In a recent study published in Nature Communication, scientists utilized artificial intelligence (AI)-driven virtual screening to uncover ‘F10’, a fresh cardiac-specific myosin inhibitor with potential applications in heart disease and heart failure treatments.
Background
The activation of cardiac myofilaments by Ca2+ triggers contraction-relaxation cycles. During these cycles, the power strokes produced by the attachment and detachment of myosin heads from thick filaments to actin filaments lead to muscle movement. The availability of myosin during this process is influenced by its interaction with proteins like titin and cardiac myosin binding protein-C (cMyBP-C).
Myosin can enter a ‘super relaxed state’ (SRX) that reduces Adenosine Triphosphatase (ATPase) activity, enhancing energy efficiency.
Disruption of this system can contribute to cardiovascular disease development, presenting an opportunity to develop a new therapy for heart failure targeting dysmiosin functions.
Unlike conventional treatments that address symptoms, myosin modulators tackle root causes directly, potentially with fewer side effects.
Further investigation is necessary to deepen the understanding of the complex interplay between the structural and functional states of cardiac myosin and to optimize innovative myosin modulators like ‘F10’ for more efficient and lower side-effect treatment of heart disease and heart failure.
About the Study
In this research, scientists employed an AI-based virtual high throughput screening (VHTS) technique using Atomwise’s AtomNet® platform to evaluate a curated library of over 4 million small molecules.
The primary focus of these molecules was the beta-cardiac myosin from humans to assess their effectiveness in targeting the Omecamtiv Mercarbil binding site.
Out of this extensive collection, the top 200 molecules that adhered to Lipinski’s Rule of Five were selected as drug-like substances. By conducting biochemical assays, myosin modulators were identified from these selected compounds.
Biochemical assays were conducted using bovine cardiac myosin S1 and rabbit skeletal F-actin. These compounds were individually mixed with an enzyme mixture in a black 96-well half-area plate.
The assay plates included negative control (Dimethyl Sulfoxide (DMSO) only) and positive control (Blebbistatin). NADH intensity measurements at various time points determined the extent of the reactions initiated by a substrate mix.
This methodology facilitated the discovery of compounds that modulate the ATPase activity of cardiac myosin.
Furthermore, demembranated myofibrils from bovine ventricles were utilized to assess the ATPase activity of the selected compounds. These myofibrils were tested in a similar assay setup, offering insights into the effects of the compounds on steady-state myofibrillar ATPase activity.
By combining AI-driven screening with biochemical validation, researchers successfully identified new cardiac myosin modulators with potential therapeutic implications.
Study Results
In this study, AI was leveraged to screen a virtual library of around four million compounds for potential cardiac myosin modulators. This approach led to the discovery of a new compound, F10, which notably inhibited ATPase activity in cardiac myosin.
F10 was chosen based on its interaction with the Omecamtiv Mecarbil binding site on human β-cardiac myosin, taking into account factors such as hydrogen bond donors and acceptors, as well as hydrophobic characteristics.
Further analysis revealed that 10 μmol L−1 of F10 inhibited ATPase activity in bovine cardiac myosins by approximately 44%. The dose-response analysis indicated effectiveness at 21 μmol L−1 (IC50).
This compound exhibited a unique chemical scaffold, distinct from known myosin effectors. Interestingly, F10 reduced the maximal rate of ATP hydrolysis without affecting the affinity of myosin S1 for F-actin.
The specificity of F10 was underscored by its differential impact on ATPase activity across various myosin isoforms in different muscle types, emphasizing its selectivity for cardiac myosin.
The study also delved into the mechanism of F10’s inhibition. Single nucleotide turnover experiments indicated that F10 slowed down the release of nucleotides from cardiac myosin by stabilizing the SRX state of myosin.
Additionally, the structural impact of F10 on demembranated rat ventricular trabeculae, which reduced maximal active isometric tension and altered the orientation of myosin heads, suggested the stabilization of proteins in the OFF state.
Moreover, F10 promptly decreased the left ventricular systolic pressure of Langendorff-perfused rat hearts without affecting heart rate or coronary perfusion. The reversible effects of F10 were faster in onset and offset compared to Mavacamten, another myosin inhibitor.
The analysis of the structure-activity relationship provided insights into F10’s binding and inhibitory mechanism. Computational docking indicated multiple potential interactions of F10 within the myosin motor domain.
Variations in F10’s chemical structure led to differences in inhibitory activity, supporting the OM binding site as a target for developing myosin modulators.
This study showcases the potential of AI in drug discovery, particularly for cardiac myosin modulators.
The introduction of F10 as a novel cardiac myosin inhibitor paves the way for developing new therapeutic agents targeting cardiac myosin for heart disease treatment.
The study underscores the value of AI in identifying novel compounds and sets the stage for further exploration in this field.
