Mathematical biosciences and engineering : MBE
Sep 30, 2022
The development of new drugs is a long and costly process, Computer-aided drug design reduces development costs while computationally shortening the new drug development cycle, in which DTA (Drug-Target binding Affinity) prediction is a key step to s...
Artificial intelligence (AI) is a rapidly growing discipline in the field of chemical toxicology. Herein, we provide a broad overview of research presented at the Fall 2022 American Chemical Society meeting, highlighting how AI is being applied acros...
With advances in artificial intelligence (AI) methods, computer-aided drug design (CADD) has developed rapidly in recent years. Effective molecular representation and accurate property prediction are crucial tasks in CADD workflows. In this review, w...
Journal of chemical information and modeling
Sep 16, 2022
In molecular discovery and drug design, structure-property relationships and activity landscapes are often qualitatively or quantitatively analyzed to guide the navigation of chemical space. The roughness (or smoothness) of these molecular property l...
International journal of molecular sciences
Sep 8, 2022
In this study, we provide a systems biology method to investigate the carcinogenic mechanism of oral squamous cell carcinoma (OSCC) in order to identify some important biomarkers as drug targets. Further, a systematic drug discovery method with a dee...
Journal of chemical information and modeling
Sep 7, 2022
In recent years, machine learning (ML) models have been found to quickly predict various molecular properties with accuracy comparable to high-level quantum chemistry methods. One such example is the calculation of electrostatic potential (ESP). Diff...
Journal of chemical information and modeling
Jul 6, 2022
In recent years, molecular deep generative models have attracted much attention for its application in drug design. The data-driven molecular deep generative model approximates the high dimensional distribution of the chemical space through learning...
A recurrent neural network (RNN) is a machine learning model that learns the relationship between elements of an input series, in addition to inferring a relationship between the data input to the model and target output. Memory augmentation allows t...
Journal of chemical information and modeling
Jun 17, 2022
Creating a wide range of new compounds that not only have ideal pharmacological properties but also easily pass long-term toxicity evaluation is still a challenging task in current drug discovery. In this study, we developed a conditional generative ...
Journal of chemical information and modeling
Jun 2, 2022
To deliver more therapeutics to more patients more quickly and economically is the ultimate goal of pharmaceutical researchers. The advent and rapid development of artificial intelligence (AI), in combination with other powerful computational methods...