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SUMMARY:AI-based Smart Molecular Design
DTSTART;VALUE=DATE-TIME:20191108T042000Z
DTEND;VALUE=DATE-TIME:20191108T044000Z
DTSTAMP;VALUE=DATE-TIME:20260724T113235Z
UID:indico-contribution-37@sshep.snu.ac.kr
DESCRIPTION:Speakers: Woo Youn Kim (Chemistry\, KAIST)\nThe ultimate goal 
 of chemistry is to make new molecules with desired properties. It is chall
 enging because chemical space is very large and discrete with a wide varie
 ty of molecules. For example\, there are only 108 molecules synthesized as
  potential drug candidates\, but 1060 molecules are estimated to be existi
 ng. High-throughput virtual screening approach has attracted great attenti
 on but still requires large costs and time. In this talk\, we propose to u
 se a molecular generative model based on deep learning algorithm as an alt
 ernative. It is specialized in controlling multiple molecular properties s
 imultaneously\, embedding them in namely the latent space. As a proof of c
 oncept\, we will show that it can be used to generate a number of molecule
 s as drugs with specific properties. We also apply it to design of new mol
 ecules with promising binding energy for a specific target protein and use
  them as potential drug candidates that are not in the database.\n\nhttps:
 //sshep.snu.ac.kr/event/107/contributions/37/
LOCATION:Seoul National University\, College of Natural Sciences\, Buildin
 g 25-1 국제회의실 (International Conference Hall)
URL:https://sshep.snu.ac.kr/event/107/contributions/37/
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