Patent ID: 6834239
Filing Date: 2004-12-21
Classification: B01J,G06N,G16C

Abstract:
A method for determining properties of products from a combinatorial chemical library P using features of their respective building blocks, the method comprising the steps of:(1) determining at least one feature for each building block in the combinatorial library P, {aijk, i=1,2, . . . , r; j=1,2, . . . , ri; k=1,2, . . . , ni}, wherein r represents the number of variation sites in the combinatorial library, ri represents the number of building blocks at the i-th variation site, and ni represents the number of features used to characterize each building block at the i-th variation site; (2) selecting a training subset of products {pi, i=1,2, . . . , m; pi &egr;P} from the combinatorial library P; (3) determining q properties for each compound pi in the selected training subset of products, wherein yi {yij, i=1,2, . . . , m, j=1,2, . . . , q} represents the determined properties of compound pi, and wherein q is greater or equal to one; (4) identifying, for each product pi of the training subset of products, the corresponding building blocks {tij, tij=1,2, . . . , rj, j=1,2, . . . , r} and concatenating their features determined in step (1) into a single vector {xi=a1ti1|a2ti2|artir}; (5) using a supervised machine learning approach to infer a mapping function Æ’ that transforms input values xi, to output values yi, from the input/output pairs in the training set T={(xi, yi), i=1,2, . . . , m}; (6) identifying, after the mapping function Æ’ is determined, for a product pz&egr;P, the corresponding building blocks {tzj, j=1, 2, . . . , r} and concatenating their features, a1tz1, a2t21, . . . , artzr, into a single vector {xz=a1t1|a2t2| . . . |artr}, and (7) mapping xzâ†’yz, using the mapping function Æ’ determined in step (5), wherein yz represents the properties of product pz.