Characterization of the Binding of Small Molecules to Intrinsically Disordered Proteins

2018 ◽  
pp. 677-702 ◽  
Author(s):  
Veselin S. Dobrev ◽  
Lisette M. Fred ◽  
Kaitlyn P. Gerhart ◽  
Steven J. Metallo
Keyword(s):  
Small Molecules ◽  
Intrinsically Disordered Proteins ◽  
Disordered Proteins ◽  
Intrinsically Disordered

scholarly journals NMR characterization of solvent accessibility and transient structure in intrinsically disordered proteins

2019 ◽  
Vol 73 (6-7) ◽  
pp. 305-317 ◽  
Author(s):  
Christoph Hartlmüller ◽  
Emil Spreitzer ◽  
Christoph Göbl ◽  
Fabio Falsone ◽  
Tobias Madl
Keyword(s):  
Intrinsically Disordered Proteins ◽  
Solvent Accessibility ◽  
Disordered Proteins ◽  
Intrinsically Disordered ◽  
Nmr Characterization ◽  
Transient Structure

scholarly journals Targeting Intrinsically Disordered Proteins through Dynamic Interactions

Biomolecules ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 743
Author(s):  
Jianlin Chen ◽  
Xiaorong Liu ◽  
Jianhan Chen
Keyword(s):  
Small Molecules ◽  
Intrinsically Disordered Proteins ◽  
Gpu Computing ◽  
Disordered Proteins ◽  
Atomistic Simulations ◽  
Conformational Ensemble ◽  
Processing Unit ◽  
Dynamic Interactions ◽  
Intrinsically Disordered ◽  
Interaction Sites

Intrinsically disordered proteins (IDPs) are over-represented in major disease pathways and have attracted significant interest in understanding if and how they may be targeted using small molecules for therapeutic purposes. While most existing studies have focused on extending the traditional structure-centric drug design strategies and emphasized exploring pre-existing structure features of IDPs for specific binding, several examples have also emerged to suggest that small molecules could achieve specificity in binding IDPs and affect their function through dynamic and transient interactions. These dynamic interactions can modulate the disordered conformational ensemble and often lead to modest compaction to shield functionally important interaction sites. Much work remains to be done on further elucidation of the molecular basis of the dynamic small molecule–IDP interaction and determining how it can be exploited for targeting IDPs in practice. These efforts will rely critically on an integrated experimental and computational framework for disordered protein ensemble characterization. In particular, exciting advances have been made in recent years in enhanced sampling techniques, Graphic Processing Unit (GPU)-computing, and protein force field optimization, which have now allowed rigorous physics-based atomistic simulations to generate reliable structure ensembles for nontrivial IDPs of modest sizes. Such de novo atomistic simulations will play crucial roles in exploring the exciting opportunity of targeting IDPs through dynamic interactions.

scholarly journals NMR Characterization of Long-Range Order in Intrinsically Disordered Proteins

2010 ◽  
Vol 132 (24) ◽  
pp. 8407-8418 ◽  
Author(s):  
Loïc Salmon ◽  
Gabrielle Nodet ◽  
Valéry Ozenne ◽  
Guowei Yin ◽  
Malene Ringkjøbing Jensen ◽  
...  
Keyword(s):  
Long Range ◽  
Intrinsically Disordered Proteins ◽  
Range Order ◽  
Disordered Proteins ◽  
Long Range Order ◽  
Intrinsically Disordered ◽  
Nmr Characterization

scholarly journals Aptamers Selected for Recognizing Amyloid β-protein—A Case for Cautious Optimism

2018 ◽  
Author(s):  
Farid Rahimi
Keyword(s):  
Intrinsically Disordered Proteins ◽  
Scientific Evidence ◽  
Protein A ◽  
Intrinsically Disordered Protein ◽  
Disordered Proteins ◽  
Full Potential ◽  
Amyloid Beta Protein ◽  
Intrinsically Disordered ◽  
Metastable Structures

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.

scholarly journals Folding Free Energy Landscape of Ordered and Intrinsically Disordered Proteins

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Song-Ho Chong ◽  
Sihyun Ham
Keyword(s):  
Free Energy ◽  
Intrinsically Disordered Proteins ◽  
Energy Landscape ◽  
Disordered Proteins ◽  
Free Energy Landscape ◽  
Ww Domain ◽  
Intrinsically Disordered ◽  
Ca 50 ◽  
Folding Free Energy

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.

scholarly journals DEEP picker is a deep neural network for accurate deconvolution of complex two-dimensional NMR spectra

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Da-Wei Li ◽  
Alexandar L. Hansen ◽  
Chunhua Yuan ◽  
Lei Bruschweiler-Li ◽  
Rafael Brüschweiler
Keyword(s):  
Neural Network ◽  
Nmr Spectra ◽  
Deep Neural Network ◽  
Intrinsically Disordered Proteins ◽  
Disordered Proteins ◽  
Two Dimensional ◽  
Molecular Systems ◽  
Intrinsically Disordered ◽  
Identification And Characterization

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.

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