Prediction of Water Distributions and Displacement at Protein-Ligand Interfaces.

The retention and displacement of water molecules during formation of ligand-protein interfaces play a major role in determining ligand binding. Understanding these effects requires a method for positioning of water molecules in the bound and unbound proteins and for defining water displacement upon ligand binding. We describe an algorithm for water placement and a calculation of ligand-driven water displacement in >9000 protein-ligand complexes. The algorithm predicts approximately 38% of experimental water positions within 1.0 Å and about 83% within 1.5 Å. We further show that the predicted water molecules can complete water networks not detected in crystallographic structures of the protein-ligand complexes. The algorithm was also applied to solvation of the corresponding unbound proteins, and this allowed calculation of water displacement upon ligand binding based on differences in the water network between the bound and unbound structures. We illustrate use of this approach through comparison of water displacement by structurally related ligands at the same binding site. This method for evaluation of water displacement upon ligand binding may be of value for prediction of the effects of ligand modification in drug design.

Modeling of the water network at protein-RNA interfaces.

Water plays an important role in the mediation of biomolecular interactions. Thus, accurate prediction and evaluation of water-mediated interactions is an important element in the computational design of interfaces involving proteins, RNA, and DNA. Here, we use an algorithm (WATGEN) to predict the locations of interfacial water molecules for a data set of 224 protein-RNA interfaces. The accuracy of the prediction is validated against water molecules present in the X-ray structures of 105 of these complexes. The complexity of the water networks is deconvoluted through definition of the characteristics of each water molecule based on its bridging properties between the protein and RNA and on its depth in the interface with respect to the bulk solvent. This approach has the potential for scoring the water network for incorporation into the computational design of protein-RNA complexes.

Similarity of protein-RNA interfaces based on motif analysis.

We have developed a method for determination of the similarity of pairs of protein-RNA complexes, which we refer to as SIMA (Similarity by Identity and Motif Alignment). The key element in the SIMA method is the description of the protein-RNA interface in terms of motifs (salt bridges, aromatic stacking interactions, nonaromatic stacks, hydrophobic interactions, and hydrogen-bonded motifs), in addition to single hydrogen bonds and van der Waals contacts. Based on a pairwise scoring function combining motif alignment with identity of the protein and RNA sequences, we define a SIMA score for any pair of protein-RNA complexes. A positive score indicates similarity between the complexes. We used the SIMA method to identify 284 nonredundant binary protein-RNA complexes out of 776 such complexes in 382 nonribosomal protein-RNA structure files obtained from the RCSB database. SIMA allows rapid and quantitative comparison of protein-RNA interfaces and may be useful for interface classification with potential functional and evolutionary implications.

Incorporation of zebularine from its 2'-deoxyribonucleoside triphosphate derivative and activity as a template-coding nucleobase.

Zebularine (1-(beta-D-ribofuranosyl)-1,2-dihydropyrimidin-2-one) was studied as both a 2 '-deoxyribosyl 5 '-triphosphate derivative and as a template incorporated into an oligonucleotide. Using a novel pyrosequencing assay, zebularine acted as cytosine analog and was incorporated into DNA with a template pairing profile most similar to cytosine, pairing with greatest efficiency opposite guanine in the template strand. Guanine was incorporated with greater affinity than adenine opposite a zebularine in the template strand. Computer modeling of base-pairing structures supported a better fit of zebularine opposite guanine than adenine. Zebularine acts as a cytosine analog, which supports its activity as an inhibitor of cytosine methyltransferase.

Computer Modeling of Spin Labels: NASNOX, PRONOX, and ALLNOX.

Measurement of distances between spin labels using electron paramagnetic resonance with the double electron-electron resonance (DEER) technique is an important method for evaluation of biomolecular structures. Computation of interlabel distances is of value for experimental planning, validation of known structures using DEER-measured distances, and determination of theoretical data for comparison with experiment. This requires steps of building labels at two defined sites on proteins, DNA or RNA; calculation of allowable label conformers based on rotation around torsional angles; computation of pairwise interlabel distances on a per conformer basis; and calculation of an average distance between the two label ensembles. We have described and validated two programs for this purpose: NASNOX, which permits computation of distances between R5 labels on DNA or RNA; and PRONOX, which similarly computes distances between R1 labels on proteins. However, these programs are limited to a specific single label and single target types. Therefore, we have developed a program, which we refer to as ALLNOX (Addition of Labels and Linkers), which permits addition of any label to any site on any target. The main principle in the program is to break the molecular system into a "label," a "linker," and a "target." The user can upload a "label" with any chemistry, define a "linker" based on a SMILES-like string, and then define the "target" site. The flexibility of ALLNOX facilitates theoretical evaluation of labels prior to synthesis and accommodates evaluation of experimental data in biochemical complexes containing multiple molecular types.

Computation of nitroxide-nitroxide distances in spin-labeled DNA duplexes.

Nanometer distances in nucleic acids can be measured by EPR using two 1-oxyl-2,2,5,5-tetramethylpyrroline radicals, with each label attached via a methylene group to a phosphorothioate-substituted backbone position as one of two phosphorothioate diastereomers (R(P) and S(P)). Correlating the internitroxide distance to the geometry of the parent molecule requires computational analysis of the label conformers. Here, we report sixteen 4-ns MD simulations on a DNA duplex d(CTACTGCTTTAG) .d(CTAAAGCAGTAG) with label pairs at C7/C19, T5/A17, and T2/T14, respectively. For each labeled duplex, four simulations were performed with S(P)/S(P), R(P)/R(P), S(P)/R(P), and R(P)/S(P) labels, with initial all trans label conformations. Another set of four simulations was performed for the 7/19-labeled duplex using a different label starting conformation. The average internitroxide distance r(MD) was within 0.2 A for the two sets of simulations for the 7/19-labeled duplex, indicating sufficient sampling of conformational space. For all three labeled duplexes studied, r(MD) agreed with experimental values, as well as with average distances obtained from an efficient conformer search algorithm (NASNOX). The simulations also showed that the labels have conformational preferences determined by the linker chemistry and label-DNA interactions. These results establish computational algorithms that allow use of the 1-oxyl-2,2,5,5-tetramethylpyrroline label for mapping global structures of nucleic acids.