AI and computational chemistry-accelerated development of an alotaketal analogue with conventional PKC selectivity-Reference-Cited by-同舟云学术

AI and computational chemistry-accelerated development of an alotaketal analogue with conventional PKC selectivity

Published:2022 Issue:47 Volume:58 Page:6693-6696
ISSN:1359-7345
Container-title:Chemical Communications
language:en
Short-container-title:Chem. Commun.

Author:

Maki Jumpei¹^ORCID,Oshimura Asami¹,Tsukano Chihiro¹^ORCID,Yanagita Ryo C.²^ORCID,Saito Yutaka³⁴,Sakakibara Yasubumi⁵,Irie Kazuhiro¹^ORCID

Affiliation:

1. Division of Food Science and Biotechnology, Graduate School of Agriculture, Kyoto University, Kyoto, 606-8502, Japan

2. Department of Applied Biological Science, Faculty of Agriculture, Kagawa University, Kagawa, 761-0795, Japan

3. Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, 135-0064, Japan

4. AIST-Waseda University Computational Bio Big-Data Open Innovation Laboratory (CBBD-OIL), 3-4-1 Okubo, Shinjuku-ku, Tokyo, 169-8555, Japan

5. Department of Biosciences and Informatics, Keio University, Kanagawa, 223-8522, Japan

Abstract

We have designed and synthesized a new PKC ligand with a novel skeleton based on alotaketals through in silico screening, docking analysis, and molecular dynamics simulation. The new ligand has a higher affinity for PKCα-C1A than for PKCδ-C1B.

Funder

Japan Society for the Promotion of Science

Publisher

Royal Society of Chemistry (RSC)

Subject

Materials Chemistry,Metals and Alloys,Surfaces, Coatings and Films,General Chemistry,Ceramics and Composites,Electronic, Optical and Magnetic Materials,Catalysis

Link

http://pubs.rsc.org/en/content/articlepdf/2022/CC/D2CC01759H

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