Biomedical subjects

M L Verdonk

Publications and source records attributed to M L Verdonk.

9 recordsLinked to original sources

PubMed2001

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.

Databases, Factual↗

PubMed2001

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.

Algorithms↗

PubMed2001

Calculating the knowledge-based similarity of functional groups using crystallographic data.

A knowledge-based method for calculating the similarity of functional groups is described and validated. The method is based on experimental information derived from small molecule crystal structures. These data are used in the form of scatterplots that show the likelihood of a non-bonded interaction being formed between functional group A (the 'central group') and functional group B (the 'contact group' or 'probe'). The scatterplots are converted into three-dimensional maps that show the propensity of the probe at different positions around the central group. Here we describe how to calculate the similarity of a pair of central groups based on these maps. The similarity method is validated using bioisosteric functional group pairs identified in the Bioster database and Relibase. The Bioster database is a critical compilation of thousands of bioisosteric molecule pairs, including drugs, enzyme inhibitors and agrochemicals. Relibase is an object-oriented database containing structural data about protein-ligand interactions. The distributions of the similarities of the bioisosteric functional group pairs are compared with similarities for all the possible pairs in IsoStar, and are found to be significantly different. Enrichment factors are also calculated showing the similarity method is statistically significantly better than random in predicting bioisosteric functional group pairs.

Artificial Intelligence↗

PubMed2000

Simple knowledge-based descriptors to predict protein-ligand interactions. methodology and validation.

A new type of shape descriptor is proposed to describe the spatial orientation for non-covalent interactions. It is built from simple, anisotropic Gaussian contributions that are parameterised by 10 adjustable values. The descriptors have been used to fit propensity distributions derived from scatter data stored in the IsoStar database. This database holds composite pictures of possible interaction geometries between a common central group and various interacting moieties, as extracted from small-molecule crystal structures. These distributions can be related to probabilities for the occurrence of certain interaction geometries among different functional groups. A fitting procedure is described that generates the descriptors in a fully automated way. For this purpose, we apply a similarity index that is tailored to the problem, the Split Hodgkin Index. It accounts for the similarity in regions of either high or low propensity in a separate way. Although dependent on the division into these two subregions, the index is robust and performs better than the regular Hodgkin index. The reliability and coverage of the fitted descriptors was assessed using SuperStar. SuperStar usually operates on the raw IsoStar data to calculate propensity distributions, e.g., for a binding site in a protein. For our purpose we modified the code to have it operate on our descriptors instead. This resulted in a substantial reduction in calculation time (factor of five to eight) compared to the original implementation. A validation procedure was performed on a set of 130 protein-ligand complexes, using four representative interacting probes to map the properties of the various binding sites: ammonium nitrogen, alcohol oxygen, carbonyl oxygen, and methyl carbon. The predicted 'hot spots' for the binding of these probes were compared to the actual arrangement of ligand atoms in experimentally determined protein-ligand complexes. Results indicate that the version of SuperStar that applies to our descriptors is capable to predict the above-mentioned atom types in ligands correctly with success rates of 59% and 74%, respectively, for all ligand atoms (regardless of their solvent accessibility), and a subset of solvent-inaccessible ones. If not only exact atom-type matches are counted, but also those that identify ligand atoms of similar physicochemical properties, the prediction rates rise to 75% and 89%. These rates are close to those obtained by the original SuperStar method (being 67% and 82%, respectively, for the prediction of exact matching atom types, and 81% and 91% in the case of predicting similar atom types).

Hydrogen Bonding↗

PubMed1999

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.

Artificial Intelligence↗

PubMed1998

Directional preferences of intermolecular contacts to hydrophobic groups.

Analysis of data from the IsoStar library shows that many hydrophobic groups exhibit strikingly strong directional preferences in their intermolecular interactions. Specific directional interactions may occur because of the large quadrupole moments of many aromatic ring systems, the residual electropositive charge on most carbon-bound H atoms and the effects of polarization on soft hetero-ring atoms such as sulfur. In consequence, the binding of a hydrophobic group to a hydrophobic protein cavity is not simply a matter of matching complementary shapes. Directional preferences of nonbonded contacts to hydrophobic groups may need to be taken into account in parameterizing the next generation of protein-ligand docking programs.

Databases, Factual↗

PubMed1997

Structure and serotonin 5-HT2C receptor activity of ortho- and meta-substituted phenylpiperazines.

The structural characteristics of ortho- and meta-substituted phenylpiperazines have been investigated in order to understand their actions at the serotonin 5-HT2C receptor. The crystal structures of the 4-methylated analogues of two phenylpiperazines that are already known as 5-HT2C ligands, 1-(1-naphthyl)-4-methylpiperazine (1NMP) and 1-[(3-trifluoromethyl)phenyl]-4-methylpiperazine (TFMPMP), and those of two novel 5-HT2C ligands, 1-(2-methoxyphenyl)piperazine (oMPP) and 1-(3-methoxyphenyl)piperazine (mMPP), are determined. Molecular mechanics calculations are performed to calculate the energy profiles of six phenylpiperazines for rotation about the central phenyl-nitrogen bond. The activities of several phenylpiperazines, in combination with their crystal structures and conformational characteristics, lead to the hypothesis that the conformation for which the piperazine ring and the phenyl ring are approximately co-planar should be the 5-HT2C receptor 'activating' conformation. This hypothesis is then used to predict the activities of the two novel 5-HT2C ligands oMPP and mMPP. oMPP is predicted to be an antagonist at this receptor, whereas mMPP is predicted to be an agonist. As this prediction was confirmed by in vitro and in vivo tests, the proposed conformation is very likely to be responsible for the activation of the 5-HT2C receptor.

Piperazines↗

PubMed1997

IsoStar: a library of information about nonbonded interactions.

Crystallographic and theoretical (ab initio) data on intermolecular nonbonded interactions have been gathered together in a computerised library ('IsoStar'). The library contains information about the nonbonded contacts formed by some 250 chemical groupings. The data can be displayed visually and used to aid protein-ligand docking or the identification of bioisosteric replacements. Data from the library show that there is great variability in the geometrical preferences of different types of hydrogen bonds, although in general there is a tendency for H-bonds to form along lone-pair directions. The H-bond acceptor abilities of oxygen and sulphur atoms are highly dependent on intramolecular environments. The nonbonded contacts formed by many hydrophobic groups show surprisingly strong directional preferences. Many unusual nonbonded interactions are to be found in the library and are of potential value for designing novel biologically active molecules.

Biochemical Phenomena↗

PubMed1993

Stereochemistry of charged nitrogen-aromatic interactions and its involvement in ligand-receptor binding.

Recently, new evidence was found for the involvement of charged nitrogen-aromatic interactions in ligand-receptor binding. In this study we report two favourable orientations of a phenyl ring with respect to a R-N+(CH3)3 group, based on crystal structure statistics from the Cambridge Structural Database. In the first orientation, the phenyl ring is situated in between the substituents at about 4.5 A from the nitrogen atom, and the ring is approximately oriented on the sphere around the nitrogen atom. In the second orientation, the phenyl ring is situated in the same direction as one of the N-C bonds at about 6.0 A from the nitrogen atom, and the ring is tilted with respect to the sphere around the nitrogen atom. The same two orientations were also found in the crystal structures of three ligand-receptor complexes, which implies that these orientations probably play a major role in molecular recognition mechanisms.

Benzene Derivatives↗