The use of the electronegativity equalization principle to study charge distributions in enzymes: application to dipeptides

In silico characterization of nanoparticles

Nanoparticles (NPs) make for intriguing heterogeneous catalysts due to their large active surface area and excellent and often size-dependent catalytic properties that emerge from a multitude of chemically different surface reaction sites. NP catalysts are, in principle, also highly tunable: even small changes to the NP size or surface facet composition, doping with heteroatoms, or changes of the supporting material can significantly alter their physicochemical properties. Because synthesis of size- and shape-controlled NP catalysts is challenging, the ability to computationally predict the most favorable NP structures for a catalytic reaction of interest is an in-demand skill that can help accelerate and streamline the material optimization process. Fundamentally, simulations of NP model systems present unique challenges to computational scientists. Not only must considerable methodological hurdles be overcome in performing calculations with hundreds to thousands of atoms while retaining appropriate accuracy to be able to probe the desired properties. Also, the data generated by simulations of NPs are typically more complex than data from simulations of, for example, single crystal surface models, and therefore often require different data analysis strategies. To this end, the present work aims to review analytical methods and data analysis strategies that have proven useful in extracting thermodynamic trends from NP simulations.

Electronic properties of amino acids and nucleobases: similarity classes and pairing principles from chemical reactivity indices

We present a new classification scheme for amino acids and nucleobases based on the electronic properties of the individual molecules. Using chemical reactivity indices such as electronegativity, electrophilicity, and chemical hardness, we can identify similarities and differences between each class of amino acids and nucleobases. Notable differences emerge in particular with regard to high, neutral or low electronegativity as well as different combinations of chemical hardness. Our approach allows us to relate these insights to the properties of the side groups in terms of a unique reference scheme. We further show that hydrophobic differences between amino acids are rather negligible in the context of electronic properties. Our classification scheme also rationalizes the occurrence of distinct stable nucleobase pairs and clearly emphasizes certain differences between individual molecules. The stability and abundant occurrence of Watson-Crick nucleobase pairs is further discussed in the context of the minimum electrophilicity principle.

A Group Electronegativity Equalization Scheme Including External Potential Effects

By calculating the electron affinity and ionization energy of different functional groups, CCSD electronegativity values are obtained, which implicitly account for the effect of the molecular environment. This latter is approximated using a chemically justified point charge model. On the basis of Sanderson's electronegativity equalization principle, this approach is shown to lead to reliable "group in molecule" electronegativities. Using a slight adjustment of the modeled environment and first-order principles, an electronegativity equalization scheme is obtained, which implicitly accounts for the major part of the external potential effect. This scheme can be applied in a predictive manner to estimate the charge transfer between two functional groups, without having to rely on cumbersome calibrations. A very satisfactory correlation is obtained between these charge transfers and those obtained from an ab initio calculation of the entire molecule.

Optimized and parallelized implementation of the electronegativity equalization method and the atom-bond electronegativity equalization method

The most common way to calculate charge distribution in a molecule is ab initio quantum mechanics (QM). Some faster alternatives to QM have also been developed, the so-called "equalization methods" EEM and ABEEM, which are based on DFT. We have implemented and optimized the EEM and ABEEM methods and created the EEM SOLVER and ABEEM SOLVER programs. It has been found that the most time-consuming part of equalization methods is the reduction of the matrix belonging to the equation system generated by the method. Therefore, for both methods this part was replaced by the parallel algorithm WIRS and implemented within the PVM environment. The parallelized versions of the programs EEM SOLVER and ABEEM SOLVER showed promising results, especially on a single computer with several processors (compact PVM). The implemented programs are available through the Web page http://ncbr.chemi.muni.cz/~n19n/eem_abeem.

‘Inductive' Charges on Atoms in Proteins: Comparative Docking with the Extended Steroid Benchmark Set and Discovery of a Novel SHBG Ligand

We have developed a novel iterative approach for calculation of partial charges in proteins within the framework of the 'molecular capacitance' model. The method operates by an effective 'inductive' electronegativity scale derived from a number of the conventional charge systems including CHARMM, AMBER, MMFF, OPLS, and PEOE among others. Our novel 'inductive' electronegativity equalization procedure allows rapid and conformation sensitive computation of adequate partial charges in proteins. Accuracy of the 'inductive' values was confirmed by their correlation with DFT-computed partial charges in common amino acids. A comparative docking study with an extended steroid data set not only illustrated the adequacy of 'inductive' protein charges but also demonstrated their superior performance compared to several conventional protein charging systems. Subsequent docking with 'inductive' charges resulted in identification of five potential leads as human Sex Hormone Binding Globulin (SHBG) ligands from a commercial library of natural compounds. When the selected substances were evaluated for their ability to bind SHBG in vitro, three of them displaced testosterone from the SHBG steroid-binding site, and with one compound this was achieved at micromolar concentrations.