Multi-and many-objective optimization: present and future in de novo drug design.

ABSTRACT: de novo Drug Design (dnDD) aims to create new molecules that satisfy multiple conflicting objectives. Since several desired properties can be considered in the optimization process, dnDD is naturally categorized as a many-objective optimization problem (ManyOOP), where more than three objectives must be simultaneously optimized. However, a large number of objectives typically pose several challenges that affect the choice and the design of optimization methodologies. Herein, we cover the application of multi- and many-objective optimization methods, particularly those based on Evolutionary Computation and Machine Learning techniques, to enlighten their potential application in dnDD. Additionally, we comprehensively analyze how molecular properties used in the optimization process ar

SUBMITTER: Angelo JS 

PROVIDER: S-EPMC10773868 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature