A predictive coarse-grained model for position-specific effects of post-translational modifications

Perdikari, Theodora Myrto; Jovic, Nina; Dignon, Gregory L.; Kim, Young C.; Fawzi, Nicolas L.; Mittal, Jeetain

doi:10.1016/j.bpj.2021.01.034

Cited by 63 publications

(72 citation statements)

References 86 publications

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“…Although straightforward, it is time and resource consuming to examine all the hydropathy scales for building an IDP CG model. Instead, in this study, we focus only on two hydropathy scales, namely the KR scale, 36 which was used in the previous models, 17,30,37 and the scale proposed by Urry et al 47 (hereafter denoted as the Urry scale). We also compared the ability of these hydropathy scales to estimate single‐chain IDP properties with the 210 parameters MJ statistical contact potential used in the KH model we used previously to capture IDP phase behavior.…”

Section: Resultsmentioning

confidence: 99%

“…The CG simulations can be conducted with off 21,30–33 or on lattice 19 models with varying resolutions 33,34 and the interactions between the CG amino acids can be informed by physics‐ or knowledge‐based potentials 35 . We have previously proposed a one bead per amino acid CG model 30 using the Kapcha‐Rossky (KR) hydropathy scale 36 referred to as the HPS‐KR model hereafter which has been successfully used in numerous previous studies of IDP LLPS 8,9,17,26–28,37,38 . Specifically, the transferable HPS‐KR model has been used to study the phase separation of several IDP sequences like the intrinsically disordered region (IDR) of DEAD‐box helicase LAF‐1 protein also referred to as LAF‐1 RGG, 9 the low complexity (LC) domain of the Fused in Sarcoma (FUS) protein 8,28,38–40 and disordered C‐terminal domain (CTD) of the TAR DNA binding protein (TDP‐43) 26 .…”

Section: Introductionmentioning

confidence: 99%

“…Specifically, the transferable HPS‐KR model has been used to study the phase separation of several IDP sequences like the intrinsically disordered region (IDR) of DEAD‐box helicase LAF‐1 protein also referred to as LAF‐1 RGG, 9 the low complexity (LC) domain of the Fused in Sarcoma (FUS) protein 8,28,38–40 and disordered C‐terminal domain (CTD) of the TAR DNA binding protein (TDP‐43) 26 . We also recently extended the HPS‐KR model to capture thermoresponsive LLPS behavior of IDPs, 31 the role of post‐translational modifications in perturbing LLPS, 37 and the multicomponent LLPS of IDP and polynucleotide mixtures 17 ; the simulations results were in very good agreement with the experimental observations 39,41,42 …”

Section: Introductionmentioning

confidence: 99%

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Improved coarse‐grained model for studying sequence dependent phase separation of disordered proteins

et al. 2021

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We present improvements to the hydropathy scale (HPS) coarse‐grained (CG) model for simulating sequence‐specific behavior of intrinsically disordered proteins (IDPs), including their liquid–liquid phase separation (LLPS). The previous model based on an atomistic hydropathy scale by Kapcha and Rossky (KR scale) is not able to capture some well‐known LLPS trends such as reduced phase separation propensity upon mutations (R‐to‐K and Y‐to‐F). Here, we propose to use the Urry hydropathy scale instead, which was derived from the inverse temperature transitions in a model polypeptide with guest residues X. We introduce two free parameters to shift (Δ) and scale (µ) the overall interaction strengths for the new model (HPS‐Urry) and use the experimental radius of gyration for a diverse group of IDPs to find their optimal values. Interestingly, many possible (Δ, µ) combinations can be used for typical IDPs, but the phase behavior of a low‐complexity (LC) sequence FUS is only well described by one of these models, which highlights the need for a careful validation strategy based on multiple proteins. The CG HPS‐Urry model should enable accurate simulations of protein LLPS and provide a microscopically detailed view of molecular interactions.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Improved coarse‐grained model for studying sequence dependent phase separation of disordered proteins

et al. 2021

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“…Despite nearly no effect on monomeric local structure and motions of FUS LC, here we find that there are slight differences in the biophysical properties of unacetylated and Nt‐Ac FUS LC. Charge changing PTMs regulate phase behavior of FUS and other proteins 8,18,19 . Previous studies found that phosphomimetic substitutions and in vitro phosphorylation, which introduce charged residues across FUS LC, decreased aggregation and phase separation compared to unmodified FUS 8 .…”

Section: Discussionmentioning

confidence: 99%

N‐terminal acetylation modestly enhances phase separation and reduces aggregation of the low‐complexity domain of RNA‐binding protein fused in sarcoma

et al. 2021

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The RNA‐binding protein fused in sarcoma (FUS) assembles via liquid–liquid phase separation (LLPS) into functional RNA granules and aggregates in amyotrophic lateral sclerosis associated neuronal inclusions. Several studies have demonstrated that posttranslational modification (PTM) can significantly alter FUS phase separation and aggregation, particularly charge‐altering phosphorylation of the nearly uncharged N‐terminal low complexity domain of FUS (FUS LC). However, the occurrence and impact of N‐terminal acetylation on FUS phase separation remains unexplored, even though N‐terminal acetylation is the most common PTM in mammals and changes the charge at the N‐terminus. First, we find that FUS is predominantly acetylated in two human cell types and stress conditions. Next, we show that recombinant FUS LC can be acetylated when co‐expressed with the NatA complex in Escherichia coli. Using NMR spectroscopy, we find that N‐terminal acetylated FUS LC (FUS LC Nt‐Ac) does not notably alter monomeric FUS LC structure or motions. Despite no difference in structure, Nt‐Ac‐FUS LC phase separates more avidly than unmodified FUS LC. More importantly, N‐terminal acetylation of FUS LC reduces aggregation. Our findings highlight the importance of N‐terminal acetylation of proteins that undergo physiological LLPS and pathological aggregation.

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“…For polymeric materials, beads are either utilized to represent monomers or defined on consideration of persistent length [ 78 ], and dissipative particle dynamics (DPD) were proposed to deal with complexities arise from much larger particles [ 79 ]. For biomolecular systems, a wide variety of coarse grained models have been developed [ 20 , 21 , 23 , 24 , 80 , 81 ]. Another important subject of CG methodology development is materials science [ 82 , 83 ].…”

Section: DC and “Caching” In Traditional Molecular Modelingmentioning

confidence: 99%

“Dividing and Conquering” and “Caching” in Molecular Modeling

Cao

Tian

2021

IJMS

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Molecular modeling is widely utilized in subjects including but not limited to physics, chemistry, biology, materials science and engineering. Impressive progress has been made in development of theories, algorithms and software packages. To divide and conquer, and to cache intermediate results have been long standing principles in development of algorithms. Not surprisingly, most important methodological advancements in more than half century of molecular modeling are various implementations of these two fundamental principles. In the mainstream classical computational molecular science, tremendous efforts have been invested on two lines of algorithm development. The first is coarse graining, which is to represent multiple basic particles in higher resolution modeling as a single larger and softer particle in lower resolution counterpart, with resulting force fields of partial transferability at the expense of some information loss. The second is enhanced sampling, which realizes “dividing and conquering” and/or “caching” in configurational space with focus either on reaction coordinates and collective variables as in metadynamics and related algorithms, or on the transition matrix and state discretization as in Markov state models. For this line of algorithms, spatial resolution is maintained but results are not transferable. Deep learning has been utilized to realize more efficient and accurate ways of “dividing and conquering” and “caching” along these two lines of algorithmic research. We proposed and demonstrated the local free energy landscape approach, a new framework for classical computational molecular science. This framework is based on a third class of algorithm that facilitates molecular modeling through partially transferable in resolution “caching” of distributions for local clusters of molecular degrees of freedom. Differences, connections and potential interactions among these three algorithmic directions are discussed, with the hope to stimulate development of more elegant, efficient and reliable formulations and algorithms for “dividing and conquering” and “caching” in complex molecular systems.

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A predictive coarse-grained model for position-specific effects of post-translational modifications

Cited by 63 publications

References 86 publications

Improved coarse‐grained model for studying sequence dependent phase separation of disordered proteins

Improved coarse‐grained model for studying sequence dependent phase separation of disordered proteins

N‐terminal acetylation modestly enhances phase separation and reduces aggregation of the low‐complexity domain of RNA‐binding protein fused in sarcoma

“Dividing and Conquering” and “Caching” in Molecular Modeling

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