The Effects of N-Linked Glycosylation on SLC6 Transporters.

Membrane transporters of the solute carrier 6 (SLC6) family mediate various physiological processes by facilitating the translocation of amino acids, neurotransmitters, and other metabolites. In the body, the activity of these transporters is tightly controlled through various post-translational modifications with implications on protein expression, stability, membrane trafficking, and dynamics. While N-linked glycosylation is a universal regulatory mechanism among eukaryotes, a consistent mechanism of how glycosylation affects the SLC6 transporter family remains elusive. It is generally believed that glycans influence transporter stability and membrane trafficking; however, the role of glycosylation on transporter dynamics remains disputable, with differing conclusions among individual transporters across the SLC6 family. In this study, we collected over 1 ms of aggregated all-atom molecular dynamics (MD) simulation data to systematically identify the impact of N-glycans on SLC6 transporter dynamics. We modeled four human SLC6 transporters, the serotonin, dopamine, glycine, and B0AT1 transporters, by first simulating all possible combinations of a glycan attached to each glycosylation site followed by investigating the effect of larger, oligo-N-linked glycans to each transporter. The simulations reveal that glycosylation does not significantly affect the transporter structure but alters the dynamics of the glycosylated extracellular loop and surrounding regions. The structural consequences of glycosylation on the loop dynamics are further emphasized with larger glycan molecules attached. However, no apparent differences in ligand stability or movement of the gating helices were observed, and as such, the simulations suggest that glycosylation does not have a profound effect on conformational dynamics associated with substrate transport.

The substrate import mechanism of the human serotonin transporter.

The serotonin transporter (SERT) initiates the reuptake of extracellular serotonin in the synapse to terminate neurotransmission. The cryogenic electron microscopy structures of SERT bound to ibogaine and the physiological substrate serotonin resolved in different states have provided a glimpse of the functional conformations at atomistic resolution. However, the conformational dynamics and structural transitions to intermediate states are not fully understood. Furthermore, the molecular basis of how serotonin is recognized and transported remains unclear. In this study, we performed unbiased microsecond-long simulations of the human SERT to investigate the structural dynamics to various intermediate states and elucidated the complete substrate import pathway. Using Markov state models, we characterized a sequential order of conformational-driven ion-coupled substrate binding and transport events and calculated the free energy barriers of conformation transitions associated with the import mechanism. We find that the transition from the occluded to inward-facing state is the rate-limiting step for substrate import and that the substrate decreases the free energy barriers to achieve the inward-facing state. Our study provides insights on the molecular basis of dynamics-driven ion-substrate recognition and transport of SERT that can serve as a model for other closely related neurotransmitter transporters.

Markov state modeling of membrane transport proteins.

The flux of ions and molecules in and out of the cell is vital for maintaining the basis of various biological processes. The permeation of substrates across the cellular membrane is mediated through the function of specialized integral membrane proteins commonly known as membrane transporters. These proteins undergo a series of structural rearrangements that allow a primary substrate binding site to be accessed from either side of the membrane at a given time. Structural insights provided by experimentally resolved structures of membrane transporters have aided in the biophysical characterization of these important molecular drug targets. However, characterizing the transitions between conformational states remains challenging to achieve both experimentally and computationally. Though molecular dynamics simulations are a powerful approach to provide atomistic resolution of protein dynamics, a recurring challenge is its ability to efficiently obtain relevant timescales of large conformational transitions as exhibited in transporters. One approach to overcome this difficulty is to adaptively guide the simulation to favor exploration of the conformational landscape, otherwise known as adaptive sampling. Furthermore, such sampling is greatly benefited by the statistical analysis of Markov state models. Historically, the use of Markov state models has been effective in quantifying slow dynamics or long timescale behaviors such as protein folding. Here, we review recent implementations of adaptive sampling and Markov state models to not only address current limitations of molecular dynamics simulations, but to also highlight how Markov state modeling can be applied to investigate the structure-function mechanisms of large, complex membrane transporters.

Evolutionary origin and structural ligand mimicry by the inserted domain of alpha-integrin proteins.

Heterodimeric integrin proteins transmit signals through conformational changes upon ligand binding between their alpha (α) and beta (ß) subunits. Early in chordate evolution, some α subunits acquired an "inserted" (I) domain, which expanded their ligand binding capacity but simultaneously obstructed the ancestral ligand-binding pocket. While this would seemingly impede conventional ligand-mediated integrin activation, it was proposed that the I domain itself could serve both as a ligand replacement and an activation trigger. Here, we provide compelling evidence in support of this longstanding hypothesis using high-resolution cryo-electron microscopy structures of two distinct integrin complexes: the ligand-free and E-cadherin-bound states of the αEß7 integrin with the I domain, as well as the α4ß7 integrin lacking the I domain in both a ligand-free state and bound to MadCAM-1. We trace the evolutionary origin of the I domain to an ancestral collagen-collagen interaction domain. Our analyses illuminate how the I domain intrinsically mimics an extrinsic ligand, enabling integrins to undergo the canonical allosteric cascade of conformational activation and dramatically expanding the range of cellular communication mechanisms in vertebrates.

Machine Learning Guided Design of High-Affinity ACE2 Decoys for SARS-CoV-2 Neutralization.

A potential therapeutic strategy for neutralizing SARS-CoV-2 infection is engineering high-affinity soluble ACE2 decoy proteins to compete for binding to the viral spike (S) protein. Previously, a deep mutational scan of ACE2 was performed and has led to the identification of a triple mutant variant, named sACE22.v.2.4, that exhibits subnanomolar affinity to the receptor-binding domain (RBD) of S. Using a recently developed transfer learning algorithm, TLmutation, we sought to identify other ACE2 variants that may exhibit similar binding affinity with decreased mutational load. Upon training a TLmutation model on the effects of single mutations, we identified multiple ACE2 double mutants that bind SARS-CoV-2 S with tighter affinity as compared to the wild type, most notably L79V;N90D that binds RBD similarly to ACE22.v.2.4. The experimental validation of the double mutants successfully demonstrates the use of machine learning approaches for engineering protein-protein interactions and identifying high-affinity ACE2 peptides for targeting SARS-CoV-2.

Structural Rearrangement of the Serotonin Transporter Intracellular Gate Induced by Thr276 Phosphorylation.

The reuptake of the neurotransmitter serotonin from the synaptic cleft by the serotonin transporter, SERT, is essential for proper neurological signaling. Biochemical studies have shown that Thr276 of transmembrane helix 5 is a site of PKG-mediated SERT phosphorylation, which has been proposed to shift the SERT conformational equilibria to promote inward-facing states, thus enhancing 5-HT transport. Recent structural and simulation studies have provided insights into the conformation transitions during substrate transport but have not shed light on SERT regulation via post-translational modifications. Using molecular dynamics simulations and Markov state models, we investigate how Thr276 phosphorylation impacts the SERT mechanism and its role in enhancing transporter stability and function. Our simulations show that Thr276 phosphorylation alters the hydrogen-bonding network involving residues on transmembrane helix 5. This in turn decreases the free energy barriers for SERT to transition to the inward-facing state, thus facilitating 5-HT import. The results provide atomistic insights into in vivo SERT regulation and can be extended to other pharmacologically important transporters in the solute carrier family.

Public Insurance Payment Does Not Compensate Hospital Cost for Care of Long-Bone Fractures Requiring Additional Surgery to Promote Union.

OBJECTIVES: To quantify the total hospital costs associated with the treatment of lower extremity long-bone fracture aseptic and septic unhealed fracture, to determine if insurance adequately covers these costs, and to examine whether insurance type correlates with barriers to accessing care. DESIGN: Retrospective cohort study. SETTING: Academic Level II trauma center. PATIENTS: All patients undergoing operative treatment of OTA/AO classification 31, 32, 33, 41, 42, and 43 fractures between 2012 and 2020 at a single Level II trauma center with minimum of 1-year follow-up. MAIN OUTCOME MEASURES: The primary outcome was the total cost of treatment for all hospital-based episodes of care. Distance traveled from primary residence was measured as a surrogate for barriers to care. RESULTS: One hundred seventeen patients with uncomplicated fracture healing, 82 with aseptic unhealed fracture, and 44 with septic unhealed fracture were included in the final cohort. The median cost of treatment for treatment of septic unhealed fracture was $148,318 [interquartile range(IQR) 87,241-256,928], $45,230 (IQR 31,510-68,030) for treatment of aseptic unhealed fracture, and $33,991 (IQR 25,609-54,590) for uncomplicated fracture healing. The hospital made a profit on all patients with commercial insurance, but lost money on all patients with public insurance. Among patients with unhealed fracture, those with public insurance traveled 4 times further for their care compared with patients with commercial insurance (P = 0.004). CONCLUSIONS: Septic unhealed fracture of lower extremity long-bone fractures is an outsized burden on the health care system. Public insurance for both septic and aseptic unhealed fracture does not cover hospital costs. The increased distances traveled by our Medi-Cal and Medicare population may reflect the economic disincentive for local hospitals to care for publicly insured patients with unhealed fractures. LEVEL OF EVIDENCE: Economic Level V. See Instructions for Authors for a complete description of levels of evidence.

Machine learning guided design of high affinity ACE2 decoys for SARS-CoV-2 neutralization.

A potential therapeutic candidate for neutralizing SARS-CoV-2 infection is engineering high-affinity soluble ACE2 decoy proteins to compete for binding of the viral spike (S) protein. Previously, a deep mutational scan of ACE2 was performed and has led to the identification of a triple mutant ACE2 variant, named ACE2 2 .v.2.4, that exhibits nanomolar affinity binding to the RBD domain of S. Using a recently developed transfer learning algorithm, TLmutation, we sought to identified other ACE2 variants, namely double mutants, that may exhibit similar binding affinity with decreased mutational load. Upon training a TLmutation model on the effects of single mutations, we identified several ACE2 double mutants that bind to RBD with tighter affinity as compared to the wild type, most notably, L79V;N90D that binds RBD with similar affinity to ACE2 2 .v.2.4. The successful experimental validation of the double mutants demonstrated the use transfer and supervised learning approaches for engineering protein-protein interactions and identifying high affinity ACE2 peptides for targeting SARS-CoV-2.