New Computer Modelling could Boost Drug Discovery

Scientists from Queen's University Belfast have developed a computer-aided data tool that could improve treatment for a range of illnesses.

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.

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 Cent. Sci. 2021. doi: 10.1021/acscentsci.1c00802

Most Popular Now

Should AI Chatbots Replace Your Therapis…

The new study exposes the dangerous flaws in using artificial intelligence (AI) chatbots for mental health support. For the first time, the researchers evaluated these AI systems against clinical standards...

AI could Help Pathologists Match Cancer …

A new study by researchers at the Icahn School of Medicine at Mount Sinai, Memorial Sloan Kettering Cancer Center, and collaborators, suggests that artificial intelligence (AI) could significantly improve how...

AI Detects Early Signs of Osteoporosis f…

Investigators have developed an artificial intelligence-assisted diagnostic system that can estimate bone mineral density in both the lumbar spine and the femur of the upper leg, based on X-ray images...

AI Tool Detects Surgical Site Infections…

A team of Mayo Clinic researchers has developed an artificial intelligence (AI) system that can detect surgical site infections (SSIs) with high accuracy from patient-submitted postoperative wound photos, potentially transforming...

Meet Your Digital Twin

Before an important meeting or when a big decision needs to be made, we often mentally run through various scenarios before settling on the best course of action. But when...

NHS National Rehabilitation Centre to De…

The new NHS National Rehabilitation Centre will deploy technology to help patients to maintain their independence as they recover from life-changing injuries and illnesses and regain quality of life. Airwave Healthcare...

AI Finds Hundreds of Potential Antibioti…

Snake, scorpion, and spider venom are most frequently associated with poisonous bites, but with the help of artificial intelligence, they might be able to help fight antibiotic resistance, which contributes...

AI Tool Accurately Detects Tumor Locatio…

An AI model trained to detect abnormalities on breast MR images accurately depicted tumor locations and outperformed benchmark models when tested in three different groups, according to a study published...

AI can Accelerate Search for More Effect…

Scientists have used an AI model to reassess the results of a completed clinical trial for an Alzheimer’s disease drug. They found the drug slowed cognitive decline by 46% in...

AI Accurately Classifies Pancreatic Cyst…

Artificial intelligence (AI) models such as ChatGPT are designed to rapidly process data. Using the AI ChatGPT-4 platform to extract and analyze specific data points from the Magnetic Resonance Imaging...

Free AI Tools can Help Doctors Read Medi…

A new study from the University of Colorado Anschutz Medical Campus shows that free, open-source artificial intelligence (AI) tools can help doctors report medical scans just as well as more...

Autonomous AI Agents in Healthcare

The use of large language models (LLMs) and other forms of generative AI (GenAI) in healthcare has surged in recent years, and many of these technologies are already applied in...