Similarity based functionalization for enumeration of synthetically plausible chemical libraries surrounding a target.

Functionalization of lead compounds to create analogs is a challenging step in discovering new molecules with desired properties and it is conducted throughout the chemical industry, including pharmaceuticals and agrochemicals. The process can be time-consuming and expensive, requiring expert intuition and experience. To help address synthesis planning challenges in late-stage functionalization, we have developed a molecular similarity approach that proposes single-step functionalization reactions based on analogy to precedent reactions. The developed approach mimics reaction strategies and suggests co-reactants defined implicitly by a corpus of known reactions. Using ca. 348 k reactions from the patent literature as a knowledge base, the recorded products or close analogs are among the top 20 proposed products in 74% of ∼44 k test reactions. The combinatorial growth inherent in recursive applications of the tool allows the enumeration of chemical libraries surrounding a target compound of interest. Moreover, each step of the resulting library synthesis leverages common chemical transformations reported in the literature accessible to most chemists.

Computer-assisted multistep chemoenzymatic retrosynthesis using a chemical synthesis planner.

Chemoenzymatic synthesis methods use organic and enzyme chemistry to synthesize a desired small molecule. Complementing organic synthesis with enzyme-catalyzed selective transformations under mild conditions enables more sustainable and synthetically efficient chemical manufacturing. Here, we present a multistep retrosynthesis search algorithm to facilitate chemoenzymatic synthesis of pharmaceutical compounds, specialty chemicals, commodity chemicals, and monomers. First, we employ the synthesis planner ASKCOS to plan multistep syntheses starting from commercially available materials. Then, we identify transformations that can be catalyzed by enzymes using a small database of biocatalytic reaction rules previously curated for RetroBioCat, a computer-aided synthesis planning tool for biocatalytic cascades. Enzymatic suggestions captured by the approach include ones capable of reducing the number of synthetic steps. We successfully plan chemoenzymatic routes for active pharmaceutical ingredients or their intermediates (e.g., Sitagliptin, Rivastigmine, and Ephedrine), commodity chemicals (e.g., acrylamide and glycolic acid), and specialty chemicals (e.g., S-Metalochlor and Vanillin), in a retrospective fashion. In addition to recovering published routes, the algorithm proposes many sensible alternative pathways. Our approach provides a chemoenzymatic synthesis planning strategy by identifying synthetic transformations that could be candidates for enzyme catalysis.

Similarity based enzymatic retrosynthesis.

Enzymes synthesize complex natural products effortlessly by catalyzing chemo-, regio-, and enantio-selective transformations. Further, biocatalytic processes are increasingly replacing conventional organic synthesis steps because they use mild solvents, avoid the use of metals, and reduce overall non-biodegradable waste. Here, we present a single-step retrosynthesis search algorithm to facilitate enzymatic synthesis of natural product analogs. First, we develop a tool, RDEnzyme, capable of extracting and applying stereochemically consistent enzymatic reaction templates, i.e., subgraph patterns that describe the changes in connectivity between a product molecule and its corresponding reactant(s). Using RDEnzyme, we demonstrate that molecular similarity is an effective metric to propose retrosynthetic disconnections based on analogy to precedent enzymatic reactions in UniProt/RHEA. Using ∼5500 reactions from RHEA as a knowledge base, the recorded reactants to the product are among the top 10 proposed suggestions in 71% of ∼700 test reactions. Second, we trained a statistical model capable of discriminating between reaction pairs belonging to homologous enzymes and evolutionarily distant enzymes using ∼30 000 reaction pairs from SwissProt as a knowledge base. This model is capable of understanding patterns in enzyme promiscuity to evaluate the likelihood of experimental evolution success. By recursively applying the similarity-based single-step retrosynthesis and evolution prediction workflow, we successfully plan the enzymatic synthesis routes for both active pharmaceutical ingredients (e.g. Islatravir, Molnupiravir) and commodity chemicals (e.g. 1,4-butanediol, branched-chain higher alcohols/biofuels), in a retrospective fashion. Through the development and demonstration of the single-step enzymatic retrosynthesis strategy using natural transformations, our approach provides a first step towards solving the challenging problem of incorporating both enzyme- and organic-chemistry based transformations into a computer aided synthesis planning workflow.

EHreact: Extended Hasse Diagrams for the Extraction and Scoring of Enzymatic Reaction Templates.

Data-driven computer-aided synthesis planning utilizing organic or biocatalyzed reactions from large databases has gained increasing interest in the last decade, sparking the development of numerous tools to extract, apply, and score general reaction templates. The generation of reaction rules for enzymatic reactions is especially challenging since substrate promiscuity varies between enzymes, causing the optimal levels of rule specificity and optimal number of included atoms to differ between enzymes. This complicates an automated extraction from databases and has promoted the creation of manually curated reaction rule sets. Here, we present EHreact, a purely data-driven open-source software tool, to extract and score reaction rules from sets of reactions known to be catalyzed by an enzyme at appropriate levels of specificity without expert knowledge. EHreact extracts and groups reaction rules into tree-like structures, Hasse diagrams, based on common substructures in the imaginary transition structures. Each diagram can be utilized to output a single or a set of reaction rules, as well as calculate the probability of a new substrate to be processed by the given enzyme by inferring information about the reactive site of the enzyme from the known reactions and their grouping in the template tree. EHreact heuristically predicts the activity of a given enzyme on a new substrate, outperforming current approaches in accuracy and functionality.

Tunable Enzymatic Synthesis of the Immunomodulator Lipid IVA To Enable Structure-Activity Analysis.

The Lipid A family of glycolipids, found in the outer membranes of all Gram-negative bacteria, exhibits considerable structural diversity in both lipid and glycan moieties. The lack of facile methods to prepare analogues of these natural products represents a major roadblock in understanding the relationship between their structure and immunomodulatory activities. Here we present a modular, cell-free multienzymatic platform to access these structure-activity relationships. By individually purifying 19 Escherichia coli proteins and reconstituting them in vitro in the presence of acetyl-CoA, UDP- N-acetylglucosamine, NADPH, and ATP, we have developed a system capable of synthesizing Lipid IVA, the first bioactive intermediate in the Lipid A pathway. Our reconstituted multienzyme system revealed considerable promiscuity for orthologs with distinct substrate specificity, as illustrated by swapping enzymes from distantly related cyanobacterial and Pseudomonas species. Analysis of the agonistic and antagonistic activities of the resulting products against the THP-1 human monocytic cell line revealed hitherto unrecognized trends, while opening the door to harnessing the potent biological activities of these complex glycolipid natural products.

Biosynthesis and structure-activity relationships of the lipid a family of glycolipids.

Lipopolysaccharide (LPS), a glycolipid found in the outer membrane of Gram-negative bacteria, is a potent elicitor of innate immune responses in mammals. A typical LPS molecule is composed of three different structural domains: a polysaccharide called the O-antigen, a core oligosaccharide, and Lipid A. Lipid A is the amphipathic glycolipid moiety of LPS. It stimulates the immune system by tightly binding to Toll-like receptor 4. More recently, Lipid A has also been shown to activate intracellular caspase-4 and caspase-5. An impressive diversity is observed in Lipid A structures from different Gram-negative bacteria, and it is well established that subtle changes in chemical structure can result in dramatically different immune activities. For example, Lipid A from Escherichia coli is highly toxic to humans, whereas a biosynthetic precursor called Lipid IVA blocks this toxic activity, and monophosphoryl Lipid A from Salmonella minnesota is a vaccine adjuvant. Thus, an understanding of structure-activity relationships in this glycolipid family could be used to design useful immunomodulatory agents. Here we review the biosynthesis, modification, and structure-activity relationships of Lipid A.