Functional and computational studies of the ligand‐associated metal binding site of β3 integrins

Abstract

A combination of experimental and computational approaches was used to provide a structural context for the role of the beta3 integrin subunit ligand-associated metal binding site (LIMBS) in the binding of physiological ligands to beta3 integrins. Specifically, we have carried out (1) adhesion assays on cells expressing normal alphaIIbeta3, normal alphaVbeta3, or the corresponding beta3 D217A LIMBS mutants; and (2) equilibrium and nonequilibrium (steered) molecular dynamics (MD) simulations of eptifibatide in complex with either a fully hydrated normal alphaIIbeta3 integrin fragment (alphaIIb beta-propeller and the beta3 betaA (I-like), hybrid, and PSI domains) or the equivalent beta3 D217A mutant. Normal alphaIIbeta3 expressing cells adhered to immobilized fibrinogen and echistatin, whereas cells expressing the alphaIIbeta3 D217A LIMBS mutant failed to adhere to either ligand. Similarly, the equivalent alphaVbeta3 mutant was unable to support adhesion to vitronectin or fibrinogen. The alphaIIbeta3 D217A mutation increased the binding of mAb AP5, which recognizes a ligand-induced binding site (LIBS) in the beta3 PSI domain, indicating that this mutation induced allosteric changes in the protein. Steered MD simulating the unbinding of eptifibatide from either normal alphaIIbeta3 or the equivalent beta3 D217A mutant suggested that the reduction in ligand binding caused by the LIMBS mutant required the loss of both the LIMBS and the metal ion-dependent adhesion site (MIDAS) metal ions. Our computational results indicate that the LIMBS plays a crucial role in ligand binding to alphaIIbeta3 by virtue of its effects on the coordination of the MIDAS.

The GPIIb/IIIa (integrin αIIbβ3) odyssey: a technology-driven saga of a receptor with twists, turns, and even a bend

“…126 Molecular dynamic simulations of select groups of atoms in the ligand binding regions of ␣IIb␤3 and ␣V␤3 have been performed in an attempt to understand the allosteric pathways leading to activation and the energetics of ligand binding. [127][128][129] These computation-intensive studies have been made possible by advances in the application of biophysical and thermodynamic principles to biologic systems and the availability of more powerful computers. The results have provided models of variations in regional flexibility and interactions with water molecules over time, the force needed to remove ligands from the binding pocket under different conditions, and the allosteric pathways leading from one conformation to another.…”

αIIbβ3 variants defined by next-generation sequencing: Predicting variants likely to cause Glanzmann thrombasthenia

“…The biochemical and molecular abnormalities in GT have been studied for nearly 40 y (4,6,(8)(9)(10). In the past 10 y, high-resolution crystallography, electron microscopy, and computational studies of the αIIbβ3 receptor have provided atomic-level information on the correlation between receptor structure and function (11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21). In addition, ethnic groups with relatively high prevalence of GT have been defined that share the same genetic abnormality based on founder mutations, and the dates that some of the mutations entered the population have been estimated (22)(23)(24)(25)(26)(27)(28).…”

“…Sixth, 3D molecular models have been built based on crystallographic and NMR data to analyze the effects of novel amino acid substitutions on receptor structure and function and the generation of alloantigens (15,(46)(47)(48)(49)(50)(51)(52)(53). The data from these models and assessments of the severity of the amino acid change in the variants have the potential to aid in predicting whether a novel variant is likely to affect receptor function and immunogenicity (54)(55)(56)(57)(58)(59).…”

Influence of ionization states of antigen on anti-fluorescein antibodies

“…In case of non-equilibrium processes such as SMD simulations, the binding free energy profiles (referred to as potential of mean force: PMF) can be calculated by Jarzynski equality [24,25]. Many researchers have also reported that SMD simulations identified the dynamic processes of protein-ligand binding and unbinding [20,[26][27][28][29][30][31][32][33][34][35][36]. We analyzed PMFs and SMD structures, and compared them among four combinations of antibody/antigen: W/FLU(À1), W/FLU(À2), M/FLU(À1) and M/FLU(À2), where characters W and M represent the wild-type and the mutant, respectively.…”