A normal mode-based geometric simulation approach for exploring biologically relevant conformational transitions in proteins

Protein conformational space populated in solution probed with aromatic residual dipolar (13) C-(1) H couplings

The use of aromatic (13) C-(1) H residual dipolar couplings (RDCs) to probe the conformational space populated in solution is demonstrated for the protein BPTI. RDCs allow one to assess accuracy of atomic resolution structures and potentially to characterize low-populated subspaces corresponding to "excited states" in conformationally labile systems. They also allow one to assess sampling accuracy of molecular dynamics simulations.

The role of a dipeptide outer-coordination sphere on H2-production catalysts: influence on catalytic rates and electron transfer

The outer-coordination sphere of enzymes acts to fine-tune the active site reactivity and control catalytic rates, suggesting that incorporation of analogous structural elements into molecular catalysts may be necessary to achieve rates comparable to those observed in enzyme systems at low overpotentials. In this work, we evaluate the effect of an amino acid and dipeptide outer-coordination sphere on [Ni(P(Ph)(2)N(Ph-R)(2))(2)](2+) hydrogen production catalysts. A series of 12 new complexes containing non-natural amino acids or dipeptides was prepared to test the effects of positioning, size, polarity and aromaticity on catalytic activity. The non-natural amino acid was either 3-(meta- or para-aminophenyl)propionic acid terminated as an acid, an ester or an amide. Dipeptides consisted of one of the non-natural amino acids coupled to one of four amino acid esters: alanine, serine, phenylalanine or tyrosine. All of the catalysts are active for hydrogen production, with rates averaging ∼1000 s(-1), 40 % faster than the unmodified catalyst. Structure and polarity of the aliphatic or aromatic side chains of the C-terminal peptide do not strongly influence rates. However, the presence of an amide bond increases rates, suggesting a role for the amide in assisting catalysis. Overpotentials were lower with substituents at the N-phenyl meta position. This is consistent with slower electron transfer in the less compact, para-substituted complexes, as shown in digital simulations of catalyst cyclic voltammograms and computational modeling of the complexes. Combining the current results with insights from previous results, we propose a mechanism for the role of the amino acid and dipeptide based outer-coordination sphere in molecular hydrogen production catalysts.

NMSim web server: integrated approach for normal mode-based geometric simulations of biologically relevant conformational transitions in proteins

The NMSim web server implements a three-step approach for multiscale modeling of protein conformational changes. First, the protein structure is coarse-grained using the FIRST software. Second, a rigid cluster normal-mode analysis provides low-frequency normal modes. Third, these modes are used to extend the recently introduced idea of constrained geometric simulations by biasing backbone motions of the protein, whereas side chain motions are biased toward favorable rotamer states (NMSim). The generated structures are iteratively corrected regarding steric clashes and stereochemical constraint violations. The approach allows performing three simulation types: unbiased exploration of conformational space; pathway generation by a targeted simulation; and radius of gyration-guided simulation. On a data set of proteins with experimentally observed conformational changes, the NMSim approach has been shown to be a computationally efficient alternative to molecular dynamics simulations for conformational sampling of proteins. The generated conformations and pathways of conformational transitions can serve as input to docking approaches or more sophisticated sampling techniques. The web server output is a trajectory of generated conformations, Jmol representations of the coarse-graining and a subset of the trajectory and data plots of structural analyses. The NMSim webserver, accessible at http://www.nmsim.de, is free and open to all users with no login requirement.

Template-Based Geometric Simulation of Flexible Frameworks

Specialised modelling and simulation methods implementing simplified physical models are valuable generators of insight. Template-based geometric simulation is a specialised method for modelling flexible framework structures made up of rigid units. We review the background, development and implementation of the method, and its applications to the study of framework materials such as zeolites and perovskites. The "flexibility window" property of zeolite frameworks is a particularly significant discovery made using geometric simulation. Software implementing geometric simulation of framework materials, "GASP", is freely available to researchers.

On the applicability of elastic network normal modes in small-molecule docking

Incorporating backbone flexibility into protein-ligand docking is still a challenging problem. In protein-protein docking, normal mode analysis (NMA) has become increasingly popular as it can be used to describe the collective motions of a biological system, but the question of whether NMA can also be useful in predicting the conformational changes observed upon small-molecule binding has only been addressed in a few case studies. Here, we describe a large-scale study on the applicability of NMA for protein-ligand docking using 433 apo/holo pairs of the Astex data sets. On the basis of sets of the first normal modes from the apo structure, we first generated for each paired holo structure a set of conformations that optimally reproduce its C(α) trace with respect to the underlying normal mode subspace. Using AutoDock, GOLD, and FlexX we then docked the original ligands into these conformations to assess how the docking performance depends on the number of modes used to reproduce the holo structure. The results of our study indicate that, even for such a best-case scenario, the use of normal mode analysis in small-molecule docking is restricted and that a general rule on how many modes to use does not seem to exist or at least is not easy to find.

Flexibility analysis of biomacromolecules with application to computer-aided drug design

Flexibility characteristics of biomacromolecules can be efficiently determined down to the atomic level by a graph-theoretical technique as implemented in the FIRST (Floppy Inclusion and Rigid Substructure Topology) and ProFlex software packages. The method has been successfully applied to a series of protein and nucleic acid structures. Here, we describe practical guidelines for setting up and performing a flexibility analysis, discuss current bottlenecks of the approach, and provide sample applications as to how this technique can support computer-aided drug design approaches.

Hot spots and transient pockets: predicting the determinants of small-molecule binding to a protein-protein interface

Protein-protein interfaces are considered difficult targets for small-molecule protein-protein interaction modulators (PPIMs ). Here, we present for the first time a computational strategy that simultaneously considers aspects of energetics and plasticity in the context of PPIM binding to a protein interface. The strategy aims at identifying the determinants of small-molecule binding, hot spots, and transient pockets, in a protein-protein interface in order to make use of this knowledge for predicting binding modes of and ranking PPIMs with respect to their affinity. When applied to interleukin-2 (IL-2), the computationally inexpensive constrained geometric simulation method FRODA outperforms molecular dynamics simulations in sampling hydrophobic transient pockets. We introduce the PPIAnalyzer approach for identifying transient pockets on the basis of geometrical criteria only. A sequence of docking to identified transient pockets, starting structure selection based on hot spot information, RMSD clustering and intermolecular docking energies, and MM-PBSA calculations allows one to enrich IL-2 PPIMs from a set of decoys and to discriminate between subgroups of IL-2 PPIMs with low and high affinity. Our strategy will be applicable in a prospective manner where nothing else than a protein-protein complex structure is known; hence, it can well be the first step in a structure-based endeavor to identify PPIMs.