## Workshop 2: Multiple Faces of Biomolecular Electrostatics

### Organizers

Emil Alexov
Computational Biophysics and Bioinformatics, Clemson University
Bo Li
Department of Mathematics, University of California, San Diego
Ray Luo
Molecular Biology and Biochemistry, University of California,
Guowei Wei
Department of Mathematics, Michigan State University

Electrostatic interactions are fundamental in nature and ubiquitous in all biomolecules, including proteins, nucleic acids, lipid bilayers, sugars, etc. Electrostatic interactions are inherently of long range, which leads to computational challenges. Since 65-90 percent of cellular mass is water under physiological condition, biomolecules live in a heterogeneous environment, where they interact with a wide range of aqueous ions, counterions, and other molecules. As a result, electrostatic interactions often manifest themselves in a vast variety of different forms, due to polarization, hyperpolarization, vibrational and rotational averages, screening effect, etc, to mention just a few. The importance of electrostatics in biomolecular systems cannot be overemphasized because they underpin the molecular mechanism for almost all important biological processes, including signal transduction, DNA recognition, transcription, post-translational modification, translation, protein folding and protein ligand binding. In general, electrostatics is often the fundamental mechanism for macromolecular structure, function, dynamics and transport. Modeling and understanding the role of electrostatics in biomolecular systems are challenging tasks, since these systems are very complicated, made of macromolecules composed of hundreds of thousands or millions of atoms, and at the same time, surrounded by millions of water molecules, which in turn constantly change their positions and orientations. The number of degrees of freedom in explicit modeling of biomolecular systems is so large that it is frequently computationally prohibited for large systems or cases involving extremely large dimensions. Implicit models and multiscale approaches offer an alternative approach that dramatically reduces the computational cost, while being accurate enough to predict experimentally measurable quantities. Despite enormous efforts in the past two decades, important challenges remain in electrostatic modeling and computation. These include the definition of solvent-solute interfaces, nonlocal dielectric effects, finite size effects, nonlinear solvent response to solute perturbation, the representation of solvent microstructures, the solution of the corresponding nonlinear partial differential equations (PDEs) for irregularly shaped molecular boundaries, the treatment of solvent polarization and multi-valent ions, the formulation and solution of nonlinear integral equations (IEs), liquid density functional theory, and variational multiscale modeling of the dynamics and transport of biomolecular systems. The advantages and limitations of various methodologies are to be explored. Successful approaches to these challenges require combined efforts of physicists, mathematicians, computer scientists and biologists. This workshop will enable interactions between scientists from a diverse set of relevant disciplines. In particular, it will be of interest to mathematicians working in the areas of multiscale modeling, differential geometry of surfaces, PDE analysis, numerical PDE, and fast algorithm, to name a few. It will significantly strengthen the leading role that the US researchers can play in mathematical molecular biosciences by pursuing cutting-edge research and collaboratively training a new generation of mathematicians in this emerging interdisciplinary field.

### Accepted Speakers

Nathan Baker
Computational and Statistical Analytics Division, Pacific Northwest National Laboratory
Charles Brooks
Biophysics Program, University of Michigan
Wei Cai
Department of Mathematics & Statistics, University of North Carolina, Charlotte
Chia-en (Angelina) Chang
Chemistry, University of California, Riverside
Zhan Chen
Mathematics, Michigan State University
Weihua Geng
Mathematics, University of Michigan
Sharon Hammes-Schiffer
Department of Chemistry, University of Illinois at Urbana-Champaign
Robert Krasny
Department of Mathematics, University of Michigan
Chun Liu
Mathematics, Penn State University
Tyler Luchko
Physics and Astronomy, California State University, Northridge
Dmitry Matyushov
Physics, Arizona State University
Julie Mitchell
Mathematics and Biochemistry, University of Wisconsin
Irina Moreira
Medicine, Center for Neuroscience and Cell Biology
Yoichiro Mori
School of Mathematics, University of Minnesota
Alexey Onufriev
B. Montgomery Pettitt
Sealy Center for Structural Biology, University of Texas Medical Branch
Pengyu Ren
Biomedical Engineering, The University of Texas at Austin
Ridgway Scott
Computer Science and Mathematics, University of Chicago
Xueyu Song
Chemistry, Iowa State University
Zhen-Gang Wang
Division of Chemistry and Chemical Engineering, California Institute of Technology
Stephen White
Dept. of Physiology & Biophysics, University of California, Irvine
Yingkai Zhang
Chemistry, New York University
John Zhang
College of Arts of Science, New York University Shanghai
Huan-Xiang Zhou
Monday, October 12, 2015
Time Session
07:45 AM

Shuttle to MBI

08:00 AM
08:30 AM

Breakfast

08:30 AM
08:45 AM

Welcome, overview, introduction: MG

08:45 AM
09:00 AM

Introduction by workshop organizers

09:00 AM
09:45 AM
John Zhang
09:45 AM
10:30 AM
Wei Cai
10:30 AM
11:00 AM

Break

11:00 AM
11:45 AM
Nathan Baker - Quantifying the influence of conformational uncertainty in biomolecular solvation

Biomolecules exhibit conformational fluctuations near equilibrium states, inducing uncertainty in various biological properties in a dynamic way. We have developed a general method to quantify the uncertainty of target properties induced by conformational fluctuations. Using a generalized polynomial chaos (gPC) expansion, we construct a surrogate model of the target property with respect to varying conformational states. We also propose a method to increase the sparsity of the gPC expansion by defining a set of conformational "active space" random variables. With the increased sparsity, we employ the compressive sensing method to accurately construct the surrogate model. We demonstrate the performance of the surrogate model by evaluating fluctuation-induced uncertainty in solvent-accessible surface area for the bovine trypsin inhibitor protein system and show that the new approach offers more accurate statistical information than standard Monte Carlo approaches. Further more, the constructed surrogate model also enables us to directly evaluate the target property under various conformational states, yielding a more accurate response surface than standard sparse grid collocation methods. In particular, the new method provides higher accuracy in high-dimensional systems, such as biomolecules, where sparse grid performance is limited by the accuracy of the computed quantity of interest. Our new framework is generalizable and can be used to investigate the uncertainty of a wide variety of target properties in biomolecular systems.

11:45 AM
12:30 PM
Huan-Xiang Zhou
12:30 PM
02:00 PM

Lunch Break

02:00 PM
02:45 PM
Julie Mitchell - What Data-Driven Models of Biophysics Tell Us About Protein Electrostatics

No abstract has been provided.

02:45 PM
03:00 PM

Break

03:00 PM
04:00 PM
Sharon Hammes-Schiffer
04:00 PM
06:00 PM

Reception and poster session in MBI Lounge

06:00 PM

Shuttle pick-up from MBI

Tuesday, October 13, 2015
Time Session
08:00 AM

Shuttle to MBI

08:15 AM
09:00 AM

Breakfast

09:00 AM
09:45 AM
09:45 AM
10:30 AM
Robert Krasny - A Treecode-Accelerated Boundary Integral Poisson-Boltzmann Solver for Electrostatics of Solvated Proteins

Electrostatic effects play an important role in determining protein structure and function. Here we present a treecode-accelerated boundary integral (TABI) solver for the electrostatic potential of a solvated protein described by the linear Poisson-Boltzmann equation. In this model the solvent is a continuum dielectric material with screening due to dissolved ions and the protein is a set of charged particles. The method employs a well-conditioned boundary integral formulation for the electrostatic potential and its normal derivative on the molecular surface. The surface is triangulated by MSMS and the integral equations are discretized by centroid collocation. The linear system is solved by GMRES and the matrix-vector product is carried out by a tree code which reduces the computational cost from $O(N^2)$ to $O(Nlog N)$, where $N$ is the number of faces in the triangulated molecular surface. We compare TABI results to those obtained using the finite-difference APBS code. The TABI solver exhibits good serial and parallel performance, with relatively simple implementation, efficient memory usage, and geometric adaptability. This is joint work with Weihua Geng (Southern Methodist University).

10:30 AM
11:00 AM

Break

11:00 AM
11:45 AM
Xueyu Song
11:45 AM
12:30 PM
Zhen-Gang Wang - Electrostatics beyond Poisson-Boltzmann: Effects of Self Energy

Ions are essential in physical chemistry, colloidal science, electrochemistry, biology and many other areas of science and engineering. While their role is commonly described in terms of screening and translational entropy, many phenomena, ranging from some classical experimental observations made many decades ago to some new systems of current interest, cannot be explained, even qualitatively, by these concepts. A key effect that is often ignored or inadequately treated in the main literature on electrolytes and polyelectrolytes is the self-energy of the ions. In this talk, I will discuss several self-energy effects in macromolecular and interfacial systems. First, we show that the preferential solvation energy of the ions provides a significant driving force for phase separation. This concept is used to develop a theory to explain the dramatic shift in the order-disorder transition temperature in PEO-PS diblock copolymers upon the addition of salt. Second, we show that the dielectric contrast between the polymer backbone and the solvent significantly affects the conformation and charge condensation in dilute polyelectrolyte solutions. Third, we show that the image force has qualitative effects on the double layer structure and forces, such as like charge attraction and charge inversion. Finally we present a simple model for understanding the specific ion effects in the interfacial activity for air/water and oil/water interfaces.

12:30 PM
02:00 PM

Lunch Break

02:00 PM
02:45 PM
Zhan Chen
02:45 PM
03:00 PM

Break

03:00 PM
03:45 PM
Weihua Geng - A treecode-accelerated boundary integral Poisson-Botlzmann solver: modeling, algorithm and application.

The Poisson-Boltzmann model is an extended model of the classical Gauss's law involving additionally multiple dielectrics (thus interface problem), solvent effects (thus continuum model) and dissolved electrolytes (thus nonlinearity). In this talk, I will introduce our recent progress in developing a numerical Poisson-Boltzmann solver with tree-code algorithms (for efficiency) and boundary integral formulation (for accuracy). Following that, I will briefly touch the attractive performance computing feature of this solver including parallelization and GPUs. I will conclude the talk with a report for the potential and established application of the Poisson-Botlzmann model/solver for computing quantities with biological significance such as electrostatic solvation energy, electrostatic forces, pKa values, etc.

03:45 PM
04:30 PM

Informal discussions/daily wrap-up

04:30 PM

Shuttle pick-up from MBI

Wednesday, October 14, 2015
Time Session
08:00 AM

Shuttle to MBI

08:15 AM
09:00 AM

Breakfast

09:00 AM
09:45 AM
B. Montgomery Pettitt - Comparing theory, heuristics and simulations in solution

Statistical thermodynamics requires having a theory of liquid structure which is accurate. Simulations are an important tool but are not a theory of the liquid state. In order to better understand general effects of the size and energy disparities between macromolecules and solvent molecules in solution, especially for macromolecular constructs self-assembled from smaller molecules, we compare theory and simulation to investigate multicomponent mixtures of fluids. We will compare a structured continuum solvation calculation on proteins with simulations and integral equations to evaluate the electrostatic free energy contribution to the solution thermodynamics. Using several peptide test cases, we compare the use of our theory with free energy simulations and traditional continuum estimates of the electrostatic solvation free energy.

09:45 AM
10:30 AM
Tyler Luchko - Partial Molar Volume Corrected Solvation Energies, Entropies and Free Energies from 3D-RISM

No abstract has been provided.

10:30 AM
11:00 AM

Break

11:00 AM
11:45 AM
Alexey Onufriev - Why Multivalent Ions Condense DNA but Not RNA?

No abstract has been submitted.

11:45 AM
12:30 PM
Stephen White - Electrostatics inside the SecY translocon protein that guides membrane protein assembly

SecY constitutes the core of the highly conserved SecYEG translocon complex that governs the translocation or integration of proteins across or into cytoplasmic membranes. Besides its role of guiding nascent membrane protein chains into the lipid bilayer, it also plays an important role in determining transmembrane topology via the so-called positive-inside rule. Site-directed mutations of translocons are known to modify the topology of nascent α-helical segments [1]. We performed molecular dynamics simulations of SecYE from Pyrococcus furiosus [2] embedded in a POPC bilayer. SecY in the P. furiosus structure is in a partially open ‘primed’ state. It conveniently remained open over the course of a 450 nsec simulation due to the presence of lipids wedged between helices TM2B and TM7 (the lateral gate), thus allowing close examination of the electrostatics within the translocon. Within the channel, water dipoles exhibit a preferred orientation, which affects the electrostatic (ES) potential. Time-averaged ES maps reveal a largely positive potential relative to the bulk aqueous phase within the channel except for a strong negative peak at the N-terminus of TM2b. This has implications for the entry of signal sequences into the translocon channel. Research supported by NIH grants RO1 GM74637 and PO1 GM86685.

12:30 PM
02:00 PM

Break

02:00 PM
02:45 PM
Yingkai Zhang
02:45 PM
03:00 PM

Break

03:00 PM
03:45 PM
Chia-en (Angelina) Chang - Modeling of enhanced catalysis in multienzyme nanostructures: effect of molecular scaffolds, spatial organization, and concentration

No abstract has been provided.

03:45 PM
04:30 PM

Informal discussions/daily wrap-up

04:30 PM

Shuttle pick-up from MBI

Thursday, October 15, 2015
Time Session
08:00 AM

Shuttle to MBI

08:15 AM
09:00 AM

Breakfast

09:00 AM
09:45 AM
Charles Brooks
09:45 AM
10:30 AM
Jana Shen
10:30 AM
11:00 AM

Break

11:00 AM
11:45 AM
Pengyu Ren
11:45 AM
12:30 PM
Irina Moreira - Structural/energetic analysis of protein-based interactions: highlighting the electrostatics contribution

No abstract has been provided.

12:30 PM
02:00 PM

Lunch Break

02:00 PM
02:45 PM
Dmitry Matyushov
02:45 PM
03:00 PM

Break

03:00 PM
03:45 PM
Qiang Cui
03:45 PM
04:30 PM

Informal discussions/daily wrap-up

04:30 PM

Shuttle pick-up from MBI

06:30 PM
07:00 PM

Cash bar

07:00 PM
07:00 PM

Banquet in the Fusion Room @ Crowne Plaza Hotel

Friday, October 16, 2015
Time Session
08:00 AM

Shuttle to MBI

08:15 AM
09:00 AM

Breakfast

09:00 AM
09:45 AM
Ridgway Scott
09:45 AM
10:30 AM
Chun Liu - Transport of Charged Particles, an Energetic Variational Approach

No abstract has been provided.

10:30 AM
11:00 AM

Break

11:00 AM
11:45 AM
Yoichiro Mori
11:45 AM
12:00 PM

Informal discussions/workshop wrap-up

12:00 PM

Shuttle pick-up from MBI (One to airport and one back to hotel)

Name Email Affiliation
Alexov, Emil ealexov@clemson.edu Computational Biophysics and Bioinformatics, Clemson University
Baker, Nathan nathan.baker@pnl.gov Computational and Statistical Analytics Division, Pacific Northwest National Laboratory
Barba, Lorena labarba@bu.edu
Brooks, Charles brookscl@umich.edu Biophysics Program, University of Michigan
Cai, Wei wcai@uncc.edu Department of Mathematics & Statistics, University of North Carolina, Charlotte
Chang, Chia-en chiaenc@ucr.edu Chemistry, University of California, Riverside
Chen, Zhan zchen@georgiasouthern.edu Mathematics, Michigan State University
Chen, Jiahui jiahuic@smu.edu mathematics, Southern Methodist University
Chen, Long chenlong@math.uci.edu Department of Mathematics, University of California at Irvine
Cisneros, Gerardo Andres andres@chem.wayne.edu Chemistry, Wayne State University
Eisenberg, Robert beisenbe@rush.edu Molecular Biophysics and Physiology, Rush University Medical Center
Fenley, Marcia mfenley@fsu.edu IMB, FSU
Geng, Weihua wgeng@mail.smu.edu Mathematics, University of Michigan
Hammes-Schiffer, Sharon shs3@illinois.edu Department of Chemistry, University of Illinois at Urbana-Champaign
Hazra, Tania thazra@crimson.ua.edu Mathematics, University of Alabama
Hohn, Maryann maryann.hohn@uconn.edu Mathematics, University of Connecticut
Im, Wonpil wonpil@ku.edu Molecular Biosciences and Center for Computational Biology, The University of Kansas
Jacobs, Donald djacobs1@uncc.edu
Koehl, Patrice koehl@cs.ucdavis.edu
Krasny, Robert krasny@umich.edu Department of Mathematics, University of Michigan
Li, Bo bli@math.ucsd.edu Department of Mathematics, University of California, San Diego
Li, Lin lli5@clemson.edu Department of Physics, Clemson University
Liu, Chun liu@math.psu.edu Mathematics, Penn State University
Luchko, Tyler tyler.luchko@csun.edu Physics and Astronomy, California State University, Northridge
Luo, Ray ray.luo@uci.edu Molecular Biology and Biochemistry, University of California,
Matyushov, Dmitry dmitrym@asu.edu Physics, Arizona State University
Mitchell, Julie jcmitchell@wisc.edu Mathematics and Biochemistry, University of Wisconsin
Moreira, Irina irina.moreira@fc.up.pt Medicine, Center for Neuroscience and Cell Biology
Mori, Yoichiro ymori@math.umn.edu School of Mathematics, University of Minnesota
Onufriev, Alexey alexey@cs.vt.edu
Pettitt, B. Montgomery pettitt@uh.edu Sealy Center for Structural Biology, University of Texas Medical Branch
Petukh, Marharyta mpetukh@clemson.edu Physics and Astronomy, Clemson University
Ren, Pengyu pren@mail.utexas.edu Biomedical Engineering, The University of Texas at Austin
Scott, Ridgway ridg@uchicago.edu Computer Science and Mathematics, University of Chicago
Song, Xueyu xsong@iastate.edu Chemistry, Iowa State University
Sun, Weitao sunwt@mail.tsinghua.edu.cn Zhou Pei-Yuan Center for Applied Mathematics, Tsinghua University
Sushko, Maria Maria.Sushko@pnnl.gov
Wang, Zhen-Gang zgw@cheme.caltech.edu Division of Chemistry and Chemical Engineering, California Institute of Technology
Wei, Guowei wei@math.msu.edu Department of Mathematics, Michigan State University
White, Stephen stephen.white@uci.edu Dept. of Physiology & Biophysics, University of California, Irvine
Wilson, Leighton lwwilson1@crimson.ua.edu
Wong, Chung wongch@msx.umsl.edu Chemistry and Biochemistry, University of Missouri-St. Louis
Yan, Jue jyan@iastate.edu Mathematics, Iowa State University
Zhang, Yingkai yingkai.zhang@nyu.edu Chemistry, New York University
Zhang, John john.zhang@nyu.edu College of Arts of Science, New York University Shanghai
Zhou, Huan-Xiang hzhou4@fsu.edu
Modeling Electrodiffusion and Osmosis in Physiological Systems

Electrolyte and cell volume regulation is essential in physiological systems. After a brief introduction to cell volume control and electrophysiology, I will discuss the classical pump-leak model of electrolyte and cell volume control. I will then generalize this to a PDE model that allows for the modeling of tissue-level electrodiffusive, convective and osmotic phenomena. This model will then be applied to the study of cortical spreading depression, a wave of ionic homeostasis breakdown, that is the basis for migraine aura and other brain pathologies.

Quantifying the influence of conformational uncertainty in biomolecular solvation

Biomolecules exhibit conformational fluctuations near equilibrium states, inducing uncertainty in various biological properties in a dynamic way. We have developed a general method to quantify the uncertainty of target properties induced by conformational fluctuations. Using a generalized polynomial chaos (gPC) expansion, we construct a surrogate model of the target property with respect to varying conformational states. We also propose a method to increase the sparsity of the gPC expansion by defining a set of conformational "active space" random variables. With the increased sparsity, we employ the compressive sensing method to accurately construct the surrogate model. We demonstrate the performance of the surrogate model by evaluating fluctuation-induced uncertainty in solvent-accessible surface area for the bovine trypsin inhibitor protein system and show that the new approach offers more accurate statistical information than standard Monte Carlo approaches. Further more, the constructed surrogate model also enables us to directly evaluate the target property under various conformational states, yielding a more accurate response surface than standard sparse grid collocation methods. In particular, the new method provides higher accuracy in high-dimensional systems, such as biomolecules, where sparse grid performance is limited by the accuracy of the computed quantity of interest. Our new framework is generalizable and can be used to investigate the uncertainty of a wide variety of target properties in biomolecular systems.

Modeling of enhanced catalysis in multienzyme nanostructures: effect of molecular scaffolds, spatial organization, and concentration

No abstract has been provided.

A treecode-accelerated boundary integral Poisson-Botlzmann solver: modeling, algorithm and application.

The Poisson-Boltzmann model is an extended model of the classical Gauss's law involving additionally multiple dielectrics (thus interface problem), solvent effects (thus continuum model) and dissolved electrolytes (thus nonlinearity). In this talk, I will introduce our recent progress in developing a numerical Poisson-Boltzmann solver with tree-code algorithms (for efficiency) and boundary integral formulation (for accuracy). Following that, I will briefly touch the attractive performance computing feature of this solver including parallelization and GPUs. I will conclude the talk with a report for the potential and established application of the Poisson-Botlzmann model/solver for computing quantities with biological significance such as electrostatic solvation energy, electrostatic forces, pKa values, etc.

A Treecode-Accelerated Boundary Integral Poisson-Boltzmann Solver for Electrostatics of Solvated Proteins

Electrostatic effects play an important role in determining protein structure and function. Here we present a treecode-accelerated boundary integral (TABI) solver for the electrostatic potential of a solvated protein described by the linear Poisson-Boltzmann equation. In this model the solvent is a continuum dielectric material with screening due to dissolved ions and the protein is a set of charged particles. The method employs a well-conditioned boundary integral formulation for the electrostatic potential and its normal derivative on the molecular surface. The surface is triangulated by MSMS and the integral equations are discretized by centroid collocation. The linear system is solved by GMRES and the matrix-vector product is carried out by a tree code which reduces the computational cost from $O(N^2)$ to $O(Nlog N)$, where $N$ is the number of faces in the triangulated molecular surface. We compare TABI results to those obtained using the finite-difference APBS code. The TABI solver exhibits good serial and parallel performance, with relatively simple implementation, efficient memory usage, and geometric adaptability. This is joint work with Weihua Geng (Southern Methodist University).

Transport of Charged Particles, an Energetic Variational Approach

No abstract has been provided.

Partial Molar Volume Corrected Solvation Energies, Entropies and Free Energies from 3D-RISM

No abstract has been provided.

What Data-Driven Models of Biophysics Tell Us About Protein Electrostatics

No abstract has been provided.

Structural/energetic analysis of protein-based interactions: highlighting the electrostatics contribution

No abstract has been provided.

Why Multivalent Ions Condense DNA but Not RNA?

No abstract has been submitted.

Comparing theory, heuristics and simulations in solution

Statistical thermodynamics requires having a theory of liquid structure which is accurate. Simulations are an important tool but are not a theory of the liquid state. In order to better understand general effects of the size and energy disparities between macromolecules and solvent molecules in solution, especially for macromolecular constructs self-assembled from smaller molecules, we compare theory and simulation to investigate multicomponent mixtures of fluids. We will compare a structured continuum solvation calculation on proteins with simulations and integral equations to evaluate the electrostatic free energy contribution to the solution thermodynamics. Using several peptide test cases, we compare the use of our theory with free energy simulations and traditional continuum estimates of the electrostatic solvation free energy.

Electrostatics beyond Poisson-Boltzmann: Effects of Self Energy

Ions are essential in physical chemistry, colloidal science, electrochemistry, biology and many other areas of science and engineering. While their role is commonly described in terms of screening and translational entropy, many phenomena, ranging from some classical experimental observations made many decades ago to some new systems of current interest, cannot be explained, even qualitatively, by these concepts. A key effect that is often ignored or inadequately treated in the main literature on electrolytes and polyelectrolytes is the self-energy of the ions. In this talk, I will discuss several self-energy effects in macromolecular and interfacial systems. First, we show that the preferential solvation energy of the ions provides a significant driving force for phase separation. This concept is used to develop a theory to explain the dramatic shift in the order-disorder transition temperature in PEO-PS diblock copolymers upon the addition of salt. Second, we show that the dielectric contrast between the polymer backbone and the solvent significantly affects the conformation and charge condensation in dilute polyelectrolyte solutions. Third, we show that the image force has qualitative effects on the double layer structure and forces, such as like charge attraction and charge inversion. Finally we present a simple model for understanding the specific ion effects in the interfacial activity for air/water and oil/water interfaces.

Electrostatics inside the SecY translocon protein that guides membrane protein assembly

SecY constitutes the core of the highly conserved SecYEG translocon complex that governs the translocation or integration of proteins across or into cytoplasmic membranes. Besides its role of guiding nascent membrane protein chains into the lipid bilayer, it also plays an important role in determining transmembrane topology via the so-called positive-inside rule. Site-directed mutations of translocons are known to modify the topology of nascent α-helical segments [1]. We performed molecular dynamics simulations of SecYE from Pyrococcus furiosus [2] embedded in a POPC bilayer. SecY in the P. furiosus structure is in a partially open ‘primed’ state. It conveniently remained open over the course of a 450 nsec simulation due to the presence of lipids wedged between helices TM2B and TM7 (the lateral gate), thus allowing close examination of the electrostatics within the translocon. Within the channel, water dipoles exhibit a preferred orientation, which affects the electrostatic (ES) potential. Time-averaged ES maps reveal a largely positive potential relative to the bulk aqueous phase within the channel except for a strong negative peak at the N-terminus of TM2b. This has implications for the entry of signal sequences into the translocon channel. Research supported by NIH grants RO1 GM74637 and PO1 GM86685.

### Participate

Request Live Stream Apply for Event

### Print

Full Schedule Participant List