Artificial intelligence and machine learning‐aided drug discovery in central nervous system diseases: State‐of‐the‐arts and future directions
Neurological disorders significantly outnumber diseases in other therapeutic areas.
However, develo** drugs for central nervous system (CNS) disorders remains the most …
However, develo** drugs for central nervous system (CNS) disorders remains the most …
Artificial intelligence and machine-learning approaches in structure and ligand-based discovery of drugs affecting central nervous system
CNS disorders are indications with a very high unmet medical needs, relatively smaller
number of available drugs, and a subpar satisfaction level among patients and caregiver …
number of available drugs, and a subpar satisfaction level among patients and caregiver …
Principles of ice-free cryopreservation by vitrification
GM Fahy, B Wowk - Cryopreservation and freeze-drying protocols, 2021 - Springer
Vitrification is an alternative to cryopreservation by freezing that enables hydrated living cells
to be cooled to cryogenic temperatures in the absence of ice. Vitrification simplifies and …
to be cooled to cryogenic temperatures in the absence of ice. Vitrification simplifies and …
Hybridizing feature selection and feature learning approaches in QSAR modeling for drug discovery
I Ponzoni, V Sebastián-Pérez, C Requena-Triguero… - Scientific reports, 2017 - nature.com
Quantitative structure–activity relationship modeling using machine learning techniques
constitutes a complex computational problem, where the identification of the most …
constitutes a complex computational problem, where the identification of the most …
Quantum artificial neural network approach to derive a highly predictive 3D-QSAR model for blood–brain barrier passage
T Kim, BH You, S Han, HC Shin, KC Chung… - International journal of …, 2021 - mdpi.com
A successful passage of the blood–brain barrier (BBB) is an essential prerequisite for the
drug molecules designed to act on the central nervous system. The logarithm of blood–brain …
drug molecules designed to act on the central nervous system. The logarithm of blood–brain …
Peptidic antifreeze materials: prospects and challenges
R Surís-Valls, IK Voets - International Journal of Molecular Sciences, 2019 - mdpi.com
Necessitated by the subzero temperatures and seasonal exposure to ice, various organisms
have developed a remarkably effective means to survive the harsh climate of their natural …
have developed a remarkably effective means to survive the harsh climate of their natural …
Derivation of Highly Predictive 3D-QSAR Models for hERG Channel Blockers Based on the Quantum Artificial Neural Network Algorithm
T Kim, KC Chung, H Park - Pharmaceuticals, 2023 - mdpi.com
The hERG potassium channel serves as an annexed target for drug discovery because the
associated off-target inhibitory activity may cause serious cardiotoxicity. Quantitative …
associated off-target inhibitory activity may cause serious cardiotoxicity. Quantitative …
Data-driven discovery of potent small molecule ice recrystallisation inhibitors
Controlling the formation and growth of ice is essential to successfully cryopreserve cells,
tissues and biologics. Current efforts to identify materials capable of modulating ice growth …
tissues and biologics. Current efforts to identify materials capable of modulating ice growth …
Synthesis, biological evaluation and molecular docking study of N-(2-methoxyphenyl)-6-((4-nitrophenyl) sulfonyl) benzamide derivatives as potent HIV-1 Vif …
M Zhou, RH Luo, XY Hou, RR Wang, GY Yan… - European journal of …, 2017 - Elsevier
Viral infectivity factor (Vif) is protective against APOBEC3G (A3G)-mediated viral cDNA
hypermutations, and development of molecules that inhibit Vif mediated A3G degradation is …
hypermutations, and development of molecules that inhibit Vif mediated A3G degradation is …
Predicting the electrochemical properties of lithium-ion battery electrode materials with the quantum neural network algorithm
Discovery of new inorganic solid materials can be accelerated with the aid of a reliable
computational tool for predicting the associated electrochemical properties. Hence, we …
computational tool for predicting the associated electrochemical properties. Hence, we …