Combinatorial library design using a multiobjective genetic algorithm

Early results from screening combinatorial libraries have been disappointing with libraries either failing to deliver the improved hit rates that were expected or resulting in hits with characteristics that make them undesirable as lead compounds. Consequently, the focus in library design has shifted toward designing libraries that are optimized on multiple properties simultaneously, for example, diversity and "druglike" physicochemical properties. Here we describe the program MoSELECT that is based on a multiobjective genetic algorithm and which is able to suggest a family of solutions to multiobjective library design where all the solutions are equally valid and each represents a different compromise between the objectives. MoSELECT also allows the relationships between the different objectives to be explored with competing objectives easily identified. The library designer can then make an informed choice on which solution(s) to explore. Various performance characteristics of MoSELECT are reported based on a number of different combinatorial libraries.     

Preparation of C8-amine and acetylamine adducts of 2'-deoxyguanosine suitably protected for DNA synthesis

[reaction: see text] C8-Amine and acetylamine adducts of 2'-deoxyguanosine were synthesized. Our approach provides solutions for the coupling of aromatic amines to a protected 8-bromo-2'-deoxyguanosine derivative, for the selective acetylation of the coupled adduct at N(8) and for a protecting group scheme preserving the integrity of the base-labile N(8) acetyl group during DNA synthesis.     

Further development of reduced graphs for identifying bioactive compounds

Reduced graphs provide summary representations of chemical structures. Here, a variety of different types of reduced graphs are compared in similarity searches. The reduced graphs are found to give comparable performance to Daylight fingerprints in terms of the number of active compounds retrieved. However, no one type of reduced graph is found to be consistently superior across a variety of different data sets. Consequently, a representative set of reduced graphs was chosen and used together with Daylight fingerprints in data fusion experiments. The results show improved performance in 10 out of 11 data sets compared to using Daylight fingerprints alone. Finally, the potential of using reduced graphs to build SAR models is demonstrated using recursive partitioning. An SAR model consistent with a published model is found following just two splits in the decision tree.     

Variation in the accumulation levels of N,N-dimethyltryptamine in micropropagated trees and in in vitro cultures of Mimosa tenuiflora

The present article reports the accumulation of N,N-dimethyltryptamine and its metabolic precursors (tryptophan, tryptamine) in different organs of micropropagated Mimosa tenuiflora trees (leaves, flowers and bark) subjected to seasonal variations (January and June), as well as in in vitro cultures (plantlets and calluses) of this plant species. The accumulation of all the tested compounds varied according to the organ, the month of collection, and age of the plant material. In all cases, the neurotoxic compound N,N-dimethyltryptamine (DMT) was detected with the lowest concentration 0.01% dry weight (DW) in flowers, and the highest 0.33% DW in bark. For the in vitro cultures, DMT was present in high yields in plantlets (0.1-0.2% DW), while in calluses this compound was initially detected but its concentration decreased significantly in the subsequent subcultures.     

SPROUT: A program for structure generation

Summary SPROUT is a new computer program for constrained structure generation that is designed to generate molecules for a range of applications in molecular recognition. It uses artificial intelligence techniques to moderate the combinatorial explosion that is inherent in structure generation. The program is presented here for the design of enzyme inhibitors. Structure generation is divided into two phases: (i) primary structure generation to produce molecular graphs to fit the steric constraints; and (ii) secondary structure generation which is the process of introducing appropriate functionality to the graphs to produce molecules that satisfy the secondary constraints, e.g., electrostatics and hydrophobicity. Primary structure generation has been tested on two enzyme receptor sites; the p-amidino-phenyl-pyruvate binding site of trypsin and the acetyl pepstatin binding site of HIV-1 protease. The program successfully generates structures that resemble known substrates and, more importantly, the predictive power of the program has been demonstrated by its ability to suggest novel structures.     

Growth mechanism of gold particles on Al2O3 substrates

We investigated the growth of small gold particles on thin alumina substrates obtained by oxidation of aluminum. The particles were vapor deposited in vacuum from a Knudsen cell source with a vapor rate of 1·10¹³ cm^?2·s^?1. In our experiments small Au particles on Al₂O₃ were examined by electron microscopy. From electron micrographs we draw a size histogram of Au particles depending on the mean deposit thickness and the deposition rate. For a mean thickness larger than 1.5 nm the particle size distributions show two peaks. The shapes and the positions of these two peaks allow us to determine the particle growth mechanism and to evidence the importance of the liquid-like coalescence resulting of diffusion and collision of the aggregates.     

Evolving interpretable structure-activity relationship models. 2. Using multiobjective optimization to derive multiple models

A multiobjective evolutionary algorithm (MOEA) is described for evolving multiple structure-activity relationships (SARs). The SARs are encoded in easy-to-interpret reduced graph queries which describe features that are preferentially present in active compounds compared to inactives. The MOEA addresses a limitation associated with many machine learning methods; that is, the inherent tradeoff that exists in recall and precision which is usually handled by combining the two objectives into a single measure with a consequent loss of control. By simultaneously optimizing recall and precision, the MOEA generates a family of SARs that lie on the precision-recall (PR) curve. The user is then able to select a query with an appropriate balance in the two objectives: for example, a low recall-high precision query may be preferred when establishing the SAR, whereas a high recall-low precision query may be more appropriate in a virtual screening context. Each query on the PR curve aims at capturing the structure-activity information into a single representation, and each can be considered as an alternative (equally valid) solution. We then investigate combining individual queries into teams with the aim of capturing multiple SARs that may exist in a data set, for example, as is commonly seen in high-throughput screening data sets. Team formation is carried out iteratively as a postprocessing step following the evolution of the individual queries. The inclusion of uniqueness as a third objective within the MOEA provides an effective way of ensuring the queries are complementary in the active compounds they describe. Substantial improvements in both recall and precision are seen for some data sets. Furthermore, the resulting queries provide more detailed structure-activity information than is present in a single query.     

A comparison of field-based similarity searching methods: CatShape, FBSS, and ROCS

Three field-based similarity methods are compared in retrospective virtual screening experiments. The methods are the CatShape module of CATALYST, ROCS, and an in-house program developed at the University of Sheffield called FBSS. The programs are used in both rigid and flexible searches carried out in the MDL Drug Data Report. UNITY 2D fingerprints are also used to provide a comparison with a more traditional approach to similarity searching, and similarity based on simple whole-molecule properties is used to provide a baseline for the more sophisticated searches. Overall, UNITY 2D fingerprints and ROCS with the chemical force field option gave comparable performance and were superior to the shape-only 3D methods. When the flexible methods were compared with the rigid methods, it was generally found that the flexible methods gave slightly better results than their respective rigid methods; however, the increased performance did not justify the additional computational cost required.