Adam Mazur

ORIUM: optimized RDC-based Iterative and Unified Model-free analysis.

Residual dipolar couplings (RDCs) are NMR parameters that provide both structural and dynamic information concerning inter-nuclear vectors, such as N–HN and Cα–Hα bonds within the protein backbone. Two approaches for extracting this information from RDCs are the model free analysis (MFA) (Meiler et al. in J Am Chem Soc 123:6098–6107, 2001; Peti et al. in J Am Chem Soc 124:5822–5833, 2002) and the direct interpretation of dipolar couplings (DIDCs) (Tolman in J Am Chem Soc 124:12020–12030, 2002). Both methods have been incorporated into iterative schemes, namely the self-consistent RDC based MFA (SCRM) (Lakomek et al. in J Biomol NMR 41:139–155, 2008) and iterative DIDC (Yao et al. in J Phys Chem B 112:6045–6056, 2008), with the goal of removing the influence of structural noise in the MFA and DIDC formulations. Here, we report a new iterative procedure entitled Optimized RDC-based Iterative and Unified Model-free analysis (ORIUM). ORIUM unifies theoretical concepts developed in the MFA, SCRM, and DIDC methods to construct a computationally less demanding approach to determine these structural and dynamic parameters. In all schemes, dynamic averaging reduces the actual magnitude of the alignment tensors complicating the determination of the absolute values for the generalized order parameters. To readdress this scaling issue that has been previously investigated (Lakomek et al. in J Biomol NMR 41:139–155, 2008; Salmon et al. in Angew Chem Int Edit 48:4154–4157, 2009), a new method is presented using only RDC data to establish a lower bound on protein motion, bypassing the requirement of Lipari–Szabo order parameters. ORIUM and the new scaling procedure are applied to the proteins ubiquitin and the third immunoglobulin domain of protein G (GB3). Our results indicate good agreement with the SCRM and iterative DIDC approaches and signify the general applicability of ORIUM and the proposed scaling for the extraction of inter-nuclear vector structural and dynamic content.

A Combination of Spin Diffusion Methods for the Determination of Protein-Ligand Complex Structural Ensembles.

Structure-based drug design (SBDD) is a powerful and widely used approach to optimize affinity of drug candidates. With the recently introduced INPHARMA method, the binding mode of small molecules to their protein target can be characterized even if no spectroscopic information about the protein is known. Here, we show that the combination of the spin-diffusion-based NMR methods INPHARMA, trNOE, and STD results in an accurate scoring function for docking modes and therefore determination of protein-ligand complex structures. Applications are shown on the model system protein kinase A and the drug targets glycogen phosphorylase and soluble epoxide hydrolase (sEH). Multiplexing of several ligands improves the reliability of the scoring function further. The new score allows in the case of sEH detecting two binding modes of the ligand in its binding site, which was corroborated by X-ray analysis.

Enhanced β-turn conformational stability of tripeptides containing ΔPhe in cis over trans configuration

Conformations of three pairs of dehydropeptides with the opposite configuration of the ΔPhe residue, Boc-Gly-ΔZ/EPhe-Phe-p-NA (Z-p-NA and E-p-NA), Boc-Gly-ΔZ/EPhe-Phe-OMe (Z-OMe and E-OMe), and Boc-Gly-ΔZ/EPhe-Phe-OH (Z-OH and E-OH) were compared on the basis of CD and NMR studies in MeOH, TFE, and DMSO. The CD results were used as the additional input data for the NMR-based calculations of the detailed solution conformations of the peptides. It was found that Z-p-NA, E-p-NA, Z-OMe, and Z-OH adopt the β-turn conformations and E-OMe and E-OH are unordered. There are two overlapping type III β-turns in Z-p-NA, type II’ β-turn in E-p-NA, and type II β-turn in Z-OMe and Z-OH. The results obtained indicate that in the case of methyl esters and peptides with a free carboxyl group, ΔZPhe is a much stronger inducer of ordered conformations than ΔEPhe. It was also found that temperature coefficients of the amide protons are not reliable indicators of intramolecular hydrogen bonds donors in small peptides.

ShereKhan – Calculating exchange parameters in relaxation dispersion data from CPMG experiments

SUMMARY Dynamics governing the function of biomolecule is usually described as exchange processes and can be monitored at atomic resolution with nuclear magnetic resonance (NMR) relaxation dispersion data. Here, we present a new tool for the analysis of CPMG relaxation dispersion profiles (ShereKhan). The web interface to ShereKhan provides a user-friendly environment for the analysis. AVAILABILITY A stable version of ShereKhan, the web application and documentation are available at http://sherekhan.bionmr.org. CONTACT dole@nmr.mpibpc.mpg.de or mako@nmr.mpibpc.mpg.de.

On-the-Fly Integration of Data from a Spin-Diffusion-Based NMR Experiment into Protein-Ligand Docking.

INPHARMA (interligand nuclear Overhauser enhancement for pharmacophore mapping) determines the relative orientation of two competitive ligands in the protein binding pocket. It is based on the observation of interligand transferred NOEs mediated by spin diffusion through protons of the protein and is, therefore, sensitive to the specific interactions of each of the two ligands with the protein. We show how this information can be directly included into a protein-ligand docking program to guide the prediction of the complex structures. Agreement between the experimental and back-calculated spectra based on the full relaxation matrix approach is translated into a score contribution that is combined with the scoring function ChemPLP of our docking tool PLANTS. This combined score is then used to predict the poses of five weakly bound cAMP-dependent protein kinase (PKA) ligands. After optimizing the setup, which finally also included trNOE data and optimized protonation states, very good success rates were obtained for all combinations of three ligands. For one additional ligand, no conclusive results could be obtained due to the ambiguous electron density of the ligand in the X-ray structure, which does not disprove alternative ligand poses. The failures of the remaining ligand are caused by suboptimal locations of specific protein side chains. Therefore, side-chain flexibility should be included in an improved INPHARMA-PLANTS version. This will reduce the strong dependence on the used protein input structure leading to improved scores overall, not only for this last ligand.

N-glycan recognition by the cyanobacterial Oscillatoria aghardii lectin.

Invited Speaker .................................................................................................................................. 53 Poster Session .................................................................................................................................... 71 Late-Breaking .................................................................................................................................. 221 Author/Invited Speaker Index ............................................................................................................ 235

Guiding protein-ligand docking with different experimental NMR-data

Today’s scoring functions are one of the main reasons that state-of-the-art protein-ligand dockings fail in about 20 % to 40 % of the targets due to the sometimes severe approximations they make. However these approximations are necessary for performance reasons. One possibility to overcome these problems is the inclusion of additional, preferably experimental information in the docking process. Especially ligand-based NMR experiments that are far less demanding than the solution of the whole complex structure are helpful. Here we present the inclusion of three different types of NMR-data into the ChemPLP [1] scoring function of our docking tool PLANTS [2]. First, STD and intraligand trNOE spectra were used to obtain distant constraints between ligand and protein atoms. This approach proved beneficial for the docking of larger peptide ligands i. e. the epitope of MUC-1 glycoprotein to the SM3 antibody [3]. In the second part the usefulness of INPHARMA data [4,5] is shown by combinig a score, evaluating the agreement between simulated and measured INPHARMA spectra, with the PLANTS ChemPLP scoring function. First results from rescoring after local optimization of the poses and full docking experiments are shown.