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Related Concept Videos

Ligand Binding and Linkage00:49

Ligand Binding and Linkage

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Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence...
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The equilibrium binding constant (Kb) quantifies the strength of a protein-ligand interaction. Kb can be calculated as follows when the reaction is at equilibrium:
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Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
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Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
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The two-state receptor model explains a drug's interaction with receptors, such as G protein-coupled receptors and ligand-gated ion channels, to induce or inhibit a biological response. When no natural ligands are present, a receptor exists in an equilibrium of inactive (Ri) and active (Ra) conformations. The inactive form does not produce a response, while the active form generates a basal effect known as constitutive activity.
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Drug-receptor bonds are formed through various chemical forces when drugs interact with target cells. Covalent bonds, strong and irreversible, are exemplified by DNA-alkylating anticancer agents that inhibit cell division. However, such irreversible drug binding lacks selectivity and can modify the DNA of the surrounding healthy cells. Covalent binding often contributes to tissue toxicity, as seen with chloroform and paracetamol metabolites binding to the liver, causing hepatotoxicity.
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Computing the relative binding affinity of ligands based on a pairwise binding comparison network.

Jie Yu1,2,3, Zhaojun Li4,5, Geng Chen1,6,7

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We developed a new computational method, the pairwise binding comparison network (PBCNet), to accurately rank ligand binding affinity. PBCNet significantly accelerates drug discovery and lead optimization with high prediction accuracy and efficiency.

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Area of Science:

  • Computational chemistry
  • Drug discovery
  • Machine learning in chemistry

Background:

  • Structure-based lead optimization remains a challenge in drug discovery.
  • Current methods rely heavily on hypotheses and medicinal chemist experience.

Purpose of the Study:

  • To introduce a novel computational approach for ranking relative binding affinity of congeneric ligands.
  • To improve prediction accuracy and computational efficiency in drug discovery.

Main Methods:

  • Developed a pairwise binding comparison network (PBCNet).
  • Utilized a physics-informed graph attention mechanism.
  • Benchmarked PBCNet on held-out datasets from Schrödinger and Merck.

Main Results:

  • PBCNet demonstrated significant advantages in prediction accuracy and computational efficiency.
  • PBCNet's performance, with fine-tuning, matched Schrödinger's FEP+.
  • Active learning-optimized PBCNet showed potential to accelerate lead optimization by 473%.

Conclusions:

  • PBCNet offers a powerful and efficient tool for relative binding affinity prediction.
  • A web service for PBCNet is available to facilitate its use in drug discovery.
  • The method has the potential to significantly accelerate lead optimization campaigns.