Scientists use AI to develop drugs that can treat opioid addiction

Every year, more than 80,000 Americans die from overdoses related to the condition.
Loukia Papadopoulos
Opioids are very addictive.jpg
Opioids are very addictive.


Did you know that approximately three million Americans have an opioid addiction, and every year, more than 80,000 Americans die from overdoses related to the condition?

Opioid drugs function by activating opioid receptors that lead to pain alleviation and well-being. Unfortunately, they also trigger physical dependence and decreased breathing, the latter often unfortunately leading to death during a drug overdose.

Past preclinical studies conducted have found that blocking these kappa-opioid receptors may offer help in treating opioid dependence, according to multiple media reports published on Saturday.

Discovering new drugs

Leslie Salas Estrada, in the lab of Marta Filizola, at the Icahn School of Medicine at Mount Sinai, now hopes to alleviate opioid addiction by discovering drugs that inhibit the kappa-opioid receptor. 

“If you’re addicted, and you’re trying to quit, at some point, you will get withdrawal symptoms, and those can be really hard to overcome,” Estrada explained to NeuroscienceNews.

“After a lot of opioid exposure, your brain gets rewired to need more drugs. Blocking the activity of the kappa opioid receptor has been shown in animal models to reduce this need to use drugs in the withdrawal period.”

The challenge of this task is in uncovering the drugs that can actually block the activity of a protein, such as the kappa-opioid receptor, in a sea of countless candidates. That’s why Estrada turned to computational tools to make the process more efficient. Estrada is using artificial intelligence (AI) to optimize her drug-finding systems.

Huge amount of information

“Artificial intelligence has the advantage of being able to take huge amounts of information and learn to recognize patterns from it. So, we believe that machine learning can help us to leverage the information that can be derived from large chemical databases to design new drugs from scratch. And in that way, we can potentially reduce the time and costs associated with drug discovery,” she said.

Estrada’s team trained a computer model to generate compounds that might block the receptor with a reinforcement learning algorithm that rewarded properties that are favorable for drug treatments. They did this by combining information about the kappa-opioid receptor and known drugs.

It proved successful thus far. The researchers have already identified several compounds that have promising attributes. They are now aiming to synthesize them and eventually test them in animal models for safety and effectiveness. 

The ultimate goal, Estrada said, is to” help people struggling with addiction,” according to NeuroscieNews.

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