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.

A naturally occurring G11S mutation in the 3C-like protease from the SARS-CoV-2 virus dramatically weakens the dimer interface

The 3C-like protease (3CLpro ) is crucial to the replication of SARS-CoV-2, the causative agent of COVID-19, and is the target of several successful drugs including Paxlovid and Xocova. Nevertheless, the emergence of viral resistance underlines the need for alternative drug strategies. 3CLpro only functions as a homodimer, making the protein-protein interface an attractive drug target. Dimerization is partly mediated by a conserved glycine at position 11. However, some naturally occurring SARS-CoV-2 sequences contain a serine at this position, potentially disrupting the dimer. We have used concentration-dependent activity assays and mass spectrometry to show that indeed the G11S mutation reduces the stability of the dimer by 600-fold. This helps to set a quantitative benchmark for the minimum potency required of any future protein-protein interaction inhibitors targeting 3CLpro and raises interesting questions regarding how coronaviruses bearing such weakly dimerizing 3CLpro enzymes are capable of replication.

14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon

Large-language models (LLMs) such as GPT-4 caught the interest of many scientists. Recent studies suggested that these models could be useful in chemistry and materials science. To explore these possibilities, we organized a hackathon. This article chronicles the projects built as part of this hackathon. Participants employed LLMs for various applications, including predicting properties of molecules and materials, designing novel interfaces for tools, extracting knowledge from unstructured data, and developing new educational applications. The diverse topics and the fact that working prototypes could be generated in less than two days highlight that LLMs will profoundly impact the future of our fields. The rich collection of ideas and projects also indicates that the applications of LLMs are not limited to materials science and chemistry but offer potential benefits to a wide range of scientific disciplines.

Computational and biophysical methods for the discovery and optimization of covalent drugs

Drugs that act by covalently attaching to their targets have been used to treat human diseases for over a hundred years. However, the deliberate design of covalent drugs was discouraged due to concerns of toxicity and off-target effects. Recent successes in covalent drug discovery have sparked fresh interest in this field. New screening and testing methods aimed at covalent inhibitors can play pivotal roles in facilitating the discovery process. This feature article focuses on computational and biophysical advances originating from our labs over the past decade and how these approaches have contributed to the design of prolyl oligopeptidase (POP) and SARS-CoV-2 3CLpro covalent inhibitors.

Novel Aurora A and Protein Kinase C (α, β1, β2, and θ) Multitarget Inhibitors: Impact of Selenium Atoms on the Potency and Selectivity

Aurora kinases and protein kinase C (PKC) have been shown to be involved in different aspects of cancer progression. To date, no dual Aurora/PKC inhibitor with clinical efficacy and low toxicity is available. Here, we report the identification of compound 2e as a potent small molecule capable of selectively inhibiting Aurora A kinase and PKC isoforms α, β1, β2 and θ. Compound 2e demonstrated significant inhibition of the colony forming ability of metastatic breast cancer cells in vitro and metastasis development in vivo. In vitro kinase screening and molecular modeling studies revealed the critical role of the selenium-containing side chains within 2e, where selenium atoms were shown to significantly improve its selectivity and potency by forming additional interactions and modulating the protein dynamics. In comparison to other H-bonding heteroatoms such as sulfur, our studies suggested that these selenium atoms also confer more favorable PK properties.

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.

Mutations in Dynamic Structural Elements Alter the Kinetics and Fidelity of the Multifunctional Class II Lanthipeptide Synthetase, HalM2

Class II lanthipeptide synthetases (LanM enzymes) catalyze the multistep post-translational modification of genetically encoded precursor peptides into macrocyclic (often antimicrobial) lanthipeptides. The reaction sequence involves dehydration of serine/threonine residues, followed by intramolecular addition of cysteine thiols onto the nascent dehydration sites to construct thioether bridges. LanMs utilize two separate active sites in an iterative yet highly coordinated manner to maintain a remarkable level of regio- and stereochemical control over the multistep maturation. The mechanisms underlying this biosynthetic fidelity remain enigmatic. We recently demonstrated that proper function of the haloduracin β synthetase (HalM2) requires dynamic structural elements scattered across the surface of the enzyme. Here, we perform kinetic simulations, structural analysis of reaction intermediates, hydrogen-deuterium exchange mass spectrometry studies, and molecular dynamics simulations to investigate the contributions of these dynamic HalM2 structural elements to biosynthetic efficiency and fidelity. Our studies demonstrate that a large, conserved loop (HalM2 residues P349-P405) plays essential roles in defining the precursor peptide binding site, facilitating efficient peptide dehydration, and guiding the order of thioether ring formation. Moreover, mutations near the interface of the HalM2 dehydratase and cyclase domains perturb cyclization fidelity and result in aberrant thioether topologies that cannot be corrected by the wild type enzyme, suggesting an element of kinetic control in the normal cyclization sequence. Overall, this work provides the most comprehensive correlation of the structural and functional properties of a LanM enzyme reported to date and should inform mechanistic studies of the biosynthesis of other ribosomally synthesized and post-translationally modified peptide natural products.

Targeting MYC: From understanding its biology to drug discovery

The MYC oncogene is considered to be a high priority target for clinical intervention in cancer patients due to its aberrant activation in more than 50% of human cancers. Direct small molecule inhibition of MYC has traditionally been hampered by its intrinsically disordered nature and lack of both binding site and enzymatic activity. In recent years, however, a number of strategies for indirectly targeting MYC have emerged, guided by the advent of protein structural information and the growing set of computational tools that can be used to accelerate the hit to lead process in medicinal chemistry. In this review, we provide an overview of small molecules developed for clinical applications of these strategies, which include stabilization of the MYC guanine quadruplex, inhibition of BET factor BRD4, and disruption of the MYC:MAX heterodimer. The recent identification of novel targets for indirect MYC inhibition at the protein level is also discussed.

Enzyme Kinetics by Isothermal Titration Calorimetry: Allostery, Inhibition, and Dynamics

Isothermal titration calorimetry (ITC) involves accurately measuring the heat that is released or absorbed in real time when one solution is titrated into another. This technique is usually used to measure the thermodynamics of binding reactions. However, there is mounting interest in using it to measure reaction kinetics, particularly enzymatic catalysis. This application of ITC has been steadily growing for the past two decades, and the method is proving to be sensitive, generally applicable, and capable of providing information on enzyme activity that is difficult to obtain using traditional biochemical assays. This review aims to give a broad overview of the use of ITC to measure enzyme kinetics. It describes several different classes of ITC experiment, their strengths and weaknesses, and recent methodological advancements. A summary of applications in the literature is given and several examples where ITC has been used to investigate challenging aspects of enzyme behavior are presented in more detail. These include examples of allostery, where small-molecule binding outside the active site modulates activity. We describe the use of ITC to measure the strength, mode (i.e., competitive, uncompetitive, or mixed), and association and dissociation kinetics of enzyme inhibitors. Further, we provide examples of ITC applied to complex, heterogeneous mixtures, such as insoluble substrates and live cells. These studies exemplify the wide range of problems where ITC can provide answers, and illustrate the versatility of the technique and potential for future development and applications.

Augmented base pairing networks encode RNA-small molecule binding preferences

RNA-small molecule binding is a key regulatory mechanism which can stabilize 3D structures and activate molecular functions. The discovery of RNA-targeting compounds is thus a current topic of interest for novel therapies. Our work is a first attempt at bringing the scalability and generalization abilities of machine learning methods to the problem of RNA drug discovery, as well as a step towards understanding the interactions which drive binding specificity. Our tool, RNAmigos, builds and encodes a network representation of RNA structures to predict likely ligands for novel binding sites. We subject ligand predictions to virtual screening and show that we are able to place the true ligand in the 71st-73rd percentile in two decoy libraries, showing a significant improvement over several baselines, and a state of the art method. Furthermore, we observe that augmenting structural networks with non-canonical base pairing data is the only representation able to uncover a significant signal, suggesting that such interactions are a necessary source of binding specificity. We also find that pre-training with an auxiliary graph representation learning task significantly boosts performance of ligand prediction. This finding can serve as a general principle for RNA structure-function prediction when data is scarce. RNAmigos shows that RNA binding data contains structural patterns with potential for drug discovery, and provides methodological insights for possible applications to other structure-function learning tasks. The source code, data and a Web server are freely available at http://rnamigos.cs.mcgill.ca.

Atom Type Independent Modeling of the Conformational Energy of Benzylic, Allylic, and Other Bonds Adjacent to Conjugated Systems

Applications of computational methods to predict binding affinities for protein/drug complexes are routinely used in structure-based drug discovery. Applications of these methods often rely on empirical force fields (FFs) and their associated parameter sets and atom types. However, it is widely accepted that FFs cannot accurately cover the entire chemical space of drug-like molecules, due to the restrictive cost of parametrization and the poor transferability of existing parameters. To address these limitations, initiatives have been carried out to develop more transferable methods, in order to allow for more rigorous descriptions of any drug-like molecule. We have previously reported H-TEQ, a method which does not rely on atom types and incorporates well established chemical principles to assign parameters to organic molecules. The previous implementation of H-TEQ (a torsional barrier prediction method) only covered saturated and lone pair containing molecules; here, we report our efforts to incorporate conjugated systems into our model. The next step was the evaluation of the introduction of unsaturations. The developed model (H-TEQ3.0) has been validated on a wide variety of molecules containing heteroaromatic groups, alkyls, and fused ring systems. Our method performs on par with one of the most commonly used FFs (GAFF2), without relying on atom types or any prior parametrization.

Torsional Energy Barriers of Biaryls Could Be Predicted by Electron Richness/Deficiency of Aromatic Rings; Advancement of Molecular Mechanics toward Atom-Type Independence

Biaryl molecules are ubiquitous pharmacophores found in natural products and pharmaceuticals. In spite of this, existing molecular mechanics force fields are unable to accurately reproduce their torsional energy profiles, except for a few well-parametrized cases. This effectively limits the ability of structure-based drug design methods to correctly identify hits involving biaryls with confidence (e.g., during virtual screening, employing docking and/or molecular dynamics simulations). Continuing in our endeavor to quantify organic chemistry principles, we showed that the torsional energy profile of biaryl compounds could be computed on-the-fly based on the electron richness/deficiency of the aromatic rings. This method, called H-TEQ 4.0, was developed using a set of 131 biaryls. It was subsequently validated on a separate set of 100 diverse biaryls, including multisubstituted, bicyclic and tricyclic druglike molecules, and produced an average root-mean-square error (RMSE) of 0.95 kcal·mol^-1. For comparison, GAFF2 produced an RMSE of 3.88 kcal·mol^-1, owing to problems associated with the transferability of torsion parameters. The success of H-TEQ 4.0 provided further evidence that force fields could transition to become atom-type independent, providing that the correct chemical principles are used. Overall, this method solved the problem of transferability of biaryl torsion parameters, while simultaneously improving the overall accuracy of the force field.

Automated, customizable and efficient identification of 3D base pair modules with BayesPairing

RNA structures possess multiple levels of structural organization. A secondary structure, made of Watson–Crick helices connected by loops, forms a scaffold for the tertiary structure. The 3D structures adopted by these loops are therefore critical determinants shaping the global 3D architecture. Earlier studies showed that these local 3D structures can be described as conserved sets of ordered non-Watson–Crick base pairs called RNA structural modules. Unfortunately, the computational efficiency and scope of the current 3D module identification methods are too limited yet to benefit from all the knowledge accumulated in the module databases. We present BayesPairing, an automated, efficient and customizable tool for (i) building Bayesian networks representing RNA 3D modules and (ii) rapid identification of 3D modules in sequences. BayesPairing uses a flexible definition of RNA 3D modules that allows us to consider complex architectures such as multi-branched loops and features multiple algorithmic improvements. We benchmarked our methods using cross-validation techniques on 3409 RNA chains and show that BayesPairing achieves up to ∼70% identification accuracy on module positions and base pair interactions. BayesPairing can handle a broader range of motifs (versatility) and offers considerable running time improvements (efficiency), opening the door to a broad range of large-scale applications.

Predicting Positions of Bridging Water Molecules in Nucleic Acid-Ligand Complexes

Over the past two decades, interests in DNA and RNA as drug targets have been growing rapidly. Following the trends observed with protein drug targets, computational approaches for drug design have been developed for this new class of molecules. Our efforts toward the development of a universal docking program, Fitted, led us to focus on nucleic acids. Throughout the development of this docking program, efforts were directed toward displaceable water molecules which must be accurately located for optimal docking-based drug discovery. However, although there is a plethora of methods to place water molecules in and around protein structures, there is, to the best of our knowledge, no such fully automated method for nucleic acids, which are significantly more polar and solvated than proteins. We report herein a new method, Splash'Em (Solvation Potential Laid around Statistical Hydration on Entire Macromolecules) developed to place water molecules within the binding cavity of nucleic acids. This fast method was shown to have high agreement with water positions in crystal structures and will therefore provide essential information to medicinal chemists.

Adjusting the Structure of 2'-Modified Nucleosides and Oligonucleotides via C4'-α-F or C4'-α-OMe Substitution: Synthesis and Conformational Analysis

We report the first syntheses of three nucleoside analogues, namely, 2',4'-diOMe-rU, 2'-OMe,4'-F-rU, and 2'-F,4'-OMe-araU, via stereoselective introduction of fluorine or methoxy functionalities at the C4'-α-position of a 4',5'-olefinic intermediate. Conformational analyses of these nucleosides and comparison to other previously reported 2',4'-disubstituted nucleoside analogues make it possible to evaluate the effect of fluorine and methoxy substitution on the sugar pucker, as assessed by NMR, X-ray diffraction, and computational methods. We found that C4'-α-F/OMe substituents reinforce the C3'-endo ( north) conformation of 2'-OMe-rU. Furthermore, the predominant C2'-endo ( south/ east) conformation of 2'-F-araU switches to C3'-endo upon introduction of these substituents at C4'. The nucleoside analogues were incorporated into DNA and RNA oligonucleotides via standard phosphoramidite chemistry, and their effects on the thermal stability of homo- and heteroduplexes were assessed via UV thermal melting experiments. We found that 4'-substituents can modulate the binding affinity of the parent 2'-modified oligomers, inducing a mildly destabilizing or stabilizing effect depending on the duplex type. This study expands the spectrum of oligonucleotide modifications available for rational design of oligonucleotide therapeutics.

Revised Mechanism for a Ruthenium-Catalyzed Coupling of Aldehyde and Terminal Alkyne

Ruthenium catalysts have been found to be of great use for many kinds of reactions. Understanding the details of the catalytic cycle allows to not only rationalize experimental results but also to improve upon reactions. Herein, we present a detailed computational study of a ruthenium-catalyzed coupling between a terminal alkyne and an aldehyde. The reaction under examination facilitates novel access to olefins with the concurrent loss of a single carbon as carbon monoxide. The reaction was first developed in 2009, but the tentative mechanism initially proposed was proven to be contradictory to some experimental data obtained since then. Using a combination of computational investigations and isotope-labeling experiments, several potential mechanisms have been studied. In contrast to the [2+2] cycloaddition mechanism suggested for similar catalysts, we propose a new consensus pathway that proceeds through the formation of a ruthenium-vinylidene complex that undergoes an aldol-type reaction with the aldehyde to yield the product olefins. Computational insights into the influence of different reagents used to optimize reaction conditions and the intricacies of decarbonylation of a Ru-CO complex affecting catalyst turnover are highlighted.

Rapid measurement of inhibitor binding kinetics by isothermal titration calorimetry

Although drug development typically focuses on binding thermodynamics, recent studies suggest that kinetic properties can strongly impact a drug candidate’s efficacy. Robust techniques for measuring inhibitor association and dissociation rates are therefore essential. To address this need, we have developed a pair of complementary isothermal titration calorimetry (ITC) techniques for measuring the kinetics of enzyme inhibition. The advantages of ITC over standard techniques include speed, generality, and versatility; ITC also measures the rate of catalysis directly, making it ideal for quantifying rapid, inhibitor-dependent changes in enzyme activity. We used our methods to study the reversible covalent and non-covalent inhibitors of prolyl oligopeptidase (POP). We extracted kinetics spanning three orders of magnitude, including those too rapid for standard methods, and measured sub-nM binding affinities below the typical ITC limit. These results shed light on the inhibition of POP and demonstrate the general utility of ITC-based enzyme inhibition kinetic measurements.

There is growing evidence that the kinetics of interactions between inhibitors and their targets can strongly impact therapeutic efficacy. Here the authors describe an isothermal titration calorimetry-based method that can rapidly quantify inhibition kinetics and measure sub-nM binding affinities.

Atom Types Independent Molecular Mechanics Method for Predicting the Conformational Energy of Small Molecules

We previously implemented a well-known qualitative chemical principle into an accurate quantitative model computing relative potential energies of conformers. According to this principle, hyperconjugation strength correlates with electronegativity of donors and acceptors. While this earlier version of our model applies to σ bonds, lone pairs, disregarded in this earlier version, also have a major impact on the conformational preferences of molecules. Among the well-established principles used by organic chemists to rationalize some organic chemical behaviors are the anomeric effect, the alpha effect, basicity, and nucleophilicity. These effects are directly related to the presence of lone pairs. We report herein our effort to incorporate lone pairs into our model to extend its applicability domain to any saturated small molecules. The developed model H-TEQ 2 has been validated on a wide variety of molecules from polyaromatic molecules to carbohydrates and molecules with high heteroatoms/carbon ratios. Interestingly, this method, in contrast to common force field-based methods, does not rely on atom types and is virtually applicable to any organic molecules.

4'-C-Methoxy-2'-deoxy-2'-fluoro Modified Ribonucleotides Improve Metabolic Stability and Elicit Efficient RNAi-Mediated Gene Silencing

We designed novel 4'-modified 2'-deoxy-2'-fluorouridine (2'-F U) analogues with the aim to improve nuclease resistance and potency of therapeutic siRNAs by introducing 4'-C-methoxy (4'-OMe) as the alpha (C4'α) or beta (C4'β) epimers. The C4'α epimer was synthesized by a stereoselective route in six steps; however, both α and β epimers could be obtained by a nonstereoselective approach starting from 2'-F U. ¹H NMR analysis and computational investigation of the α-epimer revealed that the 4'-OMe imparts a conformational bias toward the North-East sugar pucker, due to intramolecular hydrogen bonding and hyperconjugation effects. The α-epimer generally conceded similar thermal stability as unmodified nucleotides, whereas the β-epimer led to significant destabilization. Both 4'-OMe epimers conferred increased nuclease resistance, which can be explained by the close proximity between 4'-OMe substituent and the vicinal 5'- and 3'-phosphate group, as seen in the X-ray crystal structure of modified RNA. siRNAs containing several C4'α-epimer monomers in the sense or antisense strands triggered RNAi-mediated gene silencing with efficiencies comparable to that of 2'-F U.

Measuring Rapid Time-Scale Reaction Kinetics Using Isothermal Titration Calorimetry

Isothermal titration calorimetry (ITC) is a powerful tool for acquiring both thermodynamic and kinetic data for biological interactions including molecular recognition and enzymatic catalysis. ITC-based kinetics measurements typically focus on reactions taking place over long time scales (tens of minutes or hours) in order to avoid complications due to the finite length of time needed detect heat flow in the calorimeter cell. While progress has been made toward analyzing more rapid reaction kinetics by ITC, the capabilities and limitations of this approach have not been thoroughly tested to date. Here, we report that the time resolution of commercial instruments is on the order of 0.2 s or less. We successfully performed rapid ITC kinetics assays with durations of just tens of seconds using the enzyme trypsin. This is substantially shorter than previous ITC enzyme measurements. However, we noticed that for short reaction durations, standard assumptions regarding the ITC instrument response led to significant deviations between calculated and measured ITC peak shapes. To address this issue, we developed an ITC empirical response model (ITC-ERM) that quantitatively reproduces ITC peak shapes for all reaction durations. Applying the ITC-ERM approach to another enzyme (prolyl oligopeptidase), we unexpectedly discovered non-Michaelis-Menten kinetics in short time-scale measurements that are absent in more typical long time-scale experiments and are obscured in short time-scale experiments when standard assumptions regarding the instrument response are made. This highlights the potential of ITC measurements of rapid time scale kinetics in conjunction with the ITC-ERM approach to shed new light on biological dynamics.

Covalent inhibitors design and discovery

In the history of therapeutics, covalent drugs occupy a very distinct category. While representing a significant fraction of the drugs on the market, very few have been deliberately designed to interact covalently with their biological target. In this review, the prevalence of covalent drugs will first be briefly covered, followed by an introduction to their mechanisms of action and more detailed discussions of their discovery and the development of safe and efficient covalent enzyme inhibitors. All stages of a drug discovery program will be covered, from target considerations to lead optimization, strategies to tune reactivity and computational methods. The goal of this article is to provide an overview of the field and to outline good practices that are needed for the proper assessment and development of covalent inhibitors as well as a good understanding of the potential and limitations of current computational methods for the design of covalent drugs.

Fluoride-Mediated Desulfonylative Intramolecular Cyclization to Fused and Bridged Bicyclic Compounds: A Complex Mechanism

We previously reported the synthesis of polysubstituted chiral oxazepanes in three steps from commercially available starting materials. The unexpected reaction of one of these 1,4-oxazepanes in the presence of TBAF provided a 4-oxa-1-azabicyclo[4.1.0]heptane core. This unusual process significantly increased the complexity of the molecular scaffold by introducing a bicyclic core. Surprisingly, the generated bicyclic structure featuring three stereocenters was a mixture of enantiomers with no other diastereomers observed. These striking experimental observations deserved further investigations. A combination of experimental and computational investigations unveiled a complex diastereoselective mechanism. Mechanistic rationale is presented for this observed rearrangement.

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.

Phosphorylation of a constrained azacyclic FTY720 analog enhances anti-leukemic activity without inducing S1P receptor activation

The frequency of poor outcomes in relapsed leukemia patients underscores the need for novel therapeutic approaches. The FDA-approved immunosuppressant FTY720 limits leukemia progression by activating protein phosphatase 2A and restricting nutrient access. Unfortunately, FTY720 cannot be re-purposed for use in cancer patients due to on-target toxicity associated with S1P receptor activation at the elevated, anti-neoplastic dose. Here we show that the constrained azacyclic FTY720 analog SH-RF-177 lacks S1P receptor activity but maintains anti-leukemic activity in vitro and in vivo. SH-RF-177 was not only more potent than FTY720, but killed via a distinct mechanism. Phosphorylation is dispensable for FTY720’s anti-leukemic actions. However, chemical biology and genetic approaches demonstrated that the sphingosine kinase 2- (SPHK2) mediated phosphorylation of SH-RF-177 led to engagement of a pro-apoptotic target and increased potency. The cytotoxicity of membrane-permeant FTY720 phosphonate esters suggests that the enhanced potency of SH-RF-177 stems from its more efficient phosphorylation. The tight inverse correlation between SH-RF-177 IC₅₀ and SPHK2 mRNA expression suggests a useful biomarker for SH-RF-177 sensitivity. In summary, these studies indicate that FTY720 analogs that are efficiently phosphorylated but fail to activate S1P receptors may be superior anti-leukemic agents compared to compounds that avoid cardiotoxicity by eliminating phosphorylation.

Azo⋯phenyl stacking: a persistent self-assembly motif guides the assembly of fluorinated cis-azobenzenes into photo-mechanical needle crystals

We describe a novel, persistent motif of molecular assembly in photo-mechanical crystals and cocrystals of fluorinated cis-azobenzenes.

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.

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.

Discovery of novel small-molecule antagonists for GluK2

KA receptors have shown to be potential therapeutic targets in CNS diseases such as schizophrenia, depression, neuropathic pain and epilepsy. Through the use of our docking tool Fitted, we investigated the relationship between ligand activity towards GluK2 and the conformational state induced at the receptor level. By focusing our rational design on the interaction between the ligand and a tyrosine residue in the binding site, we synthesized a series of molecules based on a glutamate scaffold, and carried out electrophysiological recordings. The observed ability of some of these molecules to inhibit receptor activation shows the potential of our design for the development of effective antagonists with a molecular size comparable to that of the endogenous neurotransmitter L-glutamate.

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.

Methods for docking small molecules to macromolecules: a user's perspective. 2. Applications

A large number of research articles describe novel methodologies of docking and/or scoring methods. An even larger number of publications report the successful use of these methods in the identification of novel hit molecules. What is less documented is the application of docking methods in other areas. We review herein the application of docking methods to not only hit identification but also to de novo design, fragment-based drug discovery, lead optimization, metabolism prediction, off-target binding, selectivity, protein structure prediction and drug-drug interaction.