Investigations into the DNA-binding mode of doxorubicinone

2019 ◽  
Vol 17 (7) ◽  
pp. 1992-1998 ◽  
Author(s):  
Samuel Steucek Tartakoff ◽  
Jennifer M. Finan ◽  
Ellis J. Curtis ◽  
Haley M. Anchukaitis ◽  
Danielle J. Couture ◽  
...  

Spectroscopic and calorimetric study of DNA-binding by doxorubicin and doxorubicinone found different binding modes for the two molecules, despite their structural homology.

2016 ◽  
Vol 473 (19) ◽  
pp. 3321-3339 ◽  
Author(s):  
Kazuhiko Yamasaki ◽  
Tomoko Yamasaki

Transcription factor SATB1 (special AT-rich sequence binding protein 1) contains multiple DNA-binding domains (DBDs), i.e. two CUT-domain repeats (CUTr1 and CUTr2 from the N-terminus) and a homeodomain, and binds to the matrix attachment region (MAR) of DNA. Although CUTr1 and the homeodomain, but not CUTr2, are known to contribute to DNA binding, different research groups have not reached a consensus on which DBD is responsible for recognition of the target sequence in MAR, 5′-TAATA-3′. Here, we used isothermal titration calorimetry to demonstrate that CUTr1 has binding specificity to this motif, whereas the homeodomain shows affinity for a variety of DNAs without specificity. In line with nonspecific DNA-binding properties of the homeodomain, a mutation of the invariant Asn at position 51 of the homeodomain (typically in contact with the A base in a sequence-specific binding mode) did not affect the binding affinity significantly. The NMR analyses and computational modeling of the homeodomain, however, revealed the tertiary structure and DNA-binding mode that are typical of homeodomains capable of sequence-specific binding. We believe that the lack of highly conserved basic residues in the helix relevant to the base recognition loosens its fitting into the DNA groove and impairs the specific binding. The two DBDs, when fused in tandem, showed strong binding to DNA containing the 5′-TAATA-3′ motif with an affinity constant >108 M−1 and retained nonspecific binding activity. The combination of the sequence-specific and nonspecific DNA-binding modes of SATB1 should be advantageous in a search for target loci during transcriptional regulation.


1998 ◽  
Vol 45 (1) ◽  
pp. 221-231 ◽  
Author(s):  
J Brzeski ◽  
T Grycuk ◽  
A W Lipkowski ◽  
W Rudnicki ◽  
B Lesyng ◽  
...  

The binding properties of the SPXK- and APXK-type peptides to the AT-rich DNA fragments of different length were studied by measuring the competition of peptides with Hoechst 33258 dye for DNA binding and by the gel shift assay analysis. In parallel to the experimental studies, molecular modeling techniques were used to analyze possible binding modes of the SPXZ and APXK motifs to the AT-rich DNA. The results of the competition measurements and gel shift assays suggest that serine at the i-1 position (i is proline) can be replaced by alanine without affecting the binding properties of the motif. Thus, the presence of the conserved serine in this motif in many DNA-binding proteins is probably not dictated by structural requirements. Based on the results of molecular modeling studies we propose that the binding mode of the SPXK-type motifs to the AT-rich DNA resembles closely that between the N-terminal arm of the homeodomain and DNA. This model confirms that serine in the SPXK motifs is not essential for the DNA binding. The model also indicates that if X in the motif is glutamic acid, this residue is probably protonated in the complex with DNA.


2020 ◽  
Author(s):  
Marina Corbella ◽  
Qinghua Liao ◽  
Catia Moreira ◽  
Peter M. Kasson ◽  
Shina Caroline Lynn Kamerlin

<div> <div> <p>DNA-binding proteins play an important role in gene regulation and cellular function. The transcription factors MarA and Rob are two homologous members of the AraC/XylS family that regulate multidrug resistance. They share a common DNA-binding domain, and Rob possesses an additional C-terminal domain that permits binding of low-molecular weight effectors. Both proteins possess two helix-turn-helix (HTH) motifs capable of binding DNA; however, while MarA interacts with its promoter through both HTH-motifs, prior studies indicate that Rob binding to DNA via a single HTH-motif is sufficient for tight binding. In the present work, we perform microsecond time scale all-atom simulations of the binding of both transcription factors to different DNA sequences to understand the determinants of DNA recognition and binding. Our simulations characterize sequence-specific changes in dynamical behavior upon DNA binding, showcasing the role of Arg40 of the N-terminal HTH-motif in allowing for specific tight binding. Finally, our simulations demonstrate that an acidic C-terminal loop of Rob can control the DNA binding mode, facilitating interconversion between the distinct DNA binding modes observed in MarA and Rob. In doing so, we provide detailed molecular insight into DNA binding and recognition by these proteins, which in turn is an important step towards the efficient design of anti-virulence agents that target these proteins.</p> </div> </div>


2021 ◽  
Author(s):  
Marina Corbella ◽  
Qinghua Liao ◽  
Catia Moreira ◽  
Peter M. Kasson ◽  
Shina Caroline Lynn Kamerlin

<div> <div> <p>DNA-binding proteins play an important role in gene regulation and cellular function. The transcription factors MarA and Rob are two homologous members of the AraC/XylS family that regulate multidrug resistance. They share a common DNA-binding domain, and Rob possesses an additional C-terminal domain that permits binding of low-molecular weight effectors. Both proteins possess two helix-turn-helix (HTH) motifs capable of binding DNA; however, while MarA interacts with its promoter through both HTH-motifs, prior studies indicate that Rob binding to DNA via a single HTH-motif is sufficient for tight binding. In the present work, we perform microsecond time scale all-atom simulations of the binding of both transcription factors to different DNA sequences to understand the determinants of DNA recognition and binding. Our simulations characterize sequence-specific changes in dynamical behavior upon DNA binding, showcasing the role of Arg40 of the N-terminal HTH-motif in allowing for specific tight binding. Finally, our simulations demonstrate that an acidic C-terminal loop of Rob can control the DNA binding mode, facilitating interconversion between the distinct DNA binding modes observed in MarA and Rob. In doing so, we provide detailed molecular insight into DNA binding and recognition by these proteins, which in turn is an important step towards the efficient design of anti-virulence agents that target these proteins.</p> </div> </div>


2020 ◽  
Author(s):  
Marina Corbella ◽  
Qinghua Liao ◽  
Catia Moreira ◽  
Peter M. Kasson ◽  
Shina Caroline Lynn Kamerlin

<div> <div> <p>DNA-binding proteins play an important role in gene regulation and cellular function. The transcription factors MarA and Rob are two homologous members of the AraC/XylS family that regulate multidrug resistance. They share a common DNA-binding domain, and Rob possesses an additional C-terminal domain that permits binding of low-molecular weight effectors. Both proteins possess two helix-turn-helix (HTH) motifs capable of binding DNA; however, while MarA interacts with its promoter through both HTH-motifs, prior studies indicate that Rob binding to DNA via a single HTH-motif is sufficient for tight binding. In the present work, we perform microsecond time scale all-atom simulations of the binding of both transcription factors to different DNA sequences to understand the determinants of DNA recognition and binding. Our simulations characterize sequence-specific changes in dynamical behavior upon DNA binding, showcasing the role of Arg40 of the N-terminal HTH-motif in allowing for specific tight binding. Finally, our simulations demonstrate that an acidic C-terminal loop of Rob can control the DNA binding mode, facilitating interconversion between the distinct DNA binding modes observed in MarA and Rob. In doing so, we provide detailed molecular insight into DNA binding and recognition by these proteins, which in turn is an important step towards the efficient design of anti-virulence agents that target these proteins.</p> </div> </div>


2017 ◽  
Author(s):  
Samuel Gill ◽  
Nathan M. Lim ◽  
Patrick Grinaway ◽  
Ariën S. Rustenburg ◽  
Josh Fass ◽  
...  

<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>


2018 ◽  
Author(s):  
Samuel Gill ◽  
Nathan M. Lim ◽  
Patrick Grinaway ◽  
Ariën S. Rustenburg ◽  
Josh Fass ◽  
...  

<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>


2014 ◽  
Vol 21 (26) ◽  
pp. 3081-3094 ◽  
Author(s):  
M. Ashfaq ◽  
T. Najam ◽  
S.S.A. Shah ◽  
M.M. Ahmad ◽  
S. Shaheen ◽  
...  

Biomolecules ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 686 ◽  
Author(s):  
Alexander Neumann ◽  
Viktor Engel ◽  
Andhika B. Mahardhika ◽  
Clara T. Schoeder ◽  
Vigneshwaran Namasivayam ◽  
...  

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.


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