JOURNAL OF MOLECULAR GRAPHICS & MODELLING
Scope & Guideline
Pioneering Discoveries in Molecular Interactions
Introduction
Aims and Scopes
- Molecular Dynamics Simulations:
The journal frequently publishes studies utilizing molecular dynamics simulations to investigate the behavior of molecules in various environments, providing insights into structural and dynamical properties. - Density Functional Theory (DFT) Calculations:
DFT is a common computational method featured in the journal, allowing researchers to explore electronic structures, reaction mechanisms, and material properties at the quantum level. - Drug Discovery and Design:
A significant focus is placed on computational approaches for drug discovery, including virtual screening, molecular docking, and pharmacophore modeling to identify potential therapeutic candidates. - Material Science Applications:
The journal covers research on the properties and applications of novel materials, particularly in the context of energy storage, catalysis, and nanotechnology, often emphasizing their molecular-level interactions. - Biomolecular Interactions:
Research on protein-ligand interactions, enzyme mechanisms, and the development of biomolecular sensors is prevalent, highlighting the importance of computational methods in understanding biological processes. - Machine Learning Integration:
There is an emerging trend of integrating machine learning techniques with traditional computational methods to enhance predictive modeling and accelerate the discovery of new compounds.
Trending and Emerging
- Advanced Machine Learning Applications:
The integration of machine learning techniques in molecular modeling is on the rise, with researchers applying AI to predict molecular properties and optimize drug design. - COVID-19 Related Studies:
There has been an increase in publications focused on SARS-CoV-2, utilizing computational methods to explore drug interactions, structural dynamics, and potential inhibitors. - Nanotechnology and Nanomaterials:
Research on nanostructures and their applications in drug delivery, sensors, and energy conversion is trending, reflecting growing interest in nanoscale materials and their unique properties. - Multiscale Modeling Approaches:
The journal is seeing a trend towards multiscale modeling, combining different computational techniques to capture complex phenomena in materials and biological systems. - Environmental and Green Chemistry:
An emerging interest in sustainable practices and green chemistry is evident, with a focus on developing eco-friendly materials and processes using computational insights. - Complex Biomolecular Systems:
Research surrounding complex biomolecular systems, including protein interactions and the dynamics of larger biological assemblies, is gaining prominence, highlighting the need for detailed computational studies.
Declining or Waning
- Classical Force Field Studies:
Traditional molecular mechanics studies based on classical force fields have seen a decline, as researchers increasingly adopt more sophisticated quantum mechanical approaches like DFT and hybrid methods. - Empirical Modeling Techniques:
There has been a noticeable reduction in the publication of studies relying solely on empirical models, as the field shifts toward more data-driven, computationally intensive methods. - Static Structural Analysis:
The focus on static structural analysis of small molecules without dynamic considerations has decreased, as dynamic simulations and real-time interactions gain traction in research. - General Computational Chemistry:
There is a decline in general computational chemistry studies that do not employ advanced techniques, as the journal increasingly emphasizes high-impact studies with innovative methodologies.
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