A boosted unbiased molecular dynamics method for predicting ligands binding mechanisms: probing the binding pathway of dasatinib to Src-kinase

Farzin Sohraby; Mostafa Javaheri Moghadam; Masoud Aliyar; Hassan Aryapour

doi:10.1093/bioinformatics/btaa565

A boosted unbiased molecular dynamics method for predicting ligands binding mechanisms: Probing the binding pathway of dasatinib to Src-kinase

10.1101/650440 ◽

2019 ◽

Cited By ~ 1

Author(s):

Farzin Sohraby ◽

Mostafa Javaheri Moghadam ◽

Masoud Aliyar ◽

Hassan Aryapour

Keyword(s):

Molecular Dynamics ◽

Ligand Binding ◽

Molecular Dynamics Simulations ◽

Src Kinase ◽

Deep Understanding ◽

Binding Mode ◽

Dynamics Simulation ◽

Dynamics Simulations ◽

Computational Resources ◽

Binding Mechanisms

AbstractSmall molecules such as metabolites and drugs play essential roles in biological processes and pharmaceutical industry. Knowing their interactions with biomacromolecular targets demands a deep understanding of binding mechanisms. Dozens of papers have suggested that discovering of the binding event by means of conventional unbiased molecular dynamics (MD) simulation urges considerable amount of computational resources, therefore, only one who holds a cluster or a supercomputer can afford such extensive simulations. Thus, many researchers who do not own such resources are reluctant to take the benefits of running unbiased molecular dynamics simulation, in full atomistic details, when studying a ligand binding pathway. Many researchers are impelled to be content with biased molecular dynamics simulations which seek its validation due to its intrinsic preconceived framework. In this work, we have presented a workable stratagem to encourage everyone to perform unbiased (unguided) molecular dynamics simulations, in this case a protein-ligand binding process, by typical desktop computers and so achieve valuable results in nanosecond time scale. Here, we have described a dynamical binding’s process of an anticancer drug, the dasatinib, to the c-Src kinase in full atomistic details for the first time, without applying any biasing force or potential which may lead the drug to artificial interactions with the protein. We have attained multiple independent binding events which occurred in the nano-second timescales, surprisingly as little as ∼30 ns. Both the protonated and deprotonated forms of the dasatinib reached the crystallographic binding mode without having any major intermediate state during induction.

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Nanoindentation simulations for large atomic systems : an analysis of molecular dynamics and bridged finite element - molecular dynamics methodologies

10.32920/ryerson.14660595 ◽

2021 ◽

Author(s):

Jonathan Vandersluis

Keyword(s):

Molecular Dynamics ◽

Finite Element ◽

Md Simulation ◽

Computational Simulation ◽

Md Simulations ◽

Single Step ◽

Depth Interval ◽

Simulation Tool ◽

Custom Made ◽

Computational Resources

This thesis develops a molecular dynamics (MD) custom made computational tool to perform nanoindentation simulations on copper nanomaterials, a Face Centred Cubic (FCC) metal. The Embedding Atom Method (EAM) is used to model the interatomic forces with the substrate. Further, a bridged finite element - molecular dynamics (FE-MD) simulation tool is also adapted to perform nanoindentation experimentation. Using this bridged FE-MD simulation tool, nanoindentations are performed much more effectively than the MD simulations while saving substantial computational simulation time. While the MD simulation experienced difficulties capturing the behaviour of the system during indentation especially at faster indentation speeds, the bridged FE-MD method is capable of reaching a state of equilibrium within a single step for each indentation depth interval analyzed throughout the nanoindentation. Although the hardness values for these simulations cannot be obtained without larger scale simulations using more powerful computational resources, the simulations provide insight into the behaviour of the copper nanomaterial during nanoindentation. As a result, it is clear that the bridged FE-MD nanoindentation tool is much more effective for executing nanoindentation simulations than the traditional MD methodologies.

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Fragment Pose Prediction Using Non-Equilibrium Candidate Monte Carlo and Molecular Dynamics Simulations

10.26434/chemrxiv.10032218 ◽

2019 ◽

Author(s):

Nathan M. Lim ◽

Meghan Osato ◽

Gregory L. Warren ◽

David L. Mobley

Keyword(s):

Crystal Structure ◽

Molecular Dynamics ◽

Monte Carlo ◽

Ligand Binding ◽

Md Simulations ◽

Binding Mode ◽

Protein Crystal ◽

Pose Prediction ◽

Binding Modes ◽

Non Equilibrium

<div>Part of early stage drug discovery involves determining how molecules may bind to the target protein. Through understanding where and how molecules bind, chemists can begin to build ideas on how to design improvements to increase binding affinities. In this retrospective study, we compare how computational approaches like docking, molecular dynamics (MD) simulations, and a non-equilibrium candidate Monte Carlo (NCMC) based method (NCMC+MD) perform in predicting binding modes for a set of 12 fragment-like molecules which bind to soluble epoxide hydrolase. We evaluate each method's effectiveness in identifying the dominant binding mode and finding any additional binding modes (if any). Then, we compare our predicted binding modes to experimentally obtained X-ray crystal structures.</div><div>We dock each of the 12 small molecules into the apo-protein crystal structure and then run simulations up to 1 microsecond each. Small and fragment-like molecules likely have smaller energy barriers separating different binding modes by virtue of relatively fewer and weaker interactions relative to drug-like molecules, and thus likely undergo more rapid binding mode transitions. We expect, thus, to see more rapid transitions betweeen binding modes in our study. </div><div><br></div><div>Following this, we build Markov State Models (MSM) to define our stable ligand binding modes. We investigate if adequate sampling of ligand binding modes and transitions between them can occur at the microsecond timescale using traditional MD or a hybrid NCMC+MD simulation approach. Our findings suggest that even with small fragment-like molecules, we fail to sample all the crystallographic binding modes using microsecond MD simulations, but using NCMC+MD we have better success in sampling the crystal structure while obtaining the correct populations.</div>

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Nanoindentation simulations for large atomic systems : an analysis of molecular dynamics and bridged finite element - molecular dynamics methodologies

10.32920/ryerson.14660595.v1 ◽

2021 ◽

Author(s):

Jonathan Vandersluis

Keyword(s):

Molecular Dynamics ◽

Finite Element ◽

Md Simulation ◽

Computational Simulation ◽

Md Simulations ◽

Single Step ◽

Depth Interval ◽

Simulation Tool ◽

Custom Made ◽

Computational Resources

This thesis develops a molecular dynamics (MD) custom made computational tool to perform nanoindentation simulations on copper nanomaterials, a Face Centred Cubic (FCC) metal. The Embedding Atom Method (EAM) is used to model the interatomic forces with the substrate. Further, a bridged finite element - molecular dynamics (FE-MD) simulation tool is also adapted to perform nanoindentation experimentation. Using this bridged FE-MD simulation tool, nanoindentations are performed much more effectively than the MD simulations while saving substantial computational simulation time. While the MD simulation experienced difficulties capturing the behaviour of the system during indentation especially at faster indentation speeds, the bridged FE-MD method is capable of reaching a state of equilibrium within a single step for each indentation depth interval analyzed throughout the nanoindentation. Although the hardness values for these simulations cannot be obtained without larger scale simulations using more powerful computational resources, the simulations provide insight into the behaviour of the copper nanomaterial during nanoindentation. As a result, it is clear that the bridged FE-MD nanoindentation tool is much more effective for executing nanoindentation simulations than the traditional MD methodologies.

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Fragment Pose Prediction Using Non-Equilibrium Candidate Monte Carlo and Molecular Dynamics Simulations

10.26434/chemrxiv.10032218.v2 ◽

2019 ◽

Author(s):

Nathan M. Lim ◽

Meghan Osato ◽

Gregory L. Warren ◽

David L. Mobley

Keyword(s):

Crystal Structure ◽

Molecular Dynamics ◽

Monte Carlo ◽

Ligand Binding ◽

Md Simulations ◽

Binding Mode ◽

Protein Crystal ◽

Pose Prediction ◽

Binding Modes ◽

Non Equilibrium

<div>Part of early stage drug discovery involves determining how molecules may bind to the target protein. Through understanding where and how molecules bind, chemists can begin to build ideas on how to design improvements to increase binding affinities. In this retrospective study, we compare how computational approaches like docking, molecular dynamics (MD) simulations, and a non-equilibrium candidate Monte Carlo (NCMC) based method (NCMC+MD) perform in predicting binding modes for a set of 12 fragment-like molecules which bind to soluble epoxide hydrolase. We evaluate each method's effectiveness in identifying the dominant binding mode and finding any additional binding modes (if any). Then, we compare our predicted binding modes to experimentally obtained X-ray crystal structures.</div><div>We dock each of the 12 small molecules into the apo-protein crystal structure and then run simulations up to 1 microsecond each. Small and fragment-like molecules likely have smaller energy barriers separating different binding modes by virtue of relatively fewer and weaker interactions relative to drug-like molecules, and thus likely undergo more rapid binding mode transitions. We expect, thus, to see more rapid transitions betweeen binding modes in our study. </div><div><br></div><div>Following this, we build Markov State Models (MSM) to define our stable ligand binding modes. We investigate if adequate sampling of ligand binding modes and transitions between them can occur at the microsecond timescale using traditional MD or a hybrid NCMC+MD simulation approach. Our findings suggest that even with small fragment-like molecules, we fail to sample all the crystallographic binding modes using microsecond MD simulations, but using NCMC+MD we have better success in sampling the crystal structure while obtaining the correct populations.</div>

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Can molecular dynamics simulations improve the structural accuracy and virtual screening performance of GPCR models?

PLoS Computational Biology ◽

10.1371/journal.pcbi.1008936 ◽

2021 ◽

Vol 17 (5) ◽

pp. e1008936

Author(s):

Jon Kapla ◽

Ismael Rodriguez Espigares ◽

Flavio Ballante ◽

Jana Selent ◽

Jens Carlsson

Keyword(s):

Crystal Structure ◽

Molecular Dynamics ◽

Virtual Screening ◽

Ligand Binding ◽

Md Simulations ◽

Binding Mode ◽

Extracellular Loop ◽

Loop Region ◽

Screening Performance ◽

Virtual Screening Performance

The determination of G protein-coupled receptor (GPCR) structures at atomic resolution has improved understanding of cellular signaling and will accelerate the development of new drug candidates. However, experimental structures still remain unavailable for a majority of the GPCR family. GPCR structures and their interactions with ligands can also be modelled computationally, but such predictions have limited accuracy. In this work, we explored if molecular dynamics (MD) simulations could be used to refine the accuracy of in silico models of receptor-ligand complexes that were submitted to a community-wide assessment of GPCR structure prediction (GPCR Dock). Two simulation protocols were used to refine 30 models of the D3 dopamine receptor (D3R) in complex with an antagonist. Close to 60 μs of simulation time was generated and the resulting MD refined models were compared to a D3R crystal structure. In the MD simulations, the transmembrane helix region of the models generally drifted further away from the crystal structure conformation. However, MD refinement was able to improve the accuracy of the ligand binding mode and the second extracellular loop region. The best refinement protocol improved agreement with the experimentally observed ligand binding mode for a majority of the models. Receptor structures with improved virtual screening performance, which was assessed by molecular docking of ligands and decoys, could also be identified among the MD refined models. Application of weak restraints to the transmembrane helixes in the MD simulations further improved predictions of the ligand binding mode and second extracellular loop. These results provide guidelines for application of MD refinement in prediction of GPCR-ligand complexes and directions for further method development.

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Fragment Pose Prediction Using Non-Equilibrium Candidate Monte Carlo and Molecular Dynamics Simulations

10.26434/chemrxiv.10032218.v1 ◽

2019 ◽

Author(s):

Nathan M. Lim ◽

Meghan Osato ◽

Gregory L. Warren ◽

David L. Mobley

Keyword(s):

Crystal Structure ◽

Molecular Dynamics ◽

Monte Carlo ◽

Ligand Binding ◽

Md Simulations ◽

Binding Mode ◽

Protein Crystal ◽

Pose Prediction ◽

Binding Modes ◽

Non Equilibrium

<div>Part of early stage drug discovery involves determining how molecules may bind to the target protein. Through understanding where and how molecules bind, chemists can begin to build ideas on how to design improvements to increase binding affinities. In this retrospective study, we compare how computational approaches like docking, molecular dynamics (MD) simulations, and a non-equilibrium candidate Monte Carlo (NCMC) based method (NCMC+MD) perform in predicting binding modes for a set of 12 fragment-like molecules which bind to soluble epoxide hydrolase. We evaluate each method's effectiveness in identifying the dominant binding mode and finding any additional binding modes (if any). Then, we compare our predicted binding modes to experimentally obtained X-ray crystal structures.</div><div>We dock each of the 12 small molecules into the apo-protein crystal structure and then run simulations up to 1 microsecond each. Small and fragment-like molecules likely have smaller energy barriers separating different binding modes by virtue of relatively fewer and weaker interactions relative to drug-like molecules, and thus likely undergo more rapid binding mode transitions. We expect, thus, to see more rapid transitions betweeen binding modes in our study. </div><div><br></div><div>Following this, we build Markov State Models (MSM) to define our stable ligand binding modes. We investigate if adequate sampling of ligand binding modes and transitions between them can occur at the microsecond timescale using traditional MD or a hybrid NCMC+MD simulation approach. Our findings suggest that even with small fragment-like molecules, we fail to sample all the crystallographic binding modes using microsecond MD simulations, but using NCMC+MD we have better success in sampling the crystal structure while obtaining the correct populations.</div>

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Fully Atomistic Molecular Dynamics Computation of Physico-Mechanical Properties of PB, PS, and SBS

Nanomaterials ◽

10.3390/nano9081088 ◽

2019 ◽

Vol 9 (8) ◽

pp. 1088 ◽

Cited By ~ 1

Author(s):

Yang Kang ◽

Dunhong Zhou ◽

Qiang Wu ◽

Fuyan Duan ◽

Rufang Yao ◽

...

Keyword(s):

Molecular Dynamics ◽

Strain Rate ◽

Strain Hardening ◽

Md Simulation ◽

Md Simulations ◽

Strain Rates ◽

Young’S Moduli ◽

Plastic Modulus ◽

Styrene Butadiene ◽

Butadiene Styrene

The physical properties—including density, glass transition temperature (Tg), and tensile properties—of polybutadiene (PB), polystyrene (PS) and poly (styrene-butadiene-styrene: SBS) block copolymer were predicted by using atomistic molecular dynamics (MD) simulation. At 100 K, for PB and SBS under uniaxial tension with strain rate ε ˙ = 1010 s−1 and 109 s−1, their stress–strain curves had four features, i.e., elastic, yield, softening, and strain hardening. At 300 K, the tensile curves of the three polymers with strain rates between 108 s−1 and 1010 s−1 exhibited strain hardening following elastic regime. The values of Young’s moduli of the copolymers were independent of strain rate. The plastic modulus of PS was independent of strain rate, but the Young’s moduli of PB and SBS depended on strain rate under the same conditions. After extrapolating the Young’s moduli of PB and SBS at strain rates of 0.01–1 s−1 by the linearized Eyring-like model, the predicted results by MD simulations were in accordance well with experimental results, which demonstrate that MD results are feasible for design of new materials.

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Conservation of the conformational dynamics and ligand binding within M49 enzyme family

RSC Advances ◽

10.1039/c7ra13059g ◽

2018 ◽

Vol 8 (24) ◽

pp. 13310-13322 ◽

Cited By ~ 2

Author(s):

Saša Kazazić ◽

Zrinka Karačić ◽

Igor Sabljić ◽

Dejan Agić ◽

Marko Tomin ◽

...

Keyword(s):

Mass Spectrometry ◽

Molecular Dynamics ◽

Ligand Binding ◽

Conformational Dynamics ◽

Md Simulations ◽

Dipeptidyl Peptidase ◽

Deuterium Exchange ◽

Hydrogen Deuterium Exchange ◽

Enzyme Family ◽

Hydrogen Deuterium

The hydrogen deuterium exchange (HDX) mass spectrometry combined with molecular dynamics (MD) simulations was employed to investigate conformational dynamics and ligand binding within the M49 family (dipeptidyl peptidase III family).

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Surface Tension Evaluation Via Thermodynamic Analysis of Statistical Data From Molecular Dynamics Simulations

Volume 4 ◽

10.1115/ht-fed2004-56690 ◽

2004 ◽

Cited By ~ 1

Author(s):

Aaron P. Wemhoff ◽

Van P. Carey

Keyword(s):

Molecular Dynamics ◽

Surface Tension ◽

Density Profile ◽

Md Simulation ◽

Md Simulations ◽

Bulk Liquid ◽

Interfacial Region ◽

Lennard Jones Potential ◽

Jones Potential ◽

Lennard Jones

Surface tension determination of liquid-vapor interfaces of polyatomic fluids using traditional methods has shown to be difficult due to the requirement of evaluating complex intermolecular potentials. However, analytical techniques have recently been developed that determine surface tension solely by means of the characteristics of the interfacial region between the bulk liquid and vapor regions. A post-simulation application of the excess free energy density integration (EFEDI) method was used for analysis of the resultant density profile of molecular dynamics (MD) simulations of argon using a simple Lennard-Jones potential and diatomic nitrogen using a two-center Lennard-Jones potential. MD simulations were also run for an approximation of nitrogen using the simple Lennard-Jones potential. In each MD simulation, a liquid film was initialized between vapor regions and NVE-type simulations were run to equilibrium. The simulation domain was divided into bins across the interfacial region for fluid density collection, and the resultant interfacial region density profile was used for surface tension evaluation. Application of the EFEDI method to these MD simulation results exhibited good approximations to surface tension as a function of temperature for both a simple and complex potential.

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