Werner Treptow is a Professor of Computational Molecular Biophysics at the Universidade de Brasília. He holds a B.S. in Biology (1998) and a Ph.D. in Molecular Biology (2003) from the Universidade de Brasília, as well as a Ph.D. in Theoretical and Computational Chemistry from the Université Henri Poincaré (2004). He completed postdoctoral training with Prof. Mounir Tarek in France and Prof. Michael L. Klein at the University of Pennsylvania. Since joining UnB in 2009, his research has focused on the structure, function, and regulation of membrane proteins, alongside the training of graduate students and postdoctoral fellows. He has held visiting professor positions at Temple University (2012–2013) and the University of Chicago (2021–2023), contributed extensively as a journal reviewer, and currently serves as an Associate Editor at Frontiers in Cellular Neuroscience.
EDUCATION
2001 - 2004 University Henri Poincaré - UHP, France
Ph.D. in Theoretical and Computational Chemistry
1999 - 2003 University of Brasília - UNB, Brasília, Brazil
Ph.D. in Molecular Biology – Computational Molecular Biophysics
1994 - 1998 B.S., Biology, Federal University of Goiás - UFG, Brazil
RESEARCH, TEACHING, or OTHER INTERESTS
Multidisciplinary, Biophysics
46
Scopus Publications
1794
Scholar Citations
26
Scholar h-index
32
Scholar i10-index
Scopus Publications
Sevoflurane Inhibits Layer 5 Pyramidal Neurons via Kv1.2-Dependent Modulation of Subthreshold Currents Aelton S. Araujo, Gabriel M. de Queiroz, Sérgio Ruschi B. Silva, Werner Treptow, Katarina E. Leao Journal of Neurochemistry, 2026 General anesthetics reduce cortical activity and disrupt consciousness, yet the molecular mechanisms underlying their effects on neocortical neurons remain incompletely understood. Recent evidence implicates layer 5 pyramidal neurons (L5 PNs) as critical targets, particularly through anesthetic‐induced decoupling of distal apical dendritic inputs from somatic output. While several anesthetics impair L5 excitability, the ion channels mediating this effect have yet to be clearly identified. Voltage‐gated Kv1.2 potassium channels have emerged as compelling candidates due to their high expression in L5 PNs and their known potentiation by volatile anesthetics. In this study, we investigated the effects of low‐dose sevoflurane (~22 μM) on L5 PNs in the primary auditory cortex of adult mice using whole‐cell patch‐clamp recordings. Sevoflurane significantly suppressed firing and induced cell‐type‐specific changes in membrane properties: depolarizing the resting potential in type A neurons and increasing input resistance and altering action potential shape in type B neurons. Application of the selective Kv1.2 blocker TsTX‐Kα partially reversed these effects at subthreshold membrane potentials, implicating Kv1.2 channel potentiation in the modulation of neuronal excitability. Supporting that view, NEURON simulations using a detailed biophysical model of thick‐tufted L5b pyramidal neurons further revealed a significant sevoflurane‐induced increase in persistent K + conductance, consistent with Kv1.2 potentiation. To our knowledge, this is the first study to demonstrate distinct, cell‐type‐specific effects of sevoflurane on L5 PNs and to establish the functional relevance of Kv1.2 channel potentiation in anesthetic suppression of cortical excitability. These findings offer new insights into the molecular actions of sevoflurane and support a broader role for Kv1.2 channels in mediating anesthetic‐induced outcomes. image
Quantum machine learning-based electrokinetic mining for the identification of nanoparticles and exosomes with minimal training data Abhimanyu Thakur, Pedro Correia Santos Bezerra, Abhishek, Shihao Zeng, Kui Zhang, Werner Treptow, Alexander Luna, Urszula Dougherty, Akushika Kwesi, Isabella R. Huang, Christine Bestvina, Marina Chiara Garassino, Fuyu Duan, Yash Gokhale, Bin Duan, Yin Chen, Qizhou Lian, Marc Bissonnette, Jianpan Huang, Huanhuan Joyce Chen Bioactive Materials, 2025 Synthetic and naturally occurring particles, such as nanoparticles (NPs) and exosomes; a type of extracellular vesicles (EVs), have garnered widespread attention across various fields, including biomaterials, oncology, and delivery systems for drugs and vaccines. Traditional methods for identifying NPs and EVs, such as transmission electron microscopy, are often prohibitively expensive and labor-intensive. As an alternative, the assessment of electrokinetic attributes such as zeta potential or electrophoretic mobility, conductance, and mean count rate, offers a more cost-effective, rapid, and reliable means of characterizing these particles. In this context, we introduce the first application of a quantum machine learning (QML)-based electrokinetic mining for the identification of green-synthesized iron- and cobalt-based NPs, as well as exosomes derived from human embryonic stem cells (hESC), human lung cancer (A549) cells, and colorectal cancer (CRC) cells, based solely on their electrokinetic attributes. Comparative analyses involving cross-validation, train-test splits, confusion matrices, and Receiver Operating Characteristic (ROC) curves revealed that classical ML techniques could accurately identify the types of NPs and EVs. Notably, QML demonstrated proficiency in differentiating between various NPs and EVs, including the distinction of EVs in the plasma of CRC patients versus those of healthy individuals. Furthermore, QML's application has been extended to the identification of NPs along with EVs in the plasma of CRC patients and experimental mice, achieving higher prediction performance even with a minimal training dataset, demonstrating that QML based electrokinetic mining could identify NPs or EVs with minimal training data, thereby facilitating novel clinical development in the realm of liquid biopsies.
Investigating Statistical Conditions of Coevolutionary Signals that Enable Algorithmic Predictions of Protein Partners José Fiorote, João Alves, Letícia Stock, Werner Treptow Journal of Chemical Information and Modeling, 2025 High Resolution Image Download MS PowerPoint Slide This study examines the statistical conditions of coevolutionary signals that allow algorithmic predictions of protein partners based on amino acid sequences rather than 3D structures. It introduces a Markov stochastic model that predicts the number of correct protein partners based on coevolutionary information. The model defines state probabilities using a Poisson mixture of normal distributions, with key parameters including the total number of protein sequences M, the coevolutionary information gap α, and variance σ 0 2 . The model suggests that algorithmic approaches that maximize coevolutionary information cannot effectively resolve partners in protein families with a large number of sequences M ≥ 100. The model shows that true-positive (TP) rates can be enhanced by disregarding mismatches among similar sequences. This approach allows a distinction, in terms of {α, σ 0 2 }, between optimized solutions with trivial errors and other degenerate solutions. Our findings enable the a priori classification of protein families where partners can be reliably predicted by ignoring trivial errors between similar sequences, advancing the understanding of coevolutionary models for large protein data sets.
The binding and mechanism of a positive allosteric modulator of Kv3 channels Qiansheng Liang, Gamma Chi, Leonardo Cirqueira, Lianteng Zhi, Agostino Marasco, Nadia Pilati, Martin J. Gunthorpe, Giuseppe Alvaro, Charles H. Large, David B. Sauer, Werner Treptow, Manuel Covarrubias Nature Communications, 2024 Small-molecule modulators of diverse voltage-gated K + (Kv) channels may help treat a wide range of neurological disorders. However, developing effective modulators requires understanding of their mechanism of action. We apply an orthogonal approach to elucidate the mechanism of action of an imidazolidinedione derivative (AUT5), a highly selective positive allosteric modulator of Kv3.1 and Kv3.2 channels. AUT5 modulation involves positive cooperativity and preferential stabilization of the open state. The cryo-EM structure of the Kv3.1/AUT5 complex at a resolution of 2.5 Å reveals four equivalent AUT5 binding sites at the extracellular inter-subunit interface between the voltage-sensing and pore domains of the channel’s tetrameric assembly. Furthermore, we show that the unique extracellular turret regions of Kv3.1 and Kv3.2 essentially govern the selective positive modulation by AUT5. High-resolution apo and bound structures of Kv3.1 demonstrate how AUT5 binding promotes turret rearrangements and interactions with the voltage-sensing domain to favor the open conformation.
Unveiling Tst3, a Multi-Target Gating Modifier Scorpion α Toxin from Tityus stigmurus Venom of Northeast Brazil: Evaluation and Comparison with Well-Studied Ts3 Toxin of Tityus serrulatus Diogo Vieira Tibery, João Antonio Alves Nunes, Daniel Oliveira da Mata, Luis Felipe Santos Menezes, Adolfo Carlos Barros de Souza, Matheus de Freitas Fernandes-Pedrosa, Werner Treptow, Elisabeth Ferroni Schwartz Toxins, 2024 Studies on the interaction sites of peptide toxins and ion channels typically involve site-directed mutations in toxins. However, natural mutant toxins exist among them, offering insights into how the evolutionary process has conserved crucial sequences for activities and molecular target selection. In this study, we present a comparative investigation using electrophysiological approaches and computational analysis between two alpha toxins from evolutionarily close scorpion species of the genus Tityus, namely, Tst3 and Ts3 from T. stigmurus and T. serrulatus, respectively. These toxins exhibit three natural substitutions near the C-terminal region, which is directly involved in the interaction between alpha toxins and Nav channels. Additionally, we characterized the activity of the Tst3 toxin on Nav1.1-Nav1.7 channels. The three natural changes between the toxins did not alter sensitivity to Nav1.4, maintaining similar intensities regarding their ability to alter opening probabilities, delay fast inactivation, and induce persistent currents. Computational analysis demonstrated a preference for the down conformation of VSD4 and a shift in the conformational equilibrium towards this state. This illustrates that the sequence of these toxins retained the necessary information, even with alterations in the interaction site region. Through electrophysiological and computational analyses, screening of the Tst3 toxin on sodium isoform revealed its classification as a classic α-NaTx with a broad spectrum of activity. It effectively delays fast inactivation across all tested isoforms. Structural analysis of molecular energetics at the interface of the VSD4-Tst3 complex further confirmed this effect.
Allosteric Modulation of Membrane Proteins by Small Low-Affinity Ligands Werner Treptow Journal of Chemical Information and Modeling, 2023 Membrane proteins may respond to a variety of ligands under an applied external stimulus. These ligands include small low-affinity molecules that account for functional effects in the mM range. Understanding the modulation of protein function by low-affinity ligands requires characterizing their atomic-level interactions under dilution, challenging the current resolution of theoretical and experimental routines. Part of the problem derives from the fact that small low-affinity ligands may interact with multiple sites of a membrane protein in a highly degenerate manner to a degree that it is better conceived as a partition phenomenon, hard to track at the molecular interface of the protein. Looking for new developments in the field, we rely on the classic two-state Boltzmann model to devise a novel theoretical description of the allosteric modulation mechanism of membrane proteins in the presence of small low-affinity ligands and external stimuli. Free energy stability of the partition process and its energetic influence on the protein coupling with the external stimulus are quantified. The outcome is a simple formulation that allows the description of the equilibrium shifts of the protein in terms of the grand-canonical partition function of the ligand at dilute concentrations. The model's predictions of the spatial distribution and response probability shift across a variety of ligand concentrations, and thermodynamic conjugates can be directly compared to macroscopic measurements, making it especially useful to interpret experimental data at the atomic level. Illustration and discussion of the theory is shown in the context of general anesthetics and voltage-gated channels for which structural data are available.
Concentration-dependent thermodynamic analysis of the partition process of small ligands into proteins Leonardo Cirqueira, Letícia Stock, Werner Treptow Computational and Structural Biotechnology Journal, 2022 In the category of functional low-affinity interactions, small ligands may interact with multiple protein sites in a highly degenerate manner. Better conceived as a partition phenomenon at the molecular interface of proteins, such low-affinity interactions appear to be hidden to our current experimental resolution making their structural and functional characterization difficult in the low concentration regime of physiological processes. Characterization of the partition phenomenon under higher chemical forces could be a relevant strategy to tackle the problem provided the results can be scaled back to the low concentration range. Far from being trivial, such scaling demands a concentration-dependent understanding of self-interactions of the ligands, structural perturbations of the protein, among other molecular effects. Accordingly, we elaborate a novel and detailed concentration-dependent thermodynamic analysis of the partition process of small ligands aiming at characterizing the stability and structure of the dilute phenomenon from high concentrations. In analogy to an "aggregate" binding constant of a small molecule over multiple sites of a protein receptor, the model defines the stability of the process as a macroscopic equilibrium constant for the partition number of ligands that can be used to analyze biochemical and functional data of two-component systems driven by low-affinity interactions. Acquisition of such modeling-based structural information is expected to be highly welcome by revealing more traceable protein-binding spots for non-specific ligands.
Trivial and nontrivial error sources account for misidentification of protein partners in mutual information approaches Camila Pontes, Miguel Andrade, José Fiorote, Werner Treptow Scientific Reports, 2021 The problem of finding the correct set of partners for a given pair of interacting protein families based on multi-sequence alignments (MSAs) has received great attention over the years. Recently, the native contacts of two interacting proteins were shown to store the strongest mutual information (MI) signal to discriminate MSA concatenations with the largest fraction of correct pairings. Although that signal might be of practical relevance in the search for an effective heuristic to solve the problem, the number of MSA concatenations with near-native MI is large, imposing severe limitations. Here, a Genetic Algorithm that explores possible MSA concatenations according to a MI maximization criteria is shown to find degenerate solutions with two error sources, arising from mismatches among (i) similar and (ii) non-similar sequences. If mistakes made among similar sequences are disregarded, type-(i) solutions are found to resolve correct pairings at best true positive (TP) rates of 70%—far above the very same estimates in type-(ii) solutions. A machine learning classification algorithm helps to show further that differences between optimized solutions based on TP rates are not artificial and may have biological meaning associated with the three-dimensional distribution of the MI signal. Type-(i) solutions may therefore correspond to reliable results for predictive purposes, found here to be more likely obtained via MI maximization across protein systems having a minimum critical number of amino acid contacts on their interaction surfaces (N > 200).
Donepezil Inhibits Acetylcholinesterase via Multiple Binding Modes at Room Temperature Monica A. Silva, Alessandra S. Kiametis, Werner Treptow Journal of Chemical Information and Modeling, 2020 Donepezil is a second generation acetylcholinesterase (AChE) inhibitor for treatment of Alzheimer’s disease (AD). AChE is important for neurotransmission at neuromuscular junctions and cholinergic brain synapses by hydrolyzing acetylcholine into acetate and choline. In vitro data support that donepezil is a reversible, mixed competitive and noncompetitive inhibitor of AChE. The experimental fact then suggests a more complex binding mechanism beyond the molecular view in X-ray models resolved at cryogenic temperatures that show a unique binding mode of donepezil in the active site of the enzyme. Aiming at clarifying the mechanism behind that mixed competitive and noncompetitive nature of the inhibitor, we have applied molecular dynamics (MD) simulations and docking and free-energy calculations to investigate microscopic details and energetics of donepezil association for conditions of substrate-free and -bound states of the enzyme. Liquid-phase MD simulation at room temperature shows AChE transits between “open” and “closed” conformations to control accessibility to the active site and ligand binding. As shown by docking and free-energy calculations, association of donepezil involves its reversible axial displacement and reorientation in the active site of the enzyme, assisted by water molecules. Donepezil binds equally well the main-door anionic binding site PAS, the acyl pocket, and the catalytic site CAS by respectively adopting outward–inward–inward orientations regardless of substrate occupancy–the overall stability of that reaction process depends however on co-occupancy of the enzyme being preferential for its substrate-free state. All together, our findings support a physiologically relevant mechanism of AChE inhibition by donepezil involving multistable interactions modes at the molecular origin of the inhibitor’s activity.
Nucleosome binding peptide presents laudable biophysical and in vivo effects Kaian Teles, Vinicius Fernandes, Isabel Silva, Manuela Leite, Cesar Grisolia, Vincenzo R. Lobbia, Hugo van Ingen, Rodrigo Honorato, Paulo Lopes-de-Oliveira, Werner Treptow, Guilherme Santos Biomedicine and Pharmacotherapy, 2020
Folding simulations of a three-dimensional protein model with a nonspecific hydrophobic energy function Physical Review E Statistical Nonlinear and Soft Matter Physics, 2001
Sevoflurane Inhibits Layer 5 Pyramidal Neurons via Kv1. 2‐Dependent Modulation of Subthreshold Currents AS Araujo, GM de Queiroz, SRB Silva, W Treptow, KE Leao Journal of Neurochemistry 170 (1), e70360 , 2026 2026
Quantum machine learning-based electrokinetic mining for the identification of nanoparticles and exosomes with minimal training data A Thakur, PCS Bezerra, S Zeng, K Zhang, W Treptow, A Luna, ... Bioactive Materials 51, 414-430 , 2025 2025 Citations: 9
Investigating Statistical Conditions of Coevolutionary Signals that Enable Algorithmic Predictions of Protein Partners J Fiorote, J Alves, L Stock, W Treptow Journal of Chemical Information and Modeling 65 (8), 4107-4115 , 2025 2025
Isoleucine gate blocks K + conduction in C-type inactivation W Treptow, Y Liu, CAZ Bassetto, BI Pinto, JA Alves Nunes, RM Uriarte, ... Elife 13, e97696 , 2024 2024 Citations: 8
Unveiling Tst3, a Multi-Target Gating Modifier Scorpion α Toxin from Tityus stigmurus Venom of Northeast Brazil: Evaluation and Comparison with Well-Studied Ts3 Toxin of … DV Tibery, JAA Nunes, DO da Mata, LFS Menezes, ACB de Souza, ... Toxins 16 (6), 257 , 2024 2024 Citations: 4
The binding and mechanism of a positive allosteric modulator of Kv3 channels Q Liang, G Chi, L Cirqueira, L Zhi, A Marasco, N Pilati, MJ Gunthorpe, ... Nature Communications 15 (1), 2533 , 2024 2024 Citations: 18
Allosteric modulation of membrane proteins by small low-affinity ligands W Treptow Journal of Chemical Information and Modeling 63 (7), 2047-2057 , 2023 2023 Citations: 4
α-Alkylidene δ-lactones inhibit quorum sensing phenotypes in Chromobacterium strain CV026 showing interaction with the CviR receptor F Favero, TA Tolentino, V Fernandes, W Treptow, AL Pereira, ... RSC advances 13 (26), 18045-18057 , 2023 2023 Citations: 5
Concentration-dependent thermodynamic analysis of the partition process of small ligands into proteins L Cirqueira, L Stock, W Treptow Computational and Structural Biotechnology Journal 20, 4885-4891 , 2022 2022 Citations: 3
Trivial and nontrivial error sources account for misidentification of protein partners in mutual information approaches C Pontes, M Andrade, J Fiorote, W Treptow Scientific reports 11 (1), 6902 , 2021 2021 Citations: 4
Donepezil inhibits acetylcholinesterase via multiple binding modes at room temperature MA Silva, AS Kiametis, W Treptow Journal of Chemical Information and Modeling 60 (7), 3463-3471 , 2020 2020 Citations: 74
Nucleosome binding peptide presents laudable biophysical and in vivo effects K Teles, V Fernandes, I Silva, M Leite, C Grisolia, VR Lobbia, H van Ingen, ... Biomedicine & Pharmacotherapy 121, 109678 , 2020 2020 Citations: 9
Coevolutive, evolutive and stochastic information in protein-protein interactions M Andrade, C Pontes, W Treptow Computational and structural biotechnology journal 17, 1429-1435 , 2019 2019 Citations: 7
Atomistic model for simulations of the sedative hypnotic drug 2, 2, 2-trichloroethanol AS Kiametis, L Stock, L Cirqueira, W Treptow ACS omega 3 (11), 15916-15923 , 2018 2018 Citations: 14
Binding of the general anesthetic sevoflurane to ion channels L Stock, J Hosoume, L Cirqueira, W Treptow PLoS computational biology 14 (11), e1006605 , 2018 2018 Citations: 28
Fat nucleosome: role of lipids on chromatin V Fernandes, K Teles, C Ribeiro, W Treptow, G Santos Progress in Lipid Research 70, 29-34 , 2018 2018 Citations: 26
Concentration-dependent binding of small ligands to multiple saturable sites in membrane proteins L Stock, J Hosoume, W Treptow Scientific Reports 7 (1), 5734 , 2017 2017 Citations: 26
Biophysical studies of cholesterol effects on chromatin [S] ITG Silva, V Fernandes, C Souza, W Treptow, GM Santos Journal of Lipid Research 58 (5), 934-940 , 2017 2017 Citations: 29
Positive Allosteric Modulation of Kv Channels by Sevoflurane: Insights into the Structural Basis of Inhaled Anesthetic Action Q Liang, WD Anderson, ST Jones, CS Souza, JM Hosoume, W Treptow, ... PLoS One 10 (11), e0143363 , 2015 2015 Citations: 43
Mechanistic insights into the modulation of voltage-gated ion channels by inhalational anesthetics M Covarrubias, AF Barber, V Carnevale, W Treptow, RG Eckenhoff Biophysical journal 109 (10), 2003-2011 , 2015 2015 Citations: 67
MOST CITED SCHOLAR PUBLICATIONS
Intermediate states of the Kv1. 2 voltage sensor from atomistic molecular dynamics simulations L Delemotte, M Tarek, ML Klein, C Amaral, W Treptow Proceedings of the National Academy of Sciences 108 (15), 6109-6114 , 2011 2011 Citations: 212
Modeling membranes under a transmembrane potential L Delemotte, F Dehez, W Treptow, M Tarek The Journal of Physical Chemistry B 112 (18), 5547-5550 , 2008 2008 Citations: 129
Environment of the gating charges in the Kv1. 2 Shaker potassium channel W Treptow, M Tarek Biophysical journal 90 (9), L64-L66 , 2006 2006 Citations: 100
Pore waters regulate ion permeation in a calcium release-activated calcium channel H Dong, G Fiorin, V Carnevale, W Treptow, ML Klein Proceedings of the National Academy of Sciences 110 (43), 17332-17337 , 2013 2013 Citations: 87
Gating motions in voltage-gated potassium channels revealed by coarse-grained molecular dynamics simulations W Treptow, SJ Marrink, M Tarek The Journal of Physical Chemistry B 112 (11), 3277-3282 , 2008 2008 Citations: 79
Affinity of C 60 Neat Fullerenes with Membrane Proteins: A Computational Study on Potassium Channels S Kraszewski, M Tarek, W Treptow, C Ramseyer ACS nano 4 (7), 4158-4164 , 2010 2010 Citations: 75
Donepezil inhibits acetylcholinesterase via multiple binding modes at room temperature MA Silva, AS Kiametis, W Treptow Journal of Chemical Information and Modeling 60 (7), 3463-3471 , 2020 2020 Citations: 74
Sodium ion binding sites and hydration in the lumen of a bacterial ion channel from molecular dynamics simulations V Carnevale, W Treptow, ML Klein The Journal of Physical Chemistry Letters 2 (19), 2504-2508 , 2011 2011 Citations: 74
Conduction in a biological sodium selective channel L Stock, L Delemotte, V Carnevale, W Treptow, ML Klein The journal of physical chemistry B 117 (14), 3782-3789 , 2013 2013 Citations: 68
Mechanistic insights into the modulation of voltage-gated ion channels by inhalational anesthetics M Covarrubias, AF Barber, V Carnevale, W Treptow, RG Eckenhoff Biophysical journal 109 (10), 2003-2011 , 2015 2015 Citations: 67
Exploring conformational states of the bacterial voltage-gated sodium channel NavAb via molecular dynamics simulations C Amaral, V Carnevale, ML Klein, W Treptow Proceedings of the National Academy of Sciences 109 (52), 21336-21341 , 2012 2012 Citations: 64
Effect of sensor domain mutations on the properties of voltage-gated ion channels: molecular dynamics studies of the potassium channel Kv1. 2 L Delemotte, W Treptow, ML Klein, M Tarek Biophysical Journal 99 (9), L72-L74 , 2010 2010 Citations: 64
Initial response of the potassium channel voltage sensor to a transmembrane potential W Treptow, M Tarek, ML Klein Journal of the American Chemical Society 131 (6), 2107-2109 , 2009 2009 Citations: 61
Coupled motions between pore and voltage-sensor domains: a model for Shaker B, a voltage-gated potassium channel W Treptow, B Maigret, C Chipot, M Tarek Biophysical journal 87 (4), 2365-2379 , 2004 2004 Citations: 44
Positive Allosteric Modulation of Kv Channels by Sevoflurane: Insights into the Structural Basis of Inhaled Anesthetic Action Q Liang, WD Anderson, ST Jones, CS Souza, JM Hosoume, W Treptow, ... PLoS One 10 (11), e0143363 , 2015 2015 Citations: 43
K+ conduction in the selectivity filter of potassium channels is monitored by the charge distribution along their sequence W Treptow, M Tarek Biophysical journal 91 (10), L81-L83 , 2006 2006 Citations: 41
Molecular mapping of general anesthetic sites in a voltage-gated ion channel AF Barber, Q Liang, C Amaral, W Treptow, M Covarrubias Biophysical journal 101 (7), 1613-1622 , 2011 2011 Citations: 40
Molecular restraints in the permeation pathway of ion channels W Treptow, M Tarek Biophysical journal 91 (3), L26-L28 , 2006 2006 Citations: 40
Hinge-bending motions in the pore domain of a bacterial voltage-gated sodium channel AF Barber, V Carnevale, SG Raju, C Amaral, W Treptow, ML Klein Biochimica et Biophysica Acta (BBA)-Biomembranes 1818 (9), 2120-2125 , 2012 2012 Citations: 38
Self assembly of peptides near or within membranes using coarse grained MD simulations A Khalfa, W Treptow, B Maigret, M Tarek Chemical Physics 358 (1-2), 161-170 , 2009 2009 Citations: 38
