Ligand binding effects on the activation of the EGFR extracellular domain

2019 ◽  
Vol 21 (15) ◽  
pp. 8141-8151 ◽  
Author(s):  
Qiang Shao ◽  
Weiliang Zhu
Keyword(s):  
Drug Discovery ◽  
Ligand Binding ◽  
Md Simulations ◽  
Extracellular Domain ◽  
Activation Mechanism ◽  
Enhanced Sampling

Enhanced sampling MD simulations were run to understand the ligand binding effects on the activation mechanism of EGFR-ECD and accordingly provide valuable information for drug discovery targeting the EGFR.

scholarly journals A molecular dynamics investigation of CDK8/CycC and ligand binding: conformational flexibility and implication in drug discovery

2017 ◽  
Author(s):  
Wei Chen ◽  
Zhiye Tang ◽  
Tim Cholko ◽  
Chia-en A. Chang
Keyword(s):  
Molecular Dynamics ◽  
Drug Discovery ◽  
Ligand Binding ◽  
Md Simulations ◽  
Electrostatic Energy ◽  
Major Protein ◽  
Type I ◽  
Type Ii ◽  
Protein Motions ◽  
The Stability

AbstractThe activities of CDK8 with partner Cyclin C (CycC) are a common feature of many diseases, especially cancers. Here we report the study of dynamic behaviors and energy profiles of 13 CDK8/CycC systems, including the DMG-in and DMG-out conformations as well as 5 type I ligands and 5 type II ligands, with all-atom unbiased molecular dynamics (MD) simulations. We observed numerous regional motions within CDK8, which move in concert to form five major protein motions. The motion of the activation loop doesn’t appear to influence the binding of both types of ligands. Type I ligands remarkably reduce the motion of the C-terminal tail through the strong cation-π interaction between the ligands and ARG356, and type II ligands stabilize the αC helix by forming stable hydrogen bonds with GLU66. The MD calculations also confirmed the importance of CycC to the stability of the CDK8 system as well as the ligand binding. The MMPB/SA results show that van der Waals interaction is the main driving force for the binding of both types of ligands, but electrostatic energy and entropy penalty plays important roles in the binding of type II ligands. The volume analysis results indicate that the induced fitting theory applies in the binding of type I ligands. These results would help to improve the affinities of the existing ligands. Our MD work is complementary to crystal structures and may have implications in the development of new CDK8 inhibitors as well as in the field of drug discovery.

scholarly journals Pharmacological Characterisation of Novel Adenosine Receptor A3R Antagonists

2019 ◽  
Author(s):  
Kerry Barkan ◽  
Panagiotis Lagarias ◽  
Margarita Stampelou ◽  
Dimitrios Stamatis ◽  
Sam Hoare ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Ligand Binding ◽  
Adenosine Receptor ◽  
Md Simulations ◽  
The Body ◽  
Thiazole Ring ◽  
List Type ◽  
Binding Studies ◽  
Subtype Selectivity ◽  
Fluorescent Ligand

SummaryBackground and PurposeThe adenosine A3 receptor (A3R) belongs to a family of four adenosine receptor (AR) subtypes which all play distinct roles throughout the body. A3R antagonists have been described as potential treatments for numerous diseases including asthma. Given the similarity between ARs orthosteric binding sites, obtaining highly selective antagonists is a challenging but critical task.Experimental approach39 potential A3R, antagonists were screened using agonist-induced inhibition of cAMP. Positive hits were assessed for AR subtype selectivity through cAMP accumulation assays. The antagonist affinity was determined using Schild analysis (pA2 values) and fluorescent ligand binding. Further, a likely binding pose of the most potent antagonist (K18) was determined through molecular dynamic (MD) simulations and consistent calculated binding free energy differences between K18 and congeners, using a homology model of A3R, combined with mutagenesis studies.Key ResultsWe demonstrate that K18, which contains a 3-(dichlorophenyl)-isoxazole group connected through carbonyloxycarboximidamide fragment with a 1,3-thiazole ring, is a specific A3R (<1 µM) competitive antagonist. Structure-activity relationship investigations revealed that loss of the 3-(dichlorophenyl)-isoxazole group significantly attenuated K18 antagonistic potency. Mutagenic studies supported by MD simulations identified the residues important for binding in the A3R orthosteric site. Finally, we introduce a model that enables estimates of the equilibrium binding affinity for rapidly disassociating compounds from real-time fluorescent ligand-binding studies.Conclusions and ImplicationsThese results demonstrate the pharmacological characterisation of a selective competitive A3R antagonist and the description of its orthosteric binding mode. Our findings may provide new insight for drug discovery.What is already knownThe search for AR subtype specific compounds often leads to ones with multiple subtype bindingWhat this study addsThis study demonstrates the pharmacological characterisation of a selective competitive A3R antagonistMD simulations identified the residues important for binding in the A3R orthosteric siteClinical significanceThis study offers insight into A3R antagonists that may provide new opportunities for drug discovery

Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes Using Nonequilibrium Candidate Monte Carlo

2017 ◽  
Author(s):  
Samuel Gill ◽  
Nathan M. Lim ◽  
Patrick Grinaway ◽  
Ariën S. Rustenburg ◽  
Josh Fass ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Ligand Binding ◽  
Binding Mode ◽  
Free Energy Calculations ◽  
Dynamics Simulation ◽  
Binding Modes ◽  
Enhanced Sampling ◽  
Recent Success ◽  
Multiple Binding ◽  
Proper Sampling

<div>Accurately predicting protein-ligand binding is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid fragments. That is, we focus on computing the dominant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a receptor, and the populations of the multiple binding modes which may be relevant. This problem is important in its own right, but is even more timely given the recent success of alchemical free energy calculations. Alchemical calculations are increasingly used to predict binding free energies of ligands to receptors. However, the accuracy of these calculations is dependent on proper sampling of the relevant ligand binding modes. Unfortunately, ligand binding modes may often be uncertain, hard to predict, and/or slow to interconvert on simulation timescales, so proper sampling with current techniques can require prohibitively long simulations. We need new methods which dramatically improve sampling of ligand binding modes. Here, we develop and apply a nonequilibrium candidate Monte Carlo (NCMC) method to improve sampling of ligand binding modes.</div><div><br></div><div>In this technique the ligand is rotated and subsequently allowed to relax in its new position through alchemical perturbation before accepting or rejecting the rotation and relaxation as a nonequilibrium Monte Carlo move. When applied to a T4 lysozyme model binding system, this NCMC method shows over two orders of magnitude improvement in binding mode sampling efficiency compared to a brute force molecular dynamics simulation. This is a first step towards applying this methodology to pharmaceutically relevant binding of fragments and, eventually, drug-like molecules. We are making this approach available via our new Binding Modes of Ligands using Enhanced Sampling (BLUES) package which is freely available on GitHub.</div>

Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes Using Nonequilibrium Candidate Monte Carlo

2018 ◽  
Author(s):  
Samuel Gill ◽  
Nathan M. Lim ◽  
Patrick Grinaway ◽  
Ariën S. Rustenburg ◽  
Josh Fass ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Ligand Binding ◽  
Binding Mode ◽  
Free Energy Calculations ◽  
Dynamics Simulation ◽  
Binding Modes ◽  
Enhanced Sampling ◽  
Recent Success ◽  
Multiple Binding ◽  
Proper Sampling

<div>Accurately predicting protein-ligand binding is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid fragments. That is, we focus on computing the dominant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a receptor, and the populations of the multiple binding modes which may be relevant. This problem is important in its own right, but is even more timely given the recent success of alchemical free energy calculations. Alchemical calculations are increasingly used to predict binding free energies of ligands to receptors. However, the accuracy of these calculations is dependent on proper sampling of the relevant ligand binding modes. Unfortunately, ligand binding modes may often be uncertain, hard to predict, and/or slow to interconvert on simulation timescales, so proper sampling with current techniques can require prohibitively long simulations. We need new methods which dramatically improve sampling of ligand binding modes. Here, we develop and apply a nonequilibrium candidate Monte Carlo (NCMC) method to improve sampling of ligand binding modes.</div><div><br></div><div>In this technique the ligand is rotated and subsequently allowed to relax in its new position through alchemical perturbation before accepting or rejecting the rotation and relaxation as a nonequilibrium Monte Carlo move. When applied to a T4 lysozyme model binding system, this NCMC method shows over two orders of magnitude improvement in binding mode sampling efficiency compared to a brute force molecular dynamics simulation. This is a first step towards applying this methodology to pharmaceutically relevant binding of fragments and, eventually, drug-like molecules. We are making this approach available via our new Binding Modes of Ligands using Enhanced Sampling (BLUES) package which is freely available on GitHub.</div>

scholarly journals Protein-ligand free energies of binding from full-protein DFT calculations: convergence and choice of exchange-correlation functional

2021 ◽  
Author(s):  
Lennart Gundelach ◽  
Christofer S Tautermann ◽  
Thomas Fox ◽  
Chris-Kriton Skylaris
Keyword(s):  
Drug Discovery ◽  
Ligand Binding ◽  
Dft Calculations ◽  
Quantum Mechanical ◽  
Free Energies ◽  
Ligand Interaction ◽  
Exchange Correlation ◽  
Ligand Free ◽  
Protein Ligand Interaction ◽  
Binding Free Energies

The accurate prediction of protein-ligand binding free energies with tractable computational methods has the potential to revolutionize drug discovery. Modeling the protein-ligand interaction at a quantum mechanical level, instead of...

scholarly journals Genetic deletion of platelet glycoprotein Ib alpha but not its extracellular domain protects from atherosclerosis

2014 ◽  
Vol 112 (12) ◽  
pp. 1252-1263 ◽  
Author(s):  
Ekaterina Koltsova ◽  
Prithu Sundd ◽  
Alessandro Zarpellon ◽  
Hui Ouyang ◽  
Zbigniew Mikulski ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Ligand Binding ◽  
Myeloid Cells ◽  
Blood Platelet ◽  
Extracellular Domain ◽  
Platelet Glycoprotein ◽  
Blood Monocytes ◽  
Chemokine Production ◽  
Atherosclerosis Development ◽  
Microfluidic Chambers

SummaryThe pathogenesis of atherosclerosis involves the interplay of haematopoietic, stromal and endothelial cells. Platelet interactions with endothelium and leukocytes are pivotal for atherosclerosis promotion. Glycoprotein (GP) Ibα is the ligand-binding subunit of the platelet GPIb-IX-V receptor complex; its deficiency causes the Bernard-Soulier syndrome (BSS), characterised by absent platelet GPIb-IX-V, macrothrombocytopenia and bleeding. We designed this study to determine the role of platelet GPIbα in the pathogenesis of atherosclerosis using two unique knockout models. Ldlr-/- mice were reconstituted with wild-type (wt), GPIbα-/- (lacks GPIbα) or chimeric IL-4R/GPIbα-Tg (lacks GPIbα extracellular domain) bone marrow and assayed for atherosclerosis development after feeding with pro-atherogenic “western diet”. Here, we report that Ldlr-/- mice reconstituted with GPIbα-/- bone marrow developed less atherosclerosis compared to wt controls; accompanied by augmented accumulation of pro-inflammatory CD11b+ and CD11c+ myeloid cells, reduced oxLDL uptake and decreased TNF and IL 12p35 gene expression in the aortas. Flow cytometry and live cell imaging in whole blood-perfused microfluidic chambers revealed reduced platelet-monocyte aggregates in GPIbα-/- mice, which resulted in decreased monocyte activation. Interestingly, Ldlr -/- mice reconstituted with IL-4R/GPIbα-Tg bone marrow, producing less abnormal platelets, showed atherosclerotic lesions similar to wt mice. Platelet interaction with blood monocytes and accumulation of myeloid cells in the aortas were also essentially unaltered. Moreover, only complete GPIbα ablation altered platelet microparticles and CCL5 chemokine production. Thus, atherosclerosis reduction in mice lacking GPIbα may not result from the defective GPIbα-ligand binding, but more likely is a consequence of functional defects of GPIbα-/- platelets and reduced blood platelet counts.

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