# An LCMS-guided bioanalytical approach for rational natural product library design and optimization > **NIH NIH R01** · SAN DIEGO STATE UNIVERSITY · 2024 · $265,497 ## Abstract Project Summary/Abstract Natural products are a mainstay of drug discovery, accounting for up to 50% of approved drugs either as direct natural molecules or as inspiration for synthetic molecules. High-throughput screening of compound libraries is a common starting point for drug development campaigns. The quality of these libraries is therefore a key determinant of high-throughput screening campaign success. Natural product compound library design is particularly challenging given redundancies in natural product production between isolates and greater costs of compound production and isolation. Evidence-based and scientifically rigorous methods to optimize natural product library design are therefore urgently required. In MPIs’ previous work, they demonstrated using the example of the fungus Alternaria that liquid chromatography-tandem mass spectrometry (LC- MS/MS)-based analysis of fungal extracts could reveal the minimal number of extracts to include in a chemical library, to achieve saturation of chemical diversity. Strikingly, this number could be as small as 39 isolate extracts, depending on the Alternaria clade. It is now necessary to demonstrate the broader utility of this bioanalytical approach, to the significant biological problem of high-throughput screening natural product chemical library design. In addition, the high-throughput nature of our approach enables the systematic and unbiased assessment of different natural product diversification approaches on elicited chemical diversity. Our proposal builds on MPI’s extensive expertise in metabolomics and small molecule characterization and natural product analysis. In addition, it is enabled by the MPI’s access to the large collection of fungal isolates from the University of Oklahoma Citizen Science Soil Collection Program. This collection currently totals >78,000 isolates from 893 fungal genera. Our central hypothesis is that our untargeted metabolomics method can be applied to generate specific rules of natural product library design and provide evidence to prove or disprove current dogma governing natural product library design. We will focus on three common library design approaches, in three independent aims. Aim 1 will focus on using our approach to demonstrate that comparable chemical diversity can be obtained from focused, rationally-designed natural product libraries, compared to random serendipitous discovery. Aim 2 will systematically assess the impact of co-culture on elicited chemical diversity, comparing sympatric vs allopatric co-culture systems. Aim 3 will systematically quantify the impact of environment-mimicking culture conditions such as soil or bacterial-derived signals, on elicited chemical diversity. Overall, our results will lead to validation of a new approach for rational natural product library design, with major implications for drug development. ## Key facts - **NIH application ID:** 10862659 - **Project number:** 5R01GM145649-04 - **Recipient organization:** SAN DIEGO STATE UNIVERSITY - **Principal Investigator:** Robert Henry Cichewicz - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $265,497 - **Award type:** 5 - **Project period:** 2022-09-05 → 2026-06-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10862659 ## Citation > US National Institutes of Health, RePORTER application 10862659, An LCMS-guided bioanalytical approach for rational natural product library design and optimization (5R01GM145649-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10862659. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*