Skip to Main Content
From Computational Biophysics to Systems Biology (CBSB2015)
May 17-19, 2015  Oklahoma City, Oklahoma
OUHSC link

OU link

OU link

UCO link

OMRF link

Keynote and Invited Speakers:

Keynote Speakers:

Invited Speakers:

  • Harnessing confusing combinatorial information within MD simulations for modeling proteins.
    Ken A. Dill
    Stony Brook University

    A standard approach in integrative structural biology is to combine atomistic MD simulations, which accounts for energetics, with external experimental or restraint information, which gives guidance from structural information. However, this approach doesn't work if the information is not correct, accurate and specific. We are developing a statmech approach, called MELD, for harnessing troublesome information within MD simulations. For example, by telling an MD simulation to find structures that have both low free energies while also having good hydrophobic cores and good secondary structures, we can fold small proteins close to their native structures and aid in structure refinement.
    Back to the top of the page

  • Computer simulations of protein function: Challenges and solutions`
    Ron Elber
    Department of Chemistry and Biochemistry, University of Texas, Austin

    Biological processes are controlled by kinetics. The next biochemical reaction that will happen in a living system is determined by the speed of the reaction and not by the relative stability of the products. It is therefore crucial to understand kinetics and time scales of biological processes in order to model living systems. In my talk I will describe a simulation technology, Milestoning, developed in my group that makes it possible to investigate biochemical processes at the atomic level and extended temporal scales. As examples, I will discuss functional conformational transitions in the proteins myosin and HIV reverse transcriptase. I will also examine mechanical stability of helices and coiled coil constructs.
    Back to the top of the page

  • K-Ras Ensembles, Biology and Signaling: Questions and Observations
    Ruth Nussinov
    Cancer and Inflammation Program National Cancer Institute and Medical School, Tel Aviv University

    Ras proteins are small GTPases that act as signal transducers between cell surface receptors and several intracellular signaling cascades. KRas4B is among the frequently mutated oncogenes in human tumors. Ras proteins consist of highly homologous catalytic domains, and flexible C-terminal hypervariable regions (HVRs) that differ significantly across Ras isoforms. We have been focusing on key mechanistic questions in Ras biology from the structural standpoint. These include whether Ras forms dimers, and if so what is their structural landscape; how do Ras dimers activate Raf, a key Ras effector in a major signaling pathway; how calmodulin temporally inhibit Raf signaling, and the potential role of the hypervariable region and its membrane anchoring regulation. We believe that structural biology, computations and experiment, are uniquely able to tackle these fascinating questions
    Back to the top of the page

  • Computational modeling of cytoplasm of a bacterial cell: diffusion and hydrodynamics
    Pradipta Bandyopadhyay
    School of Computational and Integrative Sciences, Jawaharlal Nehru University

    It is known that the kinetics and thermodynamics of processes occurring in living systems can be significantly affected by the crowded nature of the biological cell. Indeed several in-vivo experiments have quantified the effect of molecular crowding. Computational modeling of a cell (or a part of it) is challenging because of the heterogeneous and complex environment inside a cell. In the current work, we have modeled the cytoplasm of an E. coli cell with a coarse grained description. Our model differs from the previous works is that shape of proteins is taken approximately and hydrodynamics interaction is modeled in a mean field manner. We have performed extensive Brownian dynamics simulation of hundreds of proteins of the model cytoplasm. Our calculated diffusion coefficient values for several proteins match closely with experimentally known values. In the talk the details of implementation of our Brownian dynamics simulation and the analysis will be described. We have also developed an analytical model to describe subdiffusion in crowded environment, which will be described as well.
    (1) A New Coarse-Grained Model for E. coli Cytoplasm: Accurate Calculation of the Diffusion Coefficient of Proteins and Observation of Anomalous Diffusion.
    Sabeeha Hasnain, Christopher L. McClendon, Monica T. Hsu, Matthew P. Jacobson, Pradipta Bandyopadhyay, PLOS ONE, 2014, DOI: 10.1371/journal.pone.0106466
    (2) An analytical correlated random walk model and its application to understand subdiffusion in crowded environment, Sabeeha Hasnain, Pradipta Bandyopadhyay (In preparation).
    Back to the top of the page

  • Accurate atomistic simulations of intrinsically disordered proteins
    Robert B. Best
    National Institutes of Health

    Intrinsically disordered proteins (IDPs), which lack structure in isolation, are increasingly recognized to play important roles in biology. While atomistic models with explicit solvent are the most accurate applicable biomolecular simulation method, their application to intrinsically disordered proteins has been challenging due to obvious shortcomings in the energy functions. I will show how relatively modest changes to the force fields can bring about substantial improvements in treating secondary structure propensity and overall dimensions of disordered proteins, and will present some applications to studying structure and dynamics in IDPs and unfolded globular proteins.
    Back to the top of the page

  • Protein non-folding as a regulatory phenomenon
    Carlos J. Camacho
    Department of Computational and Systems Biology, University of Pittsburgh

    A large number of proteins are sufficiently unstable that their full 3D structure cannot be resolved. The origins of this intrinsic disorder are not well understood, but its ubiquitous presence undercuts the principle that a protein’s structure determines its function. My seminar will present the theory of disorder in proteins, making quantitative predictions regarding its role in protein structure and function. Predictions are validated based on genome-wide surveys of both the amount of disorder for different functional categories and binding affinities for both prokaryotic and eukaryotic genomes. Without assuming any a priori structure–function relationship, we demonstrate that enzymes and low-affinity binding proteins prefer ordered structures, whereas only high-affinity binding proteins (found mostly in eukaryotes) can tolerate disorder. Relevant to regulatory networks, I will show how the increasing amount of intrinsic disorder in eukaryotes is essential to maximize the specificity of promiscuous regulatory interactions. Implications of intrinsic disorder in the evolution of regulatory networks and protein folding will also be discussed.
    Back to the top of the page

  • Modeling protein diffusion in the extracellular matrix
    Christopher Fennel
    Oklahoma State University

    Intercellular signaling is a critical component of organized tissue function in biological systems. For example, in the case of tissue damage or immune response to foreign bodies, there is a localized upregulation of signaling protein production forming a protein gradient which white blood cells follow to accumulate at the target site. Errors in this signaling system can lead to excessive tissue inflammation, such as that seen in sudden allergic reactions or longer-time health concerns like atherosclerosis. We explore here the microscopic interface of a portion of this signaling system through all-atom molecular dynamics simulations of extracellular diffusion of monocyte chemotactic protein 1 (MCP1). We perform a systematic investigation of MCP1 diffusion and adhesion in aqueous environments with varied collagen concentration, and we see quantitative agreement with diffusion in experimental tissue models. Through detailed analysis of protein conformation distributions, we highlight the primary microscopic interactions governing flow of MCP1 and its potential buildup in extracellular environments.
    Back to the top of the page

  • Membrane binding, conformational plasticity and druggability of Ras proteins: A comprehensive computational analysis
    Alemayehu Gorfet
    University of Texas Medical School at Houston

    Despite decades of studies and the well-established roles of human Ras proteins in health and disease, much remains to be learned about how they work at the molecular level. Major challenges associated with the highly dynamic nature of these proteins and the resolution limits of experimental techniques have hampered our ability to address a number of key issues. These include, at the fundamental level, the sources of signaling specificity and non-overlapping membrane organization of Ras homologous, as well as the structural determinants for the distinct role of specific point mutations in different cancer types. At a more practical level, we lacked the means by which to challenge the “invincibility” of Ras as an anti-cancer drug target. Considerable progress has been made over the last several years toward addressing each of these issues. Molecular simulations and other computational structural biology techniques have made significant contributions to this progress. Our laboratory studies Ras proteins using multi-scale molecular dynamics simulations in solution and membrane environments coupled with a variety of novel concepts, analysis tools and collaborative experiments. The current presentation will focus on the clinically most relevant isoform of Ras proteins: K-Ras. We will discuss our recent efforts toward elucidating the mechanisms of membrane binding and oligomeration of K-Ras as well as the impact of selected point mutations on its dynamics. We will highlight how some of the lessons from Ras can be generalized to other lipid-modified signaling proteins.
    Back to the top of the page

  • Detecting local residue environment similarity for recognizing near-native structure models
    Daisuke Kihara
    Purdue University

    One of the key steps in protein structure prediction/modeling is to recognize near-native models from a pool of alternative models. We developed a new representation of local amino acid environments in protein structures called the Side-chain Depth Environment (SDE) (Kim & Kihara, Proteins 2014). An SDE defines a local structural environment of a residue considering the coordinates and the depth of amino acids that locate in the vicinity of the side-chain centroid of the residue, and thus captures multi-residue interactions. When benchmarked on commonly used computational model datasets, the residue environment score compared favorably with the other existing scoring functions in selecting native and near-native models. \r\nSDE was also used in the recent CASP11 protein structure prediction assessment and led our group to the best performance among all the participants in the free modeling category.
    Back to the top of the page

  • Modeling of pH - driven protein unfolding by a combination of Molecular Dynamics techniques
    Maria Kurnikova
    Carnegie Mellon University

    Diphtheria toxin is a multi-domain protein that invades cells using their endocytosis mechanism, in which an endosome, a lipid bilayer vesicle encapsulates a foreign object. The pH inside endosome is then lowered. A translocation domain (T-domain) of the diphtheria toxin undergoes a conformational rearrangement at low pH, followed by membrane insertion, and subsequent translocation of its N-terminus with the attached catalytic domain into the cell. In solution at neutral pH a stand-alone T-domain peptide assumes globular form; acidification of solution triggers its conformational rearrangement and subsequent lipid membrane binding and insertion. The details of this conformational restructuring of the protein are not known. Recently we characterized a pH-dependent partial unfolding of T-domain by using microsecond long MD simulations and Thermodynamic Integration techniques (1). However, simulating statistical ensembles of unfolded conformation of large proteins is still a prohibitively expensive task. We will describe a novel Direct Intra Solute Electrostatic Interactions accelerated Molecular Dynamics (DISEI-aMD) approach to facilitate generating of a partially unfolded protein ensembles at a reasonable cost (2). This method aims to reduce energy barriers within rapidly changing electrostatic interactions between solute atoms at short range distances. It also results in improved reconstruction quality of the original statistical ensemble of the system. We focus on the study of conformational changes of a low pH T-domain model in explicit solvent using the DISEI-aMD. Based on the simulations of the low pH T-domain model we show that the proposed sampling method accelerates conformational rearrangement significantly faster than multiple standard aMD simulations and microsecond long conventional MD simulations. An approach to estimate an unfolded state apparent pKa will also be presented using a clustering technique and a Free Energy Perturbation method.\
    1)pH-Triggered Conformational Switching of the Diphtheria Toxin T-Domain: The Roles of N-Terminal Histidines, I.V. Kurnikov, A. Kyrychenko, J.C. Flores-Canales, M.V. Rodnin, N. Simakov, M. Vargas-Uribe, Y.O. Posokhov, M. Kurnikova, and A.S. Ladokhin J. Mol. Biol. 425, 2752 (2013)
    2)Targeting Electrostatic Interactions in Accelerated Molecular Dynamics with Application to Protein Partial Unfolding, J.C. Flores-Canales and M. Kurnikova JCTC (2015)
    Back to the top of the page

  • First Principle Solvation Free Energy of Monovalent Ions from Adaptive Force Matching
    Feng Wang
    University of Arkansas

    The interplay of protein hydration and solvation of Ions plays an important role in the stability of proteins. The intriguing correlation is manifested as the famous Hofmeister series. We parameterized pair-wise additive potentials for ion-water interactions using the adaptive force matching protocol developed in the group. By only fitting to electronic structure forces calculated with the Møller-Plesset perturbation theory (MP2) at the second order, the ion-water potential developed correctly predict the solvation free energy of various salts with an error of less than 5% when compared to experimental measurements. The solvation structure of ions is in good agreement with prior simulations based on density function theory (DFT) and QM/MM MP2. The simulations reveal new insight regarding the solvation structure of ions.
    Back to the top of the page

  • Simulations on metal ion coupled protein folding and allosteric motion
    Wei Wang
    National Laboratory of Solid State Microstructure and Department of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University,

    Binding of metal ions can reshape the energy landscapes of proteins, thereby modifying the folding and allosteric motions. For example, such binding may make the intrinsically disordered proteins have funneled energy landscapes, consequently, ensures their spontaneous folding. In addition, the binding may activate certain biological processes by inducing related conformational changes of regulation proteins. However, how the local interactions involving the metal ion binding can induce the global conformational motions of proteins remains elusive. Investigating such question requires multiple models with different details, including quantum mechanics, atomistic models, and coarse grained models. In our recent work, we have been developing such multiscale methods which can reasonably model the metal ion binding induced charge transfer, protonation/deprotonation, and large conformational motions of proteins. With such multiscale model, we elucidated the zinc-binding induced folding mechanism of classical zinc finger and the calcium-binding induced dynamic symmetry breaking in the allosteric motions of calmodulin. In addition, we studied the coupling of folding, calcium binding and allosteric motions of calmodulin domains. In this talk, I will introduce the above progresses on the metal ion coupled protein folding and allosteric motions.
    [1] Wenfei Li, Jian Zhang, Jun Wang, and Wei Wang, Metal-coupled folding of Cys2His2 zinc-finger, J. Am. Chem. Soc. 130, 892(2008).
    [2] Wenfei Li, Wei Wang, and Shoji Takada, Energy landscape views for interplay among folding, binding, and allostery of calmodulin domains, PNAS, 111, 10550 (2014).
    [3] Cheng Tan, Wenfei Li, Wei Wang, and D. Thirumalai, Water mediated Calcium coordination and asymmetric allosteric coupling in paired Calmodulin EF-hands, To be submitted.
    [4] Wenfei Li, Jun Wang, Jian Zhang, and Wei Wang, Molecular simulations of metal-coupled protein folding, Curr. Opin. in Struct. Biol.,30,25(2015).
    Back to the top of the page

  • New Fold of Estrogen Receptor: Examining Cross-talk between Domains
    Sichun Yang
    Case Western Reserve University

    Estrogen receptor alpha (ER) regulates allosteric signal transduction between hormone and transcriptional DNA binding. Despite the ER being a key target of breast cancer therapeutics, however, little is known about signaling pathways and how its hormone/DNA-binding domains communicate is still elusive. Here, we discover that a novel fold is adopted by ER, completely different from any available fold existed for hormone receptors, and identify that a set of amino acids (mostly hydrophobic) are involved at the interfaces responsible for domain cross-talk. We further derive structure ensembles of this multidomain ER fold by using integrative approaches of modeling on biophysical SAXS and synchrotron radiation measurements, and by utilizing large-scale biomolecular simulations that fully examine the energy landscape of protein-protein interactions occurred in the ER. Discovery of the hidden cross-talk between domains establishes a new pathway of ER allostery for elucidating the notorious resistance of antiestrogen therapy.
    Back to the top of the page