Predicting Ligand Binding Sites on Protein Surfaces by 3-Dimensional Probability Density Distributions of Interacting Atoms.

Predicting ligand binding sites (LBSs) on protein structures, which are obtained either from experimental or computational methods, is a useful first step in functional annotation or structure-based drug design for the protein structures. In this work, the structure-based machine learning algorithm ISMBLab-LIG was developed to predict LBSs on protein surfaces with input attributes derived from the three-dimensional probability density maps of interacting atoms, which were reconstructed on the query protein surfaces and were relatively insensitive to local conformational variations of the tentative ligand binding sites. The prediction accuracy of the ISMBLab-LIG predictors is comparable to that of the best LBS predictors benchmarked on several well-established testing datasets. More importantly, the ISMBLab-LIG algorithm has substantial tolerance to the prediction uncertainties of computationally derived protein structure models. As such, the method is particularly useful for predicting LBSs not only on experimental protein structures without known LBS templates in the database but also on computationally predicted model protein structures with structural uncertainties in the tentative ligand binding sites.

Molecular modeling to investigate the binding of Congo red toward GNNQQNY protofibril and in silico virtual screening for the identification of new aggregation inhibitors.

Understanding the nature of the recognition between amyloid protofibrils and dye molecules at the molecular level is essential to improving instructive guides for designing novel molecular probes or new inhibitors. However, the atomic details of the binding between dyes and amyloid fibrils are still not fully understood. In this study, molecular docking, consensus scoring, molecular dynamics (MD), and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) analyses were integrated to investigate the binding between Congo red (CR) and the GNNQQNY protofibril from yeast prion protein Sup35 and to further evaluate their binding stabilities and affinities. Our results reveal that there are four CR binding sites located on GNNQQNY protofibril surface. These four CR binding sites adopt dual binding modes by which CR binding with its long axis parallel and perpendicular to the long axis of the protofibril. In addition, CR was also found to bind to the edge of the protofibril via hydrophobic/aromatic and hydrogen-bonding interactions, which is inferred as the possible inhibition mechanism to prevent the elongation of the protofibril from the addition of incoming peptides. Virtual screening from National Cancer Institute (NCI) database obtained three hit compounds with higher binding affinity than CR to the edge of the protofibril due to the fact that the central parts of these compounds are able to form additional hydrogen bonds with the protofibril. The results of the study could be useful for the development of new molecular probes or inhibitors for clinical applications.

Homology modeling and dynamics study of aureusidin synthase--an important enzyme in aurone biosynthesis of snapdragon flower.

Aurones, a class of plant flavonoids, provide bright yellow color on some important ornamental flowers, such as cosmos, coreopsis, and snapdragon (Antirrhinum majus). Recently, it has been elucidated that aureusidin synthase (AUS), a homolog of plant polyphenol oxidase (PPO), plays a key role in the yellow coloration of snapdragon flowers. In addition, it has been shown that AUS is a chalcone-specific PPO specialized for aurone biosynthesis. AUS gene has been successfully demonstrated as an attractive tool to engineer yellow flowers in blue flowers. Despite these biological studies, the structural basis for the specificity of substrate interactions of AUS remains elusive. In this study, we performed homology modeling of AUS using Grenache PPO and Sweet potato catechol oxidase (CO). An AUS-inhibitor was then developed from the initial homology model based on the CO and subsequently validated. We performed a thorough study between AUS and PTU inhibitor by means of interaction energy, which indicated the most important residues in the active site that are highly conserved. Analysis of the molecular dynamics simulations of the apo enzyme and ligand-bound complex showed that complex is relatively stable than apo and the active sites of both systems are flexible. The results from this study provide very helpful information to understand the structure-function relationships of AUS.

Investigation of cation-π interactions in sugar-binding proteins.

Cation-π interaction is a non-covalent binding force that plays a significant role in protein stability and drug-receptor interactions. In this work, we have investigated the structural role of cation-π interactions in sugar-binding proteins (SBPs). We observed 212 cation-π interactions in 53 proteins out of 59 SBPs in dataset. There is an average one energetically significant cation-π interaction for every 66 residues in SBPs. In addition, Arg is highly preferred to form cation-π interactions, and the average energy of Arg-Trp is high among six pairs. Long-range interactions are predominant in the analyzed cation-π interactions. Comparatively, all interaction pairs favor to accommodate in strand conformations. The analysis of solvent accessible area indicates that most of the aromatic residues are found on buried or partially buried whereas cationic residues were found mostly on the exposed regions of protein. The cation-π interactions forming residues were found that around 43% of cation-π residues had highly conserved with the conservation score ≥6. Almost cationic and π-residues equally share in the stabilization center. Sugar-binding site analysis in available complexes showed that the frequency of Trp and Arg is high, suggesting the potential role of these two residues in the interactions between proteins and sugar molecules. Our observations in this study could help to further understand the structural stability of SBPs.