Drug discovery is aimed to design novel molecules with specific chemical properties for the treatment of targeting diseases. Generally, molecular optimization is one important step in drug discovery, which optimizes t...Drug discovery is aimed to design novel molecules with specific chemical properties for the treatment of targeting diseases. Generally, molecular optimization is one important step in drug discovery, which optimizes the physical and chemical properties of a molecule. Currently, artificial intelligence techniques have shown excellent success in drug discovery, which has emerged as a new strategy to address the challenges of drug design including molecular optimization, and drastically reduce the costs and time for drug discovery. We review the latest advances of molecular optimization in artificial intelligence-based drug discovery, including data resources, molecular properties, optimization methodologies, and assessment criteria for molecular optimization. Specifically, we classify the optimization methodologies into molecular mapping-based, molecular distribution matching-based, and guided search-based methods, respectively, and discuss the principles of these methods as well as their pros and cons. Moreover, we highlight the current challenges in molecular optimization and offer a variety of perspectives, including interpretability, multidimensional optimization, and model generalization, on potential new lines of research to pursue in future. This study provides a comprehensive review of molecular optimization in artificial intelligence-based drug discovery, which points out the challenges as well as the new prospects. This review will guide researchers who are interested in artificial intelligence molecular optimization.展开更多
Atomistic mechanisms of frictional energy dissipation have attracted significant attention.However,the dynamics of phonon excitation and dissipation remain elusive for many friction processes.Through systematic fast F...Atomistic mechanisms of frictional energy dissipation have attracted significant attention.However,the dynamics of phonon excitation and dissipation remain elusive for many friction processes.Through systematic fast Fourier transform(FFT)analyses of the frictional signals as a silicon tip sliding over a graphite surface at different angles and velocities,we experimentally demonstrate that friction mainly excites non-equilibrium phonons at the washboard frequency and its harmonics.Using molecular dynamics(MD)simulations,we further disclose the phononic origin of structural lubrication,i.e.,the drastic reduction of friction force as the contact angle between two commensurate surfaces changes.In commensurate contacting states,friction excites a large amount of phonons at the washboard frequency and many orders of its harmonics that perfectly match each other in the sliding tip and substrate,while for incommensurate cases,only limited phonons are generated at mismatched washboard frequencies and few low order harmonics in the tip and substrate.展开更多
Heterogeneous ice nucleation(HIN)on foreign surfaces plays a crucial role across a wide range of environmental and biological processes,and control of HIN is highly desirable.Functionalizing surfaces to control HIN po...Heterogeneous ice nucleation(HIN)on foreign surfaces plays a crucial role across a wide range of environmental and biological processes,and control of HIN is highly desirable.Functionalizing surfaces to control HIN poses interesting scientific challenges and holds great potential for technological impact.Here,we combine the ice nucleation tuning capability of polyelectrolytes withmussel-inspired adhesives to obtain robust surface functionalization with HIN control.展开更多
基金The National Natural Science Foundation of China,Grant/Award Numbers:62372204,62072206,62102158,61772381the Fundamental Research Funds for the Central Universities,Grant/Award Numbers:2662022JC004,2662021JC008。
文摘Drug discovery is aimed to design novel molecules with specific chemical properties for the treatment of targeting diseases. Generally, molecular optimization is one important step in drug discovery, which optimizes the physical and chemical properties of a molecule. Currently, artificial intelligence techniques have shown excellent success in drug discovery, which has emerged as a new strategy to address the challenges of drug design including molecular optimization, and drastically reduce the costs and time for drug discovery. We review the latest advances of molecular optimization in artificial intelligence-based drug discovery, including data resources, molecular properties, optimization methodologies, and assessment criteria for molecular optimization. Specifically, we classify the optimization methodologies into molecular mapping-based, molecular distribution matching-based, and guided search-based methods, respectively, and discuss the principles of these methods as well as their pros and cons. Moreover, we highlight the current challenges in molecular optimization and offer a variety of perspectives, including interpretability, multidimensional optimization, and model generalization, on potential new lines of research to pursue in future. This study provides a comprehensive review of molecular optimization in artificial intelligence-based drug discovery, which points out the challenges as well as the new prospects. This review will guide researchers who are interested in artificial intelligence molecular optimization.
基金National Natural Science Foundation of China(Grant Nos.52035003,52065037,51575104,and 52175161)the China Postdoctoral Science Foundation(Grant No.2021MD703810)+1 种基金the Postdoctoral Science Foundation of Gansu Academy of Sciences(Grant No.BSH202101)the Southeast University“Zhongying Young Scholars”Project for financial support.
文摘Atomistic mechanisms of frictional energy dissipation have attracted significant attention.However,the dynamics of phonon excitation and dissipation remain elusive for many friction processes.Through systematic fast Fourier transform(FFT)analyses of the frictional signals as a silicon tip sliding over a graphite surface at different angles and velocities,we experimentally demonstrate that friction mainly excites non-equilibrium phonons at the washboard frequency and its harmonics.Using molecular dynamics(MD)simulations,we further disclose the phononic origin of structural lubrication,i.e.,the drastic reduction of friction force as the contact angle between two commensurate surfaces changes.In commensurate contacting states,friction excites a large amount of phonons at the washboard frequency and many orders of its harmonics that perfectly match each other in the sliding tip and substrate,while for incommensurate cases,only limited phonons are generated at mismatched washboard frequencies and few low order harmonics in the tip and substrate.
文摘Heterogeneous ice nucleation(HIN)on foreign surfaces plays a crucial role across a wide range of environmental and biological processes,and control of HIN is highly desirable.Functionalizing surfaces to control HIN poses interesting scientific challenges and holds great potential for technological impact.Here,we combine the ice nucleation tuning capability of polyelectrolytes withmussel-inspired adhesives to obtain robust surface functionalization with HIN control.
