scholarly journals Generative Models of Conformational Dynamics

Author(s):  
Christopher James Langmead
2017 ◽  
Author(s):  
Jana Shen ◽  
Zhi Yue ◽  
Helen Zgurskaya ◽  
Wei Chen

AcrB is the inner-membrane transporter of E. coli AcrAB-TolC tripartite efflux complex, which plays a major role in the intrinsic resistance to clinically important antibiotics. AcrB pumps a wide range of toxic substrates by utilizing the proton gradient between periplasm and cytoplasm. Crystal structures of AcrB revealed three distinct conformational states of the transport cycle, substrate access, binding and extrusion, or loose (L), tight (T) and open (O) states. However, the specific residue(s) responsible for proton binding/release and the mechanism of proton-coupled conformational cycling remain controversial. Here we use the newly developed membrane hybrid-solvent continuous constant pH molecular dynamics technique to explore the protonation states and conformational dynamics of the transmembrane domain of AcrB. Simulations show that both Asp407 and Asp408 are deprotonated in the L/T states, while only Asp408 is protonated in the O state. Remarkably, release of a proton from Asp408 in the O state results in large conformational changes, such as the lateral and vertical movement of transmembrane helices as well as the salt-bridge formation between Asp408 and Lys940 and other sidechain rearrangements among essential residues.Consistent with the crystallographic differences between the O and L protomers, simulations offer dynamic details of how proton release drives the O-to-L transition in AcrB and address the controversy regarding the proton/drug stoichiometry. This work offers a significant step towards characterizing the complete cycle of proton-coupled drug transport in AcrB and further validates the membrane hybrid-solvent CpHMD technique for studies of proton-coupled transmembrane proteins which are currently poorly understood. <p><br></p>


Author(s):  
Balaji Selvam ◽  
Ya-Chi Yu ◽  
Liqing Chen ◽  
Diwakar Shukla

<p>The SWEET family belongs to a class of transporters in plants that undergoes large conformational changes to facilitate transport of sugar molecules across the cell membrane. However, the structures of their functionally relevant conformational states in the transport cycle have not been reported. In this study, we have characterized the conformational dynamics and complete transport cycle of glucose in OsSWEET2b transporter using extensive molecular dynamics simulations. Using Markov state models, we estimated the free energy barrier associated with different states as well as 1 for the glucose the transport mechanism. SWEETs undergoes structural transition to outward-facing (OF), Occluded (OC) and inward-facing (IF) and strongly support alternate access transport mechanism. The glucose diffuses freely from outside to inside the cell without causing major conformational changes which means that the conformations of glucose unbound and bound snapshots are exactly same for OF, OC and IF states. We identified a network of hydrophobic core residues at the center of the transporter that restricts the glucose entry to the cytoplasmic side and act as an intracellular hydrophobic gate. The mechanistic predictions from molecular dynamics simulations are validated using site-directed mutagenesis experiments. Our simulation also revealed hourglass like intermediate states making the pore radius narrower at the center. This work provides new fundamental insights into how substrate-transporter interactions actively change the free energy landscape of the transport cycle to facilitate enhanced transport activity.</p>


2019 ◽  
Author(s):  
Qi Yuan ◽  
Alejandro Santana-Bonilla ◽  
Martijn Zwijnenburg ◽  
Kim Jelfs

<p>The chemical space for novel electronic donor-acceptor oligomers with targeted properties was explored using deep generative models and transfer learning. A General Recurrent Neural Network model was trained from the ChEMBL database to generate chemically valid SMILES strings. The parameters of the General Recurrent Neural Network were fine-tuned via transfer learning using the electronic donor-acceptor database from the Computational Material Repository to generate novel donor-acceptor oligomers. Six different transfer learning models were developed with different subsets of the donor-acceptor database as training sets. We concluded that electronic properties such as HOMO-LUMO gaps and dipole moments of the training sets can be learned using the SMILES representation with deep generative models, and that the chemical space of the training sets can be efficiently explored. This approach identified approximately 1700 new molecules that have promising electronic properties (HOMO-LUMO gap <2 eV and dipole moment <2 Debye), 6-times more than in the original database. Amongst the molecular transformations, the deep generative model has learned how to produce novel molecules by trading off between selected atomic substitutions (such as halogenation or methylation) and molecular features such as the spatial extension of the oligomer. The method can be extended as a plausible source of new chemical combinations to effectively explore the chemical space for targeted properties.</p>


2018 ◽  
Author(s):  
Alexander Carl DeHaven

This thesis contains four topic areas: a review of single-molecule microscropy methods and splicing, conformational dynamics of stem II of the U2 snRNA, the impact of post-transcriptional modifications on U2 snRNA folding dynamics, and preliminary findings on Mango aptamer folding dynamics.


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