The receptor associated protein (RAP) is an antagonist and molecular chaperone that binds tightly to low-density lipoprotein receptor family members in the endoplasmic reticulum (ER). After escorting these receptors to the Golgi, RAP dissociates from the receptors. The molecular mechanism of the dissociation has been unknown until now. The solution structure of RAP-D3 domain presented here reveals a striking increase in positively charged residues on the surface of this RAP domain due to protonation of solvent-exposed histidine sidechains as the pH is reduced from a near neutral pH of the ER to the acidic pH of the Golgi. Structure-based mutagenesis studies in vitro and in cells confirm that the protonation of histidine residues as a consequence of the pH changes modulate the binding/release of RAP from LRP. This histidine switch may serve as a general mechanism for regulating cell trafficking events.

We develop fully glycosylated computational models of ACE2-Fc fusion proteins which are promising targets for a COVID-19 therapeutic. These models are tested in their interaction with a fragment of the receptor-binding domain (RBD) of the Spike Protein S of the SARS-CoV-2 virus, via atomistic molecular dynamics simulations. We see that some ACE2 glycans interact with the S fragments, and glycans are influencing the conformation of the ACE2 receptor. Additionally, we optimize algorithms for protein glycosylation modelling in order to expedite future model development. All models and algorithms are openly available.

Abstract-Communications between cells in large part drive tissue development and function, as well as disease-related processes such as tumorigenesis. Understanding the mechanistic bases of these processes necessitates quantifying specific molecules in adjacent cells or cell nuclei of intact tissue. However, a major restriction on such analyses is the lack of an efficient method that correctly segments each object (cell or nucleus) from 3-D images of an intact tissue specimen. We report a highly reliable and accurate semi-automatic algorithmic method for segmenting fluorescence-labeled cells or nuclei from 3-D tissue images. Segmentation begins with semi-automatic, 2-D object delineation in a user-selected plane, using dynamic programming (DP) to locate the border with an accumulated intensity per unit length greater that any other possible border around the same object. Then the two surfaces of the object in planes above and below the selected plane are found using an algorithm that combines DP and combinatorial searching. Following segmentation, any perceived M. Nakaya was with the Cancer and Developmental Biology Laboratory, National Cancer Institute, Frederick, MD 21702 USA. He is now with the Department of Histology and Embryology, Graduate School of Medical Science, Kanazawa University 13-1,