CAMD and CAMD and GAsGAs in Rational in RationalDrug DesignDrug DesignChristopher Michael LorenzChristopher Michael LorenzBioChemistry BioChemistry 118Q118QJune 4, 2001June 4, 2001What is CAMD?What is CAMD?CAMD stands for Computer Aided Molecular DesignThe design of new molecules based on desired propertiesFocused on modeling drugs and biological receptors the drugsbind to so that better binding, and more potent drugs can bedevelopedWhy use CAMD?Why use CAMD?Avoids tedious lab work by using computers to model molecules andtheir propertiesComputers can develop new structures and determine whether thosestructures could serve a specific purpose much faster than humansComputers can imitate the millions of years of random variation andnatural selection that specialized the molecular structures that gave riseto compounds such as morphine, penicillin, digitalis, and tamoxifenAllows discoveries of a random, almost ‘accidental’ natureCAMD Success:CAMD Success:Development of an HIV protease inhibitor by Dupont MerckDeveloped completely on acomputer by studying themolecular properties favorableto such an inhibitor, and thendesigning a molecule to meetthe necessary requirementsHIV REV bound to RNA.HIV REV bound to RNA.Forward: the computation of macroscopic propertiesgiven the molecular structureBackward: identification of the appropriate molecularstructure given the desired propertiesCAMD addresses two problems:CAMD addresses two problems:How does CAMD address these problems?How does CAMD address these problems?Genetic Algorithms (GAs)What are genetic algorithms?What are genetic algorithms?GAs are computer programs that apply optimization methodsof evolution (mutation, crossover, replication, etc.) togenerations of populations of computer code "chromosomes”Genetic AlgorithmsGenetic AlgorithmsGenetic algorithms manipulate genetic material, but instead ofDNA, this genetic material is some other linear string ofsymbols which can represent base pairs, codons, amino acids,or molecular structuresWhat happens?Genetic operators(crossovers,mutations, etc.)occur, and fittestoffspring pass on tonext generationCrossover: An ExampleCrossover: An ExampleIn this example, crossover occurs after position three of parent 1and position two of parent 2Mutation: An ExampleMutation: An ExampleThe —CH2— is replaced by a benzene ringOther OperatorsOther Operators•Blending•Insertion•Deletion•HoppingHow are the fittest offspring determined?How are the fittest offspring determined?Population members are ranked by a fitness functionfitness function, whichcould include parameters such as bond angles and energyvalues that reflect the structure's stabilityThe fitness function can estimate and rank the dockingabilities of ligands and receptors—the poorest dockingcompounds are removed, and the remainder are modifiedgenetically and continue through the loopThe members in the generation with the highest level of fitnessbecome the optimal designs, and will have a higher expectednumber of offspringFitness Functions: DifficultiesFitness Functions: DifficultiesExtremely complex:•Must build molecules andcalculate properties•Determine effects of placingmolecule on the receptor•Account for 3-D aspect ofthe molecule and its pathwayto the receptorGenetic Algorithm FrameworkGenetic Algorithm FrameworkMuch better than:Much better than:How Will How Will YouYou Make Money? Make Money?Protein Simulation ProgramsPredict structures based on sequencesPredict how ligands will dock into protein
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