A sensitive and scalable fluorescence anisotropy single stranded RNA targeting approach for monitoring riboswitch conformational states.

The capacity of riboswitches to undergo conformational changes in response to binding their native ligands is closely tied to their functional roles and is an attractive target for antimicrobial drug design. Here, we established a probe-based fluorescence anisotropy assay to monitor riboswitch conformational switching with high sensitivity and throughput. Using the Bacillus subtillis yitJ S-Box (SAM-I), Fusobacterium nucleatum impX RFN element of (FMN) and class-I cyclic-di-GMP from Vibrio cholerae riboswitches as model systems, we developed short fluorescent DNA probes that specifically recognize either ligand-free or -bound riboswitch conformational states. We showed that increasing concentrations of native ligands cause measurable and reproducible changes in fluorescence anisotropy that correlate with riboswitch conformational changes observed by native gel analysis. Furthermore, we applied our assay to several ligand analogues and confirmed that it can discriminate between ligands that bind, triggering the native conformational change, from those that bind without causing the conformational change. This new platform opens the possibility of high-throughput screening compound libraries to identify potential new antibiotics that specifically target functional conformational changes in riboswitches.

Docking Ligands into Flexible and Solvated Macromolecules. 8. Forming New Bonds─Challenges and Opportunities.

Over the years, structure-based design programs and specifically docking small molecules to proteins have become prominent in drug discovery. However, many of these computational tools have been developed to primarily dock enzyme inhibitors (and ligands to other protein classes) relying heavily on hydrogen bonds and electrostatic and hydrophobic interactions. In reality, many drug targets either feature metal ions, can be targeted covalently, or are simply not even proteins (e.g., nucleic acids). Herein, we describe several new features that we have implemented into Fitted to broaden its applicability to a wide range of covalent enzyme inhibitors and to metalloenzymes, where metal coordination is essential for drug binding. This updated version of our docking program was tested for its ability to predict the correct binding mode of drug-sized molecules in a large variety of proteins. We also report new datasets that were essential to demonstrate areas of success and those where additional efforts are required. This resource could be used by other program developers to assess their own software.

COVID-19: Famotidine, Histamine, Mast Cells, and Mechanisms.

SARS-CoV-2 infection is required for COVID-19, but many signs and symptoms of COVID-19 differ from common acute viral diseases. SARS-CoV-2 infection is necessary but not sufficient for development of clinical COVID-19 disease. Currently, there are no approved pre- or post-exposure prophylactic COVID-19 medical countermeasures. Clinical data suggest that famotidine may mitigate COVID-19 disease, but both mechanism of action and rationale for dose selection remain obscure. We have investigated several plausible hypotheses for famotidine activity including antiviral and host-mediated mechanisms of action. We propose that the principal mechanism of action of famotidine for relieving COVID-19 symptoms involves on-target histamine receptor H2 activity, and that development of clinical COVID-19 involves dysfunctional mast cell activation and histamine release. Based on these findings and associated hypothesis, new COVID-19 multi-drug treatment strategies based on repurposing well-characterized drugs are being developed and clinically tested, and many of these drugs are available worldwide in inexpensive generic oral forms suitable for both outpatient and inpatient treatment of COVID-19 disease.

COVID-19: Famotidine, Histamine, Mast Cells, and Mechanisms.

SARS-CoV-2 infection is required for COVID-19, but many signs and symptoms of COVID-19 differ from common acute viral diseases. Currently, there are no pre- or post-exposure prophylactic COVID-19 medical countermeasures. Clinical data suggest that famotidine may mitigate COVID-19 disease, but both mechanism of action and rationale for dose selection remain obscure. We explore several plausible avenues of activity including antiviral and host-mediated actions. We propose that the principal famotidine mechanism of action for COVID-19 involves on-target histamine receptor H2 activity, and that development of clinical COVID-19 involves dysfunctional mast cell activation and histamine release.

The activities of drug inactive ingredients on biological targets.

Excipients, considered "inactive ingredients," are a major component of formulated drugs and play key roles in their pharmacokinetics. Despite their pervasiveness, whether they are active on any targets has not been systematically explored. We computed the likelihood that approved excipients would bind to molecular targets. Testing in vitro revealed 25 excipient activities, ranging from low-nanomolar to high-micromolar concentration. Another 109 activities were identified by testing against clinical safety targets. In cellular models, five excipients had fingerprints predictive of system-level toxicity. Exposures of seven excipients were investigated, and in certain populations, two of these may reach levels of in vitro target potency, including brain and gut exposure of thimerosal and its major metabolite, which had dopamine D3 receptor dissociation constant K d values of 320 and 210 nM, respectively. Although most excipients deserve their status as inert, many approved excipients may directly modulate physiologically relevant targets.

Bacterial metabolism rescues the inhibition of intestinal drug absorption by food and drug additives.

Food and drug products contain diverse and abundant small-molecule additives (excipients) with unclear impacts on human physiology, drug safety, and response. Here, we evaluate their potential impact on intestinal drug absorption. By screening 136 unique compounds for inhibition of the key intestinal transporter OATP2B1 we identified and validated 24 potent OATP2B1 inhibitors, characterized by higher molecular weight and hydrophobicity compared to poor or noninhibitors. OATP2B1 inhibitors were also enriched for dyes, including 8 azo (R-N=N-R') dyes. Pharmacokinetic studies in mice confirmed that FD&C Red No. 40, a common azo dye excipient and a potent inhibitor of OATP2B1, decreased the plasma level of the OATP2B1 substrate fexofenadine, suggesting that FD&C Red No. 40 has the potential to block drug absorption through OATP2B1 inhibition in vivo. However, the gut microbiomes of multiple unrelated healthy individuals as well as diverse human gut bacterial isolates were capable of inactivating the identified azo dye excipients, producing metabolites that no longer inhibit OATP2B1 transport. These results support a beneficial role for the microbiome in limiting the unintended effects of food and drug additives in the intestine and provide a framework for the data-driven selection of excipients. Furthermore, the ubiquity and genetic diversity of gut bacterial azoreductases coupled to experiments in conventionally raised and gnotobiotic mice suggest that variations in gut microbial community structure may be less important to consider relative to the high concentrations of azo dyes in food products, which have the potential to saturate gut bacterial enzymatic activity.

Interactions of Oral Molecular Excipients with Breast Cancer Resistance Protein, BCRP.

Mechanistic-understanding-based selection of excipients may improve formulation development strategies for generic drug products and potentially accelerate their approval. Our study aimed at investigating the effects of molecular excipients present in orally administered FDA-approved drug products on the intestinal efflux transporter, BCRP (ABCG2), which plays a critical role in drug absorption with potential implications on drug safety and efficacy. We determined the interactions of 136 oral molecular excipients with BCRP in isolated membrane vesicles and identified 26 excipients as BCRP inhibitors with IC50 values less than 5 µM using 3H-cholecystokinin octapeptide (3H-CCK8). These BCRP inhibitors belonged to three functional categories of excipients: dyes, surfactants, and flavoring agents. Compared with noninhibitors, BCRP inhibitors had significantly higher molecular weights and SLogP values. The inhibitory effects of excipients identified in membrane vesicles were also evaluated in BCRP-overexpressing HEK293 cells at similar concentrations. Only 1 of the 26 inhibitors of BCRP identified in vesicles inhibited BCRP-mediated 3H-oxypurinol uptake by more than 50%, consistent with the notion that BCRP inhibition depends on transmembrane or intracellular availability of the inhibitors. Collectively, the results of this study provide new information on excipient selection during the development of drug products with active pharmaceutical ingredients that are BCRP substrates.

The Recognition of Unrelated Ligands by Identical Proteins.

Unrelated ligands, often found in drug discovery campaigns, can bind to the same receptor, even with the same protein residues. To investigate how this might occur, and whether it might be typically possible to find unrelated ligands for the same drug target, we sought examples of topologically unrelated ligands that bound to the same protein in the same site. Seventy-six pairs of ligands, each bound to the same protein (152 complexes total), were considered, classified into three groups. In the first (31 pairs of complexes), unrelated ligands interacted largely with the same pocket residues through different functional groups. In the second group (39 pairs), the unrelated ligand in each pair engaged different residues, though still within the same pocket. The smallest group (6 pairs) contained ligands with different scaffolds but with shared functional groups interacting with the same residues. We found that there are multiple chemically unrelated but physically similar functional groups that can complement any given local protein pocket; when these functional group substitutions are combined within a single molecule, they lead to topologically unrelated ligands that can each well-complement a site. It may be that many active and orthosteric sites can recognize topologically unrelated ligands.

Customizable Generation of Synthetically Accessible, Local Chemical Subspaces.

Screening large libraries of chemicals has been an efficient strategy to discover bioactive compounds; however a portion of the potential for success is limited to the available libraries. Synergizing combinatorial and computational chemistries has emerged as a time-efficient strategy to explore the chemical space more widely. Ideally, streamlining the evaluation process for larger, feasible chemical libraries would become commonplace. Thus, combinatorial tools and, for example, docking methods would be integrated to identify novel bioactive entities. The idea is simple in nature, but much more complex in practice; combinatorial chemistry is more than the coupling of chemicals into products: synthetic feasibility includes chemoselectivity, stereoselectivity, protecting group chemistry, and chemical availability which must all be considered for combinatorial library design. In addition, intuitive interfaces and simple user manipulation is key for optimal use of such tools by organic chemists-crucial for the integration of such software in medicinal chemistry laboratories. We present herein Finders and React2D-integrated into the Virtual Chemist platform, a modular software suite. This approach enhances virtual combinatorial chemistry by identifying available chemicals compatible with a user-defined chemical transformation and by carrying out the reaction leading to libraries of realistic, synthetically accessible chemicals-all with a completely automated, black-box, and efficient design. We demonstrate its utility by generating ∼40 million synthetically accessible, stereochemically accurate compounds from a single library of 100 000 purchasable molecules and 56 well-characterized chemical reactions.

Medicinal Chemistry Projects Requiring Imaginative Structure-Based Drug Design Methods.

Computational methods for docking small molecules to proteins are prominent in drug discovery. There are hundreds, if not thousands, of documented examples-and several pertinent cases within our research program. Fifteen years ago, our first docking-guided drug design project yielded nanomolar metalloproteinase inhibitors and illustrated the potential of structure-based drug design. Subsequent applications of docking programs to the design of integrin antagonists, BACE-1 inhibitors, and aminoglycosides binding to bacterial RNA demonstrated that available docking programs needed significant improvement. At that time, docking programs primarily considered flexible ligands and rigid proteins. We demonstrated that accounting for protein flexibility, employing displaceable water molecules, and using ligand-based pharmacophores improved the docking accuracy of existing methods-enabling the design of bioactive molecules. The success prompted the development of our own program, Fitted, implementing all of these aspects. The primary motivation has always been to respond to the needs of drug design studies; the majority of the concepts behind the evolution of Fitted are rooted in medicinal chemistry projects and collaborations. Several examples follow: (1) Searching for HDAC inhibitors led us to develop methods considering drug-zinc coordination and its effect on the pKa of surrounding residues. (2) Targeting covalent prolyl oligopeptidase (POP) inhibitors prompted an update to Fitted to identify reactive groups and form bonds with a given residue (e.g., a catalytic residue) when the geometry allows it. Fitted-the first fully automated covalent docking program-was successfully applied to the discovery of four new classes of covalent POP inhibitors. As a result, efficient stereoselective syntheses of a few screening hits were prioritized rather than synthesizing large chemical libraries-yielding nanomolar inhibitors. (3) In order to study the metabolism of POP inhibitors by cytochrome P450 enzymes (CYPs)-for toxicology studies-the program Impacts was derived from Fitted and helped us to reveal a complex metabolism with unforeseen stereocenter isomerizations. These efforts, combined with those of other docking software developers, have strengthened our understanding of the complex drug-protein binding process while providing the medicinal chemistry community with useful tools that have led to drug discoveries. In this Account, we describe our contributions over the past 15 years-within their historical context-to the design of drug candidates, including BACE-1 inhibitors, POP covalent inhibitors, G-quadruplex binders, and aminoglycosides binding to nucleic acids. We also remark the necessary developments of docking programs, specifically Fitted, that enabled structure-based design to flourish and yielded multiple fruitful, rational medicinal chemistry campaigns.

Elucidating Hyperconjugation from Electronegativity to Predict Drug Conformational Energy in a High Throughput Manner.

Computational chemists use structure-based drug design and molecular dynamics of drug/protein complexes which require an accurate description of the conformational space of drugs. Organic chemists use qualitative chemical principles such as the effect of electronegativity on hyperconjugation, the impact of steric clashes on stereochemical outcome of reactions, and the consequence of resonance on the shape of molecules to rationalize experimental observations. While computational chemists speak about electron densities and molecular orbitals, organic chemists speak about partial charges and localized molecular orbitals. Attempts to reconcile these two parallel approaches such as programs for natural bond orbitals and intrinsic atomic orbitals computing Lewis structures-like orbitals and reaction mechanism have appeared. In the past, we have shown that encoding and quantifying chemistry knowledge and qualitative principles can lead to predictive methods. In the same vein, we thought to understand the conformational behaviors of molecules and to encode this knowledge back into a molecular mechanics tool computing conformational potential energy and to develop an alternative to atom types and training of force fields on large sets of molecules. Herein, we describe a conceptually new approach to model torsion energies based on fundamental chemistry principles. To demonstrate our approach, torsional energy parameters were derived on-the-fly from atomic properties. When the torsional energy terms implemented in GAFF, Parm@Frosst, and MMFF94 were substituted by our method, the accuracy of these force fields to reproduce MP2-derived torsional energy profiles and their transferability to a variety of functional groups and drug fragments were overall improved. In addition, our method did not rely on atom types and consequently did not suffer from poor automated atom type assignments.

Single-Point Mutation with a Rotamer Library Toolkit: Toward Protein Engineering.

Protein engineers have long been hard at work to harness biocatalysts as a natural source of regio-, stereo-, and chemoselectivity in order to carry out chemistry (reactions and/or substrates) not previously achieved with these enzymes. The extreme labor demands and exponential number of mutation combinations have induced computational advances in this domain. The first step in our virtual approach is to predict the correct conformations upon mutation of residues (i.e., rebuilding side chains). For this purpose, we opted for a combination of molecular mechanics and statistical data. In this work, we have developed automated computational tools to extract protein structural information and created conformational libraries for each amino acid dependent on a variable number of parameters (e.g., resolution, flexibility, secondary structure). We have also developed the necessary tool to apply the mutation and optimize the conformation accordingly. For side-chain conformation prediction, we obtained overall average root-mean-square deviations (RMSDs) of 0.91 and 1.01 Å for the 18 flexible natural amino acids within two distinct sets of over 3000 and 1500 side-chain residues, respectively. The commonly used dihedral angle differences were also evaluated and performed worse than the state of the art. These two metrics are also compared. Furthermore, we generated a family-specific library for kinases that produced an average 2% lower RMSD upon side-chain reconstruction and a residue-specific library that yielded a 17% improvement. Ultimately, since our protein engineering outlook involves using our docking software, Fitted/Impacts, we applied our mutation protocol to a benchmarked data set for self- and cross-docking. Our side-chain reconstruction does not hinder our docking software, demonstrating differences in pose prediction accuracy of approximately 2% (RMSD cutoff metric) for a set of over 200 protein/ligand structures. Similarly, when docking to a set of over 100 kinases, side-chain reconstruction (using both general and biased conformation libraries) had minimal detriment to the docking accuracy.

Design, synthesis and evaluation of antiestrogen and histone deacetylase inhibitor molecular hybrids.

The combination of antiestrogens and histone deacetylase inhibitors (HDACi) has been found to be antiproliferative in breast cancer models. We designed and synthesized hybrid structures which combined structural features of the pure antiestrogen ICI-164,384 and HDACi's SAHA and entinostat in a single bifunctional molecule. The hybrids retained antiestrogenic and HDACi activity and, in the case of benzamide hybrids, were selective for Class I HDAC3 over Class II HDAC6. The hybrids possessed low micromolar to high nanomolar activity against both ER+ MCF-7 and ER- MDA-MB-231 breast cancer cell models.

Understanding P450-mediated Bio-transformations into Epoxide and Phenolic Metabolites.

Adverse drug reactions are commonly the result of cytochrome P450 enzymes (CYPs) converting the drugs into reactive metabolites. Thus, information about the CYP bioactivation of drugs would not only provide insight into metabolic stability, but also into the potential toxicity. For example, oxidation of phenyl rings may lead to either toxic epoxides or safer phenols. Herein, we demonstrate that the potential to form reactive metabolites is encoded primarily in the properties of the molecule to be oxidized. While the enzyme positions the molecule inside the binding pocket (selects the site of metabolism), the subsequent reaction is only dependent on the substrate itself. To test this hypothesis, we used this observation as a predictor of drug inherent toxicity. This approach was used to successfully identify the formation of reactive metabolites in over 100 drug molecules. These results provide a new perspective on the impact of functional groups on aromatic oxidation of drugs and their effects on toxicity.

Metabolic Instability of Cyanothiazolidine-Based Prolyl Oligopeptidase Inhibitors: a Structural Assignment Challenge and Potential Medicinal Chemistry Implications.

As part of the development of cyanothiazolidine-based prolyl oligopeptidase inhibitors, initial metabolism studies suggested multiple sites of oxidation by P450 enzymes. Surprisingly, in-depth investigations revealed that epimerization at multiple stereogenic centers was responsible for the conversion of the single primary metabolite into a panel of secondary metabolites. The rapid isomerization of all seven detected molecules precluded the use of NMR spectroscopy or X-ray crystallography for complete structural determination, presenting an interesting structure elucidation challenge. Through a combination of LC-MS analysis, synthetic work, deuterium exchange studies, and computational predictions, we were able to characterize all metabolites and to elucidate their dynamic behavior in solution. In the context of drug development, this study reveals that cyanothiazolidine moieties are problematic due to their rapid P450-mediated oxidation and the unpredictable stability of the corresponding metabolites.

Docking ligands into flexible and solvated macromolecules. 6. Development and application to the docking of HDACs and other zinc metalloenzymes inhibitors.

Metalloenzymes are ubiquitous proteins which feature one or more metal ions either directly involved in the enzymatic activity and/or structural properties (i.e., zinc fingers). Several members of this class take advantage of the Lewis acidic properties of zinc ions to carry out their various catalytic transformations including isomerization or amide cleavage. These enzymes have been validated as drug targets for a number of diseases including cancer; however, despite their pharmaceutical relevance and the availability of crystal structures, structure-based drug design methods have been poorly and indirectly parametrized for these classes of enzymes. More specifically, the metal coordination component and proton transfers of the process of drugs binding to metalloenzymes have been inadequately modeled by current docking programs, if at all. In addition, several known issues, such as coordination geometry, atomic charge variability, and a potential proton transfer from small molecules to a neighboring basic residue, have often been ignored. We report herein the development of specific functions and parameters to account for zinc-drug coordination focusing on the above-listed phenomena and their impact on docking to zinc metalloenzymes. These atom-type-dependent but atomic charge-independent functions implemented into Fitted 3.1 enable the simulation of drug binding to metalloenzymes, considering an acid-base reaction with a neighboring residue when necessary with good accuracy.

Stereo- and regioselective synthesis of polysubstituted chiral 1,4-oxazepanes.

The number of cyclic molecular scaffolds available to medicinal chemists remains limited, and simple structures such as oxazepanes are still made using multistep procedures, including a number of protection/deprotection steps and purifications. We report herein an expedient and efficient synthesis of chiral polysubstituted oxazepanes. The developed method relies on a regio- and stereoselective 7-endo cyclization through haloetherification. Mechanistic studies using a combination of computations and experiments confirmed the expected role of the asymmetry of the chiral bromonium intermediate on the haloetherification regioselectivity. Computations also suggested that the bromonium intermediate is formed with no transition state; hence, the stereoselectivity is controlled primarily by the conformation of the substrate. Applied to a set of 16 substrates, tetra- and pentasubstituted oxazepanes were prepared with good yields and moderate to excellent regio- and stereoselectivities.

Development of a computational tool to rival experts in the prediction of sites of metabolism of xenobiotics by p450s.

The metabolism of xenobiotics--and more specifically drugs--in the liver is a critical process controlling their half-life. Although there exist experimental methods, which measure the metabolic stability of xenobiotics and identify their metabolites, developing higher throughput predictive methods is an avenue of research. It is expected that predicting the chemical nature of the metabolites would be an asset for designing safer drugs and/or drugs with modulated half-lives. We have developed IMPACTS (In-silico Metabolism Prediction by Activated Cytochromes and Transition States), a computational tool combining docking to metabolic enzymes, transition state modeling, and rule-based substrate reactivity prediction to predict the site of metabolism (SoM) of xenobiotics. Its application to sets of CYP1A2, CYP2C9, CYP2D6, and CYP3A4 substrates and comparison to experts' predictions demonstrates its accuracy and significance. IMPACTS identified an experimentally observed SoM in the top 2 predicted sites for 77% of the substrates, while the accuracy of biotransformation experts' prediction was 65%. Application of IMPACTS to external sets and comparison of its accuracy to those of eleven other methods further validated the method implemented in IMPACTS.