Abietic and dehydroabietic acid are interesting diterpenes with a highly diverse repertoire of associated bioactivities. They have, among others, shown antibacterial and antifungal activity, potentially valuable in the struggle against the increasing antimicrobial resistance and imminent antibiotic shortage. In this paper, we describe the synthesis of a set of 9 abietic and dehydroabietic acid derivatives containing amino acid side chains and their in vitro antimicrobial profiling against a panel of human pathogenic microbial strains. Furthermore, their in vitro cytotoxicity against mammalian cells was evaluated. The experimental results showed that the most promising compound was 10 [methyl N-(abiet-8,11,13-trien-18-yl)-d-serinate], with an MIC of 60μg/mL against Staphylococcus aureus ATCC 25923, and 8μg/mL against methicillin-resistant S. aureus, Staphylococcus epidermidis and Streptococcus mitis. The IC value for compound 10 against Balb/c 3T3 cells was 45μg/mL.

Supplementary data are available at Bioinformatics online.

Pumilol (1), a strobane diterpenoid, reported herein for the first time, was isolated from the bark of Pinus pumila (Pall.) Regel (Siberian Dwarf Pine or Japanese Stone Pine), along with 17 known compounds including serratane triterpenoids, not previously reported from this species, and four ferulate derivatives. The absolute configuration of pumilol was established using HR-ESI-MS, NMR, the DP4+ probabilities and by comparison of the experimental and calculated electronic circular dichroism (ECD) spectra. Labda-8(17),13-dien-15-oic acid (4), bornyl (E)-4-hydroxycinnamate (14) and bornyl (E)-ferulate (15) showed activity against S. aureus and/or E. faecalis with MIC values 12.5 - 50 μm.

High-throughput screening is an established technique in drug discovery and, as such, has also found its way into academia. High-throughput screening generates a considerable amount of data, which is why specific software is used for its analysis and management. The commercially available software packages are often beyond the financial limits of small-scale academic laboratories and, furthermore, lack the flexibility to fulfill certain user-specific requirements. We have developed a Python module, screening_mgmt, which is a lightweight tool for flexible data retrieval, analysis, and storage for different screening assays in one central database. The module reads custom-made analysis scripts and plotting instructions, and it offers a graphical user interface to import, modify, and display the data in a uniform manner. During the test phase, we used this module for the management of 10,000 data points of various origins. It has provided a practical, user-friendly tool for sharing and exchanging information between researchers.

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