scholarly journals MLL1 Methyltransferase Activity is Regulated by Distinct Nucleosome Binding Modes

2021 ◽  
Author(s):  
Alex Ayoub ◽  
Sang Ho Park ◽  
Young-tae Lee ◽  
Uhn-Soo Cho ◽  
Yali Dou
Keyword(s):  
Binding Mode ◽  
Rotational Dynamics ◽  
Binding Modes ◽  
Set Domain ◽  
Nucleosome Core Particle ◽  
H3k4 Methylation ◽  
Methyltransferase Activity ◽  
Nucleosome Core ◽  
Specific Regulation ◽  
Nucleosome Binding

Here we solve the single particle cryoEM structure for the MLL1 complex with nucleosome core particle (NCP) carrying histone H3 lysine 4 to methionine mutation. The MLL1 complex displays significant rotational dynamics on the NCP, a feature distinct from the yeast SET1 complex. We identified two major binding modes of the MLL1 complex on the NCP. Both binding modes anchor on the NCP through ASH2L, but they differ drastically with regard to where the MLL1 SET domain and RbBP5 bind. We show that one of the binding modes is catalytically inactive since disrupting interactions unique to this binding mode does not affect overall MLL1 activity in an NCP-specific manner. Interestingly, the inactive binding mode is in a configuration similar to that of the ySET1-NCP complex, which is intrinsically inactive on an unmodified NCP. The high rotational dynamics of the MLL1 complex as well as distinction between MLL and yeast SET1 complexes may reflect the necessity for loci-specific regulation of H3K4 methylation states in higher eukaryotes.

Regulation of MLL1 Methyltransferase Activity in Two Distinct Nucleosome Binding Modes

Biochemistry ◽  
2021 ◽  
Author(s):  
Alex Ayoub ◽  
Sang Ho Park ◽  
Young-Tae Lee ◽  
Uhn-Soo Cho ◽  
Yali Dou
Keyword(s):  
Binding Modes ◽  
Methyltransferase Activity ◽  
Nucleosome Binding

Binding of ethidium to the nucleosome core particle. 2. Internal and external binding modes

Biochemistry ◽  
1991 ◽  
Vol 30 (23) ◽  
pp. 5644-5652 ◽  
Author(s):  
Cynthia T. McMurray ◽  
Enoch W. Small ◽  
K. E. Van Holde
Keyword(s):  
Binding Modes ◽  
Core Particle ◽  
Nucleosome Core Particle ◽  
Nucleosome Core

scholarly journals Mesoscale Modeling of a Nucleosome-Binding Antibody (PL2-6): Mono- vs. Bivalent Chromatin Complexes

2019 ◽  
Author(s):  
Christopher G. Myers ◽  
Donald E. Olins ◽  
Ada L. Olins ◽  
Tamar Schlick
Keyword(s):  
Chromatin Structure ◽  
Chromatin Fiber ◽  
Coarse Grained ◽  
Binding Modes ◽  
Linker Histones ◽  
Nucleosome Core ◽  
Chromatin Interactions ◽  
Binding Antibody ◽  
Differential Binding ◽  
Nucleosome Binding

ABSTRACTVisualizing chromatin adjacent to the nuclear envelope (denoted “epichromatin”) by in vitro immunostaining with a bivalent nucleosome-binding antibody (termed monoclonal antibody PL2-6) has suggested a distinct and conserved chromatin structure. Moreover, different staining patterns for chromatin complexed with the monovalent “Fab” fragment of PL2-6, compared to the bivalent form, point to distinct binding interactions. To help interpret antibody/chromatin interactions and these differential binding modes, we incorporate coarse-grained PL2-6 antibody modeling into our mesoscale chromatin model and analyze interactions and fiber structures for the antibody/chromatin complexes in open and condensed chromatin, with and without linker histone H1 (LH). Despite minimal and transient interactions at physiological salt, we capture differential binding for monomer and dimer antibody forms to open fibers, with much more intense interactions in the bivalent antibody/chromatin complex. For these open “zigzag” fiber morphologies, differences result from antibody competition for peptide tail contacts with internal chromatin fiber components (nucleosome core and linker DNA). Antibody competition results in dramatic conformational and energetic differences among monovalent, bivalent, and free chromatin systems in the parental linker DNA / tail interactions. These differences in binding modes and changes in internal fiber structure, driven by conformational entropy gains, help interpret the differential staining patterns for the monovalent versus bivalent antibody/chromatin complexes. More generally, such dynamic interactions which depend on the complex internal structure and self-interactions of the chromatin fiber have broader implications to other systems that bind to chromatin, such as linker histones and remodeling proteins.STATEMENT OF SIGNIFICANCEUsing mesoscale modeling, we help interpret differential binding modes for antibody/chromatin interactions to elucidate the structural details of “epichromatin” (chromatin adjacent to the nuclear envelope), which had been visualized to produce different staining patterns for monovalent and bivalent forms of the PL2-6 antibody. To our knowledge, this is the first application of such a coarse-grained computational antibody model to probe chromatin structure and mechanisms of antibody/chromatin binding. Our work emphasizes how antibody units compete with native internal chromatin fiber units (histone tails, nucleosome core, and linker DNA) for fiber-stabilizing interactions and thereby drive differential antibody binding for open zigzag chromatin fibers. Such competition, which dynamically alters internal chromatin structure upon binding, could be relevant to other chromatin binding mechanisms such as those involving linker histones or chromatin remodeling proteins.

Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes Using Nonequilibrium Candidate Monte Carlo

2017 ◽  
Author(s):  
Samuel Gill ◽  
Nathan M. Lim ◽  
Patrick Grinaway ◽  
Ariën S. Rustenburg ◽  
Josh Fass ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Ligand Binding ◽  
Binding Mode ◽  
Free Energy Calculations ◽  
Dynamics Simulation ◽  
Binding Modes ◽  
Enhanced Sampling ◽  
Recent Success ◽  
Multiple Binding ◽  
Proper Sampling

<div>Accurately predicting protein-ligand binding is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid fragments. That is, we focus on computing the dominant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a receptor, and the populations of the multiple binding modes which may be relevant. This problem is important in its own right, but is even more timely given the recent success of alchemical free energy calculations. Alchemical calculations are increasingly used to predict binding free energies of ligands to receptors. However, the accuracy of these calculations is dependent on proper sampling of the relevant ligand binding modes. Unfortunately, ligand binding modes may often be uncertain, hard to predict, and/or slow to interconvert on simulation timescales, so proper sampling with current techniques can require prohibitively long simulations. We need new methods which dramatically improve sampling of ligand binding modes. Here, we develop and apply a nonequilibrium candidate Monte Carlo (NCMC) method to improve sampling of ligand binding modes.</div><div><br></div><div>In this technique the ligand is rotated and subsequently allowed to relax in its new position through alchemical perturbation before accepting or rejecting the rotation and relaxation as a nonequilibrium Monte Carlo move. When applied to a T4 lysozyme model binding system, this NCMC method shows over two orders of magnitude improvement in binding mode sampling efficiency compared to a brute force molecular dynamics simulation. This is a first step towards applying this methodology to pharmaceutically relevant binding of fragments and, eventually, drug-like molecules. We are making this approach available via our new Binding Modes of Ligands using Enhanced Sampling (BLUES) package which is freely available on GitHub.</div>

Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes Using Nonequilibrium Candidate Monte Carlo

2018 ◽  
Author(s):  
Samuel Gill ◽  
Nathan M. Lim ◽  
Patrick Grinaway ◽  
Ariën S. Rustenburg ◽  
Josh Fass ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Ligand Binding ◽  
Binding Mode ◽  
Free Energy Calculations ◽  
Dynamics Simulation ◽  
Binding Modes ◽  
Enhanced Sampling ◽  
Recent Success ◽  
Multiple Binding ◽  
Proper Sampling

<div>Accurately predicting protein-ligand binding is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid fragments. That is, we focus on computing the dominant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a receptor, and the populations of the multiple binding modes which may be relevant. This problem is important in its own right, but is even more timely given the recent success of alchemical free energy calculations. Alchemical calculations are increasingly used to predict binding free energies of ligands to receptors. However, the accuracy of these calculations is dependent on proper sampling of the relevant ligand binding modes. Unfortunately, ligand binding modes may often be uncertain, hard to predict, and/or slow to interconvert on simulation timescales, so proper sampling with current techniques can require prohibitively long simulations. We need new methods which dramatically improve sampling of ligand binding modes. Here, we develop and apply a nonequilibrium candidate Monte Carlo (NCMC) method to improve sampling of ligand binding modes.</div><div><br></div><div>In this technique the ligand is rotated and subsequently allowed to relax in its new position through alchemical perturbation before accepting or rejecting the rotation and relaxation as a nonequilibrium Monte Carlo move. When applied to a T4 lysozyme model binding system, this NCMC method shows over two orders of magnitude improvement in binding mode sampling efficiency compared to a brute force molecular dynamics simulation. This is a first step towards applying this methodology to pharmaceutically relevant binding of fragments and, eventually, drug-like molecules. We are making this approach available via our new Binding Modes of Ligands using Enhanced Sampling (BLUES) package which is freely available on GitHub.</div>

scholarly journals Computational Investigations on the Binding Mode of Ligands for the Cannabinoid-Activated G Protein-Coupled Receptor GPR18

Biomolecules ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 686 ◽  
Author(s):  
Alexander Neumann ◽  
Viktor Engel ◽  
Andhika B. Mahardhika ◽  
Clara T. Schoeder ◽  
Vigneshwaran Namasivayam ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
G Protein ◽  
Phenyl Ring ◽  
Binding Mode ◽  
Dynamics Simulation ◽  
Simulation Studies ◽  
Binding Modes ◽  
G Protein Coupled Receptor ◽  
G Protein Coupled

GPR18 is an orphan G protein-coupled receptor (GPCR) expressed in cells of the immune system. It is activated by the cannabinoid receptor (CB) agonist ∆9-tetrahydrocannabinol (THC). Several further lipids have been proposed to act as GPR18 agonists, but these results still require unambiguous confirmation. In the present study, we constructed a homology model of the human GPR18 based on an ensemble of three GPCR crystal structures to investigate the binding modes of the agonist THC and the recently reported antagonists which feature an imidazothiazinone core to which a (substituted) phenyl ring is connected via a lipophilic linker. Docking and molecular dynamics simulation studies were performed. As a result, a hydrophobic binding pocket is predicted to accommodate the imidazothiazinone core, while the terminal phenyl ring projects towards an aromatic pocket. Hydrophobic interaction of Cys251 with substituents on the phenyl ring could explain the high potency of the most potent derivatives. Molecular dynamics simulation studies suggest that the binding of imidazothiazinone antagonists stabilizes transmembrane regions TM1, TM6 and TM7 of the receptor through a salt bridge between Asp118 and Lys133. The agonist THC is presumed to bind differently to GPR18 than to the distantly related CB receptors. This study provides insights into the binding mode of GPR18 agonists and antagonists which will facilitate future drug design for this promising potential drug target.

scholarly journals Spanning the gap: unraveling RSC dynamics in vivo

2021 ◽  
Author(s):  
Heinz Neumann ◽  
Bryan J. Wilkins
Keyword(s):  
Cell Cycle ◽  
Posttranslational Modifications ◽  
Transcriptional Activation ◽  
Binding Mode ◽  
Binding Modes ◽  
Binding Domains ◽  
Binding Interface ◽  
The Many ◽  
And Function

AbstractMultiple reports over the past 2 years have provided the first complete structural analyses for the essential yeast chromatin remodeler, RSC, providing elaborate molecular details for its engagement with the nucleosome. However, there still remain gaps in resolution, particularly within the many RSC subunits that harbor histone binding domains.Solving contacts at these interfaces is crucial because they are regulated by posttranslational modifications that control remodeler binding modes and function. Modifications are dynamic in nature often corresponding to transcriptional activation states and cell cycle stage, highlighting not only a need for enriched spatial resolution but also temporal understanding of remodeler engagement with the nucleosome. Our recent work sheds light on some of those gaps by exploring the binding interface between the RSC catalytic motor protein, Sth1, and the nucleosome, in the living nucleus. Using genetically encoded photo-activatable amino acids incorporated into histones of living yeast we are able to monitor the nucleosomal binding of RSC, emphasizing the regulatory roles of histone modifications in a spatiotemporal manner. We observe that RSC prefers to bind H2B SUMOylated nucleosomes in vivo and interacts with neighboring nucleosomes via H3K14ac. Additionally, we establish that RSC is constitutively bound to the nucleosome and is not ejected during mitotic chromatin compaction but alters its binding mode as it progresses through the cell cycle. Our data offer a renewed perspective on RSC mechanics under true physiological conditions.

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