Use Of Docking Research Articles

Nettle-induced Urticaria Treatment Study (NUTS): demonstrating the joy of research through a randomised, blinded, placebo-controlled trial

The use of dock leaves to ease the discomfort of nettle stings is a well-known folk remedy in the British Isles, yet has never been tested in a clinical trial....

Взаимодействие лидерного пептида CmlAL с рибосомой E. coli, связавшей хлорамфеникол в неканоническом сайте

With the use of docking, equilibrium and biased molecular dynamics simulations, the structure of the 70S E. coli A/A,P/P-ribosome complex with chloramphenicol, an antibiotic, bound in a non-canonical site near the peptidyl transferase center, and ClmAL leader peptide, placed in the nascent peptide exit tunnel, has been obtained. In this structure, chloramphenicol is retained in the ribosome due to wedging of its nitrophenyl residue into the cavity between the Ψ2504 and U2506 residues of 23S rRNA and formation of hydrophobic contacts with them, as well as hydrogen bonds with the G2505 and G2061 residues of 23S rRNA. The ClmAL leader peptide forms many stable hydrogen bonds with the G2061, m2A2503, U2609, and C2610 residues of 23S rRNA. Molecular dynamics simulations of this ternary complex has shown that the mechanism of antibiotic action is to induce divergence of the peptidyl transferase reaction of the substrates relative to each other at a distance that excludes the transpeptidation reaction. This divergence of the peptidyl transferase reaction substrates is stabilized by interactions between the side chain amino group of the lysine residue in the A site, on the one hand, and the C2063 base and chloramphenicol, on the other hand. In this case, the α-amino group of the lysine residue forms a hydrogen bond with the carbonyl group of the Ala-7 CmlAL residue. Together with specific interactions of the CmlAL peptide residues with the rRNA residues of the nascent peptide exit tunnel, this explains the arrest of translation in the presence of chloramphenicol at this particular sequence and, as a consequence, the presence of this sequence in the genes encoding the CmlA transporter protein, which is responsible for ribosomal resistance to this antibiotic.

The spectre of docking in circumcision debates

This articles considers the ongoing penile circumcision debates by focusing on the deployment of ‘docking,’ a sexual practice between men. Docking involves pulling one’s foreskin over the glans of another penis. In this article, I consider both “anti” and “pro” circumcision literature and the use of docking in the service of arguments about the procedure. I show that the use of docking can be traced to Daniel M. Harrison’s article “Rethinking Circumcision and Sexuality in the United States” published in Sexualities. Ultimately, I argue that while docking is interesting to consider, it remains something of spectre that haunts the debates more than it is an empirical concern. Consequently, I argue that further study is needed about docking in general, as well as in the particular context of circumcision debates.

Panoramic Review on Progress and Development of Molecular Docking

In structural molecular biology and computer-assisted drug creation, molecular docking is a crucial tool. Predicting the prevailing binding mode (s) of a ligand with a protein having a known three-dimensional structure is the aim of ligand-protein docking. Effective docking methods use a scoring system that correctly ranks candidate dockings and efficiently explore high-dimensional spaces. Lead optimization benefits greatly from the use of docking to do virtual screening on huge libraries of compounds, rate the outcomes, and offer structural ideas for how the ligands inhibit the target. It can be difficult to interpret the findings of stochastic search methods, and setting up the input structures for docking is just as crucial as docking itself. In recent years, computer-assisted drug design has relied heavily on the molecular docking technique to estimate the binding affinity and assess the interactive mode since it can significantly increase efficiency and lower research costs. The main concepts, techniques, and frequently utilized molecular docking applications are introduced in this work. Additionally, it contrasts the most popular docking applications and suggests relevant study fields. Finally, a brief summary of recent developments in molecular docking, including the integrated technique and deep learning, is provided. Current docking applications are not precise enough to forecast the binding affinity due to the insufficient molecular structure and the inadequacies of the scoring mechanism.

Recognition of the interaction between the bioactive peptide Val-Pro-Pro and the minimal promoter region of genes SOD and CAT using QCM-D and docking studies.

Bioactive peptides are biomolecules involved in very diverse mechanisms in vivo. It has been reported that bioactive peptides play a very important role in the regulation of physiological functions such as oxidative stress, hypertension, cancer and inflammation. It's been reported that the milk derived peptide (VPP) prevents the progress of hypertension in different animal models and human beings with mild hypertension. It has also been shown that oral administration of VPP produces an anti-inflammatory effect in adipose tissue of mouse models. Currently there are no reports on the possible interaction of VPP with the enzymes superoxide dismutase (SOD) and catalase (CAT), the main regulators of oxidative stress. This study analyzes the interaction between VPP and specific domains in the minimal promoter region of the genes SOD and CAT in blood samples of obese children using a QCM-D type piezoelectric biosensor. We also used molecular modeling (docking) to determine the interaction between the peptide VPP and the minimal promoter region of both genes. With QCM-D, we detected the interaction of VPP with the nitrogenous base sequences that comprise the minimal promoter regions of both genes CAT and SOD. These experimental interactions were explained at the atomic level by molecular docking simulations showing how the peptides are capable of reaching the DNA structures by means of hydrogen bonds with favored free energy values. It is possible to conclude that the combined use of docking and QCM-D allows for the determination of the interaction of small peptides (VPP) with specific sequences of genes.

Fullerenes against COVID-19: Repurposing C60 and C70 to Clog the Active Site of SARS-CoV-2 Protease.

The persistency of COVID-19 in the world and the continuous rise of its variants demand new treatments to complement vaccines. Computational chemistry can assist in the identification of moieties able to lead to new drugs to fight the disease. Fullerenes and carbon nanomaterials can interact with proteins and are considered promising antiviral agents. Here, we propose the possibility to repurpose fullerenes to clog the active site of the SARS-CoV-2 protease, Mpro. Through the use of docking, molecular dynamics, and energy decomposition techniques, it is shown that C60 has a substantial binding energy to the main protease of the SARS-CoV-2 virus, Mpro, higher than masitinib, a known inhibitor of the protein. Furthermore, we suggest the use of C70 as an innovative scaffold for the inhibition of SARS-CoV-2 Mpro. At odds with masitinib, both C60 and C70 interact more strongly with SARS-CoV-2 Mpro when different protonation states of the catalytic dyad are considered. The binding of fullerenes to Mpro is due to shape complementarity, i.e., vdW interactions, and is aspecific. As such, it is not sensitive to mutations that can eliminate or invert the charges of the amino acids composing the binding pocket. Fullerenic cages should therefore be more effective against the SARS-CoV-2 virus than the available inhibitors such as masinitib, where the electrostatic term plays a crucial role in the binding.

A Membrane Protein Complex Docking Benchmark

We report the first membrane protein–protein docking benchmark consisting of 37 targets of diverse functions and folds. The structures were chosen based on a set of parameters such as the availability of unbound structures, the modeling difficulty and their uniqueness. They have been cleaned and consistently numbered to facilitate their use in docking. Using this benchmark, we establish the baseline performance of HADDOCK, without any specific optimization for membrane proteins, for two scenarios: true interface-driven docking and ab initio docking. Despite the fact that HADDOCK has been developed for soluble complexes, it shows promising docking performance for membrane systems, but there is clearly room for further optimization. The resulting set of docking decoys, together with analysis scripts, is made freely available. These can serve as a basis for the optimization of membrane complex-specific scoring functions.

Identifying the interactions between natural, non-caloric sweeteners and the human sweet receptor by molecular docking

Natural sweeteners, such as stevia and thaumatin, exert their sweet taste by specifically binding to sweet taste receptors. However, the molecular basis of their sweetening power remains to be ascertained. In the present study, we built a comparative model of the hT1R2 and hT1R3 subunits in order to characterize their interactions with natural, non-caloric sweeteners – from glycosylated terpenoids to sweet proteins – at the molecular level. The binding free energy between hT1R2-hT1R3 and sweeteners of different families shows a strong correlation with their sweetness intensity for both, small sweeteners (r = −0.89) and sweet proteins (r = −0.97). The correlation is further improved and generalized throughout all families of sweeteners evaluated, when EC50 values are used instead of relative intensities (r = −0.91). Altogether, these results contribute to a better understanding of the sweetness perception of these sweeteners, and promote the use of docking for better prediction of resulting sweetness.

DESIGN OF DOCKING SYSTEM FOR MOBILE ROBOTICS PLATFORM TYPE AGV

Urgency of the research. Automatic battery charging of AGV platforms allows you to maximize their potential. Safe and quickly positioning AGVs in a charging station equipped with appropriate contacts, reduces the charging time as well as the purchase price of the device. Target setting. The aim of the solution is to design an automatic docking and charging station from a used hand-held charging station. In the design, it was necessary to ensure the appropriate position of the AGV platform against the docking station. Actual scientific researches and issues analysis. The issue of fast and reliable charging of mobile service robots is highly up-to-date. The reason for this is the growing deployment of AGV platforms in various industrial or service sectors. Uninvestigated parts of general matters defining. This article focuses on a specific solution for the provision of transport services. Transport services come from the need to transport medical supplies and medications in a multi-storey hospital building. The movement of the robot between the floors is solved by the use of lifts used by the personal of hospital. The research objective. The aim of the research was to design a docking and charging station utilized an already purchased power-up charger. The design was aimed at creating an appropriate power transmission system between the charger and the AGV platform batteries. The price ceiling for the whole facility was worth € 2,000. The statement of basic materials. The use of docking and charging stations for mobile service robots is dependent on a number of parameters. In particular, the parameters depend on the area of use, the size of the battery to be charged, and the amount of robots being recharged at the station. Last but not least, charging time and purchase price are also important. Conclusions. The task of the solution was to design a docking station design for the AGV platform. At the beginning, three variants were created, from which the most appropriate solution was chosen using the scoring method. However, before designing the docking station design, it was necessary to modify the existing AGV platform construction so that it could be connected to the docking station charging mechanism. The design of the docking station itself consisted of the design of the charging and charging mechanism. These mechanisms provide charge and guidance of the AGV platform to the docking station. Mechanisms are not dependent on each other, since the charging mechanism is activated later than the drive mechanism. Subsequently, a design of the docking station, which can be anchored to the floor or to the wall, was created. At the docking station there is a charger from Hoppecke, which provides the AGV platform charging. The design dimensions of the docking station have been greatly influenced by the size of the above-mentioned charger. It has been found that new and better technologies will not be needed at the docking stations in the future, as AGV platforms can be guided without their help. The development of new and better quality systems will bring new guidance options to AGV platforms and docking stations.

Predictive Structure-Based Toxicology Approaches To Assess the Androgenic Potential of Chemicals.

We present a practical and easy-to-run in silico workflow exploiting a structure-based strategy making use of docking simulations to derive highly predictive classification models of the androgenic potential of chemicals. Models were trained on a high-quality chemical collection comprising 1689 curated compounds made available within the CoMPARA consortium from the US Environmental Protection Agency and were integrated with a two-step applicability domain whose implementation had the effect of improving both the confidence in prediction and statistics by reducing the number of false negatives. Among the nine androgen receptor X-ray solved structures, the crystal 2PNU (entry code from the Protein Data Bank) was associated with the best performing structure-based classification model. Three validation sets comprising each 2590 compounds extracted by the DUD-E collection were used to challenge model performance and the effectiveness of Applicability Domain implementation. Next, the 2PNU model was applied to screen and prioritize two collections of chemicals. The first is a small pool of 12 representative androgenic compounds that were accurately classified based on outstanding rationale at the molecular level. The second is a large external blind set of 55450 chemicals with potential for human exposure. We show how the use of molecular docking provides highly interpretable models and can represent a real-life option as an alternative nontesting method for predictive toxicology.

Molecular Simulations of Disulfide-Rich Venom Peptides with Ion Channels and Membranes.

Disulfide-rich peptides isolated from the venom of arthropods and marine animals are a rich source of potent and selective modulators of ion channels. This makes these peptides valuable lead molecules for the development of new drugs to treat neurological disorders. Consequently, much effort goes into understanding their mechanism of action. This paper presents an overview of how molecular simulations have been used to study the interactions of disulfide-rich venom peptides with ion channels and membranes. The review is focused on the use of docking, molecular dynamics simulations, and free energy calculations to (i) predict the structure of peptide-channel complexes; (ii) calculate binding free energies including the effect of peptide modifications; and (iii) study the membrane-binding properties of disulfide-rich venom peptides. The review concludes with a summary and outlook.

Surfing the Protein-Protein Interaction Surface Using Docking Methods: Application to the Design of PPI Inhibitors.

Blocking protein-protein interactions (PPI) using small molecules or peptides modulates biochemical pathways and has therapeutic significance. PPI inhibition for designing drug-like molecules is a new area that has been explored extensively during the last decade. Considering the number of available PPI inhibitor databases and the limited number of 3D structures available for proteins, docking and scoring methods play a major role in designing PPI inhibitors as well as stabilizers. Docking methods are used in the design of PPI inhibitors at several stages of finding a lead compound, including modeling the protein complex, screening for hot spots on the protein-protein interaction interface and screening small molecules or peptides that bind to the PPI interface. There are three major challenges to the use of docking on the relatively flat surfaces of PPI. In this review we will provide some examples of the use of docking in PPI inhibitor design as well as its limitations. The combination of experimental and docking methods with improved scoring function has thus far resulted in few success stories of PPI inhibitors for therapeutic purposes. Docking algorithms used for PPI are in the early stages, however, and as more data are available docking will become a highly promising area in the design of PPI inhibitors or stabilizers.

Drug-induced conformational population shifts in topoisomerase-DNA ternary complexes.

Type II topoisomerases (TOP2) are enzymes that resolve the topological problems during DNA replication and transcription by transiently cleaving both strands and forming a cleavage complex with the DNA. Several prominent anti-cancer agents inhibit TOP2 by stabilizing the cleavage complex and engendering permanent DNA breakage. To discriminate drug binding modes in TOP2-α and TOP2-β, we applied our newly developed scoring function, dubbed AutoDock4RAP, to evaluate the binding modes of VP-16, m-AMSA, and mitoxantrone to the cleavage complexes. Docking reproduced crystallographic binding mode of VP-16 in a ternary complex of TOP2-β with root-mean-square deviation of 0.65 Å. Molecular dynamics simulation of the complex confirmed the crystallographic binding mode of VP-16 and the conformation of the residue R503. Drug-related conformational changes in R503 have been observed in ternary complexes with m-AMSA and mitoxantrone. However, the R503 rotamers in these two simulations deviate from their crystallographic conformations, indicating a relaxation dynamics from the conformations determined with the drug replacement procedure. The binding mode of VP-16 in the cleavage complex of TOP2-α was determined by the conjoint use of docking and molecular dynamics simulations, which fell within a similar binding pocket of TOP2-β cleavage complex. Our findings may facilitate more efficient design efforts targeting TOP2-α specific drugs.

Predicting ligand binding affinity: A comparative study on the use of docking vs. Bayesian categorization and random forest recursive partitioning

Predicting ligand binding affinity: A comparative study on the use of docking vs. Bayesian categorization and random forest recursive partitioning

Comparative Study on the Use of Docking and Bayesian Categorization To Predict Ligand Binding to Nicotinic Acetylcholine Receptors (nAChRs) Subtypes

We have carried out a comparative study between docking into homology models and Bayesian categorization, as applied to virtual screening of nicotinic ligands for binding at various nAChRs subtypes (human and rat α4β2, α7, α3β4, and α6β2β3). We found that although results vary with receptor subtype, Bayesian categorization exhibits higher accuracy and enrichment than unconstrained docking into homology models. However, docking accuracy is improved when one sets up a hydrogen-bond (HB) constraint between the cationic center of the ligand and the main-chain carbonyl group of the conserved Trp-149 or its homologue (a residue involved in cation-π interactions with the ligand basic nitrogen atom). This finding suggests that this HB is a hallmark of nicotinic ligands binding to nAChRs. Best predictions using either docking or Bayesian were obtained with the human α7 nAChR, when 100 nM was used as cutoff for biological activity. We also found that ligand-based Bayesian-derived enrichment factors and structure-based docking-derived enrichment factors highly correlate to each other. Moreover, they correlate with the mean molecular fractional polar surface area of actives ligands and the fractional hydrophobic/hydrophilic surface area of the binding site, respectively. This result is in agreement with the fact that hydrophobicity strongly contributes in promoting nicotinic ligands binding to their cognate nAChRs.

An In Silico Analysis of the Binding Modes and Binding Affinities of Small Molecule Modulators of PDZ-Peptide Interactions

Inhibitors of PDZ-peptide interactions have important implications in a variety of biological processes including treatment of cancer and Parkinson’s disease. Even though experimental studies have reported characterization of peptidomimetic inhibitors of PDZ-peptide interactions, the binding modes for most of them have not been characterized by structural studies. In this study we have attempted to understand the structural basis of the small molecule-PDZ interactions by in silico analysis of the binding modes and binding affinities of a set of 38 small molecules with known Ki or Kd values for PDZ2 and PDZ3 domains of PSD-95 protein. These two PDZ domains show differential selectivity for these compounds despite having a high degree of sequence similarity and almost identical peptide binding pockets. Optimum binding modes for these ligands for PDZ2 and PDZ3 domains were identified by using a novel combination of semi-flexible docking and explicit solvent molecular dynamics (MD) simulations. Analysis of the binding modes revealed most of the peptidomimectic ligands which had high Ki or Kd moved away from the peptide binding pocket, while ligands with high binding affinities remained in the peptide binding pocket. The differential specificities of the PDZ2 and PDZ3 domains primarily arise from differences in the conformation of the loop connecting βB and βC strands, because this loop interacts with the N-terminal chemical moieties of the ligands. We have also computed the MM/PBSA binding free energy values for these 38 compounds with both the PDZ domains from multiple 5 ns MD trajectories on each complex i.e. a total of 228 MD trajectories of 5 ns length each. Interestingly, computational binding free energies show good agreement with experimental binding free energies with a correlation coefficient of approximately 0.6. Thus our study demonstrates that combined use of docking and MD simulations can help in identification of potent inhibitors of PDZ-peptide complexes.

Design, synthesis and molecular modelling of novel methyl[4-oxo-2-(aroylimino)-3-(substituted phenyl)thiazolidin-5-ylidene]acetates as potent and selective aldose reductase inhibitors

A series of new iminothiazolidin-4-one acetate derivatives was synthesized and evaluated as aldehyde reductase (ALR1) and aldose reductase (ALR2) inhibitors. Methyl[4-oxo-2-(substituted benzoylimino)-3-(substituted phenyl)thiazolidin-5-ylidene]acetate derivatives were obtained in excellent yields by cyclocondensation of 1-aroyl-3-aroylthioureas (2a–n) with dimethylacetylene dicarboxylate (DMAD) in methanol at room temperature. Compounds were characterized by available spectroscopic techniques and compound 2k was also confirmed by X-ray crystallography. The highest ALR2 inhibitory potency in the series was observed for methyl[4-oxo-2-(benzoylimino)-3-(2-methoxyphenyl)thiazolidin-5-ylidene]acetate (2a) and methyl[4-oxo-2-(2-bromobenzoylimino)-3-(2,4-dichlorophenyl)thiazolidin-5-ylidene]acetate (2k) with IC50 values of 2.82 and 2.54 μM, respectively. The combined use of docking and molecular dynamics simulations shed light on the observed structure–selectivity relationships and binding modes of the inhibitors with the active site of ALR2. Aldose reductase inhibitors have potential as novel drugs for the treatment of diabetic complications.

3D QSAR pharmacophore modeling, in silico screening, and density functional theory (DFT) approaches for identification of human chymase inhibitors.

Human chymase is a very important target for the treatment of cardiovascular diseases. Using a series of theoretical methods like pharmacophore modeling, database screening, molecular docking and Density Functional Theory (DFT) calculations, an investigation for identification of novel chymase inhibitors, and to specify the key factors crucial for the binding and interaction between chymase and inhibitors is performed. A highly correlating (r = 0.942) pharmacophore model (Hypo1) with two hydrogen bond acceptors, and three hydrophobic aromatic features is generated. After successfully validating “Hypo1”, it is further applied in database screening. Hit compounds are subjected to various drug-like filtrations and molecular docking studies. Finally, three structurally diverse compounds with high GOLD fitness scores and interactions with key active site amino acids are identified as potent chymase hits. Moreover, DFT study is performed which confirms very clear trends between electronic properties and inhibitory activity (IC50) data thus successfully validating “Hypo1” by DFT method. Therefore, this research exertion can be helpful in the development of new potent hits for chymase. In addition, the combinational use of docking, orbital energies and molecular electrostatic potential analysis is also demonstrated as a good endeavor to gain an insight into the interaction between chymase and inhibitors.

Use of docking, cross docking and molecular dynamic simulations to rationalize the activity data of some S-dabos on wild-type and three mutant strains of reverse transcriptase

Use of docking, cross docking and molecular dynamic simulations to rationalize the activity data of some S-dabos on wild-type and three mutant strains of reverse transcriptase

Design, Synthesis, and Biological Evaluation of Coumarin Derivatives Tethered to an Edrophonium‐like Fragment as Highly Potent and Selective Dual Binding Site Acetylcholinesterase Inhibitors

A large series of substituted coumarins linked through an appropriate spacer to 3-hydroxy-N,N-dimethylanilino or 3-hydroxy-N,N,N-trialkylbenzaminium moieties were synthesized and evaluated as acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) inhibitors. The highest AChE inhibitory potency in the 3-hydroxy-N,N-dimethylanilino series was observed with a 6,7-dimethoxy-3-substituted coumarin derivative, which, along with an outstanding affinity (IC(50)=0.236 nM) exhibits excellent AChE/BChE selectivity (SI>300 000). Most of the synthesized 3-hydroxy-N,N,N-trialkylbenzaminium salts display an AChE affinity in the sub-nanomolar to picomolar range along with excellent AChE/BChE selectivities (SI values up to 138 333). The combined use of docking and molecular dynamics simulations permitted us to shed light on the observed structure-affinity and structure-selectivity relationships, to detect two possible alternative binding modes, and to assess the critical role of pi-pi stacking interactions in the AChE peripheral binding site.