Artificial intelligence (AI)-based predictive models are being used to foster a precision
medicine approach to treat complex chronic diseases such as autoimmune and …

Petro-plastic wastes cause serious environmental contamination that require effective
solutions. Developing alternatives to petro-plastics and exploring feasible degrading …

Transcription factor binding across the genome is regulated by DNA sequence and
chromatin features. However, it is not yet possible to quantify the impact of chromatin context …

Protein engineering is essential for altering the substrate scope, catalytic activity and
selectivity of enzymes for applications in biocatalysis. However, traditional approaches, such …

Molecular simulation has been widely used to study microbial proteins' structural
composition and dynamic properties, such as volatility, flexibility, and stability at the …

Tyrosine kinases and SH2 (phosphotyrosine recognition) domains have binding specificities
that depend on the amino acid sequence surrounding the target (phospho) tyrosine residue …

Recent rapid expansion of make‐on‐demand, purchasable, chemical libraries comprising
dozens of billions or even trillions of molecules has challenged the efficient application of …

A goal of unsupervised machine learning is to build representations of complex high-
dimensional data, with simple relations to their properties. Such disentangled …

Background and objective Recent studies have emphasized the significance of
computational in silico drug-target binding affinity (DTA) prediction in the field of drug …

Structure-based drug design (SBDD) utilizes the three-dimensional geometry of proteins to
identify potential drug candidates. Traditional methods, grounded in physicochemical …