scholarly journals MELD-DNA: A new tool for capturing protein-DNA binding

2021 ◽  
Author(s):  
Antonio Bauza ◽  
Alberto Perez
Keyword(s):  
Structural Biology ◽  
Conformational Changes ◽  
Dna Sequences ◽  
Structure Prediction ◽  
Binding Mode ◽  
Binding Modes ◽  
Dna Interactions ◽  
Protein Dna Interactions ◽  
Multiple Binding ◽  
New Software Development

Herein we present MELD-DNA, a novel computational approach to address the problem of protein-DNA structure prediction. This method addresses well-known issues hampering current computational approaches to bridge the gap between structural and sequence knowledge, such as large conformational changes in DNA and highly charged electrostatic interaction during binding. MELD- DNA is able to: i) sample multiple binding modes, ii) identify the preferred binding mode from the ensembles, and iii) provide qualitative binding preferences between DNA sequences. We expect the results presented herein will have impact in the field of biophysics (through new software development), structural biology (by complementing DNA structural databases) and supramolecular chemistry (by bringing new insights into protein-DNA interactions).

scholarly journals Dynamic and Structural Modeling of the Specificity in Protein-DNA Interactions Guided by Binding Assay and Structure Data

2018 ◽  
Author(s):  
Cheng Tan ◽  
Shoji Takada
Keyword(s):  
Structure Data ◽  
Dna Sequences ◽  
Complex Structure ◽  
Specific Protein ◽  
Coarse Grained ◽  
Binding Modes ◽  
Binding Assays ◽  
Dna Interactions ◽  
Protein Dna Interactions ◽  
Dynamics Simulations

ABSTRACTHow transcription factors (TFs) recognize their DNA sequences is often investigated complementarily by high-throughput protein binding assays and by structural biology experiments. The former quantifies the specificity of TF binding sites for numerous DNA sequences, often represented as the position-weight-matrix (PWM). The latter provides mechanistic insights into the interactions via the protein-DNA complex structures. However, these two types of data are not readily integrated. Here, we propose and test a new modeling method that incorporates the PWM with complex structure data. Based on pre-tuned coarse-grained models for proteins and DNAs, we model the specific protein-DNA interactions, PWMcos, in terms of an orientation-dependent potential function, which enables us to perform molecular dynamics simulations at unprecedentedly large scales. We show that the PWMcos model reproduces subtle specificity in the protein-DNA recognition. During the target search in genomic sequences, TF moves on highly rugged landscapes and occasionally flips on DNA depending on the sequence. The TATA-binding protein exhibits two remarkably distinct binding modes, of which frequencies differ between TATA-containing and TATA-less promoters. The PWMcos is general and can be applied to any protein-DNA interactions given their PWMs and complex structure data are available.

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>

SURFACE PLASMON RESONANCE SPECTROSCOPY AND QUARTZ CRYSTAL MICROBALANCE STUDY OF PROTEIN-DNA INTERACTIONS IN HORMONE RECEPTOR BIOLOGY

COSMOS ◽  
2009 ◽  
Vol 05 (01) ◽  
pp. 79-95
Author(s):  
XIAODI SU
Keyword(s):  
Surface Plasmon Resonance ◽  
Surface Plasmon ◽  
Quartz Crystal Microbalance ◽  
Conformational Changes ◽  
Plasmon Resonance ◽  
Quartz Crystal ◽  
Resonance Spectroscopy ◽  
Dna Interactions ◽  
Protein Dna Interactions

Surface plasmon resonance (SPR) spectroscopy and quartz crystal microbalance (QCM) are surface sensitive analytical techniques capable of real-time monitoring of biomolecular interactions. In this article we review our past work on the use of these two techniques for studying protein–DNA interactions, exemplified with estrogen receptors (ER) and their response elements (ERE). Various assay schemes have been developed for a comprehensive characterization of ER–ERE interactions in terms of sequence specificity, binding affinity, stoichiometry, ligand effects on binding dynamics and conformational changes in the proteins and DNA. These are all important characteristics underlining the mechanism of ER-mediated gene transcription. With these studies we have made the following demonstrations to describe the advantages of these two techniques, namely (i) SPR technique is superior and more versatile than conventional (electrophoretic mobility shift assay) EMSA for studying protein-DNA interactions; (ii) QCM is an alternative tool for studying conformational changes in protein–DNA complexes and (iii) combinational SPR and QCM analysis provides additional characterization of biomolecular films, e.g. film thickness, water content, and conformation rigidity etc.

scholarly journals Differential Histone-DNA Interactions Dictate Nucleosome Recognition of the Pioneer Transcription Factor Sox

2021 ◽  
Author(s):  
Burcu Ozden ◽  
Ramachandran Boopathi ◽  
Ayse Bercin Barlas ◽  
Imtiaz N. Lone ◽  
Jan Bednar ◽  
...  
Keyword(s):  
Conformational Changes ◽  
Dna Recognition ◽  
Binding Mode ◽  
Chromatin Binding ◽  
Dna Interactions ◽  
Recognition Sequence ◽  
Cellular Processes ◽  
Nucleosomal Dna ◽  
Pioneer Transcription Factor ◽  
Dna Strand

Pioneer transcription factors (PTFs) have the remarkable ability to directly bind to chromatin for stimulating vital cellular processes. Expanding on the recent findings, we aim to unravel the universal binding mode of the famous Sox PTF. Our findings show that the base specific hydrogen bonding (base reading) and the local DNA changes (shape reading) are required for sequence-specific nucleosomal DNA recognition by Sox. Among different nucleosomal positions, base and shape reading can be satisfied at super helical location 2 (SHL2). This indicates that due to distinct histone-DNA interactions, SHL2 acts transparently to Sox binding, where SHL4 permits solely shape reading, and SHL0 (dyad) allows no reading. We also show that at SHL2, Sox binds to its recognition sequence without imposing any major conformational changes, if its consensus DNA sequence is located at the solvent-facing nucleosomal DNA strand. These data explain how Sox have evolved to perfectly adapt for chromatin binding.

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>

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>

scholarly journals The Interaction of Fluorinated Glycomimetics with DC-SIGN: Multiple Binding Modes Disentangled by the Combination of NMR Methods and MD Simulations

2020 ◽  
Vol 13 (8) ◽  
pp. 179
Author(s):  
J. Daniel Martínez ◽  
Angela S. Infantino ◽  
Pablo Valverde ◽  
Tammo Diercks ◽  
Sandra Delgado ◽  
...  
Keyword(s):  
Md Simulations ◽  
Binding Mode ◽  
Matrix Analysis ◽  
Binding Modes ◽  
Receptor Complexes ◽  
Multiple Binding ◽  
Std Nmr ◽  
Complex Glycans ◽  
Complete Relaxation Matrix Analysis ◽  
Nmr Methods

Fluorinated glycomimetics are frequently employed to study and eventually modulate protein–glycan interactions. However, complex glycans and their glycomimetics may display multiple binding epitopes that enormously complicate the access to a complete picture of the protein–ligand complexes. We herein present a new methodology based on the synergic combination of experimental 19F-based saturation transfer difference (STD) NMR data with computational protocols, applied to analyze the interaction between DC-SIGN, a key lectin involved in inflammation and infection events with the trifluorinated glycomimetic of the trimannoside core, ubiquitous in human glycoproteins. A novel 2D-STD-TOCSYreF NMR experiment was employed to obtain the experimental STD NMR intensities, while the Complete Relaxation Matrix Analysis (CORCEMA-ST) was used to predict that expected for an ensemble of geometries extracted from extensive MD simulations. Then, an in-house built computer program was devised to find the ensemble of structures that provide the best fit between the theoretical and the observed STD data. Remarkably, the experimental STD profiles obtained for the ligand/DC-SIGN complex could not be satisfactorily explained by a single binding mode, but rather with a combination of different modes coexisting in solution. Therefore, the method provides a precise view of those ligand–receptor complexes present in solution.

The DNA-Porphyrin Interactions Studied by Vibrational and Electronic Circular Dichroism Spectroscopy

2005 ◽  
Vol 70 (11) ◽  
pp. 1799-1810 ◽  
Author(s):  
Jakub Nový ◽  
Marie Urbanová ◽  
Karel Volka
Keyword(s):  
Circular Dichroism ◽  
Conformational Changes ◽  
Binding Mode ◽  
Minor Groove ◽  
Binding Modes ◽  
Base Pairs ◽  
Electronic Circular Dichroism ◽  
Axial Ligands ◽  
Phosphate Backbone ◽  
Circular Dichroïsm

The interactions of three different porphyrins, without axial ligands - 5,10,15,20-tetrakis(1-methylpyridinium-4-yl)porphyrin-Cu(II) tetrachloride (Cu(II)TMPyP), with axial ligands - 5,10,15,20-tetrakis(1-methylpyridinium-4-yl)porphyrin-Fe(III) pentachloride (Fe(III)TMPyP), and with bulky meso substituents - 5,10,15,20-tetrakis(N,N,N-trimethylanilinium-4-yl)-porphyrin tetrachloride (TMAP), with calf thymus DNA were studied by combination of vibrational circular dichroism (VCD) and electronic circular dichroism (ECD) spectroscopy, and by IR and UV-VIS absorption spectroscopy. It has been shown that Cu(II)TMPyP prefers the intercalative binding mode with DNA in the GC-rich regions and the intercalative sites are saturated at the c(DNA)/c(Cu(II)TMPyP) ratio ~3:1, where c(DNA) and c(Cu(II)TMPyP) are total molar concentrations of nucleic acid in base pairs and porphyrin, respectively. Fe(III)TMPyP does not intercalate between the GC base pairs but binds to DNA in the minor groove. At higher c(DNA)/c(TMAP) ratios, TMAP interacts with DNA in the minor groove, but at lower ratios in the major groove and by the external binding mode accompanied by self-stacking of porphyrins along the phosphate backbone. VCD spectroscopy reliably discriminates the binding modes and specifies the conformational changes of the DNA matrices. It has been also shown that VCD spectroscopy is an effective tool for the conformational studies of DNA-porphyrin complexes. New spectroscopic "markers" in VCD spectra have been found for the specific DNA-porphyrin interactions.

scholarly journals Real-Time Analysis of Specific Protein-DNA Interactions with Surface Plasmon Resonance

2012 ◽  
Vol 2012 ◽  
pp. 1-19 ◽  
Author(s):  
Markus Ritzefeld ◽  
Norbert Sewald
Keyword(s):  
Surface Plasmon Resonance ◽  
Real Time ◽  
Surface Plasmon ◽  
Dna Sequences ◽  
Plasmon Resonance ◽  
Interaction Analysis ◽  
Physical Phenomenon ◽  
Dna Interactions ◽  
Protein Dna Interactions ◽  
Rna Interaction

Several proteins, like transcription factors, bind to certain DNA sequences, thereby regulating biochemical pathways that determine the fate of the corresponding cell. Due to these key positions, it is indispensable to analyze protein-DNA interactions and to identify their mode of action. Surface plasmon resonance is a label-free method that facilitates the elucidation of real-time kinetics of biomolecular interactions. In this article, we focus on this biosensor-based method and provide a detailed guide how SPR can be utilized to study binding of proteins to oligonucleotides. After a description of the physical phenomenon and the instrumental realization including fiber-optic-based SPR and SPR imaging, we will continue with a survey of immobilization methods. Subsequently, we will focus on the optimization of the experiment, expose pitfalls, and introduce how data should be analyzed and published. Finally, we summarize several interesting publications of the last decades dealing with protein-DNA and RNA interaction analysis by SPR.

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