scholarly journals Hidden electrostatic basis of dynamic allostery in a PDZ domain

2017 ◽  
Vol 114 (29) ◽  
pp. E5825-E5834 ◽  
Author(s):  
Amit Kumawat ◽  
Suman Chakrabarty
Keyword(s):  
Ligand Binding ◽  
Conformational Changes ◽  
Electrostatic Interactions ◽  
Pdz Domain ◽  
Allosteric Modulation ◽  
Side Chain ◽  
Salt Bridges ◽  
Population Shift ◽  
Domain Protein ◽  
Dynamics Simulations

Allosteric effect implies ligand binding at one site leading to structural and/or dynamical changes at a distant site. PDZ domains are classic examples of dynamic allostery without conformational changes, where distal side-chain dynamics is modulated on ligand binding and the origin has been attributed to entropic effects. In this work, we unearth the energetic basis of the observed dynamic allostery in a PDZ3 domain protein using molecular dynamics simulations. We demonstrate that electrostatic interaction provides a highly sensitive yardstick to probe the allosteric modulation in contrast to the traditionally used structure-based parameters. There is a significant population shift in the hydrogen-bonded network and salt bridges involving side chains on ligand binding. The ligand creates a local energetic perturbation that propagates in the form of dominolike changes in interresidue interaction pattern. There are significant changes in the nature of specific interactions (nonpolar/polar) between interresidue contacts and accompanied side-chain reorientations that drive the major redistribution of energy. Interestingly, this internal redistribution and rewiring of side-chain interactions led to large cancellations resulting in small change in the overall enthalpy of the protein, thus making it difficult to detect experimentally. In contrast to the prevailing focus on the entropic or dynamic effects, we show that the internal redistribution and population shift in specific electrostatic interactions drive the allosteric modulation in the PDZ3 domain protein.

scholarly journals The intercalation of imidazoacridinones into DNA induces conformational changes in their side chain.

2000 ◽  
Vol 47 (1) ◽  
pp. 65-78 ◽  
Author(s):  
J Mazerski ◽  
K Muchewicz
Keyword(s):  
Conformational Changes ◽  
Ring System ◽  
Van Der Waals Interactions ◽  
Side Chain ◽  
Intercalation Complex ◽  
Highly Active ◽  
Antitumor Compounds ◽  
Chemical Constitution ◽  
Modelling Techniques ◽  
Dynamics Simulations

Imidazoacridinones (IAs) are a new group of highly active antitumor compounds. The intercalation of the IA molecule into DNA is the preliminary step in the mode of action of these compounds. There are no experimental data about the structure of an intercalation complex formed by imidazoacridinones. Therefore the design of new potentially better compounds of this group should employ the molecular modelling techniques. The results of molecular dynamics simulations performed for four IA analogues are presented. Each of the compounds was studied in two systems: i) in water, and ii) in the intercalation complex with dodecamer duplex d(GCGCGCGCGCGC)2. Significant differences in the conformation of the side chain in the two environments were observed for all studied IAs. These changes were induced by electrostatic as well as van der Waals interactions between the intercalator and DNA. Moreover, the results showed that the geometry of the intercalation complex depends on: i) the chemical constitution of the side chain, and ii) the substituent in position 8 of the ring system.

scholarly journals Collaborative Behavior of Urea and KI in Denaturing Protein Native Structure

2019 ◽  
Author(s):  
Qiang Shao ◽  
Jinan Wang ◽  
Weiliang Zhu
Keyword(s):  
Molecular Dynamics ◽  
Hydrogen Bonding ◽  
Structural Dynamics ◽  
Electrostatic Interactions ◽  
Side Chain ◽  
Mixed Solution ◽  
Native Structure ◽  
Indirect Influence ◽  
Collaborative Behavior ◽  
Dynamics Simulations

AbstractIn this work, the combined influence of urea and KI on protein native structure is quantitatively investigated through the comparative molecular dynamics simulations on the structural dynamics of a polypeptide of TRPZIP4 in a series of urea/KI mixed solutions (urea concentration: 4M, KI salt concentration: 0M-6M). The observed enhanced denaturing ability of urea/KI mixture can be explained by direct interactions of urea/K+/water towards protein (electrostatic and vdW interactions from urea and electrostatic interactions from K+ and water) and indirect influence of KI on the strengthened interaction of urea towards protein backbone and side-chain. The latter indirect influence is fulfilled through the weakening of hydrogen bonding network among urea and water by the appearance of K+–water and I—urea interactions. As a result, the denaturing ability enhancement of urea and KI mixed solution is induced by the collaborative behavior of urea and KI salt.

Molecular Basis Explanation of Imatinib Resistance of Bcr-Abl Due to T315I and P-Loop Mutations from Molecular Dynamics Simulations.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 2917-2917
Author(s):  
Tai-Sung Lee ◽  
Steven Potts ◽  
Hagop Kantarjian ◽  
Jorge Cortes ◽  
Francis Giles ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Conformational Changes ◽  
Electrostatic Interactions ◽  
Large Scale ◽  
Resistance Mechanism ◽  
Md Simulations ◽  
Resistance Mechanisms ◽  
Static Structure ◽  
Imatinib Resistance ◽  
Dynamics Simulations

Abstract Molecular dynamics (MD) simulations on the complex of imatinib with the wild-type, T315I, and other 10 P-loop mutants of the tyrosine kinase Bcr-Abl have been performed to study the imatinib resistance mechanism at the atomic level. MD simulations show that large scale computational simulations could offer insight information that a static structure or simple homology modeling methods cannot provide for studying the Bcr-Abl imatinib resistance problem, especially in the case of conformational changes due to remote mutations. By utilizing the Molecular Mechanics/Poisson-Boltzmann surface area (MM-PBSA) techniques and analyzing the interactions between imatinib and individual residues, imatinib resistance mechanisms not previously thought have been revealed. Non-directly contacted P-loop mutations either unfavorably change the direct electrostatic interactions with imatinib, or cause the conformational changes influencing the contact energies between imatinib and other non-P-loop residues. We demonstrate that imatinib resistance of T315I mainly comes from the breakdown of the interactions between imatinib and E286 and M290, contradictory to previously suggested that the missing hydrogen bonding is the main contribution. We also demonstrate that except for the mutations of the direct contact residues, such as L248 and Y253, the unfavorable electrostatic interaction between P-loop and imatinib is the main reason for resistance for the P-loop mutations. Furthermore, in Y255H, protonation of the histidin is essential for rendering this mutation resistant to Gleevec. Our results demonstrate that MD is a powerful way to verify and predict clinical response or resistance to imatinib and other potential drugs.

scholarly journals Enhancing Sidechain Rotamer Sampling Using Non-Equilibrium Candidate Monte Carlo

2019 ◽  
Author(s):  
Kalistyn H. Burley ◽  
Samuel C. Gill ◽  
Nathan M. Lim ◽  
David Mobley
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Ligand Binding ◽  
Electrostatic Interactions ◽  
Molecular Simulations ◽  
Adequate Sampling ◽  
Binding Pockets ◽  
Sidechain Rotamers ◽  
Dynamics Simulations ◽  
Non Equilibrium

<div>Molecular simulations are a valuable tool for studying biomolecular motions and thermodynamics. However, such motions can be slow compared to simulation timescales, yet critical. Specifically, adequate sampling of sidechain motions in protein binding pockets proves crucial for obtaining accurate estimates of ligand binding free energies from molecular simulations. The timescale of sidechain rotamer flips can range from a few ps to several hundred ns or longer, particularly in crowded environments like the interior of proteins. Here, we apply a mixed non-equilibrium candidate Monte Carlo (NCMC)/molecular dynamics (MD) method to enhance sampling of sidechain rotamers. The NCMC portion of our method applies a switching protocol wherein the steric and electrostatic interactions between target sidechain atoms and the surrounding environment are cycled off and then back on during the course of a move proposal. Between NCMC move proposals, simulation of the system continues via traditional molecular dynamics. Here, we first validate this approach on a simple, solvated valine-alanine dipeptide system and then apply it to a well-studied model ligand binding site in T4 lysozyme L99A. We compute the rate of rotamer transitions for a valine sidechain using our approach and compare it to that of traditional molecular dynamics simulations. Here, we show that our NCMC/MD method substantially enhances sidechain sampling, especially in systems where the torsional barrier to rotation is high (>10 kcal/mol). These barriers can be intrinsic torsional barriers or steric barriers imposed by the environment.</div><div>Overall, this may provide a promising strategy to selectively improve sidechain sampling in molecular simulations.</div>

scholarly journals Enhancing Sidechain Rotamer Sampling Using Non-Equilibrium Candidate Monte Carlo

2018 ◽  
Author(s):  
Kalistyn H. Burley ◽  
Samuel C. Gill ◽  
Nathan M. Lim ◽  
David Mobley
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Ligand Binding ◽  
Electrostatic Interactions ◽  
Molecular Simulations ◽  
Adequate Sampling ◽  
Binding Pockets ◽  
Sidechain Rotamers ◽  
Dynamics Simulations ◽  
Non Equilibrium

<div>Molecular simulations are a valuable tool for studying biomolecular motions and thermodynamics. However, such motions can be slow compared to simulation timescales, yet critical. Specifically, adequate sampling of sidechain motions in protein binding pockets proves crucial for obtaining accurate estimates of ligand binding free energies from molecular simulations. The timescale of sidechain rotamer flips can range from a few ps to several hundred ns or longer, particularly in crowded environments like the interior of proteins. Here, we apply a mixed non-equilibrium candidate Monte Carlo (NCMC)/molecular dynamics (MD) method to enhance sampling of sidechain rotamers. The NCMC portion of our method applies a switching protocol wherein the steric and electrostatic interactions between target sidechain atoms and the surrounding environment are cycled off and then back on during the course of a move proposal. Between NCMC move proposals, simulation of the system continues via traditional molecular dynamics. Here, we first validate this approach on a simple, solvated valine-alanine dipeptide system and then apply it to a well-studied model ligand binding site in T4 lysozyme L99A. We compute the rate of rotamer transitions for a valine sidechain using our approach and compare it to that of traditional molecular dynamics simulations. Here, we show that our NCMC/MD method substantially enhances sidechain sampling, especially in systems where the torsional barrier to rotation is high (>10 kcal/mol). These barriers can be intrinsic torsional barriers or steric barriers imposed by the environment.</div><div>Overall, this may provide a promising strategy to selectively improve sidechain sampling in molecular simulations.</div>

scholarly journals HIV-1 Env gp41 Transmembrane Domain Dynamics are Modulated by Lipid, Water, and Ion Interactions

2018 ◽  
Author(s):  
L.R. Hollingsworth ◽  
J.A. Lemkul ◽  
D.R. Bevan ◽  
A.M. Brown
Keyword(s):  
Host Cell ◽  
Conformational Changes ◽  
Electrostatic Interactions ◽  
Transmembrane Domain ◽  
Chloride Ions ◽  
Viral Envelope ◽  
Membrane Properties ◽  
Viral Fusion ◽  
Network Of Hydrogen Bonds ◽  
Dynamics Simulations

AbstractThe gp41 transmembrane domain (TMD) of the envelope glycoprotein (Env) of the human immunodeficiency virus (HIV) modulates the conformation of the viral envelope spike, the only druggable target on the surface of the virion. Understanding of TMD dynamics is needed to better probe and target Env with small molecule and antibody therapies. However, little is known about TMD dynamics due to difficulties in describing native membrane properties. Here, we performed atomistic molecular dynamics simulations of a trimeric, prefusion TMD in a model, asymmetric viral membrane that mimics the native viral envelope. We found that water and chloride ions permeated the membrane and interacted with the highly conserved arginine bundle, (R696)3, at the center of the membrane and influenced TMD stability by creating a network of hydrogen bonds and electrostatic interactions. We propose that this (R696)3- water - anion network plays an important role in viral fusion with the host cell by modulating protein conformational changes within the membrane. Additionally, R683 and R707 at the exofacial and cytofacial membrane-water interfaces, respectively, are anchored in the lipid headgroup region and serve as a junction point for stabilization of the termini. The membrane thins as a result of the tilting of the TMD trimer, with nearby lipids increasing in volume, leading to an entropic driving force for TMD conformational change. These results provide additional detail and perspective on the influence of certain lipid types on TMD dynamics and rationale for targeting key residues of the TMD for therapeutic design. These insights into the molecular details of TMD membrane anchoring will build towards a greater understanding of dynamics that lead to viral fusion with the host cell.

scholarly journals Molecular insights from conformational ensembles via machine learning

2019 ◽  
Author(s):  
O. Fleetwood ◽  
M.A. Kasimova ◽  
A.M. Westerlund ◽  
L. Delemotte
Keyword(s):  
Machine Learning ◽  
Ligand Binding ◽  
Ion Channel ◽  
Conformational Changes ◽  
Molecular Simulations ◽  
Principal Component ◽  
Voltage Sensitivity ◽  
Learning Tools ◽  
Biomolecular Systems ◽  
Dynamics Simulations

ABSTRACTBiomolecular simulations are intrinsically high dimensional and generate noisy datasets of ever increasing size. Extracting important features in the data is crucial for understanding the biophysical properties of molecular processes, but remains a big challenge. Machine learning (ML) provides powerful dimensionality reduction tools. However, such methods are often criticized to resemble black boxes with limited human-interpretable insight.We use methods from supervised and unsupervised ML to efficiently create interpretable maps of important features from molecular simulations. We benchmark the performance of several methods including neural networks, random forests and principal component analysis, using a toy model with properties reminiscent of macromolecular behavior. We then analyze three diverse biological processes: conformational changes within the soluble protein calmodulin, ligand binding to a G protein-coupled receptor and activation of an ion channel voltage-sensor domain, unravelling features critical for signal transduction, ligand binding and voltage sensing. This work demonstrates the usefulness of ML in understanding biomolecular states and demystifying complex simulations.STATEMENT OF SIGNIFICANCEUnderstanding how biomolecules function requires resolving the ensemble of structures they visit. Molecular dynamics simulations compute these ensembles and generate large amounts of data that can be noisy and need to be condensed for human interpretation. Machine learning methods are designed to process large amounts of data, but are often criticized for their black-box nature and have historically been modestly used in the analysis of biomolecular systems. We demonstrate how machine learning tools can provide an interpretable overview of important features in a simulation dataset. We develop a protocol to quickly perform data-driven analysis of molecular simulations. This protocol is applied to identify the molecular basis of ligand binding to a receptor and of voltage sensitivity of an ion channel.

scholarly journals Factors Underlying Asymmetric Dynamics of Disaggregase and Microtubule Severing AAA+ Machines

2020 ◽  
Author(s):  
Mangesh Damre ◽  
Ashan Dayananda ◽  
Rohith Anand Varikoti ◽  
George Stan ◽  
Ruxandra I. Dima
Keyword(s):  
Conformational Changes ◽  
Large Scale ◽  
Relaxation Times ◽  
Observation Time ◽  
Salt Bridges ◽  
Relaxation Dynamics ◽  
Microtubule Severing ◽  
Substrate Peptide ◽  
Centers Of Mass ◽  
Dynamics Simulations

AbstractDisaggregation and microtubule-severing nanomachines from the AAA+ (ATPases associated with various cellular activities) superfamily assemble into ring–shaped hexamers that enable protein remodeling by coupling large–scale conformational changes with application of mechanical forces within a central pore by loops protruding within the pore. We probed these motions and intra-ring interactions that support them by performing extensive explicit solvent molecular dynamics simulations of single-ring severing proteins and the double-ring disaggregase ClpB. Simulations reveal that dynamic stability of hexamers of severing proteins and of the nucleotide binding domain 1 (NBD1) ring of ClpB, which belong to the same clade, involves a network of salt bridges that connect conserved motifs of central PL1 loops of the hexamer. Clustering analysis of ClpB highlights correlated motions of domains of neighboring protomers supporting strong inter-protomer collaboration. Severing proteins have weaker inter-protomer coupling and stronger intra-protomer stabilization through salt bridges formed between PL2 and PL3 loops. Distinct mechanisms are identified in the NBD2 ring of ClpB involving weaker inter–protomer coupling through salt bridges formed by non–canonical loops and stronger intra–protomer coupling. Pore width fluctuations associated with the PL1 constriction in the spiral states, in the presence of a substrate peptide, highlight stark differences between narrowing of channels of severing proteins and widening of the NBD1 ring of ClpB. This indicates divergent substrate processing mechanisms of remodeling and translocation by ClpB and substrate tail-end gripping and possible wedging on microtubule lattice by severing enzymes. Relaxation dynamics of the distance between the PL1 loops and the centers of mass of protomers reveals observation-time-dependent dynamics, leading to predicted relaxation times of tens of microseconds on millisecond experimental timescales. For ClpB the predicted relaxation time is in excellent agreement with the extracted time from smFRET experiments.

Molecular Dynamics Simulations of HLA-CW4-Β2M-KIR2DL1 Protein and Homology Modeling of a Complex Associated with Psoriasis Disease (HLA-CW6-Β 2M-KIR2DS1)

2021 ◽  
Author(s):  
Mansour H Almatarneh ◽  
Ahmad M Alqaisi ◽  
Enas K Ibrahim ◽  
Ghada G Kayed ◽  
Joshua W Hollett
Keyword(s):  
Molecular Dynamics ◽  
Conformational Changes ◽  
Complex Structure ◽  
3D Structure ◽  
Md Simulations ◽  
Salt Bridges ◽  
Small Peptide ◽  
Β2 Microglobulin ◽  
Dynamics Simulations ◽  
The Right

Molecular dynamics (MD) simulation was used to study the interactions of two immune proteins of HLA-Cw4-β2m-KIR2DL1 complex with small peptide QYDDAVYKL (nine amino acids) in an aqueous solution. This study aims to gain a detailed information about the conformational changes and the dynamics of the complex. The right parameters and force field for performing the MD simulations that was needed to calibrate the complex structure were determined. The non-bonded interactions (Electrostatic and van der Waals contributions), H-bond formation, and salt bridges between the ligand HLA-Cw4 and the receptor KIR2DL1 were estimated using the obtained MD trajectories. The buried surface area due to binding was calculated to get insight into the causes of specificity of receptor to ligand and explains mutations experiment. The study concluded that β2-microglobulin, one part of the complex, is not directly interacting with the peptide at the groove; therefore, it could be neglected from simulation. Our results showed that β2-microglobulin does not have any significant effect on the dynamics of the 3D-structure of the complex. This project will help in understanding to optimize candidate drug design, a small peptide that disrupts the interaction, for the optimal biological effect.

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