Jens Erik Nielsen

Continuum solvation models, such as Poisson-Boltzmann and Generalized Born methods, have become increasingly popular tools for investigating the influence of electrostatics on biomolecular structure, energetics and dynamics. However, the use of such methods requires accurate and complete structural data as well as force field parameters such as atomic charges and radii. Unfortunately, the limiting step in continuum electrostatics calculations is often the addition of missing atomic coordinates to molecular structures from the Protein Data Bank and the assignment of parameters to biomolecular structures. To address this problem, we have developed the PDB2PQR web service (http://agave.wustl.edu/pdb2pqr/). This server automates many of the common tasks of preparing structures for continuum electrostatics calculations, including adding a limited number of missing heavy atoms to biomolecular structures, estimating titration states and protonating biomolecules in a manner consistent with favorable hydrogen bonding, assigning charge and radius parameters from a variety of force fields, and finally generating 'PQR' output compatible with several popular computational biology packages. This service is intended to facilitate the setup and execution of electrostatics calculations for both experts and non-experts and thereby broaden the accessibility to the biological community of continuum electrostatics analyses of biomolecular systems.

Abstract The Adaptive Poisson–Boltzmann Solver (APBS) software was developed to solve the equations of continuum electrostatics for large biomolecular assemblages that have provided impact in the study of a broad range of chemical, biological, and biomedical applications. APBS addresses the 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 article, 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 K a values, and an improved web‐based visualization tool for viewing electrostatics.

Real-world observable physical and chemical characteristics are increasingly being calculated from the 3D structures of biomolecules. Methods for calculating pK(a) values, binding constants of ligands, and changes in protein stability are readily available, but often the limiting step in computational biology is the conversion of PDB structures into formats ready for use with biomolecular simulation software. The continued sophistication and integration of biomolecular simulation methods for systems- and genome-wide studies requires a fast, robust, physically realistic and standardized protocol for preparing macromolecular structures for biophysical algorithms. As described previously, the PDB2PQR web server addresses this need for electrostatic field calculations (Dolinsky et al., Nucleic Acids Research, 32, W665-W667, 2004). Here we report the significantly expanded PDB2PQR that includes the following features: robust standalone command line support, improved pK(a) estimation via the PROPKA framework, ligand parameterization via PEOE_PB charge methodology, expanded set of force fields and easily incorporated user-defined parameters via XML input files, and improvement of atom addition and optimization code. These features are available through a new web interface (http://pdb2pqr.sourceforge.net/), which offers users a wide range of options for PDB file conversion, modification and parameterization.

Hypoxia is a feature of the microenvironment of a growing tumor. The transcription factor NFκB is activated in hypoxia, an event that has significant implications for tumor progression. Here, we demonstrate that hypoxia activates NFκB through a pathway involving activation of IκB kinase-β (IKKβ) leading to phosphorylation-dependent degradation of IκBα and liberation of NFκB. Furthermore, through increasing the pool and/or activation potential of IKKβ, hypoxia amplifies cellular sensitivity to stimulation with TNFα. Within its activation loop, IKKβ contains an evolutionarily conserved LxxLAP consensus motif for hydroxylation by prolyl hydroxylases (PHDs). Mimicking hypoxia by treatment of cells with siRNA against PHD-1 or PHD-2 or the pan-prolyl hydroxylase inhibitor DMOG results in NFκB activation. Conversely, overexpression of PHD-1 decreases cytokine-stimulated NFκB reporter activity, further suggesting a repressive role for PHD-1 in controlling the activity of NFκB. Hypoxia increases both the expression and activity of IKKβ, and site-directed mutagenesis of the proline residue (P191A) of the putative IKKβ hydroxylation site results in a loss of hypoxic inducibility. Thus, we hypothesize that hypoxia releases repression of NFκB activity through decreased PHD-dependent hydroxylation of IKKβ, an event that may contribute to tumor development and progression through amplification of tumorigenic signaling pathways.