GLARE: a new approach for filtering large reagent lists in combinatorial library design using product properties

Z-matrix template-based substitution approach for enumeration of 3D molecular structures

The exhaustive enumeration of 3D chemical structures based on Z-matrix templates has recently been used in the quantum chemical investigation of constitutional isomers, diastereomers and rotamers. This simple yet powerful initial structure generation approach can apply beyond the investigation of compounds of identical formula by quantum chemical methods. This paper provides a comprehensive description of the overall concept followed by a practical tutorial to the approach.•The four steps required for Z-matrix template-based substitution are template construction, generation of tuples for substitution sites, removal of duplicate tuples and substitution on the template.•The generated tuples can be used to create chemical identifiers to query compound properties from chemical databases.•All of these steps are demonstrated in this paper by common model compounds and are very straightforward for an undergraduate audience to reproduce. A comparison of the approach in this paper and other options is also discussed.

Design of Novel Drug-like Molecules Using Informatics Rich Secondary Metabolites Analysis of Indian Medicinal and Aromatic Plants

BACKGROUND

Several medicinal plants are being used in Indian medicine systems from ancient times. However, in most cases, the specific molecules or the active ingredients responsible for the medicinal or therapeutic properties are not yet known.

OBJECTIVE

This study aimed to report a computational protocol as well as a tool for generating novel potential drug candidates from the bioactive molecules of Indian medicinal and aromatic plants through the chemoinformatics approach.

METHODS

We built a database of the Indian medicinal and aromatic plants coupled with associated information (plant families, plant parts used for the medicinal purpose, structural information, therapeutic properties, etc.) We also developed a Java-based chemoinformatics open-source tool called DoMINE (Database of Medicinally Important Natural products from plantaE) for the generation of virtual library and screening of novel molecules from known medicinal plant molecules. We employed chemoinformatics approaches to in-silico screened metabolites from 104 Indian medicinal and aromatic plants and designed novel drug-like bioactive molecules. For this purpose, 1665 ring containing molecules were identified by text mining of literature related to the medicinal plant species, which were later used to extract 209 molecular scaffolds. Different scaffolds were further used to build a focused virtual library. Virtual screening was performed with cluster analysis to predict drug-like and lead-like molecules from these plant molecules in the context of drug discovery. The predicted drug-like and lead-like molecules were evaluated using chemoinformatics approaches and statistical parameters, and only the most significant molecules were proposed as the candidate molecules to develop new drugs.

RESULTS AND CONCLUSION

The supra network of molecules and scaffolds identifies the relationship between the plant molecules and drugs. Cluster analysis of virtual library molecules showed that novel molecules had more pharmacophoric properties than toxicophoric and chemophoric properties. We also developed the DoMINE toolkit for the advancement of natural product-based drug discovery through chemoinformatics approaches. This study will be useful in developing new drug molecules from the known medicinal plant molecules. Hence, this work will encourage experimental organic chemists to synthesize these molecules based on the predicted values. These synthesized molecules need to be subjected to biological screening to identify potential molecules for drug discovery research.

The In Silico Drug Discovery Toolbox: Applications in Lead Discovery and Optimization

BACKGROUND

Discovery and development of a new drug is a long lasting and expensive journey that takes around 20 years from starting idea to approval and marketing of new medication. Despite R&D expenditures have been constantly increasing in the last few years, the number of new drugs introduced into market has been steadily declining. This is mainly due to preclinical and clinical safety issues, which still represent about 40% of drug discontinuation. To cope with this issue, a number of in silico techniques are currently being used for an early stage evaluation/prediction of potential safety issues, allowing to increase the drug-discovery success rate and reduce costs associated with the development of a new drug.

METHODS

In the present review, we will analyse the early steps of the drug-discovery pipeline, describing the sequence of steps from disease selection to lead optimization and focusing on the most common in silico tools used to assess attrition risks and build a mitigation plan.

RESULTS

A comprehensive list of widely used in silico tools, databases, and public initiatives that can be effectively implemented and used in the drug discovery pipeline has been provided. A few examples of how these tools can be problem-solving and how they may increase the success rate of a drug discovery and development program have been also provided. Finally, selected examples where the application of in silico tools had effectively contributed to the development of marketed drugs or clinical candidates will be given.

CONCLUSION

The in silico toolbox finds great application in every step of early drug discovery: (i) target identification and validation; (ii) hit identification; (iii) hit-to-lead; and (iv) lead optimization. Each of these steps has been described in details, providing a useful overview on the role played by in silico tools in the decision-making process to speed-up the discovery of new drugs.

The compromise of virtual screening and its impact on drug discovery

Introduction: Docking and structure-based virtual screening (VS) have been standard approaches in structure-based design for over two decades. However, our understanding of the limitations, potential, and strength of these techniques has enhanced, raising expectations. Areas covered: Based on a survey of reports in the past five years, we assess whether VS: (1) predicts binding poses in agreement with crystallographic data (when available); (2) is a superior screening tool, as often claimed; (3) is successful in identifying chemical scaffolds that can be starting points for subsequent lead optimization cycles. Data shows that knowledge of the target and its chemotypes in postprocessing lead to viable hits in early drug discovery endeavors. Expert opinion: VS is capable of accurate placements in the pocket for the most part, but does not consistently score screening collections accurately. What matters is capitalization on available resources to get closer to a viable lead or optimizable series. Integration of approaches, subjective hit selection guided by knowledge of the receptor or endogenous ligand, libraries driven by experimental guides, validation studies to identify the best docking/scoring that reproduces experimental findings, constraints regarding receptor-ligand interactions, thoroughly designed methodologies, and predefined cutoff scoring criteria strengthen VS's position in pharmaceutical research.

Price-Focused Analysis of Commercially Available Building Blocks for Combinatorial Library Synthesis

Combinatorial libraries are synthesized by combining smaller reagents (building blocks), the price of which is an important component of the total costs associated with the synthetic exercise. A significant portion of commercially available reagents are too expensive for large scale work. In this study, 13 commonly used reagent classes in combinatorial library synthesis (primary and secondary amines, carboxylic acids, alcohols, ketones, aldehydes, boronic acids, acyl halides, sulfonyl chlorides, isocyanates, isothiocyanates, azides and chloroformates) were analyzed with respect to the cost, physicochemical properties (molecular weight and calculated logP), chemical diversity, and 3D-likeness using a large data set. The results define the chemical space accessible under a constraint of limited financial resources.

Structure-based virtual screening for drug discovery: principles, applications and recent advances

Structure-based drug discovery (SBDD) is becoming an essential tool in assisting fast and cost-efficient lead discovery and optimization. The application of rational, structure-based drug design is proven to be more efficient than the traditional way of drug discovery since it aims to understand the molecular basis of a disease and utilizes the knowledge of the three-dimensional structure of the biological target in the process. In this review, we focus on the principles and applications of Virtual Screening (VS) within the context of SBDD and examine different procedures ranging from the initial stages of the process that include receptor and library pre-processing, to docking, scoring and post-processing of topscoring hits. Recent improvements in structure-based virtual screening (SBVS) efficiency through ensemble docking, induced fit and consensus docking are also discussed. The review highlights advances in the field within the framework of several success studies that have led to nM inhibition directly from VS and provides recent trends in library design as well as discusses limitations of the method. Applications of SBVS in the design of substrates for engineered proteins that enable the discovery of new metabolic and signal transduction pathways and the design of inhibitors of multifunctional proteins are also reviewed. Finally, we contribute two promising VS protocols recently developed by us that aim to increase inhibitor selectivity. In the first protocol, we describe the discovery of micromolar inhibitors through SBVS designed to inhibit the mutant H1047R PI3Kα kinase. Second, we discuss a strategy for the identification of selective binders for the RXRα nuclear receptor. In this protocol, a set of target structures is constructed for ensemble docking based on binding site shape characterization and clustering, aiming to enhance the hit rate of selective inhibitors for the desired protein target through the SBVS process.

Pfizer Global Virtual Library (PGVL): a chemistry design tool powered by experimentally validated parallel synthesis information

An unprecedented amount of parallel synthesis information was accumulated within Pfizer over the past 12 years. This information was captured by an informatics tool known as PGVL (Pfizer Global Virtual Library). PGVL was used for many aspects of drug discovery including automated reactant mining and reaction product formation to build a synthetically feasible virtual compound collection. In this report, PGVL is discussed in detail. The chemistry information within PGVL has been used to extract synthesis and design information using an intuitive desktop Graphic User Interface, PGVL Hub. Several real-case examples of PGVL are also presented.

Template-based combinatorial enumeration of virtual compound libraries for lipids

A variety of software packages are available for the combinatorial enumeration of virtual libraries for small molecules, starting from specifications of core scaffolds with attachments points and lists of R-groups as SMILES or SD files. Although SD files include atomic coordinates for core scaffolds and R-groups, it is not possible to control 2-dimensional (2D) layout of the enumerated structures generated for virtual compound libraries because different packages generate different 2D representations for the same structure. We have developed a software package called LipidMapsTools for the template-based combinatorial enumeration of virtual compound libraries for lipids. Virtual libraries are enumerated for the specified lipid abbreviations using matching lists of pre-defined templates and chain abbreviations, instead of core scaffolds and lists of R-groups provided by the user. 2D structures of the enumerated lipids are drawn in a specific and consistent fashion adhering to the framework for representing lipid structures proposed by the LIPID MAPS consortium. LipidMapsTools is lightweight, relatively fast and contains no external dependencies. It is an open source package and freely available under the terms of the modified BSD license.

Application of a sparse matrix design strategy to the synthesis of dos libraries

We have implemented an interactive and practical sparse matrix design strategy for the synthesis of DOS libraries, which facilitates the selection of diverse library members within a user-defined range of physicochemical properties while still maintaining synthetic efficiency. The utility of this approach is illustrated with the synthesis of an 8000-membered library of stereochemically diverse medium-sized rings accessible via a build/couple/pair DOS strategy. Diverse library members were selected from a virtual library by applying the maximum dissimilarity method, while the selection of similar analogs around each diverse product was ensured by picking near neighbors algorithmically based on fingerprint comparison. Adjustable filters on compound properties, which can be tailored to suit the needs of the target biology, facilitated subset selection from the synthetically accessible compounds.

GLARE: A tool for product-oriented design of combinatorial libraries

Combinatorial chemistry with two or more diversity points often leads to an immense number of theoretical products. It is sensible to select the reagents based on the desired properties of the products in the hope of maximizing the usefulness of the synthesized molecules. The presented tool enables the filtering of reagents such that any further reagent selection will form products matching the desired properties. Virtual combinatorial library leading to thousands of billions of products can be rapidly assessed. The publicly available software ( http://glare.sourceforge.net ) and key algorithmic elements are discussed.

Methods for combinatorial and parallel library design

Diversity has historically played a critical role in design of combinatorial libraries, screening sets and corporate collections for lead discovery. Large library design dominated the field in the 1990s with methods ranging anywhere from purely arbitrary through property based reagent selection to product based approaches. In recent years, however, there has been a downward trend in library size. This was due to increased information about the desirable targets gleaned from the genomics revolution and to the ever growing availability of target protein structures from crystallography and homology modeling. Creation of libraries directed toward families of receptors such as GPCRs, kinases, nuclear hormone receptors, proteases, etc., replaced the generation of libraries based primarily on diversity while single target focused library design has remained an important objective. Concurrently, computing grids and cpu clusters have facilitated the development of structure based tools that screen hundreds of thousands of molecules. Smaller "smarter" combinatorial and focused parallel libraries replaced those early un-focused large libraries in the twenty-first century drug design paradigm. While diversity still plays a role in lead discovery, the focus of current library design methods has shifted to receptor based methods, scaffold hopping/bio-isostere searching, and a much needed emphasis on synthetic feasibility. Methods such as "privileged substructures based design" and pharmacophore based design still are important methods for parallel and small combinatorial library design. This chapter discusses some of the possible design methods and presents examples where they are available.

PGVL Hub: An integrated desktop tool for medicinal chemists to streamline design and synthesis of chemical libraries and singleton compounds

PGVL Hub is an integrated molecular design desktop tool that has been developed and globally deployed throughout Pfizer discovery research units to streamline the design and synthesis of combinatorial libraries and singleton compounds. This tool supports various workflows for design of singletons, combinatorial libraries, and Markush exemplification. It also leverages the proprietary PGVL virtual space (which contains 10(14) molecules spanned by experimentally derived synthesis protocols and suitable reactants) for lead idea generation, lead hopping, and library design. There had been an intense focus on ease of use, good performance and robustness, and synergy with existing desktop tools such as ISIS/Draw and SpotFire. In this chapter we describe the three-tier enterprise software architecture, key data structures that enable a wide variety of design scenarios and workflows, major technical challenges encountered and solved, and lessons learned during its development and deployment throughout its production cycles. In addition, PGVL Hub represents an extendable and enabling platform to support future innovations in library and singleton compound design while being a proven channel to deliver those innovations to medicinal chemists on a global scale.

LoFT: similarity-driven multiobjective focused library design

We present LoFT, a tool for focused combinatorial library design. LoFT provides a set of algorithms, constructing a focused library from a chemical fragment space under optimization of multiple design criteria. A weighted multiobjective scoring function based on physicochemical descriptors is employed for traversing the chemical search space. The new aspect of LoFT is that a similarity-driven product-based library design approach is provided on fragment level. For this reason the feature tree descriptor is incorporated for similarity comparison of library compounds to given bioactive molecules as well as for diversifying the resulting libraries. The feature tree descriptor abstracts the molecular graph to a tree structure where the nodes are labeled with physicochemical properties. For comparison, the nodes of two trees are mapped onto each other. This strictly hierarchical mechanism is suitable for the efficient comparison of chemical fragments, allowing the evaluation of the resulting products on fragment level without explicitly enumerating them. LoFT was validated, applying three different data sets. Starting with a random reagent selection, we optimized the libraries using maximum similarity to known bioactive molecules and iteratively adding further criteria. Moreover, we compared these results with data we obtained with FTrees-FS.

CLEVER: pipeline for designing in silico chemical libraries

Advances in virtual screening have created new channels for expediting the process of discovering novel drugs. Of particular relevance and interest are in silico techniques that enable the enumeration of combinatorial chemical libraries, generation of 3D coordinates and assessment of their propensity for drug-likeness. In a bid to provide an integrated pipeline that encompasses the common components functional for designing, managing and analyzing combinatorial chemical libraries, we describe a platform-independent, standalone Java application entitled CLEVER (Chemical Library Editing, Visualizing and Enumerating Resource). CLEVER supports chemical library creation and manipulation, combinatorial chemical library enumeration using user-specified chemical components, chemical format conversion and visualization, as well as chemical compounds analysis and filtration with respect to drug-likeness, lead-likeness and fragment-likeness based on the physicochemical properties computed from the derived molecules. Also provided is an integrated property-based graphing component that visually depicts the diversity, coverage and distribution of selected compound collections. When deployed in conjunction with large-scale virtual screening campaigns, CLEVER can offer insights into what chemical compounds to synthesize, and more importantly, what not to synthesize. The software is available at http://datam.i2r.a-star.edu.sg/clever/.

New directions in library design and analysis

The high costs associated with high-throughput screening (HTS) coupled with the limited coverage and bias of current screening collections is such that diversity analysis continues to be an important criterion in lead generation. Whereas early approaches to diversity analysis were based on traditional descriptors such as two-dimensional fingerprints a recent emphasis has been on assessing scaffold coverage to ensure that a variety of different chemotypes are represented. Moreover, whether designing diverse or focused libraries, it is widely recognised that designs should aim to achieve a balance in a number of different properties and multiobjective optimisation provides an effective way of achieving such designs.

Scaffold composition and biological relevance of screening libraries

The chemical scaffolds from which screening libraries are built have strong influence on the libraries' utility for screening campaigns. Here we present analysis of the scaffold composition of several types of commercially available screening collections and compare those compositions to those of drugs and drug candidates.

Is There a Single 'Best Pool' of Commercial Reagents to Use in Combinatorial Library Design to Conform to a Desired Product–Property Profile?

A novel computer algorithm for library design in combinatorial chemistry, GLARE (Global Library Assessment of Reagent), is used to select an optimal subset of reagents in two related libraries according to the Lipinski rule of five applied to the products. The optimized libraries show excellent compliance with the desired profiles although the original huge libraries do not. Then we show, using ten different virtual libraries, that (a) a relatively small fraction of commercially available reagents is of general use in drug/lead-like combinatorial chemistry and (b) that between 10 and 20% of the reagents are not of general use but specific to a library. This demonstrates the utility of using a product-based reagent selection method.