Well-Balanced Force Field <i>ff</i>03<i>CMAP</i> for Folded and Disordered Proteins

Zhang, Yangpeng; Líu, Hao; Yang, Sheng; Luo, Ray; Chen, Haifeng

doi:10.1021/acs.jctc.9b00623

Cited by 53 publications

(67 citation statements)

References 85 publications

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“…Force fields developed for folded proteins in MD simulations tend to predict more compact structures of IDPs that contradict experimental measurement 476 . To address these challenges, scientists modified force fields to improve the simulations of IDPs [477][478][479][480][481] . Robustelli et al 465 performed MD simulations of 21 systems that contain folded and disordered proteins using six force fields and a 2.5-fs time step.…”

Section: A-synuclein In Solutionmentioning

confidence: 99%

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

et al. 2021

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Protein misfolding and aggregation is observed in many amyloidogenic diseases affecting either the central nervous system or a variety of peripheral tissues. Structural and dynamic characterization of all species along the pathways from monomers to fibrils is challenging by experimental and computational means because they involve intrinsically disordered proteins in most diseases. Yet understanding how amyloid species become toxic is the challenge in developing a treatment for these diseases. Here we review what computer, in vitro, in vivo and pharmacological experiments tell us about the accumulation and deposition of the oligomers of the (Aβ, tau), α-synuclein, IAPP and superoxide dismutase 1 proteins, which have been the mainstream concept underlying Alzheimer's disease (AD), Parkinson's disease (PD), type II diabetes (T2D) and amyotrophic lateral sclerosis (ALS) research, respectively for over many years.While SOD1 is a globular protein with a well-defined 3D structure, the Aβ, tau and α-synuclein proteins belong to the class of intrinsically disordered proteins (IDPs). IDPs are also known to play a critical role in many cellular functions such as signal transduction, cell growth, binding with DNA and RNA, and transcription, and are implicated in the development of cardiovascular problems and cancers 29 . The IDPs involved in neurodegenerative diseases have a few aggregation-prone regions and overall all IDPs have a low mean hydrophobicity and a high mean net charge 30 .IDPs are structurally flexible and lack stable secondary structures in aqueous solution. When isolated, they behave as polymers in a good solvent and their radii of gyration are well described by the Flory scaling law. 31 The insolubility and high self-assembly propensity of IDPs implicated in degenerative diseases have prevented high-resolution structural determination by solution nuclear magnetic resolution (NMR) and X-ray diffraction experiments. Local information at all aggregation steps can be, however, obtained by chemical shifts, residual coupling constants, and J-couplings from NMR, exchange hydrogen/deuterium (H/D) NMR, Raman spectroscopy; and secondary structure from fast Fourier infrared spectroscopy (FTIR) or circular dichroism (CD). Long-range tertiary contacts can be deduced from paramagnetic relaxation enhancement (PRE) NMR spectroscopy and single molecule Förster resonance energy transfer (sm-FRET), and short-range distance contacts can be extracted by cross linked residues determined by mass spectrometry (MS). Low-resolution 3D information of monomers and oligomers can be obtained by ion-mobility mass-spectrometry data (IM/MS) providing cross-collision sections, dynamic light scattering (DLS), pulse field gradient NMR spectroscopy and fluorescence correlation spectroscopy (FCS) providing hydrodynamics radius, small-angle X-ray scattering (SAXS) and small-angle neutron scattering (SANS), atomic force microscopy (AFM) and transmission electron microscopy (TEM) providing height features of the aggregates, as reported by some o...

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Section: A-synuclein In Solutionmentioning

confidence: 99%

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

et al. 2021

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“…We should mention here also that the current literature includes additional force field parameters for IDPs that have not been tested with different simulation techniques and simulation protocols on Aβ. These force field parameters that are not included in this study are the ff99IDPs, ff14IDPSFF, ff03CMAP, ESFF1, and RSFF1 (Jiang et al., 2014; Song et al., 2020a, 2020b; Zhang et al., 2019a, 2019b). This study focuses on the comparison of REMD simulations with extensive MD simulations using widely utilized force field parameters.…”

Section: Resultsmentioning

confidence: 99%

Secondary structure dependence of amyloid‐β(1–40) on simulation techniques and force field parameters

et al. 2021

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Our recent studies revealed that none of the selected widely used force field parameters and molecular dynamics simulation techniques yield structural properties for the intrinsically disordered α‐synuclein that are in agreement with various experiments via testing different force field parameters. Here, we extend our studies on the secondary structure properties of the disordered amyloid‐β(1–40) peptide in aqueous solution. For these purposes, we conducted extensive replica exchange molecular dynamics simulations and obtained extensive molecular dynamics simulation trajectories from David E. Shaw group. Specifically, these molecular dynamics simulations were conducted using various force field parameters and obtained results are compared to our replica exchange molecular dynamics simulations and experiments. In this study, we calculated the secondary structure abundances and radius of gyration values for amyloid‐β(1–40) that were simulated using varying force field parameter sets and different simulation techniques. In addition, the intrinsic disorder propensity, as well as sequence‐based secondary structure predisposition of amyloid‐β(1–40) and compared the findings with the results obtained from molecular simulations using various force field parameters and different simulation techniques. Our studies clearly show that the epitope region identification of amyloid‐β(1–40) depends on the chosen simulation technique and chosen force field parameters. Based on comparison with experiments, we find that best computational results in agreement with experiments are obtained using the a99sb*‐ildn, charmm36m, and a99sb‐disp parameters for the amyloid‐β(1–40) peptide in molecular dynamics simulations without parallel tempering or via replica exchange molecular dynamics simulations.

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“…The root‐mean‐square deviations (RMSDs), root‐mean‐square fluctuation (RMSF), the distance between two residues, and hydrophobic interaction between substrate and ACR were calculated with the cpptraj module in AmberTools 18 and in‐house software (Chen, 2008, 2009; Chen et al., 2010; Li et al., 2019; Liu et al., 2018, 2019; Qin et al., 2009, 2011; Rahman et al., 2020; Song et al., 2020; Song, Luo, et al., 2017; Song, Wang, et al., 2017; Wang et al., 2013, 2014; Yang et al., 2019; Ye et al., 2015; Yu et al., 2013; Zhang et al., 2019).…”

Section: Methodsmentioning

confidence: 99%

Catalytic mechanism of butane anaerobic oxidation for alkyl‐coenzyme M reductase

2021

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Methane is among the most potent of the greenhouse gases, which plays a key role in global climate change (Feldman et al., 2018;Kasting & Siefert, 2002). Most methane is naturally produced by methanogenic archaea, such as in marine sediments, cold spring, wetland and lake (Reeburgh, 2007).Most methane produced naturally can be offset by uptake into natural sinks. However, methane produced by human activities can cause the concentration of methane to increase more quickly, and that cannot be offset by sinks. Since 2007, the concentration of methane in Earth's atmosphere has increased by 6.8-10 parts per billion (ppb) per year. By 2020, the concentration of methane in the atmosphere had reached

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Well-Balanced Force Field ff03CMAP for Folded and Disordered Proteins

Cited by 53 publications

References 85 publications

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

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

Secondary structure dependence of amyloid‐β(1–40) on simulation techniques and force field parameters

Catalytic mechanism of butane anaerobic oxidation for alkyl‐coenzyme M reductase

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