PRO-LIGAND: an approach to de novo molecular design. 1. Application to the design of organic molecules

Algorithm for Exhaustive and Nonredundant Organic Stereoisomer Generation

Generation of organic stereoisomers with R/S, Z/E, and/or M/P configurations that may contain heteroatoms, multiple bonds, and any kind of cycle (isolated, spiro, condensed, and nested) is described. Inputs for processing are molecular structures in a N_tuple format resident on an automatic (canonical) or manual (non canonical) generated file which are processed by doing internal molecular graph construction, a weighted bipartite tree construction for all atoms and bonds to detect stereocenters, and symmetrical atom groups (SAG) with some specific SAG parameters that constitute a novel way for redundancy elimination of meso structures. Finally, determination of ligand CIP priorities allows for writing the output N_tuples with stereoisomer description. Several examples showing application of this methology to a wide number of structures are also presented.

FlexNovo: structure-based searching in large fragment spaces

We present a new molecular design program, FlexNovo, for structure-based searching within large fragment spaces following a sequential growth strategy. The fragment spaces consist of several thousands of chemical fragments and a corresponding set of rules that specify how the fragments can be connected. FlexNovo is based on the FlexX molecular docking software and makes use of its incremental construction algorithm and the underlying chemical models. Interaction energies are calculated by using standard scoring functions. Several placement geometry, physicochemical property (drug-likeness), and diversity filter criteria are directly integrated into the "build-up" process. FlexNovo has been used to design potential inhibitors for four targets of pharmaceutical interest (dihydrofolate reductase, cyclin-dependant kinase 2, cyclooxygenase-2, and the estrogen receptor). We have carried out calculations using different diversity parameters for each of these targets and generated solution sets containing up to 50 molecules. The compounds obtained show that FlexNovo is able to generate a diverse set of reasonable molecules with drug-like properties. The results, including an automated similarity analysis with the Feature Tree program, indicate that FlexNovo often reproduces structural motifs as well as the corresponding binding modes seen in known active structures.

Computer-based de novo design of drug-like molecules

Ever since the first automated de novo design techniques were conceived only 15 years ago, the computer-based design of hit and lead structure candidates has emerged as a complementary approach to high-throughput screening. Although many challenges remain, de novo design supports drug discovery projects by generating novel pharmaceutically active agents with desired properties in a cost- and time-efficient manner. In this review, we outline the various design concepts and highlight current developments in computer-based de novo design.

LEA3D: a computer-aided ligand design for structure-based drug design

We present an improved version of the program LEA developed to design organic molecules. Rational drug design involves finding solutions to large combinatorial problems for which an exhaustive search is impractical. Genetic algorithms provide a tool for the investigation of such problems. New software, called LEA3D, is now able to conceive organic molecules by combining 3D fragments. Fragments were extracted from both biological compounds and known drugs. A fitness function guides the search process in optimizing the molecules toward an optimal value of the properties. The fitness function is build up by combining several independent property evaluations, including the score provided by the FlexX docking program. One application in de novo drug design is described. The example makes use of the structure of Mycobacterium tuberculosis thymidine monophosphate kinase to generate analogues of one of its natural substrates. Among 22 tested compounds, 17 show inhibitory activity in the micromolar range.

A very large diversity space of synthetically accessible compounds for use with drug design programs

We have constructed a very large virtual diversity space containing more than 10(13) chemical compounds. The diversity space is built from about 400 combinatorial libraries, which have been expanded by choosing sizeable collections of suitable R-groups that can be attached to each link point of their scaffolds. These R-group collections have been created by selecting reagents that have drug-like properties from catalogs of available chemicals. As members of known combinatorial libraries, the compounds in the diversity space are in general synthetically accessible and useful as potential drug leads. Hence, the diversity space can be used as a vast source of compounds by a de novo drug design program. For example, we have used such a program to generate inhibitors of HIV integrase enzyme that exhibited activity in the micromolar range.

Genomic Messaging System and DNA Mark-Up Language for Information-Based Personalized Medicine with Clinical and Proteome Research Applications

The convergence of clinical medicine and the Life Sciences, commencing with opportunities in clinical trials and clinically linked medical research, presents many novel challenges. The Genomic Messaging System (GMS) described here was originally developed as a tool for assembling clinical genomic records of individual and collective patients, and was then generalized to become a flexible workflow component that will link clinical records to a variety of computational biology research tools, for research and ultimately for a more personalized, focused, and preventative healthcare system. Prominent among the applications linked are protein science applications, including the rapid automated modeling of patient proteins with their individual structural polymorphisms. In an initial study, GMS formed the basis of a fully automated system for modeling patient proteins with structural polymorphisms as a basis for drug selection and ultimately design on an individual patient basis.

Creating Artificial Binding Pocket Boundaries To Improve the Efficiency of Flexible Ligand Docking

Traditionally, algorithms for binding site characterization or identification focus on the problem of identifying atoms within a macromolecule that might be responsible for ligand binding. In this manuscript, we focus on the binding pocket problem from a different perspective as a challenge of calculating an artificial binding pocket boundary that is sufficient to isolate binding pocket volume. The approach involves the calculation of a macromolecule encapsulating surface (MES) that separates binding pocket volume from outside space. We show that the MES can be used to increase the efficiency of flexible docking as implemented in AutoDock 3.0. The most significant improvement in docking efficiency is seen when the entire protein is searched and results show additional support for the use of AutoDock, in and of itself, as a feasible tool for binding-site identification for cases in which a protein ligand is known.

Recent advances in de novo design strategy for practical lead identification

De novo design programs such as LEGEND, LUDI, and LeapFrog can identify novel structures that are predicted to fit the active site of a target protein. However, in the conventional de novo design strategy, the output structures obtained from the programs can be problematic with regard to synthetic accessibility and binding affinity prediction. Thus it has been practically difficult to obtain novel lead compounds that are appropriate for medicinal chemists through the de novo design strategy. Since the late 1990s, several new strategies for lead identification have been reported and the successful examples have been disclosed. One of the strategies is validation of small fragments, which can be substructures of de novo ligands, by using NMR, X-ray, or MS spectra. Another method is prioritization of output structures obtained from de novo design programs by chemical accessibility. This review describes these new strategies with practical applications and future perspectives of de novo design.

Virtual screening and fast automated docking methods

Recent advances in high-throughput protein structure determination and in computational chemistry have refocused attention on virtual screening and fast automated docking methods. This review provides a brief introduction to the basic ideas and outlines computational tools currently used. We also provide several examples of where virtual screening has proved successful, highlighting the usefulness of the approach.

Structure-based generation of a new class of potent Cdk4 inhibitors: new de novo design strategy and library design

As a first step in structure-based design of highly selective and potent Cdk4 inhibitors, we performed structure-based generation of a novel series of Cdk4 inhibitors. A Cdk4 homology model was constructed according to X-ray analysis of an activated form of Cdk2. Using this model, we applied a new de novo design strategy which combined the de novo design program LEGEND with our in-house structure selection supporting system SEEDS to generate new scaffold candidates. In this way, four classes of scaffold candidates including diarylurea were identified. By constructing diarylurea informer libraries based on the structural requirements of Cdk inhibitors in the ATP binding pocket of the Cdk4 model, we were able to identify a potent Cdk4 inhibitor N-(9-oxo-9H-fluoren-4-yl)-N'-pyridin-2-ylurea 15 (IC(50) = 0.10 microM), together with preliminary SAR. We performed a docking study between 15 and the Cdk4 model and selected a reasonable binding mode which is consistent with the SAR. Further modification based on the proposed binding mode provided a more potent compound, N-[(9bR)-5-oxo-2,3,5,9b-tetrahydro-1H-pyrrolo[2,1-a]isoindol-9-yl]-N'-pyridin-2-ylurea 26a (IC(50) = 0.042 microM), X-ray analysis of which was accomplished by the soaking method. The predicted binding mode of 15 in Cdk4 was validated by X-ray analysis of the Cdk2-26a complex.

SuperStar: comparison of CSD and PDB-based interaction fields as a basis for the prediction of protein-ligand interactions

SuperStar is an empirical method for identifying interaction sites in proteins, based entirely on the experimental information about non-bonded interactions, present in the IsoStar database. The interaction information in IsoStar is contained in scatterplots, which show the distribution of a chosen probe around structure fragments. SuperStar breaks a template molecule (e.g. a protein binding site) into structural fragments which correspond to those in the scatterplots. The scatterplots are then superimposed on the corresponding parts of the template and converted into a composite propensity map. The original version of SuperStar was based entirely on scatterplots from the CSD. Here, scatterplots based on protein-ligand interactions are implemented in SuperStar, and validated on a test set of 122 X-ray structures of protein-ligand complexes. In this validation, propensity maps are compared with the experimentally observed positions of ligand atoms of comparable types. Although non-bonded interaction geometries in small molecule structures are similar to those found in protein-ligand complexes, their relative frequencies of occurrence are different. Polar interactions are more common in the first class of structures, while interactions between hydrophobic groups are more common in protein crystals. In general, PDB and CSD-based SuperStar maps appear equally successful in the prediction of protein-ligand interactions. PDB-based maps are more suitable to identify hydrophobic pockets, and inherently take into account the experimental uncertainties of protein atomic positions. If the protonation state of a histidine, aspartate or glutamate protein side-chain is known, specific CSD-based maps for that protonation state are preferred over PDB-based maps which represent an ensemble of protonation states.

Exhaustive generation of organic isomers. 6. Stereoisomers having isolated and spiro cycles and new extended N_tuples

A new stereoisomer generation system named CAMGEC2 for generation of stereoisomers containing isolated and spiro cycles with one or more descriptors among R, S, Z, E, M, and P is developed using Graph Theory. It includes new approaches for symmetry analysis, cycle detection processes in molecular graphs in a modular way, and also an extension of the N_tuple format for linear representation of molecular graphs that keeps graph topographical information.

Developing a dynamic pharmacophore model for HIV-1 integrase

We present the first receptor-based pharmacophore model for HIV-1 integrase. The development of "dynamic" pharmacophore models is a new method that accounts for the inherent flexibility of the active site and aims to reduce the entropic penalties associated with binding a ligand. Furthermore, this new drug discovery method overcomes the limitation of an incomplete crystal structure of the target protein. A molecular dynamics (MD) simulation describes the flexibility of the uncomplexed protein. Many conformational models of the protein are saved from the MD simulations and used in a series of multi-unit search for interacting conformers (MUSIC) simulations. MUSIC is a multiple-copy minimization method, available in the BOSS program; it is used to determine binding regions for probe molecules containing functional groups that complement the active site. All protein conformations from the MD are overlaid, and conserved binding regions for the probe molecules are identified. Those conserved binding regions define the dynamic pharmacophore model. Here, the dynamic model is compared to known inhibitors of the integrase as well as a three-point, ligand-based pharmacophore model from the literature. Also, a "static" pharmacophore model was determined in the standard fashion, using a single crystal structure. Inhibitors thought to bind in the active site of HIV-1 integrase fit the dynamic model but not the static model. Finally, we have identified a set of compounds from the Available Chemicals Directory that fit the dynamic pharmacophore model, and experimental testing of the compounds has confirmed several new inhibitors.

Modern computational chemistry and drug discovery: structure generating programs

During 1996 and 1997, the first reports were disclosed of active enzyme inhibitors based entirely on novel structures created by de novo methods. De novo methods have also been used to modify and significantly improve the binding affinity of an HIV protease inhibitor. Work continues in the improvement of methods for the de novo design of compounds which fit and chemically complement a binding site. De novo algorithms that generate only synthetically feasible structures have also been reported. In addition, methods are being developed for the automatic computer generation of virtual molecular libraries which can be searched to identify molecules to match a pharmacophore or fit into a binding site.

Evaluation of a method for controlling molecular scaffold diversity in de novo ligand design

We describe an algorithm for the automated generation of molecular structures subject to geometric and connectivity constraints. The method relies on simulated annealing and simplex optimization of a penalty function that contains a variety of conditions and can be useful in structure-based drug design projects. The procedure controls the diversity and complexity of the generated molecules. Structure selection filters are an integral part and drive the algorithm. Several procedures have been developed to achieve reliable control. A number of template sets can be defined and combined to control the range of molecules which are searched. Ring systems are predefined. Normally, the ring-system complexity is on of the most elusive and difficult factors to control when fusion-, bridge- and spiro-structures are built by joining templates. Here this is not an issue; the decision about which systems are acceptable, and which are not, is made before the run is initiated. Queries for inclusion and exclusion spheres are incorporated into the objective function, and, by using a flexible notation, the structure generation can be directed and more focused. Simulated annealing is a reliable optimizer and converges asymptotically to the global minimum. The objective functions used here are degenerate, so it is likely that each run will produce a different set of good solutions.

PRO_SELECT: combining structure-based drug design and combinatorial chemistry for rapid lead discovery. 1. Technology

This paper describes a novel methodology, PRO_SELECT, which combines elements of structure-based drug design and combinatorial chemistry to create a new paradigm for accelerated lead discovery. Starting with a synthetically accessible template positioned in the active site of the target of interest, PRO_SELECT employs database searching to generate lists of potential substituents for each substituent position on the template. These substituents are selected on the basis of their being able to couple to the template using known synthetic routes and their possession of the correct functionality to interact with specified residues in the active site. The lists of potential substituents are then screened computationally against the active site using rapid algorithms. An empirical scoring function, correlated to binding free energy, is used to rank the substituents at each position. The highest scoring substituents at each position can then be examined using a variety of techniques and a final selection is made. Combinatorial enumeration of the final lists generates a library of synthetically accessible molecules, which may then be prioritized for synthesis and assay. The results obtained using PRO_SELECT to design thrombin inhibitors are briefly discussed.

Automatic identification and representation of protein binding sites for molecular docking

Molecular docking is a popular way to screen for novel drug compounds. The method involves aligning small molecules to a protein structure and estimating their binding affinity. To do this rapidly for tens of thousands of molecules requires an effective representation of the binding region of the target protein. This paper presents an algorithm for representing a protein's binding site in a way that is specifically suited to molecular docking applications. Initially the protein's surface is coated with a collection of molecular fragments that could potentially interact with the protein. Each fragment, or probe, serves as a potential alignment point for atoms in a ligand, and is scored to represent that probe's affinity for the protein. Probes are then clustered by accumulating their affinities, where high affinity clusters are identified as being the "stickiest" portions of the protein surface. The stickiest cluster is used as a computational binding "pocket" for docking. This method of site identification was tested on a number of ligand-protein complexes; in each case the pocket constructed by the algorithm coincided with the known ligand binding site. Successful docking experiments demonstrated the effectiveness of the probe representation.

RASSE: a new method for structure-based drug design

A novel method, RASSE, has been developed to suggest reasonable structures which can fit well to the binding sites of receptors. Molecules are generated by an iterative growing procedure in which atoms are added to existing fragments. Potential ligands are then picked out by special scoring rules. This atomgrowing based method is characterized by combinatorial searching of atom types and conformations. To some extent, it is the computer simulation of combinatorial chemistry. This method has been applied to the design of inhibitors for E. coli dihydrofolate reductase and human phospholipase A2. The results demonstrate that this program is capable of generating reasonable structures, thus proving its power in drug design.

Active-site-directed 3D database searching: pharmacophore extraction and validation of hits

Two new computational tools, PRO_PHARMEX and PRO_SCOPE, for use in active-site-directed searching of 3D databases are described. PRO_PHARMEX is a flexible, graphics-based program facilitating the extraction of pharmacophores from the active site of a target macromolecule. These pharmacophores can then be used to search a variety of databases for novel lead compounds. Such searches can often generate many 'hits' of varying quality. To aid the user in setting priorities for purchase, synthesis or testing, PRO_SCOPE can be used to dock molecules rapidly back into the active site and to assign them a score using an empirical scoring function correlated to the free energy of binding. To illustrate how these tools can add value to existing 3D database software, their use in the design of novel thrombin inhibitors is described.

Evolutionary algorithms in computer-aided molecular design

In recent years, search and optimisation algorithms inspired by evolutionary processes have been applied with marked success to a wide variety of problems in diverse fields of study. In this review, we survey the growing application of these 'evolutionary algorithms' in one such area: computer-aided molecular design. In the course of the review, we seek to summarise the work to date and to indicate where evolutionary algorithms have met with success and where they have not fared so well. In addition to this, we also attempt to discern some future trends in both the basic research concerning these algorithms and their application to the elucidation, design and modelling of chemical and biochemical structures.

Genetic algorithms in molecular recognition and design

Genetic algorithms provide a novel tool for the investigation of combinatorial optimization problems. A genetic algorithm takes an initial set of possible starting solutions, and iteratively improves them by means of crossover and mutation operators that are related to those involved in Darwinian evolution. This approach is illustrated by reference to applications in molecular modelling, the docking of flexible ligands into protein active sites and de novo ligand design.

PRO_LIGAND: an approach to de novo molecular design. 6. Flexible fitting in the design of peptides

This paper describes the further development of the functionality of our in-house de novo design program, PRO_LIGAND. In particular, attention is focused on the implementation and validation of the 'direct tweak' method for the construction of conformationally flexible molecules, such as peptides, from molecular fragments. This flexible fitting method is compared to the original method based on libraries of prestored conformations for each fragment. It is shown that the directed tweak method produces results of comparable quality, with significant time savings. By removing the need to generate a set of representative conformers for any new library fragment, the flexible fitting method increases the speed and simplicity with which new fragments can be included in a fragment library and also reduces the disk space required for library storage. A further improvement to the molecular construction process within PRO_LIGAND is the inclusion of a constrained minimisation procedure which relaxes fragments onto the design model and can be used to reject highly strained structures during the structure generation phase. This relaxation is shown to be very useful in simple test cases, but restricts diversity for more realistic examples. The advantages and disadvantages of these additions to the PRO_LIGAND methodology are illustrated by three examples: similar design to an alpha helix region of dihydrofolate reductase, complementary design to the active site of HIV-1 protease and similar design to an epitope region of lysozyme.

PRO_LIGAND: an approach to de novo molecular design. 4. Application to the design of peptides

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.

PRO-LIGAND: an approach to de novo molecular design. 3. A genetic algorithm for structure refinement

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.