scholarly journals Targeting G-quadruplexes with Organic Dyes: Chelerythrine–DNA Binding Elucidated by Combining Molecular Modeling and Optical Spectroscopy

Antioxidants ◽  
2019 ◽  
Vol 8 (10) ◽  
pp. 472 ◽  
Author(s):  
Alessio Terenzi ◽  
Hugo Gattuso ◽  
Angelo Spinello ◽  
Bernhard K. Keppler ◽  
Christophe Chipot ◽  
...  
Keyword(s):  
Molecular Modeling ◽  
Dna Binding ◽  
Organic Dyes ◽  
Md Simulations ◽  
Optical Absorption Spectroscopy ◽  
Regulatory Sequences ◽  
Binding Modes ◽  
Free Energies ◽  
Drug Candidates ◽  
Dna Conformations

The DNA-binding of the natural benzophenanthridine alkaloid chelerythrine (CHE) has been assessed by combining molecular modeling and optical absorption spectroscopy. Specifically, both double-helical (B-DNA) and G-quadruplex sequences—representative of different topologies and possessing biological relevance, such as telomeric or regulatory sequences—have been considered. An original multiscale protocol, making use of molecular dynamics (MD) simulations and quantum mechanics/molecular mechanics (QM/MM) calculations, allowed us to compare the theoretical and experimental circular dichroism spectra of the different DNA topologies, readily providing atomic-level details of the CHE–DNA binding modes. The binding selectivity towards G-quadruplexes is confirmed by both experimental and theoretical determination of the binding free energies. Overall, our mixed computational and experimental approach is able to shed light on the interaction of small molecules with different DNA conformations. In particular, CHE may be seen as the building block of promising drug candidates specifically targeting G-quadruplexes for both antitumoral and antiviral purposes.

scholarly journals Accurate and sensitive quantification of protein-DNA binding affinity

2018 ◽  
Vol 115 (16) ◽  
pp. E3692-E3701 ◽  
Author(s):  
Chaitanya Rastogi ◽  
H. Tomas Rube ◽  
Judith F. Kribelbauer ◽  
Justin Crocker ◽  
Ryan E. Loker ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Binding ◽  
Binding Sites ◽  
Biophysical Model ◽  
Regulatory Sequences ◽  
Binding Modes ◽  
Perfect Agreement ◽  
Dna Binding Sites

Transcription factors (TFs) control gene expression by binding to genomic DNA in a sequence-specific manner. Mutations in TF binding sites are increasingly found to be associated with human disease, yet we currently lack robust methods to predict these sites. Here, we developed a versatile maximum likelihood framework named No Read Left Behind (NRLB) that infers a biophysical model of protein-DNA recognition across the full affinity range from a library of in vitro selected DNA binding sites. NRLB predicts human Max homodimer binding in near-perfect agreement with existing low-throughput measurements. It can capture the specificity of the p53 tetramer and distinguish multiple binding modes within a single sample. Additionally, we confirm that newly identified low-affinity enhancer binding sites are functional in vivo, and that their contribution to gene expression matches their predicted affinity. Our results establish a powerful paradigm for identifying protein binding sites and interpreting gene regulatory sequences in eukaryotic genomes.

scholarly journals Binding of SPXK- and APXK-peptide motifs to AT-rich DNA. Experimental and theoretical studies.

1998 ◽  
Vol 45 (1) ◽  
pp. 221-231 ◽  
Author(s):  
J Brzeski ◽  
T Grycuk ◽  
A W Lipkowski ◽  
W Rudnicki ◽  
B Lesyng ◽  
...  
Keyword(s):  
Molecular Modeling ◽  
Dna Binding ◽  
Experimental Studies ◽  
Binding Mode ◽  
Binding Modes ◽  
Binding Properties ◽  
Peptide Motifs ◽  
Gel Shift Assay ◽  
Molecular Modeling Studies ◽  
Gel Shift

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.

Recent Advances of In-Silico Modeling of Potent Antagonists for the Adenosine Receptors

2019 ◽  
Vol 25 (7) ◽  
pp. 750-773 ◽  
Author(s):  
Pabitra Narayan Samanta ◽  
Supratik Kar ◽  
Jerzy Leszczynski
Keyword(s):  
Drug Targets ◽  
Biological Activities ◽  
Scoring Function ◽  
Md Simulations ◽  
Energy Calculation ◽  
Binding Modes ◽  
Macromolecular Systems ◽  
In Silico Modeling ◽  
Mathematical Algorithms ◽  
The Impact

The rapid advancement of computer architectures and development of mathematical algorithms offer a unique opportunity to leverage the simulation of macromolecular systems at physiologically relevant timescales. Herein, we discuss the impact of diverse structure-based and ligand-based molecular modeling techniques in designing potent and selective antagonists against each adenosine receptor (AR) subtype that constitutes multitude of drug targets. The efficiency and robustness of high-throughput empirical scoring function-based approaches for hit discovery and lead optimization in the AR family are assessed with the help of illustrative examples that have led to nanomolar to sub-micromolar inhibition activities. Recent progress in computer-aided drug discovery through homology modeling, quantitative structure-activity relation, pharmacophore models, and molecular docking coupled with more accurate free energy calculation methods are reported and critically analyzed within the framework of structure-based virtual screening of AR antagonists. Later, the potency and applicability of integrated molecular dynamics (MD) methods are addressed in the context of diligent inspection of intricated AR-antagonist binding processes. MD simulations are exposed to be competent for studying the role of the membrane as well as the receptor flexibility toward the precise evaluation of the biological activities of antagonistbound AR complexes such as ligand binding modes, inhibition affinity, and associated thermodynamic and kinetic parameters.

scholarly journals Automation of absolute protein-ligand binding free energy calculations for docking refinement and compound evaluation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Germano Heinzelmann ◽  
Michael K. Gilson
Keyword(s):  
Free Energy ◽  
Early Stage ◽  
Binding Free Energy ◽  
Low Cost ◽  
Free Energy Calculations ◽  
Free Energies ◽  
Energy Calculations ◽  
Drug Candidates ◽  
Binding Free Energy Calculations ◽  
Binding Free Energies

AbstractAbsolute binding free energy calculations with explicit solvent molecular simulations can provide estimates of protein-ligand affinities, and thus reduce the time and costs needed to find new drug candidates. However, these calculations can be complex to implement and perform. Here, we introduce the software BAT.py, a Python tool that invokes the AMBER simulation package to automate the calculation of binding free energies for a protein with a series of ligands. The software supports the attach-pull-release (APR) and double decoupling (DD) binding free energy methods, as well as the simultaneous decoupling-recoupling (SDR) method, a variant of double decoupling that avoids numerical artifacts associated with charged ligands. We report encouraging initial test applications of this software both to re-rank docked poses and to estimate overall binding free energies. We also show that it is practical to carry out these calculations cheaply by using graphical processing units in common machines that can be built for this purpose. The combination of automation and low cost positions this procedure to be applied in a relatively high-throughput mode and thus stands to enable new applications in early-stage drug discovery.

scholarly journals Fluorescent thermal shift-based method for detection of NF-κB binding to double-stranded DNA

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Peter D. Leitner ◽  
Ilja Vietor ◽  
Lukas A. Huber ◽  
Taras Valovka
Keyword(s):  
Dna Binding ◽  
Rational Design ◽  
Dissociation Constants ◽  
Inflammatory Diseases ◽  
Dimethyl Fumarate ◽  
Bioinformatic Analysis ◽  
Quantitative Detection ◽  
Regulatory Sequences ◽  
Wide Range ◽  
Inhibitory Drug

AbstractThe nuclear factor kappa B (NF-κB) family of dimeric transcription factors regulates a wide range of genes by binding to their specific DNA regulatory sequences. NF-κB is an important therapeutic target linked to a number of cancers as well as autoimmune and inflammatory diseases. Therefore, effective high-throughput methods for the detection of NF-κB DNA binding are essential for studying its transcriptional activity and for inhibitory drug screening. We describe here a novel fluorescence-based assay for quantitative detection of κB consensus double-stranded (ds) DNA binding by measuring the thermal stability of the NF-κB proteins. Specifically, DNA binding proficient NF-κB probes, consisting of the N-terminal p65/RelA (aa 1–306) and p50 (aa 1–367) regions, were designed using bioinformatic analysis of protein hydrophobicity, folding and sequence similarities. By measuring the SYPRO Orange fluorescence during thermal denaturation of the probes, we detected and quantified a shift in the melting temperatures (ΔTm) of p65/RelA and p50 produced by the dsDNA binding. The increase in Tm was proportional to the concentration of dsDNA with apparent dissociation constants (KD) of 2.228 × 10–6 M and 0.794 × 10–6 M, respectively. The use of withaferin A (WFA), dimethyl fumarate (DMF) and p-xyleneselenocyanate (p-XSC) verified the suitability of this assay for measuring dose-dependent antagonistic effects on DNA binding. In addition, the assay can be used to analyse the direct binding of inhibitors and their effects on structural stability of the protein probe. This may facilitate the identification and rational design of new drug candidates interfering with NF-κB functions.

scholarly journals Exploration of Novel Xanthine Oxidase Inhibitors Based on 1,6-Dihydropyrimidine-5-Carboxylic Acids by an Integrated in Silico Study

2021 ◽  
Vol 22 (15) ◽  
pp. 8122
Author(s):  
Na Zhai ◽  
Chenchen Wang ◽  
Fengshou Wu ◽  
Liwei Xiong ◽  
Xiaogang Luo ◽  
...  
Keyword(s):  
Xanthine Oxidase ◽  
Carboxylic Acids ◽  
Hydrophobic Interactions ◽  
Pharmacophore Model ◽  
3D Qsar ◽  
Md Simulations ◽  
Pharmacophore Modeling ◽  
Binding Modes ◽  
Comfa Model ◽  
Validation Parameters

Xanthine oxidase (XO) is an important target for the effective treatment of hyperuricemia-associated diseases. A series of novel 2-substituted 6-oxo-1,6-dihydropyrimidine-5-carboxylic acids (ODCs) as XO inhibitors (XOIs) with remarkable activities have been reported recently. To better understand the key pharmacological characteristics of these XOIs and explore more hit compounds, in the present study, the three-dimensional quantitative structure–activity relationship (3D-QSAR), molecular docking, pharmacophore modeling, and molecular dynamics (MD) studies were performed on 46 ODCs. The constructed 3D-QSAR models exhibited reliable predictability with satisfactory validation parameters, including q2 = 0.897, R2 = 0.983, rpred2 = 0.948 in a CoMFA model, and q2 = 0.922, R2 = 0.990, rpred2 = 0.840 in a CoMSIA model. Docking and MD simulations further gave insights into the binding modes of these ODCs with the XO protein. The results indicated that key residues Glu802, Arg880, Asn768, Thr1010, Phe914, and Phe1009 could interact with ODCs by hydrogen bonds, π-π stackings, or hydrophobic interactions, which might be significant for the activity of these XOIs. Four potential hits were virtually screened out using the constructed pharmacophore model in combination with molecular dockings and ADME predictions. The four hits were also found to be relatively stable in the binding pocket by MD simulations. The results in this study might provide effective information for the design and development of novel XOIs.

scholarly journals Natural Compound Modulates the Cervical Cancer Microenvironment—A Pharmacophore Guided Molecular Modelling Approaches

2018 ◽  
Vol 7 (12) ◽  
pp. 551 ◽  
Author(s):  
Shailima Rampogu ◽  
Doneti Ravinder ◽  
Smita Pawar ◽  
Keun Lee
Keyword(s):  
Cervical Cancer ◽  
Md Simulations ◽  
Data Bank ◽  
Docking Studies ◽  
New Drugs ◽  
Binding Modes ◽  
Cervical Cancer Cells ◽  
Causative Agents ◽  
Nitric Oxide Synthase 2 ◽  
Oxide Synthase

Cervical cancer is regarded as one of the major burdens noticed in women next to breast cancer. Although, human papilloma viruses (HPVs) are regarded as the principal causative agents, they require certain other factors such as oestrogen hormone to induce cervical cancer. Aromatase is an enzyme that converts androgens into oestrogens and hindering this enzyme could subsequently hamper the formation of oestrogen thereby alleviating the disease. Accordingly, in the current investigation, a structure based pharmacophore was generated considering two proteins bearing the Protein Data Bank (PDB) codes 3EQM (pharm 1) and 3S7S (pharm 2), respectively. The two models were employed as the 3D query to screen the in-house built natural compounds database. The obtained 51 compounds were escalated to molecular docking studies to decipher on the binding affinities and to predict the quintessential binding modes which were affirmed by molecular dynamics (MD) simulations. The compound has induced dose-dependent down regulation of PP2B, Nitric oxide synthase-2 (NOS2), and Interleukin 6 (IL-6) genes in the HeLa cells and has modulated the expression of apoptotic genes such as Bax, Bcl2, and caspases-3 at different concentrations. These results guide us to comprehend that the identified aromatase inhibitor was effective against the cervical cancer cells and additionally could server as scaffolds in designing new drugs.

scholarly journals Solvents to Fragments to Drugs: MD Applications in Drug Design

Molecules ◽  
2018 ◽  
Vol 23 (12) ◽  
pp. 3269 ◽  
Author(s):  
Lucas Defelipe ◽  
Juan Arcon ◽  
Carlos Modenutti ◽  
Marcelo Marti ◽  
Adrián Turjanski ◽  
...  
Keyword(s):  
Binding Free Energy ◽  
Mixed Solvents ◽  
Md Simulations ◽  
Binding Mode ◽  
Condensed State ◽  
Protein Targets ◽  
Drug Candidates ◽  
Interaction Sites ◽  
Aqueous Solvation ◽  
The Common

Simulations of molecular dynamics (MD) are playing an increasingly important role in structure-based drug discovery (SBDD). Here we review the use of MD for proteins in aqueous solvation, organic/aqueous mixed solvents (MDmix) and with small ligands, to the classic SBDD problems: Binding mode and binding free energy predictions. The simulation of proteins in their condensed state reveals solvent structures and preferential interaction sites (hot spots) on the protein surface. The information provided by water and its cosolvents can be used very effectively to understand protein ligand recognition and to improve the predictive capability of well-established methods such as molecular docking. The application of MD simulations to the study of the association of proteins with drug-like compounds is currently only possible for specific cases, as it remains computationally very expensive and labor intensive. MDmix simulations on the other hand, can be used systematically to address some of the common tasks in SBDD. With the advent of new tools and faster computers we expect to see an increase in the application of mixed solvent MD simulations to a plethora of protein targets to identify new drug candidates.

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