Protein domain-based prediction of drug/compound-target interactions and experimental validation on LIM kinases.

Predictive approaches such as virtual screening have been used in drug discovery with the objective of reducing developmental time and costs. Current machine learning and network-based approaches have issues related to generalization, usability, or model interpretability, especially due to the complexity of target proteins' structure/function, and bias in system training datasets. Here, we propose a new method "DRUIDom" (DRUg Interacting Domain prediction) to identify bio-interactions between drug candidate compounds and targets by utilizing the domain modularity of proteins, to overcome problems associated with current approaches. DRUIDom is composed of two methodological steps. First, ligands/compounds are statistically mapped to structural domains of their target proteins, with the aim of identifying their interactions. As such, other proteins containing the same mapped domain or domain pair become new candidate targets for the corresponding compounds. Next, a million-scale dataset of small molecule compounds, including those mapped to domains in the previous step, are clustered based on their molecular similarities, and their domain associations are propagated to other compounds within the same clusters. Experimentally verified bioactivity data points, obtained from public databases, are meticulously filtered to construct datasets of active/interacting and inactive/non-interacting drug/compound-target pairs (~2.9M data points), and used as training data for calculating parameters of compound-domain mappings, which led to 27,032 high-confidence associations between 250 domains and 8,165 compounds, and a finalized output of ~5 million new compound-protein interactions. DRUIDom is experimentally validated by syntheses and bioactivity analyses of compounds predicted to target LIM-kinase proteins, which play critical roles in the regulation of cell motility, cell cycle progression, and differentiation through actin filament dynamics. We showed that LIMK-inhibitor-2 and its derivatives significantly block the cancer cell migration through inhibition of LIMK phosphorylation and the downstream protein cofilin. One of the derivative compounds (LIMKi-2d) was identified as a promising candidate due to its action on resistant Mahlavu liver cancer cells. The results demonstrated that DRUIDom can be exploited to identify drug candidate compounds for intended targets and to predict new target proteins based on the defined compound-domain relationships. Datasets, results, and the source code of DRUIDom are fully-available at: https://github.com/cansyl/DRUIDom.

Distinct roles of four gelsolin-like domains of Caenorhabditis elegans gelsolin-like protein-1 in actin filament severing, barbed end capping, and phosphoinositide binding.

Caenorhabditis elegans gelsolin-like protein-1 (GSNL-1) is a new member of the gelsolin family of actin regulatory proteins [Klaavuniemi, T., Yamashiro, S., and Ono, S. (2008) J. Biol. Chem. 283, 26071-26080]. It is an unconventional gelsolin-related protein with four gelsolin-like (G) domains (G1-G4), unlike typical gelsolin-related proteins with three or six G domains. GSNL-1 severs actin filaments and caps the barbed end in a calcium-dependent manner similar to that of gelsolin. In contrast, GSNL-1 has properties different from those of gelsolin in that it remains bound to F-actin and does not nucleate actin polymerization. To understand the mechanism by which GSNL-1 regulates actin dynamics, we investigated the domain-function relationship of GSNL-1 by analyzing activities of truncated forms of GSNL-1. G1 and the linker between G1 and G2 were sufficient for actin filament severing, whereas G1 and G2 were required for barbed end capping. The actin severing activity of GSNL-1 was inhibited by phosphatidylinositol 4,5-bisphosphate (PIP2), and a PIP2-sensitive domain was mapped to G1 and G2. At least two actin-binding sites were detected: a calcium-dependent G-actin-binding site in G1 and a calcium-independent G- and F-actin-binding site in G3 and G4. These results reveal both conserved and different utilization of G domains between C. elegans GSNL-1 and mammalian gelsolin for actin regulatory functions.