Recent Advancements in the Application of Artificial Intelligence in Drug Molecular Generation and Synthesis Planning DOI Creative Commons
Buyong Ma, Yiguo Wang,

Xingzi Li

et al.

Pharmaceutical Fronts, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 2, 2024

Abstract The design and synthesis of drug molecules is a pivotal stage in development that traditionally requires significant investment time finances. However, the integration artificial intelligence (AI) accelerates identification potential candidates, optimizes process, contributes to more informed decision-making. application AI molecular generation changing way researchers explore chemical space novel compounds. It process discovery materials science, enabling rapid exploration vast landscapes for promising candidates further experimental validation. predicting reaction products planning automation synthetic chemistry tasks, supports chemists making decisions during discovery. This paper reviewed recent advances two interrelated areas: routes. will provide insights into innovative ways which transforming traditional approaches predict its future progress these key fields.

Language: Английский

Syn-MolOpt: a synthesis planning-driven molecular optimization method using data-derived functional reaction templates DOI Creative Commons

Xiaodan Yin,

Xiaorui Wang, Zhenxing Wu

et al.

Journal of Cheminformatics, Journal Year: 2025, Volume and Issue: 17(1)

Published: March 2, 2025

Molecular optimization is a crucial step in drug development, involving structural modifications to improve the desired properties of candidates. Although many deep-learning-based molecular algorithms have been proposed and may perform well on benchmarks, they usually do not pay sufficient attention synthesizability molecules, resulting optimized compounds difficult be synthesized. To address this issue, we first developed general pipeline capable constructing functional reaction template library specific any property where predictive model can built. Based these templates, introduced Syn-MolOpt, synthesis planning-oriented method. During optimization, templates steer process towards by effectively transforming relevant fragments. In four diverse tasks, including two toxicity-related (GSK3β-Mutagenicity GSK3β-hERG) metabolism-related (GSK3β-CYP3A4 GSK3β-CYP2C19) multi-property optimizations, Syn-MolOpt outperformed three benchmark models (Modof, HierG2G, SynNet), highlighting its efficacy adaptability. Additionally, visualization synthetic routes for molecules confirms effectiveness optimization. Notably, Syn-MolOpt's robust performance scenarios with limited scoring accuracy demonstrates potential real-world applications. By considering both synthesizability, promises valuable tool Scientific contribution takes into account synthesis, allowing design property-specific libraries optimized, providing reference while optimizing targeted properties. universal workflow makes it suitable various types tasks.

Language: Английский

Citations

0
Local reaction condition optimization via machine learning DOI
Wenwei Song,

Honggang Sun

Journal of Molecular Modeling, Journal Year: 2025, Volume and Issue: 31(5)

Published: April 23, 2025

Language: Английский

Citations

0
Assessing Apparent Equilibrium Concentrations in Cementation of Trace Pd, Pt, Au, and Rh from Nitrate Solutions Using Mg, Al, Fe, and Zn DOI Creative Commons
Konrad Wojtaszek, Adrianna Pach, Tomasz Michałek

et al.

Metals, Journal Year: 2024, Volume and Issue: 14(9), P. 990 - 990

Published: Aug. 30, 2024

This study explores the impact of nitrate ions on efficiency cementing noble metals from diluted waste solutions at a temperature 30 °C. The research involved measuring effectiveness different (such as Zn, Al, Mg, and Fe) in presence by assessing change metal ion concentrations before after cementation process using spectrometric analysis. Initial ware Pt = 5 ppm, Au 7.5 Pd Rh 1 ppm. Kinetic studies revealed that 24 h is adequate to achieve apparent equilibrium with pH 2 M content. identified significant recovery losses for gold platinum solutions, underlining necessity nitrate-free recycling. Zinc magnesium were effective Rh, while aluminum was efficient reduction each condition. Complete removal not achieved any tested metal, indicating need alternative methods.

Language: Английский

Citations

1
Target-triggered catalytic hairpin assembly of miR-21/155/1 coupled with dsDNA-reporter amplified detection for prediction of clinically significant coronary artery disease DOI
Tiantian Wang, Ying Zhang, Hongna Su

et al.

Sensors and Actuators B Chemical, Journal Year: 2024, Volume and Issue: unknown, P. 137053 - 137053

Published: Nov. 1, 2024

Language: Английский

Citations

1
Recent Advancements in the Application of Artificial Intelligence in Drug Molecular Generation and Synthesis Planning DOI Creative Commons
Buyong Ma, Yiguo Wang,

Xingzi Li

et al.

Pharmaceutical Fronts, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 2, 2024

Abstract The design and synthesis of drug molecules is a pivotal stage in development that traditionally requires significant investment time finances. However, the integration artificial intelligence (AI) accelerates identification potential candidates, optimizes process, contributes to more informed decision-making. application AI molecular generation changing way researchers explore chemical space novel compounds. It process discovery materials science, enabling rapid exploration vast landscapes for promising candidates further experimental validation. predicting reaction products planning automation synthetic chemistry tasks, supports chemists making decisions during discovery. This paper reviewed recent advances two interrelated areas: routes. will provide insights into innovative ways which transforming traditional approaches predict its future progress these key fields.

Language: Английский

Citations

0