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This paper discusses algorithmic techniques for measuring the degree of similarity between pairs of three-dimensional (3-D) chemical molecules represented by interatomic distance matrices. A comparison of four methods for the calculation of 3-D structural similarity suggests that the most effective one is a procedure that identifies pairs of atoms, one from each of the molecules that are being compared, that lie at the center of geometrically-related volumes of 3-D space. This atom mapping method enables the calculation of a wide range of types of intermolecular similarity coefficient, including measures that are based on physicochemical data. Massively-parallel implementations of the method are discussed, using the AMT Distributed Array Processor, that achieve a substantial increase in performance when compared with a sequential implementation on a UNIX workstation. Current work involves the use of angular information and the extension of the method to field-based similarity searching. Similarity searching in 3-D macromolecules is effected by the use of a maximal common subgraph (MCS) isomorphism algorithm with a novel, graph-based representation of the tertiary structures of proteins. This algorithm is being used to identify similarities between the 3-D structures of proteins in the Brookhaven Protein Data Bank; its use is exemplified by searches involving the NAD-binding fold motif.

Trimethyltin chloride (TMT) was given to Syrian hamsters, gerbils and marmosets, and the changes in the brain were studied 1 day to 7 weeks later by light and electron microscopy. Within the marmoset brain, TMT was found to be uniformly distributed, similar to that in the rat. In all three species, signs of poisoning included whole-body tremors and prostration, while death might occur in 3-4 days; in marmosets ataxia, agitation, aggression and occasional fits were also observed. Bilateral symmetrical neuronal necrosis and chromatolysis were seen in the majority, which involved the hippocampus, pyriform cortex, amygdaloid nucleus, neocortex, various brain stem nuclei and in marmosets the retina. The probably lethal dose of TMT in all three species is approximately 3 mg kg-1, while the LD50 for the rat is 12.6 mg kg-1. The lower figure is probably related to lack of binding to haemoglobin in contrast to the binding in the rat. TMT does not bind to human haemoglobin and thus the predicted lethal dose for humans may be about 3 mg kg-1 (15.1 mumol kg-1), while the dose required to produce neuronal damage could well be less.

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iJsing 3-D searching techniques based on algorithms derived from graph theory we have established a striking structural similarity between the structure of bovine carboxypeptidase A and that of the C-terminal domain of bovine lcucine aminopeptidasc. There is no signilicant sequence homology between the aminopeptidases and the carboxypeptidases but the strong structural relationship detected in this complex fold suggesls that there may be a very remote divergent evolutionary relationship between these two enzyme classes.

Using 3D searching techniques based on algorithms derived from graph theory, we have established two previously unreported structural similarities involving the ribonuclease H (RNase H) domain of HIV-l reverse transcriptase (RT). First. we report that there is a strong similarity between the 3D folds of the RNase H domain of RT and the 'ATPase folds' of hexokinase, the 70 kDa heat-shock cognate protem and actin. Like RNase H, these enzymes are involved in nucleotide binding and metal ion-catalysed cleavage of a phosphodiester bond. Similarities of the folding motif and the position of the metal-bmding site in these enzymes suggest possible functional analogies and evolutionary relationships with RNase H. Second, we find there is a strong resemblance between the folds of the RNase H domain and of the p66 and ~51 'connection' domains of RT. It is possible that this striking similarity within the RT structure indicates a possible ancestral gene doubling event. The stmilarity may also indicate that the connection domains possess functional roles in addition to those previously suggested, and they may therefore represent a further target for the design of therapeutic agents.

Using searching techniques based on algorithms derived from graph theory, we have established a similarity between a 3-dimensional cluster of side chains implicated in drug binding in influenza sialidase and side chains involved in isocitrate binding in Escherichia coli isocitrate dehydrogenase. The possible implications of the use of such comparative methods in drug design are discussed.Keywords: binding sites; drug design; graph theory; influenza sialidase; isocitrate dehydrogenase; structure similarity An important factor in the development of molecular biology has been the availability of computational tools for the detection of similarities in the 1-dimensional sequences of proteins and nucleic acids (Lesk, 1988). It is similarly of the greatest importance to be able to detect structural analogies within the rapidly growing database of 3-dimensional protein and nucleic acid structures in order to enhance understanding of structure/ function relationships in biological macromolecules. In this communication we describe the use of a novel program, ASSAM (Artymiuk et al., 1994), which uses algorithms derived from graph theory, in order to establish a thought-provoking analogy between binding sites in the active sites of influenza sialidase and isocitrate dehydrogenase. This analysis suggests that such comparative studies may represent another valuable approach to the rational design of novel inhibitors. Recently, von Itzstein et al. (1993) described the design of potential anti-influenza drugs, which operate by binding to a specific site on the influenza sialidase molecule, thereby inhibiting it. This was achieved using a combination of computer-assisted manual examination of the active-site structure with sialic acid and sialic acid analogues bound (Chong et al., 1992;Varghese et al., 1992), together with the use of the GRID program (GoodReprint requests to: Peter J.