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From Single-Step Edit Response to Multi-Step Molecular Optimization

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Haojie Rao (School of Computer Science, Wuhan University, Wuhan, China), Kun Li (School of Computer Science, Wuhan University, Wuhan, China), Yida Xiong (School of Computer Science, Wuhan University, Wuhan, China), Jiameng Chen (School of Computer Science, Wuhan University, Wuhan, China), Wenbin Hu (School of Computer Science, Wuhan University, Wuhan, China), Yizhen Zheng (Department of Data Science and Artificial Intelligence, Monash University, Victoria, Australia), Jiajun Yu (College of Computer Science and Technology, Zhejiang University, Hangzhou, China), Duanhua Cao (School of Life Sciences and Technology, Tongji University, Shanghai, China)

๐Ÿ’ก ๊ฐœ์š”

์ด ๋…ผ๋ฌธ์€ ํŠน์ • ์†์„ฑ ๋ณ€ํ™”๋ฅผ ๋ชฉํ‘œ๋กœ ๋ถ„์ž๋ฅผ ํŽธ์ง‘ํ•˜๋Š” ์กฐ๊ฑด๋ถ€ ๋ถ„์ž ์ตœ์ ํ™” ๋ฌธ์ œ๋ฅผ ๋‹ค๋ฃน๋‹ˆ๋‹ค. ๊ธฐ์กด ๋ฐฉ๋ฒ•๋ก ์€ ๊ฐ๋… ํ•™์Šต๊ณผ ์‹ค์ œ ๊ฒฐ์ • ๊ฐ„์˜ ๋ถˆ์ผ์น˜๋กœ ์ธํ•ด ๋ถˆ์•ˆ์ •ํ•˜๋‹ค๋Š” ๋ฌธ์ œ๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ์—ˆ๋Š”๋ฐ, ์ด๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ์ œ์•ˆ๋œ SMER-Opt๋Š” ๋‹จ์ผ ๋‹จ๊ณ„ ํŽธ์ง‘ ์‘๋‹ต ์˜ˆ์ธก๊ธฐ(SMER)์™€ ์ด๋ฅผ ์กฐํ•ฉํ•˜๋Š” ๋‹ค๋‹จ๊ณ„ ๊ณ„ํš๊ธฐ๋ฅผ ๊ฒฐํ•ฉํ•ฉ๋‹ˆ๋‹ค. ์ด ์ ‘๊ทผ ๋ฐฉ์‹์€ ์•ฝํ•˜๊ฒŒ ๊ด€๋ จ๋œ ๋ถ„์ž ์Œ์—์„œ ์ตœ์†Œ ํŽธ์ง‘ ๋‹จ์œ„๋ฅผ ์ถ”์ถœํ•˜๊ณ , ์ด๋ฅผ ํ†ตํ•ด ์ตœ์ข… ์†์„ฑ ์ฃผ์„์„ ๊ณผ์ • ์ˆ˜์ค€ ๊ฐ๋…์œผ๋กœ ์ „ํ™˜ํ•˜์—ฌ ์žฌ์‚ฌ์šฉ ๊ฐ€๋Šฅํ•œ ํŽธ์ง‘ ํ”„๋กฌํ”„ํŠธ๋ฅผ ์ƒ์„ฑํ•ฉ๋‹ˆ๋‹ค.

๐Ÿ”‘ ์‹œ์‚ฌ์  ๋ฐ ํ•œ๊ณ„

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์‹œ์‚ฌ์  1: ์†์„ฑ ๋ณ€ํ™”๋ฅผ ๋ชฉํ‘œ๋กœ ํ•˜๋Š” ๋ถ„์ž ํŽธ์ง‘์—์„œ ์‹ค์ œ ๊ฒฐ์ • ํ”„๋กœ์„ธ์Šค๋ฅผ ํšจ๊ณผ์ ์œผ๋กœ ๋ชจ๋ธ๋งํ•˜๊ธฐ ์œ„ํ•ด ๋‹จ์ผ ๋‹จ๊ณ„ ํŽธ์ง‘ ์‘๋‹ต ์˜ˆ์ธก๊ณผ ๋‹ค๋‹จ๊ณ„ ๊ณ„ํš์„ ํ†ตํ•ฉํ•˜๋Š” ์ƒˆ๋กœ์šด ์ ‘๊ทผ ๋ฐฉ์‹์„ ์ œ์‹œํ•ฉ๋‹ˆ๋‹ค.
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์‹œ์‚ฌ์  2: ์•ฝํ•˜๊ฒŒ ๊ด€๋ จ๋œ ๋ถ„์ž ์Œ์—์„œ ์ตœ์†Œ ํŽธ์ง‘ ๋‹จ์œ„๋ฅผ ์ถ”์ถœํ•˜๊ณ  ์ด๋ฅผ ๊ณผ์ • ์ˆ˜์ค€ ๊ฐ๋…์œผ๋กœ ์ „ํ™˜ํ•จ์œผ๋กœ์จ ๋ฐ์ดํ„ฐ ํšจ์œจ์„ฑ๊ณผ ํ•™์Šต ๊ฐ€๋Šฅํ•œ ํŽธ์ง‘ ํ”„๋กฌํ”„ํŠธ์˜ ์žฌ์‚ฌ์šฉ์„ฑ์„ ํ–ฅ์ƒ์‹œํ‚ต๋‹ˆ๋‹ค.
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ํ•œ๊ณ„์  ๋˜๋Š” ํ–ฅํ›„ ๊ณผ์ œ: ์ œ์•ˆ๋œ ๋ฐฉ๋ฒ•๋ก ์˜ ์„ฑ๋Šฅ์ด ๋‹ค์–‘ํ•œ ๋ถ„์ž ์†์„ฑ ๋ฐ ๋ณต์žกํ•œ ํŽธ์ง‘ ์‹œ๋‚˜๋ฆฌ์˜ค์—์„œ ์–ด๋–ป๊ฒŒ ์ผ๋ฐ˜ํ™”๋˜๋Š”์ง€์— ๋Œ€ํ•œ ์ถ”๊ฐ€์ ์ธ ๊ฒ€์ฆ์ด ํ•„์š”ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๋˜ํ•œ, ์‹ค์ œ ํ™”ํ•™์  ์ œ์•ฝ ์กฐ๊ฑด์„ ๋” ์ •๊ตํ•˜๊ฒŒ ํ†ตํ•ฉํ•˜๊ธฐ ์œ„ํ•œ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
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