# Integrated Resource for Protein Recognition Studies

> **NIH NIH R01** · UNIVERSITY OF KANSAS LAWRENCE · 2022 · $326,924

## Abstract

Project Summary
Macromolecular interactions are the basis of cellular processes. Structural characterization of these interactions
is important for better understanding of these processes and for our ability to manipulate them. The number of
macromolecular interactions in a cell is significantly larger than the number of individual macromolecules.
Structures of their assemblies are more difficult to determine experimentally than that of the individual molecules,
which further emphasizes the role of modeling in reconstruction of life processes. The project will advance our
understanding of macromolecular interaction and will facilitate development of better tools for their modeling.
The Specific Aims of the project are: (1) Resources for development of docking techniques, (2) Resources for
knowledge-based docking, and (3) Assessment of predicted interactions and CAPRI community-wide
experiment. Our long-term goals are: (a) development of resources and tools for reliable cell-scale modeling of
macromolecular interactions, which will account for dynamic changes in the molecular structures and kinetics of
association, and (b) application of these resources and tools to structural modeling of a cell, a new frontier and
a grand challenge of computational structural biology. The focus of the proposal is further development of the
integrated resource for studying macromolecular interactions. The DOCKGROUND system will be radically
expanded and diversified to become an ultimate resource for structural modeling of cellular processes, and
eventually the cell itself. The DOCKGROUND system of databases of soluble protein-protein complexes will extend
to other types of macromolecules, to serve as a source of knowledge on molecular recognition and a data
resource for docking procedures. The core of the resource will consist of regularly updated and maintained sets
of experimentally determined macromolecular complexes. The databases of unbound and modeled structures,
built upon the core bound set, will be significantly expanded and improved to advance their role in comprehensive
benchmarking for the development of docking methodologies. The database of docking decoys will provide
community-wide scoring benchmark and an important resource for development of new docking tools.
Downloadable template sets and libraries of rotamers and rotamer transition probabilities will be valuable
resources for data-driven docking. The automated template set updater will maintain the template sets for all
types of macromolecules in the expanded and diversified DOCKGROUND resource. The rotamer libraries and
rotamer-rotamer transition probabilities will be recalculated according to the growth of the DOCKGROUND sets.
Automated assessment protocols will be developed in a joint effort with the CAPRI blind prediction experiment.
The resource will integrate the developed databases and assessment protocols, with a user-friendly interface,
combining options to build customized sets of com...

## Key facts

- **NIH application ID:** 10476559
- **Project number:** 5R01GM074255-18
- **Recipient organization:** UNIVERSITY OF KANSAS LAWRENCE
- **Principal Investigator:** ILYA VAKSER
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $326,924
- **Award type:** 5
- **Project period:** 2005-03-01 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10476559

## Citation

> US National Institutes of Health, RePORTER application 10476559, Integrated Resource for Protein Recognition Studies (5R01GM074255-18). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10476559. Licensed CC0.

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