AI methods for generating, evaluating, and optimizing molecular structures according to computational objectives.
Systems may use generative models, molecular graphs, optimization algorithms, property predictors, and multi-objective evaluation.
Applications include candidate generation, scaffold exploration, property optimization, and computational design studies.
Implementation is selected according to the available data, technical constraints, required level of automation, and the existing software or research environment. The solution can be implemented as a standalone component or integrated into a larger system.
The resulting system is intended to provide a clear computational workflow that can be evaluated, maintained, and extended as the project develops. Model choice, data processing, interfaces, and deployment can therefore be adapted to the requirements of the specific project.