Molecular Docking and Computational Analysis of Organic Compounds

Molecular docking is a computational strategy to predict the binding orientation and affinity of small organic molecules—ligands—to their target macromolecules, typically proteins. When combined with in silico chemical methods, it accelerates the rational design of novel therapeutics by modelling intermolecular interactions, assessing binding energies and exploring conformational landscapes. Advances in scoring functions and search algorithms have enhanced predictive accuracy, while integration with quantum mechanical approaches such as density functional theory (DFT) allows for refined evaluation of electronic properties and reactive sites. High-throughput virtual screening platforms frequently incorporate absorption, distribution, metabolism, excretion and toxicity (ADMET) assessments, facilitating early elimination of candidates with unfavourable pharmacokinetic profiles. This synergy of structural bioinformatics and computational chemistry underpins the discovery of enzyme inhibitors, receptor modulators and covalent binders across diverse disease areas. Applications extend to agrochemical design, materials science and environmental remediation, reflecting the global significance of computational analysis in streamlining organic compound development. Emerging trends include machine-learning-enhanced scoring, enhanced sampling techniques and integration with multi-omics data to contextualise binding events within complex biological networks.

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Molecular Docking and Computational Analysis of Organic Compounds publication trend

The graph below shows the total number of articles in molecular docking and computational analysis of organic compounds across all publications each year (not limited to Nature Index journals).

Technical terms

Molecular docking: Computational method that predicts the preferred orientation and binding affinity of a ligand when bound to a protein or nucleic acid receptor.

Density functional theory (DFT): Quantum mechanical approach for modelling the electronic structure and energy of molecular systems to inform reactivity and binding characteristics.

ADMET: In silico evaluation of absorption, distribution, metabolism, excretion and toxicity properties to predict pharmacokinetic behaviour.

Hirshfeld surface analysis: Technique for visualising and quantifying close intermolecular contacts in crystal structures, highlighting regions of significant interaction.

Scoring function: Mathematical model used in docking to estimate the strength of protein–ligand interactions, guiding the ranking of candidate compounds.

References

1. 3-Chloro-3-methyl-2,6-diarylpiperidin-4-ones as Anti-Cancer Agents: Synthesis, Biological Evaluation, Molecular Docking, and In Silico ADMET Prediction. Biomolecules (2022).
2. Exploring novel fluorine-rich fuberidazole derivatives as hypoxic cancer inhibitors: Design, synthesis, pharmacokinetics, molecular docking, and DFT evaluations. PLOS ONE (2023).
3. Crystal structure, Hirshfeld surface analysis, DFT and the mol­ecular docking studies of 3-(2-chloro­acet­yl)-2,4,6,8-tetra­phenyl-3,7-di­azabicyclo­[3.3.1]nonan-9-one. Acta Crystallographica Section E: Crystallographic Communications (2024).