GHDDI and Microsoft Research use AI technology to achieve significant progress in discovering new drugs to treat global infectious diseases

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By , Distinguished Scientist, Microsoft Research AI4Science , Senior Principal Research Manager

GHDDI name and logo on the left with a rainbow spectrum colored honeycomb on the right on a green and blue gradient background

The Global Health Drug Discovery Institute (GHDDI) (opens in new tab) and Microsoft Research recently achieved significant progress in accelerating drug discovery for the treatment of global infectious diseases. Working in close collaboration, the joint team successfully used generative AI and foundation models to design several small molecule inhibitors for essential target proteins of Mycobacterium tuberculosis and coronaviruses. These new inhibitors show outstanding bioactivities, comparable to or surpassing the best-known lead compounds.

This breakthrough is a testament to the team’s combined efforts in generative AI, molecular physicochemical modeling, and iterative feedback loops between scientists and AI technologies. Normally, the discovery and in vitro confirmation of such molecules could take up to several years, but with the acceleration of AI, the joint team achieved these new results in just five months. This research also shows the tremendous potential of AI for helping scientists discover or create the building blocks needed to develop effective treatments for infectious diseases that continue to threaten the health and lives of people around the world.

Since 2019, for example, there have been more than 772 million confirmed cases of COVID-19 worldwide and nearly 7 million deaths from the virus, according to the World Health Organization (WHO), the Centers for Disease Control, and various other sources. Although vaccines have reduced the incidence and deadliness of the disease, the coronavirus continues to mutate and evolve, making it a serious ongoing threat to global health. Meanwhile, the WHO reports that tuberculosis continues to be a leading cause of death among infectious diseases, second only to COVID-19 in 2022, when 10.6 million people worldwide fell ill with TB and the disease killed 1.3 million (the most recent figures currently available).

Laying the foundation for new infectious disease treatments

Microsoft Research has rich experience in developing and pre-training large AI models specialized for proteins and molecules, demonstrated in both property prediction and molecular generation. Based on those experiences, Microsoft Research developed and maintains ownership of an AI model for molecule generation tailored for specific protein targets. The generated compounds were virtually screened and further optimized by data scientists and medicinal chemists from GHDDI, followed by compound synthesis and wet-lab experiments to quantify bioactivities. The experimental results were then fed back to the research team at Microsoft for AI model improvement and new compound generation.

This AI-expert-experiment integrated pipeline enables the success of novel compound generation for protein targets in Mycobacterium tuberculosis and coronaviruses SARS-CoV-2. In less than five months, the joint team designed several chemical compounds that are effective in inhibiting these pathogens’ essential target proteins, accelerating the structure-based drug discovery process.

Figure 1. Two potential inhibitor compounds (generated by our method) for ClpP of tuberculosis.
Dose response curves of the compounds generated for coronavirus, with GRL0617 as the reference compound, demonstrating enhanced bioactivity. The most recent progress is that the joint team has effectively optimized the IC50 to 0.18uM, which is approximately an eight-fold improvement compared to GRL0617.
Dose response curves of the compounds generated for coronavirus, with GRL0617 as the reference compound, demonstrating enhanced bioactivity. The most recent progress is that the joint team has effectively optimized the IC50 to 0.18uM, which is approximately an eight-fold improvement compared to GRL0617.

One distinguishing feature of AI-generated molecules is their novel scaffold structures, which are important because they create the potential for these molecules to be developed into a new class of drug candidates. These novel structures offer the possibility of more effective treatments, and also help to address the escalating challenge of antimicrobial resistance (AMR), a major hurdle in treating infectious diseases like tuberculosis and COVID-19.

“In the current landscape of scientific research, we encounter unparalleled challenges but also have unprecedented opportunities,” said Dr. Sheng Ding, institute director of GHDDI. “Innovation stands as the central catalyst for scientific advancement and a crucial element in addressing global health challenges. I’m excited about our collaboration with Microsoft Research and gratified with the progress we’ve jointly achieved. Without a doubt, our combined efforts will enhance R&D efficiency and expedite the process of drug discovery.”

“This represents a collaboration that transcends disciplines and boundaries,” he noted. “Our combined strengths will advance pharmaceutical research, paving new avenues in scientific exploration. Going forward, we anticipate deploying such cutting-edge technologies in uncharted realms of life sciences. This will enable us to offer more comprehensive, profound, and practical solutions for global health issues.”

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Using AI to improve global health

Embracing the principle of open innovation, the collaboration between GHDDI and Microsoft Research is dedicated to harnessing AI technology to expedite drug discovery. The goal is to contribute to global health equity through the development of lifesaving medications and the prompt delivery of safer and more effective drug solutions that are accessible to everyone.  The collaboration focuses on infectious diseases that pose a threat to global health, including but not limited to tuberculosis, viral infections, and malaria. Both parties are committed to a deep integration of generative AI, foundational models, high-throughput virtual screening, and expert knowledge to tackle these challenges.

“Successful AI-driven drug discovery necessitates a tight-knit collaboration between AI specialists and medicinal experts,” said Dr. Tie-Yan Liu, distinguished scientist at Microsoft Research AI4Science. “In recent years, our globally recognized team at Microsoft Research has been deeply engaged in interdisciplinary research between AI and natural science. To complement this, GHDDI experts bring to the table a wealth of industry experience and profound domain knowledge. Their experimental facilities not only allow for testing but also help provide invaluable feedback for training AI models. Because of our close collaboration, we look forward to producing groundbreaking research outcomes with the potential to redefine the future of healthcare through AI technology innovation.”

Accelerating drug discovery

Commenting on the research into Mycobacterium tuberculosis and coronaviruses, Dr. Rumin Zhang, chief scientific officer at GHDDI, noted that the application of AI technology by the collaborative team managed to considerably reduce the traditionally lengthy drug discovery process. The team was able to design and validate highly effective small molecule inhibitors for the pathogens in just five months.

“This is an exceptional accomplishment that underscores the immense potential of AI in efficient de novo drug design. It also vividly illustrates the team’s exceptional innovative capacity and professional prowess,” he said. “We are excited about this innovative R&D strategy leading to more groundbreaking advancements in a broader spectrum of future drug discovery projects.”

“This work is all about pushing the boundaries of AI technology for application in new drug R&D,” said Dr. Tao Qin, senior principal researcher at Microsoft Research AI4Science “We aim to leverage AI innovations to enhance human health, tackle worldwide health issues, and ensure the advantages of AI technology are accessible to all.”

“We plan to intensify and broaden our collaboration, further advancing the use of AI technology in the realm of life sciences,” said Dr. Jinjiang Guo, head of the Data Science Department at GHDDI. “This will yield novel insights that will enrich researchers’ understanding of mechanisms underlying diseases and life, thus paving the way for the development of innovative treatment strategies and providing more effective solutions for diseases that have long affected human health. We are highly optimistic about the potential of this collaboration and are confident that it will have a substantial impact on the future of the healthcare field.”

Next steps

In the next phase, Microsoft Research and GHDDI will collaborate to optimize the discovered hit compounds, enhance ADMET properties, progress toward preclinical studies, and initiate a broader range of drug-discovery projects.

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