Literature DB >> 32268219

Experimentally-driven protein structure modeling.

Nikolay V Dokholyan1.   

Abstract

Revolutions in natural and exact sciences started at the dawn of last century have led to the explosion of theoretical, experimental, and computational approaches to determine structures of molecules, complexes, as well as their rich conformational dynamics. Since different experimental methods produce information that is attributed to specific time and length scales, corresponding computational methods have to be tailored to these scales and experiments. These methods can be then combined and integrated in scales, hence producing a fuller picture of molecular structure and motion from the "puzzle pieces" offered by various experiments. Here, we describe a number of computational approaches to utilize experimental data to glance into structure of proteins and understand their dynamics. We will also discuss the limitations and the resolution of the constraints-based modeling approaches. SIGNIFICANCE: Experimentally-driven computational structure modeling and determination is a rapidly evolving alternative to traditional approaches for molecular structure determination. These new hybrid experimental-computational approaches are proving to be a powerful microscope to glance into the structural features of intrinsically or partially disordered proteins, dynamics of molecules and complexes. In this review, we describe various approaches in the field of experimentally-driven computational structure modeling.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Discrete molecular dynamics; Mass spectrometry; Molecular dynamics simulations; Molecular modeling; Statistical mechanics; Structural proteomics

Year:  2020        PMID: 32268219      PMCID: PMC7214187          DOI: 10.1016/j.jprot.2020.103777

Source DB:  PubMed          Journal:  J Proteomics        ISSN: 1874-3919            Impact factor:   4.044


  159 in total

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3.  Local unfolding of Cu, Zn superoxide dismutase monomer determines the morphology of fibrillar aggregates.

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Review 4.  The coming of age of de novo protein design.

Authors:  Po-Ssu Huang; Scott E Boyken; David Baker
Journal:  Nature       Date:  2016-09-15       Impact factor: 49.962

5.  Nucleation, rapid folding, and globular intrachain regions in proteins.

Authors:  D B Wetlaufer
Journal:  Proc Natl Acad Sci U S A       Date:  1973-03       Impact factor: 11.205

6.  New insights into FAK signaling and localization based on detection of a FAT domain folding intermediate.

Authors:  Richard D S Dixon; Yiwen Chen; Feng Ding; Sagar D Khare; Kirk C Prutzman; Michael D Schaller; Sharon L Campbell; Nikolay V Dokholyan
Journal:  Structure       Date:  2004-12       Impact factor: 5.006

Review 7.  Conformational conversion of prion protein in prion diseases.

Authors:  Zheng Zhou; Gengfu Xiao
Journal:  Acta Biochim Biophys Sin (Shanghai)       Date:  2013-04-11       Impact factor: 3.848

8.  Disorder transitions and conformational diversity cooperatively modulate biological function in proteins.

Authors:  Diego Javier Zea; Alexander Miguel Monzon; Claudia Gonzalez; María Silvina Fornasari; Silvio C E Tosatto; Gustavo Parisi
Journal:  Protein Sci       Date:  2016-04-18       Impact factor: 6.725

9.  Assemblies of calcium/calmodulin-dependent kinase II with actin and their dynamic regulation by calmodulin in dendritic spines.

Authors:  Qian Wang; Mingchen Chen; Nicholas P Schafer; Carlos Bueno; Sarah S Song; Andy Hudmon; Peter G Wolynes; M Neal Waxham; Margaret S Cheung
Journal:  Proc Natl Acad Sci U S A       Date:  2019-08-27       Impact factor: 11.205

10.  Genesis of tramsmissible protein states via deformed templating.

Authors:  Natallia Makarava; Ilia V Baskakov
Journal:  Prion       Date:  2012-07-01       Impact factor: 3.931

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  6 in total

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Review 2.  Amyloid Oligomers: A Joint Experimental/Computational Perspective on Alzheimer's Disease, Parkinson's Disease, Type II Diabetes, and Amyotrophic Lateral Sclerosis.

Authors:  Phuong H Nguyen; Ayyalusamy Ramamoorthy; Bikash R Sahoo; Jie Zheng; Peter Faller; John E Straub; Laura Dominguez; Joan-Emma Shea; Nikolay V Dokholyan; Alfonso De Simone; Buyong Ma; Ruth Nussinov; Saeed Najafi; Son Tung Ngo; Antoine Loquet; Mara Chiricotto; Pritam Ganguly; James McCarty; Mai Suan Li; Carol Hall; Yiming Wang; Yifat Miller; Simone Melchionna; Birgit Habenstein; Stepan Timr; Jiaxing Chen; Brianna Hnath; Birgit Strodel; Rakez Kayed; Sylvain Lesné; Guanghong Wei; Fabio Sterpone; Andrew J Doig; Philippe Derreumaux
Journal:  Chem Rev       Date:  2021-02-05       Impact factor: 60.622

3.  The structural heterogeneity of α-synuclein is governed by several distinct subpopulations with interconversion times slower than milliseconds.

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Review 4.  Nanoscale programming of cellular and physiological phenotypes: inorganic meets organic programming.

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5.  Integrative structural dynamics probing of the conformational heterogeneity in synaptosomal-associated protein 25.

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6.  Dystrophin gene editing by CRISPR/Cas9 system in human skeletal muscle cell line (HSkMC).

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  6 in total

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