scholarly journals PyVOL: a PyMOL plugin for visualization, comparison, and volume calculation of drug-binding sites

2019 ◽  
Author(s):  
Ryan H.B. Smith ◽  
Arvin C. Dar ◽  
Avner Schlessinger
Keyword(s):  
Binding Pocket ◽  
Drug Binding ◽  
Identification Algorithm ◽  
Volume Determination ◽  
Volume Calculation ◽  
User Input ◽  
Binding Pockets ◽  
Drug Binding Sites ◽  
Python Package ◽  
Pymol Plugin

AbstractMotivationBinding pocket volumes are a simple yet important predictor of small molecule binding; however, generating visualizations of pocket topology and performing meaningful volume comparisons can be difficult with available tools. Current programs for accurate volume determination rely on extensive user input to define bulk solvent boundaries and to partition cavities into subpockets, increasing inter-user variability in measurements as well as time demands.ResultsWe developed PyVOL, a python package with a PyMOL interface and GUI, to visualize, to characterize, and to compare binding pockets. PyVOL’s pocket identification algorithm is designed to maximize reproducibility through minimization of user-provided parameters, avoidance of grid-based methods, and automated subpocket identification. This approach permits efficient, scalable volume calculations.AvailabilityPyVOL is released under the MIT License. Source code and documentation are available through github (https://github.com/schlessingerlab/pyvol/) with distribution through PyPI (bio-pyvol)[email protected], [email protected]

scholarly journals Phylogenetic Sequence Variations in Bacterial rRNA Affect Species-Specific Susceptibility to Drugs Targeting Protein Synthesis

2011 ◽  
Vol 55 (9) ◽  
pp. 4096-4102 ◽  
Author(s):  
Subramanian Akshay ◽  
Mihai Bertea ◽  
Sven N. Hobbie ◽  
Björn Oettinghaus ◽  
Dimitri Shcherbakov ◽  
...  
Keyword(s):  
Binding Pocket ◽  
Drug Susceptibility ◽  
Drug Binding ◽  
23S Rrna ◽  
Content Type ◽  
Sequence Variations ◽  
Binding Pockets ◽  
Species Specific ◽  
Peptidyltransferase Center ◽  
A Site

ABSTRACTAntibiotics targeting the bacterial ribosome typically bind to highly conserved rRNA regions with only minor phylogenetic sequence variations. It is unclear whether these sequence variations affect antibiotic susceptibility or resistance development. To address this question, we have investigated the drug binding pockets of aminoglycosides and macrolides/ketolides. The binding site of aminoglycosides is located within helix 44 of the 16S rRNA (A site); macrolides/ketolides bind to domain V of the 23S rRNA (peptidyltransferase center). We have used mutagenesis of rRNA sequences inMycobacterium smegmatisribosomes to reconstruct the different bacterial drug binding sites and to study the effects of rRNA sequence variations on drug activity. Our results provide a rationale for differences in species-specific drug susceptibility patterns and species-specific resistance phenotypes associated with mutational alterations in the drug binding pocket.

scholarly journals Finding Druggable Sites in Proteins using TACTICS

2021 ◽  
Author(s):  
Daniel J. Evans ◽  
Remy A. Yovanno ◽  
Sanim Rahman ◽  
David W. Cao ◽  
Morgan Q. Beckett ◽  
...  
Keyword(s):  
Binding Sites ◽  
Learning Algorithm ◽  
Drug Binding ◽  
Molecular Structures ◽  
Dynamics Simulation ◽  
Conformational Heterogeneity ◽  
Main Protease ◽  
Binding Pockets ◽  
Drug Binding Sites ◽  
Fragment Docking

AbstractStructure-based drug discovery efforts require knowledge of where drug-binding sites are located on target proteins. To address the challenge of finding druggable sites, we developed a machine-learning algorithm called TACTICS (Trajectory-based Analysis of Conformations To Identify Cryptic Sites), which uses an ensemble of molecular structures (such as molecular dynamics simulation data) as input. First, TACTICS uses k-means clustering to select a small number of conformations that represent the overall conformational heterogeneity of the data. Then, TACTICS uses a random forest model to identify potentially bindable residues in each selected conformation, based on protein motion and geometry. Lastly, residues in possible binding pockets are scored using fragment docking. As proof-of-principle, TACTICS was applied to the analysis of simulations of the SARS-CoV-2 main protease and methyltransferase and the Yersinia pestis aryl carrier protein. Our approach recapitulates known small-molecule binding sites and predicts the locations of sites not previously observed in experimentally determined structures. The TACTICS code is available at https://github.com/Albert-Lau-Lab/tactics_protein_analysis.

scholarly journals A survey of the kinome pharmacopeia reveals multiple scaffolds and targets for the development of novel anthelmintics

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jessica Knox ◽  
Nicolas Joly ◽  
Edmond M. Linossi ◽  
José A. Carmona-Negrón ◽  
Natalia Jura ◽  
...  
Keyword(s):  
Caenorhabditis Elegans ◽  
Developmental Delay ◽  
Small Molecule ◽  
Parasitic Nematode ◽  
Kinase Inhibitor ◽  
Binding Pocket ◽  
Drug Binding ◽  
Nematode Infection ◽  
Selective Inhibitors ◽  
C Elegans

AbstractOver one billion people are currently infected with a parasitic nematode. Symptoms can include anemia, malnutrition, developmental delay, and in severe cases, death. Resistance is emerging to the anthelmintics currently used to treat nematode infection, prompting the need to develop new anthelmintics. Towards this end, we identified a set of kinases that may be targeted in a nematode-selective manner. We first screened 2040 inhibitors of vertebrate kinases for those that impair the model nematode Caenorhabditis elegans. By determining whether the terminal phenotype induced by each kinase inhibitor matched that of the predicted target mutant in C. elegans, we identified 17 druggable nematode kinase targets. Of these, we found that nematode EGFR, MEK1, and PLK1 kinases have diverged from vertebrates within their drug-binding pocket. For each of these targets, we identified small molecule scaffolds that may be further modified to develop nematode-selective inhibitors. Nematode EGFR, MEK1, and PLK1 therefore represent key targets for the development of new anthelmintic medicines.

scholarly journals Structural basis for subtype-specific inhibition of the P2X7 receptor

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Akira Karasawa ◽  
Toshimitsu Kawate
Keyword(s):  
P2x7 Receptor ◽  
Hydrophobic Interactions ◽  
Binding Pocket ◽  
Drug Binding ◽  
Structural Basis ◽  
Atp Binding ◽  
Allosteric Site ◽  
Channel Opening ◽  
A Site ◽  
Novel Drug

The P2X7 receptor is a non-selective cation channel activated by extracellular adenosine triphosphate (ATP). Chronic activation of P2X7 underlies many health problems such as pathologic pain, yet we lack effective antagonists due to poorly understood mechanisms of inhibition. Here we present crystal structures of a mammalian P2X7 receptor complexed with five structurally-unrelated antagonists. Unexpectedly, these drugs all bind to an allosteric site distinct from the ATP-binding pocket in a groove formed between two neighboring subunits. This novel drug-binding pocket accommodates a diversity of small molecules mainly through hydrophobic interactions. Functional assays propose that these compounds allosterically prevent narrowing of the drug-binding pocket and the turret-like architecture during channel opening, which is consistent with a site of action distal to the ATP-binding pocket. These novel mechanistic insights will facilitate the development of P2X7-specific drugs for treating human diseases.

scholarly journals First person – Jia Yu and Pei-Ju Liao

2021 ◽  
Vol 134 (24) ◽  
Keyword(s):  
Protein Interactions ◽  
Structural Model ◽  
Early Career ◽  
Drug Binding ◽  
First Person ◽  
Protein Protein Interactions ◽  
Early Career Researchers ◽  
Complex Simulation ◽  
Drug Binding Sites ◽  
Selection Of

ABSTRACT First Person is a series of interviews with the first authors of a selection of papers published in Journal of Cell Science, helping early-career researchers promote themselves alongside their papers. Jia Yu and Pei-Ju Liao are co-first authors on ‘ Structural model of human PORCN illuminates disease-associated variants and drug-binding sites’, published in JCS. Jia is a senior postdoc in the lab of David Virshup at Duke-NUS Medical School, Singapore, investigating Wnt secretion and signalling; in particular, how Wnt trafficking and secretion is regulated by two integral membrane proteins, porcupine and WLS. Pei-Ju is a research assistant in the same lab, investigating protein–protein interactions in the systems biology of signalling pathways using protein structure modelling and protein complex simulation.

scholarly journals Systematic exploration of multiple drug binding sites

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Mónika Bálint ◽  
Norbert Jeszenői ◽  
István Horváth ◽  
David van der Spoel ◽  
Csaba Hetényi
Keyword(s):  
Binding Sites ◽  
Drug Binding ◽  
Multiple Drug ◽  
Systematic Exploration ◽  
Drug Binding Sites

scholarly journals Footprinting studies on the effect of echinomycin on the structure of a bent DNA fragment

1990 ◽  
Vol 269 (1) ◽  
pp. 217-221 ◽  
Author(s):  
K R Fox ◽  
E Kentebe
Keyword(s):  
Binding Sites ◽  
Dna Structure ◽  
Drug Binding ◽  
Micrococcal Nuclease ◽  
Kinetoplast Dna ◽  
Bent Dna ◽  
Diethyl Pyrocarbonate ◽  
Drug Binding Sites ◽  
Dna Fragment

The interaction of echinomycin with a kinetoplast DNA fragment which contains phased runs of adenine residues has been examined by various footprinting techniques. DNAase I footprinting confirms that all drug-binding sites contain the dinucleotide CpG. However, not all such sequences are protected. Three sites, each of which is located between two adenine tracks in the sequence GCGA, are not protected from DNAase I attack. Enhanced cleavage by DNAase I, DNAase II and micrococcal nuclease is observed in regions surrounding drug-binding sites. The results suggest that echinomycin alters the conformation of the AT tracks, making them more like an average DNA structure. Echinomycin renders adenine residues in the sequence CGA hyper-reactive to diethyl pyrocarbonate.

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