We present an automatic method for docking organic ligands into protein Center for Information binding sites. The method can be used in the design process of specific Technology (GMD), Institute protein ligands. It combines an appropriate model of the physico-chemical for Algorithms and Scientific properties of the docked molecules with efficient methods for sampling the Computing (SCAI), Schloß conformational space of the ligand. If the ligand is flexible, it can adopt

this paper, we describe the construction of parametric surface skins using real spherical polar basis functions. As the use of such functions for protein shape representation is novel, a brief summary of their properties is also provided. We then give a description of the algebraic manipulations necessary to develop an efficient search for docking orienta- tions by incrementally rotating and translating the parametric representations. We also show that this spherical polar approach provides a natural way to model macromolecular electrostatic complementarity

Department of Structural We analyze the volume of atoms on the protein surface during a molecular-Biology, Fairchild Building dynamics simulation of a small protein (pancreatic trypsin inhibitor). To D109, Standford University calculate volumes, we use a particular geometric construction, called Voronoi Standford, CA 94305, USA polyhedra, that divides the total volume of the simulation box amongst the atoms, rendering them relatively larger or smaller depending on how tightly they are packed. We find that most of the atoms on the protein surface are larger than those buried in the core (by �6%), except for the charged atoms, which decrease in size, presumably due to electroconstriction. We also find that water molecules are larger near apolar atoms on the protein surface and smaller near charged atoms, in comparison to ‘‘bulk’ ’ water molecules far from the protein. Taken together, these findings necessarily imply that apolar atoms on the protein surface and their associated water molecules are less tightly packed (than corresponding atoms in the protein core and bulk water) and the opposite is the case for charged atoms. This looser apolar packing and tighter charged packing fundamentally reflects protein–water distances that are larger or smaller than those expected from van der Waals radii. In addition to the calculation of mean volumes, simulations allow us to investigate the volume fluctuations and hence compressibilities of the protein and solvent atoms. The relatively large volume fluctuations of atoms at the protein–water interface indicates that they have a more variable packing than corresponding atoms in the protein core or in bulk water. We try to adhere to traditional conventions throughout our calculations. Nevertheless, we are aware of and discuss three complexities that significantly qualify our calculations: the positioning of the dividing plane between atoms, the problem of vertex error, and the choice of atom radii. In particular, our results highlight how poor a ‘‘compromise’ ’ the commonly accepted value of 1.4 Å is for the radius of a water molecule.

otease-protein inhibitor and four antibody-antigen complexes. A large number of putative docked complexes have already been generated for the test systems using our rigid-body docking program, FTDOCK. They include geometries that closely resemble the crystal complex, and therefore act as a test for the renement procedure. In the protease-inhibitors, geometries that resemble the crystal complex are ranked in the top four solutions for four out of ve systems when solvation is included in the energy function, against a background of between 26 and 364 complexes in the data set. The results for the antibody-antigen complexes are not as encouraging, with only two of the four systems showing discrimination. It would appear that these results reect the somewhat different binding mechanism dominant in the two types of protein-protein complex. Binding in the protease-inhibitors appears to be "lock and key" in nature. The xed backbone and mobile side-chain representation provide a good model for

Abstract. In this paper, we propose a constraint-based approach to determining protein structures compatible with distance constraints obtained from Nuclear Magnetic Resonance (NMR) data. We compare the performance of our proposed algorithm with DYANA ("Dynamics algorithm for NMR applications ” [1]) an existing commercial application based on simulated annealing. For our test case, computation time for DYANA was more than six hours, whereas the method we propose produced similar results in 8 minutes, so we show that the application of Constraint Programming (CP) technology can greatly reduce computation time. This is a major advantage because this NMR technique generally demands multiple runs of structural computation. 1

. In this paper, we propose a mixed approach for determining protein structures compatible with distance constraints obtained from Nuclear Magnetic Resonance (NMR) data. A Constraint Processing algorithm is used to construct an approximate solution, which is then refined by a reparative optimization algorithm. We compare the performance of our proposed method with DYANA ("Dynamics algorithm for NMR applications" [1]) an existing commercial application based on simulated annealing. For our test case, computation time of DYANA was more than six hours, whereas the method we propose produced similar results in 8 minutes, so we show that the application of CP technology can greatly reduce computation time. This is a major advantage because this NMR technique generally demands multiple runs of structural computation. 1 Introduction Proteins play a wide role in metabolism control, and protein shape is an essential factor in controlling function and reactivity. A widely used analog...

this paper (i.e. standard volumes of buried atoms in proteins), and some explanations of Voronoi polyhedra in hypertext form. These items can be retrieved by sending

this document were produced directly from this program

Theprioritizationofthescreening ofcombinatoriallibrariesisanextremelyimportant taskfortherapididentificationoftightbinding ligandsandultimatelypharmaceuticalcompounds. Whenstructuralinformationforthetargetisavailable, moleculardockingisanapproachthatcanbe usedforprioritization.Here,wepresenttheinitial validationofanewrapidapproachtomolecular dockingdevelopedforprioritizingcombinatorial libraries.Thealgorithmistestedon103individual casesfromtheproteindatabankandinnearly90% ofthesecasesdockstheligandtowithin2.0ofthe observedbindingmode.BecausethemeanCPU timeis<5s/mol,thisapproachcanprocesshundredsofthousandsofcompoundsperweek. Furthermore, ifasomewhatlessthoroughsearchisperformed, thesearchtimedropsto1s/mol,thus allowingmillionsofcompoundstobedockedper weekandtestedforpotentialactivity.Proteins 2001;43:113--124.2001Wiley-Liss,Inc.

ABSTRACT We present a new computational method of docking pairs of proteins by using spherical polar Fourier correlations to accelerate the search for candidate low-energy conformations. Interaction energies are estimated using a hydrophobic excluded volume model derived from the notion of “overlapping surface skins, ” augmented by a rigorous but “soft ” model of electrostatic complementarity. This approach has several advantages over former three-dimensional grid-based fast Fourier transform (FFT) docking correlation methods even though there is no analogue to the FFT in a spherical polar representation. For example, a complete search over all six rigid-body degrees of freedom can be performed by rotating and translating only the initial expansion coefficients, many infeasible orientations may be eliminated rapidly using only low-resolution terms, and the correlations are easily localized around known binding epitopes when this knowledge is available. Typical execution times on a single processor workstation range from 2 hours for a global search (5 � 10 8 trial orientations) to a few minutes for a local search (over 6 � 10 7 orientations). The method is illustrated with several domain dimer and enzyme–inhibitor complexes and 20 large antibody–antigen complexes, using both the bound and (when available) unbound subunits. The correct conformation of the complex is frequently identified when docking bound subunits, and a good docking orientation is ranked within the top 20 in 11 out of 18 cases when starting from unbound subunits. Proteins 2000;39:178–194. © 2000 Wiley-Liss, Inc. Key words: shape complementarity; macromolecular electrostatics; Laguerre polynomials; spherical harmonics