DBMAKER: A set of programs to generate three-dimensional databases based upon user-specified criteria

Summary DBMAKER is a program that, in conjunction with CONCORD, generates three-dimensional structural databases. Numerous user-defined parameters monitor content, composition, size and connectivity information, but allow the program to generate random compounds within the scope of these constraints. SMILES string representations are generated, and conversion to 3D is performed by CONCORD. This assures high-quality 3D structures and portability to numerous proprietary storage formats. Methods are described to maintain compound registration, allowing database expansion as required without duplication.     

On the use of LUDI to search the Fine Chemicals Directory for ligands of proteins of known three-dimensional structure

Summary It is shown that the computer program LUDI can be used to search large databases of three-dimensional structures for putative ligands of proteins with known 3D structure. As an example, a subset of 30 000 small molecules (with less than 40 atoms and 0–2 rotatable bonds) from the Fine Chemicals Directory has been used in the search for possible novel ligands for four different proteins (trypsin, streptavidin, purine nucleoside phosphorylase and HIV protease). For trypsin and streptavidin, known ligands or substructures of known ligands are retrieved as top-scoring hits. In addition, a number of new interesting structures are found in all considered cases. Therefore, the method holds promise to retrieve automatically protein ligands from a 3D database if the 3D structure of the target protein is known.     

乙型肝炎表面抗原片段三维结构的同源模建及其配体的设计

利用同源模建和分子动力学优化得到了一种乙肝表面抗原片段的三维结构.通过对活性部位的分析,设计了与抗原片段相结合的配体.讨论了Trp163,Trp165和Pro70对于紧密结合配体所起的重要作用,抗原片段与配体之间的氢键也决定了它们结合的相对位置.从复合物得到的结构信息将有助于揭示配体与乙肝抗原的作用机理,促进乙型肝炎病人诊断与治疗试剂的研制     

The atom assignment problem in automated de novo drug design. 1. Transferability of molecular fragment properties

Summary This paper is the first of a series which examines the problems of atom assignment in automated de novo drug design. In subsequent papers, a combinatoric optimization method for fragment placement onto 3D molecular graphs is provided. Molecules are built from molecular graphs by placing fragments onto the graph. Here we examine the transferability of atomic residual charge, by fragment placement, with respect to the electrostatic potential. This transferability has been tested on 478 molecular structures extracted from the Cambridge Structural Database. The correlation found between the electrostatic potential computed from composite fragments and that computed for the whole molecule was encouraging, except for extended conjugated systems.     

The atom assignment problem in automated de novo drug design. 5. Tests for envelope-directed fragment placement based on molecular similarity

Summary The fragment placement method has been successfully extended to the problem of envelope-directed design. The atom assignment paradigm was based on molecular similarity between two molecular structures. A composite supersurface is defined to form the surface onto which the molecular fields are projected. The assignment process is then determined by using molecular similarity in the objective function to be optimized. In principle, this procedure is closely similar to that outlined in the previous paper for site-directed design. The rationale has been extensively tested on two benzodiazepine antagonists believed to bind to the same site.     

The atom assignment problem in automated de novo drug design. 4. Tests for site-directed fragment placement based on molecular complementarity

Summary Three previous papers in this series have outlined an optimization method for atom assignment in drug design using fragment placement. In this paper the procedure is rigorously tested on a selection of five ligand-protein co-crystals. The algorithm is presented with the molecular graph of the ligand, and the electrostatic/hydrophobic potential of the site, with the aim of creating a placement on the molecular graph which is as electrostatically complementary or hydrophobically similar to the site as possible. Various designer options were tested, including, where appropriate, hydrogen bonding and a restricted number of halogens. In most cases, the placement obtained was at least as good as the native ligand, if not significantly better.     

The atom assignment problem in automated de novo drug design. 2. A method for molecular graph and fragment perception

Summary If atom assignment onto 3D molecular graphs is to be optimized, an efficient scheme for placement must be developed. The strategy adopted in this paper is to analyze the molecular graphs in terms of cyclical and non-cyclical nodes; the latter are further divided into terminal and non-terminal nodes. Molecular fragments, from a fragments database, are described in a similar way. A canonical numbering scheme for the fragments and the local subgraph of the molecular graph enables fragments to be placed efficiently onto the molecular graph. Further optimization is achieved by placing similar fragments into bins using a hashing scheme based on the canonical numbering. The graph perception algorithm is illustrated in detail.     

The computer program LUDI: A new method for the de novo design of enzyme inhibitors

Summary A new computer program is described, which positions small molecules into clefts of protein structures (e.g. an active site of an enzyme) in such a way that hydrogen bonds can be formed with the enzyme and hydrophobic pockets are filled with hydrophobic groups. The program works in three steps. First it calculates interaction sites, which are discrete positions in space suitable to form hydrogen bonds or to fill a hydrophobic pocket. The interaction sites are derived from distributions of nonbonded contacts generated by a search through the Cambridge Structural Database. An alternative route to generate the interaction sites is the use of rules. The second step is the fit of molecular fragments onto the interaction sites. Currently we use a library of 600 fragments for the fitting. The final step in the present program is the connection of some or all of the fitted fragments to a single molecule. This is done by bridge fragments. Applications are presented for the crystal packing of benzoic acid and the enzymes dihydrofolate reductase and trypsin.     

LUDI: rule-based automatic design of new substituents for enzyme inhibitor leads

Summary Recent advances in a new method for the de novo design of enzyme inhibitors are reported. A new set of rules to define the possible nonbonded contacts between protein and ligand is presented. This method was derived from published statistical analyses of nonbonded contacts in crystal packings of organic molecules and has been implemented in the recently described computer program LUDI. Moreover, LUDI can now append a new substituent onto an already existing ligand. Applications are reported for the design of inhibitors of HIV protease and dihydrofolate reductase. The results demonstrate that LUDI is indeed capable of designing new ligands with improved binding when compared to the reference compound.     

Using the gini coefficient to measure the chemical diversity of small‐molecule libraries

Modern databases of small organic molecules contain tens of millions of structures. The size of theoretically available chemistry is even larger. However, despite the large amount of chemical information, the “big data” moment for chemistry has not yet provided the corresponding payoff of cheaper computer‐predicted medicine or robust machine‐learning models for the determination of efficacy and toxicity. Here, we present a study of the diversity of chemical datasets using a measure that is commonly used in socioeconomic studies. We demonstrate the use of this diversity measure on several datasets that were constructed to contain various congeneric subsets of molecules as well as randomly selected molecules. We also apply our method to a number of well‐known databases that are frequently used for structure‐activity relationship modeling. Our results show the poor diversity of the common sources of potential lead compounds compared to actual known drugs. © 2016 Wiley Periodicals, Inc.     

The atom assignment problem in automated de novo drug design. 3. Algorithms for optimization of fragment placement onto 3D molecular graphs

Summary Atom assignment onto 3D molecular graphs is a combinatoric problem in discrete space. If atoms are to be placed efficiently on molecular graphs produced in drug binding sites, the assignment must be optimized. An algorithm, based on simulated annealing, is presented for efficient optimization of fragment placement. Extensive tests of the method have been performed on five ligands taken from the Protein Data Bank. The algorithm is presented with the ligand graph and the electrostatic potential as input. Self placement of molecular fragments was monitored as an objective test. A hydrogen-bond option was also included, to enable the user to highlight specific needs. The algorithm performed well in the optimization, with successful replications. In some cases, a modification was necessary to reduce the tendency to give multiple halogenated structures. This optimization procedure should prove useful for automated de novo drug design.     

Towards the automatic design of synthetically accessible protein ligands: Peptides, amides and peptidomimetics

Summary The computer program LUDI for the de novo design of protein ligands was extended so that it is now able to take into account the synthetic accessibility of the constructed molecules. As an example, the design of peptides, amides and peptidomimetics using amino acids as building blocks is described. Two new libraries containing natural and non-natural amino acids were constructed for this purpose. Conformational flexibility is taken into account by using multiple conformers for each amino acid. The program was applied to the design of ligands for the enzymes elastase, renin and thermolysin.     

Combinatorial Synthesis of Small Organic Molecules

Combinatorial synthesis has developed within a few years from a laboratory curiosity to a method that is taken seriously in drug research. Rapid progress in molecular biology and the resulting ability to determine the activity of new substances extremely efficiently have led to a change in paradigm for the synthesis of test compounds: in addition to the conventional procedure of synthesizing one substance after another, new methods allowing simultaneous creation of many structurally defined substances are becoming increasingly important. A characteristic of combinatorial synthesis is that a reaction is performed with many synthetic building blocks at once—in parallel or in a mixture— rather than with just one building block. All possible combinations are formed in each step, so that a large number of products, a so-called library, is obtained from only a few reactants. Several methods have been developed for combinatorial synthesis of small organic molecules, based on research into peptide library synthesis: single substances are produced by highly automated parallel syntheses, and special techniques enable targeted synthesis of mixtures with defined components. Many structures can be obtained by combinatorial synthesis, and the size of the libraries created ranges from a few individual compounds to many thousand substances in mixtures. This article gives an overview of the combinatorial syntheses of small organic molecules reported to date, performed both in solution and on a solid support. In addition, different techniques for identification of active compounds in mixtures are presented, together with ways to automate syntheses and process the large amounts of data produced. An overview of pionering companies active in this area is also given. The final outlook attempts to predict the future development of this exponentially growing area and the influence of this new thinking in other areas of chemistry.     

Calculating the knowledge-based similarity of functional groups using crystallographic data

A knowledge-based method for calculating the similarity of functional groups is described and validated. The method is based on experimental information derived from small molecule crystal structures. These data are used in the form of scatterplots that show the likelihood of a non-bonded interaction being formed between functional group A (the `central group') and functional group B (the `contact group' or `probe'). The scatterplots are converted into three-dimensional maps that show the propensity of the probe at different positions around the central group. Here we describe how to calculate the similarity of a pair of central groups based on these maps. The similarity method is validated using bioisosteric functional group pairs identified in the Bioster database and Relibase. The Bioster database is a critical compilation of thousands of bioisosteric molecule pairs, including drugs, enzyme inhibitors and agrochemicals. Relibase is an object-oriented database containing structural data about protein-ligand interactions. The distributions of the similarities of the bioisosteric functional group pairs are compared with similarities for all the possible pairs in IsoStar, and are found to be significantly different. Enrichment factors are also calculated showing the similarity method is statistically significantly better than random in predicting bioisosteric functional group pairs.     

Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes

This paper describes the development of a simple empirical scoringfunction designed to estimate the free energy of binding for aprotein–ligand complex when the 3D structure of the complex is knownor can be approximated. The function uses simple contact terms to estimatelipophilic and metal–ligand binding contributions, a simple explicitform for hydrogen bonds and a term which penalises flexibility. Thecoefficients of each term are obtained using a regression based on 82ligand–receptor complexes for which the binding affinity is known. Thefunction reproduces the binding affinity of the complexes with across-validated error of 8.68 kJ/mol. Tests on internal consistency indicatethat the coefficients obtained are stable to changes in the composition ofthe training set. The function is also tested on two test sets containing afurther 20 and 10 complexes, respectively. The deficiencies of this type offunction are discussed and it is compared to approaches by other workers.     

The development of a simple empirical scoring function to estimate the binding constant for a protein-ligand complex of known three-dimensional structure

Summary A new simple empirical function has been developed that estimates the free energy of binding for a given protein-ligand complex of known 3D structure. The function takes into account hydrogen bonds, ionic interactions, the lipophilic protein-ligand contact surface and the number of rotatable bonds in the ligand. The dataset for the calibration of the function consists of 45 protein-ligand complexes. The new energy function reproduces the binding constants (ranging from 2.5·10^-2 to 4·10^-14 M, corresponding to binding energies between -9 and -76 kJ/mol) of the dataset with a standard deviation of 7.9 kJ/mol, corresponding to 1.4 orders of magnitude in binding affinity. The individual contributions to protein-ligand binding obtained from the scoring function are: ideal neutral hydrogen bond: -4.7 kJ/mol; ideal ionic interaction: -8.3 kJ/mol; lipophilic contact: -0.17 kJ/mol Ų; one rotatable bond in the ligand: +1.4 kJ/mol. The function also contains a constant contribution (+5.4 kJ/mol) which may be rationalized as loss of translational and rotational entropy. The function can be evaluated very fast and is therefore also suitable for application in a 3D database search or de novo ligand design program such as LUDI.     

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

Summary This paper describes the further development of the functionality of our in-house de novo design program, PRO_LIGAND. In particular, attention is focussed on the implementation and validation of the directed 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.     

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 one 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.