via IBM Research
Antibiotic resistance is no joke. It’s a huge threat to human health — even more so during the raging pandemic. We need new antibiotics, and we need them fast.
In the US alone, nearly three million people¹ get infected with antibiotic-resistant bacteria or fungi every year¹. But very few new antibiotics are being developed to replace those that no longer work. That’s because drug design is an extremely difficult and lengthy process — there are more possible chemical combinations of a new molecule than there are atoms in the Universe.
We want to help.
Paving the way to the era of Accelerated Discovery, our IBM Research team has developed an AI system that can help speed up the design of molecules for novel antibiotics. And it works — in “Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics,” published in Nature Biomedical Engineering, we outline how we used it to create two new non-toxic antimicrobial peptides (AMPs) with strong broad-spectrum potency. Peptides are small molecules — they are short strings of amino acids, the building blocks of proteins. Our approach outperforms other leading de novo AMP design methods by nearly 10 percent.
Beyond antibiotics, this generative AI system could potentially accelerate the design process of the best possible molecules for new drugs and materials — helping scientists to use AI to discover and design better candidates for more effective drugs and therapies for diseases, materials to absorb and capture carbon to help fight climate change, materials for more intelligent energy production and storage, and much more. To fight these challenges, we need to accelerate the rate of discovery of new and functional molecules — at scale.
Where is that molecule?
That’s far from easy. Zeroing in on the correct molecular configuration that would lead to a new material with desired properties among the astronomical number of possible molecules is like looking for a needle in a haystack. For peptides, one would typically have to experimentally screen more than a hundred molecules to find one with the right properties.
So we’ve turned to AI for help.
First, we used an AI generative model dubbed a deep generative autoencoder to learn about the vast space of known peptide molecules. The model captured meaningful information such as molecular similarity and function about diverse peptide sequences, enabling us to explore beyond known antimicrobial templates.
We then applied Controlled Latent attribute Space Sampling (CLaSS) — a recently developed computational method for generating novel peptide molecules with custom properties. It works by sampling from the informative latent space of peptides and relies on a rejection sampling scheme guided by the molecular property the classifier trained on during the latent representation. Since CLaSS performs attribute-conditioned sampling in the compressed latent space, it is a computationally efficient and scalable approach that can be easily repurposed.
We then used deep learning classifiers to screen the AI-generated candidate antimicrobial molecules for additional key attributes, such as toxicity and broad-spectrum activity. We performed additional screening with the help of high-throughput, coarse-grained molecular dynamics simulations. These simulations look for presence of novel physicochemical features indicative of stable and peptide-membrane binding, such as low-contact variance between peptide and membrane.
Within 48 days, our AI-boosted molecular design approach to Accelerated Discovery enabled us to identify, synthesize, and experimentally test 20 AI-generated novel candidate antimicrobial peptides. Two of them turned out to be highly potent against diverse Gram-positive and Gram-negative pathogens (including multidrug-resistant K. pneumoniae) and very unlikely to trigger drug resistance in E. coli.
We also didn’t find any cross-resistance for either of the AMPs when tested using a polymyxin-resistant strain. Live-cell confocal imaging showed the formation of membrane pores as the underlying mechanism of bactericidal mode of action of these peptides. Both antimicrobials have low toxicity — we tested them in vitro and also in mice, providing important information about the safety, toxicity and efficacy of these antimicrobial candidates in a complex animal model.
Our proposed approach could potentially lead to faster and more efficient discovery of potent and selective broad-spectrum antimicrobials to keep antibiotic-resistant bacteria at bay — for good. And we hope that our AI could also be used to help address the world’s other most difficult discovery challenges, such as designing new therapeutics, environmentally friendly and sustainable photoresists, new catalysts for more efficient carbon capture, and so much more.
Original Article: IBM AI finds new peptides – paving the way to better drug design
More from: IBM Research
The Latest Updates from Bing News & Google News
Go deeper with Bing News on:
New antibiotics
- Common Antibiotic Linked to Higher Mortality in Critical Sepsis Patients
In emergency rooms and intensive care units nationwide, clinicians must rapidly decide which antibiotics to administer when a life-threatening infection is suspected. A new University of Michigan (U-M ...
- Researchers find new approach for antibiotic development
The opportunistic bacterial pathogen Pseudomonas aeruginosa is dangerous due to its resistance to multiple antibiotics. A research team from Heinrich Heine University Düsseldorf (HHU) and Jülich ...
- Commonly used antibiotic brings more complications, death in the sickest patients
In emergency rooms and intensive care units across the country, clinicians make split-second decisions about which antibiotics to give a patient when a life-threatening infection is suspected. A new U ...
- Fears over emergence of new superbugs as antibiotic-resistant genes found in soil samples from across Scotland
Organisms with genetic defences against our most commonly used medicines are everywhere in Scotland – not good news for human and animal healthFears have been raised that potentially dangerous new ...
- In a new book, a scientist suggests ways to combat fast-spreading superbugs that defeat antibiotics
Moreover, the misuse of antibiotics isn’t limited to hospitals. In the community, unwarranted prescriptions abound. A 2023 study of 59 low- and medium income countries published in the ...
Go deeper with Google Headlines on:
New antibiotics
[google_news title=”” keyword=”new antibiotics” num_posts=”5″ blurb_length=”0″ show_thumb=”left”]
Go deeper with Bing News on:
Antibiotic development
- Machine learning model uncovers new drug design opportunities
Pathogens are nothing if not adaptable, and their ability to protect themselves against antibiotics increasingly poses a public health concern. A research team led by Los Alamos National Laboratory ...
- Weight-loss drugs ‘gold rush’ with 322 in development for £120bn-a-year market
Pharmaceutical giants are highlighting additional benefits to weight loss drugs in areas from reducing heart attacks to tackling liver disease as they seek to secure a slice of a burgeoning market in ...
- ‘Major drug bust in East Boston’: Police arrest 10 people, seize cocaine and fentanyl from home
Police on Tuesday arrested 10 people in connection with a “major drug bust” at an East Boston home, and seized large amounts of cocaine and fentanyl.
- Boston Police Arrest 10 in Drug Sting, Seize Cocaine and Fentanyl in East Boston
Boston police arrested 10 in an East Boston drug bust, Operation "Clean House," seizing cocaine, fentanyl, and cash.
- Adolescent Anxiety Is Hard to Treat. New Drug-Free Approaches May Help
Although CBT is the most established treatment for adolescent anxiety, not all youths who try it experience relief. Among those who do, many fail to maintain improvements over time. A mere 20 to 50 ...
Go deeper with Google Headlines on:
Antibiotic development
[google_news title=”” keyword=”antibiotic development” num_posts=”5″ blurb_length=”0″ show_thumb=”left”]
[embedyt] https://www.youtube.com/embed?listType=playlist&list=PL0UjJ07OSXC83oV409r1yRju8-ihA1InJ&layout=gallery[/embedyt]