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

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.

scholarly journals Binding of regulatory proteins to nucleosomes is modulated by dynamic histone tails

2020 ◽  
Author(s):  
Yunhui Peng ◽  
Shuxiang Li ◽  
Alexey Onufriev ◽  
David Landsman ◽  
Anna R. Panchenko
Keyword(s):  
Solvent Accessibility ◽  
Binding Modes ◽  
Dna Interactions ◽  
Histone Tail ◽  
Histone Tails ◽  
Post Translational Modifications ◽  
Conformational Ensembles ◽  
Nucleosomal Dna ◽  
Dynamics Simulations ◽  
Nucleosome Binding

AbstractDespite histone tails’ critical roles in epigenetic regulation, little is known about mechanisms of how histone tails modulate the nucleosomal DNA solvent accessibility and recognition of nucleosomes by other macromolecules. Here we generate extensive atomic level conformational ensembles of histone tails in the context of the full human nucleosome, totaling 26 microseconds of molecular dynamics simulations. We explore the histone tail binding with the nucleosomal and linker DNA and observe rapid conformational transitions between bound and unbound states allowing us to estimate kinetic and thermodynamic properties of the histone tail-DNA interactions. Different histone types exhibit distinct, although conformationally heterogeneous, binding modes and each histone type occludes specific DNA regions from the solvent. Using a comprehensive set of experimental data on nucleosome structural complexes, we find that majority of the studied nucleosome-binding proteins and histone tails target mutually exclusive regions on nucleosomal or linker DNA around the super-helical locations ±1, ±2, and ±7. This finding is explained within the generalized competitive binding and tail displacement models of partners recruitment to nucleosomes. Finally, we demonstrate the crosstalk between different histone post-translational modifications, where charge-altering modifications and mutations typically suppress tail-DNA interactions and enhance histone tail dynamics.

scholarly journals Machine learning predicts nucleosome binding modes of transcription factors

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
K. C. Kishan ◽  
Sridevi K. Subramanya ◽  
Rui Li ◽  
Feng Cui
Keyword(s):  
Machine Learning ◽  
Transcription Factors ◽  
Nucleosome Occupancy ◽  
Computational Prediction ◽  
Binding Modes ◽  
Validation Procedure ◽  
Binding Groove ◽  
Nucleosome Binding ◽  
Gain Access ◽  
Better Than

Abstract Background Most transcription factors (TFs) compete with nucleosomes to gain access to their cognate binding sites. Recent studies have identified several TF-nucleosome interaction modes including end binding (EB), oriented binding, periodic binding, dyad binding, groove binding, and gyre spanning. However, there are substantial experimental challenges in measuring nucleosome binding modes for thousands of TFs in different species. Results We present a computational prediction of the binding modes based on TF protein sequences. With a nested cross-validation procedure, our model outperforms several fine-tuned off-the-shelf machine learning (ML) methods in the multi-label classification task. Our binary classifier for the EB mode performs better than these ML methods with the area under precision-recall curve achieving 75%. The end preference of most TFs is consistent with low nucleosome occupancy around their binding site in GM12878 cells. The nucleosome occupancy data is used as an alternative dataset to confirm the superiority of our EB classifier. Conclusions We develop the first ML-based approach for efficient and comprehensive analysis of nucleosome binding modes of TFs.

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.

scholarly journals Nucleosome binding and histone methyltransferase activity of Drosophila PRC2

EMBO Reports ◽  
2005 ◽  
Vol 6 (4) ◽  
pp. 348-353 ◽  
Author(s):  
Maxim Nekrasov ◽  
Brigitte Wild ◽  
Jürg Müller
Keyword(s):  
Histone Methyltransferase ◽  
Methyltransferase Activity ◽  
Nucleosome Binding

On the Adsorption of Aspartate Derivatives to Calcite Surfaces in Aqueous Environment

2020 ◽  
Author(s):  
Robert Stepic ◽  
Lara Jurković ◽  
Ksenia Klementyeva ◽  
Marko Ukrainczyk ◽  
Matija Gredičak ◽  
...  
Keyword(s):  
Active Sites ◽  
Realistic Model ◽  
Binding Energies ◽  
Inhibition Mechanism ◽  
Aqueous Environment ◽  
Binding Modes ◽  
Carboxylate Groups ◽  
Dissolved Ions ◽  
Living Organisms ◽  
Dynamics Simulations

In many living organisms, biomolecules interact favorably with various surfaces of calcium carbonate. In this work, we have considered the interactions of aspartate (Asp) derivatives, as models of complex biomolecules, with calcite. Using kinetic growth experiments, we have investigated the inhibition of calcite growth by Asp, Asp2 and Asp3.This entailed the determination of a step-pinning growth regime as well as the evaluation of the adsorption constants and binding free energies for the three species to calcite crystals. These latter values are compared to free energy profiles obtained from fully atomistic molecular dynamics simulations. When using a flat (104) calcite surface in the models, the measured trend of binding energies is poorly reproduced. However, a more realistic model comprised of a surface with an island containing edges and corners, yields binding energies that compare very well with experiments. Surprisingly, we find that most binding modes involve the positively charged, ammonium group. Moreover, while attachment of the negatively charged carboxylate groups is also frequently observed, it is always balanced by the aqueous solvation of an equal or greater number of carboxylates. These effects are observed on all calcite features including edges and corners, the latter being associated with dominant affinities to Asp derivatives. As these features are also precisely the active sites for crystal growth, the experimental and theoretical results point strongly to a growth inhibition mechanism whereby these sites become blocked, preventing further attachment of dissolved ions and halting further growth.

Reversibly Sampling Conformations and Binding Modes Using Molecular Darting

2020 ◽  
Author(s):  
Samuel C. Gill ◽  
David Mobley
Keyword(s):  
Monte Carlo ◽  
Ligand Binding ◽  
Binding Sites ◽  
Degrees Of Freedom ◽  
Dynamics Simulation ◽  
Hiv Integrase ◽  
Binding Modes ◽  
System A ◽  
Multiple Binding ◽  
Internal Degrees Of Freedom

<div>Sampling multiple binding modes of a ligand in a single molecular dynamics simulation is difficult. A given ligand may have many internal degrees of freedom, along with many different ways it might orient itself a binding site or across several binding sites, all of which might be separated by large energy barriers. We have developed a novel Monte Carlo move called Molecular Darting (MolDarting) to reversibly sample between predefined binding modes of a ligand. Here, we couple this with nonequilibrium candidate Monte Carlo (NCMC) to improve acceptance of moves.</div><div>We apply this technique to a simple dipeptide system, a ligand binding to T4 Lysozyme L99A, and ligand binding to HIV integrase in order to test this new method. We observe significant increases in acceptance compared to uniformly sampling the internal, and rotational/translational degrees of freedom in these systems.</div>

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>

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