Pcetk: A pDynamo-based Toolkit for Protonation State Calculations in Proteins

pDynamo3 Molecular Modeling and Simulation Program

pDynamo3 is the first formal version of the Dynamo molecular modeling and simulation library that is written in Python 3. It follows from the previous pDynamo versions written in Python 2, the first of which was released in 2007. Both pDynamo and its predecessor, fDynamo, were designed with the aim of providing easy-to-use and flexible frameworks for performing molecular simulations at an atomistic level with a special emphasis on those employing hybrid quantum chemical and molecular mechanical potential methods. Although the use of pDynamo3 is quite similar to that of pDynamo2, it has added significant new capability and also undergone extensive restructuring that will make it much easier to extend with new functionality. The pDynamo3 code is issued under the GNU general public license at https://github.com/pdynamo/pDynamo3 with additional information on the pDynamo website https:www.pdynamo.org.

Determination of the protonation preferences of bilin pigments in cryptophyte antenna complexes

The light-harvesting mechanisms of cryptophyte antenna complexes have attracted considerable attention due to their ability to exhibit maximal photosynthetic activity under very low-light conditions and to display several colors, as well as the observation of vibronic coherent features in their two-dimensional electronic spectra. However, detailed investigations on the interplay between the protein environment and their light-harvesting properties are hampered by the uncertainty related to the protonation state of the underlying bilin pigments. Here we study the protonation preferences of four types of bilin pigments including 15,16-dihydrobiliverdin (DBV), phycoerythrobilin (PEB), phycocyanobilin (PCB) and mesobiliverdin (MBV), which are found in phycoerythrin PE545 and phycocyanin PC577, PC612, PC630 and PC645 complexes. We apply quantum chemical calculations coupled to continuum solvation calculations to predict the intrinsic acidity of bilins in aqueous solution, and then combine molecular dynamics simulations with empirical pKa estimates to investigate the impact of the local protein environment on the acidity of the pigments. We also report measurements of the absorption spectra of the five complexes in a wide range of pH in order to validate our simulations and investigate possible changes in the light harvesting properties of the complexes in the range of physiological pH found in the lumen (pH ∼ 5-7). The results suggest a pKa > 7 for DBV and MBV pigments in the α polypeptide chains of PE545 and PC630/PC645 complexes, which are not coordinated to a negatively charged amino acid. For the other PEB, DBV and PCB pigments, which interact with a Glu or Asp side chain, higher pKa values (pKa > 8) are estimated. Overall, the results support a preferential population of the fully protonated state for bilins in cryptophyte complexes under physiological conditions regardless of the specific type of pigment and local protein environment.

Norovirus RNA-dependent RNA polymerase: A computational study of metal-binding preferences

Norovirus (NV) RNA-dependent RNA polymerase (RdRP) is essential for replicating the genome of the virus, which makes this enzyme a key target for the development of antiviral agents against NV gastroenteritis. In this work, a complex of NV RdRP bound to manganese ions and an RNA primer-template duplex was investigated using X-ray crystallography and hybrid quantum chemical/molecular mechanical simulations. Experimentally, the complex crystallized in a tetragonal crystal form. The nature of the primer/template duplex binding in the resulting structure indicates that the complex is a closed back-tracked state of the enzyme, in which the 3'-end of the primer occupies the position expected for the post-incorporated nucleotide before translocation. Computationally, it is found that the complex can accept a range of divalent metal cations without marked distortions in the active site structure. The highest binding energy is for copper, followed closely by manganese and iron, and then by zinc, nickel, and cobalt. Proteins 2017; 85:1435-1445. © 2017 Wiley Periodicals, Inc.