Clustering files of chemical structures using the fuzzy k-means clustering method

This paper evaluates the use of the fuzzy k-means clustering method for the clustering of files of 2D chemical structures. Simulated property prediction experiments with the Starlist file of logP values demonstrate that use of the fuzzy k-means method can, in some cases, yield results that are superior to those obtained with the conventional k-means method and with Ward's clustering method. Clustering of several small sets of agrochemical compounds demonstrate the ability of the fuzzy k-means method to highlight multicluster membership and to identify outlier compounds, although the former can be difficult to interpret in some cases.     

Adsorption on Heterogeneous Regular Surfaces

Quantifying the role of surface shape and physicochemical surface conditions on the interfacial reactivity of particles and substrates is fundamental to a multitude of natural and engineered surface adsorption phenomena. We consider continuum/jump regime adsorption at the gas or liquid interface of arbitrary regular solid surfaces with heterogeneous surface features. In particular, the 3-D boundary value problem (based on Laplace's diffusion equation) is converted into a 2-D integral equation for the adsorbate concentration at the particle surface. This accommodates numerical descretization via the implementation of 2-D Gauss-Legendre quadratures on an arrangement of high- and low-adsorption patch trace sites constructed to completely cover the particle surface. A generalized computer program is developed to solve the resulting linear algebra problem for the unkown local adsorption current densities. We investigate the role of various distributions of high- and low-adsorption sites for a generalized class of spheres which includes the DNA-like shaped twisted spheres. The biological implications of the role of surface curvature on interfacial adsorption/reactivity at particle surfaces are also discussed. Copyright 2001 Academic Press.     

Bit-string methods for selective compound acquisition

Selective compound acquisition programs need to ensure that the compounds that are chosen do not contain undesirable functionality. This is easy to achieve if a supplier is prepared to provide unambiguous structure representations for the compounds that they have available: this paper discusses selection techniques that can be used when a supplier is prepared to make available only fragment bit-string representations for the compounds in their catalog. Experiments with three databases and three types of bit-string show that a simple k-nearest-neighbor searching method provides a surprisingly effective, although far from perfect, way of selecting compounds when only bit-string representations are available. A second approach, based on the use of a fragment weighting scheme analogous to those used in substructural analysis studies, proved to be noticeably less effective in operation.     

A laser desorption fourier transform mass spectrometric study of dimethyl 8-acetyl-3,7,12,17-tetramethylporphyrin-2,18-dipropanoate

Laser desorption Fourier transform ion cyclotron resonance positive- and negative-ion mass spectra are presented for dimethyl 8-acetyl-3,7,12,17-tetramethylporphyrin-2,18-dipropanoate. The 248-nm laser ionization thresholds for both positive and negative ions are observed to be about 2.5 MW cm^?2. The M⁺˙ molecular ion is assigned to the base peak in the low-power spectra whereas it is the M^?˙ ion for the corresponding anion spectra. Increased intensities of [M + H]⁺ and [M ? H]^? are observed with increased laser fluences of up to 38 MW cm^?2. At high laser powers the negative-ion results reveal that a series of carbon-nitrogen cumulene and polyacetylene cluster ions are formed. Laser evaporation/multiphoton ionization/ and thermal evaporation/electron impact ionization/collision-induced dissociation experiments carried out on the porphyrin M⁺˙ and [M + H]⁺ ions over a range of translational kinetic energies and delay times after acceleration are compared and used to obtain mechanistic and structural information. In contrast to the electron impact experiments, which show only side-chain cleavage, the laser-based collision-induced dissociation experiments reveal that, in addition to side-chain cleavage, it is possible to cleave the porphyrin ring to various extents depending on the ion translational energy selected.     

Reactions of 29 Transition Metal Cations, in the Same Oxidation State and under the Same Gas-Phase Conditions, with Sulfur

A total of 29 transition metals (all except Tc), all as ions M(+), have been reacted with gaseous S(8). The reactivities and reaction products provide a unique set of comparative data on a fundamental reaction of the elements. The results underlie the interpretation of many other processes and compounds in condensed phases. Series of product ions [MS(y)()](+) are formed, with y generally starting at 4, and increasing with time through 8 up to 10, 12, 16, or 21 (for La(+)). A general mechanism is proposed, in which the first {MS(8)}(+) encounter complex is reactive and undergoes S-S bond scission and rearrangement around the metal, such that [MS(8)](+) is not an early product. The early transition metals react faster than later members of the series, and third row metals react about twice as fast as first row metals. The metals which are more chalcophilic in condensed-phase chemistry are apparently less so as M(+); Hg(+) does not form observable [HgS(y)()](+) (except for a very low yield of [HgS(3)](+)) and is remarkably less reactive with sulfur than most of the other metal ions. Simple electron transfer between M(+) and S(8) does not occur except possibly for Ir(+), but S(8)(+) is sometimes observed and is believed to be formed by electron transfer from S(8) to some [MS(y)()](+) complexes. Interpretation of the rates of reaction of the ions of groups 3, 4, and 5 with S(8) is complicated because they react with adventitious water in the cell forming oxo-species. The results are discussed in the context of condensed-phase metal polysulfide chemistry.     

Comparison of fingerprint-based methods for virtual screening using multiple bioactive reference structures

Fingerprint-based similarity searching is widely used for virtual screening when only a single bioactive reference structure is available. This paper reviews three distinct ways of carrying out such searches when multiple bioactive reference structures are available: merging the individual fingerprints into a single combined fingerprint; applying data fusion to the similarity rankings resulting from individual similarity searches; and approximations to substructural analysis. Extended searches on the MDL Drug Data Report database suggest that fusing similarity scores is the most effective general approach, with the best individual results coming from the binary kernel discrimination technique.     

Enhancing the effectiveness of virtual screening by fusing nearest neighbor lists: a comparison of similarity coefficients

This paper evaluates the effectiveness of various similarity coefficients for 2D similarity searching when multiple bioactive target structures are available. Similarity searches using several different activity classes within the MDL Drug Data Report and the Dictionary of Natural Products databases are performed using BCI 2D fingerprints. Using data fusion techniques to combine the resulting nearest neighbor lists we obtain group recall results which, in many cases, are a considerable improvement on standard average recall values obtained for individual structures. It is shown that the degree of improvement can be related to the structural diversity of the activity class that is searched for, the best results being found for the most diverse groups. The group recall of active compounds using subsets of the class is also investigated: for highly self-similar activity classes, the group recall improvement saturates well before the full activity class size is reached. A rough correlation is found between the relative improvement using the group recall and the square of the number of unique compounds available in all of the merged lists. The Tanimoto coefficient is found unambiguously to be the best coefficient to use for the recovery of active compounds using multiple targets. Furthermore, when using the Tanimoto coefficient, the "MAX" fusion rule is found to be more effective than the "SUM" rule for the combination of similarity searches from multiple targets. The use of group recall can lead to improved enrichment in database searches and virtual screening.