Protocol to use TopNet for gene regulatory network modeling using gene expression data from perturbation experiments.

Inference of gene regulatory networks from gene perturbation experiments is the most reliable approach for investigating interdependence between genes. Here, we describe the initial gene perturbations, expression measurements, and preparation steps, followed by network modeling using TopNet. Summarization and visualization of the estimated networks and optional genetic testing of dependencies revealed by the network model are demonstrated. While developed for gene perturbation experiments, TopNet models data in which nodes are both perturbed and measured. For complete details on the use and execution of this protocol, please refer to McMurray et al. (2021).

Gene network modeling via TopNet reveals functional dependencies between diverse tumor-critical mediator genes.

Malignant cell transformation and the underlying reprogramming of gene expression require the cooperation of multiple oncogenic mutations. This cooperation is reflected in the synergistic regulation of non-mutant downstream genes, so-called cooperation response genes (CRGs). CRGs affect diverse hallmark features of cancer cells and are not known to be functionally connected. However, they act as critical mediators of the cancer phenotype at an unexpectedly high frequency >50%, as indicated by genetic perturbations. Here, we demonstrate that CRGs function within a network of strong genetic interdependencies that are critical to the malignant state. Our network modeling methodology, TopNet, takes the approach of incorporating uncertainty in the underlying gene perturbation data and can identify non-linear gene interactions. In the dense space of gene connectivity, TopNet reveals a sparse topological gene network architecture, effectively pinpointing functionally relevant gene interactions. Thus, among diverse potential applications, TopNet has utility for identification of non-mutant targets for cancer intervention.

Quantum Dots for Improved Single-Molecule Localization Microscopy.

Colloidal semiconductor quantum dots (QDs) have long established their versatility and utility for the visualization of biological interactions. On the single-particle level, QDs have demonstrated superior photophysical properties compared to organic dye molecules or fluorescent proteins, but it remains an open question as to which of these fundamental characteristics are most significant with respect to the performance of QDs for imaging beyond the diffraction limit. Here, we demonstrate significant enhancement in achievable localization precision in QD-labeled neurons compared to neurons labeled with an organic fluorophore. Additionally, we identify key photophysical parameters of QDs responsible for this enhancement and compare these parameters to reported values for commonly used fluorophores for super-resolution imaging.

Antigenic cartography of H1N1 influenza viruses using sequence-based antigenic distance calculation.

BACKGROUND: The ease at which influenza virus sequence data can be used to estimate antigenic relationships between strains and the existence of databases containing sequence data for hundreds of thousands influenza strains make sequence-based antigenic distance estimates an attractive approach to researchers. Antigenic mismatch between circulating strains and vaccine strains results in significantly decreased vaccine effectiveness. Furthermore, antigenic relatedness between the vaccine strain and the strains an individual was originally primed with can affect the cross-reactivity of the antibody response. Thus, understanding the antigenic relationships between influenza viruses that have circulated is important to both vaccinologists and immunologists. RESULTS: Here we develop a method of mapping antigenic relationships between influenza virus stains using a sequence-based antigenic distance approach (SBM). We used a modified version of the p-all-epitope sequence-based antigenic distance calculation, which determines the antigenic relatedness between strains using influenza hemagglutinin (HA) genetic coding sequence data and provide experimental validation of the p-all-epitope calculation. We calculated the antigenic distance between 4838 H1N1 viruses isolated from infected humans between 1918 and 2016. We demonstrate, for the first time, that sequence-based antigenic distances of H1N1 Influenza viruses can be accurately represented in 2-dimenstional antigenic cartography using classic multidimensional scaling. Additionally, the model correctly predicted decreases in cross-reactive antibody levels with 87% accuracy and was highly reproducible with even when small numbers of sequences were used. CONCLUSION: This work provides a highly accurate and precise bioinformatics tool that can be used to assess immune risk as well as design optimized vaccination strategies. SBM accurately estimated the antigenic relationship between strains using HA sequence data. Antigenic maps of H1N1 virus strains reveal that strains cluster antigenically similar to what has been reported for H3N2 viruses. Furthermore, we demonstrated that genetic variation differs across antigenic sites and discuss the implications.

Revised RNA Dihedral Parameters for the Amber Force Field Improve RNA Molecular Dynamics.

The backbone dihedral parameters of the Amber RNA force field were improved by fitting using multiple linear regression to potential energies determined by quantum chemistry calculations. Five backbone and four glycosidic dihedral parameters were fit simultaneously to reproduce the potential energies determined by a high-level density functional theory calculation (B97D3 functional with the AUG-CC-PVTZ basis set). Umbrella sampling was used to determine conformational free energies along the dihedral angles, and these better agree with the population of conformations observed in the protein data bank for the new parameters than for the conventional parameters. Molecular dynamics simulations performed on a set of hairpin loops, duplexes and tetramers with the new parameter set show improved modeling for the structures of tetramers CCCC, CAAU, and GACC, and an RNA internal loop of noncanonical pairs, as compared to the conventional parameters. For the tetramers, the new parameters largely avoid the incorrect intercalated structures that dominate the conformational samples from the conventional parameters. For the internal loop, the major conformation solved by NMR is stable with the new parameters, but not with the conventional parameters. The new force field performs similarly to the conventional parameters for the UUCG and GCAA hairpin loops and the [U(UA)6A]2 duplex.

The influence of continuous vs. pulsed laser excitation on single quantum dot photophysics.

The impact of pulsed versus continuous wave (cw) laser excitation on the photophysical properties of single quantum dots (QDs) has been investigated in an experiment in which all macroscopic variables are identical except the nature of laser excitation. Pulsed excitation exaggerates the effects of photobleaching, results in a lower probability of long ON fluorescence blinking events, and leads to shorter fluorescence lifetimes with respect to cw excitation at the same wavelength and average intensity. Spectral wandering, biexciton quantum yields, and power law exponents that describe fluorescence blinking are largely insensitive to the nature of laser excitation. These results explicitly illustrate important similarities and differences in fluorescence dynamics between pulsed and cw excitation, enabling more meaningful comparisons between literature reports and aiding in the design of new experiments to mitigate possible influences of high photon flux on QDs.

Accelerating calculations of RNA secondary structure partition functions using GPUs.

BACKGROUND: RNA performs many diverse functions in the cell in addition to its role as a messenger of genetic information. These functions depend on its ability to fold to a unique three-dimensional structure determined by the sequence. The conformation of RNA is in part determined by its secondary structure, or the particular set of contacts between pairs of complementary bases. Prediction of the secondary structure of RNA from its sequence is therefore of great interest, but can be computationally expensive. In this work we accelerate computations of base-pair probababilities using parallel graphics processing units (GPUs). RESULTS: Calculation of the probabilities of base pairs in RNA secondary structures using nearest-neighbor standard free energy change parameters has been implemented using CUDA to run on hardware with multiprocessor GPUs. A modified set of recursions was introduced, which reduces memory usage by about 25%. GPUs are fastest in single precision, and for some hardware, restricted to single precision. This may introduce significant roundoff error. However, deviations in base-pair probabilities calculated using single precision were found to be negligible compared to those resulting from shifting the nearest-neighbor parameters by a random amount of magnitude similar to their experimental uncertainties. For large sequences running on our particular hardware, the GPU implementation reduces execution time by a factor of close to 60 compared with an optimized serial implementation, and by a factor of 116 compared with the original code. CONCLUSIONS: Using GPUs can greatly accelerate computation of RNA secondary structure partition functions, allowing calculation of base-pair probabilities for large sequences in a reasonable amount of time, with a negligible compromise in accuracy due to working in single precision. The source code is integrated into the RNAstructure software package and available for download at http://rna.urmc.rochester.edu.

Single-Molecule Analysis of Cytochrome c Folding by Monitoring the Lifetime of an Attached Fluorescent Probe.

Conformational dynamics of proteins are important for function. However, obtaining information about specific conformations is difficult for samples displaying heterogeneity. Here, time-resolved fluorescence resonance energy transfer is used to characterize the folding of single cytochrome c molecules. In particular, measurements of the fluorescence lifetimes of individual cytochrome c molecules labeled with a single dye that is quenched by energy transfer to the heme were used to monitor conformational transitions of the protein under partially denaturing conditions. These studies indicate significantly more conformational heterogeneity than has been described previously. Importantly, the use of a purified singly-labeled sample made a direct comparison to ensemble data possible. The distribution of lifetimes of single-proteins was compared to the distribution of lifetimes determined from analysis of ensemble lifetime fluorescence data. The results show broad agreement between single-molecule and ensemble data, with a similar range of lifetimes. However, the single-molecule data reveal greater conformational heterogeneity.

Gold (III) Chloride-Catalyzed 6-endo-trig Oxa-Michael Addition Reactions for Diastereoselective Synthesis of Fused Tetrahydropyranones.

Alkynones were treated with boron trifluoride diethyl etherate to generate ß-iodoallenolates, which underwent intramolecular aldol reactions to produce cycloalkenyl alcohols. Diastereoselective oxa-Michael ring closure could then be induced by treatment with a catalytic amount of gold(III) chloride, affording highly functionalized tetrahydropyran-containing ring systems.

Controlled oxidation of remote sp3 C-H bonds in artemisinin via P450 catalysts with fine-tuned regio- and stereoselectivity.

The selective oxyfunctionalization of isolated sp(3) C-H bonds in complex molecules represents a formidable challenge in organic chemistry. Here, we describe a rational, systematic strategy to expedite the development of P450 oxidation catalysts with refined regio- and stereoselectivity for the hydroxylation of remote, unactivated C-H sites in a complex scaffold. Using artemisinin as model substrate, we demonstrate how a three-tier strategy involving first-sphere active site mutagenesis, high-throughput P450 fingerprinting, and fingerprint-driven P450 reactivity predictions enabled the rapid evolution of three efficient biocatalysts for the selective hydroxylation of a primary and a secondary C-H site (with both S and R stereoselectivity) in a relevant yet previously inaccessible region of this complex natural product. The evolved P450 variants could be applied to provide direct access to the desired hydroxylated derivatives at preparative scales (0.4 g) and in high isolated yields (>90%), thereby enabling further elaboration of this molecule. As an example, enantiopure C7-fluorinated derivatives of the clinical antimalarial drugs artesunate and artemether, in which a major metabolically sensitive site is protected by means of a C-H to C-F substitution, were afforded via P450-mediated chemoenzymatic synthesis.

Revision of AMBER Torsional Parameters for RNA Improves Free Energy Predictions for Tetramer Duplexes with GC and iGiC Base Pairs.

All-atom force fields are important for predicting thermodynamic, structural, and dynamic properties of RNA. In this paper, results are reported for thermodynamic integration calculations of free energy differences of duplex formation when CG pairs in the RNA duplexes r(CCGG)(2), r(GGCC)(2), r(GCGC)(2), and r(CGCG)(2) are replaced by isocytidine-isoguanosine (iCiG) pairs. Agreement with experiment was improved when ε/ζ, α/γ, ß, and χ torsional parameters in the AMBER99 force field were revised on the basis of quantum mechanical calculations. The revised force field, AMBER99TOR, brings free energy difference predictions to within 1.3, 1.4, 2.3, and 2.6 kcal/mol at 300 K, respectively, compared to experimental results for the thermodynamic cycles of CCGG → iCiCiGiG, GGCC → iGiGiCiC, GCGC → iGiCiGiC, and CGCG → iCiGiCiG. In contrast, unmodified AMBER99 predictions for GGCC → iGiGiCiC and GCGC → iGiCiGiC differ from experiment by 11.7 and 12.6 kcal/mol, respectively. In order to test the dynamic stability of the above duplexes with AMBER99TOR, four individual 50 ns molecular dynamics (MD) simulations in explicit solvent were run. All except r(CCGG)(2) retained A-form conformation for ≥82% of the time. This is consistent with NMR spectra of r(iGiGiCiC)(2), which reveal an A-form conformation. In MD simulations, r(CCGG)(2) retained A-form conformation 52% of the time, suggesting that its terminal base pairs may fray. The results indicate that revised backbone parameters improve predictions of RNA properties and that comparisons to measured sequence dependent thermodynamics provide useful benchmarks for testing force fields and computational methods.

Benchmarking AMBER force fields for RNA: comparisons to NMR spectra for single-stranded r(GACC) are improved by revised χ torsions.

Accurately modeling unpaired regions of RNA is important for predicting structure, dynamics, and thermodynamics of folded RNA. Comparisons between NMR data and molecular dynamics simulations provide a test of force fields used for modeling. Here, NMR spectroscopy, including NOESY, (1)H-(31)P HETCOR, DQF-COSY, and TOCSY, was used to determine conformational preferences for single-stranded GACC RNA. The spectra are consistent with a conformational ensemble containing major and minor A-form-like structures. In a series of 50 ns molecular dynamics (MD) simulations with the AMBER99 force field in explicit solvent, initial A-form-like structures rapidly evolve to disordered conformations. A set of 50 ns simulations with revised χ torsions (AMBER99χ force field) gives two primary conformations, consistent with the NMR spectra. A single 1.9 µs MD simulation with the AMBER99χ force field showed that the major and minor conformations are retained for almost 68% of the time in the first 700 ns, with multiple transformations from A-form to non-A-form conformations. For the rest of the simulation, random-coil structures and a stable non-A-form conformation inconsistent with NMR spectra were seen. Evidently, the AMBER99χ force field improves structural predictions for single-stranded GACC RNA compared to the AMBER99 force field, but further force field improvements are needed.

Conformational flexibility and binding interactions of the G protein ßγ heterodimer.

Previous NMR experiments on unbound G protein ßγ heterodimer suggested that particular residues in the binding interface are mobile on the nanosecond timescale. In this work we performed nanosecond-timescale molecular dynamics simulations to investigate conformational changes and dynamics of Gßγ in the presence of several binding partners: a high-affinity peptide (SIGK), phosducin, and the GDP-bound α subunit. In these simulations, the high mobility of GßW99 was reduced by SIGK, and it appeared that a tyrosine might stabilize GßW99 by hydrophobic or aromatic stacking interactions in addition to hydrogen bonds. Simulations of the phosducin-Gßγ complex showed that the mobility of GßW99 was restricted, consistent with inferences from NMR. However, large-scale conformational changes of Gßγ due to binding, which were hypothesized in the NMR study, were not observed in the simulations, most likely due to their short (nanosecond) duration. A pocket consisting of hydrophobic amino acids on Gα appears to restrict GßW99 mobility in the crystal structure of the Gαßγ? heterotrimer. The simulation trajectories are consistent with this idea. However, local conformational changes of residues GßW63, GßW211, GßW297, GßW332, and GßW339 were detected during the MD simulations. As expected, the magnitude of atomic fluctuations observed in simulations was greater for α than for the ßγ subunits, suggesting that α has greater flexibility. These observations support the notion that to maintain the high mobility of GßW99 observed by solution NMR requires that the Gß-α interface must open up on time scale longer than can be observed in nanosecond scale simulations.

Estimating binding affinities by docking/scoring methods using variable protonation states.

To investigate the effects of multiple protonation states on protein-ligand recognition, we generated alternative protonation states for selected titratable groups of ligands and receptors. The selection of states was based on the predicted pK(a) of the unbound receptor and ligand and the proximity of titratable groups of the receptor to the binding site. Various ligand tautomer states were also considered. An independent docking calculation was run for each state. Several protocols were examined: using an ensemble of all generated states of ligand and receptor, using only the most probable state of the unbound ligand/receptor, and using only the state giving the most favorable docking score. The accuracies of these approaches were compared, using a set of 176 protein-ligand complexes (15 receptors) for which crystal structures and measured binding affinities are available. The best agreement with experiment was obtained when ligand poses from experimental crystal structures were used. For 9 of 15 receptors, using an ensemble of all generated protonation states of the ligand and receptor gave the best correlation between calculated and measured affinities.

Geometric restraint drives on- and off-pathway catalysis by the Escherichia coli menaquinol:fumarate reductase.

Complex II superfamily members catalyze the kinetically difficult interconversion of succinate and fumarate. Due to the relative simplicity of complex II substrates and their similarity to other biologically abundant small molecules, substrate specificity presents a challenge in this system. In order to identify determinants for on-pathway catalysis, off-pathway catalysis, and enzyme inhibition, crystal structures of Escherichia coli menaquinol:fumarate reductase (QFR), a complex II superfamily member, were determined bound to the substrate, fumarate, and the inhibitors oxaloacetate, glutarate, and 3-nitropropionate. Optical difference spectroscopy and computational modeling support a model where QFR twists the dicarboxylate, activating it for catalysis. Orientation of the C2-C3 double bond of activated fumarate parallel to the C(4a)-N5 bond of FAD allows orbital overlap between the substrate and the cofactor, priming the substrate for nucleophilic attack. Off-pathway catalysis, such as the conversion of malate to oxaloacetate or the activation of the toxin 3-nitropropionate may occur when inhibitors bind with a similarly activated bond in the same position. Conversely, inhibitors that do not orient an activatable bond in this manner, such as glutarate and citrate, are excluded from catalysis and act as inhibitors of substrate binding. These results support a model where electronic interactions via geometric constraint and orbital steering underlie catalysis by QFR.

Reparameterization of RNA chi Torsion Parameters for the AMBER Force Field and Comparison to NMR Spectra for Cytidine and Uridine.

A reparameterization of the torsional parameters for the glycosidic dihedral angle, chi, for the AMBER99 force field in RNA nucleosides is used to provide a modified force field, AMBER99chi. Molecular dynamics simulations of cytidine, uridine, adenosine, and guanosine in aqueous solution using the AMBER99 and AMBER99chi force fields are compared with NMR results. For each nucleoside and force field, 10 individual molecular dynamics simulations of 30 ns each were run. For cytidine with AMBER99chi force field, each molecular dynamics simulation time was extended to 120 ns for convergence purposes. Nuclear magnetic resonance (NMR) spectroscopy, including one-dimensional (1D) (1)H, steady-state 1D (1)H nuclear Overhauser effect (NOE), and transient 1D (1)H NOE, was used to determine the sugar puckering and preferred base orientation with respect to the ribose of cytidine and uridine. The AMBER99 force field overestimates the population of syn conformations of the base orientation and of C2'-endo sugar puckering of the pyrimidines, while the AMBER99chi force field's predictions are more consistent with NMR results. Moreover, the AMBER99 force field prefers high anti conformations with glycosidic dihedral angles around 310 degrees for the base orientation of purines. The AMBER99chi force field prefers anti conformations around 185 degrees , which is more consistent with the quantum mechanical calculations and known 3D structures of folded ribonucleic acids (RNAs). Evidently, the AMBER99chi force field predicts the structural characteristics of ribonucleosides better than the AMBER99 force field and should improve structural and thermodynamic predictions of RNA structures.

Accounting for ligand conformational restriction in calculations of protein-ligand binding affinities.

The conformation adopted by a ligand on binding to a receptor may differ from its lowest-energy conformation in solution. In addition, the bound ligand is more conformationally restricted, which is associated with a configurational entropy loss. The free energy change due to these effects is often neglected or treated crudely in current models for predicting binding affinity. We present a method for estimating this contribution, based on perturbation theory using the quasi-harmonic model of Karplus and Kushick as a reference system. The consistency of the method is checked for small model systems. Subsequently we use the method, along with an estimate for the enthalpic contribution due to ligand-receptor interactions, to calculate relative binding affinities. The AMBER force field and generalized Born implicit solvent model is used. Binding affinities were estimated for a test set of 233 protein-ligand complexes for which crystal structures and measured binding affinities are available. In most cases, the ligand conformation in the bound state was significantly different from the most favorable conformation in solution. In general, the correlation between measured and calculated ligand binding affinities including the free energy change due to ligand conformational change is comparable to or slightly better than that obtained by using an empirically-trained docking score. Both entropic and enthalpic contributions to this free energy change are significant.

NMR analysis of G-protein betagamma subunit complexes reveals a dynamic G(alpha)-Gbetagamma subunit interface and multiple protein recognition modes.

G-protein betagamma (Gbetagamma) subunits interact with a wide range of molecular partners including: G(alpha) subunits, effectors, peptides, and small molecule inhibitors. The molecular mechanisms underlying the ability to accommodate this wide range of structurally distinct binding partners are not well understood. To uncover the role of protein flexibility and alterations in protein conformation in molecular recognition by Gbetagamma, a method for site-specific (15)N-labeling of Gbeta-Trp residue backbone and indole amines in insect cells was developed. Transverse Relaxation Optimized Spectroscopy-Heteronuclear Single-Quantum Coherence Nuclear Magnetic Resonance (TROSY-HSQC NMR) analysis of (15)N-Trp Gbetagamma identified well-dispersed signals for the individual Trp residue side chain and amide positions. Surprisingly, a wide range of signal intensities was observed in the spectrum, likely representing a range of backbone and side chain mobilities. The signal for GbetaW99 indole was very intense, suggesting a high level of mobility on the protein surface and molecular dynamics simulations indicate that GbetaW99 is highly mobile on the nanosecond timescale in comparison with other Gbeta tryptophans. Binding of peptides and phosducin dramatically altered the mobility of GbetaW99 and GbetaW332 in the binding site and the chemical shifts at sites distant from the direct binding surface in distinct ways. In contrast, binding of G(alpha)(i1)-GDP to Gbetagamma had relatively little effect on the spectrum and, most surprisingly, did not significantly alter Trp mobility at the subunit interface. This suggests the inactive heterotrimer in solution adopts a conformation with an open subunit interface a large percentage of the time. Overall, these data show that Gbetagamma subunits explore a range of conformations that can be exploited during molecular recognition by diverse binding partners.

Evaluating docking methods for prediction of binding affinities of small molecules to the G protein betagamma subunits.

Several studies have suggested that disrupting interactions of the G protein betagamma subunits with downstream binding partners might be a valuable study for pharmaceutical development. Recently, small molecules have been found which bind to Gbetagamma with high apparent affinity in an enzyme-linked immunosorbent assay (ELISA), have demonstrated selective inhibition of interactions of Gbetagamma with downstream signaling partners, and have been shown to increase antinociceptive effects of morphine and inhibit inflammation in vivo. In this paper we examine several docking and scoring protocols for estimating binding affinities for a set of 830 ligands from the NCI diversity set to the Gbeta1gamma2 subunit and compared these with IC50s measured in a competition ELISA with a high-affinity peptidic ligand. The best-performing docking protocol used a consensus score and ensemble docking and resulted in a 6-fold enrichment of high-affinity compounds in the top-ranked 5% of the ligand data set.

Effects of Restrained Sampling Space and Nonplanar Amino Groups on Free-Energy Predictions for RNA with Imino and Sheared Tandem GA Base Pairs Flanked by GC, CG, iGiC or iCiG Base Pairs.

Guanine-adenine (GA) base pairs play important roles in determining the structure, dynamics, and stability of RNA. In RNA internal loops, GA base pairs often occur in tandem arrangements and their structure is context and sequence dependent. Calculations reported here test the thermodynamic integration (TI) approach with the amber99 force field by comparing computational predictions of free energy differences with the free energy differences expected on the basis of NMR determined structures of the RNA motifs (5'-GCGGACGC-3')(2), (5'-GCiGGAiCGC-3')(2), (5'-GGCGAGCC-3')(2), and (5'-GGiCGAiGCC-3')(2). Here, iG and iC denote isoguanosine and isocytidine, which have amino and carbonyl groups transposed relative to guanosine and cytidine. The NMR structures show that the GA base pairs adopt either imino (cis Watson-Crick/Watson-Crick A-G) or sheared (trans Hoogsteen/Sugar edge A-G) conformations depending on the identity and orientation of the adjacent base pair. A new mixing function for the TI method is developed that allows alchemical transitions in which atoms can disappear in both the initial and final states. Unrestrained calculations gave DeltaG degrees values 2-4 kcal/mol different from expectations based on NMR data. Restraining the structures with hydrogen bond restraints did not improve the predictions. Agreement with NMR data was improved by 0.7 to 1.5 kcal/mol, however, when structures were restrained with weak positional restraints to sample around the experimentally determined NMR structures. The amber99 force field was modified to partially include pyramidalization effects of the unpaired amino group of guanosine in imino GA base pairs. This provided little or no improvement in comparisons with experiment. The marginal improvement is observed when the structure has potential cross-strand out-of-plane hydrogen bonding with the G amino group. The calculations using positional restraints and a nonplanar amino group reproduce the signs of DeltaG degrees from the experimental results and are, thus, capable of providing useful qualitative insights complementing the NMR experiments. Decomposition of the terms in the calculations reveals that the dominant terms are from electrostatic and interstrand interactions other than hydrogen bonds in the base pairs. The results suggest that a better description of the backbone is key to reproducing the experimental free energy results with computational free energy predictions.