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Introduction into the human bodymakes most nanoparticle systemssusceptible to aggregation via nonspecific protein binding. Here,we developed a peptide-capped gold nanoparticle platform that withstandsaggregation in undiluted human serum at 37 °C for 24 h. Thisbiocompatible and natural system is based on mimicking human proteinswhich are enriched in negatively charged glutamic acid and positivelycharged lysine residues on their surface. The multifunctional EKEKEKE-PPPPC-Ampeptide sequence consists of a stealth glutamic acid/lysine portioncombined with a surface anchoring linker containing four prolinesand a cysteine. Particle stability was measured via optical spectroscopyand dynamic light scattering in single protein, high salt, and undilutedhuman serum solutions. In vitro cell experiments demonstrate EKEKEKE-PPPPC-Amcapped gold nanoparticles effectively minimize nonspecific cell uptakeby nonphagocytic bovine aortic endothelial cells and phagocytic murinemacrophage RAW 264.7 cells. Cytotoxicity studies show that peptide-cappedgold nanoparticles do not affect cell viability. Finally, the peptideEKEKEKE-PPPPC-Am was extended with cyclic RGD to demonstrate specificcell targeting and stealth without using poly(ethylene glycol). Addingthe functional peptide via peptide sequence extension avoids complexconjugation chemistries that are used for connection to syntheticmaterials. Inductively coupled plasma mass spectroscopy results indicatehigh aortic bovine endothelial cell uptake of c[RGDfE(SGG-KEKEKE-PPPPC-Am)]capped gold nanoparticles and low uptake of the control scrambledsequence c[RDGfE(SGG-KEKEKE-PPPPC-Am)] capped gold nanoparticles. [ABSTRACT FROM AUTHOR]

Chargedamino acids are the most common on surfaces of proteinsand understanding the interactions between these charged amino acids,salt bridging, is crucial for understanding protein–proteininteractions. Previous simulations have been limited to implicit solventor fixed binding geometry due to the sampling required for convergedfree energies. Using well-tempered metadynamics, we have calculatedsalt bridge free energy surfaces in water and confirmed the resultswith NMR experiments. The simulations give binding free energies,quantitative ranking of salt bridging strength, and insights intothe hydration of the salt bridges. The arginine–aspartate saltbridge was found to be the weakest and arginine-glutamate the strongest,showing that arginine can discriminate between aspartate and glutamate,whereas the salt bridges with lysine are indistinguishable in theirfree energy. The salt bridging hydration is found to be complementaryto salt bridge orientation with arginine having specific orientations. [ABSTRACT FROM AUTHOR]

Protein arrays are a high-throughput approach for proteomic profiling, vital for achieving a greater understanding of biological systems, in addition to disease diagnostics and monitoring therapeutic treatments. In this work, zwitterionic carboxybetaine polymer (pCB) coated substrates were investigated as an array surface platform to enable convenient amino-coupling chemistry on a single directly functionalizable and unblocked film for the sensitive detection of target analytes from undiluted human blood plasma. Using a surface plasmon resonance (SPR) imaging sensor, the antibody immobilization conditions which provided excellent spot morphology and the largest antigen response were determined. It was found that pCB functionalization and the corresponding antigen detection both increased with pH and antibody concentration. Additionally, immobilization only required an aqueous buffer without the need for additives to improve spot quality. The nonspecific protein adsorption to undiluted human plasma on both the antibody immobilized pCB spots and the background were found to be about 9 and 6 ng/cm², respectively. A subsequent array consisting of three antibodies spotted onto pCB revealed little cross-reactivity for antigens spiked into the undiluted plasma. The low postfunctionalized nonfouling properties combined with antibody amplification showed similar sensitivities achievable with conventional spectroscopic SPR sensors and the same pCB films, but now with high-throughput capabilities. This represents the first demonstration of low fouling properties following antibody functionalization on protein arrays from undiluted human plasma and indicates the great potential of the pCB platform for high-throughput protein analysis. [ABSTRACT FROM AUTHOR]

Positive allosteric modulation of the mu-opioid receptor is a promising strategy to address the ever-growing problem of acute and chronic pain management. Positive allosteric modulators (PAMs) of the mu-opioid receptor could be employed to enhance the efficacy of endogenous opioid peptides to a degree that provides pain relief without the need for traditional opioid drugs. Alternatively, PAMs might be used to enhance the action of opioid drugs and so provide an opioid-sparing effect, allowing for the use of lower doses of opioid agonists and potentially decreasing associated side effects. BMS-986122 (2-(3-bromo-4-methoxyphenyl)-3-[(4-chlorophenyl)-sulfonyl]-thiazolidine) has been previously identified as a PAM of the mu-opioid receptor. In the present work, we have designed and synthesized 33 analogs of BMS-986122 to explore the structure-activity relationships of this scaffold and confirm its allosteric mechanism of action. Among several newly identified modulators, the most promising compound ( 14b ) had improved activity to increase the in vitro potency of the standard mu-opioid agonist DAMGO and showed in vivo activity in mice to enhance the antinociceptive action of morphine.

Na v 1.7 is an extensively investigated target for pain with a strong genetic link in humans, yet in spite of this effort, it remains challenging to identify efficacious, selective, and safe inhibitors. Here, we disclose the discovery and preclinical profile of GDC-0276 ( 1 ) and GDC-0310 ( 2 ), selective Na v 1.7 inhibitors that have completed Phase 1 trials. Our initial search focused on close-in analogues to early compound 3 . This resulted in the discovery of GDC-0276 ( 1 ), which possessed improved metabolic stability and an acceptable overall pharmacokinetics profile. To further derisk the predicted human pharmacokinetics and enable QD dosing, additional optimization of the scaffold was conducted, resulting in the discovery of a novel series of N-benzyl piperidine Na v 1.7 inhibitors. Improvement of the metabolic stability by blocking the labile benzylic position led to the discovery of GDC-0310 ( 2 ), which possesses improved Na v selectivity and pharmacokinetic profile over 1 .

Misfolded amyloid peptides are neurotoxic molecules associated with Alzheimer's disease. The Aβ 21-30 peptide fragment is a decapeptide fragment of the complete Aβ42 peptide which is a hypothesized cause of Alzheimer's disease via amyloid fibrillogenesis. Aβ 21-30 is investigated here with a combination of NMR (nuclear magnetic resonance) spectroscopy experiments and molecular dynamics simulations with experiment directed simulation (EDS). EDS is a maximum entropy biasing method that augments a molecular dynamics simulation with experimental data (NMR chemical shifts) to improve agreement with experiments and thus accuracy. EDS molecular dynamics shows that the Aβ 21-30 monomer has a β turn stabilized by the following interactions: S26-K28, D23-S26, and D23-K28. NMR, total correlation spectroscopy, and rotating frame Overhauser effect spectroscopy experiments provide independent agreement. Subsequent two- and four-monomer EDS simulations show aggregation. Diffusion coefficients calculated from molecular simulation also agreed with experimentally measured values only after using EDS, providing independent assessment of accuracy. This work demonstrates how accuracy can be improved by directly using experimental data in molecular dynamics of complex processes like self-assembly.

The sodium channel Na V 1.7 has emerged as a promising target for the treatment of pain based on strong genetic validation of its role in nociception. In recent years, a number of aryl and acyl sulfonamides have been reported as potent inhibitors of Na V 1.7, with high selectivity over the cardiac isoform Na V 1.5. Herein, we report on the discovery of a novel series of N-([1,2,4]triazolo[4,3- a]pyridin-3-yl)methanesulfonamides as selective Na V 1.7 inhibitors. Starting with the crystal structure of an acyl sulfonamide, we rationalized that cyclization to form a fused heterocycle would improve physicochemical properties, in particular lipophilicity. Our design strategy focused on optimization of potency for block of Na V 1.7 and human metabolic stability. Lead compounds 10, 13 (GNE-131), and 25 showed excellent potency, good in vitro metabolic stability, and low in vivo clearance in mouse, rat, and dog. Compound 13 also displayed excellent efficacy in a transgenic mouse model of induced pain.

Despite several years of research, the ion exchange mechanisms in chloride/proton antiporters and many other coupled transporters are not yet understood at the molecular level. Here, we present a novel approach to kinetic modeling and apply it to ion exchange in ClC-ec1. Our multiscale kinetic model is developed by (1) calculating the state-to-state rate coefficients with reactive and polarizable molecular dynamics simulations, (2) optimizing these rates in a global kinetic network, and (3) predicting new electrophysiological results. The model shows that the robust Cl:H exchange ratio (2.2:1) can indeed arise from kinetic coupling without large protein conformational changes, indicating a possible facile evolutionary connection to chloride channels. The E148 amino acid residue is shown to couple chloride and proton transport through protonation-dependent blockage of the central anion binding site and an anion-dependent pK a value, which influences proton transport. The results demonstrate how an ensemble of different exchange pathways, as opposed to a single series of transitions, culminates in the macroscopic observables of the antiporter, such as transport rates, chloride/proton stoichiometry, and pH dependence.

To extract meaningful data from molecular simulations, it is necessary to incorporate new experimental observations as they become available. Recently, a new method was developed for incorporating experimental observations into molecular simulations, called experiment directed simulation (EDS), which utilizes a maximum entropy argument to bias an existing model to agree with experimental observations while changing the original model by a minimal amount. However, there is no discussion in the literature of whether or not the minimal bias systematically and generally improves the model by creating agreement with the experiment. In this work, we show that the relative entropy of the biased system with respect to an ideal target is always reduced by the application of a minimal bias, such as the one utilized by EDS. Using all-atom simulations that have been biased with EDS, one can then easily and rapidly improve a bottom-up multiscale coarse-grained (MS-CG) model without the need for a time-consuming reparametrization of the underlying atomistic force field. Furthermore, the improvement given by the many-body interactions introduced by the EDS bias can be maintained after being projected down to effective two-body MS-CG interactions. The result of this analysis is a new paradigm in coarse-grained modeling and simulation in which the "bottom-up" and "top-down" approaches are combined within a single, rigorous formalism based on statistical mechanics. The utility of building the resulting EDS-MS-CG models is demonstrated on two molecular systems: liquid methanol and ethylene carbonate.

Creating models that are consistent with experimental data is essential in molecular modeling. This is often done by iteratively tuning the molecular force field of a simulation to match experimental data. An alternative method is to bias a simulation, leading to a hybrid model composed of the original force field and biasing terms. We previously introduced such a method called experiment directed simulation (EDS). EDS minimally biases simulations to match average values. In this work, we introduce a new method called experiment directed metadynamics (EDM) that creates minimal biases for matching entire free energy surfaces such as radial distribution functions and phi/psi angle free energies. It is also possible with EDM to create a tunable mixture of the experimental data and free energy of the unbiased ensemble with explicit ratios. EDM can be proven to be convergent, and we also present proof, via a maximum entropy argument, that the final bias is minimal and unique. Examples of its use are given in the construction of ensembles that follow a desired free energy. The example systems studied include a Lennard-Jones fluid made to match a radial distribution function, an atomistic model augmented with bioinformatics data, and a three-component electrolyte solution where ab initio simulation data is used to improve a classical empirical model.

A primary goal in molecular simulations is to modify the potential energy of a system so that properties of the simulation match experimental data. This is traditionally done through iterative cycles of simulation and reparameterization. An alternative approach is to bias the potential energy so that the system matches experimental data. This can be done while minimally changing the underlying free energy of the molecular simulation. Current minimal biasing methods require replicas, which can lead to unphysical dynamics and introduces new complexity: the choice of replica number and their properties. Here, we describe a new method, called experiment directed simulation that does not require replicas, converges rapidly, can match many data simultaneously, and minimally modifies the potential. The experiment directed simulation method is demonstrated on model systems and a three-component electrolyte simulation. The theory used to derive the method also provides insight into how changing a molecular force-field impacts the expected value of observables in simulation.

Polycarboxybetaine and poly(ethylene glycol) materials resist nonspecific protein adsorption but differ in influencing biological functions such as enzymatic activity. To investigate this difference, we studied the influence of carboxybetaine and oligo(ethylene glycol) moieties on hydrophobic interactions using molecular simulations. We employed a model system composed of two non-polar plates and studied the potential of mean force of plate-plate association in carboxybetaine, (ethylene glycol)4, and (ethylene glycol)2 solutions using well-tempered metadynamics simulations. Water, trimethylamine N-oxide, and urea solutions were used as reference systems. We analyzed the variation of the potential of mean force in various solutions to study how carboxybetaine and oligo(ethylene glycol) moieties influence the hydrophobic interactions. To study the origin of their influence, we analyzed the normalized distributions of moieties and water molecules using molecular dynamics simulations. The simulation results showed that oligo(ethylene glycol) moieties repel water molecules away from the non-polar plates and weaken the hydrophobic interactions. Carboxybetaine moieties do not repel water molecules away from the plates and therefore do not influence the hydrophobic interactions.

Peptide libraries allow researchers to quickly find hundreds of peptide sequences with a desired property. Currently, the large amount of data generated from peptide libraries is analyzed by hand, where researchers search for repeating patterns in the peptide sequences. Such patterns are called motifs. In this work, we describe a set of algorithms which allow quick, efficient, and standard analysis of peptide libraries. Four main techniques are described: (1) choice of the number of motifs present in a peptide library; (2) separation of the peptides into groups of similar sequences; (3) fitting of a model to the peptides to extract motifs; (4) analysis of the library using quantitative structure-property relationships if no clear motifs are present. The application of five previously published data sets shows these techniques can automatically repeat the work of experts quickly and allow much more flexibility in analysis. A new way of visually presenting peptide libraries is also described, which allows visual inspection of the grouping and spread of sequences. The algorithms have been implemented in an open-source plug-in called "peplib" and an online web application.

In this work, we report a study on the differential hydration of carboxybetaine and sulfobetaine using molecular simulations. The coordination number, spatial distribution, dipole orientation distribution, and residence time of water molecules around the positively charged group (N(CH(3))(3)(+)) and negatively charged group (COO(-) for carboxybetaine and SO(3)(-) for sulfobetaine) were investigated to compare the hydration of these two betaines. The results show that the negatively charged group of sulfobetaine has more water molecules around it than that of carboxybetaine, while the water molecules around the negatively charged group of the carboxybetaine have a sharper spatial distribution, more preferential dipole orientation, and longer residence time. The behavior of water molecules around the positively charged group of sulfobetaine is similar to those around the positively charged group of carboxybetaine. For both sulfobetaine and carboxybetaine, the positively charged groups are surrounded by more water molecules than the negatively charged groups, whereas the water molecules around the negatively charged groups are more ordered than those around the positively charged ones. We also investigated the hydration free energy of these two molecules with the free energy perturbation method and found that their values are all considerably lower than that of oligo(ethylene glycol).