Biology subjects

Wang, D.-N.

Publications and source records attributed to Wang, D.-N..

6 recordsLinked to original sources

bioRxiv2026

Structures of the human sodium-citrate cotransporter NaCT with and without substrates

The human sodium-citrate cotransporter NaCT imports various tri- and dicarboxylates into the cell as TCA cycle intermediates. This substrate uptake process is driven by an inward sodium gradient. The protein is a member of the Divalent Anion-Sodium Symporter (DASS) family. Whereas extensive biochemical and structural studies have been carried out for NaCT, how the substrate binding and translocation is coupled to the sodium gradient remains unclear. Here using single particle cryo-electron microscopy, we determined the structures of the human NaCT protein in three states: sodium-free, in the presence of sodium, and sodium- and substrate-bound. These structures suggest a simultaneous binding mechanism for sodium-substrate coupling, distinct from the sequential binding, conformational selection mechanism previously observed for the bacterial DASS protein VcINDY.

biophysics↗

bioRxiv2025

Small molecule inhibitors of the NorA multidrug efflux pump potentiate antibiotic activity by binding the outward-open conformation

Antibiotic resistance is among the greatest threats of the modern era. Multidrug efflux pumps expel antibiotics from bacterial cells and present a particular challenge by conferring resistance to a broad range of antibiotic classes; however, there is currently a lack of potent and selective inhibitors. Here, we report the discovery of IMP-2380, a drug-like chemical probe for the multidrug efflux pump NorA that delivers low-nanomolar potentiation of ciprofloxacin activity in vitro and activity in an in vivo S. aureus infection model. A phenotypic high-throughput screen for inhibitors of the ciprofloxacin-activated SOS DNA repair pathway in methicillin-resistant Staphylococcus aureus (MRSA) identified hit compounds targeting NorA, and subsequent optimization established IMP-2380 as the most potent NorA inhibitor discovered to date. The structure of NorA bound to IMP-2380 was solved by cryo-electron microscopy at 2.52 [A] resolution, revealing that the small molecule locks the pump in the outward-open conformation. This closes the inner face and prevents antibiotics binding from the cytosol, providing an explanation for the exceptional potency of IMP-2380 and structure-activity relationship across the series. IMP-2380 represents an in vivo active NorA inhibitor, functioning via a structurally defined outward-open binding mode, and will enable future exploration of NorA as a druggable target to combat antibiotic resistance.

biochemistry↗

bioRxiv2022

Elevator mechanism dynamics in a sodium-coupled dicarboxylate transporter

VcINDY, the sodium-dependent dicarboxylate transporter from Vibrio cholerae, is responsible for C4- and C5-carboxylate uptake into cells. The molecular mechanism of how VcINDY physically moves substrates across the membrane, and does so in an energetically efficient manner, is unclear. Here, we use single-molecule fluorescence resonance energy transfer experiments to directly observe the individual mechanistic steps that VcINDY takes to translocate substrates across a lipid bilayer, and then test key predictions of transport cycle mechanistic models. Our data provide the first direct evidence that VcINDY undergoes stochastic, elevator-type conformational motions that enable substrate translocation. Kinetic analysis suggests that the two protomers of the VcINDY homodimer undergo those motions in a non-cooperative manner, and thus catalyze two independent transport reactions. The relative substrate independence of those motions supports the notion that the VcINDY transport cycle maintains strict co-substrate coupling using a cooperative binding mechanism. Finally, thermodynamic modeling provides insight into how such a cooperative binding mechanism provides a generalized approach to optimizing transport for many secondary active transporters. Significance StatementTransporter proteins use energy to move molecular materials into and out of cells. To be efficient, the transporter motions responsible for moving the molecules must be tightly choreographed to avoid wasting energy without transporting anything. By measuring the motions and kinetics of a prototypical transporter (VcINDY) at the single-molecule level, this study finds the first evidence that transporters like VcINDY achieve efficient transport by coordinating constantly dynamic, "elevator-type" motions while sitting in the cellular membrane. The efficiency of these surprisingly dynamic transporters is then revealed by thermodynamic modeling, which explains the molecular basis behind how highly cooperative, substrate binding reactions may have evolved as the optimal strategy for maximizing transporter efficiency.

biophysics↗

bioRxiv2022

Structural basis of ion - substrate coupling in the Na+-dependent dicarboxylate transporter VcINDY

The Na+-dependent dicarboxylate transporter from Vibrio cholerae (VcINDY) is a prototype for the divalent anion sodium symporter (DASS) family. While the utilization of an electrochemical Na+ gradient to power substrate transport is well established for VcINDY, the structural basis of this coupling between sodium and substrate binding is not currently understood. Here, using a combination of cryo-EM structure determination, succinate binding and site-directed cysteine alkylation assays, we demonstrate that the VcINDY protein couples sodium- and substrate-binding via a previously unseen induced-fit mechanism. In the absence of sodium, substrate binding is abolished, with the succinate binding regions exhibiting increased flexibility, including HPinb, TM10b and the substrate clamshell motifs. Upon sodium binding, these regions become structurally ordered and create a proper binding site for the substrate. Taken together, these results provide strong evidence that VcINDYs induced-fit mechanism is a result of the sodium-dependent formation of the substrate binding site.

biophysics↗

bioRxiv2019

Using machine learning to predict organismal growth temperatures from protein primary sequences

BackgroundThe link between protein or nucleic acid sequence and biochemical or organismal phenotype is essential for understanding the molecular mechanisms of evolution, reverse ecology, and designing proteins and genes with specific properties. However, it is difficult to practically make use of the relationship between sequence and phenotype due to the complex relationship between sequence and folding or activity. ResultsHere, we predict the originating species optimal growth temperatures of individual protein sequences using trained machine learning models. Both multilayer perceptron and k Nearest Neighbor regression outperformed linear regression could predict the originating species optimal growth temperature from protein sequences, achieving a root mean squared error of 3.6 {degrees}C. Similar machine learning models could predict organismal optimal growth pH and oxygen tolerance, and the quantitative properties of individual proteins or nucleic acids. ConclusionsUsing multilayer perceptron and k Nearest Neighbor regressions, we were able to build models specific to individual protein or nucleic acid families that can predict a variety of quantitative phenotypes. This methodology will be useful the in silico screening of individual mutations for particular properties, and also effective in the predicting the phenotypes of uncharacterized biological sequences and organisms.

bioinformatics↗

bioRxiv2018

Prediction of Optimal Growth Temperature using only Genome Derived Features

Optimal growth temperature is a fundamental characteristic of all living organisms. Knowledge of this temperature is central to the study the organism, the thermal stability and temperature dependent activity of its genes, and the bioprospecting of its genome for thermally adapted proteins. While high throughput sequencing methods have dramatically increased the availability of genomic information, the growth temperatures of the source organisms are often unknown. This limits the study and technological application of these species and their genomes. Here, we present a novel method for the prediction of growth temperatures of prokaryotes using only genomic sequences. By applying the reverse ecology principle that an organisms genome includes identifiable adaptations to its native environment, we can predict a species optimal growth temperature with an accuracy of 4.69 {degrees}C root-mean-square error and a correlation coefficient of 0.908. The accuracy can be further improved for specific taxonomic clades or by excluding psychrophiles. This method provides a valuable tool for the rapid calculation of organism growth temperature when only the genome sequence is known.

bioinformatics↗