Computational combinatorial chemistry for de novo ligand design: Review and assessment

Peptide science: A "rule model" for new generations of peptidomimetics

Peptides have been heavily investigated for their biocompatible and bioactive properties. Though a wide array of functionalities can be introduced by varying the amino acid sequence or by structural constraints, properties such as proteolytic stability, catalytic activity, and phase behavior in solution are difficult or impossible to impart upon naturally occurring α-L-peptides. To this end, sequence-controlled peptidomimetics exhibit new folds, morphologies, and chemical modifications that create new structures and functions. The study of these new classes of polymers, especially α-peptoids, has been highly influenced by the analysis, computational, and design techniques developed for peptides. This review examines techniques to determine primary, secondary, and tertiary structure of peptides, and how they have been adapted to investigate peptoid structure. Computational models developed for peptides have been modified to predict the morphologies of peptoids and have increased in accuracy in recent years. The combination of in vitro and in silico techniques have led to secondary and tertiary structure design principles that mirror those for peptides. We then examine several important developments in peptoid applications inspired by peptides such as pharmaceuticals, catalysis, and protein-binding. A brief survey of alternative backbone structures and research investigating these peptidomimetics shows how the advancement of peptide and peptoid science has influenced the growth of numerous fields of study. As peptide, peptoid, and other peptidomimetic studies continue to advance, we will expect to see higher throughput structural analyses, greater computational accuracy and functionality, and wider application space that can improve human health, solve environmental challenges, and meet industrial needs. STATEMENT OF SIGNIFICANCE: Many historical, chemical, and functional relations draw a thread connecting peptides to their recent cognates, the "peptidomimetics". This review presents a comprehensive survey of this field by highlighting the width and relevance of these familial connections. In the first section, we examine the experimental and computational techniques originally developed for peptides and their morphing into a broader analytical and predictive toolbox. The second section presents an excursus of the structures and properties of prominent peptidomimetics, and how the expansion of the chemical and structural diversity has returned new exciting properties. The third section presents an overview of technological applications and new families of peptidomimetics. As the field grows, new compounds emerge with clear potential in medicine and advanced manufacturing.

CAN SEMIEMPIRICAL QUANTUM MODELS CALCULATE THE BINDING ENERGY OF HYDROGEN BONDING FOR BIOLOGICAL SYSTEMS?

A modified semiempirical model named RM1BH, which is based on RM1 parameterizations, is proposed to simulate varied biological hydrogen-bonded systems. The RM1BH is formulated by adding Gaussian functions to the core–core repulsion items in original RM1 formula to reproduce the binding energies of hydrogen bonding of experimental and high-level computational results. In the parameterizations of our new model, 35 base-pair dimers, 18 amino acid residue dimers, 14 dimers between a base and an amino acid residue, and 20 other multimers were included. The results performed with RM1BH were compared with experimental values and the benchmark density-functional (B3LYP/6-31G**/BSSE) and Möller–Plesset perturbation (MP2/6-31G**/BSSE) calculations on various biological hydrogen-bonded systems. It was demonstrated that RM1BH model outperforms the PM3 and RM1 models in the calculations of the binding energies of biological hydrogen-bonded systems by very close agreement with the values of both high-level calculations and experiments. These results provide insight into the ideas, methods, and views of semiempirical modifications to investigate the weak interactions of biological systems.

Determination of ligand-binding sites on proteins using long-range hydrophobic potential

Here we developed a new program, HydrophoBicity On a Protein (HBOP), to find the ligand-binding site of a protein using the long-range hydrophobic-potential function estimated from the experimental data of Israelachvili and Pashley. We calculated the hydrophobic-potential energies at each grid point of a lattice around a protein using the potential function. The hydrophobic potential was evaluated using the carbon atoms of the hydrophobic residues, with the exception of those of the amide groups. We tested HBOP on 26 types of protein (72 protein-ligand complexes), the three-dimensional structures of which were determined experimentally. Although only one hydrophobic function was used, HBOP could successfully identify the binding sites in all of the proteins tested. Moreover, in 24 of the proteins, the binding sites were located in the most hydrophobic region. Surprisingly, the binding sites on sugar binding proteins were the most hydrophobic sites. It implies that the hydrophobic interaction plays an important role in the formation of protein-ligand complexes.

Ligand design by a combinatorial approach based on modeling and experiment: application to HLA-DR4

Combinatorial synthesis and large scale screening methods are being used increasingly in drug discovery, particularly for finding novel lead compounds. Although these "random" methods sample larger areas of chemical space than traditional synthetic approaches, only a relatively small percentage of all possible compounds are practically accessible. It is therefore helpful to select regions of chemical space that have greater likelihood of yielding useful leads. When three-dimensional structural data are available for the target molecule this can be achieved by applying structure-based computational design methods to focus the combinatorial library. This is advantageous over the standard usage of computational methods to design a small number of specific novel ligands, because here computation is employed as part of the combinatorial design process and so is required only to determine a propensity for binding of certain chemical moieties in regions of the target molecule. This paper describes the application of the Multiple Copy Simultaneous Search (MCSS) method, an active site mapping and de novo structure-based design tool, to design a focused combinatorial library for the class II MHC protein HLA-DR4. Methods for the synthesizing and screening the computationally designed library are presented; evidence is provided to show that binding was achieved. Although the structure of the protein-ligand complex could not be determined, experimental results including cross-exclusion of a known HLA-DR4 peptide ligand (HA) by a compound from the library. Computational model building suggest that at least one of the ligands designed and identified by the methods described binds in a mode similar to that of native peptides.

AllChem: generating and searching 1020 synthetically accessible structures

AllChem is a system that is intended to make practical the generation and searching of an unprecedentedly vast number ( approximately 10(20)) of synthetically accessible and medicinally relevant structures. Also, by providing possible synthetic routes to a structure along with its design rationale, AllChem encourages simultaneous consideration of both costs and benefits during each lead discovery and optimization decision, thereby promising to be effective with synthetic chemists among its primary users. AllChem is still under intensive development so the following initial description necessarily has more the character of an interim progress report than of a finished research publication.

RM1: A reparameterization of AM1 for H, C, N, O, P, S, F, Cl, Br, and I

Twenty years ago, the landmark AM1 was introduced, and has since had an increasingly wide following among chemists due to its consistently good results and time-tested reliability--being presently available in countless computational quantum chemistry programs. However, semiempirical molecular orbital models still are of limited accuracy and need to be improved if the full potential of new linear scaling techniques, such as MOZYME and LocalSCF, is to be realized. Accordingly, in this article we present RM1 (Recife Model 1): a reparameterization of AM1. As before, the properties used in the parameterization procedure were: heats of formation, dipole moments, ionization potentials and geometric variables (bond lengths and angles). Considering that the vast majority of molecules of importance to life can be assembled by using only six elements: C, H, N, O, P, and S, and that by adding the halogens we can now build most molecules of importance to pharmaceutical research, our training set consisted of 1736 molecules, representative of organic and biochemistry, containing C, H, N, O, P, S, F, Cl, Br, and I atoms. Unlike AM1, and similar to PM3, all RM1 parameters have been optimized. For enthalpies of formation, dipole moments, ionization potentials, and interatomic distances, the average errors in RM1, for the 1736 molecules, are less than those for AM1, PM3, and PM5. Indeed, the average errors in kcal x mol(-1) of the enthalpies of formation for AM1, PM3, and PM5 are 11.15, 7.98, and 6.03, whereas for RM1 this value is 5.77. The errors, in Debye, of the dipole moments for AM1, PM3, PM5, and RM1 are, respectively, 0.37, 0.38, 0.50, and 0.34. Likewise, the respective errors for the ionization potentials, in eV, are 0.60, 0.55, 0.48, and 0.45, and the respective errors, in angstroms, for the interatomic distances are 0.036, 0.029, 0.037, and 0.027. The RM1 average error in bond angles of 6.82 degrees is only slightly higher than the AM1 figure of 5.88 degrees, and both are much smaller than the PM3 and PM5 figures of 6.98 degrees and 9.83 degrees, respectively. Moreover, a known error in PM3 nitrogen charges is corrected in RM1. Therefore, RM1 represents an improvement over AM1 and its similar successor PM3, and is probably very competitive with PM5, which is a somewhat different model, and not fully disclosed. RM1 possesses the same analytical construct and the same number of parameters for each atom as AM1, and, therefore, can be easily implemented in any software that already has AM1, not requiring any change in any line of code, with the sole exception of the values of the parameters themselves.

Conformational sampling via a self-regulating effective energy surface

The difficulty of efficiently sampling the phase space of complex systems with rough energy surfaces is well known. Typical solutions to the problem involve accelerating the crossing of barriers, but such methods often have the secondary problem that the low-energy states of interest are inadequately sampled, unless the parameters of the search algorithm are modified as the system evolves. A method is presented to improve the sampling with particular emphasis on the low-energy conformations, which make the most important contributions to the thermodynamics of the system. The algorithm proposed here samples the details of the minima, while easily surmounting barriers. This is achieved by introducing a self-regulating sampling variable which depends on the current state of the system. Two replicas of the system are introduced and the sampling variable is treated as a particle coupled to the physical system. The method is illustrated with a simple model system and is applied to the realistic example of barrier crossing in a protein-ligand complex.

Synthetic polymer systems in drug development

The use of synthetic polymers in drug discovery is reviewed, with particular reference to the increasing number of chemistries for therapeutic candidate preparation that employ linear polymers possessing differential solubilities in a variety of solvents. The uses of these polymers as primary components in liquid-phase organic synthesis, particularly applied to the generation of chemical compound libraries, are discussed, along with the challenges facing synthetic chemists and pharmaceutical scientists in preparing new and more efficient supports. The advantages inherent to the emerging field of liquid-phase combinatorial synthesis (LPCS) are considered and a number of key therapeutic targets prepared by newer polymer-supported routes are highlighted. Finally, the potential development issues for both liquid and solid-phase organic chemistries applied to parallel or combinatorial synthesis are discussed, taking into account future trends in the drug discovery and development process as a whole.

Use of MCSS to design small targeted libraries: application to picornavirus ligands

Computational methods were used to design structure-based combinatorial libraries of antipicornaviral capsid-binding ligands. The multiple copy simultaneous search (MCSS) program was employed to calculate functionality maps for many diverse functional groups for both the poliovirus and rhinovirus capsid structures in the region of the known drug binding pocket. Based on the results of the MCSS calculations, small combinatorial libraries consisting of 10s or 100s of three-monomer compounds were designed and synthesized. Ligand binding was demonstrated by a noncell-based mass spectrometric assay, a functional immuno-precipitation assay, and crystallographic analysis of the complexes of the virus with two of the candidate ligands. The P1/Mahoney poliovirus strain was used in the experimental studies. A comparison showed that the MCSS calculations had correctly identified the observed binding site for all three monomer units in one ligand and for two out of three in the other ligand. The correct central monomer position in the second ligand was reproduced in calculations in which the several key residues lining the pocket were allowed to move. This study validates the computational methodology. It also illustrates that subtle changes in protein structure can lead to differences in docking results and points to the importance of including target flexibility, as well as ligand flexibility, in the design process.

Design of inhibitors of Ras--Raf interaction using a computational combinatorial algorithm

Drugs that inhibit important protein-protein interactions are hard to find either by screening or rational design, at least so far. Most drugs on the market that target proteins today are therefore aimed at well-defined binding pockets in proteins. While computer-aided design is widely used to facilitate the drug discovery process for binding pockets, its application to the design of inhibitors that target the protein surface initially seems to be limited because of the increased complexity of the task. Previously, we had started to develop a computational combinatorial design approach based on the well-known 'multiple copy simultaneous search' (MCSS) procedure to tackle this problem. In order to identify sequence patterns of potential inhibitor peptides, a three-step procedure is employed: first, using MCSS, the locations of specific functional groups on the protein surface are identified; second, after constructing the peptide main chain based on the location of favorite locations of N-methylacetamide groups, functional groups corresponding to amino acid side chains are selected and connected to the main chain C(alpha) atoms; finally, the peptides generated in the second step are aligned and probabilities of amino acids at each position are calculated from the alignment scheme. Sequence patterns of potential inhibitors are determined based on the propensities of amino acids at each C(alpha) position. Here we report the optimization of inhibitor peptides using the sequence patterns determined by our method. Several short peptides derived from our prediction inhibit the Ras--Raf association in vitro in ELISA competition assays, radioassays and biosensor-based assays, demonstrating the feasibility of our approach. Consequently, our method provides an important step towards the development of novel anti-Ras agents and the structure-based design of inhibitors of protein--protein interactions.

X-ray structures of small ligand-FKBP complexes provide an estimate for hydrophobic interaction energies

A new crystal form of native FK506 binding protein (FKBP) has been obtained which has proved useful in ligand binding studies. Three different small molecule ligand complexes and the native enzyme have been determined at higher resolution than 2.0 A. Dissociation constants of the related small molecule ligands vary from 20 mM for dimethylsulphoxide to 200 microM for tetrahydrothiophene 1-oxide. Comparison of the four available crystal structures shows that the protein structures are identical to within experimental error, but there are differences in the water structure in the active site. Analysis of the calculated buried surface areas of these related ligands provides an estimated van der Waals contribution to the binding energy of -0.5 kJ/A(2) for non-polar interactions between ligand and protein.

A method for computational combinatorial peptide design of inhibitors of Ras protein

A computational combinatorial approach is proposed for the design of a peptide inhibitor of Ras protein. The procedure involves three steps. First, a 'Multiple Copy Simultaneous Search' identifies the location of specific functional groups on the Ras surface. This search method allowed us to identify an important binding surface consisting of two beta strands (residues 5-8 and 52-56), in addition to the well known Ras effector loop and switch II region. The two beta strands had not previously been reported to be involved in Ras-Raf interaction. Second, after constructing the peptide inhibitor chain based on the location of N-methylacetamide (NMA) minima, functional groups are selected and connected to the main chain Calpha atom. This step generates a number of possible peptides with different sequences on the Ras surface. Third, potential inhibitors are designed based on a sequence alignment of the peptides generated in the second step. This computational approach reproduces the conserved pattern of hydrophobic, hydrophilic and charged amino acids identified from the Ras effectors. The advantages and limitations of this approach are discussed.

An analysis of conformational changes on protein-protein association: implications for predictive docking

Conformational changes on complex formation have been measured for 39 pairs of structures of complexed proteins and unbound equivalents, averaged over interface and non-interface regions and for individual residues. We evaluate their significance by comparison with the differences seen in 12 pairs of independently solved structures of identical proteins, and find that just over half have some substantial overall movement. Movements involve main chains as well as side chains, and large changes in the interface are closely involved with complex formation, while those of exposed non-interface residues are caused by flexibility and disorder. Interface movements in enzymes are similar in extent to those of inhibitors. All eight of the complexes (six enzyme-inhibitor and two antibody-antigen) that have structures of both components in an unbound form available show some significant interface movement. However, predictive docking is successful even when some of the largest changes occur. We note however that the situation may be different in systems other than the enzyme-inhibitors which dominate this study. Thus the general model is induced fit but, because there is only limited conformational change in many systems, recognition can be treated as lock and key to a first approximation.

Chance favors the prepared mind--from serendipity to rational drug design

Accidental discoveries always played an important role in science, especially in the search for new drugs. Several examples of serendipitous findings, leading to therapeutically useful drugs, are presented and discussed. Captopril, an antihypertensive Angiotensin-converting enzyme inhibitor, was the first drug that could be derived from a structural model of a protein. Dorzolamide, a Carboanhydrase inhibitor for the treatment of glaucoma, and the HIV protease inhibitors Saquinavir, Indinavir, Ritonavir, and Nelfinavir are further examples of therapeutically used drugs from structure-based design. More enzyme inhibitors, e.g. the anti-influenza drugs Zanamivir and GS 4104, are in clinical development. In the absence of a protein 3D structure, the 3D structures of certain ligands may be used for rational design. This approach is exemplified by the design of specifically acting integrin receptor antagonists. In the last years, combinatorial and computational approaches became important methods for rational drug design. SAR by NMR searches for low-affinity ligands that bind to proximal subsites of an enzyme; linkage with an appropriate tether produces nanomolar inhibitors. The de novo design program LUDI and the docking program FlexX are tools for the computer-aided design of protein ligands. Work is in progress to combine such approaches to strategies for combinatorial drug design.

A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases

The discovery of various protein/receptor targets from genomic research is expanding rapidly. Along with the automation of organic synthesis and biochemical screening, this is bringing a major change in the whole field of drug discovery research. In the traditional drug discovery process, the industry tests compounds in the thousands. With automated synthesis, the number of compounds to be tested could be in the millions. This two-dimensional expansion will lead to a major demand for resources, unless the chemical libraries are made wisely. The objective of this work is to provide both quantitative and qualitative characterization of known drugs which will help to generate "drug-like" libraries. In this work we analyzed the Comprehensive Medicinal Chemistry (CMC) database and seven different subsets belonging to different classes of drug molecules. These include some central nervous system active drugs and cardiovascular, cancer, inflammation, and infection disease states. A quantitative characterization based on computed physicochemical property profiles such as log P, molar refractivity, molecular weight, and number of atoms as well as a qualitative characterization based on the occurrence of functional groups and important substructures are developed here. For the CMC database, the qualifying range (covering more than 80% of the compounds) of the calculated log P is between -0.4 and 5.6, with an average value of 2.52. For molecular weight, the qualifying range is between 160 and 480, with an average value of 357. For molar refractivity, the qualifying range is between 40 and 130, with an average value of 97. For the total number of atoms, the qualifying range is between 20 and 70, with an average value of 48. Benzene is by far the most abundant substructure in this drug database, slightly more abundant than all the heterocyclic rings combined. Nonaromatic heterocyclic rings are twice as abundant as the aromatic heterocycles. Tertiary aliphatic amines, alcoholic OH and carboxamides are the most abundant functional groups in the drug database. The effective range of physicochemical properties presented here can be used in the design of drug-like combinatorial libraries as well as in developing a more efficient corporate medicinal chemistry library.

X-ray structures and analysis of 11 cyclosporin derivatives complexed with cyclophilin A

Eight new X-ray structures of different cyclophilin A/cyclosporin-derivative complexes are presented. These structures, combined with the existing three published cyclosporin complexes, provide a useful structural database for the analysis of protein-ligand interactions. The effect of small chemical differences on protein-ligand hydrogen-bonding, van der Waals interactions and water structure is presented.

The synthesis and screening of a combinatorial peptide library for affinity ligands for glycosylated haemoglobin

This paper reports the synthesis and screening of a combinatorial peptide library for new affinity ligands for glycosylated haemoglobin (HbA1c), which is an important indicator of diabetes control. The new ligands are suitable for large-scale synthesis and overcome the disadvantages of antibodies (unstable and expensive to produce etc.), while remaining as efficient as antibodies in binding to the analyte. The library consisted of 262,144 hexapeptides synthesised using the one-bead-one-compound technique. The hexapeptides attached onto beads were screened with glycosylated haemoglobin HbA1c. The structures of the peptides exhibiting high affinity were characterised by Edman microsequencing. Computer modelling simulation of one of the lead sequences has shown that this class of ligand has a high affinity and specificity for glycosylated haemoglobin.

Computer-Aided Design of Thrombin Inhibitors

Computer-aided ligand design is an active, challenging, and multidisciplinary research field that blends knowledge of biochemistry, physics, and computer sciences. Whenever it is possible to experimentally determine or to model the three-dimensional structure of a pharmacologically relevant enzyme or receptor, computational approaches can be used to design specific high-affinity ligands. This article describes methods, applications, and perspectives of computer-assisted ligand design.

Use of the multiple copy simultaneous search (MCSS) method to design a new class of picornavirus capsid binding drugs

A combinatorial ligand design approach based on the multiple copy simultaneous search (MCSS) method and a simple scheme for joining MCSS functional group sites was applied to the binding pocket of P3/Sabin poliovirus and rhinovirus 14. The MCSS method determines where specific functional (chemical) groups have local potential energy minima in the binding site. Before the virus application, test calculations were run to determine the optimal set of input parameters to be used in evaluating the MCSS results. The MCSS minima are analysed and selected minima are connected with (CH2)n linkers to form candidate ligands, whose structures are optimized in the binding site. Estimates of the binding strength were made for the ligands and compared with those for known drugs. The results indicate that the proposed ligands should bind to P3/Sabin poliovirus at least as well as the best of the existing drugs, and that they should also bind to P1/Mahoney poliovirus and rhinovirus 14. A detailed comparison of the poliovirus and rhinovirus binding pockets and an analysis of drug binding specificity is presented.

Computational combinatorial ligand design: application to human alpha-thrombin

A new method is presented for computer-aided ligand design by combinatorial selection of fragments that bind favorably to a macromolecular target of known three-dimensional structure. Firstly, the multiple-copy simultaneous-search procedure (MCSS) is used to exhaustively search for optimal positions and orientations of functional groups on the surface of the macromolecule (enzyme or receptor fragment). The MCSS minima are then sorted according to an approximated binding free energy, whose solvation component is expressed as a sum of separate electrostatic and nonpolar contributions. The electrostatic solvation energy is calculated by the numerical solution of the linearized Poisson-Boltzmann equation, while the nonpolar contribution to the binding free energy is assumed to be proportional to the loss in solvent-accessible surface area. The program developed for computational combinatorial ligand design (CCLD) allows the fast and automatic generation of a multitude of highly diverse compounds, by connecting in a combinatorial fashion the functional groups in their minimized positions. The fragments are linked as two atoms may be either fused, or connected by a covalent bond or a small linker unit. To avoid the combinatorial explosion problem, pruning of the growing ligand is performed according to the average value of the approximated binding free energy of its fragments. The method is illustrated here by constructing candidate ligands for the active site of human alpha-thrombin. The MCSS minima with favorable binding free energy reproduce the interaction patterns of known inhibitors. Starting from these fragments, CCLD generates a set of compounds that are closely related to high-affinity thrombin inhibitors. In addition, putative ligands with novel binding motifs are suggested. Probable implications of the MCSS-CCLD approach for the evolving scenario of drug discovery are discussed.

Optimization and visualization of molecular diversity of combinatorial libraries

One of the major goals of rational design of combinatorial libraries is to design libraries with maximum diversity to enhance the potential of finding active compounds in the initial rounds of high-throughput screening programs. We present strategies to visualize and optimize the structural diversity of sets of molecules, which can be either potential substituents to be attached at specific positions of the library scaffold, or entire molecules corresponding to enumerated libraries. The selection of highly diverse subsets of molecules from the library is based on the stochastic optimization of 'Diversity' functions using a single-point-mutation Monte Carlo technique. The Diversity functions are defined in terms of the distances among molecules in multidimensional property space resulting from the calculation of 2D and 3D molecular descriptors. Several Diversity functions, including an implementation of D-Optimal design, are applied to select diverse subsets and the results are compared. The diversity of the selected subsets of molecules is visualized by embedding the intermolecular distances, defined by the molecules in multidimensional property space, into a three-dimensional space.

Current computational tools for de novo ligand design

Several new algorithms have been proposed recently for computational de novo ligand design. Empirical scoring functions are now available to prioritize the suggested structures. The first successful applications have been reported.