Chain molecule deformation in a uniform flow - a computer experiment

MOOKYUNG CHEON,IKSOO CHANG(장익수),JOEL KOPLIK,JAYANTH R. BANAVAR 대한기계학회 2002 대한기계학회 춘추학술대회 Vol.2002 No.4

We investigate the stretching of a polymer in a uniform flow using molecular dynamics (MD) simulations. Our MD simulations represent an ab-initio experiment with no explicit assumption for the dynamics of a single chain except for using the generic Lennard-Jones and the FENE potentials. In spite of the modest length of our simulated chains, the qualitative features of experiments on DNA are reproduced and the predictions of a wormlike chain theory are found to hold, with the polymer molecule being free draining at large extensions.

Uncovering multiloci-ordering by algebraic property of Laplacian matrix and its Fiedler vector

Cheon, Mookyung,Kim, Choongrak,Chang, Iksoo Oxford University Press 2016 Bioinformatics Vol.32 No.6

<P>Motivation: The loci-ordering, based on two-point recombination fractions for a pair of loci, is the most important step in constructing a reliable and fine genetic map. Results: Using the concept from complex graph theory, here we propose a Laplacian ordering approach which uncovers the loci-ordering of multiloci simultaneously. The algebraic property for a Fiedler vector of a Laplacian matrix, constructed from the recombination fraction of the loci-ordering for 26 loci of barley chromosome IV, 846 loci of Arabidopsis thaliana and 1903 loci of Malus domestica, together with the variable threshold uncovers their loci-orders. It offers an alternative yet robust approach for ordering multiloci.</P>

Extending the PRIME model for protein aggregation to all 20 amino acids

Cheon, Mookyung,Chang, Iksoo,Hall, Carol K. Wiley Subscription Services, Inc., A Wiley Company 2010 Proteins Vol.78 No.14

<P><B>Abstract</B></P><P>We extend PRIME, an intermediate‐resolution protein model previously used in simulations of the aggregation of polyalanine and polyglutamine, to the description of the geometry and energetics of peptides containing all 20 amino acid residues. The 20 amino acid side chains are classified into 14 groups according to their hydrophobicity, polarity, size, charge, and potential for side chain hydrogen bonding. The parameters for extended PRIME, called PRIME 20, include hydrogen‐bonding energies, side chain interaction range and energy, and excluded volume. The parameters are obtained by applying a perceptron‐learning algorithm and a modified stochastic learning algorithm that optimizes the energy gap between 711 known native states from the PDB and decoy structures generated by gapless threading. The number of independent pair interaction parameters is chosen to be small enough to be physically meaningful yet large enough to give reasonably accurate results in discriminating decoys from native structures. The most physically meaningful results are obtained with 19 energy parameters. Proteins 2010. © 2010 Wiley‐Liss, Inc.</P>

Structural Conversion of Aβ _17–42 Peptides from Disordered Oligomers to U-Shape Protofilaments via Multiple Kinetic Pathways

Cheon, Mookyung,Hall, Carol K.,Chang, Iksoo Public Library of Science 2015 PLoS computational biology Vol.11 No.5

<▼1><P>Discovering the mechanisms by which proteins aggregate into fibrils is an essential first step in understanding the molecular level processes underlying neurodegenerative diseases such as Alzheimer’s and Parkinson's. The goal of this work is to provide insights into the structural changes that characterize the kinetic pathways by which amyloid-β peptides convert from monomers to oligomers to fibrils. By applying discontinuous molecular dynamics simulations to PRIME20, a force field designed to capture the chemical and physical aspects of protein aggregation, we have been able to trace out the entire aggregation process for a system containing 8 Aβ17–42 peptides. We uncovered two fibrillization mechanisms that govern the structural conversion of Aβ17–42 peptides from disordered oligomers into protofilaments. The first mechanism is monomeric conversion templated by a U-shape oligomeric nucleus into U-shape protofilament. The second mechanism involves a long-lived and on-pathway metastable oligomer with S-shape chains, having a C-terminal turn, en route to the final U-shape protofilament. Oligomers with this C-terminal turn have been regarded in recent experiments as a major contributing element to cell toxicity in Alzheimer’s disease. The internal structures of the U-shape protofilaments from our PRIME20/DMD simulation agree well with those from solid state NMR experiments. The approach presented here offers a simple molecular-level framework to describe protein aggregation in general and to visualize the kinetic evolution of a putative toxic element in Alzheimer’s disease in particular.</P></▼1><▼2><P><B>Author Summary</B></P><P>Understanding the mechanisms of protein folding and aggregation is of fundamental importance in elucidating the biological function of proteins and their complex. Many advances have been made in our ability to describe protein folding based both on ideas from biophysics and improvements in supercomputing power, yet realistic simulations of the entire kinetic process of protein aggregation including fibril formation still remain challenging tasks in biophysics and computational biology. This work describes a breakthrough in our ability to simulate the aggregation of proteins on a molecular level and the emergence of the toxic species responsible for the cause of neuro-degenerative diseases such as Alzheimer’s disease. Based on this work, one can now trace the entire aggregation process starting from disordered monomers to meta-stable oligomers to protofilament and then amyloid fibril. This is a significant advance over the current state of the art in both biophysics and computational biology in uncovering the fundamental mechanisms behind the amyloid fibril formation for aggregation-prone proteins.</P></▼2>

Cooperative folding kinetics of BBL protein and peripheral subunit-binding domain homologues.

Yu, Wookyung,Chung, Kwanghoon,Cheon, Mookyung,Heo, Muyoung,Han, Kyou-Hoon,Ham, Sihyun,Chang, Iksoo National Academy of Sciences 2008 PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF Vol.105 No.7

<P>Recent experiments claiming that Naf-BBL protein follows a global downhill folding raised an important controversy as to the folding mechanism of fast-folding proteins. Under the global downhill folding scenario, not only do proteins undergo a gradual folding, but folding events along the continuous folding pathway also could be mapped out from the equilibrium denaturation experiment. Based on the exact calculation using a free energy landscape, relaxation eigenmodes from a master equation, and Monte Carlo simulation of an extended Muñoz-Eaton model that incorporates multiscale-heterogeneous pairwise interactions between amino acids, here we show that the very nature of a two-state cooperative transition such as a bimodal distribution from an exact free energy landscape and biphasic relaxation kinetics manifest in the thermodynamics and folding-unfolding kinetics of BBL and peripheral subunit-binding domain homologues. Our results provide an unequivocal resolution to the fundamental controversy related to the global downhill folding scheme, whose applicability to other proteins should be critically reexamined.</P>

Perceptron learning of pairwise contact energies for proteins incorporating the amino acid environment.

Heo, Muyoung,Kim, Suhkmann,Moon, Eun-Joung,Cheon, Mookyung,Chung, Kwanghoon,Chang, Iksoo Published by the American Physical Society through 2005 Physical review. E, Statistical, nonlinear, and so Vol.72 No.1

<P>Although a coarse-grained description of proteins is a simple and convenient way to attack the protein folding problem, the construction of a global pairwise energy function which can simultaneously recognize the native folds of many proteins has resulted in partial success. We have sought the possibility of a systematic improvement of this pairwise-contact energy function as we extended the parameter space of amino acids, incorporating local environments of amino acids, beyond a 20 x 20 matrix. We have studied the pairwise contact energy functions of 20 x 20, 60 x 60, and 180 x 180 matrices depending on the extent of parameter space, and compared their effect on the learnability of energy parameters in the context of a gapless threading, bearing in mind that a 20 x 20 pairwise contact matrix has been shown to be too simple to recognize the native folds of many proteins. In this paper, we show that the construction of a global pairwise energy function was achieved using 1006 training proteins of a homology of less than 30%, which include all representatives of different protein classes. After parametrizing the local environments of the amino acids into nine categories depending on three secondary structures and three kinds of hydrophobicity (desolvation), the 16290 pairwise contact energies (scores) of the amino acids could be determined by perceptron learning and protein threading. These could simultaneously recognize all the native folds of the 1006 training proteins. When these energy parameters were tested on the 382 test proteins of a homology of less than 90%, 370 (96.9%) proteins could recognize their native folds. We set up a simple thermodynamic framework in the conformational space of decoys to calculate the unfolded fraction and the specific heat of real proteins. The different thermodynamic stabilities of E.coli ribonuclease H (RNase H) and its mutants were well described in our calculation, agreeing with the experiment.</P>