Self-assembly of proteins into amyloid aggregates displays a broad diversity of morphologies, both at the protofibrillar and final fibrillar species. These polymorphic species can coexist at fixed experimental conditions, and their relative abundance can be controlled by changing the solvent composition, or stirring the solution. However, the extent to which external conditions regulate the equilibrium of morphologically distinct species is still unknown. Here we investigate the nucleation of distinct fibril morphologies using computer simulations of a simplified model of an amyloid polypeptide. Counterintuitively, the energetically less favorable fibril morphologies nucleate more frequently than the morphologies of higher stability for models with low aggregation propensity. The free-energy profiles of the aggregation process indicate that the nucleation barrier determines the population fractions of different fibril morphologies, i.e., amyloid polymorphism is under kinetic control.

Allostery is one of the pervasive mechanisms through which proteins in living systems carry out enzymatic activity, cell signaling, and metabolism control. Effective modeling of the protein function regulation requires a synthesis of the thermodynamic and structural views of allostery. We present here a structure-based statistical mechanical model of allostery, allowing one to observe causality of communication between regulatory and functional sites, and to estimate per residue free energy changes. Based on the consideration of ligand free and ligand bound systems in the context of a harmonic model, corresponding sets of characteristic normal modes are obtained and used as inputs for an allosteric potential. This potential quantifies the mean work exerted on a residue due to the local motion of its neighbors. Subsequently, in a statistical mechanical framework the entropic contribution to allosteric free energy of a residue is directly calculated from the comparison of conformational ensembles in the ligand free and ligand bound systems. As a result, this method provides a systematic approach for analyzing the energetics of allosteric communication based on a single structure. The feasibility of the approach was tested on a variety of allosteric proteins, heterogeneous in terms of size, topology and degree of oligomerization. The allosteric free energy calculations show the diversity of ways and complexity of scenarios existing in the phenomenology of allosteric causality and communication. The presented model is a step forward in developing the computational techniques aimed at detecting allosteric sites and obtaining the discriminative power between agonistic and antagonistic effectors, which are among the major goals in allosteric drug design.

No abstract

No abstract