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Virtual molecular screening is used to dock small-molecule libraries to a macromolecule in order to find lead compounds with desired biological function. This in silico method is well known for its application in computer-aided drug design. This chapter describes how to perform small-molecule virtual screening by docking with PyRx, which is open-source software with an intuitive user interface that runs on all major operating systems (Linux, Windows, and Mac OS). Specific steps for using PyRx, as well as considerations for data preparation, docking, and data analysis, are also described.

alpha-Cobratoxin (Cbtx), the neurotoxin isolated from the venom of the Thai cobra Naja kaouthia , causes paralysis by preventing acetylcholine (ACh) binding to nicotinic acetylcholine receptors (nAChRs). In the current study, the region of the Cbtx molecule that is directly involved in binding to nAChRs is used as the target for anticobratoxin drug design. The crystal structure (1YI5) of Cbtx in complex with the acetylcholine binding protein (AChBP), a soluble homolog of the extracellular binding domain of nAChRs, was selected to prepare an alpha-cobratoxin active binding site for docking. The amino acid residues (Ser182-Tyr192) of the AChBP structure, the binding site of Cbtx, were used as the positive control to validate the prepared Cbtx active binding site (root mean square deviation < 1.2 A). Virtual screening of the National Cancer Institute diversity set, a library of 1990 compounds with nonredundant pharmacophore profiles, using AutoDock against the Cbtx active site, revealed 39 potential inhibitor candidates. The adapted in vitro radioligand competition assays using [(3)H]epibatidine and [(125)I]bungarotoxin against the AChBPs from the marine species, Aplysia californica (Ac), and from the freshwater snails, Lymnaea stagnalis (Ls) and Bolinus truncates (Bt), revealed 4 compounds from the list of inhibitor candidates that had micromolar to nanomolar interferences for the toxin binding to AChBPs. Three hits (NSC42258, NSC121865, and NSC134754) can prolong the survival time of the mice if administered 30 min before injection with Cbtx, but only NSC121865 and NSC134754 can prolong the survival time if injected immediately after injection with Cbtx. These inhibitors serve as novel templates/scaffolds for the development of more potent and specific anticobratoxin.

The FightAIDS@Home distributed computing project uses AutoDock for an initial virtual screen of HIV protease structures against a broad range of 1771 ligands including both known protease inhibitors and a diverse library of other ligands. The volume of results allows novel large-scale analyses of binding energy "profiles" for HIV structures. Beyond identifying potential lead compounds, these characterizations provide methods for choosing representative wild-type and mutant protein structures from the larger set. From the binding energy profiles of the PDB structures, a principal component analysis based analysis identifies seven "spanning" proteases. A complementary analysis finds that the wild-type protease structure 2BPZ best captures the central tendency of the protease set. Using a comparison of known protease inhibitors against the diverse ligand set yields an AutoDock binding energy "significance" threshold of -7.0 kcal/mol between significant, strongly binding ligands and other weak/nonspecific binding energies. This threshold captures nearly 98% of known inhibitor interactions while rejecting more than 95% of suspected noninhibitor interactions. These methods should be of general use in virtual screening projects and will be used to improve further FightAIDS@Home experiments.

The W191G cavity of cytochrome c peroxidase is useful as a model system for introducing small molecule oxidation in an artificially created cavity. A set of small, cyclic, organic cations was previously shown to bind in the buried, solvent-filled pocket created by the W191G mutation. We docked these ligands and a set of non-binders in the W191G cavity using AutoDock 3.0. For the ligands, we compared docking predictions with experimentally determined binding energies and X-ray crystal structure complexes. For the ligands, predicted binding energies differed from measured values by +/- 0.8 kcal/mol. For most ligands, the docking simulation clearly predicted a single binding mode that matched the crystallographic binding mode within 1.0 A RMSD. For 2 ligands, where the docking procedure yielded an ambiguous result, solutions matching the crystallographic result could be obtained by including an additional crystallographically observed water molecule in the protein model. For the remaining 2 ligands, docking indicated multiple binding modes, consistent with the original electron density, suggesting disordered binding of these ligands. Visual inspection of the atomic affinity grid maps used in docking calculations revealed two patches of high affinity for hydrogen bond donating groups. Multiple solutions are predicted as these two sites compete for polar hydrogens in the ligand during the docking simulation. Ligands could be distinguished, to some extent, from non-binders using a combination of two trends: predicted binding energy and level of clustering. In summary, AutoDock 3.0 appears to be useful in predicting key structural and energetic features of ligand binding in the W191G cavity.

Recognition templates encapsulate the structural and energetic features for the specific recognition of a given ligand by a protein active site. These templates identify the major interactions used for specific recognition and may be used to find specific binding sites in proteins of unknown function. We present a grid-based method for deriving recognition templates for adenylate groups from a set of diverse nucleotide-binding proteins. The templates reveal the basis of specific binding of adenylate, including tight shape complementarity, specific hydrogen bonds, and underscoring the importance of a key steric contact for excluding guanylate from adenylate-specific sites. We demonstrate the utility of recognition templates in identifying specific adenylate-binding sites in a diverse set of dinucleotide-binding proteins., (Copyright 2001 Academic Press.)

The modeling of supramolecular structure presents two major challenges: (1) managing the large amount of sequence, structural and biochemical data, and (2) presenting the data to the user in a flexible and comprehensible manner that addresses these problems. We describe a visualization environment for the creation and analysis of supramolecular models. A set of modular symmetry tools, collectively called SymGen, has been created, providing a flexible platform for the creation of complex assemblies, with interactive control of all symmetry elements and their parameters. A second tool, SymSearch, allows a range of parameters defined within SymGen to be sampled and the resulting conformations to be evaluated. The environment avoids information overload, caused by the large number of atoms in supramolecular complexes, by using a multiresolution spherical harmonic representation that allows the user to display only essential features. Spherical harmonics also enables control of the triangulation level, allowing the user to reduce the complexity of the geometric description to retain interactive speed. The visual fidelity of the surface data is retained by using texture maps that are independent of the resolution of the underlying triangulation. We describe the design and implementation of this environment, and three illustrative examples of its utility.

Because of their wide use in molecular modeling, methods to compute molecular surfaces have received a lot of interest in recent years. However, most of the proposed algorithms compute the analytical representation of only the solvent-accessible surface. There are a few programs that compute the analytical representation of the solvent-excluded surface, but they often have problems handling singular cases of self-intersecting surfaces and tend to fail on large molecules (more than 10,000 atoms). We describe here a program called MSMS, which is shown to be fast and reliable in computing molecular surfaces. It relies on the use of the reduced surface that is briefly defined here and from which the solvent-accessible and solvent-excluded surfaces are computed. The four algorithms composing MSMS are described and their complexity is analyzed. Special attention is given to the handling of self-intersecting parts of the solvent-excluded surface called singularities. The program has been compared with Connolly's program PQMS [M.L. Connolly (1993) Journal of Molecular Graphics, Vol. 11, pp. 139-141] on a set of 709 molecules taken from the Brookhaven Data Base. MSMS was able to compute topologically correct surfaces for each molecule in the set. Moreover, the actual time spent to compute surfaces is in agreement with the theoretical complexity of the program, which is shown to be O[n log(n)] for n atoms. On a Hewlett-Packard 9000/735 workstation, MSMS takes 0.73 s to produce a triangulated solvent-excluded surface for crambin (1 crn, 46 residues, 327 atoms, 4772 triangles), 4.6 s for thermolysin (3tln, 316 residues, 2437 atoms, 26462 triangles), and 104.53 s for glutamine synthetase (2gls, 5676 residues, 43632 atoms, 476665 triangles).

AutoDock is a suite of C programs used to predict the bound conformations of a small, flexible ligand to a macromolecular target of known structure. The technique combines simulated annealing for conformation searching with a rapid grid-based method of energy evaluation. This paper reviews recent applications of the technique and describes the enhancements included in the current release.

We present a method for the approximation and real-time visualization of large-scale motion of protein surfaces. A molecular surface is represented by an expansion of spherical harmonic functions, and the motion of protein atoms around their equilibrium positions is computed by normal mode analysis. The motion of the surface is approximated by projecting the normal mode vectors of the solvent-accessible atoms to the spherical harmonic representation of the molecular surface. These surface motion vectors are represented by a separate spherical harmonic expansion. Representing the surface geometry and the surface motion vectors by spherical harmonic expansions allows variable-resolution analysis and real-time display of the large-scale surface motion. This technique has been applied to interactive visualization, interactive surface manipulation, and animation.

Texture mapping is an increasingly popular technique in molecular modeling. It is particularly effective in representing high-resolution surface detail using a low-resolution polygonal model. We describe how texture mapping can be used with parametric molecular surfaces represented as expansions of spherical harmonic functions. We define analytically the texture image and its transformation to a parametric surface. Unlike most methods of texture mapping, this transformation defines a one-to-one correspondence between the surface and the texture; texture coordinates are derived from the location of the surface point and not from physical properties at the surface point. This has advantages for the interactive visualization of surface data. We control the interactive response time by lowering the resolution of the polygon mesh while retaining the high-resolution detail of the texture, or we can lower the resolution of the texture image with the same polygonal model. By using a well-defined convention for texture coordinates, we can use the same image for the original surface or its parametric representation, and we can rapidly switch between images that represent different surface properties without recomputing the texture coordinates. Parametric surfaces allow new flexibility for the visualization of molecular surface data.

The Metropolis technique of conformation searching is combined with rapid energy evaluation using molecular affinity potentials to give an efficient procedure for docking substrates to macromolecules of known structure. The procedure works well on a number of crystallographic test systems, functionally reproducing the observed binding modes of several substrates.