Journal of Medicinal Chemistry · 2005 · 161 citations · 34 references
PharmacyMedicinal ChemistryComputational ChemistryDrug DesignDrug DiscoveryDe Novo Drug DesignFragment-based Drug DesignFragment-based OptimizationMolecular DockingProtein DockingProtein-ligand DockingDe Novo Ligand DesignDocking-based Drug DesignFragment-based De Novo DesignRational DesignStructure-based De Novo DesignStructure-based Ligand Design
Rational drug design tackles large combinatorial problems that are impractical to solve exhaustively, and genetic algorithms are a common tool for exploring such spaces. The study presents an improved version of the LEA program for designing organic molecules. LEA3D generates organic molecules by assembling 3D fragments from biological compounds and known drugs, guided by a fitness function that integrates multiple property evaluations—including a FlexX docking score—to optimize molecules, and it was applied to design analogues of a natural substrate for Mycobacterium tuberculosis thymidine monophosphate kinase. Of 22 tested compounds, 17 exhibited micromolar‑range inhibitory activity.
We present an improved version of the program LEA developed to design organic molecules. Rational drug design involves finding solutions to large combinatorial problems for which an exhaustive search is impractical. Genetic algorithms provide a tool for the investigation of such problems. New software, called LEA3D, is now able to conceive organic molecules by combining 3D fragments. Fragments were extracted from both biological compounds and known drugs. A fitness function guides the search process in optimizing the molecules toward an optimal value of the properties. The fitness function is build up by combining several independent property evaluations, including the score provided by the FlexX docking program. One application in de novo drug design is described. The example makes use of the structure of Mycobacterium tuberculosis thymidine monophosphate kinase to generate analogues of one of its natural substrates. Among 22 tested compounds, 17 show inhibitory activity in the micromolar range.
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Genetic algorithms in search, optimization, and machine learning
Choice Reviews Online · 1989 · 49.3K citations
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