Drug-discovery and drug-development endeavors are laborious, costly and time consuming.
These programs can take upward of 12 years and cost US $2.5 billion, with a failure rate of …

Drug discovery is adapting to novel technologies such as data science, informatics, and
artificial intelligence (AI) to accelerate effective treatment development while reducing costs …

Systematically identifying functional peptides is difficult owing to the vast combinatorial
space of peptide sequences. Here we report a machine-learning pipeline that mines the …

With the recent explosion of chemical libraries beyond a billion molecules, more efficient
virtual screening approaches are needed. The Deep Docking (DD) platform enables up to …

Due to their high target specificity and binding affinity, therapeutic antibodies are currently
the largest class of biotherapeutics. The traditional largely empirical antibody development …

The convergence of biology and computational science has ushered in a revolutionary era,
revolutionizing our understanding of biological systems and providing novel solutions to …

Antimicrobial resistance (AMR) has become more of a concern in recent decades,
particularly in infections associated with global public health threats. The development of …

Objective Breast cancer is a global health concern that demands attention. In our
contribution to addressing this disease, our study focuses on investigating a wireless micro …

Recent explosive growth of 'make-on-demand'chemical libraries brought unprecedented
opportunities but also significant challenges to the field of computer-aided drug discovery …

The COVID-19 pandemic has necessitated the development of reliable diagnostic methods
for accurately detecting the novel coronavirus and its variants. Deep learning (DL) …