Structure-activity relationships derived by machine learning: the use of atoms and their bond connectivities to predict mutagenicity by inductive logic programming.

We present a general approach to forming structure-activity relationships (SARs). This approach is based on representing chemical structure by atoms and their bond connectivities in combination with the inductive logic programming (ILP) algorithm PROGOL. Existing SAR methods describe chemical structure by using attributes which are general properties of an object. It is not possible to map chemical structure directly to attribute-based descriptions, as such descriptions have no internal organization. A more natural and general way to describe chemical structure is to use a relational description, where the internal construction of the description maps that of the object described. Our atom and bond connectivities representation is a relational description. ILP algorithms can form SARs with relational descriptions. We have tested the relational approach by investigating the SARs of 230 aromatic and heteroaromatic nitro compounds. These compounds had been split previously into two subsets, 188 compounds that were amenable to regression and 42 that were not. For the 188 compounds, a SAR was found that was as accurate as the best statistical or neural network-generated SARs. The PROGOL SAR has the advantages that it did not need the use of any indicator variables handcrafted by an expert, and the generated rules were easily comprehensible. For the 42 compounds, PROGOL formed a SAR that was significantly (P < 0.025) more accurate than linear regression, quadratic regression, and back-propagation. This SAR is based on an automatically generated structural alert for mutagenicity.

Evolution of gilled mushrooms and puffballs inferred from ribosomal DNA sequences

Homobasidiomycete fungi display many complex fruiting body morphologies, including mushrooms and puffballs, but their anatomical simplicity has confounded efforts to understand the evolution of these forms. We performed a comprehensive phylogenetic analysis of homobasidiomycetes, using sequences from nuclear and mitochondrial ribosomal DNA, with an emphasis on understanding evolutionary relationships of gilled mushrooms and puffballs. Parsimony-based optimization of character states on our phylogenetic trees suggested that strikingly similar gilled mushrooms evolved at least six times, from morphologically diverse precursors. Approximately 87% of gilled mushrooms are in a single lineage, which we call the “euagarics.” Recently discovered 90 million-year-old fossil mushrooms are probably euagarics, suggesting that (i) the origin of this clade must have occurred no later than the mid-Cretaceous and (ii) the gilled mushroom morphology has been maintained in certain lineages for tens of millions of years. Puffballs and other forms with enclosed spore-bearing structures (Gasteromycetes) evolved at least four times. Derivation of Gasteromycetes from forms with exposed spore-bearing structures (Hymenomycetes) is correlated with repeated loss of forcible spore discharge (ballistospory). Diverse fruiting body forms and spore dispersal mechanisms have evolved among Gasteromycetes. Nevertheless, it appears that Hymenomycetes have never been secondarily derived from Gasteromycetes, which suggests that the loss of ballistospory has constrained evolution in these lineages.

(4-Aminomethyl)phenylguanidine derivatives as nonpeptidic highly selective inhibitors of human urokinase

Increased expression of the serine protease urokinase-type plasminogen activator (uPA) in tumor tissues is highly correlated with tumor cell migration, invasion, proliferation, progression, and metastasis. Thus inhibition of uPA activity represents a promising target for antimetastatic therapy. So far, only the x-ray crystal structure of uPA inactivated by H-Glu-Gly-Arg-chloromethylketone has been reported, thus limited data are available for a rational structure-based design of uPA inhibitors. Taking into account the trypsin-like arginine specificity of uPA, (4-aminomethyl)phenylguanidine was selected as a potential P1 residue and iterative derivatization of its amino group with various hydrophobic residues, and structure–activity relationship-based optimization of the spacer in terms of hydrogen bond acceptor/donor properties led to N-(1-adamantyl)-N′-(4-guanidinobenzyl)urea as a highly selective nonpeptidic uPA inhibitor. The x-ray crystal structure of the uPA B-chain complexed with this inhibitor revealed a surprising binding mode consisting of the expected insertion of the phenylguanidine moiety into the S1 pocket, but with the adamantyl residue protruding toward the hydrophobic S1′ enzyme subsite, thus exposing the ureido group to hydrogen-bonding interactions. Although in this enzyme-bound state the inhibitor is crossing the active site, interactions with the catalytic residues Ser-195 and His-57 are not observed, but their side chains are spatially displaced for steric reasons. Compared with other trypsin-like serine proteases, the S2 and S3/S4 pockets of uPA are reduced in size because of the 99-insertion loop. Therefore, the peculiar binding mode of the new type of uPA inhibitors offers the possibility of exploiting optimized interactions at the S1′/S2′ subsites to further enhance selectivity and potency. Because crystals of the uPA/benzamidine complex allow inhibitor exchange by soaking procedures, the structure-based design of new generations of uPA inhibitors can rely on the assistance of x-ray analysis.