Alzheimer’s disease (AD) is characterized by the deposition of β-sheet–rich, insoluble amyloid β-peptide (Aβ) plaques; however, plaque burden is not correlated with cognitive impairment in AD patients; instead, it is correlated with the presence of toxic soluble oligomers. Here, we show, by a variety of different techniques, that these Aβ oligomers adopt a nonstandard secondary structure, termed “α-sheet.” These oligomers form in the lag phase of aggregation, when Aβ-associated cytotoxicity peaks, en route to forming nontoxic β-sheet fibrils. De novo-designed α-sheet peptides specifically and tightly bind the toxic oligomers over monomeric and fibrillar forms of Aβ, leading to inhibition of aggregation in vitro and neurotoxicity in neuroblastoma cells. Based on this specific binding, a soluble oligomer-binding assay (SOBA) was developed as an indirect probe of α-sheet content. Combined SOBA and toxicity experiments demonstrate a strong correlation between α-sheet content and toxicity. The designed α-sheet peptides are also active in vivo where they inhibit Aβ-induced paralysis in a transgenic Aβ Caenorhabditis elegans model and specifically target and clear soluble, toxic oligomers in a transgenic APPsw mouse model. The α-sheet hypothesis has profound implications for further understanding the mechanism behind AD pathogenesis.

Apolipoprotein (apo) E4 is the major genetic risk factor for Alzheimer disease (AD) and likely contributes to neuropathology through various pathways. Here we report that the intracellular trafficking of apoE4 is impaired in Neuro-2a cells and primary neurons, as shown by measuring fluorescence recovery after photobleaching. In Neuro-2a cells, more apoE4 than apoE3 molecules remained immobilized in the endoplasmic reticulum (ER) and the Golgi apparatus, and the lateral motility of apoE4 was significantly lower in the Golgi apparatus (but not in the ER) than that of apoE3. Likewise, the immobile fraction was larger, and the lateral motility was lower for apoE4 than apoE3 in mouse primary hippocampal neurons. ApoE4 with the R61T mutation, which abolishes apoE4 domain interaction, was less immobilized, and its lateral motility was comparable with that of apoE3. The trafficking impairment of apoE4 was also rescued by disrupting domain interaction with the small-molecule structure correctors GIND25 and PH002. PH002 also rescued apoE4-induced impairments of neurite outgrowth in Neuro-2a cells and dendritic spine development in primary neurons. ApoE4 did not affect trafficking of amyloid precursor protein, another AD-related protein, through the secretory pathway. Thus, domain interaction renders more newly synthesized apoE4 molecules immobile and slows their trafficking along the secretory pathway. Correcting the pathological structure of apoE4 by disrupting domain interaction is a potential therapeutic approach to treat or prevent AD related to apoE4.The three isoforms of human apoE (apoE2, apoE3, and apoE4) differ at amino acid positions 112 or 158 or both (1, 2). ApoE4 is the major genetic risk factor for Alzheimer disease (AD) 2 (3-5), and apoE4 carriers account for 65-80% of all AD cases, highlighting the importance of apoE4 in AD pathogenesis (6). Two biophysical properties that distinguish apoE4 from the other isoforms likely hold the key to a mechanistic understanding of its association with AD. First, apoE4 is more unstable and tends to form a molten globule state (7,8). Second, the amino-terminal domain (amino acids 1-191) of apoE4 interacts with its carboxyl-terminal domain (amino acids 223-299) (9, 10). This domain interaction occurs predominantly in apoE4, in which positively charged Arg-112 repels the side chain of Arg-61 in the amino-terminal domain, allowing the formation of a salt bridge between Arg-61 and the negatively charged Glu-255 in the carboxyl-terminal domain (9, 10). Domain interaction occurs to a significantly lesser extent in apoE2 and apoE3 because both have Cys-112, resulting in a different conformation of Arg-61 (11). Importantly, only human apoE has Arg-61; the 17 other species in which the apoE gene has been sequenced have 11). Mutation of Arg-61 to Thr in apoE4 prevents domain interaction, converting apoE4 to an apoE3-like molecule (9 -12). ApoE4 domain interaction occurs on lipoprotein particles in vitro in human plasma, in cultured Neuro-2a cells, and in Arg-61 knock-in mice, in wh...

Drugging large protein pockets is a challenge due to the need for higher molecular weight ligands, which generally possess undesirable physicochemical properties. In this communication, we highlight a strategy leveraging small molecule active site dimers to inhibit the large symmetric binding pocket in the STING protein. By taking advantage of the 2:1 binding stoichiometry, maximal buried interaction with STING protein can be achieved while maintaining the ligand physicochemical properties necessary for oral exposure. This mode of binding requires unique considerations for potency optimization including simultaneous optimization of protein−ligand as well as ligand−ligand interactions. Successful implementation of this strategy led to the identification of 18, which exhibits good oral exposure, slow binding kinetics, and functional inhibition of STING-mediated cytokine release.

A grand challenge in the field of structural biology is to design and engineer proteins that exhibit targeted functions. Although much success on this front has been achieved, design success rates remain low, an ever-present reminder of our limited understanding of the relationship between amino acid sequences and the structures they adopt. In addition to experimental techniques and rational design strategies, computational methods have been employed to aid in the design and engineering of proteins. Molecular dynamics (MD) is one such method that simulates the motions of proteins according to classical dynamics. Here, we review how insights into protein dynamics derived from MD simulations have influenced the design of proteins. One of the greatest strengths of MD is its capacity to reveal information beyond what is available in the static structures deposited in the Protein Data Bank. In this regard simulations can be used to directly guide protein design by providing atomistic details of the dynamic molecular interactions contributing to protein stability and function. MD simulations can also be used as a virtual screening tool to rank, select, identify, and assess potential designs. MD is uniquely poised to inform protein design efforts where the application requires realistic models of protein dynamics and atomic level descriptions of the relationship between dynamics and function. Here, we review cases where MD simulations was used to modulate protein stability and protein function by providing information regarding the conformation(s), conformational transitions, interactions, and dynamics that govern stability and function. In addition, we discuss cases where conformations from protein folding/unfolding simulations have been exploited for protein design, yielding novel outcomes that could not be obtained from static structures.