In the MOLiNTEL project, we attempt to understand how neurons communicate with each other to respond to external stimuli at the very molecular level. To address this complex and multifaceted problem we focused on analyzing the underlying signaling machinery of the neuron-neuron junction called the “synapse”. The most crucial components of this machinery are proteins from the iGluR family. iGluRs are responsible for making neurons “plastic” i.e. they allow neurons either strengthen or weaken connection based on the type and the volume of signaling between the neurons. This neuronal plasticity is the crux of our ability to learn, memorize and infer knowledge. Failures in the iGluR machinery are directly connected to diseases associated with neurodegenerative diseases such as Alzheimer’s. To develop medication specifically targeting the defective functionality of these proteins it is of great importance to understand the complex dynamics of these proteins which are responsible for the failure states. Using state-of-the-art molecular modelling and high throughput artificial intelligence methods we wanted to unravel the relation between the structure, dynamics, and function of the members of the iGluR family. Once these relationships are pinned down, then it is possible to concentrate on the task of building defect-specific therapeutic approaches to solve medical issues. To identify this relationship, we also aimed to build a computational machinery that can systematically and objectively explore the dynamic landscape of the iGluR family members in an efficient manner so that we could connect the function of these proteins to their structure. This was built in the form of a software framework operating on top of and posterior to all available simulation protocols. The advantage of this framework is of course more general, and it can be used in alternative scenarios involving other simulation systems. At the conclusion of our two years of work, we built the software framework. Using this framework, we were successfully able to find the mechanism of activation of two members of iGluR family, named AMPA-receptors and NMDA-receptors. In addition, the software tools developed as a part of the project have allowed us to investigate other protein families associated with neuronal signaling, such as the GPCR family. We are currently comparing the two mechanisms to each other to try and understand how and why these mechanisms differ between the members of the iGluR family. Such a comparison is meant to give us insight into how these members can be differentially targeted by pharmaceutical approaches despite their structural similarities.