398 research outputs found
Improvements to the APBS biomolecular solvation software suite
The Adaptive Poisson-Boltzmann Solver (APBS) software was developed to solve
the equations of continuum electrostatics for large biomolecular assemblages
that has provided impact in the study of a broad range of chemical, biological,
and biomedical applications. APBS addresses three key technology challenges for
understanding solvation and electrostatics in biomedical applications: accurate
and efficient models for biomolecular solvation and electrostatics, robust and
scalable software for applying those theories to biomolecular systems, and
mechanisms for sharing and analyzing biomolecular electrostatics data in the
scientific community. To address new research applications and advancing
computational capabilities, we have continually updated APBS and its suite of
accompanying software since its release in 2001. In this manuscript, we discuss
the models and capabilities that have recently been implemented within the APBS
software package including: a Poisson-Boltzmann analytical and a
semi-analytical solver, an optimized boundary element solver, a geometry-based
geometric flow solvation model, a graph theory based algorithm for determining
p values, and an improved web-based visualization tool for viewing
electrostatics
A Continuum Poisson-Boltzmann Model for Membrane Channel Proteins
Membrane proteins constitute a large portion of the human proteome and
perform a variety of important functions as membrane receptors, transport
proteins, enzymes, signaling proteins, and more. The computational studies of
membrane proteins are usually much more complicated than those of globular
proteins. Here we propose a new continuum model for Poisson-Boltzmann
calculations of membrane channel proteins. Major improvements over the existing
continuum slab model are as follows: 1) The location and thickness of the slab
model are fine-tuned based on explicit-solvent MD simulations. 2) The highly
different accessibility in the membrane and water regions are addressed with a
two-step, two-probe grid labeling procedure, and 3) The water pores/channels
are automatically identified. The new continuum membrane model is optimized (by
adjusting the membrane probe, as well as the slab thickness and center) to best
reproduce the distributions of buried water molecules in the membrane region as
sampled in explicit water simulations. Our optimization also shows that the
widely adopted water probe of 1.4 {\AA} for globular proteins is a very
reasonable default value for membrane protein simulations. It gives an overall
minimum number of inconsistencies between the continuum and explicit
representations of water distributions in membrane channel proteins, at least
in the water accessible pore/channel regions that we focus on. Finally, we
validate the new membrane model by carrying out binding affinity calculations
for a potassium channel, and we observe a good agreement with experiment
results.Comment: 40 pages, 6 figures, 5 table
Acceleration of Linear Finite-Difference Poisson-Boltzmann Methods on Graphics Processing Units
Electrostatic interactions play crucial roles in biophysical processes such
as protein folding and molecular recognition. Poisson-Boltzmann equation
(PBE)-based models have emerged as widely used in modeling these important
processes. Though great efforts have been put into developing efficient PBE
numerical models, challenges still remain due to the high dimensionality of
typical biomolecular systems. In this study, we implemented and analyzed
commonly used linear PBE solvers for the ever-improving graphics processing
units (GPU) for biomolecular simulations, including both standard and
preconditioned conjugate gradient (CG) solvers with several alternative
preconditioners. Our implementation utilizes standard Nvidia CUDA libraries
cuSPARSE, cuBLAS, and CUSP. Extensive tests show that good numerical accuracy
can be achieved given that the single precision is often used for numerical
applications on GPU platforms. The optimal GPU performance was observed with
the Jacobi-preconditioned CG solver, with a significant speedup over standard
CG solver on CPU in our diversified test cases. Our analysis further shows that
different matrix storage formats also considerably affect the efficiency of
different linear PBE solvers on GPU, with the diagonal format best suited for
our standard finite-difference linear systems. Further efficiency may be
possible with matrix-free operations and integrated grid stencil setup
specifically tailored for the banded matrices in PBE-specific linear systems.Comment: 5 figures, 2 table
PBEQ-Solver for online visualization of electrostatic potential of biomolecules
PBEQ-Solver provides a web-based graphical user interface to read biomolecular structures, solve the Poisson-Boltzmann (PB) equations and interactively visualize the electrostatic potential. PBEQ-Solver calculates (i) electrostatic potential and solvation free energy, (ii) proteināprotein (DNA or RNA) electrostatic interaction energy and (iii) pKa of a selected titratable residue. All the calculations can be performed in both aqueous solvent and membrane environments (with a cylindrical pore in the case of membrane). PBEQ-Solver uses the PBEQ module in the biomolecular simulation program CHARMM to solve the finite-difference PB equation of molecules specified by users. Users can interactively inspect the calculated electrostatic potential on the solvent-accessible surface as well as iso-electrostatic potential contours using a novel online visualization tool based on MarvinSpace molecular visualization software, a Java applet integrated within CHARMM-GUI (http://www.charmm-gui.org). To reduce the computational time on the server, and to increase the efficiency in visualization, all the PB calculations are performed with coarse grid spacing (1.5 Ć
before and 1 Ć
after focusing). PBEQ-Solver suggests various physical parameters for PB calculations and users can modify them if necessary. PBEQ-Solver is available at http://www.charmm-gui.org/input/pbeqsolver
Membrane Protein Properties Revealed through Data-Rich Electrostatics Calculations.
The electrostatic properties of membrane proteins often reveal many of their key biophysical characteristics, such as ion channel selectivity and the stability of charged membrane-spanning segments. The Poisson-Boltzmann (PB) equation is the gold standard for calculating protein electrostatics, and the software APBSmem enables the solution of the PB equation in the presence of a membrane. Here, weĀ describe significant advances to APBSmem, including full automation of system setup, per-residue energy decomposition, incorporation of PDB2PQR, calculation of membrane-induced pKa shifts, calculation of non-polar energies, and command-line scripting for large-scale calculations. We highlight these new features with calculations carried out on a number of membrane proteins, including the recently solved structure of the ion channel TRPV1 and a large survey of 1,614 membrane proteins of known structure. This survey provides a comprehensive list of residues with large electrostatic penalties for being embedded in the membrane, potentially revealing interesting functional information
Tools for Biomolecular Modeling and Simulation
Electrostatic interactions play a pivotal role in understanding biomolecular systems, influencing their structural stability and functional dynamics. The Poisson-Boltzmann (PB) equation, a prevalent implicit solvent model that treats the solvent as a continuum while describes the mobile ions using the Boltzmann distribution, has become a standard tool for detailed investigations into biomolecular electrostatics. There are two primary methodologies: grid-based finite difference or finite element methods and body-fitted boundary element methods. This dissertation focuses on developing fast and accurate PB solvers, leveraging both methodologies, to meet diverse scientific needs and overcome various obstacles in the field
Calculations of the Second Virial Coefficients of Protein Solutions with an Extended Fast Multipole Method
The osmotic second virial coefficients B2 are directly related to the solubility of protein molecules in electrolyte solutions and can be useful to narrow down the search parameter space of protein crystallization conditions. Using a residue level model of protein-protein interaction in electrolyte solutions B2 of bovine pancreatic trypsin inhibitor and lysozyme in various solution conditions such as salt concentration, pH and temperature are calculated using an extended fast multipole method in combination with the boundary element formulation. Overall, the calculated B2 are well correlated with the experimental observations for various solution conditions. In combination with our previous work on the binding affinity calculations it is reasonable to expect that our residue level model can be used as a reliable model to describe protein-protein interaction in solutions
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