Since its establishment in 2013, BioLiP has become one of the widely used resources for protein–ligand interactions. Nevertheless, several known issues occurred with it over the past decade. For example, the protein–ligand interactions are represented in the form of single chain-based tertiary structures, which may be inappropriate as many interactions involve multiple protein chains (known as quaternary structures). We sought to address these issues, resulting in Q-BioLiP, a comprehensive resource for quaternary structure-based protein–ligand interactions. The major features of Q-BioLiP include: (1) representing protein structures in the form of quaternary structures rather than single chain-based tertiary structures; (2) pairing DNA/RNA chains properly rather than separation; (3) providing both experimental and predicted binding affinities; (4) retaining both biologically relevant and irrelevant interactions to alleviate the wrong justification of ligands’ biological relevance; and (5) developing a new quaternary structure-based algorithm for the modelling of protein–ligand complex structure. With these new features, Q-BioLiP is expected to be a valuable resource for studying biomolecule interactions, including protein–small molecule interaction, protein–metal ion interaction, protein–peptide interaction, protein–protein interaction, protein–DNA/RNA interaction, and RNA–small molecule interaction. Q-BioLiP is freely available at https://yanglab.qd.sdu.edu.cn/Q-BioLiP/.

Protein structure prediction has been transformed by AlphaFold2 and related systems; however, accurately modeling protein−ligand interactions remains a major challenge. Template-based prediction using homologous structures remains a powerful strategy. Here, we introduce COACH-D 2.0, a substantially enhanced template-based method for predicting protein−ligand binding sites. This upgrade features three key advances: (1) integration of multimeric templates from Q-BioLiP into our in-house library, (2) a new multimeric structure processing module enabling binding site prediction for protein complexes, and (3) an efficient template screening strategy that significantly boosts both prediction speed and accuracy. Evaluations against the previous version and leading methods on three benchmark datasets demonstrate the superior performance of COACH-D 2.0. The server is freely accessible at https://yanglab.qd.sdu.edu.cn/COACH-D/.

Identifying structurally similar proteins from large-scale databases is a fundamental challenge in structural bioinformatics. The recent release of millions of predicted structures by AlphaFold2 presents unprecedented scale and efficiency challenges for existing tools. To address this, we introduce the mTM-align2 server, a significantly upgraded version of mTM-align. This new platform is capable of searching both monomeric and multimeric structures against a comprehensive database of approximately 3 million entries in seconds. mTM-align2 achieves a two- to three-fold increase in search speed while maintaining accuracy comparable to that of other state-of-the-art methods. The server is available at https://yanglab.qd.sdu.edu.cn/mTM-align/.