Interfacial Dynamics and Growth Modes of ß2-Microglobulin Dimers.

Protein aggregation is a complex process, strongly dependent on environmental conditions and highly structurally heterogeneous, both at the final level of fibril structure and intermediate level of oligomerization. Since the first step in aggregation is the formation of a dimer, it is important to clarify how certain properties of the latter (e.g., stability or interface geometry) may play a role in self-association. Here, we report a simple model that represents the dimer's interfacial region by two angles and combine it with a simple computational method to investigate how modulations of the interfacial region occurring on the ns-µs time scale change the dimer's growth mode. To illustrate the proposed methodology, we consider 15 different dimer configurations of the ß2m D76N mutant protein equilibrated with long Molecular Dynamics simulations and identify which interfaces lead to limited and unlimited growth modes, having, therefore, different aggregation profiles. We found that despite the highly dynamic nature of the starting configurations, most polymeric growth modes tend to be conserved within the studied time scale. The proposed methodology performs remarkably well taking into consideration the nonspherical morphology of the ß2m dimers, which exhibit unstructured termini detached from the protein's core, and the relatively weak binding affinities of their interfaces, which are stabilized by nonspecific apolar interactions. The proposed methodology is general and can be applied to any protein for which a dimer structure has been experimentally determined or computationally predicted.

In Silico End-to-End Protein-Ligand Interaction Characterization Pipeline: The Case of SARS-CoV-2.

SARS-CoV-2 triggered a worldwide pandemic disease, COVID-19, for which an effective treatment has not yet been settled. Among the most promising targets to fight this disease is SARS-CoV-2 main protease (Mpro), which has been extensively studied in the last few months. There is an urgency for developing effective computational protocols that can help us tackle these key viral proteins. Hence, we have put together a robust and thorough pipeline of in silico protein-ligand characterization methods to address one of the biggest biological problems currently plaguing our world. These methodologies were used to characterize the interaction of SARS-CoV-2 Mpro with an α-ketoamide inhibitor and include details on how to upload, visualize, and manage the three-dimensional structure of the complex and acquire high-quality figures for scientific publications using PyMOL (Protocol 1); perform homology modeling with MODELLER (Protocol 2); perform protein-ligand docking calculations using HADDOCK (Protocol 3); run a virtual screening protocol of a small compound database of SARS-CoV-2 candidate inhibitors with AutoDock 4 and AutoDock Vina (Protocol 4); and, finally, sample the conformational space at the atomic level between SARS-CoV-2 Mpro and the α-ketoamide inhibitor with Molecular Dynamics simulations using GROMACS (Protocol 5). Guidelines for careful data analysis and interpretation are also provided for each Protocol.

Predicting stable binding modes from simulated dimers of the D76N mutant of ß 2-microglobulin.

The D76N mutant of the ß 2 m protein is a biologically motivated model system to study protein aggregation. There is strong experimental evidence, supported by molecular simulations, that D76N populates a highly dynamic conformation (which we originally named I 2 ) that exposes aggregation-prone patches as a result of the detachment of the two terminal regions. Here, we use Molecular Dynamics simulations to study the stability of an ensemble of dimers of I 2 generated via protein-protein docking. MM-PBSA calculations indicate that within the ensemble of investigated dimers the major contribution to interface stabilization at physiological pH comes from hydrophobic interactions between apolar residues. Our structural analysis also reveals that the interfacial region associated with the most stable binding modes are particularly rich in residues pertaining to both the N- and C-terminus, as well residues from the BC- and DE-loops. On the other hand, the less stable interfaces are stabilized by intermolecular interactions involving residues from the CD- and EF-loops. By focusing on the most stable binding modes, we used a simple geometric rule to propagate the corresponding dimer interfaces. We found that, in the absence of any kind of structural rearrangement occurring at an early stage of the oligomerization pathway, some interfaces drive a self-limited growth process, while others can be propagated indefinitely allowing the formation of long, polymerized chains. In particular, the interfacial region of the most stable binding mode reported here falls in the class of self-limited growth.