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.

Structural Polymorphism of Guanine Quadruplex-Containing Regions in Human Promoters.

Intramolecular guanine quadruplexes (G4s) are non-canonical nucleic acid structures formed by four guanine (G)-rich tracts that assemble into a core of stacked planar tetrads. G4-forming DNA sequences are enriched in gene promoters and are implicated in the control of gene expression. Most G4-forming DNA contains more G residues than can simultaneously be incorporated into the core resulting in a variety of different possible G4 structures. Although this kind of structural polymorphism is well recognized in the literature, there remain unanswered questions regarding possible connections between G4 polymorphism and biological function. Here we report a detailed bioinformatic survey of G4 polymorphism in human gene promoter regions. Our analysis is based on identifying G4-containing regions (G4CRs), which we define as stretches of DNA in which every residue can form part of a G4. We found that G4CRs with higher degrees of polymorphism are more tightly clustered near transcription sites and tend to contain G4s with shorter loops and bulges. Furthermore, we found that G4CRs with well-characterized biological functions tended to be longer and more polymorphic than genome-wide averages. These results represent new evidence linking G4 polymorphism to biological function and provide new criteria for identifying biologically relevant G4-forming regions from genomic data.

Modulating the selectivity of inhibitors for prolyl oligopeptidase inhibitors and fibroblast activation protein-α for different indications.

We have previously described several different chemical series of bicyclic prolyl oligopeptidase (POP) inhibitors as probes for neurodegenerative diseases that demonstrated nanomolar activity in vitro and submicromolar activity in cellulo. The more recent implication of POP in cancer, together with homologous fibroblast activation protein α (FAP), implicated in tumor growth, led us to consider developing POP/FAP dual inhibitors as a promising strategy for the development of cancer therapeutics. At this stage, we thought to evaluate the requirements for selectivity of inhibitors for POP over FAP and to evaluate molecular platforms that would enable the development of selective POP and dual POP/FAP inhibitors. We report herein docking-guided design of a new bicyclic scaffold and synthesis of both covalent and non-covalent bicyclic inhibitors. Biological evaluation of first-of-their-kind [4.3.0] bicyclic compounds confirmed that reactive groups, or covalent warheads, are required for inhibitor activity. This work ultimately led to one scaffold yielding new POP-selective inhibitors and a dual inhibitor equipotent to the only drug targeting FAP and POP that ever reached clinical trials.

A cryptic third active site in cyanophycin synthetase creates primers for polymerization.

Cyanophycin is a nitrogen reserve biopolymer in many bacteria that has promising industrial applications. Made by cyanophycin synthetase 1 (CphA1), it has a poly-L-Asp backbone with L-Arg residues attached to each aspartate sidechain. CphA1s are thought to typically require existing segments of cyanophycin to act as primers for cyanophycin polymerization. In this study, we show that most CphA1s will not require exogenous primers and discover the surprising cause of primer independence: CphA1 can make minute quantities of cyanophycin without primer, and an unexpected, cryptic metallopeptidase-like active site in the N-terminal domain of many CphA1s digests these into primers, solving the problem of primer availability. We present co-complex cryo-EM structures, make mutations that transition CphA1s between primer dependence and independence, and demonstrate that primer dependence can be a limiting factor for cyanophycin production in heterologous hosts. In CphA1, domains with opposite catalytic activities combine into a remarkable, self-sufficient, biosynthetic nanomachine.

Novel Aurora A and Protein Kinase C (α, ß1, ß2, 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, ß1, ß2 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.

Design, synthesis and in vitro evaluation of novel SARS-CoV-2 3CLpro covalent inhibitors.

Severe diseases such as the ongoing COVID-19 pandemic, as well as the previous SARS and MERS outbreaks, are the result of coronavirus infections and have demonstrated the urgent need for antiviral drugs to combat these deadly viruses. Due to its essential role in viral replication and function, 3CLpro (main coronaviruses cysteine-protease) has been identified as a promising target for the development of antiviral drugs. Previously reported SARS-CoV 3CLpro non-covalent inhibitors were used as a starting point for the development of covalent inhibitors of SARS-CoV-2 3CLpro. We report herein our efforts in the design and synthesis of submicromolar covalent inhibitors when the enzymatic activity of the viral protease was used as a screening platform.

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 ß 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.

Use of Extended-Hückel Descriptors for Rapid and Accurate Predictions of Conjugated Torsional Energy Barriers.

Over the past few decades, virtual high-throughput screening (vHTS) and molecular dynamics simulations have become effective and widely used tools in the initial stages of drug discovery efforts. These methods allow a great number of druglike molecules to be screened quickly and inexpensively. Unfortunately, however, the accuracies of both these methods rely on the quality of the underlying molecular mechanics force fields (FFs), which are often poor. This major weakness originates from the reliance of FFs on a finite list of specific parameters, called atom types, which have low transferability between molecules. In particular, the torsional energy barriers of druglike molecules are notoriously difficult to predict. Continuing our endeavor to understand factors affecting the torsional energy barriers of small molecules and quantify them, we showed that descriptors calculated using the extended-Hückel method could be used to rapidly assign accurate torsion parameters for conjugated molecules. This method, called H-TEQ 4.5, was developed using a set of 684 conjugated molecules. It was subsequently validated on a test set of 200 diverse molecules and produced an average root-mean-square error (rmse) of 1.01 kcal·mol-1, with respect to the reference quantum mechanic torsional profiles. For comparison, GAFF2, MMFF94, and MAB produced average rmse's of 3.49, 1.50, and 1.77 kcal·mol-1, respectively. H-TEQ 4.5 is also computationally inexpensive, running just under 0.25 ms for a biphenyl molecule on a home computer, allowing it to be used for vHTS of large libraries of compounds. Overall, H-TEQ 4.5 solved the problems associated with the transferability of torsion parameters for conjugated molecules. This method was incorporated into the Molecular Operating Environment and will be available for a wide variety of applications.

Design and discovery of boronic acid drugs.

Research related to boronic acids, from synthetic development to materials to drug discovery, has skyrocketed in the past 20 years. In terms of drug discovery, the incorporation of boronic acids into medicinal chemistry endeavours has seen a steady increase in recent years. In fact, the Food and Drug Administration (FDA) and Health Canada have thus far approved five boronic acid drugs, three of which were approved in the past four years, and several others are in clinical trials. Boronic acids have several desirable properties that has led to their increased use, including potentially enhancing potency of drugs and/or improving their pharmacokinetics profile. This review explores discovery processes of boronic acid drugs. It begins with a brief scope of boron in natural products and in current drugs, followed by an investigation into the various rationalizations for boronic acid incorporation and the synthetic developments that focused on facilitating their addition into organic compounds. We hope that the knowledge we have assembled in this literature review will encourage medicinal chemists to consider the potential benefits of incorporating boronic acids into their future drug discovery endeavours.

Discovery of covalent prolyl oligopeptidase boronic ester inhibitors.

Over the past decade, many drug discovery endeavors have been invested in targeting the serine proteases prolyl oligopeptidase (POP) for the treatment of Alzheimer's and Parkinson's disease and, more recently, epithelial cancers. Our research group has focused on the discovery of reversible covalent inhibitors, namely nitriles, to target the catalytic serine residue in this enzyme. While there have been many inhibitors discovered containing a nitrile to covalently bind to the catalytic serine, we have been investigating others, particularly boronic acids and boronic esters, the latter of which have been largely unexplored as covalent warheads. Herein we report a series of computationally-designed POP boronic ester pro-drug inhibitors exhibiting nanomolar-potencies in vitro as their active boronic acid species. These easily-accessible (1-2 step syntheses) compounds could facilitate future biochemical and biological studies of this enzyme's role in neurodegenerative diseases and cancer progression.

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.

Integrated Synthetic, Biophysical, and Computational Investigations of Covalent Inhibitors of Prolyl Oligopeptidase and Fibroblast Activation Protein α.

Over the past decade, there has been increasing interest in covalent inhibition as a drug design strategy. Our own interest in the development of prolyl oligopeptidase (POP) and fibroblast activation protein α (FAP) covalent inhibitors has led us to question whether these two serine proteases were equal in terms of their reactivity toward electrophilic warheads. To streamline such investigations, we exploited both computational and experimental methods to investigate the influence of different reactive groups on both potency and binding kinetics using both our own series of POP inhibitors and others' discovered hits. A direct correlation between inhibitor reactivity and residence time was demonstrated through quantum mechanics methods and further supported by experimental studies. This computational method was also successfully applied to FAP, as an overview of known FAP inhibitors confirmed our computational predictions that more reactive warheads (e.g., boronic acids) must be employed to inhibit FAP than for POP.