Accessible High-Throughput Virtual Screening Molecular Docking Software for Students and Educators

Jacob, Reed B.; Andersen, Tim; McDougal, Owen M.

doi:10.1371/journal.pcbi.1002499

Cited by 98 publications

(62 citation statements)

References 37 publications

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“…In order to assist the selection of metabolites for further experimental analysis binding energy of RR metabolites have been tested computationally using high-throughput docking analysis performed using PyRx (Scripps Research Institute, La Jolla, CA, USA) [63] and AutoDock4 (Scripps Research Institute, La Jolla, CA, USA) [64]. A zinc atom has been added to the FGSG_04603 structural model according to the analysis of the structural overlap between the experimental and modeled data.…”

Section: Resultsmentioning

confidence: 99%

Metabolomics and Cheminformatics Analysis of Antifungal Function of Plant Metabolites

Čuperlović-Culf¹,

Rajagopalan²,

Tulpan³

et al. 2016

Metabolites

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Fusarium head blight (FHB), primarily caused by Fusarium graminearum, is a devastating disease of wheat. Partial resistance to FHB of several wheat cultivars includes specific metabolic responses to inoculation. Previously published studies have determined major metabolic changes induced by pathogens in resistant and susceptible plants. Functionality of the majority of these metabolites in resistance remains unknown. In this work we have made a compilation of all metabolites determined as selectively accumulated following FHB inoculation in resistant plants. Characteristics, as well as possible functions and targets of these metabolites, are investigated using cheminformatics approaches with focus on the likelihood of these metabolites acting as drug-like molecules against fungal pathogens. Results of computational analyses of binding properties of several representative metabolites to homology models of fungal proteins are presented. Theoretical analysis highlights the possibility for strong inhibitory activity of several metabolites against some major proteins in Fusarium graminearum, such as carbonic anhydrases and cytochrome P450s. Activity of several of these compounds has been experimentally confirmed in fungal growth inhibition assays. Analysis of anti-fungal properties of plant metabolites can lead to the development of more resistant wheat varieties while showing novel application of cheminformatics approaches in the analysis of plant/pathogen interactions.

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Section: Resultsmentioning

confidence: 99%

Metabolomics and Cheminformatics Analysis of Antifungal Function of Plant Metabolites

Čuperlović-Culf¹,

Rajagopalan²,

Tulpan³

et al. 2016

Metabolites

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“…The process of docking is based on two processes: sampling and scoring [5]. Sampling refers to the capacity to search an active site on a protein, macromolecule or, in this case, affinity host.…”

Section: Docking Calculationsmentioning

confidence: 99%

“…Docking models use molecular force fields, which simulate interactions and potential energy between atoms. Force field parameters may be derived from experiments, calculations from quantum mechanics, or both [5]. In addition to providing a numeric estimate for binding affinity, docking programs produce visualizations of how molecules interact.…”

Section: Introductionmentioning

confidence: 99%

Using QSARs for predictions in drug delivery

Rivera-Delgado

Xin

Recum

2019

Preprint

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Drug delivery research is an inherently empirical process, however high-throughput approaches could take advantage of understanding drug/material interactions such as from electrostatic, hydrophobic, or other non-covalent interactions between therapeutic molecules and a drug delivery polymer. Cyclodextrin polymers have been investigated for drug delivery specifically due to their capacity to exploit this affinity interaction to change the rate of drug release. Testing drug candidates; however, for affinity is time-consuming, making computational predictions more effective. One option, molecular "docking" programs, provide predictions of affinity, but lack reliability, as their accuracy with cyclodextrin remains unverified experimentally.Alternatively, quantitative structure-activity relationship models (QSARs), which analyze statistical relationships between molecular properties, appear more promising. Previously constructed QSARs for cyclodextrin are not publicly available, necessitating an openly accessible model. Around 600 experimental affinities between cyclodextrin and guest molecules were cleaned and imported from published research. The software PaDEL-Descriptor calculated over 1000 chemical descriptors for each molecule, which were then analyzed in R to create several QSARs with different statistical methods. These QSARs proved highly time efficient, calculating in minutes what docking programs would take hours to accomplish. Additionally, on test sets, QSARs reached R 2 values of around 0.7-0.8. The speed, accuracy, and accessibility of these QSARs improve evaluation of individual drugs and facilitate screening of large datasets for potential candidates in cyclodextrin affinity-based delivery systems. An app was built to rapidly access model predictions for end users using the "shiny" library in R. To demonstrate the usability for drug release planning, the QSAR predictions were coupled with a mechanistic model of diffusion within the app. Integrating new modules should provide an accessible approach to use other cheminformatic tools in the field of drug delivery.

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“…Calculation of physicochemical descriptors, as well as the prediction of ADME properties: Absorption, Distribution, Metabolism, Excretion and Toxicity, were determined using three different programs: SwissADME [26], admetSAR [27] and PASS online [28], which are used for drug discovery. The toxicity prediction was also carried out using PASS online [28], which estimates the predicted types of activity with the estimated probability for each type of activity "to be active" Pa and "to be inactive" Pi, which vary from zero to one [28].…”

Section: Similarity Analysis Of Drugsmentioning

confidence: 99%

Identification of flavone and its derivatives as potential inhibitors of transcriptional regulator LasR of Pseudomonasaeruginosausing virtual screening

Abelyan

Grabski

Tiratsuyan

2019

Preprint

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Antibiotic resistance is a global problem nowadays and in 2017 the World Health Organization published the list of bacteria for which treatment are urgently needed, where Pseudomonas aeruginosa is of critical priority. Current therapies lack efficacy because this organism creates biofilms conferring increased resistance to antibiotics and host immune responses. The strategy is to "not kill, but disarm" the pathogen and resistance will be developed slowly. It has been shown that LasI/LasR system is the main component of the quorum sensing system in P. aeruginosa. LasR is activated by the interaction with its native autoinducer. A lot flavones and their derivatives are used as antibacterial drug compounds. The purpose is to search compounds that will inhibit LasR. This leads to the inhibition of the synthesis of virulence factors thus the bacteria will be vulnerable and not virulent. We performed virtual screening using multiple docking programs for obtaining consensus predictions. The results of virtual screening suggest benzamides which are synthetical derivatives of flavones as potential inhibitors of transcriptional regulator LasR. These are consistent with recently published experimental data, which demonstrate the high antibacterial activity of benzamides. The compounds interact with the ligand binding domain of LasR with higher binding affinity than with DNA binding domain. Among the selected compounds, by conformational analysis, it was found that there are compounds that bind to the same amino acids of ligand binding domain as the native autoinducer. This could indicate the possibility of competitive interaction of these compounds. A number of compounds that bind to other conservative amino acids ligand binding domain have also been discovered, which will be of interest for further study. Selected compounds meet the criteria necessary for their consideration as drugs and can serve as a basis for conducting further in vitro / in vivo experiments. It could be used for the development of modern anti-infective therapy based on the quorum sensing system of P. aeruginosa.

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Accessible High-Throughput Virtual Screening Molecular Docking Software for Students and Educators

Cited by 98 publications

References 37 publications

Metabolomics and Cheminformatics Analysis of Antifungal Function of Plant Metabolites

Metabolomics and Cheminformatics Analysis of Antifungal Function of Plant Metabolites

Using QSARs for predictions in drug delivery

Identification of flavone and its derivatives as potential inhibitors of transcriptional regulator LasR of Pseudomonasaeruginosausing virtual screening

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