Markov state modeling of membrane transport proteins

Ensemble Adaptive Sampling Scheme: Identifying an Optimal Sampling Strategy via Policy Ranking

Efficient sampling in biomolecular simulations is critical for accurately capturing the complex dynamic behaviors of biological systems. Adaptive sampling techniques aim to improve efficiency by focusing computational resources on the most relevant regions of the phase space. In this work, we present a framework for identifying the optimal sampling policy through metric-driven ranking. Our approach systematically evaluates the policy ensemble and ranks the policies based on their ability to explore the conformational space effectively. Through a series of biomolecular simulation case studies, we demonstrate that the choice of a different adaptive sampling policy at each round significantly outperforms single policy sampling, leading to faster convergence and improved sampling performance. This approach takes an ensemble of adaptive sampling policies and identifies the optimal policy for the next round based on current data. Beyond presenting this ensemble view of adaptive sampling, we also propose two sampling algorithms that approximate this ranking framework on the fly. The modularity of this framework allows incorporation of any adaptive sampling policy, making it versatile and suitable as a comprehensive adaptive sampling scheme.

Dissecting Large-Scale Structural Transitions in Membrane Transporters Using Advanced Simulation Technologies

Membrane transporters are integral membrane proteins that act as gatekeepers of the cell, controlling fundamental processes such as recruitment of nutrients and expulsion of waste material. At a basic level, transporters operate using the "alternating access model," in which transported substances are accessible from only one side of the membrane at a time. This model usually involves large-scale structural changes in the transporter, which often cannot be captured using unbiased, conventional molecular simulation techniques. In this article, we provide an overview of some of the major simulation techniques that have been applied to characterize the structural dynamics and energetics involved in the transition of membrane transporters between their functional states. After briefly introducing each technique, we discuss some of their advantages and limitations and provide some recent examples of their application to membrane transporters.

SWEET Family Transporters Act as Water-Conducting Carrier Proteins in Plants

Dedicated water channels are involved in the facilitated diffusion of water molecules across cell membranes in plants. Transporter proteins are also known to transport water molecules along with substrates; however, the molecular mechanism of water permeation is not well understood in plant transporters. Here, we show that plant sugar transporters from the SWEET (sugar will eventually be exported transporter) family act as water-conducting carrier proteins via a variety of passive and active mechanisms that allow the diffusion of water molecules from one side of the membrane to the other. This study provides a molecular perspective on how plant membrane transporters act as water carrier proteins, a topic that has not been extensively explored in the literature. Water permeation in membrane transporters could occur via four distinct mechanisms, which form our hypothesis for water transport in SWEETs. These hypotheses are tested using molecular dynamics simulations of the outward-facing, occluded, and inward-facing states of AtSWEET1 to identify the water permeation pathways and the flux associated with them. The hydrophobic gates at the center of the transport tunnel act as barriers that restrict water permeation. We have performed in silico single and double mutations of the hydrophobic gate residues to examine the changes in water conductivity. Surprisingly, the double mutant allows water permeation to the intracellular half of the membrane and forms a continuous water channel. These computational results are validated by experimentally examining the transport of hydrogen peroxide molecules by the AtSWEET family of transporters. We have also shown that the transport of hydrogen peroxide follows a mechanism similar to that of water transport in AtSWEET1. Finally, we conclude that similar water-conduction states are also present in other SWEETs due to the high degree of sequence and structural conservation exhibited by this transporter family.

Molecular insights into the elevator-type mechanism of the cyanobacterial bicarbonate transporter BicA

Cyanobacteria are responsible for up to 80% of aquatic carbon dioxide fixation and have evolved a specialized carbon concentrating mechanism to increase photosynthetic yield. As such, cyanobacteria are attractive targets for synthetic biology and engineering approaches to address the demands of global energy security, food production, and climate change for an increasing world's population. The bicarbonate transporter BicA is a sodium-dependent, low-affinity, high-flux bicarbonate symporter expressed in the plasma membrane of cyanobacteria. Despite extensive biochemical characterization of BicA, including the resolution of the BicA crystal structure, the dynamic understanding of the bicarbonate transport mechanism remains elusive. To this end, we have collected over 1 ms of all-atom molecular dynamics simulation data of the BicA dimer to elucidate the structural rearrangements involved in the substrate transport process. We further characterized the energetics of the transition of BicA protomers and investigated potential mutations that are shown to decrease the free energy barrier of conformational transitions. In all, our study illuminates a detailed mechanistic understanding of the conformational dynamics of bicarbonate transporters and provides atomistic insights to engineering these transporters for enhanced photosynthetic production.

Energetics of substrate transport in proton-dependent oligopeptide transporters

The PepTSo transporter mediates the transport of peptides across biological membranes. Despite advancements in structural biology, including cryogenic electron microscopy structures resolving PepTSo in different states, the molecular basis of peptide recognition and transport by PepTSo is not fully elucidated. In this study, we used molecular dynamics simulations, Markov State Models (MSMs), and Transition Path Theory (TPT) to investigate the transport mechanism of an alanine-alanine peptide (Ala-Ala) through the PepTSo transporter. Our simulations revealed conformational changes and key intermediate states involved in peptide translocation. We observed that the presence of the Ala-Ala peptide substrate lowers the free energy barriers associated with transition to the inward-facing state. We also show a proton transport model and analyzed the pharmacophore features of intermediate states, providing insights for rational drug design. These findings highlight the significance of substrate binding in modulating the conformational dynamics of PepTSo and identify critical residues that facilitate transport.

SWEET family transporters act as water conducting carrier proteins in plants

Dedicated water channels are involved in the facilitated diffusion of water molecules across the cell membrane in plants. Transporter proteins are also known to transport water molecules along with substrates, however the molecular mechanism of water permeation is not well understood in plant transporters. Here, we show plant sugar transporters from the SWEET (Sugar Will Eventually be Exported Transporter) family act as water-conducting carrier proteins via a variety of passive and active mechanisms that allow diffusion of water molecules from one side of the membrane to the other. This study provides a molecular perspective on how plant membrane transporters act as water carrier proteins, a topic that has not been extensively explored in literature. Water permeation in membrane transporters could occur via four distinct mechanisms which form our hypothesis for water transport in SWEETs. These hypothesis are tested using molecular dynamics simulations of the outward-facing, occluded, and inward-facing state of AtSWEET1 to identify the water permeation pathways and the flux associated with them. The hydrophobic gates at the center of the transport tunnel act as a barrier that restricts water permeation. We have performed in silico single and double mutations of the hydrophobic gate residues to examine the changes in the water conductivity. Surprisingly, the double mutant allows the water permeation to the intracellular half of the membrane and forms a continuous water channel. These computational results are validated by experimentally examining the transport of hydrogen peroxide molecules by the AtSWEET family of transporters. We have also shown that the transport of hydrogen peroxide follows the similar mechanism as water transport in AtSWEET1. Finally, we conclude that similar water-conduction states are also present in other SWEET transporters due to the high sequence and structure conservation exhibited by this transporter family.

Energetics of substrate transport in proton-dependent oligopeptide transporters

The PepT So transporter mediates the transport of peptides across biological membranes. Despite advancements in structural biology, including cryogenic electron microscopy structures resolving PepT So in different states, the molecular basis of peptide recognition and transport by PepT So is not fully elucidated. In this study, we employed molecular dynamics simulations, Markov State Models (MSMs), and Transition Path Theory (TPT) to investigate the transport mechanism of an alanine-alanine peptide (Ala-Ala) through the PepT So transporter. Our simulations revealed conformational changes and key intermediate states involved in peptide translocation. We observed that the presence of the Ala-Ala peptide substrate lowers the free energy barriers associated with transition to the inward-facing state. Furthermore, we elucidated the proton transport model and analyzed the pharmacophore features of intermediate states, providing insights for rational drug design. These findings highlight the significance of substrate binding in modulating the conformational dynamics of PepT So and identify critical residues that facilitate transport.

EnGens: a computational framework for generation and analysis of representative protein conformational ensembles

Proteins are dynamic macromolecules that perform vital functions in cells. A protein structure determines its function, but this structure is not static, as proteins change their conformation to achieve various functions. Understanding the conformational landscapes of proteins is essential to understand their mechanism of action. Sets of carefully chosen conformations can summarize such complex landscapes and provide better insights into protein function than single conformations. We refer to these sets as representative conformational ensembles. Recent advances in computational methods have led to an increase in the number of available structural datasets spanning conformational landscapes. However, extracting representative conformational ensembles from such datasets is not an easy task and many methods have been developed to tackle it. Our new approach, EnGens (short for ensemble generation), collects these methods into a unified framework for generating and analyzing representative protein conformational ensembles. In this work, we: (1) provide an overview of existing methods and tools for representative protein structural ensemble generation and analysis; (2) unify existing approaches in an open-source Python package, and a portable Docker image, providing interactive visualizations within a Jupyter Notebook pipeline; (3) test our pipeline on a few canonical examples from the literature. Representative ensembles produced by EnGens can be used for many downstream tasks such as protein-ligand ensemble docking, Markov state modeling of protein dynamics and analysis of the effect of single-point mutations.

EnGens: a computational framework for generation and analysis of representative protein conformational ensembles

Proteins are dynamic macromolecules that perform vital functions in cells. A protein structure determines its function, but this structure is not static, as proteins change their conformation to achieve various functions. Understanding the conformational landscapes of proteins is essential to understand their mechanism of action. Sets of carefully chosen conformations can summarize such complex landscapes and provide better insights into protein function than single conformations. We refer to these sets as representative conformational ensembles. Recent advances in computational methods have led to an increase in number of available structural datasets spanning conformational landscapes. However, extracting representative conformational ensembles from such datasets is not an easy task and many methods have been developed to tackle it. Our new approach, EnGens (short for ensemble generation), collects these methods into a unified framework for generating and analyzing protein conformational ensembles. In this work we: (1) provide an overview of existing methods and tools for protein structural ensemble generation and analysis; (2) unify existing approaches in an open-source Python package, and a portable Docker image, providing interactive visualizations within a Jupyter Notebook pipeline; (3) test our pipeline on a few canonical examples found in the literature. Representative ensembles produced by EnGens can be used for many downstream tasks such as protein-ligand ensemble docking, Markov state modeling of protein dynamics and analysis of the effect of single-point mutations.

Ins and Outs of Rocker Switch Mechanism in Major Facilitator Superfamily of Transporters

The major facilitator superfamily (MFS) of transporters consists of three classes of membrane transporters: symporters, uniporters, and antiporters. Despite such diverse functions, MFS transporters are believed to undergo similar conformational changes within their distinct transport cycles, known as the rocker-switch mechanism. While the similarities between conformational changes are noteworthy, the differences are also important since they could potentially explain the distinct functions of symporters, uniporters, and antiporters of the MFS superfamily. We reviewed a variety of experimental and computational structural data on a select number of antiporters, symporters, and uniporters from the MFS family to compare the similarities and differences of the conformational dynamics of three different classes of transporters.

Elucidating activation and deactivation dynamics of VEGFR-2 transmembrane domain with coarse-grained molecular dynamics simulations

The vascular endothelial growth factor receptor 2 (VEGFR-2) is a member of receptor tyrosine kinases (RTKs) and is a dimeric membrane protein that functions as a primary regulator of angiogenesis. As is usual with RTKs, spatial alignment of its transmembrane domain (TMD) is essential toward VEGFR-2 activation. Experimentally, the helix rotations within TMD around their own helical axes are known to participate importantly toward the activation process in VEGFR-2, but the detailed dynamics of the interconversion between the active and inactive TMD forms have not been clearly elucidated at the molecular level. Here, we attempt to elucidate the process by using coarse grained (CG) molecular dynamics (MD) simulations. We observe that inactive dimeric TMD in separation is structurally stable over tens of microseconds, suggesting that TMD itself is passive and does not allow spontaneous signaling of VEGFR-2. By starting from the active conformation, we reveal the mechanism of TMD inactivation through analyzing the CG MD trajectories. We observe that interconversions between a left-handed overlay and a right-handed one are essential for the process of going from an active TMD structure to the inactive form. In addition, our simulations find that the helices can rotate properly when the overlaying structure of the helices interconverts and when the crossing angle of the two helices changes by larger than ~40 degrees. As the activation right after the ligand attachment on VEGFR-2 will take place in the reverse manner of this inactivation process, these structural aspects will also appear importantly for the activation process. The rather large change in helix configuration for activation also explains why VEGFR-2 rarely self-activate and how the activating ligand structurally drive the whole VEGFR-2. This mechanism of TMD activation / inactivation within VEGFR-2 may help in further understanding the overall activation processes of other RTKs.

Multiagent Reinforcement Learning-Based Adaptive Sampling for Conformational Dynamics of Proteins

Machine learning is increasingly applied to improve the efficiency and accuracy of molecular dynamics (MD) simulations. Although the growth of distributed computer clusters has allowed researchers to obtain higher amounts of data, unbiased MD simulations have difficulty sampling rare states, even under massively parallel adaptive sampling schemes. To address this issue, several algorithms inspired by reinforcement learning (RL) have arisen to promote exploration of the slow collective variables (CVs) of complex systems. Nonetheless, most of these algorithms are not well-suited to leverage the information gained by simultaneously sampling a system from different initial states (e.g., a protein in different conformations associated with distinct functional states). To fill this gap, we propose two algorithms inspired by multiagent RL that extend the functionality of closely related techniques (REAP and TSLC) to situations where the sampling can be accelerated by learning from different regions of the energy landscape through coordinated agents. Essentially, the algorithms work by remembering which agent discovered each conformation and sharing this information with others at the action-space discretization step. A stakes function is introduced to modulate how different agents sense rewards from discovered states of the system. The consequences are three-fold: (i) agents learn to prioritize CVs using only relevant data, (ii) redundant exploration is reduced, and (iii) agents that obtain higher stakes are assigned more actions. We compare our algorithm with other adaptive sampling techniques (least counts, REAP, TSLC, and AdaptiveBandit) to show and rationalize the gain in performance.

Stable Isotope Fractionation of Metals and Metalloids in Plants: A Review

This work critically reviews stable isotope fractionation of essential (B, Mg, K, Ca, Fe, Ni, Cu, Zn, Mo), beneficial (Si), and non-essential (Cd, Tl) metals and metalloids in plants. The review (i) provides basic principles and methodologies for non-traditional isotope analyses, (ii) compiles isotope fractionation for uptake and translocation for each element and connects them to physiological processes, and (iii) interlinks knowledge from different elements to identify common and contrasting drivers of isotope fractionation. Different biological and physico-chemical processes drive isotope fractionation in plants. During uptake, Ca and Mg fractionate through root apoplast adsorption, Si through diffusion during membrane passage, Fe and Cu through reduction prior to membrane transport in strategy I plants, and Zn, Cu, and Cd through membrane transport. During translocation and utilization, isotopes fractionate through precipitation into insoluble forms, such as phytoliths (Si) or oxalate (Ca), structural binding to cell walls (Ca), and membrane transport and binding to soluble organic ligands (Zn, Cd). These processes can lead to similar (Cu, Fe) and opposing (Ca vs. Mg, Zn vs. Cd) isotope fractionation patterns of chemically similar elements in plants. Isotope fractionation in plants is influenced by biotic factors, such as phenological stages and plant genetics, as well as abiotic factors. Different nutrient supply induced shifts in isotope fractionation patterns for Mg, Cu, and Zn, suggesting that isotope process tracing can be used as a tool to detect and quantify different uptake pathways in response to abiotic stresses. However, the interpretation of isotope fractionation in plants is challenging because many isotope fractionation factors associated with specific processes are unknown and experiments are often exploratory. To overcome these limitations, fundamental geochemical research should expand the database of isotope fractionation factors and disentangle kinetic and equilibrium fractionation. In addition, plant growth studies should further shift toward hypothesis-driven experiments, for example, by integrating contrasting nutrient supplies, using established model plants, genetic approaches, and by combining isotope analyses with complementary speciation techniques. To fully exploit the potential of isotope process tracing in plants, the interdisciplinary expertise of plant and isotope geochemical scientists is required.

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.