Computer-aided drug design

Computer-aided drug design uses computational methods to identify, model, and optimize molecules as potential medicines, often before laboratory testing.

Structure-based drug design: Drug design guided by a biological target’s three-dimensional structure. It predicts how candidate molecules fit a target’s binding site.
Protein structure prediction: Computational prediction of a protein’s three-dimensional structure from its amino-acid sequence. Predicted structures can supply targets when experimental structures are missing.
Virtual screening: Computational prioritization of compounds for experimental testing against a biological target or activity. It narrows large chemical collections to candidates for laboratory assays.
Experimental drug discovery: The identification and refinement of therapeutic compounds through laboratory experiments. It supplies measurements that computational predictions require for testing and calibration.
Ligand-based drug design: Drug design that uses known active molecules to infer features of new candidates. It can guide design when the target’s structure is unavailable.
Molecular mechanics: Modeling molecular energy and motion using classical equations and parameterized force fields. Many design calculations rely on its approximate representation of atoms and bonds.
De novo drug design: Computational generation or construction of new molecules to satisfy desired properties or target interactions. It creates candidate structures rather than only ranking existing compounds.
Fragment-based drug discovery: A strategy that finds small, weakly binding molecules and grows or links them into candidates. It combines experimental fragment evidence with computational growth and optimization.
Molecular docking: A computational method that predicts how a molecule may bind to a biological target. Docking estimates candidate poses and binding scores against a target.
Quantum chemistry: The application of quantum mechanics to calculate the properties and behavior of molecules. It provides electronic-level calculations for properties that classical models cannot capture.

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