An approach to de novo molecular design, PRO-LIGAND, has been developed that, in the environment of a large, integrated molecular design and simulation system, provides a unified framework for the generation of novel molecules which are either similar or complementary to a specified target. The approach is based on a methodology that has proved to be effective in other studies--placing molecular fragments upon target interaction sites-but incorporates many novel features such as the use of a rapid graph-theoretical algorithm for fragment placing, a generalised driver for structure generation which offers a large variety of fragment assembly strategies to the user and the pre-screening of library fragments. After a detailed description of the relevant modules of the package, PRO-LIGAND's efficacy in aiding rational drug design is demonstrated by its ability to design mimics of methotrexate and potential inhibitors for dihydrofolate reductase and HIV-1 protease.

In some instances, peptides can play an important role in the discovery of lead compounds. This paper describes the peptide design facility of the de novo drug design package, PRO_LIGAND. The package provides a unified framework for the design of peptides that are similar or complementary to a specified target. The approach uses single amino acid residues, selected from preconstructed libraries of different residues and conformations, and places them on top of predefined target interaction sites. This approach is a well-tested methodology for the design of organics but has not been used for peptides before. Peptides represent a difficulty because of their great conformational flexibility and a study of the advantages and disadvantages of this simple approach is an important step in the development of design tools. After a description of our general approach, a more detailed discussion of its adaptation to peptides is given. The method is then applied to the design of peptide-based inhibitors to HIV-1 protease and the design of structural mimics of the surface region of lysozyme. The results are encouraging and point the way towards further development of interaction site-based approaches for peptide design.

Recently, the development of computer programs which permit the de novo design of molecular structures satisfying a set of steric and chemical constraints has become a burgeoning area of research and many operational systems have been reported in the literature. Experience with PRO-LIGAND-the de novo design methodology embodied in our in-house molecular design and simulation system PRO-METHEUS-has suggested that the addition of a genetic algorithm (GA) structure refinement procedure can 'add value' to an already useful tool. Starting with the set of designed molecules as an initial population, the GA can combine features from both high- and low-scoring structures and, over a number of generations, produce individuals of better score than any of the starting structures. This paper describes how we have implemented such a procedure and demonstrates its efficacy in improving two sets of molecules generated by different de novo design projects.

A computational approach for molecular design, PRO_LIGAND, has been developed within the PROMETHEUS molecular design and simulation system in order to provide a unified framework for the de novo generation of diverse molecules which are either similar or complementary to a specified target. In this instance, the target is a pharmacophore derived from a series of active structures either by a novel interpretation of molecular field analysis data or by a pharmacophore-mapping procedure based on clique detection. After a brief introduction to PRO_LIGAND, a detailed description is given of the two pharmacophore generation procedures and their abilities are demonstrated by the elucidation of pharmacophores for steroid binding and ACE inhibition, respectively. As a further indication of its efficacy in aiding the rational drug design process, PRO_LIGAND is then employed to build novel organic molecules to satisfy the physicochemical constraints implied by the pharmacophores.

Thirty-six compounds, representing six different structural classes of insecticides which are known to act at the gamma-aminobutyric acid receptor/chloride ionophore, have been superimposed by methods which maximise the commonality of steric and electrostatic fields. Maximal steric and electrostatic alignment was derived by pairwise comparisons of the different chemical classes with picrotoxinin. To test the validity of the combined superposition, a Comparative Molecular Field Analysis (CoMFA) was carried out within SYBYL, using recently published in vivo and in vitro binding data for insecticides. The resultant partial least-squares (PLS) analysis of sampled steric and electrostatic fields showed a significant statistical correlation with the published biological data. The predictive model obtained was shown to have a greater than 95% chance of significance.