scholarly journals Advances in Molecular Dynamics Simulations and Enhanced Sampling Methods for the Study of Protein Systems

2020 ◽  
Vol 21 (17) ◽  
pp. 6339
Author(s):  
Raudah Lazim ◽  
Donghyuk Suh ◽  
Sun Choi
Keyword(s):  
Molecular Dynamics ◽  
Md Simulation ◽  
Enhanced Sampling ◽  
Structure Based Drug Design ◽  
Simulation Tools ◽  
Computer Calculations ◽  
Function Relationship ◽  
Dynamics Simulations ◽  
Relationship Of

Molecular dynamics (MD) simulation is a rigorous theoretical tool that when used efficiently could provide reliable answers to questions pertaining to the structure-function relationship of proteins. Data collated from protein dynamics can be translated into useful statistics that can be exploited to sieve thermodynamics and kinetics crucial for the elucidation of mechanisms responsible for the modulation of biological processes such as protein-ligand binding and protein-protein association. Continuous modernization of simulation tools enables accurate prediction and characterization of the aforementioned mechanisms and these qualities are highly beneficial for the expedition of drug development when effectively applied to structure-based drug design (SBDD). In this review, current all-atom MD simulation methods, with focus on enhanced sampling techniques, utilized to examine protein structure, dynamics, and functions are discussed. This review will pivot around computer calculations of protein-ligand and protein-protein systems with applications to SBDD. In addition, we will also be highlighting limitations faced by current simulation tools as well as the improvements that have been made to ameliorate their efficiency.

Investigating targets for neuropharmacological intervention by molecular dynamics simulations

2019 ◽  
Vol 47 (3) ◽  
pp. 909-918
Author(s):  
Giulia Rossetti ◽  
Achim Kless ◽  
Luhua Lai ◽  
Tiago F. Outeiro ◽  
Paolo Carloni
Keyword(s):  
Molecular Dynamics ◽  
Disease Onset ◽  
Physiological Saline ◽  
Diagnostic Tools ◽  
Biologically Relevant ◽  
Neuroactive Drugs ◽  
Function Relationship ◽  
Dynamics Simulations ◽  
Relationship Of ◽  
Insight Into

Abstract Medical research has identified over 500 brain disorders. Among these, there are still only very few neuropathologies whose causes are fully understood and, consequently, very few drugs whose mechanism of action is known. No FDA drug has been identified for major neurodegenerative diseases, such as Alzheimer's and Parkinson's. We still lack effective treatments and strategies for modulating progression or even early neurodegenerative disease onset diagnostic tools. A great support toward the highly needed identification of neuroactive drugs comes from computer simulation methods and, in particular, from molecular dynamics (MD). This provides insight into structure–function relationship of a target and predicts structure, dynamics and energetics of ligand/target complexes under biologically relevant conditions like temperature and physiological saline concentration. Here, we present examples of the predictive power of MD for neuroactive ligands/target complexes. This brief survey from our own research shows the usefulness of partnerships between academia and industry, and from joint efforts between experimental and theoretical groups.

Use of Molecular Dynamics Simulations in Structure-Based Drug Discovery

2019 ◽  
Vol 25 (31) ◽  
pp. 3339-3349 ◽  
Author(s):  
Indrani Bera ◽  
Pavan V. Payghan
Keyword(s):  
Molecular Dynamics ◽  
Drug Discovery ◽  
Molecular Dynamics Simulations ◽  
Drug Target ◽  
Structural Information ◽  
Drug Binding ◽  
Structure Based Drug Design ◽  
Drug Designing ◽  
Target Binding ◽  
Dynamics Simulations

Background: Traditional drug discovery is a lengthy process which involves a huge amount of resources. Modern-day drug discovers various multidisciplinary approaches amongst which, computational ligand and structure-based drug designing methods contribute significantly. Structure-based drug designing techniques require the knowledge of structural information of drug target and drug-target complexes. Proper understanding of drug-target binding requires the flexibility of both ligand and receptor to be incorporated. Molecular docking refers to the static picture of the drug-target complex(es). Molecular dynamics, on the other hand, introduces flexibility to understand the drug binding process. Objective: The aim of the present study is to provide a systematic review on the usage of molecular dynamics simulations to aid the process of structure-based drug design. Method: This review discussed findings from various research articles and review papers on the use of molecular dynamics in drug discovery. All efforts highlight the practical grounds for which molecular dynamics simulations are used in drug designing program. In summary, various aspects of the use of molecular dynamics simulations that underline the basis of studying drug-target complexes were thoroughly explained. Results: This review is the result of reviewing more than a hundred papers. It summarizes various problems that use molecular dynamics simulations. Conclusion: The findings of this review highlight how molecular dynamics simulations have been successfully implemented to study the structure-function details of specific drug-target complexes. It also identifies the key areas such as stability of drug-target complexes, ligand binding kinetics and identification of allosteric sites which have been elucidated using molecular dynamics simulations.

scholarly journals Contributions of Molecular Dynamics Simulations to Elastohydrodynamic Lubrication

2021 ◽  
Vol 69 (1) ◽  
Author(s):  
James P. Ewen ◽  
Hugh A. Spikes ◽  
Daniele Dini
Keyword(s):  
Molecular Dynamics ◽  
Shear Rate ◽  
Experimental Design ◽  
Md Simulation ◽  
Elastohydrodynamic Lubrication ◽  
Quantitative Agreement ◽  
Coupling Methods ◽  
Fundamental Understanding ◽  
Shear Heating ◽  
Dynamics Simulations

AbstractThe prediction of friction under elastohydrodynamic lubrication (EHL) conditions remains one of the most important and controversial areas of tribology. This is mostly because the pressure and shear rate conditions inside EHL contacts are particularly severe, which complicates experimental design. Over the last decade, molecular dynamics (MD) simulation has played an increasingly significant role in our fundamental understanding of molecular behaviour under EHL conditions. In recent years, MD simulation has shown quantitative agreement with friction and viscosity results obtained experimentally, meaning that they can, either in isolation or through the use of multiscale coupling methods, begin to be used to test and inform macroscale models for EHL problems. This is particularly useful under conditions that are relevant inside machine components, but are difficult to obtain experimentally without uncontrollable shear heating.

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