… deep learning architectures that we think deserve special attention and consideration for drug
design and discovery: … Many more deep learning approaches have been conceived, and …

… , deep neural networks can automatically learn … discovery with DL methods in detail, we
discuss deep neural networks (DNNs), DL with CNN layers, DL with RNN layers, hybrid learning, …

… the most successful implementations of the deep learning (DL) … deep learning architectures
has emerged as the first attempted technologies to address AI challenges (4). Deep learning …

… an inverse design model based on a deep encoder-decoder architecture for targeted
molecular design. Inspired by neural machine language translation, the deep neural network …

… Deep Learning Deep learning methods can be described as a class of representation-learning
techniques that are able to discover, from the raw data, multiple-level of representations …

… the implementation of artificial intelligence and deep learning in this field. Moreover… deep
learning advancements provide an excellent opportunity for rational drug design and discovery …

… Some popular deep learning architectures are introduced in the current study. … in drug
discovery. Examples will be discussed covering bioactivity prediction, de novo molecular design, …

… From source identification to lead discovery and medicinal … Discovery and design approach,
both demand automation, … The impact of DL in the workflow of drug discovery, design, and …

… design of polycrystalline structures that fracture in precisely controllable ways. Our results can
specifically be applied to the design of … training conditions to discover new mechanisms of …

… now provides a guide for early-stage drug design and discovery in the current big data era.
… Here, we review current state-of-the-art deep-learning studies in the context of drug discovery …