Focus and Scope

Journal of Computational Chemistry Modeling and Data Science publishes original research articles, review papers (including state-of-the-art, systematic, and critical reviews), and short communications that report significant advances in computational chemistry, molecular modeling, chemometrics, and data science in chemistry. The journal aims to provide an international platform for theoretical, computational, and data-driven approaches to understanding chemical systems at molecular and multiscale levels. Short communications are intended for concise, high-impact contributions presenting novel methods, algorithms, preliminary results, or innovative applications with clear scientific significance. The scope of the journal includes, but is not limited to, the following areas:

  1. Computational Chemistry and Molecular Modeling
    • Quantum chemistry methods (ab initio, DFT, semi-empirical approaches)
    • Molecular mechanics and force-field development
    • Molecular dynamics (MD) and Monte Carlo simulations
    • Hybrid QM/MM and multiscale modeling approaches
  2. Molecular Simulation and Theoretical Chemistry
    • Structural and dynamical simulations of molecular systems
    • Intermolecular interactions and binding free energy calculations
    • Enhanced sampling techniques and rare-event simulations
    • Modeling of biological, materials, and environmental systems
  3. Data Science in Chemistry
    • Chemical data mining and statistical learning
    • Machine learning and artificial intelligence for chemical property prediction
    • Deep learning for molecular representation and modeling
    • Big data analytics and high-dimensional chemical data analysis
    • Predictive modeling and uncertainty quantification in chemical systems
  4. Chemometrics and Multivariate Data Analysis
    • Exploratory and predictive chemometric methods (PCA, HCA, PLS, PLS-DA, OPLS)
    • Data preprocessing, normalization, scaling, and alignment
    • Model validation, robustness assessment, and overfitting control
    • Data fusion and multiblock analysis
    • Applications to spectroscopic, chromatographic, and omics data
  5. Computational Drug Discovery and Chemical Biology
    • Molecular docking and virtual screening
    • Computer-aided drug design (CADD)
    • Protein–ligand interaction modeling
    • Biomolecular simulations and data-driven drug discovery
  6. Computational Materials Science and Nanotechnology
    • Modeling of functional materials, catalysts, and energy materials
    • Simulation of nanomaterials, surfaces, and interfaces
    • Prediction of electronic, optical, and mechanical properties
  7. Reaction Modeling and Physical Chemistry
    • Reaction mechanisms and pathways
    • Kinetic and thermodynamic modeling
    • Surface chemistry and heterogeneous catalysis
  8. Methods, Software, and High-Performance Computing
    • Development and benchmarking of computational chemistry and data science algorithms
    • Scientific software and workflow development
    • High-performance computing (HPC) and cloud-based computing
    • Reproducible, open, and FAIR chemical data practices
  9. Review, Perspective, and Short Communication Articles
    • Comprehensive and critical reviews of emerging methods and applications
    • Systematic reviews and meta-analyses of chemical data
    • Perspective articles highlighting future trends in computational and data-driven chemistry
    • Short communications reporting concise and innovative findings
  10. Interdisciplinary and Applied Studies
    • Integration of computational chemistry, data science, and experimental approaches
    • Applications in pharmaceuticals, food science, environmental chemistry, energy, and chemical industries