Efficient split synthesis for targeted libraries.
We propose a new approach for fabricating more sophisticated combinatorial chemistry libraries via split synthesis and evaluate its potential through extensive simulation. Our algorithmically intensive method promises to reduce the time and materials costs of synthesizing libraries which are (1) too large to synthesize economically by sequential or parallel synthesis, (2) too long or irregular for conventional split synthesis generation techniques, and (3) not used in sufficient quantity to justify the setup costs of array makers. It also encourages the design of more focused and interesting libraries than are typically constructed using split synthesis. Our algorithms automate the design of efficient synthesis procedures for motif-based libraries which are too complex to design by hand. Our software allows the user to select the most desirable tradeoff between minimizing the number of steps in the synthesis process and containing the combinatorial explosion of the number of compounds synthesized.
Cohen
B
B
Department of Computer Science, State University of New York at Stony Brook 11794-4400, USA.
Skiena
S
S
D000465:Algorithms; D000818:Animals; D002625:Chemistry, Organic / Q000191:economics / Q000379:methods*; D002645:Chickens; D004268:DNA-Binding Proteins / Q000138:chemical synthesis; D016208:Databases, Factual; D006801:Humans; D008956:Models, Chemical; D019151:Peptide Library; D015302:Simian Immunodeficiency Virus / Q000737:chemistry; D014157:Transcription Factors / Q000138:chemical synthesis
D004268:DNA-Binding Proteins; D019151:Peptide Library; D014157:Transcription Factors; C099948:fetoprotein transcription factor