables otherwise disordered pKID to fold. We also show that it is the pKID–KIX intermolecular interactions originating from hydrophobic residues that mainly confer the steep folding funnel. The present work not only provides the quantitative characterization of the protein folding free energy landscape, but also establishes the usefulness of the folding funnel concept to IDPs.


2019 ◽  
Vol 73 (6-7) ◽  
pp. 305-317 ◽  
Author(s):  
Christoph Hartlmüller ◽  
Emil Spreitzer ◽  
Christoph Göbl ◽  
Fabio Falsone ◽  
Tobias Madl

2010 ◽  
Vol 132 (24) ◽  
pp. 8407-8418 ◽  
Author(s):  
Loïc Salmon ◽  
Gabrielle Nodet ◽  
Valéry Ozenne ◽  
Guowei Yin ◽  
Malene Ringkjøbing Jensen ◽  
...  

Author(s):  
Farid Rahimi

Aptamers are versatile oligonucleotide ligands used for molecular recognition of diverse targets. However, application of aptamers to the field of amyloid β-protein (Aβ) has been limited so far. Aβ is an intrinsically disordered protein that exists in a dynamic conformational equilibrium, presenting time-dependent ensembles of short-lived, metastable structures and assemblies that have been generally difficult to isolate and characterize. Moreover, despite understanding of potential physiological roles of Aβ, this peptide has been linked to the pathogenesis of Alzheimer disease, and its pathogenic roles remain controversial. Accumulated scientific evidence thus far highlights undesirable or nonspecific interactions between selected aptamers and different Aβ assemblies likely due to metastable nature of Aβ or inherent affinity of RNA oligonucleotides to β-sheet-rich fibrillar structures of amyloidogenic proteins. Accordingly, lessons drawn from Aβ–aptamer studies emphasize that purity and uniformity of the protein target and rigorous characterization of aptamers’ specificity are important for realizing and garnering the full potential of aptamers selected for recongizing Aβ or other intrinsically disordered proteins. This review summarizes studies of aptamers selected for recognizing different Aβ assemblies and highlights controversies, difficulties, and limitations of such studies.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Da-Wei Li ◽  
Alexandar L. Hansen ◽  
Chunhua Yuan ◽  
Lei Bruschweiler-Li ◽  
Rafael Brüschweiler

AbstractThe analysis of nuclear magnetic resonance (NMR) spectra for the comprehensive and unambiguous identification and characterization of peaks is a difficult, but critically important step in all NMR analyses of complex biological molecular systems. Here, we introduce DEEP Picker, a deep neural network (DNN)-based approach for peak picking and spectral deconvolution which semi-automates the analysis of two-dimensional NMR spectra. DEEP Picker includes 8 hidden convolutional layers and was trained on a large number of synthetic spectra of known composition with variable degrees of crowdedness. We show that our method is able to correctly identify overlapping peaks, including ones that are challenging for expert spectroscopists and existing computational methods alike. We demonstrate the utility of DEEP Picker on NMR spectra of folded and intrinsically disordered proteins as well as a complex metabolomics mixture, and show how it provides access to valuable NMR information. DEEP Picker should facilitate the semi-automation and standardization of protocols for better consistency and sharing of results within the scientific community.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Pablo Herrera-Nieto ◽  
Adrià Pérez ◽  
Gianni De Fabritiis

Abstract The exploration of intrinsically disordered proteins in isolation is a crucial step to understand their complex dynamical behavior. In particular, the emergence of partially ordered states has not been explored in depth. The experimental characterization of such partially ordered states remains elusive due to their transient nature. Molecular dynamics mitigates this limitation thanks to its capability to explore biologically relevant timescales while retaining atomistic resolution. Here, millisecond unbiased molecular dynamics simulations were performed in the exemplar N-terminal region of p53. In combination with state-of-the-art Markov state models, simulations revealed the existence of several partially ordered states accounting for $$\sim $$ ∼ 40% of the equilibrium population. Some of the most relevant states feature helical conformations similar to the bound structure of p53 to Mdm2, as well as novel $$\beta $$ β -sheet elements. This highlights the potential complexity underlying the energy surface of intrinsically disordered proteins.


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