New computational tool enables prediction of key functional sites in
proteins based on structure

Date:
September 3, 2020
Source:
Penn State
Summary:
A new technology that uses a protein's structure to predict the
inner wiring that controls the protein's function and dynamics is
now available for scientists to utilize. The tool may be useful
for protein engineering and drug design.



FULL STORY ==========================================================================
A new technology that uses a protein's structure to predict the inner
wiring that controls the protein's function and dynamics is now available
for scientists to utilize. The tool, developed by researchers at Penn
State, may be useful for protein engineering and drug design.


========================================================================== Nikolay Dokholyan, professor of pharmacology at Penn State College of
Medicine, and postdoctoral scholar Jian Wang created an algorithm called
Ohm that can predict allosteric sites in a protein. These are locations
where proteins are particularly sensitive to relay certain changes in
their structure and function as a result of external stimuli including
other proteins, small molecules, water or ions. Signaling at and between allosteric sites in proteins regulate many biological processes.

According to Dokholyan, Ohm's ability to predict allosteric sites in
proteins may be useful for developing targeted therapeutics for certain
disease states.

He said that many drugs on the market, such as G Protein-Coupled Receptor (GPCR) drugs, may cause unintended side effects because they target
proteins that are similar in structure to their intended target.

"Drugs designed to target specific allosteric sites on a protein of
interest can hopefully avoid side effects caused by drugs that target
similar proteins," Dokholyan said. "Ohm may be useful for biomedical researchers seeking to identify allosteric sites in proteins that play
key roles in biological processes of certain diseases." Proteins carry
out essential functions in the body and are built using genetic code
inscribed in a person's DNA. Each protein is built using sequences of
20 different amino acids.

Wang and Dokholyan hypothesized that the physical forces from interactions between the atoms that make up the amino acids would allow them to predict allosteric pathways and sites in proteins. Ohm was designed to account
for the interactions between atoms and identifies areas of density in
proteins to predict allosteric pathways and sites in proteins.

"In a crystalline structure, atoms are spaced evenly apart and energy
flows through it in an even fashion," Dokholyan said. "Proteins'
structures are heterogeneous, so energy will flow through them in regions
where the atoms are more densely packed together. Ohm identifies regions
and pathways of atomic density that allow it to predict allosteric
sites in proteins." They tested the functionality of the program by
inputting the genetic data from 20 proteins with known allosteric sites
to see if the program would accurately predict the same spots. Results
from the analysis, published in Nature Communications, showed that Ohm identified many of the same allosteric sites as those predicted from
previous methods and experiments.

Dokholyan, a member of the Penn State Cancer Institute, said that Ohm
can analyze allosteric paths in any protein and that researchers can
access the tool through a server on his lab's website.

"Researchers around the world can use Ohm to predict allosteric sites
and pathways in their protein of interest," Wang said. "This tool will
be essential for the future of allosteric drug development that seeks
to reduce unwanted side effects through specific targeting."

========================================================================== Story Source: Materials provided by Penn_State. Note: Content may be
edited for style and length.


========================================================================== Journal Reference:
1. Jian Wang, Abha Jain, Leanna R. McDonald, Craig Gambogi, Andrew
L. Lee,
Nikolay V. Dokholyan. Mapping allosteric communications within
individual proteins. Nature Communications, 2020; 11 (1) DOI:
10.1038/s41467-020- 17618-2 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2020/09/200903095628.htm

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