Interest in docking technologies has grown parallel to the ever increasing number and
diversity of 3D models for macromolecular therapeutic targets. Structure-Based Virtual …

In this work, we propose a machine learning approach to generate novel molecules starting
from a seed compound, its three-dimensional (3D) shape, and its pharmacophoric features …

Peptide cyclization can improve stability, conformational constraint, and compactness.
However, apart from beta-turn structures, which are well incorporated into cyclic peptides …

The drug discovery process starts with in-silico exploration of chemicals and is now using
more and more machine learning to leverage the data held by pharmaceuticals …

Natural products (NPs) provide an almost unlimited repository of inspirations for new drug-
like molecules.[1–3] Various strategies to harness the full potential of natural products have …

Interference with the hERG potassium ion channel may cause cardiac arrhythmia and can
even lead to death. Over the last few decades, several drugs, already on the market, and …

Equol (EQ) is metabolized product of daidzein which is beneficial for health, related with
positive outcome in various diseases such as osteoporosis, cancers, menopausal …

Designing novel drugs is a complex process which requires finding molecules in a vast
chemical space that bind to a specific biomolecular target and have favorable physio …

The human hexokinase isoform II (HKII) is one of the important enzymes for dengue virus
(DENV) replication and thus has been suggested as a potential therapeutic target for DENV …

Deep Neural Networks and Embedding Methods in Drugs Interactions Analysis Page 1 Deep
Neural Networks and Embedding Methods in Drugs Interactions Analysis LIU, Pengfei A Thesis …