David J. Osguthorpe

Ab initio protein folding.

Ab initio protein folding methods have been developing rapidly over the past few years and, at the last Critical assessment of methods of protein structure prediction (CASP) meeting, it was shown that important progress has been made in generating structure from sequence. Both methods based on statistical potentials and methods using physics-based potentials have shown improvements. Most current methods use statistics-based potentials and the development of these is ongoing. Additionally, the inclusion of multiple sequence data in the algorithms in order to aid in finding the native structure is a common theme. The use of physics-based potentials is less developed, which means that less progress has been made in understanding why a sequence forms a structure.

Ligand-gated ion channels. Homology and diversity.

Outline of the Ligand-Gated Ion Channel (LGIC) Superfamily Structure and Function The Recognition Site for Agonists and Competitive Antagonists Other Features of the Extracellular Domain The Transmembrane Domain and the Ion Channel The Major Intracellular Region Quaternary Structure Evolutionary Diversity of LGICs Origins of the Superfamily Events in nACh Receptor Evolution Events in GABA A and Glycine Receptor Evolution Concluding Remarks References

Refined models for computer simulation of protein folding: Applications to the study of conserved secondary structure and flexible hinge points during the folding of pancreatic trypsin inhibitor

Abstract A new model and parameters are proposed for the computer simulation of protein folding, which satisfy requirements for a fully automatic simulation as discussed in recent critical reviews. The parameters were obtained, refined or checked by empirical observations on proteins of known sequence and conformation, in order to avoid as much as possible theoretical deductions about the nature of the interactions between groups in proteins, which may not be justified by the current status of the art. The major improvement over previous methods is to retain a more realistic and complete representation of the protein backbone, and to alternatively reduce the number of variables by coupling their behaviour. As an example, the method is applied to simulate the folding of pancreatic trypsin inhibitor, and leads to a root-mean-square fit of 6·0 A with good secondary structure. This also allows a more detailed examination of secondary structure transitions during protein folding than has been possible hitherto. Although, in the simulation discussed most extensively, the advantage of initial statistical predictions is demonstrated, the secondary structure was free to change in the simulation. A simulation from an extended chain is also described, and refinements tested. By observing changes in secondary structure during the simulated folding, it is shown that α-helices and extended chain regions predicted at the outset, or formed early in the simulation, are conserved, and that certain residues are crucial as flexible hinge-points to bring the secondary structure together in order to achieve tertiary packing. In view of recent debate about the importance of glycyl residues as hinge-points, and the danger of imparting glycyl-like backbone behaviour to non-glycyl residues suspected to be hinge-points, it is of considerable interest that the hinge-point residues identified by us are not , in general, glycyl residues. This makes an important distinction between a “reverse turn region”, for which glycine is statistically a strong candidate, and a hinge-point in the protein backbone. It is discussed that reverse turns are locally determined and likely to be fairly stable during the folding process, while hinge-points are determined by tertiary interactions. This distinction, implicit in most papers concerned with statistical methods of secondary structure prediction, has not been made clearly in recent reports of folding simulations.

Exploring Protein Flexibility: Incorporating Structural Ensembles From Crystal Structures and Simulation into Virtual Screening Protocols

The capacity of proteins to adapt their structure in response to various perturbations including covalent modifications, and interactions with ligands and other proteins plays a key role in biological processes. Here, we explore the ability of molecular dynamics (MD), replica exchange molecular dynamics (REMD), and a library of structures of crystal-ligand complexes, to sample the protein conformational landscape and especially the accessible ligand binding site geometry. The extent of conformational space sampled is measured by the diversity of the shapes of the ligand binding sites. Since our focus here is the effect of this plasticity on the ability to identify active compounds through virtual screening, we use the structures generated by these techniques to generate a small ensemble for further docking studies, using binding site shape hierarchical clustering to determine four structures for each ensemble. These are then assessed for their capacity to optimize enrichment and diversity in docking. We test these protocols on three different receptors: androgen receptor (AR), HIV protease, and CDK2. We show that REMD enhances structural sampling slightly as compared both to MD, and the distortions induced by ligand binding as reflected in the crystal structures. The improved sampling of the simulation methods does not translate directly into improved docking performance, however. The ensemble approach did improve enrichment and diversity, and the ensemble derived from the crystal structures performed somewhat better than those derived from the simulations.

Generation of receptor structural ensembles for virtual screening using binding site shape analysis and clustering.

Accounting for protein flexibility is an essential yet challenging component of structure‐based virtual screening. Whereas an ideal approach would account for full protein and ligand flexibility during the virtual screening process, this is currently intractable using available computational resources. An alternative is ensemble docking, where calculations are performed on a set of individual rigid receptor conformations and the results combined. The primary challenge associated with this approach is the choice of receptor structures to use for the docking calculations. In this work, we show that selection of a small set of structures based on clustering on binding site volume overlaps provides an efficient and effective way to account for protein flexibility in virtual screening. We first apply the method to crystal structures of cyclin‐dependent kinase 2 and HIV protease and show that virtual screening for ensembles of four cluster representative structures yields consistently high enrichments and diverse actives. We then apply the method to a structural ensemble of the androgen receptor generated with molecular dynamics and obtain results that are in agreement with those from the crystal structures of cyclin‐dependent kinase 2 and HIV protease. This work provides a step forward in the incorporation of protein flexibility into structure‐based virtual screening.

Inhibition of phospholipase A2; a molecular recognition study

A model of the enzyme PLA2 with a phospholipid substrate bound in the active site was derived using molecular graphics and molecular mechanics modelling techniques, and its ability to account for competitive inhibition tested by modelling the analogous complex of the enzyme and a known inhibitor; the model was then applied to the study of the binding of a new inhibitor, 3-arachidonyl-4(O-phosphoethanolamino)-methyltetrahydrofuran-2-one and the absolute stereochemistry for active site binding of this inhibitor predicted to be (3S,4R).

Partitioning the motion in molecular dynamics simulations into characteristic modes of motion

Molecular dynamics (MD) simulations result in a comprehensive description of molecular motion. However, to gain insight into the dynamic behavior of molecules it is important to be able to identify different types of motions and characterize them. We have developed a novel technique aimed at characterizing the motion of the system using digital signal processing techniques. The amplitudes and phases of the Fourier transform of the atomic fluctuations are used to define the characteristic modes of motion in the MD trajectory. This yields a pictorial description of the oscillatory motions in a manor analogous to normal‐mode (NM) analysis. The validity of this method has been tested on small molecules such as water, acetamide, and a blocked polyalanine in a helical conformation. The NMs obtained by diagonalizing the mass‐weighted second derivative matrix were combined to generate “NM trajectories” that served as well‐characterized test cases. Distinct characteristic modes can be extracted from both NM and MD trajectories. The modes extracted from the NM trajectories were identical to the original NMs. The modes extracted from the MD trajectories were in most cases highly correlated to the corresponding NM. However, intermixing of some of the modes occurred, particularly when conformational changes took place. This technique is flexible and can be applied to the molecular system as a whole or to a subset of atoms of interest. Fourier transform calculations are fast and therefore the analysis stage is not demanding in computational resources. Anharmonicity is included explicitly in the simulations and solvent can be included as well.

Design of a natural cis peptide bond motif to form type VI β-turn mimetic

Abstract Starting from a pyro-glutamic acid residue, which has a natural cis amide bond motif, and extending the chain appropriately from its C y atom, a type VI β-turn mimetic can be designed. The stability of the model can be enhanced by making a spiro compound linking the C y atom to previous N in the extended chain. Three out of a possible four values defining the β-turn are constrained by local cyclisations giving a well defined and rigid model for a type VI β-turn.

MOLECULAR DYNAMICS: DECIPHERING THE DATA

SummaryThe dynamic behaviour of molecules is important in determining their activity. Molecular dynamics (MD) simulations give a detailed description of motion, from small fluctuations to conformational transitions, and can include solvent effects. However, extracting useful information about conformational motion from a trajectory is not trivial. We have used digital signal-processing techniques to characterise the motion in MD simulations, including: calculating the frequency distribution, applying filtering functions, and extraction of vectors defining the characteristic motion for each frequency in an MD simulation. We describe here some typical results obtained for peptides and proteins. The nature of the low-frequency modes of motion, as obtained from MD and normal mode (NM) analysis, of Ace-(Ala)31-Nma and of a proline mutant is discussed. Low-frequency modes extracted from the MD trajectories of Rop protein and phospholipase A2 reveal characteristic motions of secondary structure elements, as well as concerted motions that are of significance to the proteins biological activity. MD simulations are also used frequently as a tool for conformational searches and for investigating protein folding/unfolding. We have developed a novel method that uses time-domain filtering to channel energy into conformational motion and thus enhance conformational transitions. The selectively enhanced molecular dynamics method is tested on the small molecule hexane.

Structure-activity studies with fragments and analogues of salmonid melanin-concentrating hormone

A number of cyclic and linear fragments and analogues of MCH were synthesized and their biological potencies tested using the isolated carp scale melanophore assay. In this system the cyclic portion MCH(5-14) exhibited only 0.1% bioactivity, which was markedly enhanced by the addition of the exocyclic sequences MCH(15-17) and MCH(1-4). The exocyclic sequence itself, MCH(1-4,15-17), had minimal activity, however. Substitution of Tyr11 with phenylalanine reduced the potency of the ring structure MCH(5-14) by about 4-fold. Substitution of Gly8 with D-alanine reduced the potency of MCH(5-14) 16-fold, while both substitutions together caused a still more marked reduction (200-fold) in bioactivity. Linearized fragments of MCH, extending from MCH(15-17) to [Cys(Acm)5,14]MCH(1-17), showed a progressive increase in potency. The linearized forms of MCH, MCH(5-17) and MCH(5-14), were approximately 100-fold or less potent than their cyclic forms. The significant increases in bioactivity produced by the addition of the C- and N-terminal exocyclic sequence even to these linearized forms further emphasizes the importance of these regions for interaction at the receptor site.