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RNA molecules play critical roles in cellular functions at the level of gene expression and regulation. The intricate 3D structures and the functional roles of RNAs make RNA molecules ideal targets for therapeutic drugs. The rational design of RNA-targeted drug requires accurate modeling of RNA-ligand interactions. Recently a new computational tool, RLDOCK, was developed to predict ligand binding sites and binding poses. Using an iterative multiscale sampling and search algorithm and a energy-based evaluation of ligand poses, the method enables efficient and accurate predictions for RNA-ligand interactions. Here we present a detailed illustration of the computational procedure for the practical implementation of the RLDOCK method. Using Flavin mononucleotide (FMN) docking to F. nucleatum FMN riboswitch as an example, we illustrate the computational protocol for RLDOCK-based prediction of RNA- ligand interactions. The RLDOCK software is freely accessible at http://https://github.com/Vfold-RNA/RLDOCK.

For improved control of biomaterial property design, a better understanding of complex coacervation involving anionic polysaccharides and proteins is needed. Here, we address the initial steps in condensate formation of β-lactoglobulin A (β-LgA) with nine defined alginate oligosaccharides (AOSs) and describe their multivalent interactions in structural detail. Binding of AOSs containing four, five, or six uronic acid residues (UARs), either all mannuronate (M), all guluronate (G), or alternating M and G embodying the block structural components of alginates, was characterized by isothermal titration calorimetry, nuclear magnetic resonance spectroscopy (NMR), and molecular docking. β-LgA was highly multivalent exhibiting binding stoichiometries decreasing from five to two AOSs with increasing degree of polymerization (DP) and similar affinities in the mid micromolar range. The different AOS binding sites on β-LgA were identified by NMR chemical shift perturbation analyses and showed diverse compositions of charged, polar and hydrophobic residues. Distinct sites for the shorter AOSs merged to accommodate longer AOSs. The AOSs bound dynamically to β-LgA, as concluded from saturation transfer difference and 1H-ligand-targeted NMR analyses. Molecular docking using Glide within the Schrödinger suite 2016-1 revealed the orientation of AOSs to only vary slightly at the preferred β-LgA binding site resulting in similar XP glide scores. The multivalency coupled with highly dynamic AOS binding with lack of confined conformations in the β-LgA complexes may help explain the first steps toward disordered β-LgA alginate coacervate structures. For improved control of biomaterial property design, a better understanding of complex coacervation involving anionic polysaccharides and proteins is needed. Here, we address the initial steps in condensate formation of beta-lactoglobulin A (beta-LgA) with nine defined alginate oligosaccharides (AOSs) and describe their multivalent interactions in structural detail. Binding of AOSs containing four, five, or six uronic acid residues (UARs), either all mannuronate (M), all guluronate (G), or alternating M and G embodying the block structural components of alginates, was characterized by isothermal titration calorimetry, nuclear magnetic resonance spectroscopy (NMR), and molecular docking. beta-LgA was highly multivalent exhibiting binding stoichiometries decreasing from five to two AOSs with increasing degree of polymerization (DP) and similar affinities in the mid micromolar range. The different AOS binding sites on beta-LgA were identified by NMR chemical shift perturbation analyses and showed diverse compositions of charged, polar and hydrophobic residues. Distinct sites for the shorter AOSs merged to accommodate longer AOSs. The AOSs bound dynamically to beta-LgA, as concluded from saturation transfer difference and H-1-ligand-targeted NMR analyses. Molecular docking using Glide within the Schrodinger suite 2016-1 revealed the orientation of AOSs to only vary slightly at the preferred beta-LgA binding site resulting in similar XP glide scores. The multivalency coupled with highly dynamic AOS binding with lack of confined conformations in the beta-LgA complexes may help explain the first steps toward disordered beta-LgA alginate coacervate structures.

Necroptosis is a form of programmed cell death that in case of misregulation can lead to inflammatory diseases. Mixed lineage kinase domain-like protein (MLKL), the effector protein in the canonical necroptosis signaling pathway, becomes activated by phosphorylation. Here, we report the identification of novel reversible binders of the MLKL executioner domain by a protein NMR-detected fragment-based screen. Determination of protein fragment costructures using NMR spectroscopy revealed a small molecule binding site that is distinct from the previously identified binding site of covalent MLKL inhibitors. Affinity optimization of the initially prioritized hit with millimolar affinity was achieved by NMR-guided structure-based design and yielded fragment-like molecules with a KD of 50 μM. Furthermore, we demonstrate that the improved fragment competes for the same binding site as nonyl-maltoside, a detergent that in conjunction with phytic acid activates the MLKL executioner domain.

Elevated expression of the c-MYC oncogene is one of the most common abnormalities in human cancers. Unfortunately, efforts to identify pharmacological inhibitors that directly target MYC have not yet yielded a drug-like molecule due to the lack of any known small molecule binding pocket in the protein, which could be exploited to disrupt MYC function. We have recently described a strategy to target MYC indirectly, where a screening effort designed to identify compounds that can rapidly decrease endogenous c-MYC protein levels in a MYC-amplified cell line led to the discovery of a compound series that phenocopies c-MYC knockdown by siRNA. Herein, we describe our medicinal chemistry program that led to the discovery of potent, orally bioavailable c-MYC-reducing compounds. The development of a minimum pharmacophore model based on empirical structure activity relationship as well as the property-based approach used to modulate pharmacokinetics properties will be highlighted.

The novel SARS-CoV-2 uses ACE2 (Angiotensin-Converting Enzyme 2) receptor as an entry point. Insights on S protein receptor-binding domain (RBD) interaction with ACE2 receptor and drug repurposing has accelerated drug discovery for the novel SARS-CoV-2 infection. Finding small molecule binding sites in S protein and ACE2 interface is crucial in search of effective drugs to prevent viral entry. In this study, we employed molecular dynamics simulations in mixed solvents together with virtual screening to identify small molecules that could be potential inhibitors of S protein -ACE2 interaction. Observation of organic probe molecule localization during the simulations revealed multiple sites at the S protein surface related to small molecule, antibody, and ACE2 binding. In addition, a novel conformation of the S protein was discovered that could be stabilized by small molecules to inhibit attachment to ACE2. The most promising binding site on RBD-ACE2 interface was targeted with virtual screening and top-ranked compounds (DB08248, DB02651, DB03714, and DB14826) are suggested for experimental testing. The protocol described here offers an extremely fast method for characterizing key proteins of a novel pathogen and for the identification of compounds that could inhibit or accelerate spreading of the disease.

Cytoglobin is a conserved hemoprotein ubiquitously expressed in mammalian tissues, which conducts electron transfer reactions with proposed signaling functions in nitric oxide (NO) and lipid metabolism. Cytoglobin has an E7 distal histidine (His81), which unlike related globins such as myoglobin and hemoglobin, is in equilibrium between a bound, hexacoordinate state and an unbound, pentacoordinate state. The His81 binding equilibrium appears to be allosterically modulated by the presence of an intramolecular disulfide between two cysteines (Cys38 and Cys83). The formation of this disulfide bridge regulates nitrite reductase activity and lipid binding. Herein, we attempt to clarify the effects of defined thiol oxidation states on small molecule binding of cytoglobin heme, using cyanide binding to probe the ferric state. Cyanide binding kinetics to wild-type cytoglobin reveal at least two kinetically distinct subpopulations, depending on thiol oxidation states. Experiments with covalent thiol modification by NEM, glutathione, and amino acid substitutions (C38S, C83S and H81A), indicate that subpopulations ranging from fully reduced thiols, single thiol oxidation, and intramolecular disulfide formation determine heme binding properties by modulating the histidine-heme affinity and ligand binding. The redox modulation of ligand binding is sensitive to physiological levels of hydrogen peroxide, with a functional midpoint redox potential for the native cytoglobin intramolecular disulfide bond of −189 ± 4 mV, a value within the boundaries of intracellular redox potentials. These results support the hypothesis that Cys38 and Cys83 on cytoglobin serve as sensitive redox sensors that modulate the cytoglobin distal heme pocket reactivity and ligand binding.

Graphical abstract, We study the models submitted to round 12 of the Critical Assessment of protein Structure Prediction (CASP) experiment to assess how well the binding properties are conserved when the X-ray structures of the target proteins are replaced by their models. To explore small molecule binding we generate distributions of molecular probes – which are fragment-sized organic molecules of varying size, shape, and polarity – around the protein, and count the number of interactions between each residue and the probes, resulting in a vector of interactions we call a binding fingerprint. The similarity between two fingerprints, one for the X-ray structure and the other for a model of the protein, is determined by calculating the correlation coefficient between the two vectors. The resulting correlation coefficients are shown to correlate with global measures of accuracy established in CASP, and the relationship yields an accuracy threshold that has to be reached for meaningful binding surface conservation. The clusters formed by the probe molecules reliably predict binding hot spots and ligand binding sites in both X-ray structures and reasonably accurate models of the target, but ensembles of models may be needed for assessing the availability of proper binding pockets. We explored ligand docking to the few targets that had bound ligands in the X-ray structure. More targets were available to assess the ability of the models to reproduce protein–protein interactions by docking both the X-ray structures and models to their interaction partners in complexes. It was shown that this application is more difficult than finding small ligand binding sites, and the success rates heavily depend on the local structure in the potential interface. In particular, predicted conformations of flexible loops are frequently incorrect in otherwise highly accurate models, and may prevent predicting correct protein–protein interactions.

The activation, storage, and separation of gases and fuels are closely related to the reduction of greenhouse gas emissions, the widespread use of renewable energies, and the application of industr...

Monoclonal antibodies and their fragments are widely used for research and therapy. Fab fragments are useful since they retain antigen binding specificity, but being smaller proteins, are better able to penetrate biological compartments and tumors, and do not induce Fc-dependent immunological system activation. Our laboratory developed an anti-cocaine mAb (named h2E2) for the treatment of cocaine use disorders, which is currently in advanced pre-clinical development. We are also interested in the Fab fragment of this mAb for potential therapy of acute cocaine overdose. Previously, we previously showed that this mAb and its F(ab’)(2) and Fab fragments undergo discrete domain unfolding, as detected by non-reducing SDS-PAGE, and that ligand-induced protein thermal stabilization can be quantitated utilizing differential scanning fluorimetry in the absence of SDS. Here, we demonstrate that multiple Fab protein gel bands observed using non-reducing SDS-PAGE in the presence and absence of cocaine and its metabolites can be explained and interpreted based on the differential stabilization of two unfolding domains in the Fab fragment. The variable domain is stabilized by ligands against SDS unfolding, while the constant domain is not. This data and its interpretation are also supported by differential scanning fluorimetry data for the Fab fragment in SDS. It is likely that these non-reducing SDS-PAGE results and the gel band domain unfolding model will be applicable to other small molecule binding antibodies. Thus, non-reducing SDS-PAGE is a widely available and simple method for assessing domain stability and multi-step unfolding of Fab fragments.

The higher-order structure (HOS) of proteins plays a critical role in their function; therefore, it is important to our understanding of their function that we have as much information as possible about their three-dimensional structure and how it changes with time. Mass spectrometry (MS) has become an important tool for determining protein HOS owing to its high throughput, mid-to-high spatial resolution, low sample amount requirement and broad compatibility with various protein systems. Modern MS-based protein HOS analysis relies, in part, on footprinting, where a reagent reacts ‘to mark’ the solvent-accessible surface of the protein, and MS-enabled proteomic analysis locates the modifications to afford a footprint. Fast photochemical oxidation of proteins (FPOP), first introduced in 2005, has become a powerful approach for protein footprinting. Laser-induced hydrogen peroxide photolysis generates hydroxyl radicals that react with solvent-accessible side chains (14 out of 20 amino acid side chains) to fulfill the footprinting. The reaction takes place at sub-milliseconds, faster than most of labeling-induced protein conformational changes, thus enabling a ‘snapshot’ of protein HOS in solution. As a result, FPOP has been employed in solving several important problems, including mapping epitopes, following protein aggregation, locating small molecule binding, measuring ligand-binding affinity, monitoring protein folding and unfolding and determining hidden conformational changes invisible to other methods. Broader adoption will be promoted by dissemination of the technical details for assembling the FPOP platform and for dealing with the complexities of analyzing FPOP data. In this protocol, we describe the FPOP platform, the conditions for successful footprinting and its examination by mass measurements of the intact protein, the post-labeling sample handling and digestion, the liquid chromatography–tandem MS analysis of the digested sample and the data analysis with Protein Metrics Suite. This protocol is intended not only as a guide for investigators trying to establish an FPOP platform in their own lab but also for those willing to incorporate FPOP as an additional tool in addressing their questions of interest. Footprinting reports solvent accessibilities of a protein or protein complex. This protocol describes a fast photochemical oxidation of proteins platform for footprinting, with laser-initiated H2O2 photolysis and mass spectrometry analysis.

Hydration is a critical factor in the ligand binding process. Herein, to examine the hydration states of ligand binding sites, the three‐dimensional distribution function for the water oxygen site, gO(r), is computed for 3,706 ligand‐free protein structures based on the corresponding small molecule–protein complexes using the 3D‐RISM theory. For crystallographic waters (CWs) close to the ligand, gO(r) reveals that several CWs are stabilized by interaction networks formed between the ligand, CW, and protein. Based on the gO(r) for the crystallographic binding pose of the ligand, hydrogen bond interactions are dominant in the highly hydrated regions while weak interactions such as CH‐O are dominant in the moderately hydrated regions. The polar heteroatoms of the ligand occupy the highly hydrated and moderately hydrated regions in the crystallographic (correct) and wrongly docked (incorrect) poses, respectively. Thus, the gO(r) of polar heteroatoms may be used to distinguish the correct binding poses., The hydration states of ligand binding sites are comprehensively analyzed using a theory of solvation. An analysis of the hydration states at the positions of ligand heavy atoms indicates that the polar heteroatoms of the ligand tend to occupy highly hydrated regions in the correct ligand poses and moderately hydrated regions in the incorrect ligand poses, suggesting a way to distinguish these two poses.

Although the potential value of RNA as a target for new small molecule therapeutics is becoming increasingly credible, the physicochemical properties required for small molecules to selectively bind to RNA remain relatively unexplored. To investigate the druggability of RNAs with small molecules, we have employed affinity mass spectrometry, using the Automated Ligand Identification System (ALIS), to screen 42 RNAs from a variety of RNA classes, each against an array of chemically diverse drug-like small molecules (~50,000 compounds) and functionally annotated tool compounds (~5100 compounds). The set of RNA-small molecule interactions that was generated was compared with that for protein-small molecule interactions, and naïve Bayesian models were constructed to determine the types of specific chemical properties that bias small molecules toward binding to RNA. This set of RNA-selective chemical features was then used to build an RNA-focused set of ~3800 small molecules that demonstrated increased propensity toward binding the RNA target set. In addition, the data provide an overview of the specific physicochemical properties that help to enable binding to potential RNA targets. This work has increased the understanding of the chemical properties that are involved in small molecule binding to RNA, and the methodology used here is generally applicable to RNA-focused drug discovery efforts.

The design and discovery of small molecule medicines has largely been focused on a small number of druggable protein families. A new paradigm is emerging, however, in which small molecules exert a biological effect by interacting with RNA, both to study human disease biology and provide lead therapeutic modalities. Due to this potential for expanding target pipelines and treating a larger number of human diseases, robust platforms for the rational design and optimization of small molecules interacting with RNAs (SMIRNAs) are in high demand. This review highlights three major pillars in this area. First, the transcriptome-wide identification and validation of structured RNA elements, or motifs, within disease-causing RNAs directly from sequence is presented. Second, we provide an overview of high-throughput screening approaches to identify SMIRNAs as well as discuss the lead identification strategy, Inforna, which decodes the three-dimensional (3D) conformation of RNA motifs with small molecule binding partners, directly from sequence. An emphasis is placed on target validation methods to study the causality between modulating the RNA motif in vitro and the phenotypic outcome in cells. Third, emergent modalities that convert occupancy-driven mode of action SMIRNAs into event-driven small molecule chemical probes, such as RNA cleavers and degraders, are presented. Finally, the future of the small molecule RNA therapeutics field is discussed, as well as hurdles to overcome to develop potent and selective RNA-centric chemical probes.

Graphical abstract, Protein-protein interactions play an essential role in many biological processes, and their perturbation is a major cause of disease. The use of small molecules to modulate them is attracting increased attention, but protein interfaces generally do not have clear cavities for binding small compounds. A proposed strategy is to target interface hot-spot residues, but their identification through computational approaches usually require the complex structure, which is not often available. In this context, pyDock energy-based docking and scoring can predict hot-spots on the unbound proteins, thus not requiring the complex structure. Here, we have devised a new strategy to detect protein–protein inhibitor binding sites, based on the integration of molecular dynamics for the generation of transient cavities, and docking-based interface hot-spot prediction for the selection of the suitable cavities. This integrative approach has been validated on a test set formed by protein–protein complexes with known inhibitors for which complete structural data of unbound molecules and complexes is available. The results show that local conformational sampling with short molecular dynamics can generate transient cavities similar to the known inhibitor binding sites, and that docking simulations can identify the best cavities with similar predictive accuracy as when knowing the real interface. In a few cases, these predicted pockets are shown to be suitable for protein–ligand docking. The proposed strategy will be useful for many protein–protein complexes for which there is no available structure, as long as the the unbound proteins do not deviate dramatically from the bound conformations.

Self-cleaving ribozymes engineered to be activated or inhibited by a small molecule binding to an RNA aptamer inserted within a ribozyme (aptazymes) have proven to be useful for controlling gene expression in living cells. In mammalian cells, an aptazyme embedded in the 5′ or 3′ untranslated region of an mRNA functions as a synthetic riboswitch to chemically regulate gene expression. However, the variety of aptazyme architectures and the ribozyme scaffolds that have been used for mammalian riboswitches has been limited. In particular, fewer synthetic riboswitches that activate gene expression in response to a small molecule (ON-switches) in mammalian cells have been reported compared to OFF-switches. In this work, we developed mammalian riboswitches that function as guanine-activated ON-switches based on a novel aptazyme architecture in which an aptamer and a ribozyme are fused in tandem. The riboswitch performance was optimized by fine-tuning the stability of a critical stem that controls the ribozyme structure and function, yielding switches with ON/OFF ratios greater than 6.0. Our new aptazyme architecture expands the RNA device toolbox for controlling gene expression in mammalian cells.

Small molecule binding assays to target proteins are a core component of drug discovery and development. While a number of assay formats are available, significant drawbacks still remain in cost, sensitivity, and throughput. To improve assays by capitalizing on the power of DNA sequence analysis, we have developed an assay method that combines DNA encoding with split-and-pool sample handling. The approach involves affinity labeling of DNA-linked ligands to a protein target. Critically, the labeling event assesses ligand binding and enables subsequent pooling of several samples . Application of a purifying selection on the pool for protein-labeled DNAs allows detection of ligand binding by quantification of DNA barcodes. We demonstrate the approach in both ligand displacement and direct binding formats and demonstrate its utility in determination of relative ligand affinity, profiling ligand specificity, and high-throughput small molecule screening.

Charge sensitive optical detection (CSOD) technique is a label-free method for real-time measurement of molecular interactions. Traditional label-free optical detection techniques mostly measure the mass of a molecule, and they are less sensitive to small molecules. In contrast, CSOD detects the charge of a molecule, where the signal does not diminish with the size of the molecule, thus capable for studying small molecules. In addition, CSOD is compatible with the standard microplate platform, making it suitable for high-throughput screening of drug candidates. In CSOD, an optical fiber functionalized with the probe molecule is dipped into a well of a microplate where an alternate perpendicular electrical field is applied to the fiber, which drives the fiber into oscillation because of the presence of surface charge on the fiber. The binding of the target molecules changes the charge of the fiber, and thus the amplitude and phase of the oscillating fiber, which are precisely measured through tracking of the optical images of the fiber tip.

TLR7 and TLR8 are key members of the Toll-like receptor family, playing crucial roles in the signaling pathways of innate immunity, and thus become attractive therapeutic targets of many diseases including infections and cancer. Although TLR7 and TLR8 show a highly degree of sequence homology, their biological response to small molecule binding is very different. Aiming to understand the mechanism of selective profiles of small molecule modulators against TLR7 and TLR8, we carried out molecular dynamic simulations on three imidazoquinoline derivatives bound to the receptors separately. They are Resiquimod (R), Hybrid-2 (H), and Gardiquimod (G), selective agonists of TLR7 and TLR8. Our MD trajectories indicated that in the complex of TLR7-R and TLR7-G, the two chains forming the TLR7 dimer tended to remain “open” conformation, while the rest systems maintained in the closed format. The agonists R, H, and G developed conformational deviation mainly on the aliphatic tail. Furthermore, we attempted to quantify the selectivity between TLR7 and TLR8 by binding free energies via MM-GBSA method. It showed that the three selected modulators were more favorable for TLR7 than TLR8, and the ranking from the strongest to the weakest was H, R and G, aligning well with experiment data. In the TLR7, the flexible and hydrophobic aliphatic side chain of H has stronger van der Waals interactions with Val381 and Phe351 but only pick up interaction with one amino acid residue i.e. Tyr353 of TLR8. Unsurprisingly, the positively charged side chain of G has less favor interaction with Ile585 of TLR7 and Val573 of TLR8 explaining G is weak agonist in both TLR7 and TLR8. All three imidazoquinolines can form stable hydrogen bonds with Asp555 of TLR7 and the corresponding Asp543 of TLR8. In brief, the set of total 400ns MD studies sheds light on the potential selective mechanisms of agonists towards TLR7 and TLR8, indicating the van der Waals interaction as the driving force for the agonists binding, thus provides us insights for more potent and selective modulators to cooperate with the hydrophobic nature of the binding pocket.

G-quadruplexes are four-stranded nucleic acid secondary structures of biological significance and have emerged as an attractive drug target. The G4 formed in the MYC promoter (MycG4) is one of the most studied small-molecule targets, and a model system for parallel structures that are prevalent in promoter DNA G4s and RNA G4s. Molecular docking has become an essential tool in structure-based drug discovery for protein targets, and is also increasingly applied to G4 DNA. However, DNA, and in particular G4, binding sites differ significantly from protein targets. Here we perform the first systematic evaluation of four commonly used docking programs (AutoDock Vina, DOCK 6, Glide, and RxDock) for G4 DNA-ligand binding pose prediction using four small molecules whose complex structures with the MycG4 have been experimentally determined in solution. The results indicate that there are considerable differences in the performance of the docking programs and that DOCK 6 with GB/SA rescoring performs better than the other programs. We found that docking accuracy is mainly limited by the scoring functions. The study shows that current docking programs should be used with caution to predict G4 DNA-small molecule binding modes.

The hydration shells of proteins mediate interactions, such as small molecule binding, that are vital to their biological function or in some cases their dysfunction. However, even when the structure of a protein is known, the properties of its hydration environment cannot be easily predicted due to the complex interplay between protein surface heterogeneity and the collective fluctuations of water's hydrogen bonding network. This manuscript presents a theoretical study of the influence of surface charge heterogeneity on the polarization response of the liquid water interface. We introduce a new computational method for analyzing simulation data that is capable of quantifying water's nonlinear polarization response and determining the effective surface charge distribution of hydrated surfaces over atomistic length scales. When applied to a protein, this method is capable of revealing new insight into the influence of conformational dynamics on hydration structure, as we highlight by illustrating how salt-bridge formation enhances the polarization of the local hydration shell. To illustrate the utility of this method, we present the results of molecular dynamics simulations of liquid water in contact with a heterogeneous model surface and the CheY protein.

Fluorescent noncanonical amino acids (fNCAAs) could serve as starting points for the rational design of protein-based fluorescent sensors of biological activity. However, efforts toward this goal are likely hampered by a lack of atomic-level characterization of fNCAAs within proteins. Here, we describe the spectroscopic and structural characterization of five streptavidin mutants that contain the fNCAA l-(7-hydroxycoumarin-4-yl)ethylglycine (7-HCAA) at sites proximal to the binding site of its substrate, biotin. Many of the mutants exhibited altered fluorescence spectra in response to biotin binding, which included both increases and decreases in fluorescence intensity as well as red- or blue-shifted emission maxima. Structural data were also obtained for three of the five mutants. The crystal structures shed light on interactions between 7-HCAA and functional groups, contributed either by the protein or by the substrate, that may be responsible for the observed changes in the 7-HCAA spectra. These data could be used in future studies aimed at the rational design of fluorescent, protein-based sensors of small molecule binding or dissociation.

Transcription factors (TF), such as Myc, are proteins implicated in disease pathogenesis, with dysregulation of Myc expression in 50% of all human cancers. Still, targeting Myc remains a challenge due to the lack of small molecule binding pockets in the tertiary structure. Here, we report synthetic covalently linked TF mimetics that inhibit oncogenic Myc-driven transcription by antagonistic binding of the target DNA-binding site. We combined automated flow peptide chemistry with palladium(II) oxidative addition complexes (OACs) to engineer covalent protein dimers derived from the DNA-binding domains of Myc, Max, and Omomyc TF analogs. Palladium-mediated cross-coupling of synthesized protein monomers resulted in milligram quantities of seven different covalent homo- and heterodimers. The covalent helical dimers were found to bind DNA and exhibited improved thermal stability. Cell-based studies revealed the Max-Max covalent dimer is cell-penetrating and interfered with Myc-dependent gene transcription resulting in reduced cancer cell proliferation (EC50 of 6 μM in HeLa). RNA sequencing and gene analysis of extracted RNA from treated cancer cells confirmed that the covalent Max-Max homodimer interferes with Myc-dependent transcription. Flow chemistry, combined with palladium(II) OACs, has enabled a practical strategy to generate new bioactive compounds to inhibit tumor cell proliferation.

The CDK family plays a crucial role in the control of the cell cycle. Dysregulation and mutation of the CDKs has been implicated in cancer and the CDKs have been investigated extensively as potential therapeutic targets. Selective inhibition of specific isoforms of the CDKs is crucial to achieve therapeutic effect while minimising toxicity. We present a group of photoaffinity probes designed to bind to the family of CDKs. The site of crosslinking of the optimised probe, as well as its ability to enrich members of the CDK family from cell lysates, was investigated. In a proof of concept study, we subsequently developed a photoaffinity probe-based competition assay to profile CDK inhibitors. We anticipate that this approach will be widely applicable to the study of small molecule binding to protein families of interest.

The analysis and prediction of small molecule binding sites is very important for drug discovery and drug design. The traditional experimental methods for detecting small molecule binding sites are usually expensive and time consuming, and the tools for single species small molecule research are equally inefficient. In recent years, some algorithms for predicting binding sites of protein-small molecules have been developed based on the geometric and sequence characteristics of proteins. In this paper, we have proposed SmoPSI, a classification model based on the XGBoost algorithm for predicting the binding sites of small molecules, using protein sequence information. The model achieved better results with an AUC of 0.918 and an ACC of 0.913. The experimental results demonstrate that our method achieves high performances and outperforms many existing predictors. In addition, we also analyzed the binding residues and nonbinding residues and finally found the PSSM; hydrophilicity, hydrophobicity, charge, and hydrogen bonding have obviously different effects on the binding-site predictions.

Mass spectrometry (MS)-based protein footprinting, a valuable structural tool in mapping protein-ligand interaction, has been extensively applied to protein-protein complexes, showing success in mapping large interfaces. Here, we utilized an integrated footprinting strategy incorporating both hydrogen-deuterium exchange (HDX) and hydroxyl radical footprinting (i.e., fast photochemical oxidation of proteins (FPOP)) for molecular-level characterization of the interaction of human bromodomain-containing protein 4 (BRD4) with a hydrophobic benzodiazepine inhibitor. HDX does not provide strong evidence for the location of the binding interface, possibly because the shielding of solvent by the small molecule is not large. Instead, HDX suggests that BRD4 appears to be stabilized by showing a modest decrease in dynamics caused by binding. In contrast, FPOP points to a critical binding region in the hydrophobic cavity, also identified by crystallography, and, therefore, exhibits higher sensitivity than HDX in mapping the interaction of BRD4 with compound 1. In the absence or under low concentrations of the radical scavenger, FPOP modifications on Met residues show significant differences that reflect the minor change in protein conformation. This problem can be avoided by using a sufficient amount of proper scavenger, as suggested by the FPOP kinetics directed by a dosimeter of the hydroxyl radical.

Recent crystallography studies have shown that the binding site oxyanion hole plays an important role in inhibitor binding, but can exist in two conformations (active/inactive). We have undertaken molecular dynamics (MD) calculations to better understand oxyanion hole dynamics and thermodynamics. We find that the Zika virus (ZIKV) NS2B/NS3 protease maintains a stable closed conformation over multiple 100-ns conventional MD simulations in both the presence and absence of inhibitors. The S1, S2, and S3 pockets are stable as well. However, in two of eight simulations, the A132-G133 peptide bond in the binding pocket of S1' spontaneously flips to form a 310 -helix that corresponds to the inactive conformation of the oxyanion hole, and then maintains this conformation until the end of the 100-ns conventional MD simulations without inversion of the flip. This conformational change affects the S1' pocket in ZIKV NS2B/NS3 protease active site, which is important for small molecule binding. The simulation results provide evidence at the atomic level that the inactive conformation of the oxyanion hole is more favored energetically when no specific interactions are formed between substrate/inhibitor and oxyanion hole residues. Interestingly, however, transition between the active and inactive conformation of the oxyanion hole can be observed by boosting the valley potential in accelerated MD simulations. This supports a proposed induced-fit mechanism of ZIKV NS2B/NS3 protease from computational methods and provides useful direction to enhance inhibitor binding predictions in structure-based drug design.

Summary Polymorphism in the microglial receptor CD33 gene has been linked to late-onset Alzheimer disease (AD), and reduced expression of the CD33 sialic acid-binding domain confers protection. Thus, CD33 inhibition might be an effective therapy against disease progression. Progress toward discovery of selective CD33 inhibitors has been hampered by the absence of an atomic resolution structure. We report here the crystal structures of CD33 alone and bound to a subtype-selective sialic acid mimetic called P22 and use them to identify key binding residues by site-directed mutagenesis and binding assays to reveal the molecular basis for its selectivity toward sialylated glycoproteins and glycolipids. We show that P22, when presented on microparticles, increases uptake of the toxic AD peptide, amyloid-β (Aβ), into microglial cells. Thus, the sialic acid-binding site on CD33 is a promising pharmacophore for developing therapeutics that promote clearance of the Aβ peptide that is thought to cause AD., Graphical Abstract, Highlights • A sialic acid mimetic increases the uptake of Alzheimer peptide into microglia • Crystal structure of cell surface receptor CD33 bound to the sialic acid mimetic • Crystal structure of unliganded CD33 and mutagenesis studies revealed key residues • CD33 carbohydrate-binding site is a pharmacophore for Alzheimer drug development, Molecular Structure; Neuroscience; Molecular Neuroscience; Components of the Immune System; Protein Structure Aspects

RNA is a regulator and catalyst of many cellular processes. Efforts to therapeutically harness RNA began with the discovery of myriad coding and non-coding RNAs and their versatile modes of action. However, due to its dynamic structure and the polar and repetitive nature of its surface, RNA presents a challenging target for drug design. For an RNA to be druggable, it must contain a motif that assumes a nearly fixed and unique conformation that a small molecule can recognize and bind consistently and with high affinity. Hence, reliable methods for determining the secondary and tertiary structures of RNA, and even the features and occupancy of potential drug binding sites are of utmost importance for the effective design of RNA-based therapeutics. Selective 2'-hydroxyl acylation analyzed by primer extension and mutational profiling (SHAPE-MaP) has emerged as such a method, by which RNA secondary structure can be probed at single-nucleotide resolution, under a variety of conditions, and in the presence of RNA-specific small-molecule ligands. In this review, we describe an in-depth protocol for using SHAPE-MaP to characterize RNA-small molecule interactions in cell culture (in cellulo). This method can be applied to transcripts of any size or abundance, and to determine the sites and affinities of small molecule binding, making it an essential and versatile tool for drug discovery.

Highlights • Techniques for quantitative in vitro analysis of fluorogen-RNA aptamers are needed. • We have recently developed a novel method for the production of functional-RNA arrays. • A protocol for the production of fluorogen-binding RNA aptamer arrays is presented. • We assess the malachite green-binding aptamer and Spinach aptamer using RNA arrays. • We demonstrate application of RNA arrays to biosensors using a Spinach/SAM RNA array., The discovery and engineering of more and more functions of RNA has highlighted the utility of RNA-targeting small molecules. Recently, several fluorogen-binding RNA aptamers have been developed that have been applied to live cell imaging of RNA and metabolites as RNA tags or biosensors, respectively. Although the design and application of these fluorogen-binding RNA aptamer-based devices is straightforward in theory, in practice, careful optimisation is required. For this reason, high throughput in vitro screening techniques, capable of quantifying fluorogen-RNA aptamer interactions, would be beneficial. We recently developed a method for generating functional-RNA arrays and demonstrated that they could be used to detect fluorogen-RNA aptamer interactions. Specifically, we were able to visualise the interaction between malachite green and the malachite green-binding aptamer. Here we expand this study to demonstrate that functional-RNA arrays can be used to quantify fluorogen-aptamer interactions. As proof-of-concept, we provide detailed protocols for the production of malachite green-binding RNA aptamer and DFHBI-binding Spinach RNA aptamer arrays. Furthermore, we discuss the potential utility of the technology to fluorogen-binding RNA aptamers, including application as a molecular biosensor platform. We anticipate that functional-RNA array technology will be beneficial for a wide variety of biological disciplines.

Structural characterization of small molecule binding site hotspots within the global proteome is uniquely enabled by photoaffinity labeling (PAL) coupled with chemical enrichment and unbiased analysis by mass spectrometry (MS). MS-based binding site maps provide structural resolution of interaction sites in conjunction with identification of target proteins. However, binding site hotspot mapping has been confined to relatively simple small molecules to date; extension to more complex compounds would enable the structural definition of new binding modes in the proteome. Here, we extend PAL and MS methods to derive a binding site hotspot map for the immunosuppressant rapamycin, a complex macrocyclic natural product that forms a ternary complex with the proteins FKBP12 and FRB. Photo-rapamycin was developed as a diazirine-based PAL probe for rapamycin, and the FKBP12-photo-rapamycin-FRB ternary complex formed readily in vitro. Photoirradiation, digestion, and MS analysis of the ternary complex revealed a McLafferty rearrangement product of photo-rapamycin conjugated to specific surfaces on FKBP12 and FRB. Molecular modeling based on the binding site map revealed two distinct conformations of complex-bound photo-rapamycin, providing a 5.0 Å distance constraint between the conjugated residues and the diazirine carbon and a 9.0 Å labeling radius for the diazirine upon photoactivation. These measurements may be broadly useful in the interpretation of binding site measurements from PAL. Thus, in characterizing the ternary complex of photo-rapamycin by MS, we applied binding site hotspot mapping to a macrocyclic natural product and extracted precise structural measurements for interpretation of PAL products that may enable the discovery of new binding sites in the "undruggable" proteome.

Phytohormones regulate the plasticity of plant growth and development, and responses to biotic and abiotic stresses. Many hormone signal transduction cascades involve ubiquitination and subsequent degradation of proteins by the 26S proteasome. The conjugation of ubiquitin to a substrate is facilitated by the E1 activating, E2 conjugating, and the substrate-specifying E3 ligating enzymes. The most prevalent type of E3 ligase in plants is the Cullin–RING ligase (CRL)-type, with F-box proteins (FBPs) as the substrate recognition component. The activity of these SKP–Cullin–F-box (SCF) complexes needs to be tightly regulated in time and place. Here, we review the regulation of SCF function in plants on multiple levels, with a focus on the auxin and jasmonate SCF-type receptor complexes. We discuss in particular the relevance of protein–protein interactions and post-translational modifications as mechanisms to keep SCF functioning under control. Additionally, we highlight the unique property of SCFTIR1/AFB and SCFCOI1 to recognize substrates by forming co-receptor complexes. Finally, we explore how engineered selective agonists can be used to study and uncouple the outcomes of the complex auxin and jasmonate signaling networks that are governed by these FBPs.

RNA has attracted considerable attention as a target for small molecules. However, methods to identify, study, and characterize suitable RNA targets have lagged behind strategies for protein targets. One approach that has received considerable attention for protein targets has been to utilize computational analysis to investigate ligandable “pockets” on proteins that are amenable to small molecule binding. These studies have shown that selected physical properties of pockets are important parameters that govern the ability of a structure to bind to small molecules. This work describes a similar analysis to study pockets on all RNAs in the Protein Data Bank (PDB). Using parameters such as buriedness, hydrophobicity, volume, and other properties, the set of all RNAs is analyzed and compared to all proteins. Considerable overlap is observed between the properties of pockets on RNAs and proteins. Thus, many RNAs are capable of populating conformations with pockets that are likely suitable for small molecule binding. Further, principal moment of inertia (PMI) calculations reveal that liganded RNAs exist in diverse structural space, much of which overlaps with protein structural space. Taken together, these results suggest that complex folded RNAs adopt unique structures with pockets that may represent viable opportunities for small molecule targeting.

Proteins are nature’s most versatile molecular machines. Deep neural networks trained on large protein datasets have recently been used to tackle the unmet complexity of protein sequence–function relationships. The implicit knowledge contained in these networks represents a powerful, but thus far inaccessible, resource for understanding protein biology. Here, we show that occlusion-based sensitivity analysis can leverage the knowledge present in deep-neural-network-based protein sequence classifiers to identify functionally relevant parts of proteins. We first validated our approach by successfully predicting positions that mediate small molecule binding or catalytic activity across different protein classes. Next, we inferred the impact of point mutations on the activity of ERK and HRas, signalling factors frequently deregulated in cancer. Finally, we used our approach to identify engineering hotspots in CRISPR–Cas9 and anti-CRISPR protein AcrIIA4. Our work demonstrates how implicit knowledge in neural networks can be harnessed for protein functional dissection and protein engineering. Deep neural networks are a powerful tool for predicting protein function, but identifying the specific parts of a protein sequence that are relevant to its functions remains a challenge. An occlusion-based sensitivity technique helps interpret these deep neural networks, and can guide protein engineering by locating functionally relevant protein positions.

KRAS is the most commonly mutated oncogene in human cancer, with particularly high mutation frequencies in pancreatic cancers, colorectal cancers, and lung cancers [Ostrem, J. M., and Shokat, K. M. (2016) Nat. Rev. Drug Discovery 15, 771–785]. The high prevalence of KRAS mutations and its essential role in many cancers make it a potentially attractive drug target; however, it has been difficult to create small molecule inhibitors of mutant K-Ras proteins. Here, we identified a putative small molecule binding site on K-RasG12D using computational analyses of the protein structure and then used a combination of computational and biochemical approaches to discover small molecules that may bind to this pocket, which we have termed the P110 site, due to its adjacency to proline 110. We confirmed that one compound, named K-Ras allosteric ligand KAL-21404358, bound to K-RasG12D, as measured by microscale thermophoresis, a thermal shift assay, and nuclear magnetic resonance spectroscopy. KAL-21404358 did not bind...

Despite their wide applicability, the selection of small molecule-binding RNA aptamers with both high affinity binding and specificity is still challenging. Aptamers that excel at both binding and structure switching are particularly rare and difficult to find. Here, we present the protocol of a Capture-SELEX that specifically allows the in vitro selection of small-molecule binding aptamers, which are essential building blocks for the design process of synthetic riboswitches and biosensors. Moreover, we provide a comparative overview of our proposed methodology versus alternative in vitro selection protocols with a special focus on the design of the pool. Finally, we have included detailed notes to point out useful tips and pitfalls for future application.

Recent advances in native mass spectrometry (MS) have enabled the elucidation of how small molecule binding to membrane proteins modulates their structure and function. The protein-stabilizing osmolyte, trimethylamine oxide (TMAO), exhibits attractive properties for native MS studies. Here, we report significant charge reduction, nearly threefold, for three membrane protein complexes in the presence of this osmolyte without compromising mass spectral resolution. TMAO improves the ability to resolve individual lipid-binding events to the ammonia channel (AmtB) by over 200% compared to typical native conditions. The generation of ions with compact structure and access to a larger number of lipid-binding events through the incorporation of TMAO increases the utility of IM-MS for structural biology studies. Graphical Abstract.

Graphical abstract, The increasing appreciation for the crucial roles of RNAs in infectious and non-infectious human diseases makes them attractive therapeutic targets. Coding and non-coding RNAs frequently fold into complex conformations which, if effectively targeted, offer opportunities to therapeutically modulate numerous cellular processes, including those linked to undruggable protein targets. Despite the considerable skepticism as to whether RNAs can be targeted with small molecule therapeutics, overwhelming evidence suggests the challenges we are currently facing are not outside the realm of possibility. In this review, we highlight the most recent advances in molecular techniques that have sparked a revolution in understanding the RNA structure-to-function relationship. We bring attention to the application of these modern techniques to identify druggable RNA targets and to assess small molecule binding specificity. Finally, we discuss novel screening methodologies that support RNA drug discovery and present examples of therapeutically valuable RNA targets.

Regulation of complex biological networks has proven to be a key bottleneck in synthetic biology. Interactions between the structurally flexible RNA and various other molecules in the form of riboswitches have shown a high-regulation specificity and efficiency and synthetic riboswitches have filled the toolbox of devices in many synthetic biology applications. Here we report the development of a novel, small molecule binding RNA aptamer, whose binding is dependent on light-induced change of conformation of its small molecule ligand. As ligand we chose an azobenzene because of its reliable photoswitchability and modified it with chloramphenicol for a better interaction with RNA. The synthesis of the ligand ‘azoCm’ was followed by extensive biophysical analysis regarding its stability and photoswitchability. RNA aptamers were identified after several cycles of in vitro selection and then studied regarding their binding specificity and affinity toward the ligand. We show the successful development of an RNA aptamer that selectively binds to only the trans photoisomer of azoCm with a KD of 545 nM. As the aptamer cannot bind to the irradiated ligand (λ = 365 nm), a light-selective RNA binding system is provided. Further studies may now result in the engineering of a reliable, light-responsible riboswitch.

Aptamers are widely employed as recognition elements in small molecule biosensors due to their ability to recognize small molecule targets with high affinity and selectivity. Structure-switching aptamers are particularly promising for biosensing applications because target-induced conformational change can be directly linked to a functional output. However, traditional evolution methods do not select for the significant conformational change needed to create structure-switching biosensors. Modified selection methods have been described to select for structure-switching architectures, but these remain limited by the need for immobilization. Herein we describe the first homogenous, structure-switching aptamer selection that directly reports on biosensor capacity for the target. We exploit the activity of restriction enzymes to isolate aptamer candidates that undergo target-induced displacement of a short complementary strand. As an initial demonstration of the utility of this approach, we performed selection against kanamycin A. Four enriched candidate sequences were successfully characterized as structure-switching biosensors for detection of kanamycin A. Optimization of biosensor conditions afforded facile detection of kanamycin A (90 μM to 10 mM) with high selectivity over three other aminoglycosides. This research demonstrates a general method to directly select for structure-switching biosensors and can be applied to a broad range of small-molecule targets., RE-SELEX is the first homogenous method for in vitro evolution of structure-switching DNA aptamers.