Unknown

Dataset Information

0

Combinatorial computational method gives new picomolar ligands for a known enzyme.


ABSTRACT: Combinatorial small molecule growth algorithm was used to design inhibitors for human carbonic anhydrase II. Two enantiomeric candidate molecules were predicted to bind with high potency (with R isomer binding stronger than S), but in two distinct conformations. The experiments verified that computational predictions concerning the binding affinities and the binding modes were correct for both isomers. The designed R isomer is the best-known inhibitor (K(d) approximately 30 pM) of human carbonic anhydrase II.

SUBMITTER: Grzybowski BA 

PROVIDER: S-EPMC122179 | biostudies-literature | 2002 Feb

REPOSITORIES: biostudies-literature

altmetric image

Publications

Combinatorial computational method gives new picomolar ligands for a known enzyme.

Grzybowski Bartosz A BA   Ishchenko Alexey V AV   Kim Chu-Young CY   Topalov George G   Chapman Robert R   Christianson David W DW   Whitesides George M GM   Shakhnovich Eugene I EI  

Proceedings of the National Academy of Sciences of the United States of America 20020129 3


Combinatorial small molecule growth algorithm was used to design inhibitors for human carbonic anhydrase II. Two enantiomeric candidate molecules were predicted to bind with high potency (with R isomer binding stronger than S), but in two distinct conformations. The experiments verified that computational predictions concerning the binding affinities and the binding modes were correct for both isomers. The designed R isomer is the best-known inhibitor (K(d) approximately 30 pM) of human carbonic  ...[more]

Similar Datasets

| S-EPMC1636520 | biostudies-literature
| S-EPMC6071824 | biostudies-other
| S-EPMC2836207 | biostudies-literature
| S-EPMC6503962 | biostudies-literature
| S-EPMC7187524 | biostudies-literature
| S-EPMC7221819 | biostudies-literature
| S-EPMC5431009 | biostudies-literature
| S-EPMC2522373 | biostudies-literature
| S-EPMC4136388 | biostudies-literature
| S-EPMC6369663 | biostudies-literature