New compstatin peptides containing N-terminal extensions and non-natural amino acids exhibit potent complement inhibition and improved solubility characteristics

Compstatin peptides are complement inhibitors that bind and inhibit cleavage of complement C3. Peptide binding is enhanced by hydrophobic interactions; however, poor solubility promotes aggregation in aqueous environments. We have designed new compstatin peptides derived from the W4A9 sequence (Ac-ICVWQDWGAHRCT-NH2, cyclized between C2 and C12), based on structural, computational, and experimental studies. Furthermore, we developed and utilized a computational framework for the design of peptides containing non-natural amino acids. These new compstatin peptides contain polar N-terminal extensions and non-natural amino acid substitutions at positions 4 and 9. Peptides with α-modified non-natural alanine analogs at position 9, as well as peptides containing only N-terminal polar extensions, exhibited similar activity compared to W4A9, as quantified via ELISA, hemolytic, and cell-based assays, and showed improved solubility, as measured by UV absorbance and reverse-phase HPLC experiments. Because of their potency and solubility, these peptides are promising candidates for therapeutic development in numerous complement-mediated diseases.

Forcefield_NCAA: ab initio charge parameters to aid in the discovery and design of therapeutic proteins and peptides with unnatural amino acids and their application to complement inhibitors of the compstatin family

We describe the development and testing of ab initio derived, AMBER ff03 compatible charge parameters for a large library of 147 noncanonical amino acids including β- and N-methylated amino acids for use in applications such as protein structure prediction and de novo protein design. The charge parameter derivation was performed using the RESP fitting approach. Studies were performed assessing the suitability of the derived charge parameters in discriminating the activity/inactivity between 63 analogs of the complement inhibitor Compstatin on the basis of previously published experimental IC50 data and a screening procedure involving short simulations and binding free energy calculations. We found that both the approximate binding affinity (K*) and the binding free energy calculated through MM-GBSA are capable of discriminating between active and inactive Compstatin analogs, with MM-GBSA performing significantly better. Key interactions between the most potent Compstatin analog that contains a noncanonical amino acid are presented and compared to the most potent analog containing only natural amino acids and native Compstatin. We make the derived parameters and an associated web interface that is capable of performing modifications on proteins using Forcefield_NCAA and outputting AMBER-ready topology and parameter files freely available for academic use at http://selene.princeton.edu/FFNCAA . The forcefield allows one to incorporate these customized amino acids into design applications with control over size, van der Waals, and electrostatic interactions.

Derivation of ligands for the complement C3a receptor from the C-terminus of C5a

The complement cascade is a highly sophisticated network of proteins that are well regulated and directed in response to invading pathogens or tissue injury. Complement C3a and C5a are key mediators produced by this cascade, and their dysregulation has been linked to a plethora of inflammatory and autoimmune diseases. Consequently, this has stimulated interest in the development of ligands for the receptors for these complement peptides, C3a receptor, and C5a1 (C5aR/CD88). In this study we used computational methods to design novel C5a1 receptor ligands. However, functional screening in human monocyte-derived macrophages using the xCELLigence label-free platform demonstrated altered specificity of our ligands. No agonist/antagonist activity was observed at C5a1, but we instead saw that the ligands were able to partially agonize the closely related complement receptor C3a receptor. This was verified in the presence of C3a receptor antagonist SB 290157 and in a stable cell line expressing either C5a1 or C3a receptor alone. C3a agonism has been suggested to be a potential treatment of acute neutrophil-driven traumatic pathologies, and may have great potential as a therapeutic avenue in this arena.

WeFold: a coopetition for protein structure prediction

The protein structure prediction problem continues to elude scientists. Despite the introduction of many methods, only modest gains were made over the last decade for certain classes of prediction targets. To address this challenge, a social-media based worldwide collaborative effort, named WeFold, was undertaken by 13 labs. During the collaboration, the laboratories were simultaneously competing with each other. Here, we present the first attempt at "coopetition" in scientific research applied to the protein structure prediction and refinement problems. The coopetition was possible by allowing the participating labs to contribute different components of their protein structure prediction pipelines and create new hybrid pipelines that they tested during CASP10. This manuscript describes both successes and areas needing improvement as identified throughout the first WeFold experiment and discusses the efforts that are underway to advance this initiative. A footprint of all contributions and structures are publicly accessible at http://www.wefold.org.

A Comparative Theoretical and Computational Study on Robust Counterpart Optimization: III. Improving the Quality of Robust Solutions

In this paper, we study the solution quality of robust optimization problems when they are used to approximate probabilistic constraints and propose a novel method to improve the quality. Two solution frameworks are first compared: (1) the traditional robust optimization framework which only uses the a priori probability bounds and (3) the approximation framework which uses the a posteriori probability bound. We illustrate that the traditional robust optimization method is computationally efficient but its solution is in general conservative. On the other hand, the a posteriori probability bound based method provides less conservative solution but it is computationally more difficult because a nonconvex optimization problem is solved. Based on the comparative study of the two methods, we propose a novel iterative solution framework which combines the advantage of the a priori bound and the a posteriori probability bound. The proposed method can improve the solution quality of traditional robust optimization framework without significantly increasing the computational effort. The effectiveness of the proposed method is illustrated through numerical examples and applications in planning and scheduling problems.

De novo design and experimental characterization of ultrashort self-associating peptides

Self-association is a common phenomenon in biology and one that can have positive and negative impacts, from the construction of the architectural cytoskeleton of cells to the formation of fibrils in amyloid diseases. Understanding the nature and mechanisms of self-association is important for modulating these systems and in creating biologically-inspired materials. Here, we present a two-stage de novo peptide design framework that can generate novel self-associating peptide systems. The first stage uses a simulated multimeric template structure as input into the optimization-based Sequence Selection to generate low potential energy sequences. The second stage is a computational validation procedure that calculates Fold Specificity and/or Approximate Association Affinity (K*association) based on metrics that we have devised for multimeric systems. This framework was applied to the design of self-associating tripeptides using the known self-associating tripeptide, Ac-IVD, as a structural template. Six computationally predicted tripeptides (Ac-LVE, Ac-YYD, Ac-LLE, Ac-YLD, Ac-MYD, Ac-VIE) were chosen for experimental validation in order to illustrate the self-association outcomes predicted by the three metrics. Self-association and electron microscopy studies revealed that Ac-LLE formed bead-like microstructures, Ac-LVE and Ac-YYD formed fibrillar aggregates, Ac-VIE and Ac-MYD formed hydrogels, and Ac-YLD crystallized under ambient conditions. An X-ray crystallographic study was carried out on a single crystal of Ac-YLD, which revealed that each molecule adopts a β-strand conformation that stack together to form parallel β-sheets. As an additional validation of the approach, the hydrogel-forming sequences of Ac-MYD and Ac-VIE were shuffled. The shuffled sequences were computationally predicted to have lower K*association values and were experimentally verified to not form hydrogels. This illustrates the robustness of the framework in predicting self-associating tripeptides. We expect that this enhanced multimeric de novo peptide design framework will find future application in creating novel self-associating peptides based on unnatural amino acids, and inhibitor peptides of detrimental self-aggregating biological proteins.

Energy Supply Chain Optimization of Hybrid Feedstock Processes: A Review

The economic, environmental, and social performances of energy systems depend on their geographical locations and the surrounding market infrastructure for feedstocks and energy products. Strategic decisions to locate energy conversion facilities must take all upstream and downstream operations into account, prompting the development of supply chain modeling and optimization methods. This article reviews the contributions of energy supply chain studies that include heat, power, and liquid fuels production. Studies are categorized based on specific features of the mathematical model, highlighting those that address energy supply chain models with and without considerations of multiperiod decisions. Studies that incorporate uncertainties are discussed, and opportunities for future research developments are outlined.

Molecular recognition of CCR5 by an HIV-1 gp120 V3 loop

The binding of protein HIV-1 gp120 to coreceptors CCR5 or CXCR4 is a key step of the HIV-1 entry to the host cell, and is predominantly mediated through the V3 loop fragment of HIV-1 gp120. In the present work, we delineate the molecular recognition of chemokine receptor CCR5 by a dual tropic HIV-1 gp120 V3 loop, using a comprehensive set of computational tools predominantly based on molecular dynamics simulations and free energy calculations. We report, what is to our knowledge, the first complete HIV-1 gp120 V3 loop : CCR5 complex structure, which includes the whole V3 loop and the N-terminus of CCR5, and exhibits exceptional agreement with previous experimental findings. The computationally derived structure sheds light into the functional role of HIV-1 gp120 V3 loop and CCR5 residues associated with the HIV-1 coreceptor activity, and provides insights into the HIV-1 coreceptor selectivity and the blocking mechanism of HIV-1 gp120 by maraviroc. By comparing the binding of the specific dual tropic HIV-1 gp120 V3 loop with CCR5 and CXCR4, we observe that the HIV-1 gp120 V3 loop residues 13-21, which include the tip, share nearly identical structural and energetic properties in complex with both coreceptors. This result paves the way for the design of dual CCR5/CXCR4 targeted peptides as novel potential anti-AIDS therapeutics.

De novo peptide design and experimental validation of histone methyltransferase inhibitors

Histones are small proteins critical to the efficient packaging of DNA in the nucleus. DNA–protein complexes, known as nucleosomes, are formed when the DNA winds itself around the surface of the histones. The methylation of histone residues by enhancer of zeste homolog 2 (EZH2) maintains gene repression over successive cell generations. Overexpression of EZH2 can silence important tumor suppressor genes leading to increased invasiveness of many types of cancers. This makes the inhibition of EZH2 an important target in the development of cancer therapeutics. We employed a three-stage computational de novo peptide design method to design inhibitory peptides of EZH2. The method consists of a sequence selection stage and two validation stages for fold specificity and approximate binding affinity. The sequence selection stage consists of an integer linear optimization model that was solved to produce a rank-ordered list of amino acid sequences with increased stability in the bound peptide-EZH2 structure. These sequences were validated through the calculation of the fold specificity and approximate binding affinity of the designed peptides. Here we report the discovery of novel EZH2 inhibitory peptides using the de novo peptide design method. The computationally discovered peptides were experimentally validated in vitro using dose titrations and mechanism of action enzymatic assays. The peptide with the highest in vitro response, SQ037, was validated in nucleo using quantitative mass spectrometry-based proteomics. This peptide had an IC50 of 13.5 mM, demonstrated greater potency as an inhibitor when compared to the native and K27A mutant control peptides, and demonstrated competitive inhibition versus the peptide substrate. Additionally, this peptide demonstrated high specificity to the EZH2 target in comparison to other histone methyltransferases. The validated peptides are the first computationally designed peptides that directly inhibit EZH2. These inhibitors should prove useful for further chromatin biology investigations.