A fast algorithm for searching for molecules containing a pharmacophore in very large virtual combinatorial libraries.

We present a new algorithm for identifying molecules that display a pharmacophore, or in general a structural motif, by efficiently constructing and screening huge virtual combinatorial libraries of diverse compounds. The uniqueness of this algorithm is its ability to build and screen libraries of ca. 10(18) 3D molecular conformations within a reasonable time scale, thereby increasing the chemical space that can be virtually screened by many orders of magnitude. The algorithm may be used to design new molecules that display a desired pharmacophore on predefined sets of chemical scaffolds. This is demonstrated herein by screening a library of backbone cyclic peptides to find candidate peptido- and proteinomimetics.     

Rational principles of compound selection for combinatorial library design

It is practically impossible in a short period of time to synthesize and test all compounds in any large exhaustive chemical library. We discuss rational approaches to selecting representative subsets of virtual libraries that help direct experimental synthetic efforts for both targeted and diverse library design. For targeted library design, we consider principles based on the similarity to lead molecules. In the case of diverse library design, we discuss algorithms aimed at the selection of both diverse and representative subsets of the entire chemical library space. We illustrate methodologies with several practical examples.     

Application of self-organizing maps in compounds pattern recognition and combinatorial library design

In the computer-aided drug design, in order to find some new leads from a large library of compounds, the pattern recognition study of the diversity and similarity assessment of the chemical compounds is required; meanwhile in the combinatorial library design, more attention is given to design target focusing library along with diversity and drug-likeness criteria. This review presents the current state-of-art applications of Kohonen self-organizing maps (SOM) for studying the compounds pattern recognition, comparing the property of molecular surfaces, distinguishing drug-like and nondrug-like molecules, splitting a dataset into the proper training and test sets before constructing a QSAR (Quantitative Structural-Activity Relationship) model, and also for the combinatorial libraries comparison and the combinatorial library design. The Kohonen self-organizing map will continue to play an important role in drug discovery and library design.     

Design of compound libraries for fragment screening

Approaches to the design of libraries for fragment screening are illustrated with reference to a 20 k generic fragment screening library and a 1.2 k generic NMR screening library. Tools and methods for library design that have been developed within AstraZeneca are described, including Foyfi fingerprints and the Flush program for neighborhood characterization. It will be shown how Flush and the BigPicker, which selects maximally diverse sets of compounds, are used to apply the Core and Layer method for library design. Approaches to partitioning libraries into cocktails are also described.     

Expanding medicinal chemistry into 3D space: metallofragments as 3D scaffolds for fragment-based drug discovery

Fragment-based drug discovery (FBDD) is a powerful strategy for the identification of new bioactive molecules. FBDD relies on fragment libraries, generally of modest size, but of high chemical diversity. Although good chemical diversity in FBDD libraries has been achieved in many respects, achieving shape diversity – particularly fragments with three-dimensional (3D) structures – has remained challenging. A recent analysis revealed that >75% of all conventional, organic fragments are predominantly 1D or 2D in shape. However, 3D fragments are desired because molecular shape is one of the most important factors in molecular recognition by a biomolecule. To address this challenge, the use of inert metal complexes, so-called ‘metallofragments’ (mFs), to construct a 3D fragment library is introduced. A modest library of 71 compounds has been prepared with rich shape diversity as gauged by normalized principle moment of inertia (PMI) analysis. PMI analysis shows that these metallofragments occupy an area of fragment space that is unique and highly underrepresented when compared to conventional organic fragment libraries that are comprised of orders of magnitude more molecules. The potential value of this metallofragment library is demonstrated by screening against several different types of proteins, including an antiviral, an antibacterial, and an anticancer target. The suitability of the metallofragments for future hit-to-lead development was validated through the determination of IC₅₀ and thermal shift values for select fragments against several proteins. These findings demonstrate the utility of metallofragment libraries as a means of accessing underutilized 3D fragment space for FBDD against a variety of protein targets.

Fragment-based drug discovery (FBDD) using 3-dimensional metallofragments is a new strategy for the identification of bioactive molecules.     

Library design practices for success in lead generation with small molecule libraries

The generation of novel structures amenable to rapid and efficient lead optimization comprises an emerging strategy for success in modern drug discovery. Small molecule libraries of sufficient size and diversity to increase the chances of discovery of novel structures make the high throughput synthesis approach the method of choice for lead generation. Despite an industry trend for smaller, more focused libraries, the need to generate novel lead structures makes larger libraries a necessary strategy. For libraries of a several thousand or more members, solid phase synthesis approaches are the most suitable. While the technology and chemistry necessary for small molecule library synthesis continue to advance, success in lead generation requires rigorous consideration in the library design process to ensure the synthesis of molecules possessing the proper characteristics for subsequent lead optimization. Without proper selection of library templates and building blocks, solid phase synthesis methods often generate molecules which are too heavy, too lipophilic and too complex to be useful for lead optimization. The appropriate filtering of virtual library designs with multiple computational tools allows the generation of information-rich libraries within a drug-like molecular property space. An understanding of the hit-to-lead process provides a practical guide to molecular design characteristics. Examples of leads generated from library approaches also provide a benchmarking of successes as well as aspects for continued development of library design practices.     

Molecular design based on 3D pharmacophores. Applications to 5-HT7 receptors

A definition of a pharmacophore for the 5-HT7 antagonists was carried out by searching the common chemical features of selective antagonists from the literature. A molecular design is described by analyzing the differences between this new pharmacophore and three other 3D serotonin pharmacophores previously described. This comparison led to the synthesis of a new series of potent 5-HT7 antagonists.     

The measurement of molecular diversity: A three-dimensional approach

Summary This paper describes a method for selecting a small, highly diverse subset from a large pool of molecules. The method has been employed in the design of combinatorial synthetic libraries for use in high-throughput screening for pharmaceutical lead generation. It computes diversity in terms of the main factors relevant to ligand-protein binding, namely the three-dimensional arrangement of steric bulk and of polar functionalities and molecular entropy. The method was used to select a set of 20 carboxylates suitable for use as side-chain precursors in a polyamine-based library. The method depends on estimates of various physical-chemical parameters involved in ligand-protein binding; experiments examined the sensitivity of the method to these parameters. This paper compares the diversity of randomly and rationally selected side-chain sets; the results suggest that careful design of synthetic combinatorial libraries may increase their effectiveness several-fold.     

Small Targeted Cytotoxics: Current State and Promises from DNA‐Encoded Chemical Libraries

The targeted delivery of potent cytotoxic agents has emerged as a promising strategy for the treatment of cancer and other serious conditions. Traditionally, antibodies against markers of disease have been used as drug‐delivery vehicles. More recently, lower molecular weight ligands have been proposed for the generation of a novel class of targeted cytotoxics with improved properties. Advances in this field crucially rely on efficient methods for the identification and optimization of organic molecules capable of high‐affinity binding and selective recognition of target proteins. The advent of DNA‐encoded chemical libraries allows the construction and screening of compound collections of unprecedented size. In this Review, we survey developments in the field of small ligand‐based targeted cytotoxics and show how innovative library technologies will help develop the drugs of the future.     

Privileged structures: applications in drug discovery

Over the past 15 years the privileged structure concept has emerged as a fruitful approach to the discovery of novel biologically active molecules. Privileged structures are molecular scaffolds with versatile binding properties, such that a single scaffold is able to provide potent and selective ligands for a range of different biological targets through modification of functional groups. In addition, privileged structures typically exhibit good drug-like properties, which in turn leads to more drug-like compound libraries and leads. The net result is the production of high quality leads that provide a solid foundation for further development. The identification of privileged structures will be discussed, emphasizing the importance of understanding the structure-target relationships that confer "privileged" status. This understanding allows privileged structure based libraries to be targeted at distinct target families (e.g. GPCRs, LGIC, enzymes/kinases). Privileged structures have been successfully exploited across and within different target families and promises to be an effective approach to the discovery and optimization of novel bioactive molecules. The application of the privileged structure approach, both in traditional medicinal chemistry and in the design of focused libraries, will be discussed with the aid of illustrative examples.     

In silico designing breast cancer peptide vaccine for binding to MHC class I and II: A molecular docking study

Antigenic peptides or cancer peptide vaccines can be directly delivered to cancer patients to produce immunologic responses against cancer cells. Specifically, designed peptides can associate with Major Histocompatibility Complex (MHC) class I or II molecules on the cell surface of antigen presenting cells activating anti-tumor effector mechanisms by triggering helper T cell (Th) or cytotoxic T cells (CTL). In general, high binding to MHCs approximately correlates with in vivo immunogenicity. Consequently, a molecular docking technique was run on a library of novel discontinuous peptides predicted by PEPOP from Human epidermal growth factor receptor 2 (HER2 ECD) subdomain III. This technique is expected to improve the prediction accuracy in order to identify the best MHC class I and II binder peptides. Molecular docking analysis through GOLD identified the peptide 1412 as the best MHC binder peptide to both MHC class I and II molecules used in the study. The GOLD results predicted HLA-DR4, HLA-DP2 and TCR as the most often targeted receptors by the peptide 1412. These findings, based on bioinformatics analyses, can be exploited in further experimental analyses in vaccine design and cancer therapy to find possible proper approaches providing beneficial effects.     

The measurement of molecular diversity by receptor site interaction simulation

The assembly of large compound libraries for the purpose of screening against various receptor targets to identify chemical leads for drug discovery programs has created a need for methods to measure the molecular diversity of such libraries. The method described here, for which we propose the acronym RESIS (for Receptor Site Interaction Simulation), relates directly to this use. A database is built of three-dimensional representations of the compounds in the library and a set of three-point three-dimensional theoretical receptor sites is generated based on putative hydrophobic and polar interactions. A series of flexible, three-dimensional searches is then performed over the database, using each of the theoretical sites as the basis for one such search. The resulting pattern of hits across the grid of theoretical receptor sites provides a measure of the molecular diversity of the compound library. This can be conveniently displayed as a density map which provides a readily comprehensible visual impression of the library diversity characteristics. A library of 7500 drug compounds derived from the CIPSLINEPC databases was characterized with respect to molecular diversity using the RESIS method. Some specific uses for the information obtained from application of the method are discussed. A comparison was made of the results from the RESIS method with those from a recently published two-dimensional approach for assessing molecular diversity using sets of compounds from the Maybridge database (MAY).     

An evolution-inspired strategy to design disulfide-rich peptides tolerant to extensive sequence manipulation

Natural disulfide-rich peptides (DRPs) are valuable scaffolds for the development of new bioactive molecules and therapeutics. However, there are only a limited number of topologically distinct DRP folds in nature, and most of them suffer from the problem of in vitro oxidative folding. Thus, strategies to design DRPs with new constrained topologies beyond the scope of natural folds are desired. Herein we report a general evolution-inspired strategy to design new DRPs with diverse disulfide frameworks, which relies on the incorporation of two cysteine residues and a random peptide sequence into a precursor disulfide-stabilized fold. These peptides can spontaneously fold in redox buffers to the expected tricyclic topologies with high yields. Moreover, we demonstrated that these DRPs can be used as templates for the construction of phage-displayed peptide libraries, enabling the discovery of new DRP ligands from fully randomized sequences. This study thus paves the way for the development of new DRP ligands and therapeutics with structures not derived from natural DRPs.

A general method was developed to design multicyclic peptides with diverse disulfide frameworks amenable to random peptide library design, enabling the development of new disulfide-rich peptide ligands and therapeutics with structures not derived from natural peptides.     

In Silico Screening of Natural Compounds for Candidates 5HT6 Receptor Antagonists against Alzheimer’s Disease

Alzheimer’s disease (AD), a devastating neurodegenerative disease, is the focus of pharmacological research. One of the targets that attract the most attention for the potential therapy of AD is the serotonin 5HT6 receptor, which is the receptor situated exclusively in CNS on glutamatergic and GABAergic neurons. The neurochemical impact of this receptor supports the hypothesis about its role in cognitive, learning, and memory systems, which are of critical importance for AD. Natural products are a promising source of novel bioactive compounds with potential therapeutic potential as a 5HT6 receptor antagonist in the treatment of AD dementia. The ZINC—natural product database was in silico screened in order to find the candidate antagonists of 5-HT6 receptor against AD. A virtual screening protocol that includes both short-and long-range interactions between interacting molecules was employed. First, the EIIP/AQVN filter was applied for in silico screening of the ZINC database followed by 3D QSAR and molecular docking. Ten best candidate compounds were selected from the ZINC Natural Product database as potential 5HT6 Receptor antagonists and were proposed for further evaluation. The best candidate was evaluated by molecular dynamics simulations and free energy calculations.     

A combinatorial approach toward the discovery of non-peptide, subtype-selective somatostatin receptor ligands

The tetradecapeptide somatostatin is widely distributed throughout the body and is thought to be involved with a variety of regulatory functions. Recently, five human somatostatin receptors (hSSTR1-5) have been cloned and characterized. Several selective peptidal agonists of the hSSTR receptors are known, and we sought to apply this information to the design of novel non-peptide small molecule ligands for each receptor. Initial computational methods identified a 200 nM murine SSTR2 active compound via a database search of our sample collection. A combinatorial library was designed around the structural class of the compound with the goal of rapidly developing this initial lead into the desired subtype-selective small molecules in order to characterize the pharmacology of each of the receptor subtypes. The library was synthesized using the resin-archive, iterative deconvolution format. The total number of unique compounds in the library was expected to be 131,670, present in 79 mixtures of 1330 or 2660 compounds per mixture. Through sequences of screening and mixture deconvolution, the components of selective and highly active (Ki = 50 pM to 200 nM) non-peptide small molecule ligands for somatostatin subtypes 1, 2, 4, and 5 were identified. In addition to discovering compounds with the desired activity and selectivity, useful structure/activity information was generated which can be used in the design of new compounds and second-generation combinatorial libraries.