Chodera, John D.

Pande, Vijay S.

Parton, Daniel L.

Shukla, Diwakar

Zhao, Yutong

Elsevier - Publisher Connector 

Toward a Global View of the Conformational Landscape of the Human Kinome 

Wednesday, February 19, 2014 655afundamental understanding of protein-protein interactions, but also to the
development of efficient computational methods to rationally design protein in-
terfaces with tunable specificity and affinity, and numerous applications in
biomedicine.
Funded by: NSF DMR-1006537 and PHY-1019147, the Raymond and Beverly
Sack- ler Institute for Biological, Physical and Engineering Sciences, and Ho-
ward Hughes Medical Institute (HHMI) International Research Fellowship.
3310-Pos Board B38
From Aminomutases to Ammonia Lyases: A Protein Engineering Study
Marcelo F. Masman, Matthew M. Heberling, Dick B. Janssen.
Biotransformation and Biocatalysis, University of Groningen, Groningen,
Netherlands.
Ammonia lyases and aminomutases are emerging as important enzymatic sys-
tems, not only in green synthetic routes to chiral amines, but also as potential
target for enzyme therapeutic for treating diseases such as phenylketonuria and
cancer (1). On the other hand, b-amino acids harbor many applications in their
free form and as building blocks of bioactive compounds (2, 3). Although, these
eco-friendly biocatalytic routes have been extensively explored, they are far
from optimal. The aim of this work is to engineer a phenylalanine aminomutase
(PAM) to acquire lyase properties for the efficient production of enantio-pure
b-Phe (key component of taxol (2)). Thus, this study was guided by molecular
modeling techniques to decipher which structural components functionally
separate PAM and the phenylalanine ammonia lyase (PAL). Despite the great
structural similarity of the active site of these enzymes, PAL is a-selective with
much faster deamination rates relative to PAM, which exhibits 50% a- and b-
regioselectivity (1, 4). Recent studies have implicated loop regions as key struc-
tural determinants between PAM and PAL (5). Here, we report novel insight
into the implications of the active-site loop residues of PAM, which influence
mutase/lyase activity. Several mutants were proposed, cloned, expressed and
characterized. Overall, this enzyme engineering work represents the first suc-
cessful attempt to convert a PAM to a PAL through strict mutase-to-lyase res-
idue mutations. Such a breakthrough may guide future investigations into the
functional determinants of these enzymes and possibly foster the engineering
of faster PAM variants used for the efficient synthesis of b-Phe.
1. Heberling, M.M., et al. 2013. Current Opinion in Chemical Biology.
2. Malik, S., et al. 2011. Process Biochemistry.
3. Liljeblad, A. et al. 2006. Tetrahedron.
4. Wu, B., et al. 2011. Angew. Chem. Int. Ed.
5. Bartsch, S., et al. 2013. ChemCatChem.
3311-Pos Board B39
Simple Rules Imposed on a Primitive Cubic Lattice Robustly Generate
Structures that Mimic Features of Real Proteins
Deniz Turgut1, Osman B. Okan1, Aravind Rammohan2, Angel E. Garcia1,
Rahmi Ozisik1.
1Materials Science and Engineering, Rensselaer Polytechnic Institute, Troy,
NY, USA, 2Corning Inc., Painted Post, NY, USA.
We introduce a set of simple and well-defined rules, which produce protein-like
networks when they are imposed on a primitive cubic lattice. The resulting arti-
ficial structures successfully mimic the geometric and topological features of
real proteins, and therefore, provide the opportunity to understand characteris-
tics of protein structures and lead to the creation of synthetic proteins. The pro-
posed method does not involve a chain-fitting step and does not require
individual set of reference structures.We start with a cubic lattice, whose lattice
sites contain beads representing protein residues. Many cubic lattices are
emptied up to 60% vacancy concentration by randomly removing beads while
maintaining a connected network of occupied sites. The maximum vacancy
concentration of 60% was obtained from first and second nearest neighbor
occupancies of real protein residues. A Reverse Monte-Carlo/Simulated
Annealing (RMC/SA) simulation that is constrained to fit the average radial
distribution function of residues of 278 proteins is then performed. Results indi-
cate that the RMC/SA procedure recovers the average radial distribution func-
tion without disturbing other structural properties such as bond orientational
order parameters and network topology. Based on various structural properties,
our results indicate that these artificially created structures closely resemble
real residue networks.
3312-Pos Board B40
Inferring Protein Structures from Sparse and Ambiguous Data
Justin L. MacCallum, Alberto Perez, Kenneth A. Dill.
Laufer Center for Physical and Quantitative Biology, Stony Brook, Stony
Brook, NY, USA.
We have developed a new computational framework called MeLD: Modeling
with Limited Data. MeLD is an integrative modeling approach that combines
physical modeling and statistical mechanics with data from experiment andbioinformatics. The approach is tailored to deal with data with the following
properties: (1) the data is sparse, where there may be little to no information
about some part of the structure; (2) the information is often ambiguous and
not totally reliable. I will present several applications of MeLD, including suc-
cessful structure determination from sparsely-labeled NMR data and EPR data,
accurate structures predicted from evolutionarily inferred contacts, and the cor-
rect prediction of the binding mode of an intrinsically disordered protein based
on site-directed mutagenesis data.
3313-Pos Board B41
Simulation Study of Soluble Toxic Oligomeric Structures of Amyloid-Beta
Sukanya Sasmal1, Timothy Balmorez2, K. Aurelia Ball3, Teresa Head-
Gordon4.
1Department of Chemical and Biomolecular Engineering, University of
California, Berkeley, Berkeley, CA, USA, 2Chemical Biology, University of
California, Berkeley, Berkeley, CA, USA, 3Graduate Group in Biophysics,
University of California, Berkeley, Berkeley, CA, USA, 4Department of
Chemistry, Bioengineering and Chemical and Biomolecular Engineering,
University of California, Berkeley, Berkeley, CA, USA.
Although early attention has focused on toxicity of amyloid plaques as the
cause of Alzheimer’s disease (AD), there is stronger evidence that soluble
Ab oligomers, and more recently pre-fibrillar oligomers, show better correla-
tion with AD symptoms than do the insoluble fibrillar states exhibited at the
completion of the amyloid cascade. In recent work a new oligomeric Ab
form known as the "globulomer" was found to inhibit calcium uptake by
neuronal cells and to contribute to memory loss in lab animals. At present
we have no knowledge of the globulomer structure, nor a smaller species
known as the pre-globulomer, which is usually a necessary first step in the
design of small molecule drug therapeutics. We will present our hypothesis
about the structural ensembles of these two oligomeric forms based on molec-
ular dynamics simulations and calculation of NMR observables and amide ex-
change data.
3314-Pos Board B42
Computer Simulations for Predicting Membrane Protein Structures with
the Replica-Exchange Methods and Implicit Membrane Model of a
Restricted Configurational Space
Ryo Urano, Yuko Okamoto.
Nagoya University, Nagoya, Aichi, Japan.
The structures of membrane proteins are necessary to examine the functions
and the mechanisms. The determination of membrane proteins takes a long
time yet despite the development of experimental techniques. Thus, we
have developed simulation methods for predicting alpha-helical membrane
proteins. For the purpose, replica-exchange methods (REM) and a particular
implicit membrane model are used. Distortions and kinked helix structures in
transmembrane helices are frequently observed as a characteristic appearance
of experimental membrane protein structures. Concerted rotation of torsion
angles and dihedral angle of main chains in Monte Carlo move sets are
implemented for including the distortions. Our implicit membrane model is
to mimic the sampled configuration during native folding of membrane
proteins after inserted membrane environment. We applied this method to
bacteriorhodopsin, which has seven dis-
torted transmembrane helices. From the
random ideal helix configuration, we ob-
tained local-minimum free energy states
by REM simulations and principal compo-
nent analysis. The RMSD value of whole
backbone atoms from the PDB structure
is 2.5 angstroms. The RMSD values in
each helix structure about distortions are
also less than about 1.5 angstroms.3315-Pos Board B43
Toward a Global View of the Conformational Landscape of the Human
Kinome
Daniel L. Parton1, Diwakar Shukla2, Yutong Zhao2, Vijay S. Pande2,
John D. Chodera1.
1Memorial Sloan-Kettering Cancer Center, New York, NY, USA, 2Stanford
University, Stanford, CA, USA.
The human genome contains about 500 protein kinases, which play a central
role in the regulation of the majority of cellular pathways. Mutations in kinase
genes - often resulting in dysregulation of their phosphotransferase activity -
are a frequent cause of disease, including many types of cancer. Kinases are
especially flexible proteins, and undergo significant conformational changes
during their catalytic and regulatory cycles. This conformational heterogeneity
is also of fundamental importance in determining the binding affinity and
656a Wednesday, February 19, 2014selectivity of inhibitory ligands, their susceptibility to resistance mutations, and
the discovery of putative allosteric binding sites. Markov state models have
recently emerged as a practical computational approach to the enumeration
of protein conformational states, and can be constructed by aggregating the
data from multiple, independent, short molecular dynamics trajectories in a sta-
tistical fashion. We aim to apply this technique to the entire human kinome,
simulating each protein kinase catalytic domain using a range of high perfor-
mance compute resources, including the distributed simulation framework, Fol-
ding@Home. In combination with recent developments in GPU-accelerated
simulation algorithms, this approach allows us to obtain aggregate trajectory
lengths on the order of milliseconds. An automated software pipeline provides
the ability to quickly generate multiple starting configurations for each kinase,
while a central database of publicly available kinase data has been set up and
used for tasks such as the selection of catalytic domain sequences and the
assignment of relative priorities to each kinase. In parallel with our computa-
tional approach, we are working towards expressing a diverse range of kinases
in bacterial systems, and scaling up a fluorescence-based assay to plate format
for direct measurement of kinase inhibitor binding affinities. Our poster will
present preliminary results from these efforts.
3316-Pos Board B44
Docking Benchmark Set of Protein Models
Ivan Anishchanka1,2, Petras J. Kundrotas1, Alexander V. Tuzikov2,
Ilya A. Vakser1,3.
1Center for Bioinformatics, The University of Kansas, Lawrence, KS, USA,
2National Academy of Sciences of Belarus, Minsk, Belarus, 3Department of
Molecular Biosciences, The University of Kansas, Lawrence, KS, USA.
Protein docking is a computational procedure for predicting the 3D structure of
protein complexes. Docking has been extensively benchmarked on experimen-
tally determined protein structures. However, studies of protein-protein interac-
tions increasingly involve modeled structures of the individual interactors.
These structures are inherently less accurate than the X-ray structures. Thus,
the utility of docking procedures, when applied to protein models, should be
thoroughly tested in benchmarking studies. Such benchmark set of protein
models was developed as part of the DOCKGROUND resource (http://
dockground.bioinformatics.ku.edu). The set contains 63 complexes with each
monomer represented by six models with a pre-defined Ca RMSD from the
native structure (1, 2, . 6 A˚). The models were generated by a combination
of homology modeling and Nudged Elastic Band method. A new, extended
set of protein models was recently built for 165 nonredundant hetero complexes
from DOCKGROUND. For more realistic representation of the models, they
were generated exclusively by I-TASSER protein modeling package. The
benchmark sets were used in the assessment of protein docking methodologies.
3317-Pos Board B45
Structural Similarity in Modeling of Homodimers
Petras Kundrotas1, Ilya Vakser1, Joe¨l Janin2.
1University of Kansas, LAWRENCE, KS, USA, 2, Universite´ Paris-Sud 11,
Orsay, France.
Template-based methods, which utilize known protein structures, are
commonly employed to model individual proteins from their sequences.
Here we benchmark a template-based method, previously proposed for
modeling hetero-dimeric complexes, on sets of homodimeric assemblies. The
method is based on structural alignment of assembly subunits and identifies
templates for the vast majority of the test targets. In many cases, the target-
template pairs have sequence identity too low for reliable detection by
sequence-based methods. An overall dimer geometry as well as interface resi-
due contacts are correctly reproduced for almost half of the targets. We present
analysis of the obtained models and their templates, which revealed incorrectly
determined quaternary structure for a number of entries in the Protein Data
Bank.
3318-Pos Board B46
Three-Dimensional Structure of the 54-Kda Subunit of the Chloroplast
Signal Recognition Particle using Molecular Modeling
Rory Henderson, Mercede Furr, Srinivas Jayanthi, Alicia Brown,
Robyn Goforth, Ralph Henry, T.K.S. Kumar.
University of Arkansas, Faytteville, AR, USA.
The chloroplast signal recognition particle is a heterodimeric complex of the
54kDa cytosolic signal recognition particle homologue (cpSRP54), and a novel
43kDa subunit (cpSRP43). While a nearly complete three-dimensional struc-
ture of cpSRP43 has been obtained, no structure is yet available for cpSRP54.
The three-dimensional structure for cpSRP54 could provide valuable informa-
tion for the rationalization of the extensive information already available
regarding its function, and in the understanding of the as yet undetermined
mechanism of light harvesting chlorophyll binding protein’s (LHCP) insertioninto the thylakoid membrane. In this study, we developed an in silico, three-
dimensional structural model of cpsRP54 using a combination of homology
modeling, de novo structure prediction and molecular dynamics simulation.
The resulting structure is consistent with the known properties of the protein
and sheds new light on some of the mechanistic details of its functioning.
3319-Pos Board B47
A Molecular Dynamics Simulation Study of Outer Membrane Phospholi-
pase a (OMPLA) Structure and Dynamics in an Asymmetric Lipopolysac-
charide Membrane
Emilia L. Wu1, Patrick J. Fleming2, Jeffery B. Klauda3, Karen G. Fleming2,
Wonpil Im1.
1University of Kansas, Lawrence, KS, USA, 2John Hopkins University,
Baltimore, MD, USA, 3The University of Maryland, College Park, MD, USA.
The outer membrane of Gram-negative bacteria is a unique and highly asym-
metric lipid bilayer composed of phospholipids in the inner leaflet and mostly
lipopolysaccharide (LPS) in the outer leaflet. Outer membrane phospholipase A
(OmpLA) is an integral membrane enzyme in Escherichia coli. The structure of
monomeric OmpLA consists of a 12-stranded antiparallel b-strands with a
convex and a flat side, six loops at the extracellular side and five turns at the
periplasmic side of the membrane. Utilizing the latest C36 CHARMM lipid
and carbohydrate force field, we have constructed a model of OmpLA
embedded in an asymmetric lipid bilayer with rough LPS molecules (without
O-antigen) in one leaflet and phosphatidylethanolamine, phosphatidylglycerol,
and cardiolipin in the other leaflet to model the realistic outer membrane envi-
ronment. The simulation results will be discussed in terms of the key structural
properties of the bacterial outer membrane including hydrophobic thickness,
area per lipid, and acyl chain order parameter. We will also show the difference
of OmpLA structure and dynamics compared to that in a DLPC bilayer. At the
same time a comparison between simulations with different numbers of LPS
molecules on the outer leaflet will elucidate the potential technical difficulties
in building asymmetric bilayer.
3320-Pos Board B48
Modular Platform for Biomolecular Modeling and Simulations
Dominik Gront.
Faculty of Chemistry, University of Warsaw, Warsaw, Poland.
Computational software has been a cornerstone of many biological sciences
such as biophysics, bioinformatics or biomolecular modelling in general. The
last few decades witnessed numerous software packages that implemented
newly emerging methods and algorithms. In parallel with the development of
methods to solve particular scientific problems, the general picture how a suite
of computational software should be constructed also evolved.
Here we present the design, implementation and functionality of BioShell[1,2]
software - a versatile package for biomolecular modelling. Its functionality
ranges from processing structural and sequence databases to sampling confor-
mations both in Cartesian and alignment space. Highly modular structure facil-
itates easy extension of the package. Its modules may be conveniently bound by
a high-level Python script into a single pipeline.
One of the newest BioShell applications is three-dimensional threading. A
Monte Carlo search scheme samples the conformational space of alignments
between a query sequence and a template structure. In another example, Bio-
Shell modules were used to build a simple computational model of RNA
molecules.
1. D. Gront, and A. Kolinski, Bioinformatics, 2005, 22, 621-622.
2. D. Gront, and A. Kolinski, Bioinformatics, 2008, 24, 584-585.
3321-Pos Board B49
A Global Machine Learning Based Scoring Function for Protein Structure
Prediction
Eshel Faraggi1,2, Andrzej Kloczkowski2,3.
1Department of Biochemistry and Molecular Biology, Indiana University
School of Medicine, Indianapolis, IN, USA, 2Battelle Center for
Mathematical Medicine, Nationwide Children’s Hospital, Columbus, OH,
USA, 3Department of Pediatrics, The Ohio State University, Columbus, OH,
USA.
We present a knowledge-based function to score protein decoys based on their
similarity to native structure. A set of features is constructed to describe the
structure and sequence of the entire protein chain. Furthermore, a qualitative
relationship is established between the calculated features and the underlying
electromagnetic interaction that dominates this scale. The features we use are
associated with residue-residue distances, residue-solvent distances, pairwise
knowledge based potentials and a four-body potential. In addition we introduce
a new target to be predicted, the fitness score, which measures the similarity of
a model to the native structure. This new approach enables us to obtain infor-
mation both from decoys and from native structures. It is also devoid of


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Toward a Global View of the Conformational Landscape of the Human Kinome

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