59th Annual Meeting of the Biophysical-Society, Baltimore, MD, FEB 07-11, 2015International audienceno abstrac

Cocco, Simona

De Leonardis, Eleonora

Lutz, Benjamin

Monasson, Rémi

Schug, Alexander

Szurmant, Hendrik

Weigt, Martin

Hal-Diderot

Protein and RNA Structure Prediction by Integration of Co-Evolutionary Information into Molecular Simulation

Monasson, Remi

Elsevier - Publisher Connector 

Protein and RNA Structure Prediction by Integration of Co-Evolutionary Information into Molecular Simulation 

Sunday, February 8, 2015 13amethylammonium, acetate and water[4]. With the removal of the previous am-
biguity brought by using water as both the hydrogen-bond donor and acceptor
fragment[2], improved screening results are seen using targets in the DUD data-
base in the extended SILCS-Pharm method. Validations of the protocol using
eight different protein targets show equal or better screening results when
compared with results using common docking methods such as DOCK or Au-
toDock, indicating the potential utility of the approach in rational drug design.
[1] YuW, Guvench O, MacKerell AD, Jr. (2013) In:Understanding and exploit-
ing protein-protein interactions as drug targets. Future Science Book Series.
Future Science Ltd, London, UK, p90-102.
[2] Yu W, Lakkaraju SK, Raman EP, MacKerell AD, Jr. (2014) J Comput
Aided Mol Des 28(5):491-507.
[3] Guvench O, MacKerell AD, Jr. (2009) PLoS Comput Biol 5(7):e1000435.
[4] Raman EP, Yu W, Lakkaraju SK, MacKerell AD, Jr. (2013) J Chem Inf
Model 53(12):3384-3398.
63-Plat
Quantifying Macromolecular Conformational Transition Pathways
Oliver Beckstein, Sean L. Seyler, Avishek Kumar, Michael F. Thorpe.
Physics, Arizona State University, Tempe, AZ, USA.
Diverse classes of proteins such as molecular motors, enzymes, and active
transmembrane transporters function through large-scale conformational
changes. Computer simulations of these conformational transitions are chal-
lenging. A range of coarse-grained and biased simulation techniques have
been used to generate individual transitions or ensembles of transition pathways
but it has been difficult to compare pathways produced by different methods
and so to assess their relative strengths. We introduce a comprehensive method
(pathway similarity analysis, PSA) for quantitatively characterizing and
comparing macromolecular pathways. The Hausdorff and Frechet metrics
(known from computational geometry) are used to quantify the degree of sim-
ilarity between piecewise-linear curves in configuration space. We tested PSA
on a toy system to study the effect of temperature fluctuations (path roughness)
and dimensionality. We compare a sample of publicly accessible transition
pathway simulation servers and our own dynamic importance sampling
(DIMS) MD method for the closed-to-open transitions of the apo enzyme ad-
enylate kinase (AdK). PSA was applied to ensembles of hundreds of trajec-
tories of the conformational transitions of the transporter Mhp1 and of AdK
and diphtheria toxin, which were produced by DIMS MD and the Geometrical
Pathways algorithm. Clustered PSA enabled the selection of a small subset of
representative trajectories for further analysis. A strength of PSA is its use of
the full information available from the 3N-dimensional configuration space tra-
jectory, without requiring additional specific knowledge about the system. We
show how trajectory analysis methods relying on pre-defined collective vari-
ables such as native contacts or geometric quantities can be used synergistically
with PSA. We discuss the method’s potential to enhance our understanding of
transition path sampling methods, validate them, and ultimately help guide
future research toward deeper physical insights into conformational transitions.
64-Plat
Computational Design of Repeat-Proteins with a Predefined Geometry
Sebastian Ra¨misch1, Ulrich Weininger2, Jonas Martnisson1, Mikael Akke2,
Ingemar Andre´1.
1Department of Biochemistry and Structural Biology, Lund University, Lund,
Sweden, 2Department of Biophysical Chemistry, Lund University, Lund,
Sweden.
New protein design methods are needed to further improve the development of
protein-binding scaffolds. Repeat proteins are linear tandem arrays of structur-
ally similar building blocks, and they are established platforms for engineering
proteins inhibitors and biosensors. However, current sequence-based engineer-
ing approaches lack the possibility of customizing the overall shape of a binder
to its target molecule. Structure-based protein design offers a possibility of
optimizing the overall shape of engineered binding scaffolds to better match
their targets. We developed a protocol for the computational design of
shape-optimized binding scaffolds that can better match their targets. By
combining sequence optimization of existing repeats and de novo design of
capping structures, we designed leucine-rich repeat (LRR) proteins where the
building blocks assemble with a novel geometry. We validated the geometric
design approach by engineering an artificial donut-like ring structure con-
structed from ten self-compatible repeats. Characterization of the design con-
structs revealed that buried cysteines play a central role for stability and
folding cooperativity in certain LRR proteins. This may be used to selectively
stabilize or destabilize specific parts of a protein. The computational procedure
may now be employed to develop repeat proteins with various geometricalshapes for applications where greater control of the interface geometry is
desired.
65-Plat
Computational Prediction of G-Quadruplex Formation
Jacob S. Calvert1, Alex Kreig1, Saurabh Sinha2, Sua Myong1.
1Bioengineering, University of Illinois at Urbana-Champaign, Champaign,
IL, USA, 2Computer Science, University of Illinois at Urbana-Champaign,
Champaign, IL, USA.
Guanine-rich regions of genomic DNA can spontaneously fold into secondary
structures called G-quadruplexes (GQs). Akin to tiny switches, GQs regulate
genetic processes through their folding and unfolding. Their interest to basic
science, as well as their potential as therapeutic targets for human diseases,
has motivated the creation of computational tools for their prediction.
Currently, GQ folding predictors are based on results from structural and
biochemical studies of GQ formed in single-stranded (ss) DNA. As a result, ex-
isting tools perform poorly when applied to the prediction of GQ formation in
double-stranded (ds) DNA, the native context within which genomic GQs are
found. Here, we present a probabilistic model of GQ formation, which is
learned from large-scale human genomic pull-down experiments and applied
to the analysis of gene ontological data. Advances in the characterization of
GQs in dsDNA have enabled us to integrate results from small-molecule bind-
ing assays and single-molecule FRET microscopy into our model. In order to
obtain training sets of sequences, we identified nearly 700,000 unique, potential
GQs and categorized them according to pull-down experiment outcomes.
Model parameters learned from these training sets agree with experimental
evidence and, when asked to predict the folding of dsDNA GQ sequences, out-
performed existing models of GQ folding. To further explore the model’s util-
ity, we screened potential GQ drug targets by selecting high-scoring sequences
for gene ontological analysis. Our results indicate that highly scoring sequences
are preferentially located near cancer-related genes. This tool can be applied to
genomic sequences to locate the most strongly forming GQs, revealing valu-
able information for the design of GQ-targeting therapies, and represents the
next step toward the practical, widespread use of GQs in medicine and
technology.
66-Plat
Protein and RNA Structure Prediction by Integration of Co-Evolutionary
Information into Molecular Simulation
Eleonora De Leonardis1,2, Benjamin Lutz3,4, Simona Cocco5,
Remi Monasson6, Hendrik Szurmant7, Martin Weigt1,2, Alexander Schug3.
1Computational and Quantitative Biology, Sorbonne Universite´s, Universite´
Pierre et Marie Curie, Paris, France, 2Computational and Quantitative
Biology, CNRS, Paris, France, 3Steinbuch Centre for Computing, Karlsruhe
Institute of Technology, Karlsruhe, Germany, 4Fakulta¨t fu¨r Physik, Karlsruhe
Institute of Technology, Karlsruhe, Germany, 5Laboratoire de Physique
Statistique, Ecole Normale Supe´rieure, associe´ au CNRS et a` l’Universite´
Pierre et Marie Curie, Paris, France, 6Laboratoire de Physique The´orique,
Ecole Normale Supe´rieure, associe´ au CNRS et a` l’Universite´ Pierre et Marie
Curie, Paris, France, 7Molecular and Experimental Medicine, The Scripps
Research Institute, La Jolla, CA, USA.
Exploring the relationship of structure and function is crucial for the under-
standing of molecular life. Despite significant progress of experimental
methods, the structural characterization of important structures for both pro-
teins and RNA - typically preceding any detailed mechanistic exploration
of their function - remains challenging. In recent years, increasingly ubiqui-
tous availability of sequential information and novel statistical analysis has al-
lowed to trace the co-evolution of residues and predict contact maps. These
contact maps can be exploited in structure prediction tools. One maximum en-
tropy based approach is called Direct Coupling Analysis (DCA)[1] and, e.g.,
was found to be sufficient for the blind prediction of a protein complex[2]
and its active conformation[3] later confirmed by experiment. We have
successfully adapted this method to the specifics of RNA (rnaDCA): While
it is comparably simple to predict RNA secondary structure through
analyzing possible Watson-Crick base pairings, predicting tertiary contacts
has remained - despite significant effort - an elusive task met with limited suc-
cess. In contrast, our novel rnaDCA is able to extract tertiary contacts from
genomic data. We further demonstrate that these tertiary contacts are suffi-
cient to systematically improve tertiary RNA prediction quality[4]. Consid-
ering the large gap of known ncRNA sequences to experimentally resolved
tertiary structures, we are convinced that this will significantly impact all
structural RNA related research.
14a Sunday, February 8, 2015References
[1] Weigt M et al., Proc Nat Acad Sci USA (2009) 106, 67-72; F. Morcos et al.,
Proc Nat Acad Sci (2011) 108, E1293-E1301
[2] Schug A et al., Proc Nat Acad Sci USA (2009) 106, 22124-22129
[3] Dago A et al., Proc Nat Acad Sci USA (2012), 109: E1733-42
[4] E. De Leonardis et al. Direct-Coupling Analysis of nucleotide coevolution
facilitates RNA tertiary structure prediction, (submitted)
67-Plat
Structural Ensembles of Intrinsically Disordered Proteins usingMolecular
Dynamics Simulation
Sarah Rauscher, Vytautas Gapsys, Bert de Groot, Helmut Grubmu¨ller.
Theoretical & Computational Biophysics, Max Planck Institute for
Biophysical Chemistry, Go¨ttingen, Germany.
Intrinsically disordered proteins (IDPs) fulfill many biological roles and are
important drug targets. However, they are poorly understood relative to the
wealth of structural information available for globular proteins. Their structural
characterization presents a formidable challenge to both theory and experi-
ment: the structure of an IDP must be described as a structural ensemble of
many interconverting conformations.
Here, we use molecular dynamics simulations to obtain structural ensembles of
two IDPs: (1) a 79-residue FG-nucleoporin peptide, which is responsible for the
selectivity of the nuclear pore complex and (2) a 24-residue RS-repeat peptide
derived from serine/arginine-rich-splicing-factor-1, which is crucial in RNA
splicing. Because force fields for polypeptides have been developed primarily
to study folded proteins, it is not clear how accurately they can model disor-
dered states. To address this issue, we performed simulations using four force
fields: amber99sb*-ildn, amber ff03w, CHARMM22*, and CHARMM36 using
replica exchange (RE) for a total of 150 microseconds per force field.
The structural ensembles we obtain for both the FG and RS peptides differ mark-
edlybetween force fieldswith respect tohydrogen bonding, radius of gyration, and
secondary structure, and are sufficiently converged to make such a comparison.
Importantly, secondary structure content differs more on average between force
fields than between the two peptide sequences. Thus, disordered peptides appear
tobe particularly sensitive to force field selection,muchmore so thanglobular pro-
teins.We compared the structural ensembles obtainedwith each force field to both
NMR and small angle x-ray scattering data for the RS peptide by computing
ensemble averages of the experimental observables. The CHARMM22* force
field provides the most accurate description of the force fields tested. In addition,
we find that CHARMM22* provides the fastest sampling of configuration space.
Platform: Protein-Nucleic Acid Interactions I
68-Plat
Binding Competition Studied with Single Molecule FRET: The Integron
Recombinase Outcompetes the Single-Stranded DNA Binding Protein
for its Recombination Site
M. Svea Grieb, Varsha Natarajan, Marko Swoboda, Michael Schlierf.
B CUBE-Center for Molecular Bioengineering, TU Dresden, Dresden,
Germany.
Bacteria can adapt impressively to environmental changes and acquire antibiotic
multiresistance. Adaptation is mainly achieved by the integron, a genetic device
that uses DNA site-specific recombination to collect and express gene cassettes.
Integron recombination is unique as its recombinase, IntI, targets a single-
stranded recombination site, called attC. attC sites fold themselves into an
imperfect hairpin structureof 65 to150nucleotides, resembling a canonical recom-
bination site. However, it is unknown how attC hairpins form in the bacterial cyto-
plasm. This is an interesting question, as high amounts of single-stranded DNA
binding protein (SSB) are present in the cytoplasm to prevent DNA secondary
structure formation, which interfere with cellular processes, like DNA replication.
To investigate if IntI can counter the effect of SSB, we characterized the binding
mechanism of IntI and SSB to an attC hairpin, both individually and simulta-
neously, using single-molecule Fo¨rster Resonance Energy Transfer (smFRET).
We show that SSB is able to open a folded attC hairpin by binding to it in the non-
cooperative SSB(65) mode. Contrary to binding unstructured ssDNA, SSB
avoids the cooperative SSB(35) mode when binding hairpins, even in very
high protein-to-DNA ratios.We performed a kinetic analysis to quantify the con-
centration and substrate dependent dynamics of SSB binding/unbinding. We
further found that the recombinase IntI plays an antagonistic role, as it stabilizes
the folded attC site. Experimentswith target competition revealed that IntI is able
to counterbalance SSB even at much lower concentration.
We conclude that SSB impedes attC hairpin formation at background IntI con-
centrations, and thus ensures the genetic stability of those palindromic se-
quences. However, after induction of IntI expression, the action of SSB is
outcompeted, allowing IntI to bind to its target site.69-Plat
Single-Molecule FRET for Dynamic Structural Biology: DNA Polymerase
i Structure and Mechanism with Angstrom Precision
Marko Sustarsic1, Timothy Craggs1, Johannes Hohlbein2,
Andrew Cuthbert1, Nicholas Taylor1, Hendrik Kaju3, Majid Mosayebi3,
Jonathan Doye3, Achillefs N. Kapanidis1.
1Department of Physics, University of Oxford, Oxford, United Kingdom,
2Laboratory of Biophysics, Wageningen UR, Wageningen, United Kingdom,
3Department of Chemistry, University of Oxford, Oxford, United Kingdom.
A key question in the function of DNA-processing enzymes is their mechanism
for rapid location and binding of target sites in DNA. DNA polymerase I (Pol)
is involved in high-fidelity DNA replication and repair, and must recognize
gapped and flapped DNA substrates. Due to their transient and dynamic nature,
the structures of these complexes and the recognition mechanism by which they
are formed are largely unknown.
Combining single-molecule Fo¨rster Resonance Energy Transfer (smFRET)
with dye-position modelling, we can obtain absolute distance measurements
with angstrom precision. We have used 120 such distances in a rigid-body
docking approach to determine the structure of the single-nucleotide-gapped
DNA-Pol binary complex, and that of the gapped-DNA substrate alone.
In the complex structure, the DNA substrate exhibits a 120-degree bend. The
upstream DNA is channeled into the Pol active site, and its position is in excel-
lent agreement (RMSD < 3 A˚) with the position of short DNA fragments seen
in crystal structures of Pol. The downstream DNA is partially melted and held
in close proximity to F771, a residue important for strand displacement.
The structure of the gapped-DNA substrate alone adopts a 20-degree bend and a
twist. Our coarse-grained simulations show short excursions of the substrate to
partially kinked conformations not accessible to duplex DNA. Together, these
data are consistent with a two-step model whereby Pol recognizes and binds a
partially kinked conformation of gapped DNA, which then further rearranges to
the fully bent state seen in the complex structure.
Finally, using our method of internalization by electroporation, we have
observed single-molecule FRET signals corresponding to unbound and Pol-
bound gapped DNA in live bacteria, confirming the physiological relevance of
the proposed substrate and complex structures and the recognition mechanism.
70-Plat
Heterochromatin Assembly and Dynamics on the Single Molecule Level
Sinan Kilic, Bachmann Andreas, Louise Bryan, Beat Fierz.
EPFL, Lausanne, Switzerland.
Multivalent interactions between effector proteins and histone post-
translational modifications (PTMs) represent elementary processes in the chro-
matin signaling pathway. One such effector, heterochromatin protein 1 alpha
(HP1a), is a major component of transcriptionally repressive heterochromatin.
HP1a contains a chromodomain, a reader for H3 trimethylated at lysine 9
(H3K9me3), and forms dimers thereby allowing multivalent chromatin binding
and playing a role in chromatin fiber compaction.
Macroscopic heterochromatin foci in the cell are stable structures, however,
fluorescence photobleaching experiments demonstrate rapid dynamics of indi-
vidual HP1a proteins. The mechanistic details between dynamic HP1 binding
and its structural role in chromatin compaction is however not well understood.
We used single-molecule total internal reflection fluorescence microscopy
(smTIRFM) to directly observe HP1a interaction dynamics with chemically
defined chromatin fibers. In addition, we employed protein chemistry method
to control the oligomeric state of individual HP1a proteins. Together, our mea-
surements reveal that the HP1a residence time depends both on the local den-
sity of H3K9me3 marks, as well as on the oligomeric state of the protein. In
addition, HP1a dimerization greatly accelerates its association kinetics with
chromatin.
We thus propose that an increased chromatin binding rate is a key advantage of
effector multivalency, allowing efficient competition between chromatin effec-
tors and thus resulting in the maintenance of a stable chromatin state, which can
quickly adapt to cellular signals.
71-Plat
RNA Unwinding by the Helicase Mtr4p and the TRAMP Complex Inves-
tigated via High-Resolution Optical Trapping
Eric M. Patrick1, Sukanya Srinivasan2, Eckhard Jankowsky2,
Matthew J. Comstock1.
1Department of Physics and Astronomy, Michigan State University, East
Lansing, MI, USA, 2Department of Biochemistry, Center for RNAMolecular
Biology, Case Western University, Cleveland, OH, USA.
We present single-molecule high-resolution optical trapping measurements of
RNA unwinding by the Ski2-like nuclear helicase Mtr4p both alone and within
the Trf4/Air2/Mtr4 polyadenylation (TRAMP) complex. RNA helicases such


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Protein and RNA Structure Prediction by Integration of Co-Evolutionary Information into Molecular Simulation

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