# Structural Modeling of Multifarious Protein Complexes

> **NIH NIH R01** · PURDUE UNIVERSITY · 2020 · $294,786

## Abstract

Project Summary
Many important cellular processes, such as gene expression regulation, transport, and cell
division, are carried out by protein complexes. To compensate for the difficulty of solving protein
complex structures, computational approaches for protein docking prediction have been
developed over recent decades. Although steady progress has been observed in the field, current
methods and developments are largely limited to pairwise protein docking. The proposed project
aims to extend the capability of protein docking methods to two important classes of protein
complexes, multimeric complexes and disordered interactions, while making further
improvements in pairwise protein docking. A substantial fraction of protein complexes involved in
critical cellular processes are multimeric complexes or involve interactions with intrinsically
disordered regions. As these two types of complex structures are particularly difficult to determine
by experimental means, it is an urgent and important task for protein structural bioinformatics to
develop efficient and accurate computational methods to build models for these types of
complexes. Structure models provide hypotheses for designing biochemical experiments to
elucidate interactions in a complex, which can lead to solving full or partial complex structures.
The structural information provided by multimeric protein docking is not merely an incremental
scale-up of pairwise docking; multimeric docking can also predict interacting and non-interacting
subunits and assembly order within a complex. The developed docking methods will be applied
to build models of protein complexes from four biological systems in collaboration with biologists.
The proposed methods for protein complex structure prediction are also useful for designing drugs
for protein-protein interaction targets as well as artificial design of protein complexes and bio-
nanomaterials. Collaboration with biologists will further enhance integrated computational and
experimental approaches in biology.

## Key facts

- **NIH application ID:** 9879748
- **Project number:** 5R01GM123055-04
- **Recipient organization:** PURDUE UNIVERSITY
- **Principal Investigator:** Daisuke Kihara
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $294,786
- **Award type:** 5
- **Project period:** 2017-06-01 → 2022-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9879748

## Citation

> US National Institutes of Health, RePORTER application 9879748, Structural Modeling of Multifarious Protein Complexes (5R01GM123055-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9879748. Licensed CC0.

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