Ligand binding by antibody IgE Lb4: assessment of binding site preferences using microcalorimetry, docking, and free energy simulations

Toward the Ultimate Limit of Analyte Detection, in Graphene-Based Field-Effect Transistors

The ultimate sensitivity of field-effect-transistor (FET)-based devices for ionic species detection is of great interest, given that such devices are capable of monitoring single-electron-level modulations. It is shown here, from both theoretical and experimental perspectives, that for such ultimate limits to be approached the thermodynamic as well as kinetic characteristics of the (FET surface)-(linker)-(ion-receptor) ensemble must be considered. The sensitivity was probed in terms of optimal packing of the ensemble, through a minimal charge state/capacitance point of view and atomic force microscopy. Through the fine-tuning of the linker and receptor interaction with the sensing surface, a record limit of detection as well as specificity in the femtomolar range, orders of magnitude better than previously obtained and in excellent accord with prediction, was observed.

Mcg light chain dimer as a model system for ligand design: a docking study

Mcg light chain dimer has been extensively studied by crystallography and peptide binding studies to investigate its peptide cross-reactivity as well as to use it as a model system for designing space filling peptide ligands. Here we extend these investigations by utilizing automated docking. Mcg light chain dimer is an ideal model system for such study due to the availability of experimental data for both the native structure and the 14 complexes with various peptide ligands. We show the ability of the docking approach to reproduce the experimental structures and discuss the limitations associated with such outcomes. We demonstrate the usefulness of the docking approach in generating structural information otherwise not available from the experiment.

Efficient docking of peptides to proteins without prior knowledge of the binding site

Reliability in docking of ligand molecules to proteins or other targets is an important challenge for molecular modeling. Applications of the docking technique include not only prediction of the binding mode of novel drugs, but also other problems like the study of protein-protein interactions. Here we present a study on the reliability of the results obtained with the popular AutoDock program. We have performed systematical studies to test the ability of AutoDock to reproduce eight different protein/ligand complexes for which the structure was known, without prior knowledge of the binding site. More specifically, we look at factors influencing the accuracy of the final structure, such as the number of torsional degrees of freedom in the ligand. We conclude that the Autodock program package is able to select the correct complexes based on the energy without prior knowledge of the binding site. We named this application blind docking, as the docking algorithm is not able to "see" the binding site but can still find it. The success of blind docking represents an important finding in the era of structural genomics.

Biomolecular simulations: recent developments in force fields, simulations of enzyme catalysis, protein-ligand, protein-protein, and protein-nucleic acid noncovalent interactions

Computer modeling has been developed and widely applied in studying molecules of biological interest. The force field is the cornerstone of computer simulations, and many force fields have been developed and successfully applied in these simulations. Two interesting areas are (a) studying enzyme catalytic mechanisms using a combination of quantum mechanics and molecular mechanics, and (b) studying macromolecular dynamics and interactions using molecular dynamics (MD) and free energy (FE) calculation methods. Enzyme catalysis involves forming and breaking of covalent bonds and requires the use of quantum mechanics. Noncovalent interactions appear ubiquitously in biology, but here we confine ourselves to review only noncovalent interactions between protein and protein, protein and ligand, and protein and nucleic acids.

Docking of combinatorial peptide libraries into a broadly cross-reactive human IgM

A monoclonal IgM cryoglobulin with diverse binding behavior was isolated from a patient (Mez) with Waldenström's macroglobulinemia. It gave very high titers in the binding of combinatorially synthesized libraries of peptides ranging in size from two to eight residues. The crystal structure of Mez Fv revealed that the binding site was divided into two cavities of unequal volumes with dimensions and chemical properties that were compatible with the binding of peptides. Access to this unique combination of structural information and peptide binding data led us to carry out Mez-peptide docking simulations to gain insight into the Mez binding propensities. In the present article, the results for docking of five peptide libraries are combined with discussions of the methods and approximations involved in the docking process. We analyze the origins of peptide binding affinity for Mez IgM in terms of its cross-reactivity and its structural preferences.

Automated docking of ligands to antibodies: methods and applications

Many approaches to studying protein-ligand interactions by computational docking are currently available. Given the structures of a protein and a ligand, the ultimate goal of all docking methods is to predict the structure of the resulting complex. This requires a suitable representation of molecular structures and properties, search algorithms to efficiently scan the configuration space for favorable interaction geometries, and accurate scoring functions to evaluate and rank the generated orientations. For many of the available methods, tests on experimentally known antibody-antigen or antibody-hapten complexes have appeared in the literature. In addition, some of them have been used in predictive studies on antibody-ligand interactions to provide structural insights where adequate experimental information is missing. The AutoDock program is presented as example of a method for flexibly docking ligands to antibodies. Applying parameters of the second-generation AMBER force field, three antibody-hapten complexes (AN02, DB3, NC6.8) are used as new test cases to analyze the ability of the method to reproduce experimental findings. The X-ray structures could be reconstituted and the corresponding solutions were ranked with best energy score in all cases. Docking to the free instead of the complexed NC6.8 structure indicated the limits of the rigid protein treatment, although fairly good guesses about the location of the binding site and the contact residues could still be obtained if conformational flexibility was allowed at least in the ligand.