Mehdi Mobli

Venomics: a new paradigm for natural products-based drug discovery

The remarkable potency and pharmacological diversity of animal venoms has made them an increasingly valuable source of lead molecules for drug and insecticide discovery. Nevertheless, most of the chemical diversity encoded within these venoms remains uncharacterized, despite decades of research, in part because of the small quantities of venom available. However, recent advances in the miniaturization of bioassays and improvements in the sensitivity of mass spectrometry and NMR spectroscopy have allowed unprecedented access to the molecular diversity of animal venoms. Here, we discuss these technological developments in the context of establishing a high-throughput pipeline for venoms-based drug discovery.

Macromolecular NMR spectroscopy for the non-spectroscopist

NMR spectroscopy is a powerful tool for studying the structure, function and dynamics of biological macromolecules. However, non‐spectroscopists often find NMR theory daunting and data interpretation nontrivial. As the first of two back‐to‐back reviews on NMR spectroscopy aimed at non‐spectroscopists, the present review first provides an introduction to the basics of macromolecular NMR spectroscopy, including a discussion of typical sample requirements and what information can be obtained from simple NMR experiments. We then review the use of NMR spectroscopy for determining the 3D structures of macromolecules and examine how to judge the quality of NMR‐derived structures.

Nonuniform sampling and non-Fourier signal processing methods in multidimensional NMR

Beginning with the introduction of Fourier Transform NMR by Ernst and Anderson in 1966, time domain measurement of the impulse response (the free induction decay, FID) consisted of sampling the signal at a series of discrete intervals. For compatibility with the discrete Fourier transform (DFT), the intervals are kept uniform, and the Nyquist theorem dictates the largest value of the interval sufficient to avoid aliasing. With the proposal by Jeener of parametric sampling along an indirect time dimension, extension to multidimensional experiments employed the same sampling techniques used in one dimension, similarly subject to the Nyquist condition and suitable for processing via the discrete Fourier transform. The challenges of obtaining high-resolution spectral estimates from short data records using the DFT were already well understood, however. Despite techniques such as linear prediction extrapolation, the achievable resolution in the indirect dimensions is limited by practical constraints on measuring time. The advent of non-Fourier methods of spectrum analysis capable of processing nonuniformly sampled data has led to an explosion in the development of novel sampling strategies that avoid the limits on resolution and measurement time imposed by uniform sampling. The first part of this review discusses the many approaches to data sampling in multidimensional NMR, the second part highlights commonly used methods for signal processing of such data, and the review concludes with a discussion of other approaches to speeding up data acquisition in NMR.

Production of Recombinant Disulfide-Rich Venom Peptides for Structural and Functional Analysis via Expression in the Periplasm of E. coli

Disulfide-rich peptides are the dominant component of most animal venoms. These peptides have received much attention as leads for the development of novel therapeutic agents and bioinsecticides because they target a wide range of neuronal receptors and ion channels with a high degree of potency and selectivity. In addition, their rigid disulfide framework makes them particularly well suited for addressing the crucial issue of in vivo stability. Structural and functional characterization of these peptides necessitates the development of a robust, reliable expression system that maintains their native disulfide framework. The bacterium Escherichia coli has long been used for economical production of recombinant proteins. However, the expression of functional disulfide-rich proteins in the reducing environment of the E. coli cytoplasm presents a significant challenge. Thus, we present here an optimised protocol for the expression of disulfide-rich venom peptides in the periplasm of E. coli, which is where the endogenous machinery for production of disulfide-bonds is located. The parameters that have been investigated include choice of media, induction conditions, lysis methods, methods of fusion protein and peptide purification, and sample preparation for NMR studies. After each section a recommendation is made for conditions to use. We demonstrate the use of this method for the production of venom peptides ranging in size from 2 to 8 kDa and containing 2–6 disulfide bonds.

Phox homology band 4.1/ezrin/radixin/moesin-like proteins function as molecular scaffolds that interact with cargo receptors and Ras GTPases

Following endocytosis, the fates of receptors, channels, and other transmembrane proteins are decided via specific endosomal sorting pathways, including recycling to the cell surface for continued activity. Two distinct phox-homology (PX)-domain-containing proteins, sorting nexin (SNX) 17 and SNX27, are critical regulators of recycling from endosomes to the cell surface. In this study we demonstrate that SNX17, SNX27, and SNX31 all possess a novel 4.1/ezrin/radixin/moesin (FERM)-like domain. SNX17 has been shown to bind to Asn-Pro-Xaa-Tyr (NPxY) sequences in the cytoplasmic tails of cargo such as LDL receptors and the amyloid precursor protein, and we find that both SNX17 and SNX27 display similar affinities for NPxY sorting motifs, suggesting conserved functions in endosomal recycling. Furthermore, we show for the first time that all three proteins are able to bind the Ras GTPase through their FERM-like domains. These interactions place the PX-FERM-like proteins at a hub of endosomal sorting and signaling processes. Studies of the SNX17 PX domain coupled with cellular localization experiments reveal the mechanistic basis for endosomal localization of the PX-FERM-like proteins, and structures of SNX17 and SNX27 determined by small angle X-ray scattering show that they adopt non-self-assembling, modular structures in solution. In summary, this work defines a novel family of proteins that participate in a network of interactions that will impact on both endosomal protein trafficking and compartment specific Ras signaling cascades.

The N–Terminal Tail of hERG Contains an Amphipathic α–Helix That Regulates Channel Deactivation

The cytoplasmic N–terminal domain of the human ether–a–go–go related gene (hERG) K+ channel is critical for the slow deactivation kinetics of the channel. However, the mechanism(s) by which the N–terminal domain regulates deactivation remains to be determined. Here we show that the solution NMR structure of the N–terminal 135 residues of hERG contains a previously described Per–Arnt–Sim (PAS) domain (residues 26–135) as well as an amphipathic α–helix (residues 13–23) and an initial unstructured segment (residues 2–9). Deletion of residues 2–25, only the unstructured segment (residues 2–9) or replacement of the α–helix with a flexible linker all result in enhanced rates of deactivation. Thus, both the initial flexible segment and the α–helix are required but neither is sufficient to confer slow deactivation kinetics. Alanine scanning mutagenesis identified R5 and G6 in the initial flexible segment as critical for slow deactivation. Alanine mutants in the helical region had less dramatic phenotypes. We propose that the PAS domain is bound close to the central core of the channel and that the N–terminal α–helix ensures that the flexible tail is correctly orientated for interaction with the activation gating machinery to stabilize the open state of the channel.

A Dynamic Pharmacophore Drives the Interaction between Psalmotoxin-1 and the Putative Drug Target Acid-Sensing Ion Channel 1a

Acid-sensing ion channel 1a (ASIC1a) is a primary acid sensor in the peripheral and central nervous system. It has been implicated as a novel therapeutic target for a broad range of pathophysiological conditions including pain, ischemic stroke, depression, and autoimmune diseases such as multiple sclerosis. The only known selective blocker of ASIC1a is π-TRTX-Pc1a (PcTx1), a disulfide-rich 40-residue peptide isolated from spider venom. π-TRTX-Pc1a is an effective analgesic in rodent models of acute pain and it provides neuroprotection in a mouse model of ischemic stroke. Thus, understanding the molecular basis of the π-TRTX-Pc1a–ASIC1a interaction should facilitate development of therapeutically useful ASIC1a blockers. We therefore developed an efficient bacterial expression system to produce a panel of π-TRTX-Pc1a mutants for probing structure-activity relationships as well as isotopically labeled toxin for determination of its solution structure and dynamics. We demonstrate that the toxin pharmacophore resides in a β-hairpin loop that was revealed to be mobile over a wide range of time scales using molecular dynamics simulations in combination with NMR spin relaxation and relaxation dispersion measurements. The toxin-receptor interaction was modeled by in silico docking of the toxin structure onto a homology model of rat ASIC1a in a restraints-driven approach that was designed to take account of the dynamics of the toxin pharmacophore and the consequent remodeling of side-chain conformations upon receptor binding. The resulting model reveals new insights into the mechanism of action of π-TRTX-Pc1a and provides an experimentally validated template for the rational design of therapeutically useful π-TRTX-Pc1a mimetics.

Selenoether oxytocin analogues have analgesic properties in a mouse model of chronic abdominal pain

Poor oral availability and susceptibility to reduction and protease degradation is a major hurdle in peptide drug development. However, drugable receptors in the gut present an attractive niche for peptide therapeutics. Here we demonstrate, in a mouse model of chronic abdominal pain, that oxytocin receptors are significantly upregulated in nociceptors innervating the colon. Correspondingly, we develop chemical strategies to engineer non-reducible and therefore more stable oxytocin analogues. Chemoselective selenide macrocyclization yields stabilized analogues equipotent to native oxytocin. Ultra-high-field nuclear magnetic resonance structural analysis of native oxytocin and the seleno-oxytocin derivatives reveals that oxytocin has a pre-organized structure in solution, in marked contrast to earlier X-ray crystallography studies. Finally, we show that these seleno-oxytocin analogues potently inhibit colonic nociceptors both in vitro and in vivo in mice with chronic visceral hypersensitivity. Our findings have potentially important implications for clinical use of oxytocin analogues and disulphide-rich peptides in general.

An automated tool for maximum entropy reconstruction of biomolecular NMR spectra

calculations are computationally costly (that is, efficiency is low). Modern large-scale ∆∆G prediction methods use heuristic algorithms with effective force fields and empirical parameters to estimate the stability changes caused by mutations in agreement with experimental data2–5. There are, however, two considerable drawbacks pertinent to the heuristic methods. First, most of these prediction methods rely on parameter training using available experimental ∆∆G data. Such training is usually biased toward mutations that feature large-to-small residue substitutions, such as alanine-scanning experiments (that is, poor transferability). Second, protein backbone flexibility, which is crucial for resolving atomic clashes and backbone strains in mutant proteins, is not considered in these methods, thereby reducing accuracy and limiting the application of heuristic methods (that is, limited applicability). To address the issues of efficiency, transferability and applicability, we developed the Eris method, which uses a physical force field with atomic modeling as well as fast side-chain packing and backbone relaxation algorithms. The free energy is expressed as a weighted sum of van der Waals forces, solvation, hydrogen bonding and backbone-dependent statistical energies6 (Supplementary Methods online). The weighting parameters are independently trained to recapitulate the native amino acid sequences for 34 proteins using high-resolution X-ray structures6. Additionally, an integral step of Eris is backbone relaxation when severe atom clashes or backbone strains are detected during calculation. We tested Eris on 595 mutants from five proteins, for which the ∆∆G values were documented (Fig. 1a). We found significant agreement between the predicted and measured ∆∆G values with a correlation coefficient of 0.75 (P = 2 × 10−108). The correlation between the predictions and experiments is comparable to that reported using other methods2–5. Unlike previous methods, Eris also has high predictive power for small-to-large3 sidechain-size mutations (Fig. 1b,c), owing to its ability to effectively relax backbone structures and resolve clashes introduced by mutations. As a direct comparison with other methods, we computed the stability changes of the small-to-large mutations using Eris and other web-based stability prediction servers. We found that Eris outperformed other available servers (Supplementary Discussion and Supplementary Tables 1 and 2 online). Additionally, Eris features a protein structure pre-relaxation option, which remarkably improves the prediction accuracy when a highresolution protein structure is not available (Supplementary Discussion and Supplementary Fig. 1 online). Our test validates the unbiased force field, side-chain packing and backbone relaxation algorithms in Eris. We anticipate Eris will be applicable to examining a much larger variety of mutations during protein engineering. We built a web-based Eris server for ∆∆G estimation. The server is freely accessible online (http:// eris.dokhlab.org).

Nonuniform Sampling and Maximum Entropy Reconstruction in Multidimensional NMR

NMR spectroscopy is one of the most powerful and versatile analytic tools available to chemists. The discrete Fourier transform (DFT) played a seminal role in the development of modern NMR, including the multidimensional methods that are essential for characterizing complex biomolecules. However, it suffers from well-known limitations: chiefly the difficulty in obtaining high-resolution spectral estimates from short data records. Because the time required to perform an experiment is proportional to the number of data samples, this problem imposes a sampling burden for multidimensional NMR experiments. At high magnetic field, where spectral dispersion is greatest, the problem becomes particularly acute. Consequently multidimensional NMR experiments that rely on the DFT must either sacrifice resolution in order to be completed in reasonable time or use inordinate amounts of time to achieve the potential resolution afforded by high-field magnets. Maximum entropy (MaxEnt) reconstruction is a non-Fourier method of spectrum analysis that can provide high-resolution spectral estimates from short data records. It can also be used with nonuniformly sampled data sets. Since resolution is substantially determined by the largest evolution time sampled, nonuniform sampling enables high resolution while avoiding the need to uniformly sample at large numbers of evolution times. The Nyquist sampling theorem does not apply to nonuniformly sampled data, and artifacts that occur with the use of nonuniform sampling can be viewed as frequency-aliased signals. Strategies for suppressing nonuniform sampling artifacts include the careful design of the sampling scheme and special methods for computing the spectrum. Researchers now routinely report that they can complete an N-dimensional NMR experiment 3(N-1) times faster (a 3D experiment in one ninth of the time). As a result, high-resolution three- and four-dimensional experiments that were prohibitively time consuming are now practical. Conversely, tailored sampling in the indirect dimensions has led to improved sensitivity. Further advances in nonuniform sampling strategies could enable further reductions in sampling requirements for high resolution NMR spectra, and the combination of these strategies with robust non-Fourier methods of spectrum analysis (such as MaxEnt) represent a profound change in the way researchers conduct multidimensional experiments. The potential benefits will enable more advanced applications of multidimensional NMR spectroscopy to study biological macromolecules, metabolomics, natural products, dynamic systems, and other areas where resolution, sensitivity, or experiment time are limiting. Just as the development of multidimensional NMR methods presaged multidimensional methods in other areas of spectroscopy, we anticipate that nonuniform sampling approaches will find applications in other forms of spectroscopy.