scholarly journals A Short Review on the Application of Combining Molecular Docking and Molecular Dynamics Simulations in Field of Drug Discovery

2014 ◽  
Vol 7 (2) ◽  
pp. 75-78 ◽  
Author(s):  
Gugan Kothandan ◽  
Jagadeesan Ganapathy
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Drug Discovery ◽  
Molecular Dynamics Simulations ◽  
Short Review ◽  
Dynamics Simulations

Advancements in Docking and Molecular Dynamics Simulations Towards Ligand-receptor Interactions and Structure-function Relationships

2018 ◽  
Vol 18 (20) ◽  
pp. 1755-1768 ◽  
Author(s):  
Ahmad Abu Turab Naqvi ◽  
Taj Mohammad ◽  
Gulam Mustafa Hasan ◽  
Md. Imtaiyaz Hassan
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Drug Discovery ◽  
Molecular Dynamics Simulations ◽  
Computational Method ◽  
Dynamics Simulation ◽  
Ligand Molecule ◽  
Ligand Interaction ◽  
Modern Drug ◽  
Dynamics Simulations

Protein-ligand interaction is an imperative subject in structure-based drug design and protein function prediction process. Molecular docking is a computational method which predicts the binding of a ligand molecule to the particular receptor. It predicts the binding pose, strength and binding affinity of the molecules using various scoring functions. Molecular docking and molecular dynamics simulations are widely used in combination to predict the binding modes, binding affinities and stability of different protein-ligand systems. With advancements in algorithms and computational power, molecular dynamics simulation is now a fundamental tool to investigative bio-molecular assemblies at atomic level. These methods in association with experimental support have been of great value in modern drug discovery and development. Nowadays, it has become an increasingly significant method in drug discovery process. In this review, we focus on protein-ligand interactions using molecular docking, virtual screening and molecular dynamics simulations. Here, we cover an overview of the available methods for molecular docking and molecular dynamics simulations, and their advancement and applications in the area of modern drug discovery. The available docking software and their advancement including application examples of different approaches for drug discovery are also discussed. We have also introduced the physicochemical foundations of molecular docking and simulations, mainly from the perception of bio-molecular interactions.

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.

Promising inhibitors of nsp2 of CHIKV using molecular docking and temperature-dependent molecular dynamics simulations

2021 ◽  
pp. 1-9
Author(s):  
Mahendera Kumar Meena ◽  
Durgesh Kumar ◽  
Kamlesh Kumari ◽  
Nagendra Kumar Kaushik ◽  
Rammapa Venkatesh Kumar ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulations ◽  
Temperature Dependent ◽  
Dynamics Simulations

scholarly journals In silico chemical profiling and identification of neuromodulators from Curcuma amada targeting Acetylcholinesterase

2020 ◽  
Author(s):  
Md. Chayan Ali ◽  
Yeasmin Akter Munni ◽  
Raju Das ◽  
Marium sultana ◽  
Nasrin Akter ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulations ◽  
In Silico ◽  
Network Pharmacology ◽  
Chemical Profiling ◽  
Ache Inhibitors ◽  
Curcuma Amada ◽  
In Silico Admet ◽  
Dynamics Simulations

AbstractCurcuma amada or Mango ginger, a member of the Zingiberaceae family, has been revealed as a beneficiary medicinal plant having diverse pharmacological activities against a wide range of diseases. Due to having neuromodulation properties of this plant, the present study characterized the secondary metabolites of Curcuma amada for their drug-likeness properties, identified potent hits by targeting Acetylcholinesterase (AChE) and revealed neuromodulatory potentiality by network pharmacology approaches. Here in silico ADMET analysis was performed for chemical profiling, and molecular docking and molecular dynamics simulations were used to hit selection and binding characterizations. Accordingly, ADMET prediction showed that around 87.59% of compounds processed drug-likeness activity, where four compounds have been screened out by molecular docking. Guided from induced-fit docking, molecular dynamics simulations revealed phytosterol and curcumin derivatives as the most favorable AChE inhibitors with the highest binding energy, as resulted from MM-PBSA analysis. Furthermore, all of the four hits were appeared to modulate several signaling molecules and intrinsic cellular pathways in network pharmacology analysis, which are associated with neuronal growth survival, inflammation, and immune response, supporting their capacity to revert the condition of neuro-pathobiology. Together, the present in silico based characterization and system pharmacology based findings demonstrate Curcuma amada, as a great source of neuromodulating compounds, which brings about new development for complementary and alternative medicine for the prevention and treatment of neurodegenerative disorders.

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