Molecular recognition of receptor sites using a genetic algorithm with a description of desolvation

Pin1 and Par14 peptidyl prolyl isomerase inhibitors block cell proliferation

Disruption of the parvulin family peptidyl prolyl isomerase (PPIase) Pin1 gene delays reentry into the cell cycle when quiescent primary mouse embryo fibroblasts are stimulated with serum. Since Pin1 regulates cell cycle progression, a Pin1 inhibitor would be expected to block cell proliferation. To identify such inhibitors, we screened a chemical compound library for molecules that inhibited human Pin1 PPIase activity in vitro. We found a set of compounds that inhibited Pin1 PPIase activity in vitro with low microM IC50s and inhibited the growth of several cancer lines. Among the inhibitors, PiB, diethyl-1,3,6,8-tetrahydro-1,3,6,8-tetraoxobenzo[lmn] phenanthroline-2,7-diacetate ethyl 1,3,6,8-tetrahydro-1,3,6,8-tetraoxo-benzo[lmn] phenanthroline-(2H,7H)-diacetate, had the least nonspecific toxicity. These results suggest that Pin1 inhibitors could be used as a novel type of anticancer drug that acts by blocking cell cycle progression.

Distilling the essential features of a protein surface for improving protein-ligand docking, scoring, and virtual screening

For the successful identification and docking of new ligands to a protein target by virtual screening, the essential features of the protein and ligand surfaces must be captured and distilled in an efficient representation. Since the running time for docking increases exponentially with the number of points representing the protein and each ligand candidate, it is important to place these points where the best interactions can be made between the protein and the ligand. This definition of favorable points of interaction can also guide protein structure-based ligand design, which typically focuses on which chemical groups provide the most energetically favorable contacts. In this paper, we present an alternative method of protein template and ligand interaction point design that identifies the most favorable points for making hydrophobic and hydrogen-bond interactions by using a knowledge base. The knowledge-based protein and ligand representations have been incorporated in version 2.0 of SLIDE and resulted in dockings closer to the crystal structure orientations when screening a set of 57 known thrombin and glutathione S-transferase (GST) ligands against the apo structures of these proteins. There was also improved scoring enrichment of the dockings, meaning better differentiation between the chemically diverse known ligands and a approximately 15,000-molecule dataset of randomly-chosen small organic molecules. This approach for identifying the most important points of interaction between proteins and their ligands can equally well be used in other docking and design techniques. While much recent effort has focused on improving scoring functions for protein-ligand docking, our results indicate that improving the representation of the chemistry of proteins and their ligands is another avenue that can lead to significant improvements in the identification, docking, and scoring of ligands.

Pattern recognition and massively distributed computing

A feature of Peter Kollman's research was his exploitation of the latest computational techniques to devise novel applications of the free energy perturbation method. He would certainly have seized upon the opportunities offered by massively distributed computing. Here we describe the use of over a million personal computers to perform virtual screening of 3.5 billion druglike molecules against protein targets by pharmacophore pattern matching, together with other applications of pattern recognition such as docking ligands without any a priori knowledge about the binding site location.

Structure-based virtual screening: an overview

Enormous advances in genomics have resulted in a large increase in the number of potential therapeutic targets that are available for investigation. This growth in potential targets has increased the demand for reliable target validation, as well as technologies that can identify rapidly several quality lead candidates. Virtual screening, and in particular receptor-based virtual screening, has emerged as a reliable, inexpensive method for identifying leads. Although still an evolving method, advances in computational techniques have enabled virtual screening to have a positive impact on the discovery process. Here, the current strengths and weaknesses of the technology are discussed, and emphasis is placed on aspects of the work-flow of a virtual screening campaign, from preparation through to post-screening analysis.

Targeting thrombin and factor VIIa: design, synthesis, and inhibitory activity of functionally relevant indolizidinones

Guided by molecular modeling, docking experiments, and available X-ray crystal structure data on the serine protease Factor VIIa and thrombin, a series of indolizidinone derivatives was designed and synthesized having diverse functionality at the P1, P2, and P3 sites.

A fast annealing evolutionary algorithm for global optimization

By combining the aspect of population in genetic algorithms (GAs) and the simulated annealing algorithm (SAA), a novel algorithm, called fast annealing evolutionary algorithm (FAEA), is proposed. The algorithm is similar to the annealing evolutionary algorithm (AEA), and a very fast annealing technique is adopted for the annealing procedure. By an application of the algorithm to the optimization of test functions and a comparison of the algorithm with other stochastic optimization methods, it is shown that the algorithm is a highly efficient optimization method. It was also applied in optimization of Lennard-Jones clusters and compared with other methods in this study. The results indicate that the algorithm is a good tool for the energy minimization problem.

A novel approach for identifying the surface atoms of macromolecules

A significant number of atoms lie buried beneath the "molecular surface" of proteins and other biologic macromolecules. Interactions between ligands and these macromolecules are dominated by interactions with the "surface atoms". Although interactions with the "buried" or interior atoms of the macromolecule certainly contribute to the total intermolecular interaction energy, many computer-assisted drug design (CADD) strategies can benefit from the identification of those atoms "on the surface" of proteins and other macromolecules. We have developed a simple, yet novel method to distinguish the surface atoms of macromolecules from the interior atoms which is based on computing the atomic contributions to the solvent-accessible surface (SAS) area. This report describes that method and demonstrates that it compares very favorably with four alternative methods.

Modified AutoDock for accurate docking of protein kinase inhibitors

Protein kinases are an important class of enzymes controlling virtually all cellular signaling pathways. Consequently, selective inhibitors of protein kinases have attracted significant interest as potential new drugs for many diseases. Computational methods, including molecular docking, have increasingly been used in the inhibitor design process [1]. We have considered several docking packages in order to strengthen our kinase inhibitor work with computational capabilities. In our experience, AutoDock offered a reasonable combination of accuracy and speed, as opposed to methods that specialize either in fast database searches or detailed and computationally intensive calculations. However, AutoDock did not perform well in cases where extensive hydrophobic contacts were involved, such as docking of SB203580 to its target protein kinase p38. Another shortcoming was a hydrogen bonding energy function, which underestimated the attraction component and, thus, did not allow for sufficiently accurate modeling of the key hydrogen bonds in the kinase-inhibitor complexes. We have modified the parameter set used to model hydrogen bonds, which increased the accuracy of AutoDock and appeared to be generally applicable to many kinase-inhibitor pairs without customization. Binding to largely hydrophobic sites, such as the active site of p38, was significantly improved by introducing a correction factor selectively affecting only carbon and hydrogen energy grids, thus, providing an effective, although approximate, treatment of solvation.

Automated docking to multiple target structures: incorporation of protein mobility and structural water heterogeneity in AutoDock

Protein motion and heterogeneity of structural waters are approximated in ligand-docking simulations, using an ensemble of protein structures. Four methods of combining multiple target structures within a single grid-based lookup table of interaction energies are tested. The method is evaluated using complexes of 21 peptidomimetic inhibitors with human immunodeficiency virus type 1 (HIV-1) protease. Several of these structures show motion of an arginine residue, which is essential for binding of large inhibitors. A structural water is also present in 20 of the structures, but it must be absent in the remaining one for proper binding. Mean and minimum methods perform poorly, but two weighted average methods permit consistent and accurate ligand docking, using a single grid representation of the target protein structures.

Consensus scoring for ligand/protein interactions

Several different functions have been put forward for evaluating the energetics of ligand binding to proteins. Those employed in the DOCK, GOLD and FlexX docking programs have been especially widely used, particularly in connection with virtual high-throughput screening (vHTS) projects. Until recently, such evaluation functions were usually considered only in conjunction with the docking programs that relied on them. In such studies, the evaluation function in question actually fills two distinct roles: it serves as the objective function being optimized (fitness function), but is also the scoring function used to compare the candidate docking configurations generated by the program. We have used descriptions available in the open literature to create free-standing scoring functions based on those used in DOCK and GOLD, and have implemented the more recently formulated PMF [J. Med. Chem. 42 (1999) 791] scoring function as well. The performance of these functions was examined individually for each of several data sets for which both crystal structures and affinities are available, as was the performance of the FlexX scoring function. Various ways of combining individual scores into a consensus score (CScore) were also considered. The individual and consensus scores were also used to try to pick out configurations most similar to those found in crystal structures from among a set of candidate configurations produced by FlexX docking runs. We find that the reliability and interpretability of results can be improved by combining results from all four functions into a CScore.

Total synthesis and biological evaluation of the nakijiquinones

The Her-2/Neu receptor tyrosine kinase is vastly overexpressed in about 30% of primary breast, ovary, and gastric carcinomas. The nakijiquinones are the only naturally occurring inhibitors of this important oncogene, and structural analogues of the nakijiquinones may display inhibitory properties toward other receptor tyrosine kinases involved in cell signaling and proliferation. Here, we describe the first enantioselective synthesis of the nakijiquinones. Key elements of the synthesis are (i) the reductive alkylation of a Wieland-Miescher-type enone with a tetramethoxyaryl bromide, (ii) the oxidative conversion of the aryl ring into a p-quinoid system, (iii) the regioselective saponification of one of the two vinylogous esters incorporated therein, and (iv) the selective introduction of different amino acids via nucleophilic conversion of the remaining vinylogous ester into the corresponding vinylogous amide. The correct stereochemistry and substitution patterns are completed by conversion of two keto groups into a methyl group and an endocyclic olefin via olefination/reduction and olefination/isomerization sequences, respectively. This synthesis route also gave access to analogues of nakijiquinone C with inverted configuration at C-2 or with an exocyclic instead of an endocyclic double bond. Investigation of the kinase-inhibiting properties of the synthesized derivatives revealed that the C-2 epimer 30 of nakijiquinone C is a potent and selective inhibitor of the KDR receptor, a receptor tyrosine kinase involved in tumor angiogenesis. Molecular modeling studies based on the crystal structure of KDR and a model of the ATP binding site built from a crystal structure of FGF-R revealed an insight into the structural basis for the difference in activity between the natural product nakijiquinone C and the C-2 epimer 30.

A comparative docking study and the design of potentially selective MMP inhibitors

As part of a program aimed at the design and synthesis of constrained MMP inhibitors, a survey of the reported X-ray and NMR structures of MMP/inhibitor complexes was performed, revealing mutations of key amino acids at different subsites between MMPs. A comparative study of fully automated docking programs AutoDock and DOCK in closely approximating the X-ray crystal structures of ten selected MMP inhibitors was performed. AutoDock proved to be highly reliable, efficient and predictive for a set of inhibitors with less than six atom types.

SuperStar: comparison of CSD and PDB-based interaction fields as a basis for the prediction of protein-ligand interactions

SuperStar is an empirical method for identifying interaction sites in proteins, based entirely on the experimental information about non-bonded interactions, present in the IsoStar database. The interaction information in IsoStar is contained in scatterplots, which show the distribution of a chosen probe around structure fragments. SuperStar breaks a template molecule (e.g. a protein binding site) into structural fragments which correspond to those in the scatterplots. The scatterplots are then superimposed on the corresponding parts of the template and converted into a composite propensity map. The original version of SuperStar was based entirely on scatterplots from the CSD. Here, scatterplots based on protein-ligand interactions are implemented in SuperStar, and validated on a test set of 122 X-ray structures of protein-ligand complexes. In this validation, propensity maps are compared with the experimentally observed positions of ligand atoms of comparable types. Although non-bonded interaction geometries in small molecule structures are similar to those found in protein-ligand complexes, their relative frequencies of occurrence are different. Polar interactions are more common in the first class of structures, while interactions between hydrophobic groups are more common in protein crystals. In general, PDB and CSD-based SuperStar maps appear equally successful in the prediction of protein-ligand interactions. PDB-based maps are more suitable to identify hydrophobic pockets, and inherently take into account the experimental uncertainties of protein atomic positions. If the protonation state of a histidine, aspartate or glutamate protein side-chain is known, specific CSD-based maps for that protonation state are preferred over PDB-based maps which represent an ensemble of protonation states.

Fragment-Based flexible ligand docking by evolutionary optimization

A new computational approach for the efficient docking of flexible ligands in a rigid protein is presented. It exploits the binding modes of functional groups determined by an exhaustive search with solvation. The search in ligand conformational space is performed by a genetic algorithm whose scoring function approximates steric effects and intermolecular hydrogen bonds. Ligand conformations generated by the genetic algorithm are docked in the protein binding site by optimizing the fit of their fragments to optimal positions of chemically related functional groups. We show that the use of optimal binding modes of molecular fragments allows to dock known inhibitors with about ten rotatable bonds in the active site of the uncomplexed and complexed conformations of thrombin and HIV-1 protease.

A virtual high throughput screen for high affinity cytochrome P450cam substrates. Implications for in silico prediction of drug metabolism

Structure-based virtual screening techniques require reliable scoring functions to discriminate potential substrates effectively. In this study we compared the performance of GOLD, PMF, DOCK and FlexX scoring functions in FlexX flexible docking to cytochrome P450cam binding site. Crystal structures of protein-substrate complexes were most effectively reproduced by the FlexX/PMF method. On the other hand, the FlexX/GOLD approach provided the best correlation between experimental binding constants and predicted scores. Binding modes selected by the FlexX/PMF approach were rescored by GOLD to obtain a reliable measure of binding energetics. The effectiveness of the FlexX/PMF/GOLD method was demonstrated by the correct classification of 32 out of the 33 experimentally studied compounds and also in a virtual HTS test on a library of 10,000 compounds. Although almost all the available functions were developed to be general, our study on cytochrome P450cam substrates suggests that careful selection or even tailoring the scoring function might increase the prediction power of virtual screens significantly. The FlexX/PMF/GOLD methodology was tested on cytochrome P450 3A4 substrates and inhibitors. This preliminary study revealed that the combined function was able to recognise 334 out of the 345 compounds bound to 3A4.

FlexE: efficient molecular docking considering protein structure variations

Side-chain or even backbone adjustments upon docking of different ligands to the same protein structure, a phenomenon known as induced fit, are frequently observed. Sometimes point mutations within the active site influence the ligand binding of proteins. Furthermore, for homology derived protein structures there are often ambiguities in side-chain placement and uncertainties in loop modeling which may be critical for docking applications. Nevertheless, only very few molecular docking approaches have taken into account such variations in protein structures. We present the new software tool FlexE which addresses the problem of protein structure variations during docking calculations. FlexE can dock flexible ligands into an ensemble of protein structures which represents the flexibility, point mutations, or alternative models of a protein. The FlexE approach is based on a united protein description generated from the superimposed structures of the ensemble. For varying parts of the protein, discrete alternative conformations are explicitly taken into account, which can be combinatorially joined to create new valid protein structures.FlexE was evaluated using ten protein structure ensembles containing 105 crystal structures from the PDB and one modeled structure with 60 ligands in total. For 50 ligands (83 %) FlexE finds a placement with an RMSD to the crystal structure below 2.0 A. In all cases our results are of similar quality to the best solution obtained by sequentially docking the ligands into all protein structures (cross docking). In most cases the computing time is significantly lower than the accumulated run times for the single structures. FlexE takes about five and a half minutes on average for placing one ligand into the united protein description on a common workstation. The example of the aldose reductase demonstrates the necessity of considering protein structure variations for docking calculations. We docked three potent inhibitors into four protein structures with substantial conformational changes within the active site. Using only one rigid protein structure for screening would have missed potential inhibitors whereas all inhibitors can be docked taking all protein structures into account.

Design, synthesis and stability of N-acyloxymethyl- and N-aminocarbonyloxymethyl-2-azetidinones as human leukocyte elastase inhibitors

A series of N-acyloxymethyl- and N-aminocarbonyloxymethyl derivatives of 2-azetidinones, 3, with different substituent patterns at the beta-lactam C-3 and C-4 positions, were designed as potential mechanism-based inhibitors for human leukocyte elastase and found to exhibit inhibitory potency and selectivity for the enzyme.

SuperStar: improved knowledge-based interaction fields for protein binding sites

SuperStar is an empirical method for identifying interaction sites in proteins, based entirely on experimental information about non-bonded interactions occurring in small-molecule crystal structures, taken from the IsoStar database. We describe recent modifications and additions to SuperStar, validating the results on a test set of 122 X-ray structures of protein-ligand complexes. In this validation, propensity maps are generated for all the binding sites of these proteins, using four different probes: a charged NH(+)(3) nitrogen atom, a carbonyl oxygen atom, a hydroxyl oxygen atom and a methyl carbon atom. Next, the maps are compared with the experimentally observed positions of ligand atoms of these types. A peak-searching algorithm is introduced that highlights potential interaction hot spots. For the three hydrogen-bonding probes - NH(+)(3) nitrogen atom, carbonyl oxygen atom and hydroxyl oxygen atom - the average distance from the ligand atom to the nearest SuperStar peak is 1.0-1.2 A (0.8-1.0 A for solvent-inaccessible ligand atoms). For the methyl carbon atom probe, this distance is about 1.5 A, probably because interactions to methyl groups are much less directional. The most important addition to SuperStar is the enabling of propensity maps around metal centres - Ca(2+), Mg(2+) and Zn(2+) - in protein binding sites. The results are validated on a test set of 24 protein-ligand complexes that have a metal ion in their binding site. Coordination geometries are derived automatically, using only the protein atoms that coordinate to the metal ion. The correct coordination geometry is derived in approximately 75 % of the cases. If the derived geometry is assumed during the SuperStar calculation, the average distance from a ligand atom coordinating to the metal ion to the nearest peak in the propensity map for an oxygen probe is 0.87(7) A. If the correct coordination geometry is imposed, this distance reduces to 0.59(7)A. This indicates that the SuperStar predictions around metal-binding sites are at least as good as those around other protein groups. Using clustering techniques, a non-redundant set of probes is selected from the set of probes available in the IsoStar database. The performance in SuperStar of all these probes is tested on the test set of protein-ligand complexes. With the exception of the "ether oxygen" probe and the "any NH(+)" probe, all new probes perform as well as the four probes introduced first.

Ligand-receptor docking with the Mining Minima optimizer

The optimizer developed for the Mining Minima algorithm, which uses ideas from Genetic Algorithms, the Global Underestimator Method, and Poling, has been adapted for use in ligand-receptor docking. The present study describes the resulting methodology and evaluates its accuracy and speed for 27 test systems. The performance of the new docking algorithm appears to be competitive with that of previously published methods. The energy model, an empirical force field with a distance-dependent dielectric treatment of solvation, is adequate for a number of test cases, although incorrect low-energy conformations begin to compete with the correct conformation for larger sampling volumes and for highly solvent-exposed binding sites that impose little steric constraint on the ligand.

Side-chain flexibility in proteins upon ligand binding

Ligand binding may involve a wide range of structural changes in the receptor protein, from hinge movement of entire domains to small side-chain rearrangements in the binding pocket residues. The analysis of side chain flexibility gives insights valuable to improve docking algorithms and can provide an index of amino-acid side-chain flexibility potentially useful in molecular biology and protein engineering studies. In this study we analyzed side-chain rearrangements upon ligand binding. We constructed two non-redundant databases (980 and 353 entries) of "paired" protein structures in complexed (holo-protein) and uncomplexed (apo-protein) forms from the PDB macromolecular structural database. The number and identity of binding pocket residues that undergo side-chain conformational changes were determined. We show that, in general, only a small number of residues in the pocket undergo such changes (e.g., approximately 85% of cases show changes in three residues or less). The flexibility scale has the following order: Lys > Arg, Gln, Met > Glu, Ile, Leu > Asn, Thr, Val, Tyr, Ser, His, Asp > Cys, Trp, Phe; thus, Lys side chains in binding pockets flex 25 times more often then do the Phe side chains. Normalizing for the number of flexible dihedral bonds in each amino acid attenuates the scale somewhat, however, the clear trend of large, polar amino acids being more flexible in the pocket than aromatic ones remains. We found no correlation between backbone movement of a residue upon ligand binding and the flexibility of its side chain. These results are relevant to 1. Reduction of search space in docking algorithms by inclusion of side-chain flexibility for a limited number of binding pocket residues; and 2. Utilization of the amino acid flexibility scale in protein engineering studies to alter the flexibility of binding pockets.

Automated docking of ligands to antibodies: methods and applications

Many approaches to studying protein-ligand interactions by computational docking are currently available. Given the structures of a protein and a ligand, the ultimate goal of all docking methods is to predict the structure of the resulting complex. This requires a suitable representation of molecular structures and properties, search algorithms to efficiently scan the configuration space for favorable interaction geometries, and accurate scoring functions to evaluate and rank the generated orientations. For many of the available methods, tests on experimentally known antibody-antigen or antibody-hapten complexes have appeared in the literature. In addition, some of them have been used in predictive studies on antibody-ligand interactions to provide structural insights where adequate experimental information is missing. The AutoDock program is presented as example of a method for flexibly docking ligands to antibodies. Applying parameters of the second-generation AMBER force field, three antibody-hapten complexes (AN02, DB3, NC6.8) are used as new test cases to analyze the ability of the method to reproduce experimental findings. The X-ray structures could be reconstituted and the corresponding solutions were ranked with best energy score in all cases. Docking to the free instead of the complexed NC6.8 structure indicated the limits of the rigid protein treatment, although fairly good guesses about the location of the binding site and the contact residues could still be obtained if conformational flexibility was allowed at least in the ligand.

A novel energy-based stochastic method for positioning polar protons in protein structures from X-rays

A novel automated method for the optimal placement of polar hydrogens in a protein structure is presented. The algorithm adds initially, to a protein data bank file of the protein, nonrotatable hydrogens such as peptide backbone hydrogens according to geometric considerations. Then, water protons and polar side chain protons of lysine, serine, threonine, tyrosine, aspartic acid, glutamic acid, and the C and N termini of a protein are added according to energy considerations. A unique stochastic approach has been developed to overcome a combinatorial explosion in the search for the lowest energy structure. First, the system is divided into ensembles. Each ensemble is treated separately: N conformations are sampled at random, their energies computed, whereas common components of high-energy combinations are gathered on one hand, and low-energy combinations on the other. Components that yield only high-energy conformations and do not contribute to any low energies are excluded. This is reiterated while the total amount of combinations is decreased along the iterative process. When the total number of combinations is lower than a user defined threshold, all remaining combinations are evaluated by exhaustive search. Energy evaluations use nonbonding energy expressions alone. The program was tested on five high-resolution crystal structures: bovine pancreatic trypsin inhibitor (Brookhaven Protein Data Bank file 5PTI), RNase-A (5RSA), trypsin (1NTP), and carbon monoxymyoglobin (2MB5), for which neutron diffraction structures are available, as well as phosphate binding protein (1IXH) for which very high resolution X-ray crystallography was used. The low RMS values prove the efficiency of this algorithm as a tool for positioning protons in proteins. It may be used for other biological structures.

De novo design of peptides targeted to the EF hands of calmodulin

This report describes the use of the concept of inversion of hydropathy patterns to the de novo design of peptides targeted to a predetermined site on a protein. Eight- and 12-residue peptides were constructed with the EF hands or Ca(2+)-coordinating sites of calmodulin as their anticipated points of interaction. These peptides, but not unrelated peptides nor those with the same amino acid composition but a scrambled sequence, interacted with the two carboxyl-terminal Ca(2+)-binding sites of calmodulin as well as the EF hands of troponin C. The interactions resulted in a conformational change whereby the 8-mer peptide-calmodulin complex could activate phosphodiesterase in the absence of Ca(2+). In contrast, the 12-mer peptide-calmodulin complex did not activate phosphodiesterase but rather inhibited activation by Ca(2+). This inhibition could be overcome by high levels of Ca(2+). Thus, it would appear that the aforementioned concept can be used to make peptide agonists and antagonists that are targeted to predetermined sites on proteins such as calmodulin.

The sensitivity of the results of molecular docking to induced fit effects: application to thrombin, thermolysin and neuraminidase

This paper describes the application of PRO_LEADS to the flexible docking of ligands into crystallographically derived enzyme structures that are assumed to be rigid. PRO_LEADS uses a Tabu search methodology to perform the flexible search and an empirically derived estimate of the binding affinity to drive the docking process. The paper tests the extent to which the assumption of a rigid enzyme compromises the accuracy of the results. All-pairs docking experiments are performed for three enzymes (thrombin, thermolysin and influenza virus neuraminidase) based on six or more ligand-enzyme crystal structures for each enzyme. In 76% of the cases, PRO_LEADS can successfully identify the correct ligand conformation as the lowest energy configuration when the enzyme structure is derived from that ligand's crystal structure, but the methodology only docks 49% of the cases successfully when the ligand is docked against enzyme crystal structures derived from other ligands. Small movements in the enzyme structure lead to an under-prediction in the energy of the correct binding mode by up to 14 kJ/mol and in some cases this under-prediction can lead to the native mode not being recognised as the lowest energy solution. The type of movements responsible for mis-docking are: the movement of sidechains as a result of changes in C alpha position; the movement of sidechains without changes in C alpha position; the movement of flexible portions of main chains to facilitate the formation of hydrogen bonds; and the movement of metal atoms bound to the enzyme active site. The work illustrates that the assumption of a rigid active site can lead to errors in identification of the correct binding mode and the assessment of binding affinity, even for enzymes which show relatively small shift in atomic positions from one ligand to the next. A good docking code, such as PRO_LEADS, can usually dock successfully if there is induced fit in relatively rigid enzymes but there remains the need to develop improved strategies for dealing with enzyme flexibility. The work implies that treatments of enzyme flexibility which focus only on sidechain rotations will not deal with the critical shifts responsible for mis-docking of ligands in thrombin, thermolysin and neuraminidase. The paper demonstrates the utility of all pairs docking experiments as a method of assessing the effectiveness of docking methodologies in dealing with enzyme flexibility.

4-hydroxy-5,6-dihydro-2H-pyran-2-ones.3. Bicyclic and hetero-aromatic ring systems as 3-position scaffolds to bind to S1' and S2' of the HIV-1 protease enzyme

5,6-Dihydro-2H-pyran-2-ones are potent inhibitors of HIV-1 protease, which bind to the S1, S2, S1', and S2' pockets and have a unique binding mode with the catalytic aspartyl groups and the flap region of the enzyme. Efforts to explore 3-position heterocyclic scaffolds that bind to the S1' and S2' pockets have provided a number of selected analogs that display high HIV-1 protease inhibitory activity. reserved.

SuperStar: a knowledge-based approach for identifying interaction sites in proteins

An empirical method for identifying interaction sites in proteins is described and validated. The method is based entirely on experimental information about non-bonded interactions occurring in small-molecule crystal structures. These data are used in the form of scatterplots that show the experimentally observed distribution of one functional group (the "contact group" or "probe") around another. A template molecule (e.g. a protein binding site) is broken down into structure fragments and the scatterplots, showing the distribution of a chosen probe around these structure fragments, are superimposed on the corresponding parts of the template. The scatterplots are then translated into a three-dimensional map that shows the propensity of the probe at different positions around the template molecule. The method is illustrated for l -arabinose-binding protein, complexed with l -arabinose and with d -fucose, and for dihydrofolate reductase complexed with methotrexate. The method is validated on 122 X-ray structures of protein-ligand complexes. For all the binding sites of these proteins, propensity maps are generated for four different probes: a charged NH+3nitrogen, a carbonyl oxygen, a hydroxyl oxygen and a methyl carbon atom. Next, the maps are compared with the experimentally observed positions of ligand atoms of these types. For 74% of these ligand atoms (84% of the solvent-inaccessible ones) the calculated propensity of the matching probe at the experimental positions is higher than expected by chance. For 68% of the atoms (82% of the solvent-inaccessible ones) the propensity of the matching probe is higher than that of the other three probes. These results indicate that the approach generally gives good predictions for protein-ligand interactions. The potential applications of the propensity maps range from an aid in manual docking and structure-based drug design to their use in pharmacophore development.

Docking of flexible ligands to flexible receptors in solution by molecular dynamics simulation

In this paper, a method of simulating the docking of small flexible ligands to flexible receptors in water is reported. The method is based on molecular dynamics simulations and is an extension of an algorithm previously reported by Di Nola et al. (Di Nola et al., Proteins 1994;19:174-182). The method allows a fast exploration of the receptor surface, using a high temperature of the center of mass translational motion, while the ligand internal motions, the solvent, and the receptor are simulated at room temperature. In addition, the method allows a fast center of mass motion of the ligand, even in solution. The dampening effect of the solvent can be overcome by applying different weights to the interactions between system subsets (solvent, receptor, and ligand). Specific ligand-receptor distances have been used to compare the results of the simulations with the crystal structure. The method is applied, as a test system, to the docking of the phosphocholine to the immunoglobulin McPC603. The results show the similarity of structure between the complex in solution and in the crystal.

A method for biomolecular structural recognition and docking allowing conformational flexibility

In this work, we present an algorithm developed to handle biomolecular structural recognition problems, as part of an interdisciplinary research endeavor of the Computer Vision and Molecular Biology fields. A key problem in rational drug design and in biomolecular structural recognition is the generation of binding modes between two molecules, also known as molecular docking. Geometrical fitness is a necessary condition for molecular interaction. Hence, docking a ligand (e.g., a drug molecule or a protein molecule), to a protein receptor (e.g., enzyme), involves recognition of molecular surfaces. Conformational transitions by "hinge-bending" involves rotational movements of relatively rigid parts with respect to each other. The generation of docked binding modes between two associating molecules depends on their three dimensional structures (3-D) and their conformational flexibility. In comparison to the particular case of rigid-body docking, the computational difficulty grows considerably when taking into account the additional degrees of freedom intrinsic to the flexible molecular docking problem. Previous docking techniques have enabled hinge movements only within small ligands. Partial flexibility in the receptor molecule is enabled by a few techniques. Hinge-bending motions of protein receptors domains are not addressed by these methods, although these types of transitions are significant, e.g., in enzymes activity. Our approach allows hinge induced motions to exist in either the receptor or the ligand molecules of diverse sizes. We allow domains/subdomains/group of atoms movements in either of the associating molecules. We achieve this by adapting a technique developed in Computer Vision and Robotics for the efficient recognition of partially occluded articulated objects. These types of objects consist of rigid parts which are connected by rotary joints (hinges). Our method is based on an extension and generalization of the Hough transform and the Geometric Hashing paradigms for rigid object recognition. We show experimental results obtained by the successful application of the algorithm to cases of bound and unbound molecular complexes, yielding fast matching times. While the "correct" molecular conformations of the known complexes are obtained with small RMS distances, additional, predictive good-fitting binding modes are generated as well. We conclude by discussing the algorithm's implications and extensions, as well as its application to investigations of protein structures in Molecular Biology and recognition problems in Computer Vision.

Drug discovery: past, present and future

New drug discovery from early on involved a trial-and-error approach on naturally derived materials and substances until the end of the nineteenth century. The first half of the twentieth century witnessed systematic pharmacological evaluations of both natural and synthetic compounds. However, most new drugs until the 1970s were discovered by serendipity. With the exponential development of molecular biology on one hand and computer technology on the other, it became possible from 1980 onwards to place drug discovery on a rational basis. Cloning of genes has led to the development of methodologies for specific receptor-directed and enzyme-directed drug discoveries. Advances in recombinant DNA and transgenic technologies have enabled the production of human hormonal and other endogenous biomolecules as new drugs. As we understand more about the co-ordinating and regulating powers of the cerebral cortex during the next century, especially of the frontal lobe, man may be able to use bio-feedback training to voluntarily regulate the release of neurotransmitters, hormones, and other molecules involved in the regulation of various physiological processes in health as well as in disease.

Reaching the global minimum in docking simulations: a Monte Carlo energy minimization approach using Bezier splines

The docking problem faces two major challenges: the global optimization of a multivariable function, such as the energy, and the ability to discriminate between true and false positive results, i.e., native from nonnative structures based on the input energy function. Among all energy evaluation tools, only a local energy-minimization method using an accurate enough potential function is able to discriminate between native and nonnative structures. To meet these requirements, a Monte Carlo with energy-minimization method has been incorporated into a new ECEPP/3 docking program. The efficiency of the simulation results from the use of an energy-grid technique based on Bezier splines and from a simplification of the receptor by switching on the energy of only important residues of the active site. Simulations of a thrombin-inhibitor complex show that the global minimum of the energy function was reached in every independent run within less than 3 min of time on an IBM RX 6000 computer. For comparison, 10 standard independent Monte Carlo simulations with 10(6) steps in each were carried out. Only three of them led to a conformation close to the x-ray structure. The latter simulations required an average of 24 min and about 10 hr with and without the grid, respectively. Another important result is that the Bezier spline technique not only speeds up the calculation by reducing the number of operations during the energy evaluation but also helps in reaching the global minimum by smoothing out the potential energy surface.

Low-resolution structures of proteins in solution retrieved from X-ray scattering with a genetic algorithm

Small-angle x-ray solution scattering (SAXS) is analyzed with a new method to retrieve convergent model structures that fit the scattering profiles. An arbitrary hexagonal packing of several hundred beads containing the problem object is defined. Instead of attempting to compute the Debye formula for all of the possible mass distributions, a genetic algorithm is employed that efficiently searches the configurational space and evolves best-fit bead models. Models from different runs of the algorithm have similar or identical structures. The modeling resolution is increased by reducing the bead radius together with the search space in successive cycles of refinement. The method has been tested with protein SAXS (0.001 < S < 0.06 A(-1)) calculated from x-ray crystal structures, adding noise to the profiles. The models obtained closely approach the volumes and radii of gyration of the known structures, and faithfully reproduce the dimensions and shape of each of them. This includes finding the active site cavity of lysozyme, the bilobed structure of gamma-crystallin, two domains connected by a stalk in betab2-crystallin, and the horseshoe shape of pancreatic ribonuclease inhibitor. The low-resolution solution structure of lysozyme has been directly modeled from its experimental SAXS profile (0.003 < S < 0.03 A(-1)). The model describes lysozyme size and shape to the resolution of the measurement. The method may be applied to other proteins, to the analysis of domain movements, to the comparison of solution and crystal structures, as well as to large macromolecular assemblies.

Development of filter functions for protein-ligand docking

Current docking methods can generate bound conformations of a ligand close to the experimentally observed structure of a protein-ligand complex. However, the scoring functions used to evaluate the potential solutions are not yet reliable enough at giving the highest ranks to the best structure predictions. One approach to this problem is the use of filter functions that are applied to all docked conformations to remove structures with certain energetically unfavorable properties. We present a computationally efficient scheme for such a postprocessing of docking results. For each of the conformations generated for a given protein-ligand complex, four properties are calculated: the fraction of the ligand volume buried inside the binding pocket, the size of lipophilic cavities along the protein-ligand interface, the solvent-accessible surface (SAS) of nonpolar parts of the ligand, and the number of close contacts between nonhydrogen-bonded polar atoms of the ligand and the protein. These four terms were used to filter out the majority of the calculated solutions and to rescore the remaining ones. On a test set of 32 protein-ligand complexes, this protocol significantly improves the accuracy of the structure predictions.

GENFOLD: a genetic algorithm for folding protein structures using NMR restraints

We report the development and validation of the program GENFOLD, a genetic algorithm that calculates protein structures using restraints obtained from NMR, such as distances derived from nuclear Overhauser effects, and dihedral angles derived from coupling constants. The program has been tested on three proteins: the POU domain (a small three-helix DNA-binding protein), bovine pancreatic trypsin inhibitor (BPTI), and the starch-binding domain from Aspergillus niger glucoamylase I, a 108-residue beta-sheet protein. Structures were calculated for each protein using published NMR restraints. In addition, structures were calculated for BPTI using artificial restraints generated from a high-resolution crystal structure. In all cases the fittest calculated structures were close to the target structure, and could be refined to structures indistinguishable from the target structures by means of a low-temperature simulated annealing refinement. The effectiveness of the program is similar to that of distance geometry and simulated annealing methods, and it is capable of using a very wide range of restraints as input. It can thus be readily extended to the calculation of structures of large proteins, for which few NOE restraints may be available.

Comparison of protein surfaces using a genetic algorithm

A genetic algorithm (GA) is described which is used to compare the solvent-accessible surfaces of two proteins or fragments of proteins, represented by a dot surface calculated using the Connolly algorithm. The GA is used to move one surface relative to the other to locate the most similar surface region between the two. The matching process is enhanced by the use of the surface normals and shape terms provided by the Connolly program and also by a simple hydrogen-bonding descriptor and an additional shape descriptor. The algorithm has been tested in applications ranging from the comparison of small surface patches to the comparison of whole protein surfaces, and it has performed correctly in all cases. Examples of the matches are given and a quantitative analysis of the quality of the matches is performed. A number of possible future enhancements to the program are described which would allow the GA to be used for more complex surface comparisons.

Multiple automatic base selection: protein-ligand docking based on incremental construction without manual intervention

A possible way of tackling the molecular docking problem arising in computer-aided drug design is the use of the incremental construction method. This method consists of three steps: the selection of a part of a molecule, a so-called base fragment, the placement of the base fragment into the active site of a protein, and the subsequent reconstruction of the complete drug molecule. Assuming that a part of a drug molecule is known, which is specific enough to be a good base fragment, the method is proven to be successful for a large set of docking examples. In addition, it leads to the fastest algorithms for flexible docking published so far. In most real-world applications of docking, large sets of ligands have to be tested for affinity to a given protein. Thus, manual selection of a base fragment is not practical. On the other hand, the selection of a base fragment is critical in that only few selections lead to a low-energy structure. We overcome this limitation by selecting a representative set of base fragments instead of a single one. In this paper, we present a set of rules and algorithms to automate this selection. In addition, we extend the incremental construction method to deal with multiple fragmentations of the drug molecule. Our results show that with multiple automated base selection, the quality of the docking predictions is almost as good as with one manually preselected base fragment. In addition, the set of solutions is more diverse and alternative binding modes with low scores are found. Although the run time of the overall algorithm increases, the method remains fast enough to search through large ligand data sets.

A comparison of heuristic search algorithms for molecular docking

This paper describes the implementation and comparison of four heuristic search algorithms (genetic algorithm, evolutionary programming, simulated annealing and tabu search) and a random search procedure for flexible molecular docking. To our knowledge, this is the first application of the tabu search algorithm in this area. The algorithms are compared using a recently described fast molecular recognition potential function and a diverse set of five protein-ligand systems. Statistical analysis of the results indicates that overall the genetic algorithm performs best in terms of the median energy of the solutions located. However, tabu search shows a better performance in terms of locating solutions close to the crystallographic ligand conformation. These results suggest that a hybrid search algorithm may give superior results to any of the algorithms alone.