158a
Sunday, February 8, 2015
webserver which requires only coordinate file to be inputted and the user is pro-
vided with various, but easy to navigate, options. The output information
including the change in hydrogen bonds network and binding energy due to
amino acid substitution is displayed on the output and is available for download.
Calibration is the final and critical stage of the design of the force fields for pro-
teins and other biological macromolecules. For proteins, the usual goal of this
procedure is to optimize the force-field parameters to reproduce the native
structures of selected training proteins. However, the resulting force fields
are usually not sufficiently predictive, because only the structures of folded pro-
teins are used. Thus, a force field is not sufficiently trained to distinguish folded
structures from misfolded ones. In this work, we propose a novel approach, in
which a force field is calibrated with the ensembles of structures determined by
NMR at various temperatures that encompass the region of thermal unfolding.
The method is based on applying the maximum-likelihood principle. Each
conformation of the NMR-determined ensemble at a given temperature is an
experimental point and the theoretical probability-density function is repre-
sented by a sum of Gaussians centred at the decoys from the corresponding en-
sembles generated by simulations; in this work the replica exchange molecular
dynamics procedure was used. The maximum-likelihood function (-logL) is
minimized using the current decoy set, then new decoys are generated with
the optimized force-field parameters. The procedure is iterated until conver-
gence. The method was applied to the physics-based coarse-grained UNRES
force field developed in our laboratory. On the first attempt, NMR structures
of a small alpha-helical protein, the tryptophan cage, were used. The resulting
force field predicted correctly the structures of 13 out of 14 alpha-helical pro-
teins with different helix-packing topology and size from 36 to 104 amino-acid
residues. Results of the calibration of the UNRES force field with more pro-
teins, including villin headpiece (alpha), the C-terminal fragment of the IGG
protein (beta), and full-sequence design 1 (alphaþbeta), will be presented.
789-Pos Board B569
Quantum Mechanical Molecular Mechanical Calculations using
AMOEBA Force Fields
Yihan Shao, Andrew Simmonett, Frank Pickard, Gerhard Koenig,
Bernard Brooks.
NHLBI, Rockville, MD, USA.
We report an implementation of quantum mechanical molecular mechanical
(QM/MM) calculations with AMOEBA force field applied to water molecules
in the molecular mechanics region. Three AMOEBA parameter sets
(AMOEBA03, iAMOEBA, and AMOEBA14) are employed, and compared
to TIP3P and other water models in terms of their performance in QM/MM cal-
culations. The effect of the MM polarization (MM induced dipoles due to QM
electron density) will also be discussed.
786-Pos Board B566
Bio.B-Gen: An Initial System Generator for Biological Molecular
Simulations
Dmitri Rozmanov, Peter Tieleman.
Biological Sciences and Centre for Molecular Simulation, University of
Calgary, Calgary, AB, Canada.
Atomistic and coarse-grained simulations can be a great help in uncovering the
mechanisms of physical processes at microscopic and mesoscopic levels at
time scales ranging from femtoseconds to milliseconds.
Any simulation study involves (1) setting up an appropriate simulation system
representing the physical problem, (2) running the simulation and collecting in-
formation about the system, and (3) analyzing the collected data. The last step
eventually leads to final conclusions about the system. Software for molecular
simulation has been in development for many years and a number of high quality
freely distributed general purpose simulation packages is available for re-
searchers. Data analysis tools are usually less general as they often depend on a
specific research project and the system under investigation. While many simula-
tion packages come with a set of some general data analysis utilities, it is not un-
usual for such analysis tools to be developed on a per project basis inside research
groups. Interestingly, there is a very limited set of available tools for setting up
simulation systems, even though this is the very first and vital step of every simu-
lation study. This lack of convenient general simulation system generators some-
times may even dictate the kind of simulations done based on the available initial
systems rather than on the system being the best for a particular problem.
In this work we describe a general software tool, bio.b-gen, for the creation of
initial systems for biological molecular simulations. A number of case systems
are demonstrated using an atomistic force field as well as the coarse grained
MARTINI force field. The tool is designed to generate initial systems for the
GROMACS general simulation package.
787-Pos Board B567
Validation and Development of the Force Field Parameters for Drug and
Drug-Like Molecules
Katarzyna B. Koziara1, Martin Stroet1, Alpeshkumar K. Malde1,
Alan E. Mark1,2
.
1The University of Queensland, Brisbane, Australia, 2Institute for Molecular
Bioscience, Brisbane, Australia.
790-Pos Board B570
The Do’s and Do Not’s of a 100 Million Atom Molecular Dynamics
Simulation
Highly optimized and well-validated parameters have been developed for struc-
ture refinement and computer simulation of biomolecules. However, the force
fields for most drug and drug-like ligand molecules are not properly validated.
Out of ~100,000 X-ray crystal structures in the Protein Data Bank (2014),
>25,000 structures contain at least one of >17,000 chemically diverse ligand
molecules. In addition, there is over a million ligand molecules of interest in
databases such as NCI and Pubchem. Understanding interatomic interactions
of a given ligand with its target acceptor is crucial in molecular modelling
and the lack of precise force field parameters for small heteromolecules may
result in failure of drug design efforts.
A web accessible Automated force field Topology Builder (ATB; http://
the generation of force field parameters for chemically diverse ligand mole-
cules. The ATB performs quantum mechanical calculations combined with a
knowledge-based approach to ensure compatibility with a biomolecular force
field. The topologies and parameters created can be used in simulations,
computational drug design and X-ray refinement.
Most importantly, a fully automated validation of the force field parameters has
been incorporated into the ATB methodology. Recent work on the validation of
parameters against structural and thermodynamic data as well as the outcome
of participating in the SAMPL4 community challenge for the prediction of hy-
dration free energy of drug-like molecules will be presented. Further refinement
strategies to improve the parameters by scaling of the van der Waals and elec-
trostatic interactions will be discussed as well.
Abhishek Singharoy1, Danielle Chandler1, Jacob Durrant2, Melih Sener1,
Rommie Amaro2, Klaus Schulten1.
1Beckman Institute, University of Illinois, Urbana Champaign, IL, USA,
2Chemistry, University of California, San diago, CA, USA.
The ever so growing prowess of petascale computing resources has pushed the
envelope of biomolecular modeling, simulation, and analysis into the regime of
hundred million atom systems. To bring a very challenging organelle-scale
system under simulation control often involves substantial modifications of ex-
isting computational tools. Using two ongoing simulations of a bacterial chro-
matophore and the influenza virion coat, we demonstrate VMD-, NAMD-,
MDFF-, and python-based innovations that enable large-scale biomolecular
simulations. The protocol involves new semi-automated, yet high throughput,
ways of large-scale atomic model construction, including in disordered mem-
brane environments, their solvation, ionization, and equilibration, particularly
for system sizes in excess of tens of million atoms. Discussions will extend
to tools for characterizing the physical properties of a hundred million atom
system, such as long-range electrostatics. Finally, the scientific purpose of per-
forming such simulations will be justified in the light of results obtained from
whole-chromatophore and whole-virion-coat simulations.
791-Pos Board B571
Minimally-Biased Metadynamics Method to Sample Conformational
Ensembles Compatible with Experimental Measurements
Fabrizio Marinelli, Jose´ D. Faraldo-Go´mez.
788-Pos Board B568
Theoretical Molecular Biophysics Section, National Institutes of Health
(NHLBI), Bethesda, MD, USA.
A Novel Method for Force-Field Calibration Based on Maximum-
Likelihood Approach and Thermal Unfolding Data
Bart1omiej Zaborowski1, Dawid Jagie1a1, Adam K. Sieradzan1,
Cezary R. Czaplewski1, Anna Ha1abis2, Agnieszka Lewandowska2,
A primary goal in computational biophysics is to harness experimental mea-
surements to obtain information on the structure and dynamics of biomolecules.
However, most biophysical techniques such as NMR and EPR spectroscopy
provide signals that arise from an ensemble of multiple molecular conforma-
tions. Thus, it is typically not straightforward to extract detailed structural
information from the experimental data. A possible strategy is to bias the
conformational sampling obtained in a molecular dynamics simulations in
2
2
1
_
ꢀ
Wioletta Zmudzinska , Stanis1aw O1dziej , Jozef A. Liwo .
1Faculty of Chemistry, University of Gdansk, Gdansk, Poland,
2Intercollegiate Faculty of Biotechnology, University of Gdansk and Medical
University of Gdansk, Gdansk, Poland.