Biomedical subjects

M Hendlich

Publications and source records attributed to M Hendlich.

7 recordsLinked to original sources

PubMed2000

Knowledge-based scoring function to predict protein-ligand interactions.

The development and validation of a new knowledge-based scoring function (DrugScore) to describe the binding geometry of ligands in proteins is presented. It discriminates efficiently between well-docked ligand binding modes (root-mean-square deviation <2.0 A with respect to a crystallographically determined reference complex) and those largely deviating from the native structure, e.g. generated by computer docking programs. Structural information is extracted from crystallographically determined protein-ligand complexes using ReLiBase and converted into distance-dependent pair-preferences and solvent-accessible surface (SAS) dependent singlet preferences for protein and ligand atoms. Definition of an appropriate reference state and accounting for inaccuracies inherently present in experimental data is required to achieve good predictive power. The sum of the pair preferences and the singlet preferences is calculated based on the 3D structure of protein-ligand binding modes generated by docking tools. For two test sets of 91 and 68 protein-ligand complexes, taken from the Protein Data Bank (PDB), the calculated score recognizes poses generated by FlexX deviating <2 A from the crystal structure on rank 1 in three quarters of all possible cases. Compared to FlexX, this is a substantial improvement. For ligand geometries generated by DOCK, DrugScore is superior to the "chemical scoring" implemented into this tool, while comparable results are obtained using the "energy scoring" in DOCK. None of the presently known scoring functions achieves comparable power to extract binding modes in agreement with experiment. It is fast to compute, regards implicitly solvation and entropy contributions and produces correctly the geometry of directional interactions. Small deviations in the 3D structure are tolerated and, since only contacts to non-hydrogen atoms are regarded, it is independent from assumptions of protonation states.

Artificial Intelligence↗

PubMed1998

Databases for protein-ligand complexes.

Recent advances in experimental techniques have led to an enormous explosion of available data about protein-ligand complexes. To exploit the information that is hidden in these large data, collection tools for managing and accessing huge data collections are needed. This paper discusses databases for protein-ligand data which are accessible via the World Wide Web. A strong focus is placed on the ReLiBase database system which is a new three-dimensional database for storing and analysing structures of protein-ligand complexes currently deposited in the Brookhaven Protein Data Bank (PDB). ReLiBase contains efficient query tools for identifying and analysing ligands and protein-ligand complexes. Its application for structure-based drug design is illustrated.

Databases, Factual↗

PubMed1997

LIGSITE: automatic and efficient detection of potential small molecule-binding sites in proteins.

LIGSITE is a new program for the automatic and time-efficient detection of pockets on the surface of proteins that may act as binding sites for small molecule ligands. Pockets are identified with a series of simple operations on a cubic grid. Using a set of receptor-ligand complexes we show that LIGSITE is able to identify the binding sites of small molecule ligands with high precision. The main advantage of LIGSITE is its speed. Typical search times are in the range of 5 to 20 s for medium-sized proteins. LIGSITE is therefore well suited for identification of pockets in large sets of proteins (e.g., protein families) for comparative studies. For graphical display LIGSITE produces VRML representations of the protein-ligand complex and the binding site for display with a VRML viewer such as WebSpace from SGI.

Algorithms↗

PubMed1996

PRODRG, a program for generating molecular topologies and unique molecular descriptors from coordinates of small molecules.

A software package is described that operates on small molecules observed in the PDB collection of protein structures. Molecular topology files for many molecular modeling programs can be generated automatically. The three-dimensional coordinates of small molecules can be converted to molecular descriptor strings that encode them uniquely in order to enable small-molecule recognition, despite high variability in atom and molecule nomenclature. From this descriptor a plausible 3D structure can be regenerated using energy minimisation. Alternatively, an ensemble of structures can be generated using a distance-geometry-based algorithm.

Ligands↗

PubMed1995

Constituting a receptor-ligand information base from quality-enriched data.

Many different resources are needed for analyzing relevant experimental data in drug design. Currently this data is difficult to access, because it is stored in heterogeneous databases, spread over many platforms, poorly interconnected, incomplete, erroneous, or just not electronically available. In order to establish a high quality database for drug design we have developed a new demand-driven methodology for integrating and semantically enriching heterogeneous data from different research areas and for migrating the data into an object-oriented database management system. In this way we have established a database containing well-prepared, relevant data needed for drug design and offering the advantages of modern database technology, like a comprehensive object-oriented data model, a flexible declarative query language and support for persistent storage and sharing of data in a multi-user environment.

Amino Acid Sequence↗

PubMed1992

Assembly of polypeptide and protein backbone conformations from low energy ensembles of short fragments: development of strategies and construction of models for myoglobin, lysozyme, and thymosin beta 4.

Recently we developed methods for the construction of knowledge-based mean fields from a data base of known protein structures. As shown previously, this approach can be used to calculate ensembles of probable conformations for short fragments of polypeptide chains. Here we develop procedures for the assembly of short fragments to complete three-dimensional models of polypeptide chains. The amino acid sequence of a given protein is decomposed into all possible overlapping fragments of a given length, and an ensemble of probable conformations is calculated for each fragment. The fragments are assembled to a complete model by choosing appropriate conformations from the individual ensembles and by averaging over equivalent angles. Finally a consistent model is obtained by rebuilding the conformation from the average angles. From the average angles the local variability of the structure can be calculated, which is a useful criterion for the reliability of the model. The procedure is applied to the calculation of the local backbone conformations of myoglobin and lysozyme whose structures have been solved by X-ray analysis and thymosin beta 4, a polypeptide of 43 amino acid residues whose structure was recently investigated by NMR spectroscopy. We demonstrate that substantial fractions of the calculated local backbone conformations are similar to the experimentally determined structures.

Amino Acid Sequence↗

PubMed1990

Identification of native protein folds amongst a large number of incorrect models. The calculation of low energy conformations from potentials of mean force.

We present an approach that is able to detect native folds amongst a large number of non-native conformations. The method is based on the compilation of potentials of mean force of the interactions of the C beta atoms of all amino acid pairs from a database of known three-dimensional protein structures. These potentials are used to calculate the conformational energy of amino acid sequences in a number of different folds. For a substantial number of proteins we find that the conformational energy of the native state is lowest amongst the alternatives. Exceptions are proteins containing large prosthetic groups, Fe-S clusters or polypeptide chains that do not adopt globular folds. We discuss briefly potential applications in various fields of protein structural research.

Animals↗