The shift in the extinction maximum, lambda(max), of the localized surface plasmon resonance (LSPR) spectrum of triangular Ag nanoparticles (similar to90 nm wide and 50 nm high) is used to probe the interaction between a surface-confined antigen, biotin (B), and a solution-phase antibody, anti-biotin (AB). Exposure of biotin-functionalized Ag nanotriangles to 7 x 10(-7) M < [AB] < 7 x 10(-6) M caused a similar to38 nm red-shift in the LSPR lambda(max). The experimental normalized response of the LSPR lambda(max) shift, (DeltaR/DeltaR(max)), versus [AB] was measured over the concentration range 7 x 10(-10) M < [AB] < 7 x 10(-6) M. Comparison of the experimental data with the theoretical normalized response for a 1:1 binding model yielded values for the saturation response, DeltaR(max) = 38.0 nm, the surface-confined thermodynamic binding constant, K-a,K-surf = 4.5 x 10(7) M-1, and the limit of detection (LOD) < 7 x 10(-10) M. The experimental saturation response was interpreted in terms of a closest-packed structural model for the surface B-AB complex in which the long axis of AB, l(AB) = 15 nm, is oriented horizontally and the short axis, h(AB) = 4 nm is oriented vertically to the nanoparticle surface. This model yields a quantitative response for the saturation response, &UDelta;R-max = 40.6 nm, in good agreement with experiment, &UDelta;R-max = 38.0 nm. An atomic force microscopy (AFM) study supports this interpretation. In addition, major improvements in the LSPR nanobiosensor are reported. The LSPR nanobiosensor substrate was changed from glass to mica, and a surfactant, Triton X-100, was used in the nanosphere lithography fabrication procedure. These changes increased the adhesion of the Ag nanotriangles by a factor of 9 as determined by AFM normal force studies. The improved adhesion of Ag nanotriangles now enables the study of the B-AB immunoassay in a physiologically relevant fluid environment as well as in real-time. These results represent important new steps in the development of the LSPR nanosensor for applications in medical diagnostics, biomedical research, and environmental science.