New computer modeling could boost drug discovery
Date:
October 27, 2021
Source:
Queen's University Belfast
Summary:
Scientists have developed a computer-aided data tool that could
improve treatment for a range of illnesses.
FULL STORY
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Scientists from Queen's University Belfast have developed a computer-aided
data tool that could improve treatment for a range of illnesses.
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The computer modelling tool will predict novel sites of binding for
potential drugs that are more selective, leading to more effective drug
targeting, increasing therapeutic efficacy and reducing side effects.
The data tool or protocol will uncover a novel class of compounds --
allosteric drugs in G protein-coupled receptors (GPCRs).
GPCRs are the largest membrane protein family that transduce a signal
inside cells from hormones, neurotransmitters, and other endogenous
molecules. As a result of their broad influence on human physiology,
GPCRs are drug targets in many therapeutic areas such as inflammation,
infertility, metabolic and neurological disorders, viral infections
and cancer. Currently over a third of drugs act via GPCRs. Despite
the substantial therapeutic success, the discovery of GPCR drugs is
challenging due to promiscuous binding and subsequent side effects.
Recent studies point to the existence of other binding sites, called
allosteric sites that drugs can bind to and provide several therapeutic
benefits. However, the discovery of allosteric sites and drugs has been
mostly serendipitous.
Recent X-ray crystallography, that determines the atomic and molecular
structure, and cryo-electron microscopy that offers 3D models of several
GPCRs offer opportunities to develop computer-aided methodologies to
search for allosteric sites.
The researchers developed a computer-aided protocol to map allosteric
sites in GPCRs with a view to start rational search of allosteric drugs,
presenting the opportunity for new solutions and therapies for a range
of diseases.
Dr Irina Tikhonova from the School of Pharmacy at Queen's University
and senior author, explains: "We have developed a novel, cost-effective
and rapid pipeline for the discovery of GPCRs allosteric sites, which
overcomes the limitations of current computational protocols such as
membrane distortion and non-specific binding.
"Our pipeline can identify allosteric sites in a short time, which makes
it suitable for industry settings. As such, our pipeline is a feasible
solution to initiate structure-based search of allosteric drugs for any
membrane-bound drug targets that have an impact on cancer, inflammation,
and CNS diseases." This research published in ACS Central Science is a
collaboration with Queen's University Belfast and Queen Mary University
of London. It is supported by the European Union 's Horizon 2020 research
and innovation programme under the Marie-Sklodowska-Curie grants agreement
and Biotechnology and Biological Science Research Council.
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Story Source: Materials provided by Queen's_University_Belfast. Note:
Content may be edited for style and length.
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Journal Reference:
1. Antonella Ciancetta, Amandeep Kaur Gill, Tianyi Ding, Dmitry
S. Karlov,
George Chalhoub, Peter J. McCormick, Irina G. Tikhonova. Probe
Confined Dynamic Mapping for G Protein-Coupled Receptor
Allosteric Site Prediction. ACS Central Science, 2021; DOI:
10.1021/acscentsci.1c00802
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Link to news story:
https://www.sciencedaily.com/releases/2021/10/211027121951.htm
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