Making "real" molecules in virtual space

Predicting "realistic" compounds of given chemical reactions with virtual synthesis tools usually requires the manual intervention of experienced chemists in the enumeration phase for the selection of appropriate reactants, assignment of the corresponding reaction sites, and removal of the unlikely products. To automate the virtual synthesis process, we have moved the expertise intensive parts from the compound library design phase to the reaction library design phase. ChemAxon is building an in silico reaction library containing important preparative transformations, where each reaction definition contains a generic transformation scheme and additional rules to handle the various starting compounds according to the corresponding chemo-, regio-, and stereoselectivity issues. Having well designed reaction definitions in hand, our software tool is able to generate synthetically feasible compound libraries with minimal effort in the enumeration phase.     

Combinatorics of combinatorial chemistry

The hot topic among medicinal chemists today is a novel technique for chemical synthesis in drug research called combinatorial chemistry, where usually a core structure and some building‐block molecules are given and all combinatorially possible combinations are produced. The resulting set of compounds (called a library) can afterwards be systematically screened for a desired biological activity. In this paper we discuss the applications of the mathematical discipline of combinatorics to this process, especially an algorithm for the exhaustive and redundancy‐free generation of a combinatorial library as well as equations for the enumeration of library sizes. This revised version was published online in July 2006 with corrections to the Cover Date.     

Multiobjective optimization of combinatorial libraries

Combinatorial chemistry and high-throughput screening have caused a fundamental shift in the way chemists contemplate experiments. Designing a combinatorial library is a controversial art that involves a heterogeneous mix of chemistry, mathematics, economics, experience, and intuition. Although there seems to be little agreement as to what constitutes an ideal library, one thing is certain: only one property or measure seldom defines the quality of the design. In most real-world applications, a good experiment requires the simultaneous optimization of several, often conflicting, design objectives, some of which may be vague and uncertain. In this paper, we discuss a class of algorithms for subset selection rooted in the principles of multiobjective optimization. Our approach is to employ an objective function that encodes all of the desired selection criteria, and then use a simulated annealing or evolutionary approach to identify the optimal (or a nearly optimal) subset from among the vast number of possibilities. Many design criteria can be accommodated, including diversity, similarity to known actives, predicted activity and/or selectivity determined by quantitative structure-activity relationship (QSAR) models or receptor binding models, enforcement of certain property distributions, reagent cost and availability, and many others. The method is robust, convergent, and extensible, offers the user full control over the relative significance of the various objectives in the final design, and permits the simultaneous selection of compounds from multiple libraries in full- or sparse-array format.     

Reagent Selector: using Synthon Analysis to visualize reagent properties and assist in combinatorial library design

Reagent Selector is an intranet-based tool that aids in the selection of reagents for use in combinatorial library construction. The user selects an appropriate reagent group as a query, for example, primary amines, and further refines it on the basis of various physicochemical properties, resulting in a list of potential reagents. The results of this selection process are, in turn, converted into synthons: the fragments or R-groups that are to be incorporated into the combinatorial library. The Synthon Analysis interface graphically depicts the chemical properties for each synthon as a function of the topological bond distance from the scaffold attachment point. Displayed in this fashion, the user is able to visualize the property space for the universe of synthons as well as that of the synthons selected. Ultimately, the reagent list that embodies the selected synthons is made available to the user for reagent procurement. Application of the approach to a sample reagent list for a G-protein coupled receptor targeted library is described.     

Automated compound verification using 2D-NMR HSQC data in an open-access environment

Since the introduction of NMR prediction software, medicinal chemists have imagined submitting their compounds to corporate compound registration systems that would ultimately display a simplified pass/fail result. We initially implemented such a system based on HPLC and liquid chromatography mass spectrometry (LCMS) data that is embedded within our industry standard sample submission and registration process. By using gradient-heteronuclear single quantum coherence (HSQC) experiments, we have extended this concept to NMR data through a comparison of experimentally acquired data against predicted (1)H and (13)C NMR data. Integration of our compound registration system with our analytical instruments now provides our chemists unattended and automated NMR verification for collections of submitted compounds. The benefits achieved from automated processing and interpretation of results produced enhanced confidence in our compound library and released the chemists from the tedium of manipulating large amounts of data. This allows scientists to focus more of their attention to the drug discovery process.     

ENPDA: an evolutionary structure-based <Emphasis Type="Italic">de novo</Emphasis> peptide design algorithm

Summary One of the goals of computational chemists is to automate the de novo design of bioactive molecules. Despite significant advances in computational approaches to ligand design and binding energy evaluation, novel procedures for ligand design are required. Evolutionary computation provides a new approach to this design endeavor. We propose an evolutionary tool for de novo peptide design, based on the evaluation of energies for peptide binding to a user-defined protein surface patch. Special emphasis has been placed on the evaluation of the proposed peptides, leading to two different evaluation heuristics. The software developed was successfully tested on the design of ligands for the proteins prolyl oligopeptidase, p53, and DNA gyrase.     

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.     

Library Design Guided by In-house Developed Computer Tools

In recent years, combinatorial library synthesis for drug discovery begins to migrate from library synthesis solely dictated by chemistry availability to design and synthesis of libraries with more drug-like properties. Lipinski's rule of five has been used to evaluate drug-like properties of individual compound; recently LibProTM, a new computation program has been developed at Pharmacopeia to evaluate durg-like properties of libraries. By using LibPrpTM, chemists at Pharmacopeia are able to obtain information of molecular weight and ClogP distribution of a library, and percentage of library members that violate Lipinski's rule after input structures of synthons for each combinatorial step. Currently, a "virtual library design” approach that is to calculate properties of a library at conceptual phase of the library design has been used to predetermine the value of the library. Also a new computer program used to predict "Absorption” of compounds will also be discussed.     

Copper-Catalyzed Aminothiolation of 1,3-Dienes via a Dihydrothiazine Intermediate

Heteroatom-containing organic molecules are of particular interest to medicinal chemists and materials scientists. A strategy to reach these architectures via direct difunctionalization of abundant 1,3-dienes is especially attractive. Herein, we describe the development of a regio- and diastereoselective 1,4-aminothiolation of 1,3-dienes with a sulfur diimide reagent, a copper catalyst, and alkyl Grignard reagents. This unique protocol provides remote nitrogen and sulfur functionalities with high levels of stereocontrol. The reaction proceeds via a tandem hetero-Diels–Alder cycloaddition of N,N′-bis(benzenesulfonyl)sulfur diimide with 1,3-diene followed by copper-catalyzed Grignard substitution. Mechanistic studies support a copper catalyzed formation of an unprecedented [10-S-4] sulfurane that reductively eliminates to afford a 3,6-dihydrothiazine, which is selectively converted to 1,4-aminothiols.     

MDMS: Software Facilitating Performing Molecular Dynamics Simulations

Molecular Dynamics Made Simple (MDMS) is software that facilitates performing molecular dynamics (MD) simulations of solvated protein/protein–ligand complexes with Amber, one of the most popular MD codes. It guides users through the whole process of running MD starting with choosing a protein structure, preparing the model, parametrization of the system, establishing parameters for controlling MD, and finally running simulations. By accommodating every step required for running MD, this software ensures that the simulations performed by a user will provide as realistic insight as it is possible. Its sequential structure and a text-based interface ensure ease of use, while the flexibility required for complex cases is still preserved. MDMS also provides a very time-efficient and streamlined method to start MD simulations, which makes it a feasible tool for both novices and experienced computational chemists. © 2019 Wiley Periodicals, Inc.     

Enumerating the total colorings of a polyhedron and application to polyhedral links

In this paper we consider the enumeration problem of a particular three-dimensional molecular or chemical compound system which has a polyhedral frame where the vertices, edges and faces represent ‘units’ such as atoms, bonds, ligands, polymers, or other objects of chemical interests. In this system, chirality is also taken into account. This enumeration problem is mathematically modeled as the ‘total coloring’ enumeration problem of a polyhedron: i.e., the number of ways to color all the vertices, edges and faces of the polyhedron by using three or more corresponding color sets, in which some colors may be chiral. We establish a general formula for this enumeration problem by extending the fundamental version of Pólya’s enumeration theorem. In particular, we apply this technique to the enumeration problem of polyhedral links which have received special attention from biochemists, mathematical chemists and mathematicians over the past two decades.     

Beyond mere diversity: tailoring combinatorial libraries for drug discovery

Combinatorial library design attempts to choose the best set of substituents for a combinatorial synthetic scheme to maximize the chances of finding a useful compound, such as a drug lead. Initial efforts were focused primarily on maximizing diversity, perhaps allowing some bias by the inclusion of a small, fixed set of pharmacophoric substituents. However, many factors besides diversity impact good library design for drug discovery. A library can be better "tailored" by assigning the candidate substituents to categories such as polar, pharmacophoric, rigid, low molecular weight, and expensive. Stratified sampling by successive steps of D-optimal design generates diverse designs which are also consistent with desirable profiles of these properties. Comparing the diversity scores among design profiles reveals the tradeoffs between diversity, physical property distributions, synthetic difficulty, expense, and pharmacophoric bias. The diversity scores can be calibrated by scoring the best designs from subsets of the candidates made either from specific classes of substituents or by randomly eliminating candidates. This procedure shows how poor random designs are compared even to highly biased optimal designs. Library design requires a synergistic effort between computational and synthetic medicinal chemists, so specialized interactive software has been developed to integrate substructure searching, display, and statistical experimental design to facilitate this interaction for the effective design of well-tailored libraries.     

Preparation of samarium(II) iodide: quantitative evaluation of the effect of water, oxygen, and peroxide content, preparative methods, and the activation of samarium metal

Samarium(II) iodide (SmI(2)) is one of the most important reducing agents in organic synthesis. Synthetic chemistry promoted by SmI(2) depends on the efficient and reliable preparation of the reagent. Unfortunately, users can experience difficulties preparing the reagent, and this has prevented realization of the full synthetic potential of SmI(2). To provide synthetic chemists with general and reliable methods for the preparation of SmI(2), a systematic evaluation of the factors involved in its synthesis has been carried out. Our studies confirm that SmI(2) is a user-friendly reagent. Factors such as water, oxygen, and peroxide content in THF have little influence on the synthesis of SmI(2). In addition, the use of specialized glovebox equipment or Schlenk techniques is not required for the preparation of SmI(2). However, our studies suggest that the quality of samarium metal is an important factor and that the use of low quality metal is the main cause of failed preparations of the reagent. Accordingly, we report a straightforward method for activation of "inactive" samarium metal and demonstrate the broad utility of this protocol through the electron transfer reductions of a range of substrates using SmI(2) prepared from otherwise "inactive" metal. An investigation into the stability of SmI(2) solutions and an evaluation of commercially available solutions of the reagent is also reported.     

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

We present a novel computer algorithm, called GLARE (Global Library Assessment of REagents), that addresses the issue of optimal reagent selection in combinatorial library design. This program reduces or eliminates the time a medicinal chemist spends examining reagents which a priori cannot be part of a "good" library. Our approach takes the large reagent sets returned by standard chemical database queries and produces often considerably reduced reagent sets that are well-behaved with respect to a specific template. The pruning enforces "goodness" constraints such as the Lipinski rule of five on the product properties such that any reagent selection from the resulting sets produces only "good" products. The algorithm we implemented has three important features: (i) As opposed to genetic algorithms or other stochastic algorithms, GLARE uses a deterministic greedy procedure that smoothly filters out nonviable reagents. (ii) The pruning method can be biased to produce reagent sets with a balanced size, conserving proportionally more reagents in smaller sets. (iii) For very large combinatorial libraries, a partitioning scheme allows libraries as large as 10(12) to be evaluated in 0.25 s on an IBM AMD Opteron processor. This algorithm is validated on a diverse set of 12 libraries. The results that we obtained show an excellent compliance to the product property requirements and very fast timings.     

Integrating medicinal chemistry, organic/combinatorial chemistry, and computational chemistry for the discovery of selective estrogen receptor modulators with Forecaster, a novel platform for drug discovery

As part of a large medicinal chemistry program, we wish to develop novel selective estrogen receptor modulators (SERMs) as potential breast cancer treatments using a combination of experimental and computational approaches. However, one of the remaining difficulties nowadays is to fully integrate computational (i.e., virtual, theoretical) and medicinal (i.e., experimental, intuitive) chemistry to take advantage of the full potential of both. For this purpose, we have developed a Web-based platform, Forecaster, and a number of programs (e.g., Prepare, React, Select) with the aim of combining computational chemistry and medicinal chemistry expertise to facilitate drug discovery and development and more specifically to integrate synthesis into computer-aided drug design. In our quest for potent SERMs, this platform was used to build virtual combinatorial libraries, filter and extract a highly diverse library from the NCI database, and dock them to the estrogen receptor (ER), with all of these steps being fully automated by computational chemists for use by medicinal chemists. As a result, virtual screening of a diverse library seeded with active compounds followed by a search for analogs yielded an enrichment factor of 129, with 98% of the seeded active compounds recovered, while the screening of a designed virtual combinatorial library including known actives yielded an area under the receiver operating characteristic (AU-ROC) of 0.78. The lead optimization proved less successful, further demonstrating the challenge to simulate structure activity relationship studies.     

Copper‐Catalyzed Aminothiolation of 1,3‐Dienes via a Dihydrothiazine Intermediate

Heteroatom‐containing organic molecules are of particular interest to medicinal chemists and materials scientists. A strategy to reach these architectures via direct difunctionalization of abundant 1,3‐dienes is especially attractive. Herein, we describe the development of a regio‐ and diastereoselective 1,4‐aminothiolation of 1,3‐dienes with a sulfur diimide reagent, a copper catalyst, and alkyl Grignard reagents. This unique protocol provides remote nitrogen and sulfur functionalities with high levels of stereocontrol. The reaction proceeds via a tandem hetero‐Diels–Alder cycloaddition of N,N′‐bis(benzenesulfonyl)sulfur diimide with 1,3‐diene followed by copper‐catalyzed Grignard substitution. Mechanistic studies support a copper catalyzed formation of an unprecedented [10‐S‐4] sulfurane that reductively eliminates to afford a 3,6‐dihydrothiazine, which is selectively converted to 1,4‐aminothiols.     

Chemistry of biologically important flavones

The syntheses of flavones with biologically important functional groups like C-glycoside, isoprenyl, and hydroxy functionalities at different positions available to medicinal chemists for SAR studies are reviewed. Some rearrangements and transformations facilitating the functionalization of flavones are also discussed.     

IADE: a system for intelligent automatic design of bioisosteric analogs

IADE, a software system supporting molecular modellers through the automatic design of non-classical bioisosteric analogs, scaffold hopping and fragment growing, is presented. The program combines sophisticated cheminformatics functionalities for constructing novel analogs and filtering them based on their drug-likeness and synthetic accessibility using automatic structure-based design capabilities: the best candidates are selected according to their similarity to the template ligand and to their interactions with the protein binding site. IADE works in an iterative manner, improving the fitness of designed molecules in every generation until structures with optimal properties are identified. The program frees molecular modellers from routine, repetitive tasks, allowing them to focus on analysis and evaluation of the automatically designed analogs, considerably enhancing their work efficiency as well as the area of chemical space that can be covered. The performance of IADE is illustrated through a case study of the design of a nonclassical bioisosteric analog of a farnesyltransferase inhibitor??an analog that has won a recent ??Design a Molecule?? competition.