Ligand Binding Site Detection b Local Structure Alignment and Its Performance Complementarity

Accurate determination of potential ligand binding sites (BS) is a key step for protein function characterization and structure-based drug design. Despite promising results of template-based BS prediction methods using global structure alignment (GSA), there is a room to improve the performance by properly incorporating local structure alignment (LSA) because BS are local structures and often similar for proteins with dissimilar global folds. We present a template-based ligand BS prediction method using G-LoSA, our LSA tool. A large benchmark set validation shows that G-LoSA predicts drug-like ligands’ positions in single-chain protein targets more precisely than TM-align, a GSA-based method, while the overall success rate of TM-align is better. G-LoSA is particularly efficient for accurate detection of local structures conserved across proteins with diverse global topologies. Recognizing the performance complementarity of G-LoSA to TM-align and a non-template geometry-based method, fpocket, a robust consensus scoring method, CMCS-BSP (Complementary Methods and Consensus Scoring for ligand Binding Site Prediction), is developed and shows improvement on prediction accuracy. The G-LoSA source code is freely available at http://im.bioinformatics.ku.edu/GLoSA

Identification of Ligand Templates using Local Structure Alignment for Structure-based Drug Design

With a rapid increase in the number of high-resolution protein-ligand structures, the known protein-ligand structures can be used to gain insight into ligand-binding modes in a target protein. Based on the fact that the structurally similar binding sites share information about their ligands, we have developed a local structure alignment tool, G-LoSA (Graph-based Local Structure Alignment). In G-LoSA, the known protein-ligand binding-site structure library is searched to detect binding-site structures with similar geometry and physicochemical properties to a query binding-site structure regardless of sequence continuity and protein fold. Then, the ligands in the identified complexes are used as templates (i.e., template ligands) to predict/design a ligand for the target protein. The performance of G-LoSA is validated against 76 benchmark targets from the Astex diverse set. Using the currently available protein-ligand structure library, G-LoSA is able to identify a single template ligand (from a non-homologous protein complex) that is highly similar to the target ligand in more than half of the benchmark targets. In addition, our benchmark analyses show that an assembly of structural fragments from multiple template ligands with partial similarity to the target ligand can be used to design novel ligand structures specific to the target protein. This study clearly indicates that a template-based ligand modeling has potential for de novo ligand design and can be a complementary approach to the receptor structure based methods

Effects of N-glycosylation on protein conformation and dynamics: Protein Data Bank analysis and molecular dynamics simulation study

N-linked glycosylation is one of the most important, chemically complex, and ubiquitous post-translational modifications in all eukaryotes. The N-glycans that are covalently linked to proteins are involved in numerous biological processes. There is considerable interest in developments of general approaches to predict the structural consequences of site-specific glycosylation and to understand how these effects can be exploited in protein design with advantageous properties. In this study, the impacts of N-glycans on protein structure and dynamics are systematically investigated using an integrated computational approach of the Protein Data Bank structure analysis and atomistic molecular dynamics simulations of glycosylated and deglycosylated proteins. Our study reveals that N-glycosylation does not induce significant changes in protein structure, but decreases protein dynamics, likely leading to an increase in protein stability. Overall, these results suggest not only a common role of glycosylation in proteins, but also a need for certain proteins to be properly glycosylated to gain their intrinsic dynamic properties.This work was supported by NIH U54GM087519 and XSEDE MCB070009. We gratefully acknowledge Sunhwan Jo for helping us to use Glycan Reader. Anton computer time was provided by the National Center for Multiscale Modeling of Biological Systems (MMBioS) through Grant P41GM103712-S1 from the National Institutes of Health and the Pittsburgh Supercomputing Center (PSC). The Anton machine at PSC was generously made available by D.E. Shaw Research

Restricted N-glycan Conformational Space in the PDB and Its Implication in Glycan Structure Modeling

A grant from the One-University Open Access Fund at the University of Kansas was used to defray the author’s publication fees in this Open Access journal. The Open Access Fund, administered by librarians from the KU, KU Law, and KUMC libraries, is made possible by contributions from the offices of KU Provost, KU Vice Chancellor for Research & Graduate Studies, and KUMC Vice Chancellor for Research. For more information about the Open Access Fund, please see http://library.kumc.edu/authors-fund.xml.Understanding glycan structure and dynamics is central to understanding protein-carbohydrate recognition and its role in protein-protein interactions. Given the difficulties in obtaining the glycan's crystal structure in glycoconjugates due to its flexibility and heterogeneity, computational modeling could play an important role in providing glycosylated protein structure models. To address if glycan structures available in the PDB can be used as templates or fragments for glycan modeling, we present a survey of the N-glycan structures of 35 different sequences in the PDB. Our statistical analysis shows that the N-glycan structures found on homologous glycoproteins are significantly conserved compared to the random background, suggesting that N-glycan chains can be confidently modeled with template glycan structures whose parent glycoproteins share sequence similarity. On the other hand, N-glycan structures found on non-homologous glycoproteins do not show significant global structural similarity. Nonetheless, the internal substructures of these N-glycans, particularly, the substructures that are closer to the protein, show significantly similar structures, suggesting that such substructures can be used as fragments in glycan modeling. Increased interactions with protein might be responsible for the restricted conformational space of N-glycan chains. Our results suggest that structure prediction/modeling of N-glycans of glycoconjugates using structure database could be effective and different modeling approaches would be needed depending on the availability of template structures

E-Learning Nutrition Education Program for Low-Income Adults: Perspectives of Key Stakeholders

Through focus group interviews, we examined the perceptions of Extension peer nutrition educators (n = 6) and low-income adults (n = 8) regarding the feasibility of an e-learning nutrition education program, titled Food eTalk, tailored to Georgians eligible for Supplemental Nutrition Assistance Program Education (SNAP-Ed). Findings indicated two themes: (a) Participants have regular smartphone-based Internet access, and nutrition education e-learning programs should be designed to match typical smartphone use patterns and (b) recommendations to increase Food eTalk engagement involve carefully selected content and consideration to mandate SNAP-Ed participation. These findings are informing user-centered development of Food eTalk and may be of use to others creating such programs

Application of Binding Free Energy Calculations to Prediction of Binding Modes and Affinities of MDM2 and MDMX Inhibitors

Molecular docking is widely used to obtain binding modes and binding affinities of a molecule to a given target protein. Despite considerable efforts, however, prediction of both properties by docking remains challenging mainly due to protein’s structural flexibility and inaccuracy of scoring functions. Here, an integrated approach has been developed to improve the accuracy of binding mode and affinity prediction, and tested for small molecule MDM2 and MDMX antagonists. In this approach, initial candidate models selected from docking are subjected to equilibration MD simulations to further filter the models. Free energy perturbation molecular dynamics (FEP/MD) simulations are then applied to the filtered ligand models to enhance the ability in predicting the near-native ligand conformation. The calculated binding free energies for MDM2 complexes are overestimated compared to experimental measurements mainly due to the difficulties in sampling highly flexible apo-MDM2. Nonetheless, the FEP/MD binding free energy calculations are more promising for discriminating binders from nonbinders than docking scores. In particular, the comparison between the MDM2 and MDMX results suggests that apo-MDMX has lower flexibility than apo-MDM2. In addition, the FEP/MD calculations provide detailed information on the different energetic contributions to ligand binding, leading to a better understanding of the sensitivity and specificity of protein-ligand interactions

CHARMM-GUI Ligand Binder for Absolute Binding Free Energy Calculations and Its Application

Advanced free energy perturbation molecular dynamics (FEP/MD) simulation methods are available to accurately calculate absolute binding free energies of protein-ligand complexes. However, these methods rely on several sophisticated command scripts implementing various biasing energy restraints to enhance the convergence of the FEP/MD calculations, which must all be handled properly to yield correct results. Here, we present a user-friendly web interface, CHARMM-GUI Ligand Binder (http://www.charmm-gui.org/input/gbinding), to provide standardized CHARMM input files for calculations of absolute binding free energies using the FEP/MD simulations. A number of features are implemented to conveniently setup the FEP/MD simulations in highly customizable manners, thereby permitting an accelerated throughput of this important class of computations while decreasing the possibility of human errors. The interface and a series of input files generated by the interface are tested with illustrative calculations of absolute binding free energies of three non-polar aromatic ligands to the L99A mutant of T4 lysozyme and three FK506-related ligands to FKBP12. Statistical errors within individual calculations are found to be small (~1 kcal/mol), and the calculated binding free energies generally agree well with the experimental measurements and the previous computational studies (within ~2 kcal/mol). CHARMM-GUI Ligand Binder provides a convenient and reliable way to setup the ligand binding free energy calculations and can be applicable to pharmaceutically important protein-ligand systems