Simon K. Kearsley

Why do we need so many chemical similarity search methods

Computational tools to search chemical structure databases are essential to finding leads early in a drug discovery project. Similarity methods are among the most diverse and most useful. We will present some lessons we have gathered over many years experience with in-house methods on several therapeutic problems. The effectiveness of any similarity method can vary greatly from one biological activity to another in a way that is difficult to predict. Also, any two methods tend to select different subsets of actives from a database, so it is advisable to use several search methods where possible.

CHEMICAL SIMILARITY USING PHYSIOCHEMICAL PROPERTY DESCRIPTORS

Similarity searches using topological descriptors have proved extremely useful in aiding large-scale screening. We describe alternative forms of the atom pair (Carhart et al. J. Chem. Inf. Comput. Sci. 1985, 25, 64−73.) and topological torsion (Nilakantan et al. J. Chem. Inf. Comput. Sci. 1987, 27, 82−85.) descriptors that use physiochemical atom types. These types are based on binding property class, atomic log P contribution, and partial atomic charges. The new descriptors are meant to be more “fuzzy” than the original descriptors. We propose objective criteria for determining how effective one descriptor is versus another in selecting active compounds from large databases. Using these criteria, we run similarity searches over the Derwent Standard Drug File with ten typical druglike probes. The new descriptors are not as good as the original descriptors in selecting actives if one considers the average over all probes, but the new descriptors do better for several individual probes. Generally we find th...

FLOG: A system to select ‘quasi-flexible’ ligands complementary to a receptor of known three-dimensional structure

SummaryWe present a system, FLOG (Flexible Ligands Oriented on Grid), that searches a database of 3D coordinates to find molecules complementary to a macromolecular receptor of known 3D structure. The philosophy of FLOG is similar to that reported for DOCK [Shoichet, B.K. et al., J. Comput. Chem., 13 (1992) 380]. In common with that system, we use a match center representation of the volume of the binding cavity and we use a clique-finding algorithm to generate trial orientations of each candidate ligand in the binding site. Also we use a grid representation of the receptor to assess the fit of each orientation. We have introduced a number of novel features within this paradigm. First, we address ligand flexibility by including up to 25 explicit conformations of each structure in our databases. Nonhydrogen atoms in each database entry are assigned one of seven atom types (anion, cation, donor, acceptor, polar, hydrophobic and other) based on their local bonded chemical environments. Second, we have devised a new grid-based scoring function compatible with this ‘heavy atom’ representation of the ligands. This includes several potentials (electrostatic, hydrogen bonding, hydrophobic and van der Waals) calculated from the location of the receptor atoms. Third, we have improved the fitting stage of the search. Initial dockings are generated with a more efficient clique-finding algorithm. This new algorithm includes the concept of ‘essential points’, match centers that must be paired with a ligand atom. Also, we introduce the use of a rapid simplex-based rigid-body optimizer to refine the orientations. We demonstrate, using dihydrofolate reductase as a sample receptor, that the FLOG system can select known inhibitors from a large database of drug-like compounds.

An alternative method for the alignment of molecular structures: Maximizing electrostatic and steric overlap

The SEAL method has been developed which will optimize the alignment of two three-dimensional structures using their atomic partial charges and steric volumes as factors. In addition, this method will perform the superimposition many times using randomly generated starting configurations and keep only the best unique results based on the value of the alignment function. The computer generated alignments of methotrexate and dihydrofolic acid are compared with the alignments found in the active site of Dihydrofolate Reductase. The marine neurotoxins, saxitoxin and tetrodotoxin, are aligned and the results compared to other alignment techniques. The relationship of the SEAL alignments to the potential field error is explored. Program on disk.

CHEMICAL SIMILARITY USING GEOMETRIC ATOM PAIR DESCRIPTORS

Similarity searches using topological descriptors have proved extremely useful in aiding large-scale screening. In this paper we describe the geometric atom pair, the 3D analog of the topological atom pair descriptor (Carhart et al. J. Chem. Inf. Comput. Sci. 1985, 25, 64−73). We show the results of geometric similarity searches using the CONCORD-build structures of typical small druglike molecules as probes. The database to be searched is a 3D version of the Derwent Standard Drug File that contains an average of 10 explicit conformations per compound. Using objective criteria for determining how good a descriptor is in selecting active compounds from large databases, we compare the results using the geometric versus the topological atom pair. We find that geometric and topological atom pairs are about equally effective in selecting active compounds from large databases. How the two types of descriptors rank active compounds is generally about the same as well, but occasionally active compounds will be se...

Flexibases: A way to enhance the use of molecular docking methods

SummarySpecially expanded databases containing three-dimensional structures are created to enhance the utility of docking methods to find new leads, i.e., active compounds of pharmacological interest. The expansion is based on the automatic generation of a set of maximally dissimilar conformations. The ligand receptor system of methotrexate and dihydrofolate reductase is used to demonstrate the feasibility of creating flexibases and their utility in docking studies.

Comparison of knowledge-based and distance geometry approaches for generation of molecular conformations.

A knowledge-based approach for generating conformations of molecules has been developed. The method described here provides a good sampling of the molecules conformational space by restricting the generated conformations to those consistent with the reference database. The present approach, internally named et for enumerate torsions, differs from previous database-mining approaches by employing a library of much larger substructures while treating open chains, rings, and combinations of chains and rings in the same manner. In addition to knowledge in the form of observed torsion angles, some knowledge from the medicinal chemist is captured in the form of which substructures are identified. The knowledge-based approach is compared to Blaney et al.s distance geometry (DG) algorithm for sampling the conformational space of molecules. The structures of 113 protein-bound molecules, determined by X-ray crystallography, were used to compare the methods. The present knowledge-based approach (i) generates conformations closer to the experimentally determined conformation, (ii) generates them sooner, and (iii) is significantly faster than the DG method.

Designing targeted libraries with genetic algorithms11Color Plates for this article are on page 525.

Abstract In combinatorial synthesis, molecules are assembled by linking chemically similar fragments. Because the number of available chemical fragments often greatly exceeds the number that can be used in one synthetic experiment, one needs a rational method for choosing a subset of desirable fragments. If a combinatorial library is to be targeted against a particular biological activity, virtual screening methods can be used to predict which molecules in a virtual library are most likely to be active. When the number of possible molecules in a virtual library is very large, genetic algorithms (GAs) or simulated annealing can be used to quickly find high-scoring molecules by sampling a small subset of the total combinatorial space. We previously demonstrated how a GA can be used to select a subset of fragments for a combinatorial library, and we used topology-based methods of scoring. Here we extend that earlier work in three ways. (1) We demonstrate use of the GA with 3D scoring methods developed in our laboratory. (2) We show that the approach of assembling libraries from fragments in high-scoring molecules is a reasonable one. (3) We compare results from a library-based GA to those from a molecule-based GA.

Dynamic control of allosteric antagonism of leukocyte function antigen-1 and intercellular adhesion molecule-1 interaction.

Leukocyte function associated antigen‐1 (LFA‐1) plays a critical role in T cell migration and has been recognized as a therapeutic target for immune disorders. Several classes of small molecule antagonists have been developed to block LFA‐1 interaction with intercellular adhesion molecule‐1 (ICAM‐1). Recent structural studies show that the antagonists bind to an allosteric site in the I‐domain of LFA‐1. However, it is not yet clear how these small molecules work as antagonists since no significant conformational change is observed in the I‐domain–antagonist complex structures. Here we present a computational study suggesting how these allosteric antagonists affect the dynamics of the I‐domain. The lowest frequency vibrational mode calculated from an LFA‐1 I‐domain structure shows large scale “coil‐down” motion of the C‐terminal α7 helix, which may lead to the open form of the I‐domain. The presence of an allosteric antagonist greatly reduces this motion of the α7 helix as well as other parts of the I‐domain. Thus, our study suggests that allosteric antagonists work by eliminating breathing motion that leads to the open conformation of the I‐domain. Proteins 2006.

Using similarity searches over databases of estimated 13C NMR spectra for structure identification of natural product compounds

Abstract Structure elucidation for natural product compounds is assisted by making similarity comparisons between the uncharacterized experimental 13C NMR spectrum with relevant databases of estimated spectra. Databases of estimated spectra are deduced from a small set of assigned structures using HOSE codes. Using spectra estimated from structures circumvents problems of inconsistent, incomplete, missing or irrelevant data. It also enables rapid generation of reasonably sized databases that are unavailable from commercial sources. We validate the similarity method theoretically by analyzing what can be best expected from a match of an estimated set of peaks to the experimental spectrum. We also show by example that the method is successful when used in the laboratory.