Complex macrocycle exploration: parallel, heuristic, and constraint-based conformer generation using ForceGen.

ForceGen is a template-free, non-stochastic approach for 2D to 3D structure generation and conformational elaboration for small molecules, including both non-macrocycles and macrocycles. For conformational search of non-macrocycles, ForceGen is both faster and more accurate than the best of all tested methods on a very large, independently curated benchmark of 2859 PDB ligands. In this study, the primary results are on macrocycles, including results for 431 unique examples from four separate benchmarks. These include complex peptide and peptide-like cases that can form networks of internal hydrogen bonds. By making use of new physical movements ("flips" of near-linear sub-cycles and explicit formation of hydrogen bonds), ForceGen exhibited statistically significantly better performance for overall RMS deviation from experimental coordinates than all other approaches. The algorithmic approach offers natural parallelization across multiple computing-cores. On a modest multi-core workstation, for all but the most complex macrocycles, median wall-clock times were generally under a minute in fast search mode and under 2 min using thorough search. On the most complex cases (roughly cyclic decapeptides and larger) explicit exploration of likely hydrogen bonding networks yielded marked improvements, but with calculation times increasing to several minutes and in some cases to roughly an hour for fast search. In complex cases, utilization of NMR data to constrain conformational search produces accurate conformational ensembles representative of solution state macrocycle behavior. On macrocycles of typical complexity (up to 21 rotatable macrocyclic and exocyclic bonds), design-focused macrocycle optimization can be practically supported by computational chemistry at interactive time-scales, with conformational ensemble accuracy equaling what is seen with non-macrocyclic ligands. For more complex macrocycles, inclusion of sparse biophysical data is a helpful adjunct to computation

Study of protein-macrocycle Interactions for lessons in drug design

Macrocycles (MCs) have become an increasing area of interest for drug design efforts, especially for classically “difficult” targets like protein-protein interactions (PPIs). And although there are many examples of successful MC drugs derived from natural products, there is little information about the characteristics of compounds with effective pharmacological and physicochemical properties. In this dissertation, I describe the development of design guidelines for new MC drugs based on a representative set of known inhibitor MCs and their target proteins. Analysis of both the individual MC structures and their interactions in the protein complex resulted in identification of several structural and physicochemical features likely to promote favorable binding and bioavailability. Additionally, investigation of the binding sites on the proteins suggest that MCs can bind targets conventionally considered “non-druggable,” strengthening the argument for exploring MC compounds to increase the druggable target space. Furthermore, this work includes the application of the proposed design guidelines to the development of synthetic MC libraries for a PPI target, the NEMO/IKKβ complex

In Silico Design and Selection of CD44 Antagonists:implementation of computational methodologies in drug discovery and design

Drug discovery (DD) is a process that aims to identify drug candidates through a thorough evaluation of the biological activity of small molecules or biomolecules. Computational strategies (CS) are now necessary tools for speeding up DD. Chapter 1 describes the use of CS throughout the DD process, from the early stages of drug design to the use of artificial intelligence for the de novo design of therapeutic molecules. Chapter 2 describes an in-silico workflow for identifying potential high-affinity CD44 antagonists, ranging from structural analysis of the target to the analysis of ligand-protein interactions and molecular dynamics (MD). In Chapter 3, we tested the shape-guided algorithm on a dataset of macrocycles, identifying the characteristics that need to be improved for the development of new tools for macrocycle sampling and design. In Chapter 4, we describe a detailed reverse docking protocol for identifying potential 4-hydroxycoumarin (4-HC) targets. The strategy described in this chapter is easily transferable to other compounds and protein datasets for overcoming bottlenecks in molecular docking protocols, particularly reverse docking approaches. Finally, Chapter 5 shows how computational methods and experimental results can be used to repurpose compounds as potential COVID-19 treatments. According to our findings, the HCV drug boceprevir could be clinically tested or used as a lead molecule to develop compounds that target COVID-19 or other coronaviral infections. These chapters, in summary, demonstrate the importance, application, limitations, and future of computational methods in the state-of-the-art drug design process

Structure generation and de novo design using reaction networks

This project is concerned with de novo molecular design whereby novel molecules are built in silico and evaluated against properties relevant to biological activity, such as physicochemical properties and structural similarity to active compounds. The aim is to encourage cost-effective compound design by reducing the number of molecules requiring synthesis and analysis. One of the main issues in de novo design is ensuring that the molecules generated are synthesisable. In this project, a method is developed that enables virtual synthesis using rules derived from reaction sequences. Individual reactions taken from reaction databases were connected to form reaction networks. Reaction sequences were then extracted by tracing paths through the network and used to create ‘reaction sequence vectors’ (RSVs) which encode the differences between the start and end points of th esequences. RSVs can be applied to molecules to generate virtual products which are based on literature precedents. The RSVs were applied to structure-activity relationship (SAR) exploration using examples taken from the literature. They were shown to be effective in expanding the chemical space that is accessible from the given starting materials. Furthermore, each virtual product is associated with a potential synthetic route. They were then applied in de novo design scenarios with the aim of generating molecules that are predicted to be active using SAR models. Using a collection of RSVs with a set of small molecules as starting materials for de novo design proved that the method was capable of producing many useful, synthesisable compounds worthy of future study. The RSV method was then compared with a previously published method that is based on individual reactions (reaction vectors or RVs). The RSV approach was shown to be considerably faster than de novo design using RVs, however, the diversity of products was more limited

Diverse Applications of Flow Technology in Discovery Chemistry

The research presented herein describes the development of methods and applications of flow technology in discovery chemistry. The first two chapters highlight the use of several beneficial features offered by flow technology to increase the throughput, safety, and convenience of organic synthesis. The last two chapters describe the use of microfluidic technology as a platform for rapid reaction discovery. Working with researchers at Abbott Laboratories, a droplet-based library method was developed. This approach allowed for the preparation of a theoretically unlimited number of compounds in a single run using minimal amounts of material. The universal nature of this approach was subsequently demonstrated in the preparation of two 20-membered libraries based around thiazole and pyrazole cores. A second methodology study, also completed with researchers at Abbott Laboratories, took advantage of the intrinsic closed environment of flow systems which enabled the creation, reaction, and removal of noxious chemicals in situ. Using these features an in situ synthesis of isocyanides, reagents notorious for their unpleasant smell, was developed. Coupling this method to the Ugi four-component reaction, a series of medicinally relevant amides was synthesized. Reactions performed in the flow system experienced an overall reduction in transformation time from two-days to two-hours and gave yields that were generally higher than those for the same reactions performed on the benchtop or in the microwave. Expanding the application of this technology toward the discovery and development of new synthetic methodologies we partnered with the laboratory of Dr. John A. Porco, Jr. at Boston University to explore transformations of multifunctional substrates. Given the variant nature of these reactions, both a simple iminium ether and a densely functionalized iminium ether derived from a bicyclo[3.2.1]octanoid scaffold were explored. Multidimensional reaction screening on an automated microfluidic platform was employed to facilitate the simultaneous investigation of multiple reaction variables. While the majority of products obtained from the study resulted from expected modes of O- and N- alkylation, several interesting transformations were uncovered. These included the pseudo-dimerization of homophthalic anhydride, an unusual integration of the van Leusen sulfone, and an unexpected carbon-carbon bond forming event of ethyl diazoacetate and acetonitrile. Finally, in a follow-up study, collaboration with Boston University was continued to explore additional reactivity of the bicyclo[3.2.1]octanoid scaffold. Preliminary reaction screens uncovered the synthesis of a series of densely functionalized donor-acceptor cyclopropanes which resulted from the photochemical rearrangement of the bicyclic scaffolds. Expansion of the photochemical screening to a polycyclic iminium ether led to the first example of an aza-di-pi reaction of a charged iminium species. Subjection of the new cyclopropane scaffolds to a variety of reaction conditions led to the discovery of additional rearrangement reactions affording several structurally diverse chemotypes including a fused dihydropyran, a fused pyrrole, a bicyclic imide, and a complex cyclic imine

Enumeration, conformation sampling and population of libraries of peptide macrocycles for the search of chemotherapeutic cardioprotection agents

Peptides are uniquely endowed with features that allow them to perturb previously difficult to drug biomolecular targets. Peptide macrocycles in particular have seen a flurry of recent interest due to their enhanced bioavailability, tunability and specificity. Although these properties make them attractive hit-candidates in early stage drug discovery, knowing which peptides to pursue is non‐trivial due to the magnitude of the peptide sequence space. Computational screening approaches show promise in their ability to address the size of this search space but suffer from their inability to accurately interrogate the conformational landscape of peptide macrocycles. We developed an in‐silico compound enumerator that was tasked with populating a conformationally laden peptide virtual library. This library was then used in the search for cardio‐protective agents (that may be administered, reducing tissue damage during reperfusion after ischemia (heart attacks)). Our enumerator successfully generated a library of 15.2 billion compounds, requiring the use of compression algorithms, conformational sampling protocols and management of aggregated compute resources in the context of a local cluster. In the absence of experimental biophysical data, we performed biased sampling during alchemical molecular dynamics simulations in order to observe cyclophilin‐D perturbation by cyclosporine A and its mitochondrial targeted analogue. Reliable intermediate state averaging through a WHAM analysis of the biased dynamic pulling simulations confirmed that the cardio‐protective activity of cyclosporine A was due to its mitochondrial targeting. Paralleltempered solution molecular dynamics in combination with efficient clustering isolated the essential dynamics of a cyclic peptide scaffold. The rapid enumeration of skeletons from these essential dynamics gave rise to a conformation laden virtual library of all the 15.2 Billion unique cyclic peptides (given the limits on peptide sequence imposed). Analysis of this library showed the exact extent of physicochemical properties covered, relative to the bare scaffold precursor. Molecular docking of a subset of the virtual library against cyclophilin‐D showed significant improvements in affinity to the target (relative to cyclosporine A). The conformation laden virtual library, accessed by our methodology, provided derivatives that were able to make many interactions per peptide with the cyclophilin‐D target. Machine learning methods showed promise in the training of Support Vector Machines for synthetic feasibility prediction for this library. The synergy between enumeration and conformational sampling greatly improves the performance of this library during virtual screening, even when only a subset is used

Synthesis of unnatural enone-containing α-amino acids: precursors to chiral N-heterocycles

A fast and efficient synthetic route was developed for the synthesis of a novel class of enone-containing alpha-amino acid. An amino acid-derived beta-ketophosphonate ester was subjected to Horner-Wadsworth-Emmons conditions using a variety of aldehydes to produce a diverse library of alpha,beta-unsaturated amino acids. E-Configured enone-containing amino acids were also deprotected using a two-stage approach to give the parent alpha-amino acids. A minor modification to the route enabled the synthesis of Z-configured enones via the Still-Gennari reaction. A small library of Z-enones was produced using various aldehydes. Enone-functionalised alpha-amino acids were employed as substrates for an intramolecular cyclisation reaction to generate 6-substituted-4-oxopipecolic acids. A diastereoselective one-pot reductive amination/cyclisation strategy was developed to gain access to the anti-diastereomer of the chiral N-heterocycles. A small selection of 6-substituted-4-oxopipecolic acids was synthesised. 6-Substituted-4-oxopipecolic acids were also reduced diastereoselectively to generate 4- hydroxypipecolic acid analogues

Visible Light-Driven C-H Functionalization Reactions: Methodology Design and Development of a Droplet Microfluidics Screening Platform

The use of visible light for promoting chemical reactivity has far-reaching implications in providing access to otherwise challenging bond constructions in drug discovery, as well as minimizing the environmental impact of industrial pharmaceutical production. Along with harnessing a more sustainable energy source (e.g. sunlight), photocatalysis presents a means to circumvent the use of toxic reagents and hazardous conditions classically employed for promoting free radical chemistry in the synthesis of biologically active compounds. This thesis focuses on the development of visible light-mediated methods for the late-stage functionalization of heterocyclic drug scaffolds, as well as the design of a droplet microfluidics platform for the high-throughput optimization of photocatalytic reactions. Chapter 1 provides a detailed summary of visible light-driven methodology that have been developed to enable the C–H alkylation of biologically relevant (hetero)arenes. The application of photoredox catalysis for alkyl radical generation has given rise to a multitude of methods that feature enhanced functional group tolerance, generality, and operational simplicity. This chapter will highlight examples of visible light-driven Minisci alkylation strategies that represent key advancements in this area of research. The scope and limitation of these transformations will be discussed, with a focus on examining the underlying pathways for alkyl radical generation. Chapter 2 focuses on a method for the photoredox (perfluoro)alkylation of heteroarenes using alkyl carboxylic acid derivatives. Late-stage introduction of alkyl and perfluoroalkylated groups onto unfunctionalized positions on a drug scaffold holds significant potential for accelerating the drug discovery process. As such, the development of a visible light-driven heteroarene alkylation strategy, including optimization studies, elucidation of scope, and mechanistic studies, is described. Chapter 3 describes our efforts in developing a droplet microfluidics-based, nanoelectrospray ionization-mass spectrometry (nESI-MS) platform for screening photoredox catalysis reactions. Both the time and resource-efficient principles governing this technology underscore its anticipated impact on providing accelerated access to an array of diversified drug scaffolds using sustainable, visible light-driven synthetic methods. Application of this system towards the high-throughput late-stage diversification of complex pharmaceutical scaffolds is established in this chapter. Chapter 4 continues to explore the utility of droplet microfluidics as a platform for screening photoredox reactions in continuous flow. Here, we describe the development of a droplet microfluidic photoreactor setup that combines ESI-MS analysis to enable high-throughput reaction discovery on picomole scale. This platform is anticipated to enable the direct optimization of flow reaction parameters (e.g. flow rate, residence time) and in turn, expedite the translation of discovery scale flow conditions to pilot scale continuous flow operations. Chapter 5 discusses a microwave heating strategy for streamlining the synthesis and diversification of Ir(III)+ polypyridyl complexes for applications in photoredox catalysis. This method is envisioned to help accelerate future developments in visible-light mediated chemistry. Additionally, the synthesis of novel nanohoop ligand-bearing Ir(III)+ polypyridyl complexes is described, along with the photophysical and electronic characterization of these complexes.PHDChemistryUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/155187/1/suna_1.pd

Prospective Exploration of Synthetically Feasible, Medicinally Relevant Chemical Space

We describe a novel approach to direct the exploration of chemical space in an effort to balance synthetic accessibility and medicinal relevancy prior to experimental work. Reaction transforms containing empirical reactivity and compatibility information are dynamically assembled into reaction sequences (vProtocols) utilizing commercially available starting material feedstock. These vProtocols are evolved and optimized by a genetic algorithm, which leverages fitness functions based on predicted properties of generated molecular products. We present the underlying concepts, methodology and initial results of this prospective approach