Multiple sequence alignment (MSA) has evolved into a fundamental tool in the biological
sciences, playing a pivotal role in predicting molecular structures and functions. With broad …

Single-cell genomics, combined with advanced AI models, hold transformative potential for
understanding complex biological processes in plants. This article reviews deep-learning …

Predicting protein-small molecule binding sites, the initial step in structure-guided drug
design, remains challenging for proteins lacking experimentally derived ligand-bound …

Comparing and searching protein structures independent of primary sequence has proved
useful for remote homology detection, function annotation and protein classification. With the …

Engineering protein dynamics is a challenging and unsolved problem in protein design.
Loop transplantation or loop grafting has been previously employed to transfer dynamic …

Protein circular permutations are crucial for understanding protein evolution and
functionality. Traditional detection methods face challenges: sequence-based approaches …

Highlights•Traditional sequence similarity-based protein homology tools struggle to identify
homologs in the twilight zone.•New homolog detection tools that using protein language …

Biological foundation models hold significant promise for deciphering complex biological
functions. However, evaluating their performance on functional tasks remains challenging …

Background Due to the recent revolution of artificial intelligence (AI), AI-enabled large
language models (LLMs) have flourished and started to be applied in various sectors of …