Glutamate binding triggers monomerization of unliganded mGluR2 dimers.

The Metabotropic glutamate receptor 2 (mGluR2) is involved in several neurological and psychiatric disorders and is an attractive drug target. It is believed to form a strict dimer and the dimeric assembly is necessary for glutamate induced activation. Although many studies have focused on glutamate induced conformational changes, the dimerization propensity of mGluR2 with and without glutamate has never been investigated. Also, the role of the unstructured loop in dimerization of mGluR2 is not clear. Here, using Forster Resonance Energy Transfer (FRET) based assay in live cells we show that mGluR2 does not form a "strict dimer" rather it exists in a dynamic monomer-dimer equilibrium. The unstructured loop moderately destabilizes the dimers. Furthermore, binding of glutamate to mGluR2 induces conformational change that promotes monomerization of mGluR2. In the absence of an unstructured loop, mGluR2 neither undergoes conformational change nor monomerizes upon binding to glutamate.

Unstructured loop is essential for the activation of mGluR2.

Metabotropic Glutamate Receptors (mGluRs) are Class C G-protein coupled receptors (GPCRs) that are expressed throughout the central nervous system and are involved in several neurological and psychiatric disorders. Although, many studies focused on Glutamate induced activation of mGluR2, however, the role of unstructured loop (or "BC loop") in activation of metabotropic Glutamate receptors is currently unknown. Here, using Förster Resonance Energy Transfer (FRET) based assay in live cells we show that unstructured loop is required for Glutamate induced conformation and hence the activation of the receptor.

Assessment of Solvated Interaction Energy Function for Ranking Antibody-Antigen Binding Affinities.

Affinity modulation of antibodies and antibody fragments of therapeutic value is often required in order to improve their clinical efficacies. Virtual affinity maturation has the potential to quickly focus on the critical hotspot residues without the combinatorial explosion problem of conventional display and library approaches. However, this requires a binding affinity scoring function that is capable of ranking single-point mutations of a starting antibody. We focus here on assessing the solvated interaction energy (SIE) function that was originally developed for and is widely applied to scoring of protein-ligand binding affinities. To this end, we assembled a structure-function data set called Single-Point Mutant Antibody Binding (SiPMAB) comprising several antibody-antigen systems suitable for this assessment, i.e., based on high-resolution crystal structures for the parent antibodies and coupled with high-quality binding affinity measurements for sets of single-point antibody mutants in each system. Using this data set, we tested the SIE function with several mutation protocols based on the popular methods SCWRL, Rosetta, and FoldX. We found that the SIE function coupled with a protocol limited to sampling only the mutated side chain can reasonably predict relative binding affinities with a Spearman rank-order correlation coefficient of about 0.6, outperforming more aggressive sampling protocols. Importantly, this performance is maintained for each of the seven system-specific component subsets as well as for other relevant subsets including non-alanine and charge-altering mutations. The transferability and enrichment in affinity-improving mutants can be further enhanced using consensus ranking over multiple methods, including the SIE, Talaris, and FOLDEF energy functions. The knowledge gained from this study can lead to successful prospective applications of virtual affinity maturation.

Investigation of Changes in Tetracycline Repressor Binding upon Mutations in the Tetracycline Operator.

The tetracycline operon is an important gene network component, commonly used in synthetic biology applications because of its switch-like character. At the heart of this system is the highly specific interaction of the tet repressor protein (TetR) with its cognate DNA sequence (tetO). TetR binding on tetO practically stops expression of genes downstream of tetO by excluding RNA polymerase from binding the promoter and initiating transcription. Mutating the tetO sequence alters the strength of TetR-tetO binding and thus provides a tool to synthetic biologists to manipulate gene expression levels. We employ molecular dynamics (MD) simulations coupled with the free energy perturbation method to investigate the binding affinity of TetR to different tetO mutants. We also carry out in vivo tests in Escherichia coli for a series of promoters based on these mutants. We obtain reasonable agreement between experimental green fluorescent protein (GFP) repression levels and binding free energy differences computed from molecular simulations. In all cases, the wild-type tetO sequence yields the strongest TetR binding, which is observed both experimentally, in terms of GFP levels, and in simulation, in terms of free energy changes. Two of the four tetO mutants we tested yield relatively strong binding, whereas the other two mutants tend to be significantly weaker. The clustering and relative ranking of this subset of tetO mutants is generally consistent between our own experimental data, previous experiments with different systems and the free energy changes computed from our simulations. Overall, this work offers insights into an important synthetic biological system and demonstrates the potential, as well as limitations of molecular simulations to quantitatively explain biologically relevant behavior.

Multiscale models of the antimicrobial peptide protegrin-1 on gram-negative bacteria membranes.

Antimicrobial peptides (AMPs) are naturally-occurring molecules that exhibit strong antibiotic properties against numerous infectious bacterial strains. Because of their unique mechanism of action, they have been touted as a potential source for novel antibiotic drugs. We present a summary of computational investigations in our lab aimed at understanding this unique mechanism of action, in particular the development of models that provide a quantitative connection between molecular-level biophysical phenomena and relevant biological effects. Our work is focused on protegrins, a potent class of AMPs that attack bacteria by associating with the bacterial membrane and forming transmembrane pores that facilitate the unrestricted transport of ions. Using fully atomistic molecular dynamics simulations, we have computed the thermodynamics of peptide-membrane association and insertion, as well as peptide aggregation. We also present a multi-scale analysis of the ion transport properties of protegrin pores, ranging from atomistic molecular dynamics simulations to mesoscale continuum models of single-pore electrodiffusion to models of transient ion transport from bacterial cells. Overall, this work provides a quantitative mechanistic description of the mechanism of action of protegrin antimicrobial peptides across multiple length and time scales.

Dimerization of protegrin-1 in different environments.

The dimerization of the cationic ß-hairpin antimicrobial peptide protegrin-1 (PG1) is investigated in three different environments: water, the surface of a lipid bilayer membrane, and the core of the membrane. PG1 is known to kill bacteria by forming oligomeric membrane pores, which permeabilize the cells. PG1 dimers are found in two distinct, parallel and antiparallel, conformations, known as important intermediate structural units of the active pore oligomers. What is not clear is the sequence of events from PG1 monomers in solution to pores inside membranes. The step we focus on in this work is the dimerization of PG1. In particular, we are interested in determining where PG1 dimerization is most favorable. We use extensive molecular dynamics simulations to determine the potential of mean force as a function of distance between two PG1 monomers in the aqueous subphase, the surface of model lipid bilayers and the interior of these bilayers. We investigate the two known distinct modes of dimerization that result in either a parallel or an antiparallel ß-sheet orientation. The model bilayer membranes are composed of anionic palmitoyl-oleoyl-phosphatidylglycerol (POPG) and palmitoyl-oleoyl-phosphatidylethanolamine (POPE) in a 1:3 ratio (POPG:POPE). We find the parallel PG1 dimer association to be more favorable than the antiparallel one in water and inside the membrane. However, we observe that the antiparallel PG1 ß-sheet dimer conformation is somewhat more stable than the parallel dimer association at the surface of the membrane. We explore the role of hydrogen bonds and ionic bridges in peptide dimerization in the three environments. Detailed knowledge of how networks of ionic bridges and hydrogen bonds contribute to peptide stability is essential for the purpose of understanding the mechanism of action for membrane-active peptides as well as for designing peptides which can modulate membrane properties. The findings are suggestive of the dominant pathways leading from individual PG1 molecules in solution to functional pores in bacterial membranes.

A chemical probe of CARM1 alters epigenetic plasticity against breast cancer cell invasion.

CARM1 is a cancer-relevant protein arginine methyltransferase that regulates many aspects of transcription. Its pharmacological inhibition is a promising anti-cancer strategy. Here SKI-73 (6a in this work) is presented as a CARM1 chemical probe with pro-drug properties. SKI-73 (6a) can rapidly penetrate cell membranes and then be processed into active inhibitors, which are retained intracellularly with 10-fold enrichment for several days. These compounds were characterized for their potency, selectivity, modes of action, and on-target engagement. SKI-73 (6a) recapitulates the effect of CARM1 knockout against breast cancer cell invasion. Single-cell RNA-seq analysis revealed that the SKI-73(6a)-associated reduction of invasiveness acts by altering epigenetic plasticity and suppressing the invasion-prone subpopulation. Interestingly, SKI-73 (6a) and CARM1 knockout alter the epigenetic plasticity with remarkable difference, suggesting distinct modes of action for small-molecule and genetic perturbations. We therefore discovered a CARM1-addiction mechanism of cancer metastasis and developed a chemical probe to target this process.

Drugs that are small molecules have the potential to block the individual proteins that drive the spread of cancer, but their design is a challenge. This is because they need to get inside the cell and find their target without binding to other proteins on the way. However, small molecule drugs often have an electric charge, which makes it hard for them to cross the cell membrane. Additionally, most proteins are not completely unique, making it harder for the drugs to find the correct target. CARM1 is a protein that plays a role in the spread of breast cancer cells, and scientists are currently looking for a small molecule that will inhibit its action. The group of enzymes that CARM1 belongs to act by taking a small chemical group, called a methyl group, from a molecule called SAM, and transferring it to proteins that switch genes on and off. In the case of CARM1, this changes cell behavior by turning on genes involved in cell movement. Genetically modifying cells so they will not produce any CARM1 stops the spread of breast cancer cells, but developing a drug with the same effects has proved difficult. Existing drugs that can inhibit CARM1 in a test tube struggle to get inside cells and to distinguish between CARM1 and its related enzymes. Now, Cai et al. have modified and tested a CARM1 inhibitor to address these problems, and find out how these small molecules work. At its core, the inhibitor has a structure very similar to a SAM molecule, so it can fit into the SAM binding pocket of CARM1 and its related enzymes. To stop the inhibitor from binding to other proteins, Cai et al. made small changes to its structure until it only interacted with CARM1.Then, to get the inhibitor inside breast cancer cells, Cai et al. cloaked its charged area with a chemical shield, allowing it to cross the cell membrane. Inside the cell, the chemical shield broke away, allowing the inhibitor to attach to CARM1. Analysis of cells showed that this inhibition only affected the cancer cells most likely to spread. Blocking CARM1 switched off genes involved in cell movement and stopped cancer cells from travelling through 3D gels. This work is a step towards making a drug that can block CARM1 in cancer cells, but there is still further work to be done. The next stages will be to test whether the new inhibitor works in other types of cancer cells, in living animals, and in human patient samples.

Prediction of binding free energy for adsorption of antimicrobial peptide lactoferricin B on a POPC membrane.

Molecular dynamics (MD) simulations are used to study the interaction of a zwitterionic palmitoyl-oleoyl-phosphatidylcholine (POPC) bilayer with the cationic antimicrobial peptide bovine lactoferricin (LFCinB) in a 100 mM NaCl solution at 310 K. The interaction of LFCinB with POPC is used as a model system for studying the details of membrane-peptide interactions, with the peptide selected because of its antimicrobial nature. Seventy-two 3 ns MD simulations, with six orientations of LFCinB at 12 different distances from a POPC membrane, are carried out to determine the potential of mean force (PMF) or free energy profile for the peptide as a function of the distance between LFCinB and the membrane surface. To calculate the PMF for this relatively large system a new variant of constrained MD and thermodynamic integration is developed. A simplified method for relating the PMF to the LFCinB-membrane binding free energy is described and used to predict a free energy of adsorption (or binding) of -1.05+/-0.39 kcal/mol , and corresponding maximum binding force of about 20 pN, for LFCinB-POPC. The contributions of the ions-LFCinB and the water-LFCinB interactions to the PMF are discussed. The method developed will be a useful starting point for future work simulating peptides interacting with charged membranes and interactions involved in the penetration of membranes, features necessary to understand in order to rationally design peptides as potential alternatives to traditional antibiotics.

Assisted Design of Antibody and Protein Therapeutics (ADAPT).

Effective biologic therapeutics require binding affinities that are fine-tuned to their disease-related molecular target. The ADAPT (Assisted Design of Antibody and Protein Therapeutics) platform aids in the selection of mutants that improve/modulate the affinity of antibodies and other biologics. It uses a consensus z-score from three scoring functions and interleaves computational predictions with experimental validation, significantly enhancing the robustness of the design and selection of mutants. The platform was tested on three antibody Fab-antigen systems that spanned a wide range of initial binding affinities: bH1-VEGF-A (44 nM), bH1-HER2 (3.6 nM) and Herceptin-HER2 (0.058 nM). Novel triple mutants were obtained that exhibited 104-, 46- and 32-fold improvements in binding affinity for each system, respectively. Moreover, for all three antibody-antigen systems over 90% of all the intermediate single and double mutants that were designed and tested showed higher affinities than the parent sequence. The contributions of the individual mutants to the change in binding affinity appear to be roughly additive when combined to form double and triple mutants. The new interactions introduced by the affinity-enhancing mutants included long-range electrostatics as well as short-range nonpolar interactions. This diversity in the types of new interactions formed by the mutants was reflected in SPR kinetics that showed that the enhancements in affinities arose from increasing on-rates, decreasing off-rates or a combination of the two effects, depending on the mutation. ADAPT is a very focused search of sequence space and required only 20-30 mutants for each system to be made and tested to achieve the affinity enhancements mentioned above.

Thermodynamic analysis of protegrin-1 insertion and permeation through a lipid bilayer.

Molecular dynamics (MD) simulations are used to study the pathway for the insertion of the cationic antimicrobial peptide protegrin-1 (PG1) into mixed anionic lipid bilayers composed of palmitoyl-oleoyl-phosphatidylglycerol (POPG) and palmitoyl-oleoyl-phosphatidylethanolamine (POPE) in a 1:3 ratio (POPG/POPE). We calculate the potential of mean force (PMF) during the transfer of the peptide from the bulk aqueous phase to the transmembrane (TM) configuration using the adaptive biasing force (ABF) method. We find that the PMF has two energy minima separated by an energy barrier. One minimum corresponds to the fully transmembrane inserted state, with a free energy of -20.1 kcal/mol. The second PMF minimum, which corresponds to adsorption to the membrane surface, has a value of -2.5 kcal/mol. The PMF also shows the existence of a free energy barrier of +6.3 kcal/mol for the insertion process. Using the Kramers theory Langevin equation and the Grote-Hynes theory generalized Langevin equation, we calculated the transmission coefficient for PG1 diffusion through the potential barrier. We focus on the use of the PMF and the time correlation function of the fluctuation of the instantaneous force to calculate the rate constants for insertion/deinsertion of PG1 from the mixed POPG/POPE membrane. The influence of the activation free energy barrier on the dynamics of the insertion and permeation of peptides through the membrane are discussed.

Free energy profile of the interaction between a monomer or a dimer of protegrin-1 in a specific binding orientation and a model lipid bilayer.

The free energies of adsorption of the monomer or dimer of the cationic beta-hairpin antimicrobial peptide protegrin-1 (PG1) in a specific binding orientation on a lipid bilayer are determined using molecular dynamics (MD) simulations and Poisson-Boltzmann calculations. The bilayer is composed of anionic palmitoyl-oleoyl-phosphatidylglycerol (POPG) and palmitoyl-oleoyl-phosphatidylethanolamine (POPE) with ratio 1:3 (POPG/POPE). PG1 is believed to kill bacteria by binding on their membranes. There, it forms pores that lyse the bacteria. Herein we focus on the thermodynamics of binding. In particular, we explore the role of counterion release from the lipid bilayer upon adsorption of either the monomeric or the dimeric form of PG1. Twenty-two 4-ns-long MD trajectories of equilibrated systems are generated to determine the free energy profiles for the monomer and dimer as a function of the distance between the peptide(s) and the membrane surface. The MD simulations are conducted at 11 different separations from the membrane for each of the two systems, one with PG1, the second with a PG1 dimer of only a specific orientation of the monomer and dimer without taking into account the change of entropy for the peptide. To calculate the potential of mean force for each peptide/membrane system, a variant of constrained MD and thermodynamic integration is used. We observed that PG1 dimer binds more favorably to the POPG/POPE membrane. A simple method for relating the free energy profile to the PG1-membrane binding constant is employed to predict a free energy of adsorption of -2.4 +/- 0.8 kcal/mol. A corresponding PG1-dimer-membrane binding constant is calculated as -3.5 +/- 1.1 kcal/mol. Free energy profiles from MD simulation were extensively analyzed and compared with results of Poisson-Boltzmann theory. We find the peptide-membrane attraction to be dominated by the entropy increase due to the release of counterions in a POPG/POPE lipid bilayer.

Binding free energy and counterion release for adsorption of the antimicrobial peptide lactoferricin B on a POPG membrane.

Molecular dynamics (MD) simulations are used to study the interaction of an anionic palmitoyl-oleoyl-phosphatidylglycerol (POPG) bilayer with the cationic antimicrobial peptide bovine lactoferricin (LFCinB) in a 100 mM NaCl solution at 310 K. The interaction of LFCinB with a POPG bilayer is employed as a model system for studying the details of membrane adsorption selectivity of cationic antimicrobial peptides. Seventy eight 4 ns MD production run trajectories of the equilibrated system, with six restrained orientations of LFCinB at 13 different separations from the POPG membrane, are generated to determine the free energy profile for the peptide as a function of the distance between LFCinB and the membrane surface. To calculate the profile for this relatively large system, a variant of constrained MD and thermodynamic integration is used. A simplified method for relating the free energy profile to the LFCinB-POPG membrane binding constant is employed to predict a free energy of adsorption of -5.4+/-1.3 kcal/mol and a corresponding maximum adsorption binding force of about 58 pN. We analyze the results using Poisson-Boltzmann theory. We find the peptide-membrane attraction to be dominated by the entropy increase due to the release of counterions and polarized water from the region between the charged membrane and peptide, as the two approach each other. We contrast these results with those found earlier for adsorption of LFCinB on the mammalianlike palmitoyl-oleoyl-phosphatidylcholine membrane.