Graph representation learning aims to effectively encode high-dimensional sparse graph-
structured data into low-dimensional dense vectors, which is a fundamental task that has …

Computer-aided drug design (CADD) is one of the pivotal approaches to contemporary pre-
clinical drug discovery, and various computational techniques and software programs are …

Efficient identification of drug mechanisms of action remains a challenge. Computational
docking approaches have been widely used to predict drug binding targets; yet, such …

In silico tools, such as molecular docking, are widely applied to study interactions and
binding affinity of biological activity of proteins and peptides. However, restricted sampling of …

In recent years, the use of machine learning (ML) in computational chemistry has enabled
numerous advances previously out of reach due to the computational complexity of …

The drug development process is a major challenge in the pharmaceutical industry since it
takes a substantial amount of time and money to move through all the phases of developing …

Background In recent years, the antioxidant capacity of plant protein-derived peptides has
been depicted in a growing number of studies. Plant proteins have been considered as the …

X-linked inhibitor of apoptosis protein (XIAP) is a member of inhibitor of apoptosis protein
(IAP) family responsible for neutralizing the caspases-3, caspases-7, and caspases-9 …

Molecular docking is an established in silico structure-based method widely used in drug
discovery. Docking enables the identification of novel compounds of therapeutic interest …

Food-derived bioactive peptides (FBPs) are gaining interest due to their great potential in
agricultural byproduct valorization and high-activity peptide screening. The introduction of …