scholarly journals CANDOCK: Chemical Atomic Network-Based Hierarchical Flexible Docking Algorithm Using Generalized Statistical Potentials

2020 ◽  
Vol 60 (3) ◽  
pp. 1509-1527 ◽  
Author(s):  
Jonathan Fine ◽  
Janez Konc ◽  
Ram Samudrala ◽  
Gaurav Chopra
Keyword(s):  
Flexible Docking ◽  
Statistical Potentials ◽  
Docking Algorithm ◽  
Flexible Docking Algorithm

scholarly journals CANDOCK: Chemical Atomic Network Based Hierarchical Flexible Docking Algorithm Using Generalized Statistical Potentials

2018 ◽  
Author(s):  
Jonathan Fine ◽  
Janez Konc ◽  
Ram Samudralal ◽  
Gaurav Chopra
Keyword(s):  
Metal Ions ◽  
Binding Pocket ◽  
Binding Mode ◽  
Potential Functions ◽  
Chemical Environment ◽  
Conformational Space ◽  
Binding Affinities ◽  
Flexible Docking ◽  
Docking Algorithm ◽  
Essential Components

Small molecule docking has proven to be invaluable for drug design and discovery. However, existing docking methods have several limitations, such as, ignoring interactions with essential components in the chemical environment of the binding pocket (e.g. cofactors, metal-ions, etc.), incomplete sampling of chemically relevant ligand conformational space, and they are unable to consistently correlate docking scores of the best binding pose with experimental binding affinities. We present CANDOCK, a novel docking algorithm that utilizes a hierarchical approach to reconstruct ligands from an atomic grid using graph theory and generalized statistical potential functions to sample chemical relevant ligand conformations. Our algorithm accounts for protein flexibility, solvent, metal ions and cofactors interactions in the binding pocket that are traditionally ignored by current methods. We evaluate the algorithm on the PDBbind and Astex proteins to show its ability to reproduce the binding mode of the ligands that is independent of the initial ligand conformation in these benchmarks. Finally, we identify the best selector and ranker potential functions, such that, the statistical score of best selected docked pose correlates with the experimental binding affinities of the ligands for any given protein target. Our results indicate that CANDOCK is a generalized flexible docking method that addresses several limitations of current docking methods by considering all interactions in the chemical environment of a binding pocket for correlating the best docked pose with biological activity.

scholarly journals CANDOCK: Chemical Atomic Network Based Hierarchical Flexible Docking Algorithm Using Generalized Statistical Potentials

2018 ◽  
Author(s):  
Jonathan Fine ◽  
Janez Konc ◽  
Ram Samudralal ◽  
Gaurav Chopra
Keyword(s):  
Metal Ions ◽  
Binding Pocket ◽  
Binding Mode ◽  
Potential Functions ◽  
Chemical Environment ◽  
Conformational Space ◽  
Binding Affinities ◽  
Flexible Docking ◽  
Docking Algorithm ◽  
Essential Components

Small molecule docking has proven to be invaluable for drug design and discovery. However, existing docking methods have several limitations, such as, ignoring interactions with essential components in the chemical environment of the binding pocket (e.g. cofactors, metal-ions, etc.), incomplete sampling of chemically relevant ligand conformational space, and they are unable to consistently correlate docking scores of the best binding pose with experimental binding affinities. We present CANDOCK, a novel docking algorithm that utilizes a hierarchical approach to reconstruct ligands from an atomic grid using graph theory and generalized statistical potential functions to sample chemical relevant ligand conformations. Our algorithm accounts for protein flexibility, solvent, metal ions and cofactors interactions in the binding pocket that are traditionally ignored by current methods. We evaluate the algorithm on the PDBbind and Astex proteins to show its ability to reproduce the binding mode of the ligands that is independent of the initial ligand conformation in these benchmarks. Finally, we identify the best selector and ranker potential functions, such that, the statistical score of best selected docked pose correlates with the experimental binding affinities of the ligands for any given protein target. Our results indicate that CANDOCK is a generalized flexible docking method that addresses several limitations of current docking methods by considering all interactions in the chemical environment of a binding pocket for correlating the best docked pose with biological activity.

scholarly journals CANDOCK: Chemical atomic network based hierarchical flexible docking algorithm using generalized statistical potentials

2018 ◽  
Author(s):  
Jonathan A Fine ◽  
Janez Konc ◽  
Ram Samudrala ◽  
Gaurav Chopra
Keyword(s):  
Metal Ions ◽  
Binding Pocket ◽  
Binding Mode ◽  
Potential Functions ◽  
Chemical Environment ◽  
Conformational Space ◽  
Binding Affinities ◽  
Flexible Docking ◽  
Docking Algorithm ◽  
Essential Components

Small molecule docking has proven to be invaluable for drug design and discovery. However, existing docking methods have several limitations, such as, improper treatment of the interactions of essential components in the chemical environment of the binding pocket (e.g. cofactors, metal-ions, etc.), incomplete sampling of chemically relevant ligand conformational space, and the inability to consistently correlate docking scores of the best binding pose with experimental binding affinities. We present CANDOCK, a novel docking algorithm that utilizes a hierarchical approach to reconstruct ligands from an atomic grid using graph theory and generalized statistical potential functions to sample biologically relevant ligand conformations. Our algorithm accounts for protein flexibility, solvent, metal ions and cofactors interactions in the binding pocket that are traditionally ignored by current methods. We evaluate the algorithm on the PDBbind and Astex proteins to show its ability to reproduce the binding mode of the ligands that is independent of the initial ligand conformation in these benchmarks. Finally, we identify the best selector and ranker potential functions, such that, the statistical score of best selected docked pose correlates with the experimental binding affinities of the ligands for any given protein target. Our results indicate that CANDOCK is a generalized flexible docking method that addresses several limitations of current docking methods by considering all interactions in the chemical environment of a binding pocket for correlating the best docked pose with biological activity.

scholarly journals Structural and functional insights into esterase-mediated macrolide resistance

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Michał Zieliński ◽  
Jaeok Park ◽  
Barry Sleno ◽  
Albert M. Berghuis
Keyword(s):  
Active Site ◽  
Pathogenic Bacteria ◽  
Catalytic Mechanism ◽  
Three Dimensional ◽  
Resistance Mechanisms ◽  
Docking Studies ◽  
Macrolide Resistance ◽  
Flexible Docking ◽  
Sequence Identity ◽  
Substrate Spectrum

AbstractMacrolides are a class of antibiotics widely used in both medicine and agriculture. Unsurprisingly, as a consequence of their exensive usage a plethora of resistance mechanisms have been encountered in pathogenic bacteria. One of these resistance mechanisms entails the enzymatic cleavage of the macrolides’ macrolactone ring by erythromycin esterases (Eres). The most frequently identified Ere enzyme is EreA, which confers resistance to the majority of clinically used macrolides. Despite the role Eres play in macrolide resistance, research into this family enzymes has been sparse. Here, we report the first three-dimensional structures of an erythromycin esterase, EreC. EreC is an extremely close homologue of EreA, displaying more than 90% sequence identity. Two structures of this enzyme, in conjunction with in silico flexible docking studies and previously reported mutagenesis data allowed for the proposal of a detailed catalytic mechanism for the Ere family of enzymes, labeling them as metal-independent hydrolases. Also presented are substrate spectrum assays for different members of the Ere family. The results from these assays together with an examination of residue conservation for the macrolide binding site in Eres, suggests two distinct active site archetypes within the Ere enzyme family.

scholarly journals Exploring aromatic cage flexibility of the histone methyllysine reader protein Spindlin1 and its impact on binding mode prediction: an in silico study

2021 ◽  
Author(s):  
Chiara Luise ◽  
Dina Robaa ◽  
Wolfgang Sippl
Keyword(s):  
Molecular Dynamic ◽  
In Silico ◽  
Binding Pocket ◽  
Binding Mode ◽  
Molecular Dynamic Simulations ◽  
Flexible Docking ◽  
Dynamic Simulations ◽  
Binding Mode Prediction ◽  
Aromatic Cage ◽  
The Right

AbstractSome of the main challenges faced in drug discovery are pocket flexibility and binding mode prediction. In this work, we explored the aromatic cage flexibility of the histone methyllysine reader protein Spindlin1 and its impact on binding mode prediction by means of in silico approaches. We first investigated the Spindlin1 aromatic cage plasticity by analyzing the available crystal structures and through molecular dynamic simulations. Then we assessed the ability of rigid docking and flexible docking to rightly reproduce the binding mode of a known ligand into Spindlin1, as an example of a reader protein displaying flexibility in the binding pocket. The ability of induced fit docking was further probed to test if the right ligand binding mode could be obtained through flexible docking regardless of the initial protein conformation. Finally, the stability of generated docking poses was verified by molecular dynamic simulations. Accurate binding mode prediction was obtained showing that the herein reported approach is a highly promising combination of in silico methods able to rightly predict the binding mode of small molecule ligands in flexible binding pockets, such as those observed in some reader proteins.

Fully Flexible Docking via Reaction-Coordinate-Independent Molecular Dynamics Simulations

2018 ◽  
Vol 58 (2) ◽  
pp. 490-500 ◽  
Author(s):  
Martina Bertazzo ◽  
Mattia Bernetti ◽  
Maurizio Recanatini ◽  
Matteo Masetti ◽  
Andrea Cavalli
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Reaction Coordinate ◽  
Flexible Docking ◽  
Dynamics Simulations

Combined Conformational Search and Finite-Difference Poisson?Boltzmann Approach for Flexible Docking

1994 ◽  
Vol 238 (3) ◽  
pp. 455-465 ◽  
Author(s):  
M. Zacharias ◽  
B.A. Luty ◽  
M.E. Davis ◽  
J.A. McCammon
Keyword(s):  
Finite Difference ◽  
Conformational Search ◽  
Flexible Docking ◽  
Poisson Boltzmann
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