# Development and Testing of New Computational Methods for Ligand Discovery and Mechanism

> **NIH NIH R35** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2022 · $798,338

## Abstract

Abstract
Our long-term goal is to develop structure-based and chemoinformatic methods in ligand discovery, testing
these in experimental model systems and applying them to targets of biological interest. To give the reader a
sense of our direction, we sketch several questions within four broad foci:
A. Development of new docking methods and their testing in model systems like simplified cavity sites, where
individual terms may be disentangled. Several upcoming projects leverage the ultra-large libraries we
introduced in the last period, including: i. are bigger libraries always better, or at some library size do we
saturate? ii. As the library grows, are we still bounded by bio-like molecules, or do we diverge away from
these? How does this affect docking hit quality? iii. Can we treat libraries of tens-of-billions to trillions of
molecules with better methods and look-ahead pattern matching? We are also exploring iv. flexible receptor
docking in the model cavities, and v. treatment of ligand conformational and desolvation strain.
B. Turning the structure-based enterprise on its head, we return to the logic of classical pharmacology with
modern chemoinformatics, seeking to predict targets from their ligands. Leveraging work in the last period, we
i. Investigate if widely consumed molecules, such as neutraceuticals, have specific targets and ii. Use network
pharmacology to find molecules to modulate the human targets subverted by SARS-Cov-2 viral proteins.
C. Application of these methods to biologically interesting targets, often GPCRs. In the upcoming period, we i.
explore bespoke ultra-large libraries for amingergic GPCRs; ii. Extend domain of applicability to transporters;
iii. Seek chemical probes for the yeast mating-factor GPCR Ste2 to complement the power of yeast genetics.
D. The role of colloidal aggregation and phospholipidosis in early drug discovery. Projects in the upcoming
period investigate i. Exploiting colloidal aggregates for drug delivery; ii. Investigating the mechanism of
colloidal aggregation and its impact in early discovery; iii. Investigating a new phenomenon that may have
wide impact on cell-based ligand discovery, phospholipidosis.
This MIRA was previously funded by five grants, and its breadth reflects that. While ambitious, its pragmatism
is supported by the productivity of the last period and by extensive preliminary results.

## Key facts

- **NIH application ID:** 10406014
- **Project number:** 2R35GM122481-06
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Brian K Shoichet
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $798,338
- **Award type:** 2
- **Project period:** 2017-06-01 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10406014

## Citation

> US National Institutes of Health, RePORTER application 10406014, Development and Testing of New Computational Methods for Ligand Discovery and Mechanism (2R35GM122481-06). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10406014. Licensed CC0.

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