Historically, proteins are the main biomolecules considered for small molecule drug design. More than 95% of current therapeutics have been developed to modulate protein targets. However, in recent years, certain RNAs have been identified as druggable targets, thereby opening the race to drug RNA with small molecules.

Our target-agnostic AI-based drug discovery platform generates small molecules that can interact with well-defined RNA structures and modulate downstream processes. We currently develop small molecules that can bind to the internal ribosome entry site (IRES) in the 5&#39; untranslated region of the hepatitis C virus (HCV) RNA genome, which is responsible for the initiation of viral protein synthesis. Our AI-designed molecules are able to alter the structural features of a functional HCV RNA and have the ability to inhibit virus-mediated translation and replication.

About Hepatitis C Virus 
HCV is estimated to infect about 1% of the global population. In 2019, approximately 300k people died from HCV. Current direct acting antiviral drugs demonstrate high efficacy. However, about 5% of patients do not succeed in eradicating HCV, largely due to antiviral drugs triggering strong drug selection favoring mutants that offer partial resistance to them. Thus, it is necessary to continue developing or improving the efficiency of antiviral drugs against HCV

&nbsp;

RNA-Binding Molecules Against Hepatitis C Virus

The one-ligand-one-target-one-disease approach is a tested drug design principle that has been successfully implemented in development of therapeutic agents for human and veterinary diseases. However, the fact is that drugs usually interact with more than one target, so they are pleiotropic. It could be the cause of side effects, however, pleiotropy is a two-edged sword as it may increase the therapeutic effect because many diseases are not caused by a defect in one specific target but based on a plethora of targets.

Our AI-based drug discovery platform allows us to design small molecules able to modulate two different targets thought to be responsible for the certain disease. We currently utilize our platform to develop dual-acting drug candidates against influenza A and B viruses. Our AI-designed molecules are simultaneously acting on two different viral proteins essential for the viral life cycle, thereby increasing the therapeutic effect and resistance barrier for the new class of antivirals.

&nbsp;

About Influenza Virus 
According to the World Health Organization reports, the seasonal influenza virus causes up to 5 mln cases of severe illness and up to 500k deaths per year worldwide. Although seasonal vaccines and antiviral drugs are available, there is a constant need for developing new anti-influenza drugs due to resistance and high genetic variability issues observed among new Influenza virus strains. 
 
Dataset of dual-acting molecules

We have open-sourced our top-performing NCEs for academic use. If you want access to the list of NCEs, please, fill in the form below. A paper describing how we generated and evaluated dual-acting molecules will be published soon.

Projects