The molecular mechanisms underlying Alzheimer's disease (AD) have been and are still under heavy scrutiny to better understand what leads to the onset and progression of the disease, and to design and develop efficacious therapeutic strategies. These decade-long studies have taught us a lot regarding the various molecular pathways involved in the pathology, but a complete dynamic picture of the underlying pathological mechanisms is still missing.We propose to provide a technological answer to fill this gap by developing and using a computational approach that integrates AD-related experimental findings and their effects on multiple aspects of neuronal function. The present study focuses on implementing one known pathogenic process: the binding of amyloid beta, the hallmark of AD, on NMDA receptors, receptors present in the main type of excitatory synapses in the brain, thereby affecting synaptic transmission and downstream pathways. We describe model implementation and calibration; we then quantify the downstream effects of this disruption both in terms of electrical activity (changes in short-term spiking activity of the postsynaptic neuron), and biochemical pathways activation through changes in calcium dynamics (an important trigger to longer-term changes). The computational approach outlined constitutes an insightful instrument to examine the downstream consequences of multiple pathogenic dysfunctions on higher level observables and sets the path for in-silico discovery and testing of therapeutic agents.