De Novo Covalent Binder design using FBDD

Accelerate your covalent binder discovery for challenging protein targets with Aganitha 

Context

Covalent Binders for challenging protein targets

Covalent binders are molecules that form a strong bond with their target protein. This bond occurs between an electrophilic “warhead” on the ligand and a nucleophilic amino acid residue (like cysteine) on the protein’s surface. This approach has gained significant traction in drug discovery, particularly for challenging targets.

Significance of Covalent Binders

High Specificity

Targeting less abundant residues such as cysteine minimizes off-target binding

Strong Efficacy

The covalent bond leads to prolonged drug action and potentially lower dosages.

Proven Success

The covalent drug market exceeds US $50 billion, with over 55 approved drugs and rising approvals in recent years

Outcomes

Key features of Aganitha’s Approach

Aganitha’s in silico workflow for designing covalent binders leverages Fragment Based Drug Design (FBDD) in conjunction with Generative Chemistry and Molecular Dynamics. Here’s how we can enhance your covalent binder design process.

Identify Your Ideal Targets

  • We help you identify suitable targets for covalent binding within your disease areas of interest.
  • Our analysis of 3D protein structures locates reactive residues and binding pockets for covalent bond formation.

Optimize Known Warheads

  • Leverage known synthesizable warheads tailored to your specific targets
  • Benefit from optimized warhead reactivity and selectivity for your targets

Accelerate Your Discovery with FBDD

  • Leverage our advanced computational screening of covalent and non-covalent fragments using high throughput & automated docking pipelines.
  • Benefit from AI-driven fragment linking and growing strategies to speed up your lead discovery.

Streamline Your Hit Identification and Optimization

  • Save time and resources with our virtual screening and ADMET filtering of candidate molecules.
  • The most promising candidates undergo further scrutiny using Molecular Dynamics (MD) simulations and binding free energy calculations.

Gain Deep Insights with Advanced Modeling

  • Visualize your protein-ligand interactions through our physiological condition simulations.
  • Make informed decisions based on our estimations of binding free energies and residence times.

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