Cellular polyamines condense hyperphosphorylated Tau, triggering Alzheimer's disease.

Many gaps in our understanding of Alzheimer's disease remain despite intense research efforts. One such prominent gap is the mechanism of Tau condensation and fibrillization. One viewpoint is that positively charged Tau is condensed by cytosolic polyanions. However, this hypothesis is likely based on an overestimation of the abundance and stability of cytosolic polyanions and an underestimation of crucial intracellular constituents - the cationic polyamines. Here, we propose an alternative mechanism grounded in cellular biology. We describe extensive molecular dynamics simulations and analysis on physiologically relevant model systems, which suggest that it is not positively charged, unmodified Tau that is condensed by cytosolic polyanions but negatively charged, hyperphosphorylated Tau that is condensed by cytosolic polycations. Our work has broad implications for anti-Alzheimer's research and drug development and the broader field of tauopathies in general, potentially paving the way to future etiologic therapies.

Bridging solvent molecules mediate RNase A - Ligand binding.

Due to its high catalytic activity and readily available supply, ribonuclease A (RNase A) has become a pivotal enzyme in the history of protein science. Moreover, this great interest has carried over to computational chemistry and molecular dynamics, where RNase A has become a model system for various types of studies, all the while being an important drug design target in its own right. Here, we present a detailed molecular dynamics study of RNase-ligand binding involving 22 compounds, spanning nearly five orders of magnitude in affinity, and totaling 8.8 µs of sampling with the standard Amber parameters and an additional 8.8 µs of sampling with a modified potential. We show that short-lived, solvent-mediated bridging interactions are crucial to RNase-ligand binding. We characterize the behavior of bridging solvent molecules, uncovering a power-law dependence between the lifetime of a solvent bridge and the probability of its occurrence. We also demonstrate that from an energetic perspective, bridging solvent in RNase A-ligand binding behaves like part of the enzyme, rather than the ligands. Moreover, we describe an automated pipeline for the detection and processing of bridging interactions, and offer an independent assessment of the performance of the state-of-the-art fixed-charge force fields. Thus, our work has broad implications for drug design and computational chemistry in general.

Energetic Fingerprinting of Ligand Binding to Paralogous Proteins: The Case of the Apoptotic Pathway.

Networks of biological molecules are key to cellular function, governing processes ranging from signal cascade propagation to metabolic pathway regulation. Genetic duplication processes give rise to sets of regulatory proteins that have evolved from a common ancestor, leading to interactomes whose dysregulation is often associated with disease. A better understanding of the determinants of specificity at interfaces shared by functionally related proteins is crucial to the rational design of novel pharmacotherapeutic agents. To this end, a comprehensive data set of drug and drug-like binders was assembled for the Bcl-xL and Bcl-2 antiapoptotic proteins-archetypal examples of regulatory systems governed by evolutionarily conserved protein-protein interactions. These were first used to derive a two-dimensional quantitative structure-activity relationship (2D QSAR) model, predicting ligand specificity for these homologous proteins. The strengths and weaknesses of high-throughput 2D QSAR were then compared and contrasted to those of theoretically rigorous thermodynamic integration calculations performed on 14 complexes of Bcl-xL-specific, Bcl-2-specific, and potent dual binders bound to the Bcl-xL and Bcl-2 proteins. We demonstrate that free energy calculations provide an added layer of essential information, which traditional QSAR cannot capture. Moreover, we show that protein energetic responses to different ligands, expressed as per-residue energy values, can be used to fingerprint the protein-ligand interaction, extending the framework of four-dimensional molecular dynamics/quantitative structure-activity relationships (4D-MD/QSAR) toward the facilitation of future drug design strategies.

Protein-protein interactions in paralogues: Electrostatics modulates specificity on a conserved steric scaffold.

An improved knowledge of protein-protein interactions is essential for better understanding of metabolic and signaling networks, and cellular function. Progress tends to be based on structure determination and predictions using known structures, along with computational methods based on evolutionary information or detailed atomistic descriptions. We hypothesized that for the case of interactions across a common interface, between proteins from a pair of paralogue families or within a family of paralogues, a relatively simple interface description could distinguish between binding and non-binding pairs. Using binding data for several systems, and large-scale comparative modeling based on known template complex structures, it is found that charge-charge interactions (for groups bearing net charge) are generally a better discriminant than buried non-polar surface. This is particularly the case for paralogue families that are less divergent, with more reliable comparative modeling. We suggest that electrostatic interactions are major determinants of specificity in such systems, an observation that could be used to predict binding partners.

Energetics and Dynamics Across the Bcl-2-Regulated Apoptotic Pathway Reveal Distinct Evolutionary Determinants of Specificity and Affinity.

Critical regulatory pathways are replete with instances of intra- and interfamily protein-protein interactions due to the pervasiveness of gene duplication throughout evolution. Discerning the specificity determinants within these systems has proven a challenging task. Here, we present an energetic analysis of the specificity determinants within the Bcl-2 family of proteins (key regulators of the intrinsic apoptotic pathway) via a total of ∼20 µs of simulation of 60 distinct protein-protein complexes. We demonstrate where affinity and specificity of protein-protein interactions arise across the family, and corroborate our conclusions with extensive experimental evidence. We identify energy and specificity hotspots that may offer valuable guidance in the design of targeted therapeutics for manipulating the protein-protein interactions within the apoptosis-regulating pathway. Moreover, we propose a conceptual framework that allows us to quantify the relationship between sequence, structure, and binding energetics. This approach may represent a general methodology for investigating other paralogous protein-protein interaction sites.