PKAD: a database of experimentally measured pKa values of ionizable groups in proteins.

Ionizable residues play key roles in many biological phenomena including protein folding, enzyme catalysis and binding. We present PKAD, a database of experimentally measured pKas of protein residues reported in the literature or taken from existing databases. The database contains pKa data for 1350 residues in 157 wild-type proteins and for 232 residues in 45 mutant proteins. Most of these values are for Asp, Glu, His and Lys amino acids. The database is available as downloadable file as well as a web server (http://compbio.clemson.edu/pkad). The PKAD database can be used as a benchmarking source for development and improvement of pKa's prediction methods. The web server provides additional information taken from the corresponding structures and amino acid sequences, which allows for easy search and grouping of the experimental pKas according to various biophysical characteristics, amino acid type and others.

DelPhiPKa: Including salt in the calculations and enabling polar residues to titrate.

DelPhiPKa is a widely used and unique approach to compute pKa 's of ionizable groups that does not require molecular surface to be defined. Instead, it uses smooth Gaussian-based dielectric function to treat computational space via Poisson-Boltzmann equation (PBE). Here, we report an expansion of DelPhiPKa functionality to enable inclusion of salt in the modeling protocol. The method considers the salt mobile ions in solvent phase without defining solute-solvent boundary. Instead, the ions are penalized to enter solute interior via a desolvation penalty term in the Boltzmann factor in the framework of PBE. Hence, the concentration of ions near the protein is balanced by the desolvation penalty and electrostatic interactions. The study reveals that correlation between experimental and calculated pKa 's is improved significantly by taking into consideration the presence of salt. Furthermore, it is demonstrated that DelphiPKa reproduces the salt sensitivity of experimentally measured pKa 's. Another new development of DelPhiPKa allows for computing the pKa 's of polar residues such as cysteine, serine, threonine and tyrosine. With this regard, DelPhiPKa is benchmarked against experimentally measured cysteine and tyrosine pKa 's and for cysteine it is shown to outperform other existing methods (DelPhiPKa RMSD of 1.73 vs RMSD between 2.40 and 4.72 obtained by other existing pKa prediction methods).

Predicting protein-DNA binding free energy change upon missense mutations using modified MM/PBSA approach: SAMPDI webserver.

Motivation: Protein-DNA interactions are essential for regulating many cellular processes, such as transcription, replication, recombination and translation. Amino acid mutations occurring in DNA-binding proteins have profound effects on protein-DNA binding and are linked with many diseases. Hence, accurate and fast predictions of the effects of mutations on protein-DNA binding affinity are essential for understanding disease-causing mechanisms and guiding plausible treatments. Results: Here we report a new method Single Amino acid Mutation binding free energy change of Protein-DNA Interaction (SAMPDI). The method utilizes modified Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) approach along with an additional set of knowledge-based terms delivered from investigations of the physicochemical properties of protein-DNA complexes. The method is benchmarked against experimentally determined binding free energy changes caused by 105 mutations in 13 proteins (compiled ProNIT database and data from recent references), and results in correlation coefficient of 0.72. Availability and implementation: http://compbio.clemson.edu/SAMPDI. Contact: ealexov@clemson.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

DelPhiForce web server: electrostatic forces and energy calculations and visualization.

SUMMARY: Electrostatic force is an essential component of the total force acting between atoms and macromolecules. Therefore, accurate calculations of electrostatic forces are crucial for revealing the mechanisms of many biological processes. We developed a DelPhiForce web server to calculate and visualize the electrostatic forces at molecular level. DelPhiForce web server enables modeling of electrostatic forces on individual atoms, residues, domains and molecules, and generates an output that can be visualized by VMD software. Here we demonstrate the usage of the server for various biological problems including protein-cofactor, domain-domain, protein-protein, protein-DNA and protein-RNA interactions. AVAILABILITY AND IMPLEMENTATION: The DelPhiForce web server is available at: http://compbio.clemson.edu/delphi-force. CONTACT: delphi@clemson.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.