We here consider the general problem of receptor–ligand binding in the context of antibody–antigen binding. On the one hand, we establish a quantitative mapping between macroscopic binding rates of a ...

ligand, and complex configurations, and computing the solvation free energies for each state with the Poisson-Boltzmann equation. Normal mode analysis can be performed to determine the contribution of ...

Energy minimization was performed on each ligand using the MMFF94 force field in Avogadro v1.2 (Morris et al., 2009). Furthermore, the Pred-Rxn utility by IBM was used to predict the likely binding ...

These modules allow the ProteinReDiff framework to capture intricate protein–ligand interactions, improve the fidelity of binding affinity predictions and enable more precise redesigns of ligand ...

Researchers now offer a simplified method they call ProteinReDiff that uses artificial intelligence to speed the redesign of ligand-binding proteins. In biology, the binding of cellular proteins ...

Researchers led by Truong Son Hy, Ph.D., from the University of Alabama at Birmingham, offer a simplified method they call ProteinReDiff that uses artificial intelligence to speed the redesign of ...

Researchers led by Truong Son Hy, PhD, from the University of Alabama at Birmingham, offer a simplified method they call ProteinReDiff that uses artificial intelligence to speed the redesign of ligand ...

Ligand Pharmaceuticals stock is on the rise with optimistic analyst ratings and a plan for 20% annual revenue growth. Learn ...

Drug discovery is a costly and time-intensive process, with binding free energy calculations between the potential drug ...

A novel geometric deep learning framework designs ligand-specific protein binders, enhancing therapeutic potential in cell therapies and synthetic biology.