Chapter category: Drug Design
Evolutionary De Novo Design
Adaptive Systems in Drug Design
Edited by: Gisbert SchneiderISBN: 1-58706-059-0
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Chapter authors:
Gisbert Schneider
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"GAs have been shown to be capable of describing extremely complex bahaviour in a range of application domains, including those of molecular recognition and design." (P. Willett)1
In the previous Chapters we have addressed some issues related to adaptive optimization methods and fitness calculation in the context of drug design tasks, in particular evolutionary algorithms and artificial neural networks. To close the design cycle depicted in Figure 1.4 we still have to define the molecule generator. This will be the main focus of this Chapter. We will highlight only selected approaches, which we have chosen either because they illustrate a general principle, or we have particular experience with these methods. Again the focus will be on evolutionary techniques.
Generally, current computer-based molecular design approaches may be regarded as being guided by two major strategies:
- Structure-based design relying on a 3D receptor model of the ligand-binding pocket
- Ligand-based design starting from the knowledge of one or several known actives without taking the 3D receptor structure into account.
The majority of the current structure-based design tools are based on a computer model of a binding site and require a scoring function that computes an estimate of the binding affinity of a molecule—e.g., a potential inhibitor—in a given conformation (also called a pose) within the binding pocket. In contrast, ligand-based tools usually build on a scoring function that implements some sort of similarity principle rather than estimating binding affinity in a receptor-ligand docking experiment. Of course, both approaches complement each other and can be combined—depending on how much biostructure information is available at the beginning or becomes available during a project. New structures can for example be docked into or grown within a binding pocket (provided a receptor structure is available) or compared to a known active reference molecule.
Additional chapters from this book:
Analysis of Chemical Space
Gisbert Schneider
A main goal of virtual screening is to select activity-enriched sets of molecules — or single molecules exhibiting desired activity—from the space of all synthetically accessible ...
Evolutionary De Novo Design
Gisbert Schneider
"GAs have been shown to be capable of describing extremely complex bahaviour in a range of application domains, including those of molecular recognition and design." (P. Willett)
Prediction of Drug-Like Properties
Gisbert Schneider
Historically, computer-aided molecular design (CAMD) has focused on lead identification and lead optimization, and many innovative strategies have been developed that assist in improving th...
Modeling Structure-Activity Relationships
Gisbert Schneider
Traditionally, the design of novel drugs has essentially been a trial-and-error process despite the tremendous efforts devoted to it by pharmaceutical and academic research groups. It is es...
A Conceptual Framework
Gisbert Schneider
"It is no longer just sufficient to synthesise and test; experiments are played out in silico with prediction, classification, and visualisation being the necessary tools of medicin...
