Chemical similarity searching is a basic research tool that can be used to find small molecules which are similar in shape to known active molecules. Despite its popularity, the retrieval of local molecular features that are critical to functional activity related to target binding often fails. To overcome this limitation, we developed a novel machine learning-based chemical binding similarity score by using various evolutionary relationships of binding targets. The chemical similarity was defined by the probability of chemical compounds binding to identical targets. Comprehensive and heterogeneous multiple target-binding chemical data were integrated into a paired data format and processed using multiple classification similarity-learning models with various levels of target evolutionary information. Encoding evolutionary information to chemical compounds through their binding targets substantially expanded available chemical-target interaction data and significantly improved model performance. The output probability of our integrated model, referred to as ensemble evolutionary chemical binding similarity (ensECBS), was effective for finding hidden chemical relationships. The developed method can serve as a novel chemical similarity tool that uses evolutionarily conserved target binding information.

Tyrosinase is an enzyme that plays a crucial role in the melanogenesis of humans and the browning of food products. Thus, tyrosinase inhibitors that are useful to the cosmetic and food industries are required. In this study, we have used evolutionary chemical binding similarity (ECBS) to screen a virtual chemical database for human tyrosinase, which resulted in seven potential tyrosinase inhibitors confirmed through the tyrosinase inhibition assay. The tyrosinase inhibition percentage for three of the new actives was over 90% compared to 61.9% of kojic acid. From the structural analysis through pharmacophore modeling and molecular docking with the human tyrosinase model, the pi–pi interaction of tyrosinase inhibitors with conserved His367 and the polar interactions with Asn364, Glu345, and Glu203 were found to be essential for tyrosinase–ligand interactions. The pharmacophore features and the docking models showed high consistency, revealing the possible essential binding interactions of inhibitors to human tyrosinase. We have also presented the activity cliff analysis that successfully revealed the chemical features related to substantial activity changes found in the new tyrosinase inhibitors. The newly identified inhibitors and their structure–activity relationships presented here will help to identify or design new human tyrosinase inhibitors.

Since its first report in the Middle East in 2012, the Middle East respiratory syndrome-coronavirus (MERS-CoV) has become a global concern due to the high morbidity and mortality of individuals infected with the virus. Although the majority of MERS-CoV cases have been reported in Saudi Arabia, the overall risk in areas outside the Middle East remains significant as inside Saudi Arabia. Additional pandemics of MERS-CoV are expected, and thus novel tools and reagents for therapy and diagnosis are urgently needed. Here, we used phage display to develop novel monoclonal antibodies (mAbs) that target MERS-CoV. A human Fab phage display library was panned against the S2 subunit of the MERS-CoV spike protein (MERS-S2P), yielding three unique Fabs (S2A3, S2A6, and S2D5). The Fabs had moderate apparent affinities (Half maximal effective concentration (EC₅₀ = 123–421 nM) for MERS-S2P, showed no cross-reactivity to spike proteins from other CoVs, and were non-aggregating and thermostable (T_m = 61.5–80.4 °C). Reformatting the Fabs into IgGs (Immunoglobulin Gs) greatly increased their apparent affinities (K_D = 0.17–1.2 nM), presumably due to the effects of avidity. These apparent affinities were notably higher than that of a previously reported anti-MERS-CoV S2 reference mAb (K_D = 8.7 nM). Furthermore, two of the three mAbs (S2A3 and S2D5) bound only MERS-CoV (Erasmus Medical Center (EMC)) and not other CoVs, reflecting their high binding specificity. However, the mAbs lacked MERS-CoV neutralizing activity. Given their high affinity, specificity, and desirable stabilities, we anticipate that these anti-MERS-CoV mAbs would be suitable reagents for developing antibody-based diagnostics in laboratory or hospital settings for point-of-care testing.

Algae are unique natural products that can produce various types of biologically active compounds. The 70% ethanol extract of brown algae Sargassum macrocarpum collected from the East Sea of Korea inhibited human monoamine oxidases A and B enzymes (hMAO-A and hMAO-B) at a 50 μg/mL concentration. The bioassay-guided isolation was performed through solid-phase extraction and the Sepbox system followed by serial high-performance liquid chromatography on the reverse phase condition, resulting in the identification of two new monocyclic terpenoid lactones, sargassumins A and B (1 and 2). The planar structures of the compounds were determined by a combination of spectroscopic data. The absolute configurations were determined by the interpretation of circular dichroism data. Compound 1 exhibited mild hMAO-A inhibition (42.18 ± 2.68% at 200 μM) and docked computationally into the active site of hMAO-A (−8.48 kcal/mol). Although compound 2 could not be tested due to insufficient quantity, it docked better into hMAO-A (−9.72 kcal/mol). Therefore, the above results suggest that this type of monocyclic terpenoid lactone could be one of the potential lead compounds for the treatment of psychiatric or neurological diseases.