Conformational searching using a population-based incremental learning algorithm.

A new population-based incremental learning algorithm for conformational searching of molecules is presented. This algorithm is particularly effective at determining, by relatively small number of energy minimizations, global energy minima of large flexible molecules. The algorithm is also able to find a large set of low energy conformations of more rigid small molecules. The performance of the algorithm is relation to other algorithm is examined via the test molecules: C(18) H(38) , C(39)H(80) , cycloheptadecane and a set of five drug-like molecules.

A gradient descent algorithm for minimizing amino acid coupling reactions when synthesizing cyclic-peptide libraries.

Combinatorial chemistry has become an invaluable tool in medicinal chemistry for the identification of new drug leads. For example, libraries of predetermined sequences and head-to-tail cyclized peptides are routinely synthesized in our laboratory using the IRORI approach. Such libraries are used as molecular toolkits that enable the development of pharmacophores that define activity and specificity at receptor targets. These libraries can be quite large and difficult to handle, due to physical and chemical constraints imposed by their size. Therefore, smaller sub-libraries are often targeted for synthesis. The number of coupling reactions required can be greatly reduced if the peptides having common amino acids are grouped into the same sub-library (batching). This paper describes a schedule optimizer to minimize the number of coupling reactions by rotating and aligning sequences while simultaneously batching. The gradient descent method thereby reduces the number of coupling reactions required for synthesizing cyclic peptide libraries. We show that the algorithm results in a 75% reduction in the number of coupling reactions for a typical cyclic peptide library.

A convenient method for synthesis of cyclic peptide libraries.

Cyclic peptides have been reported to bind to multiple, unrelated classes of receptor with high affinity. Owing to the robustness of amide bond chemistry, the ability to explore extensive chemical diversity by incorporation of unnatural and natural amino acids, and the ability to explore conformational diversity, through the incorporation of various constraints, arrays of cyclic peptides can be tailored to broadly sample chemical diversity. We describe the combination of a safety catch linker with a directed-sorted procedure for the synthesis of large arrays of diverse cyclic peptides for high-throughput screening.