INTRODUCTION: After the initial wave of antibiotic discovery, few novel classes of antibiotics have emerged, with the latest dating back to the 1980's. Furthermore, the pace of antibiotic drug discovery is unable to keep up with the increasing preval...
INTRODUCTION: Deep discriminative and generative neural-network models are becoming an integral part of the modern approach to ligand-based novel drug discovery. The variety of different architectures of neural networks, the methods of their training...
: Drug discovery is the process through which potential new compounds are identified by means of biology, chemistry, and pharmacology. Due to the high complexity of genomic data, AI techniques are increasingly needed to help reduce this and aid the a...
Novel drug discovery remains an enormous challenge, with various computer-aided drug design (CADD) approaches having been widely employed for this purpose. CADD, specifically the commonly used support vector machines (SVMs), can employ machine learni...
: Artificial intelligence systems based on neural networks (NNs) find rules for drug discovery according to training molecules, but first, the molecules need to be represented in certain ways. Molecular descriptors and fingerprints have been used as ...