Biomedical subjects

M Rarey

Publications and source records attributed to M Rarey.

10 recordsLinked to original sources

PubMed1999

Two-stage method for protein-ligand docking.

A two-stage method for the computational prediction of the structure of protein-ligand complexes is proposed. Given an experimentally determined structure of the protein, in the first stage a large number of plausible ligand conformations is generated using the fast docking algorithm FlexX. In the second stage these conformations are minimized and reranked using a method based on a classical force field. The two-stage method is tested for 10 different protein-ligand complexes. For 9 of them experimentally determined structures are known. It turns out that the two-stage method strongly improves the predictive power as compared to that of the fast docking stage alone. The tenth case is a bona fide prediction of a complex of thrombin with a new inhibitor for which no experimentally determined structure is available so far.

Algorithms↗

PubMed1999

The particle concept: placing discrete water molecules during protein-ligand docking predictions.

Water is known to play a significant role in the formation of protein-ligand complexes. In this paper, we focus on the influence of water molecules on the structure of protein-ligand complexes. We present an algorithmic approach, called the particle concept, for integrating the placement of single water molecules in the docking algorithm of FLEXX. FLEXX is an incremental construction approach to ligand docking consisting of three phases: the selection of base fragments, the placement of the base fragments, and the incremental reconstruction of the ligand inside the active site of a protein. The goal of the extension is to find water molecules at favorable places in the protein-ligand interface which may guide the placement of the ligand. In a preprocessing phase, favorable positions of water molecules inside the active site are calculated and stored in a list of possible water positions. During the incremental construction phase, water molecules are placed at the precomputed positions if they can form additional hydrogen bonds to the ligand. Steric constraints resulting from the water molecules as well as the geometry of the hydrogen bonds are used to optimize the ligand orientation in the active site during the reconstruction process. We have tested the particle concept on a series of 200 protein-ligand complexes. Although the average improvement of the prediction results is minor, we were able to predict water molecules between the protein and the ligand correctly in several cases. For instance in the case of HIV-1 protease, where a single water molecule between the protein and the ligand is known to be of importance in complex formation, significant improvements can be achieved.

Algorithms↗

PubMed1999

Docking of hydrophobic ligands with interaction-based matching algorithms.

MOTIVATION: Matching of chemical interacting groups is a common concept for docking and fragment placement algorithms in computer-aided drug design. These algorithms have been proven to be reliable and fast if at least a certain number of hydrogen bonds or salt bridges occur. However, the algorithms typically run into problems if hydrophobic fragments or ligands should be placed. In order to dock hydrophobic fragments without significant loss of computational efficiency, we have extended the interaction model and placement algorithms in our docking tool FlexX. The concept of multi-level interactions is introduced into the algorithms for automatic selection and placement of base fragments. RESULTS: With the multi-level interaction model and the corresponding algorithmic extensions, we were able to improve the overall performance of FlexX significantly. We tested the approach with a set of 200 protein-ligand complexes taken from the Brookhaven Protein Data Bank (PDB). The number of test cases which can be docked within 1.5 A RMSD from the crystal structure can be increased from 58 to 64%. The performance gain is paid for by an increase in computation time from 73 to 91 s on average per protein-ligand complex. AVAILABILITY: The FlexX molecular docking software is available for UNIX platforms IRIX, Solaris and Linux. See http://cartan.gmd.de/FlexX for additional information.

Algorithms↗

PubMed1998

Feature trees: a new molecular similarity measure based on tree matching.

In this paper we present a new method for evaluating molecular similarity between small organic compounds. Instead of a linear representation like fingerprints, a more complex description, a feature tree, is calculated for a molecule. A feature tree represents hydrophobic fragments and functional groups of the molecule and the way these groups are linked together. Each node in the tree is labeled with a set of features representing chemical properties of the part of the molecule corresponding to the node. The comparison of feature trees is based on matching subtrees of two feature trees onto each other. Two algorithms for tackling the matching problem are described throughout this paper. On a dataset of about 1000 molecules, we demonstrate the ability of our approach to identify molecules belonging to the same class of inhibitors. With a second dataset of 58 molecules with known binding modes taken from the Brookhaven Protein Data Bank, we show that the matchings produced by our algorithms are compatible with the relative orientation of the molecules in the active site in 61% of the test cases. The average computation time for a pair comparison is about 50 ms on a current workstation.

Algorithms↗

PubMed1997

CASP2 experiences with docking flexible ligands using FlexX.

We have applied our docking program FlexX to all eight CASP2 targets involving protein complexes with small ligands. Of the seven targets that were kept in the CASP2 experiment, we could solve two. We found important parts of the solution in four other examples, and were unsuccessful on the remaining example. This paper discusses all predictions in detail. Each of our prediction runs took just a few minutes of computer time on a standard workstation and could thus be demonstrated in real time at the CASP meeting. We believe that this speed is the prime strength of our program FlexX. In quality, our predictions are competitive with those produced by other predictors. The experiment showed that possible objectives of improvement of the FlexX program are to incorporate relevant aspects of receptor flexibility, deal with water molecules in the receptor pocket, allow for a postoptimization to refine favorable complexes, and improve the scoring function.

Amiloride↗

PubMed1997

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.

Automation↗

PubMed1996

A fast flexible docking method using an incremental construction algorithm.

We present an automatic method for docking organic ligands into protein binding sites. The method can be used in the design process of specific protein ligands. It combines an appropriate model of the physico-chemical properties of the docked molecules with efficient methods for sampling the conformational space of the ligand. If the ligand is flexible, it can adopt a large variety of different conformations. Each such minimum in conformational space presents a potential candidate for the conformation of the ligand in the complexed state. Our docking method samples the conformation space of the ligand on the basis of a discrete model and uses a tree-search technique for placing the ligand incrementally into the active site. For placing the first fragment of the ligand into the protein, we use hashing techniques adapted from computer vision. The incremental construction algorithm is based on a greedy strategy combined with efficient methods for overlap detection and for the search of new interactions. We present results on 19 complexes of which the binding geometry has been crystallographically determined. All considered ligands are docked in at most three minutes on a current workstation. The experimentally observed binding mode of the ligand is reproduced with 0.5 to 1.2 A rms deviation. It is almost always found among the highest-ranking conformations computed.

Algorithms↗

PubMed1996

Placement of medium-sized molecular fragments into active sites of proteins.

We present an algorithm for placing molecular fragments into the active site of a receptor. A molecular fragment is defined as a connected part of a molecule containing only complete ring systems. The algorithm is part of a docking tool, called FLEXX, which is currently under development at GMD. The overall goal is to provide means of automatically computing low-energy conformations of the ligand within the active site, with an accuracy approaching the limitations of experimental methods for resolving molecular structures and within a run time that allows for docking large sets of ligands. The methods by which we plan to achieve this goal are the explicit exploitation of molecular flexibility of the ligand and the incorporation of physicochemical properties of the molecules. The algorithm for fragment placement, which is the topic of this paper, is based on pattern recognition techniques and is able to predict a small set of possible positions of a molecular fragment with low flexibility within seconds on a workstation. In most cases, a placement with rms deviation below 1.0 A with respect to the X-ray structure is found among the 10 highest ranking solutions, assuming that the receptor is given in the bound conformation.

Algorithms↗

PubMed1996

Computational methods for biomolecular docking.

With the rapidly increasing amount of molecular biological data available, the computer-based analysis of molecular interactions becomes more and more feasible. Methods for computer-aided molecular docking have to include a reasonably accurate model of energy and must be able to deal with the combinatorial complexity incurred by the molecular flexibility of the docking partners. In both respects, recent years have seen substantial progress.

Databases, Factual↗

PubMed1995

Time-efficient docking of flexible ligands into active sites of proteins.

We present an algorithm for placing flexible molecules in active sites of proteins. The two major goals in the development of our docking program, called FLEXX, are the explicit exploitation of molecular flexibility of the ligand and the development of a model of the docking process that includes the physico-chemical properties of the molecules. The algorithm consists of three phases: The selection of a base fragment, the placement of the base fragment in the active site, and the incremental construction of the ligand inside the active site. Except for the selection of the base fragment, the algorithm runs without manual intervention. The algorithm is tested by reproducing 11 receptor-ligand complexes known from X-ray crystallography. In all cases, the algorithm predicts a placement of the ligand which is similar to the crystal structure (about 1.5 A RMS deviation or less) in a few minutes on a workstation, assuming that the receptor is given in the bound conformation.

Algorithms↗