Nanohole Arrays of Mixed Designs and Microwriting for Simultaneous and Multiple Protein Binding Studies

PubMed Central

Ji, Jin; Yang, Jiun-Chan; Larson, Dale N.

2009-01-01

We demonstrate using nanohole arrays of mixed designs and a microwriting process based on dip-pen nanolithography to monitor multiple, different protein binding events simultaneously in real time based on the intensity of Extraordinary Optical Transmission of nanohole arrays. The microwriting process and small footprint of the individual nanohole arrays enabled us to observe different binding events located only 16μm apart, achieving high spatial resolution. We also present a novel concept that incorporates nanohole arrays of different designs to improve confidence and accuracy of binding studies. For proof of concept, two types of nanohole arrays, designed to exhibit opposite responses to protein bindings, were fabricated on one transducer. Initial studies indicate that the mixed designs could help to screen out artifacts such as protein intrinsic signals, providing improved accuracy of binding interpretation. PMID:19297143

Combining Rosetta with molecular dynamics (MD): A benchmark of the MD-based ensemble protein design.

PubMed

Ludwiczak, Jan; Jarmula, Adam; Dunin-Horkawicz, Stanislaw

2018-07-01

Computational protein design is a set of procedures for computing amino acid sequences that will fold into a specified structure. Rosetta Design, a commonly used software for protein design, allows for the effective identification of sequences compatible with a given backbone structure, while molecular dynamics (MD) simulations can thoroughly sample near-native conformations. We benchmarked a procedure in which Rosetta design is started on MD-derived structural ensembles and showed that such a combined approach generates 20-30% more diverse sequences than currently available methods with only a slight increase in computation time. Importantly, the increase in diversity is achieved without a loss in the quality of the designed sequences assessed by their resemblance to natural sequences. We demonstrate that the MD-based procedure is also applicable to de novo design tasks started from backbone structures without any sequence information. In addition, we implemented a protocol that can be used to assess the stability of designed models and to select the best candidates for experimental validation. In sum our results demonstrate that the MD ensemble-based flexible backbone design can be a viable method for protein design, especially for tasks that require a large pool of diverse sequences. Copyright © 2018 Elsevier Inc. All rights reserved.

Peptide-oligonucleotide conjugates as nanoscale building blocks for assembly of an artificial three-helix protein mimic

NASA Astrophysics Data System (ADS)

Lou, Chenguang; Martos-Maldonado, Manuel C.; Madsen, Charlotte S.; Thomsen, Rasmus P.; Midtgaard, Søren Roi; Christensen, Niels Johan; Kjems, Jørgen; Thulstrup, Peter W.; Wengel, Jesper; Jensen, Knud J.

2016-07-01

Peptide-based structures can be designed to yield artificial proteins with specific folding patterns and functions. Template-based assembly of peptide units is one design option, but the use of two orthogonal self-assembly principles, oligonucleotide triple helix and a coiled coil protein domain formation have never been realized for de novo protein design. Here, we show the applicability of peptide-oligonucleotide conjugates for self-assembly of higher-ordered protein-like structures. The resulting nano-assemblies were characterized by ultraviolet-melting, gel electrophoresis, circular dichroism (CD) spectroscopy, small-angle X-ray scattering and transmission electron microscopy. These studies revealed the formation of the desired triple helix and coiled coil domains at low concentrations, while a dimer of trimers was dominating at high concentration. CD spectroscopy showed an extraordinarily high degree of α-helicity for the peptide moieties in the assemblies. The results validate the use of orthogonal self-assembly principles as a paradigm for de novo protein design.

A Template-Based Protein Structure Reconstruction Method Using Deep Autoencoder Learning.

PubMed

Li, Haiou; Lyu, Qiang; Cheng, Jianlin

2016-12-01

Protein structure prediction is an important problem in computational biology, and is widely applied to various biomedical problems such as protein function study, protein design, and drug design. In this work, we developed a novel deep learning approach based on a deeply stacked denoising autoencoder for protein structure reconstruction. We applied our approach to a template-based protein structure prediction using only the 3D structural coordinates of homologous template proteins as input. The templates were identified for a target protein by a PSI-BLAST search. 3DRobot (a program that automatically generates diverse and well-packed protein structure decoys) was used to generate initial decoy models for the target from the templates. A stacked denoising autoencoder was trained on the decoys to obtain a deep learning model for the target protein. The trained deep model was then used to reconstruct the final structural model for the target sequence. With target proteins that have highly similar template proteins as benchmarks, the GDT-TS score of the predicted structures is greater than 0.7, suggesting that the deep autoencoder is a promising method for protein structure reconstruction.

Protein Design for Nanostructural Engineering: General Aspects.

PubMed

Grove, Tijana Z; Cortajarena, Aitziber L

2016-01-01

This chapter aims to introduce the main challenges in the field of protein design for engineering of nanostructures and functional materials. First, we introduce proteins and illustrate the key characteristics that open many possibilities for the use of proteins in nanotechnology. Then, we describe the current state of the art of nanopatterning techniques and the actual needs of the emerging field of nanotechnology to develop new tools in order to achieve precise control and manipulation of elements at the nanoscale. In this sense, the increasing knowledge of protein science and advances in protein design allow to tackle current challenges such as the design of nanodevices, nanopatterned surfaces, and nanomachines. This book highlights the recent progresses of protein nanotechnology over the last decade and emphasizes the power of protein engineering through illustrative examples of protein based-assemblies and their potential applications.

Synergistic Integration of Experimental and Simulation Approaches for the de Novo Design of Silk-Based Materials.

PubMed

Huang, Wenwen; Ebrahimi, Davoud; Dinjaski, Nina; Tarakanova, Anna; Buehler, Markus J; Wong, Joyce Y; Kaplan, David L

2017-04-18

Tailored biomaterials with tunable functional properties are crucial for a variety of task-specific applications ranging from healthcare to sustainable, novel bio-nanodevices. To generate polymeric materials with predictive functional outcomes, exploiting designs from nature while morphing them toward non-natural systems offers an important strategy. Silks are Nature's building blocks and are produced by arthropods for a variety of uses that are essential for their survival. Due to the genetic control of encoded protein sequence, mechanical properties, biocompatibility, and biodegradability, silk proteins have been selected as prototype models to emulate for the tunable designs of biomaterial systems. The bottom up strategy of material design opens important opportunities to create predictive functional outcomes, following the exquisite polymeric templates inspired by silks. Recombinant DNA technology provides a systematic approach to recapitulate, vary, and evaluate the core structure peptide motifs in silks and then biosynthesize silk-based polymers by design. Post-biosynthesis processing allows for another dimension of material design by controlled or assisted assembly. Multiscale modeling, from the theoretical prospective, provides strategies to explore interactions at different length scales, leading to selective material properties. Synergy among experimental and modeling approaches can provide new and more rapid insights into the most appropriate structure-function relationships to pursue while also furthering our understanding in terms of the range of silk-based systems that can be generated. This approach utilizes nature as a blueprint for initial polymer designs with useful functions (e.g., silk fibers) but also employs modeling-guided experiments to expand the initial polymer designs into new domains of functional materials that do not exist in nature. The overall path to these new functional outcomes is greatly accelerated via the integration of modeling with experiment. In this Account, we summarize recent advances in understanding and functionalization of silk-based protein systems, with a focus on the integration of simulation and experiment for biopolymer design. Spider silk was selected as an exemplary protein to address the fundamental challenges in polymer designs, including specific insights into the role of molecular weight, hydrophobic/hydrophilic partitioning, and shear stress for silk fiber formation. To expand current silk designs toward biointerfaces and stimuli responsive materials, peptide modules from other natural proteins were added to silk designs to introduce new functions, exploiting the modular nature of silk proteins and fibrous proteins in general. The integrated approaches explored suggest that protein folding, silk volume fraction, and protein amino acid sequence changes (e.g., mutations) are critical factors for functional biomaterial designs. In summary, the integrated modeling-experimental approach described in this Account suggests a more rationally directed and more rapid method for the design of polymeric materials. It is expected that this combined use of experimental and computational approaches has a broad applicability not only for silk-based systems, but also for other polymer and composite materials.

Elucidating the druggable interface of protein-protein interactions using fragment docking and coevolutionary analysis.

PubMed

Bai, Fang; Morcos, Faruck; Cheng, Ryan R; Jiang, Hualiang; Onuchic, José N

2016-12-13

Protein-protein interactions play a central role in cellular function. Improving the understanding of complex formation has many practical applications, including the rational design of new therapeutic agents and the mechanisms governing signal transduction networks. The generally large, flat, and relatively featureless binding sites of protein complexes pose many challenges for drug design. Fragment docking and direct coupling analysis are used in an integrated computational method to estimate druggable protein-protein interfaces. (i) This method explores the binding of fragment-sized molecular probes on the protein surface using a molecular docking-based screen. (ii) The energetically favorable binding sites of the probes, called hot spots, are spatially clustered to map out candidate binding sites on the protein surface. (iii) A coevolution-based interface interaction score is used to discriminate between different candidate binding sites, yielding potential interfacial targets for therapeutic drug design. This approach is validated for important, well-studied disease-related proteins with known pharmaceutical targets, and also identifies targets that have yet to be studied. Moreover, therapeutic agents are proposed by chemically connecting the fragments that are strongly bound to the hot spots.

Automated selection of stabilizing mutations in designed and natural proteins.

PubMed

Borgo, Benjamin; Havranek, James J

2012-01-31

The ability to engineer novel protein folds, conformations, and enzymatic activities offers enormous potential for the development of new protein therapeutics and biocatalysts. However, many de novo and redesigned proteins exhibit poor hydrophobic packing in their predicted structures, leading to instability or insolubility. The general utility of rational, structure-based design would greatly benefit from an improved ability to generate well-packed conformations. Here we present an automated protocol within the RosettaDesign framework that can identify and improve poorly packed protein cores by selecting a series of stabilizing point mutations. We apply our method to previously characterized designed proteins that exhibited a decrease in stability after a full computational redesign. We further demonstrate the ability of our method to improve the thermostability of a well-behaved native protein. In each instance, biophysical characterization reveals that we were able to stabilize the original proteins against chemical and thermal denaturation. We believe our method will be a valuable tool for both improving upon designed proteins and conferring increased stability upon native proteins.

Automated selection of stabilizing mutations in designed and natural proteins

PubMed Central

Borgo, Benjamin; Havranek, James J.

2012-01-01

The ability to engineer novel protein folds, conformations, and enzymatic activities offers enormous potential for the development of new protein therapeutics and biocatalysts. However, many de novo and redesigned proteins exhibit poor hydrophobic packing in their predicted structures, leading to instability or insolubility. The general utility of rational, structure-based design would greatly benefit from an improved ability to generate well-packed conformations. Here we present an automated protocol within the RosettaDesign framework that can identify and improve poorly packed protein cores by selecting a series of stabilizing point mutations. We apply our method to previously characterized designed proteins that exhibited a decrease in stability after a full computational redesign. We further demonstrate the ability of our method to improve the thermostability of a well-behaved native protein. In each instance, biophysical characterization reveals that we were able to stabilize the original proteins against chemical and thermal denaturation. We believe our method will be a valuable tool for both improving upon designed proteins and conferring increased stability upon native proteins. PMID:22307603

Segmented molecular design of self-healing proteinaceous materials

PubMed Central

Sariola, Veikko; Pena-Francesch, Abdon; Jung, Huihun; Çetinkaya, Murat; Pacheco, Carlos; Sitti, Metin; Demirel, Melik C.

2015-01-01

Hierarchical assembly of self-healing adhesive proteins creates strong and robust structural and interfacial materials, but understanding of the molecular design and structure–property relationships of structural proteins remains unclear. Elucidating this relationship would allow rational design of next generation genetically engineered self-healing structural proteins. Here we report a general self-healing and -assembly strategy based on a multiphase recombinant protein based material. Segmented structure of the protein shows soft glycine- and tyrosine-rich segments with self-healing capability and hard beta-sheet segments. The soft segments are strongly plasticized by water, lowering the self-healing temperature close to body temperature. The hard segments self-assemble into nanoconfined domains to reinforce the material. The healing strength scales sublinearly with contact time, which associates with diffusion and wetting of autohesion. The finding suggests that recombinant structural proteins from heterologous expression have potential as strong and repairable engineering materials. PMID:26323335

Segmented molecular design of self-healing proteinaceous materials

NASA Astrophysics Data System (ADS)

Sariola, Veikko; Pena-Francesch, Abdon; Jung, Huihun; Çetinkaya, Murat; Pacheco, Carlos; Sitti, Metin; Demirel, Melik C.

2015-09-01

Hierarchical assembly of self-healing adhesive proteins creates strong and robust structural and interfacial materials, but understanding of the molecular design and structure-property relationships of structural proteins remains unclear. Elucidating this relationship would allow rational design of next generation genetically engineered self-healing structural proteins. Here we report a general self-healing and -assembly strategy based on a multiphase recombinant protein based material. Segmented structure of the protein shows soft glycine- and tyrosine-rich segments with self-healing capability and hard beta-sheet segments. The soft segments are strongly plasticized by water, lowering the self-healing temperature close to body temperature. The hard segments self-assemble into nanoconfined domains to reinforce the material. The healing strength scales sublinearly with contact time, which associates with diffusion and wetting of autohesion. The finding suggests that recombinant structural proteins from heterologous expression have potential as strong and repairable engineering materials.

Segmented molecular design of self-healing proteinaceous materials.

PubMed

Sariola, Veikko; Pena-Francesch, Abdon; Jung, Huihun; Çetinkaya, Murat; Pacheco, Carlos; Sitti, Metin; Demirel, Melik C

2015-09-01

Hierarchical assembly of self-healing adhesive proteins creates strong and robust structural and interfacial materials, but understanding of the molecular design and structure-property relationships of structural proteins remains unclear. Elucidating this relationship would allow rational design of next generation genetically engineered self-healing structural proteins. Here we report a general self-healing and -assembly strategy based on a multiphase recombinant protein based material. Segmented structure of the protein shows soft glycine- and tyrosine-rich segments with self-healing capability and hard beta-sheet segments. The soft segments are strongly plasticized by water, lowering the self-healing temperature close to body temperature. The hard segments self-assemble into nanoconfined domains to reinforce the material. The healing strength scales sublinearly with contact time, which associates with diffusion and wetting of autohesion. The finding suggests that recombinant structural proteins from heterologous expression have potential as strong and repairable engineering materials.

Computer-aided drug design for AMP-activated protein kinase activators.

PubMed

Wang, Zhanli; Huo, Jianxin; Sun, Lidan; Wang, Yongfu; Jin, Hongwei; Yu, Hui; Zhang, Liangren; Zhou, Lishe

2011-09-01

AMP-activated protein kinase (AMPK) is an important therapeutic target for the potential treatment of metabolic disorders, cardiovascular disease and cancer. Recently, various classes of compounds that activate AMPK by direct or indirect interactions have been reported. The importance of computer-aided drug design approaches in the search for potent activators of AMPK is now established, including structure-based design, ligand-based design, fragment-based design, as well as structural analysis. This review article highlights the computer-aided drug design approaches utilized to discover of activators targeting AMPK. The principles, advantages or limitation of the different methods are also being discussed together with examples of applications taken from the literatures.

Computational design and experimental verification of a symmetric protein homodimer.

PubMed

Mou, Yun; Huang, Po-Ssu; Hsu, Fang-Ciao; Huang, Shing-Jong; Mayo, Stephen L

2015-08-25

Homodimers are the most common type of protein assembly in nature and have distinct features compared with heterodimers and higher order oligomers. Understanding homodimer interactions at the atomic level is critical both for elucidating their biological mechanisms of action and for accurate modeling of complexes of unknown structure. Computation-based design of novel protein-protein interfaces can serve as a bottom-up method to further our understanding of protein interactions. Previous studies have demonstrated that the de novo design of homodimers can be achieved to atomic-level accuracy by β-strand assembly or through metal-mediated interactions. Here, we report the design and experimental characterization of a α-helix-mediated homodimer with C2 symmetry based on a monomeric Drosophila engrailed homeodomain scaffold. A solution NMR structure shows that the homodimer exhibits parallel helical packing similar to the design model. Because the mutations leading to dimer formation resulted in poor thermostability of the system, design success was facilitated by the introduction of independent thermostabilizing mutations into the scaffold. This two-step design approach, function and stabilization, is likely to be generally applicable, especially if the desired scaffold is of low thermostability.

Refolding of proteins from inclusion bodies: rational design and recipes.

PubMed

Basu, Anindya; Li, Xiang; Leong, Susanna Su Jan

2011-10-01

The need to develop protein biomanufacturing platforms that can deliver proteins quickly and cost-effectively is ever more pressing. The rapid rate at which genomes can now be sequenced demands efficient protein production platforms for gene function identification. There is a continued need for the biotech industry to deliver new and more effective protein-based drugs to address new diseases. Bacterial production platforms have the advantage of high expression yields, but insoluble expression of many proteins necessitates the development of diverse and optimised refolding-based processes. Strategies employed to eliminate insoluble expression are reviewed, where it is concluded that inclusion bodies are difficult to eliminate for various reasons. Rational design of refolding systems and recipes are therefore needed to expedite production of recombinant proteins. This review article discusses efforts towards rational design of refolding systems and recipes, which can be guided by the development of refolding screening platforms that yield both qualitative and quantitative information on the progression of a given refolding process. The new opportunities presented by light scattering technologies for developing rational protein refolding buffer systems which in turn can be used to develop new process designs armed with better monitoring and controlling functionalities are discussed. The coupling of dynamic and static light scattering methodologies for incorporation into future bioprocess designs to ensure delivery of high-quality refolded proteins at faster rates is also discussed.

Recent advances in exploiting ionic liquids for biomolecules: Solubility, stability and applications.

PubMed

Sivapragasam, Magaret; Moniruzzaman, Muhammad; Goto, Masahiro

2016-08-01

The technological utility of biomolecules (e.g. proteins, enzymes and DNA) can be significantly enhanced by combining them with ionic liquids (ILs) - potentially attractive "green" and "designer" solvents - rather than using in conventional organic solvents or water. In recent years, ILs have been used as solvents, cosolvents, and reagents for biocatalysis, biotransformation, protein preservation and stabilization, DNA solubilization and stabilization, and other biomolecule-based applications. Using ILs can dramatically enhance the structural and chemical stability of proteins, DNA, and enzymes. This article reviews the recent technological developments of ILs in protein-, enzyme-, and DNA-based applications. We discuss the different routes to increase biomolecule stability and activity in ILs, and the design of biomolecule-friendly ILs that can dissolve biomolecules with minimum alteration to their structure. This information will be helpful to design IL-based processes in biotechnology and the biological sciences that can serve as novel and selective processes for enzymatic reactions, protein and DNA stability, and other biomolecule-based applications. Copyright © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Computational design of a pH-sensitive IgG binding protein.

PubMed

Strauch, Eva-Maria; Fleishman, Sarel J; Baker, David

2014-01-14

Computational design provides the opportunity to program protein-protein interactions for desired applications. We used de novo protein interface design to generate a pH-dependent Fc domain binding protein that buries immunoglobulin G (IgG) His-433. Using next-generation sequencing of naïve and selected pools of a library of design variants, we generated a molecular footprint of the designed binding surface, confirming the binding mode and guiding further optimization of the balance between affinity and pH sensitivity. In biolayer interferometry experiments, the optimized design binds IgG with a Kd of ∼ 4 nM at pH 8.2, and approximately 500-fold more weakly at pH 5.5. The protein is extremely stable, heat-resistant and highly expressed in bacteria, and allows pH-based control of binding for IgG affinity purification and diagnostic devices.

Protein-Protein Docking in Drug Design and Discovery.

PubMed

Kaczor, Agnieszka A; Bartuzi, Damian; Stępniewski, Tomasz Maciej; Matosiuk, Dariusz; Selent, Jana

2018-01-01

Protein-protein interactions (PPIs) are responsible for a number of key physiological processes in the living cells and underlie the pathomechanism of many diseases. Nowadays, along with the concept of so-called "hot spots" in protein-protein interactions, which are well-defined interface regions responsible for most of the binding energy, these interfaces can be targeted with modulators. In order to apply structure-based design techniques to design PPIs modulators, a three-dimensional structure of protein complex has to be available. In this context in silico approaches, in particular protein-protein docking, are a valuable complement to experimental methods for elucidating 3D structure of protein complexes. Protein-protein docking is easy to use and does not require significant computer resources and time (in contrast to molecular dynamics) and it results in 3D structure of a protein complex (in contrast to sequence-based methods of predicting binding interfaces). However, protein-protein docking cannot address all the aspects of protein dynamics, in particular the global conformational changes during protein complex formation. In spite of this fact, protein-protein docking is widely used to model complexes of water-soluble proteins and less commonly to predict structures of transmembrane protein assemblies, including dimers and oligomers of G protein-coupled receptors (GPCRs). In this chapter we review the principles of protein-protein docking, available algorithms and software and discuss the recent examples, benefits, and drawbacks of protein-protein docking application to water-soluble proteins, membrane anchoring and transmembrane proteins, including GPCRs.

A sequence-based hybrid predictor for identifying conformationally ambivalent regions in proteins.

PubMed

Liu, Yu-Cheng; Yang, Meng-Han; Lin, Win-Li; Huang, Chien-Kang; Oyang, Yen-Jen

2009-12-03

Proteins are dynamic macromolecules which may undergo conformational transitions upon changes in environment. As it has been observed in laboratories that protein flexibility is correlated to essential biological functions, scientists have been designing various types of predictors for identifying structurally flexible regions in proteins. In this respect, there are two major categories of predictors. One category of predictors attempts to identify conformationally flexible regions through analysis of protein tertiary structures. Another category of predictors works completely based on analysis of the polypeptide sequences. As the availability of protein tertiary structures is generally limited, the design of predictors that work completely based on sequence information is crucial for advances of molecular biology research. In this article, we propose a novel approach to design a sequence-based predictor for identifying conformationally ambivalent regions in proteins. The novelty in the design stems from incorporating two classifiers based on two distinctive supervised learning algorithms that provide complementary prediction powers. Experimental results show that the overall performance delivered by the hybrid predictor proposed in this article is superior to the performance delivered by the existing predictors. Furthermore, the case study presented in this article demonstrates that the proposed hybrid predictor is capable of providing the biologists with valuable clues about the functional sites in a protein chain. The proposed hybrid predictor provides the users with two optional modes, namely, the high-sensitivity mode and the high-specificity mode. The experimental results with an independent testing data set show that the proposed hybrid predictor is capable of delivering sensitivity of 0.710 and specificity of 0.608 under the high-sensitivity mode, while delivering sensitivity of 0.451 and specificity of 0.787 under the high-specificity mode. Though experimental results show that the hybrid approach designed to exploit the complementary prediction powers of distinctive supervised learning algorithms works more effectively than conventional approaches, there exists a large room for further improvement with respect to the achieved performance. In this respect, it is of interest to investigate the effects of exploiting additional physiochemical properties that are related to conformational ambivalence. Furthermore, it is of interest to investigate the effects of incorporating lately-developed machine learning approaches, e.g. the random forest design and the multi-stage design. As conformational transition plays a key role in carrying out several essential types of biological functions, the design of more advanced predictors for identifying conformationally ambivalent regions in proteins deserves our continuous attention.

Impact of computational structure-based methods on drug discovery.

PubMed

Reynolds, Charles H

2014-01-01

Structure-based drug design has become an indispensible tool in drug discovery. The emergence of structure-based design is due to gains in structural biology that have provided exponential growth in the number of protein crystal structures, new computational algorithms and approaches for modeling protein-ligand interactions, and the tremendous growth of raw computer power in the last 30 years. Computer modeling and simulation have made major contributions to the discovery of many groundbreaking drugs in recent years. Examples are presented that highlight the evolution of computational structure-based design methodology, and the impact of that methodology on drug discovery.

Computational protein design: a review

NASA Astrophysics Data System (ADS)

Coluzza, Ivan

2017-04-01

Proteins are one of the most versatile modular assembling systems in nature. Experimentally, more than 110 000 protein structures have been identified and more are deposited every day in the Protein Data Bank. Such an enormous structural variety is to a first approximation controlled by the sequence of amino acids along the peptide chain of each protein. Understanding how the structural and functional properties of the target can be encoded in this sequence is the main objective of protein design. Unfortunately, rational protein design remains one of the major challenges across the disciplines of biology, physics and chemistry. The implications of solving this problem are enormous and branch into materials science, drug design, evolution and even cryptography. For instance, in the field of drug design an effective computational method to design protein-based ligands for biological targets such as viruses, bacteria or tumour cells, could give a significant boost to the development of new therapies with reduced side effects. In materials science, self-assembly is a highly desired property and soon artificial proteins could represent a new class of designable self-assembling materials. The scope of this review is to describe the state of the art in computational protein design methods and give the reader an outline of what developments could be expected in the near future.

Structure-based design of combinatorial mutagenesis libraries

PubMed Central

Verma, Deeptak; Grigoryan, Gevorg; Bailey-Kellogg, Chris

2015-01-01

The development of protein variants with improved properties (thermostability, binding affinity, catalytic activity, etc.) has greatly benefited from the application of high-throughput screens evaluating large, diverse combinatorial libraries. At the same time, since only a very limited portion of sequence space can be experimentally constructed and tested, an attractive possibility is to use computational protein design to focus libraries on a productive portion of the space. We present a general-purpose method, called “Structure-based Optimization of Combinatorial Mutagenesis” (SOCoM), which can optimize arbitrarily large combinatorial mutagenesis libraries directly based on structural energies of their constituents. SOCoM chooses both positions and substitutions, employing a combinatorial optimization framework based on library-averaged energy potentials in order to avoid explicitly modeling every variant in every possible library. In case study applications to green fluorescent protein, β-lactamase, and lipase A, SOCoM optimizes relatively small, focused libraries whose variants achieve energies comparable to or better than previous library design efforts, as well as larger libraries (previously not designable by structure-based methods) whose variants cover greater diversity while still maintaining substantially better energies than would be achieved by representative random library approaches. By allowing the creation of large-scale combinatorial libraries based on structural calculations, SOCoM promises to increase the scope of applicability of computational protein design and improve the hit rate of discovering beneficial variants. While designs presented here focus on variant stability (predicted by total energy), SOCoM can readily incorporate other structure-based assessments, such as the energy gap between alternative conformational or bound states. PMID:25611189

Solid-phase synthesis and screening of N-acylated polyamine (NAPA) combinatorial libraries for protein binding.

PubMed

Iera, Jaclyn A; Jenkins, Lisa M Miller; Kajiyama, Hiroshi; Kopp, Jeffrey B; Appella, Daniel H

2010-11-15

Inhibitors for protein-protein interactions are challenging to design, in part due to the unique and complex architectures of each protein's interaction domain. Most approaches to develop inhibitors for these interactions rely on rational design, which requires prior structural knowledge of the target and its ligands. In the absence of structural information, a combinatorial approach may be the best alternative to finding inhibitors of a protein-protein interaction. Current chemical libraries, however, consist mostly of molecules designed to inhibit enzymes. In this manuscript, we report the synthesis and screening of a library based on an N-acylated polyamine (NAPA) scaffold that we designed to have specific molecular features necessary to inhibit protein-protein interactions. Screens of the library identified a member with favorable binding properties to the HIV viral protein R (Vpr), a regulatory protein from HIV, that is involved in numerous interactions with other proteins critical for viral replication. Published by Elsevier Ltd.

HYDROGEL-BASED NANOCOMPOSITES OF THERAPEUTIC PROTEINS FOR TISSUE REPAIR

PubMed Central

Zhu, Suwei; Segura, Tatiana

2014-01-01

The ability to design artificial extracellular matrices as cell instructive scaffolds has opened the door to technologies capable of studying cell fates in vitro and to guide tissue repair in vivo. One main component of the design of artificial extracellular matrices is the incorporation of protein-based biochemical cues to guide cell phenotypes and multicellular organizations. However, promoting the long-term bioactivity, controlling the bioavailability and understanding how the physical presentations of these proteins impacts cellular fates are among the challenges of the field. Nanotechnolgy has advanced to meet the challenges of protein therapeutics. For example, the approaches to incorporating proteins into tissue repairing scaffolds have ranged from bulk encapsulations to smart nanodepots that protect proteins from degradations and allow opportunities for controlled release. PMID:24778979

HYDROGEL-BASED NANOCOMPOSITES OF THERAPEUTIC PROTEINS FOR TISSUE REPAIR.

PubMed

Zhu, Suwei; Segura, Tatiana

2014-05-01

The ability to design artificial extracellular matrices as cell instructive scaffolds has opened the door to technologies capable of studying cell fates in vitro and to guide tissue repair in vivo . One main component of the design of artificial extracellular matrices is the incorporation of protein-based biochemical cues to guide cell phenotypes and multicellular organizations. However, promoting the long-term bioactivity, controlling the bioavailability and understanding how the physical presentations of these proteins impacts cellular fates are among the challenges of the field. Nanotechnolgy has advanced to meet the challenges of protein therapeutics. For example, the approaches to incorporating proteins into tissue repairing scaffolds have ranged from bulk encapsulations to smart nanodepots that protect proteins from degradations and allow opportunities for controlled release.

Synthetic beta-solenoid proteins with the fragment-free computational design of a beta-hairpin extension

PubMed Central

MacDonald, James T.; Kabasakal, Burak V.; Godding, David; Kraatz, Sebastian; Henderson, Louie; Barber, James; Freemont, Paul S.; Murray, James W.

2016-01-01

The ability to design and construct structures with atomic level precision is one of the key goals of nanotechnology. Proteins offer an attractive target for atomic design because they can be synthesized chemically or biologically and can self-assemble. However, the generalized protein folding and design problem is unsolved. One approach to simplifying the problem is to use a repetitive protein as a scaffold. Repeat proteins are intrinsically modular, and their folding and structures are better understood than large globular domains. Here, we have developed a class of synthetic repeat proteins based on the pentapeptide repeat family of beta-solenoid proteins. We have constructed length variants of the basic scaffold and computationally designed de novo loops projecting from the scaffold core. The experimentally solved 3.56-Å resolution crystal structure of one designed loop matches closely the designed hairpin structure, showing the computational design of a backbone extension onto a synthetic protein core without the use of backbone fragments from known structures. Two other loop designs were not clearly resolved in the crystal structures, and one loop appeared to be in an incorrect conformation. We have also shown that the repeat unit can accommodate whole-domain insertions by inserting a domain into one of the designed loops. PMID:27573845

CavityPlus: a web server for protein cavity detection with pharmacophore modelling, allosteric site identification and covalent ligand binding ability prediction.

PubMed

Xu, Youjun; Wang, Shiwei; Hu, Qiwan; Gao, Shuaishi; Ma, Xiaomin; Zhang, Weilin; Shen, Yihang; Chen, Fangjin; Lai, Luhua; Pei, Jianfeng

2018-05-10

CavityPlus is a web server that offers protein cavity detection and various functional analyses. Using protein three-dimensional structural information as the input, CavityPlus applies CAVITY to detect potential binding sites on the surface of a given protein structure and rank them based on ligandability and druggability scores. These potential binding sites can be further analysed using three submodules, CavPharmer, CorrSite, and CovCys. CavPharmer uses a receptor-based pharmacophore modelling program, Pocket, to automatically extract pharmacophore features within cavities. CorrSite identifies potential allosteric ligand-binding sites based on motion correlation analyses between cavities. CovCys automatically detects druggable cysteine residues, which is especially useful to identify novel binding sites for designing covalent allosteric ligands. Overall, CavityPlus provides an integrated platform for analysing comprehensive properties of protein binding cavities. Such analyses are useful for many aspects of drug design and discovery, including target selection and identification, virtual screening, de novo drug design, and allosteric and covalent-binding drug design. The CavityPlus web server is freely available at http://repharma.pku.edu.cn/cavityplus or http://www.pkumdl.cn/cavityplus.

Computational redesign of a protein-protein interface for high affinity and binding specificity using modular architecture and naturally occurring template fragments.

PubMed

Potapov, V; Reichmann, D; Abramovich, R; Filchtinski, D; Zohar, N; Ben Halevy, D; Edelman, M; Sobolev, V; Schreiber, G

2008-12-05

A new method is presented for the redesign of protein-protein interfaces, resulting in specificity of the designed pair while maintaining high affinity. The design is based on modular interface architecture and was carried out on the interaction between TEM1 beta-lactamase and its inhibitor protein, beta-lactamase inhibitor protein. The interface between these two proteins is composed of several mostly independent modules. We previously showed that it is possible to delete a complete module without affecting the overall structure of the interface. Here, we replace a complete module with structure fragments taken from nonrelated proteins. Nature-optimized fragments were chosen from 10(7) starting templates found in the Protein Data Bank. A procedure was then developed to identify sets of interacting template residues with a backbone arrangement mimicking the original module. This generated a final list of 361 putative replacement modules that were ranked using a novel scoring function based on grouped atom-atom contact surface areas. The top-ranked designed complex exhibited an affinity of at least the wild-type level and a mode of binding that was remarkably specific despite the absence of negative design in the procedure. In retrospect, the combined application of three factors led to the success of the design approach: utilizing the modular construction of the interface, capitalizing on native rather than artificial templates, and ranking with an accurate atom-atom contact surface scoring function.

Structure-based drug design for G protein-coupled receptors.

PubMed

Congreve, Miles; Dias, João M; Marshall, Fiona H

2014-01-01

Our understanding of the structural biology of G protein-coupled receptors has undergone a transformation over the past 5 years. New protein-ligand complexes are described almost monthly in high profile journals. Appreciation of how small molecules and natural ligands bind to their receptors has the potential to impact enormously how medicinal chemists approach this major class of receptor targets. An outline of the key topics in this field and some recent examples of structure- and fragment-based drug design are described. A table is presented with example views of each G protein-coupled receptor for which there is a published X-ray structure, including interactions with small molecule antagonists, partial and full agonists. The possible implications of these new data for drug design are discussed. © 2014 Elsevier B.V. All rights reserved.

A critical analysis of computational protein design with sparse residue interaction graphs

PubMed Central

Georgiev, Ivelin S.

2017-01-01

Protein design algorithms enumerate a combinatorial number of candidate structures to compute the Global Minimum Energy Conformation (GMEC). To efficiently find the GMEC, protein design algorithms must methodically reduce the conformational search space. By applying distance and energy cutoffs, the protein system to be designed can thus be represented using a sparse residue interaction graph, where the number of interacting residue pairs is less than all pairs of mutable residues, and the corresponding GMEC is called the sparse GMEC. However, ignoring some pairwise residue interactions can lead to a change in the energy, conformation, or sequence of the sparse GMEC vs. the original or the full GMEC. Despite the widespread use of sparse residue interaction graphs in protein design, the above mentioned effects of their use have not been previously analyzed. To analyze the costs and benefits of designing with sparse residue interaction graphs, we computed the GMECs for 136 different protein design problems both with and without distance and energy cutoffs, and compared their energies, conformations, and sequences. Our analysis shows that the differences between the GMECs depend critically on whether or not the design includes core, boundary, or surface residues. Moreover, neglecting long-range interactions can alter local interactions and introduce large sequence differences, both of which can result in significant structural and functional changes. Designs on proteins with experimentally measured thermostability show it is beneficial to compute both the full and the sparse GMEC accurately and efficiently. To this end, we show that a provable, ensemble-based algorithm can efficiently compute both GMECs by enumerating a small number of conformations, usually fewer than 1000. This provides a novel way to combine sparse residue interaction graphs with provable, ensemble-based algorithms to reap the benefits of sparse residue interaction graphs while avoiding their potential inaccuracies. PMID:28358804

cOSPREY: A Cloud-Based Distributed Algorithm for Large-Scale Computational Protein Design

PubMed Central

Pan, Yuchao; Dong, Yuxi; Zhou, Jingtian; Hallen, Mark; Donald, Bruce R.; Xu, Wei

2016-01-01

Abstract Finding the global minimum energy conformation (GMEC) of a huge combinatorial search space is the key challenge in computational protein design (CPD) problems. Traditional algorithms lack a scalable and efficient distributed design scheme, preventing researchers from taking full advantage of current cloud infrastructures. We design cloud OSPREY (cOSPREY), an extension to a widely used protein design software OSPREY, to allow the original design framework to scale to the commercial cloud infrastructures. We propose several novel designs to integrate both algorithm and system optimizations, such as GMEC-specific pruning, state search partitioning, asynchronous algorithm state sharing, and fault tolerance. We evaluate cOSPREY on three different cloud platforms using different technologies and show that it can solve a number of large-scale protein design problems that have not been possible with previous approaches. PMID:27154509

Integrating structure-based and ligand-based approaches for computational drug design.

PubMed

Wilson, Gregory L; Lill, Markus A

2011-04-01

Methods utilized in computer-aided drug design can be classified into two major categories: structure based and ligand based, using information on the structure of the protein or on the biological and physicochemical properties of bound ligands, respectively. In recent years there has been a trend towards integrating these two methods in order to enhance the reliability and efficiency of computer-aided drug-design approaches by combining information from both the ligand and the protein. This trend resulted in a variety of methods that include: pseudoreceptor methods, pharmacophore methods, fingerprint methods and approaches integrating docking with similarity-based methods. In this article, we will describe the concepts behind each method and selected applications.

Design, production and molecular structure of a new family of artificial alpha-helicoidal repeat proteins (αRep) based on thermostable HEAT-like repeats.

PubMed

Urvoas, Agathe; Guellouz, Asma; Valerio-Lepiniec, Marie; Graille, Marc; Durand, Dominique; Desravines, Danielle C; van Tilbeurgh, Herman; Desmadril, Michel; Minard, Philippe

2010-11-26

Repeat proteins have a modular organization and a regular architecture that make them attractive models for design and directed evolution experiments. HEAT repeat proteins, although very common, have not been used as a scaffold for artificial proteins, probably because they are made of long and irregular repeats. Here, we present and validate a consensus sequence for artificial HEAT repeat proteins. The sequence was defined from the structure-based sequence analysis of a thermostable HEAT-like repeat protein. Appropriate sequences were identified for the N- and C-caps. A library of genes coding for artificial proteins based on this sequence design, named αRep, was assembled using new and versatile methodology based on circular amplification. Proteins picked randomly from this library are expressed as soluble proteins. The biophysical properties of proteins with different numbers of repeats and different combinations of side chains in hypervariable positions were characterized. Circular dichroism and differential scanning calorimetry experiments showed that all these proteins are folded cooperatively and are very stable (T(m) >70 °C). Stability of these proteins increases with the number of repeats. Detailed gel filtration and small-angle X-ray scattering studies showed that the purified proteins form either monomers or dimers. The X-ray structure of a stable dimeric variant structure was solved. The protein is folded with a highly regular topology and the repeat structure is organized, as expected, as pairs of alpha helices. In this protein variant, the dimerization interface results directly from the variable surface enriched in aromatic residues located in the randomized positions of the repeats. The dimer was crystallized both in an apo and in a PEG-bound form, revealing a very well defined binding crevice and some structure flexibility at the interface. This fortuitous binding site could later prove to be a useful binding site for other low molecular mass partners. Copyright © 2010 Elsevier Ltd. All rights reserved.

Rosetta:MSF: a modular framework for multi-state computational protein design.

PubMed

Löffler, Patrick; Schmitz, Samuel; Hupfeld, Enrico; Sterner, Reinhard; Merkl, Rainer

2017-06-01

Computational protein design (CPD) is a powerful technique to engineer existing proteins or to design novel ones that display desired properties. Rosetta is a software suite including algorithms for computational modeling and analysis of protein structures and offers many elaborate protocols created to solve highly specific tasks of protein engineering. Most of Rosetta's protocols optimize sequences based on a single conformation (i. e. design state). However, challenging CPD objectives like multi-specificity design or the concurrent consideration of positive and negative design goals demand the simultaneous assessment of multiple states. This is why we have developed the multi-state framework MSF that facilitates the implementation of Rosetta's single-state protocols in a multi-state environment and made available two frequently used protocols. Utilizing MSF, we demonstrated for one of these protocols that multi-state design yields a 15% higher performance than single-state design on a ligand-binding benchmark consisting of structural conformations. With this protocol, we designed de novo nine retro-aldolases on a conformational ensemble deduced from a (βα)8-barrel protein. All variants displayed measurable catalytic activity, testifying to a high success rate for this concept of multi-state enzyme design.

Rosetta:MSF: a modular framework for multi-state computational protein design

PubMed Central

Hupfeld, Enrico; Sterner, Reinhard

2017-01-01

Computational protein design (CPD) is a powerful technique to engineer existing proteins or to design novel ones that display desired properties. Rosetta is a software suite including algorithms for computational modeling and analysis of protein structures and offers many elaborate protocols created to solve highly specific tasks of protein engineering. Most of Rosetta’s protocols optimize sequences based on a single conformation (i. e. design state). However, challenging CPD objectives like multi-specificity design or the concurrent consideration of positive and negative design goals demand the simultaneous assessment of multiple states. This is why we have developed the multi-state framework MSF that facilitates the implementation of Rosetta’s single-state protocols in a multi-state environment and made available two frequently used protocols. Utilizing MSF, we demonstrated for one of these protocols that multi-state design yields a 15% higher performance than single-state design on a ligand-binding benchmark consisting of structural conformations. With this protocol, we designed de novo nine retro-aldolases on a conformational ensemble deduced from a (βα)8-barrel protein. All variants displayed measurable catalytic activity, testifying to a high success rate for this concept of multi-state enzyme design. PMID:28604768

Hydrogel Biomaterials: A Smart Future?

PubMed Central

Kopeček, Jindřich

2007-01-01

Hydrogels were the first biomaterials developed for human use. The state-of-the-art and potential for the future are discussed. Recently, new designs have produced mechanically strong synthetic hydrogels. Protein based hydrogels and hybrid hydrogels containing protein domains present a novel advance; such biomaterials may self-assemble from block or graft copolymers containing biorecognition domains. One of the domains, the coiled-coil, ubiquitously found in nature, has been used as an example to demonstrate the developments in the design of smart hydrogels. The application potential of synthetic, protein-based, DNA-based, and hybrid hydrogels bodes well for the future of this class of biomaterials. PMID:17697712

Structure-Based Design of Highly Selective Inhibitors of the CREB Binding Protein Bromodomain.

PubMed

Denny, R Aldrin; Flick, Andrew C; Coe, Jotham; Langille, Jonathan; Basak, Arindrajit; Liu, Shenping; Stock, Ingrid; Sahasrabudhe, Parag; Bonin, Paul; Hay, Duncan A; Brennan, Paul E; Pletcher, Mathew; Jones, Lyn H; Chekler, Eugene L Piatnitski

2017-07-13

Chemical probes are required for preclinical target validation to interrogate novel biological targets and pathways. Selective inhibitors of the CREB binding protein (CREBBP)/EP300 bromodomains are required to facilitate the elucidation of biology associated with these important epigenetic targets. Medicinal chemistry optimization that paid particular attention to physiochemical properties delivered chemical probes with desirable potency, selectivity, and permeability attributes. An important feature of the optimization process was the successful application of rational structure-based drug design to address bromodomain selectivity issues (particularly against the structurally related BRD4 protein).

Isotachophoresis-Based Surface Immunoassay.

PubMed

Paratore, Federico; Zeidman Kalman, Tal; Rosenfeld, Tally; Kaigala, Govind V; Bercovici, Moran

2017-07-18

In the absence of amplification methods for proteins, the immune-detection of low-abundance proteins using antibodies is fundamentally limited by binding kinetic rates. Here, we present a new class of surface-based immunoassays in which protein-antibody reaction is accelerated by isotachophoresis (ITP). We demonstrate the use of ITP to preconcentrate and deliver target proteins to a surface decorated with specific antibodies, where effective utilization of the focused sample is achieved by modulating the driving electric field (stop-and-diffuse ITP mode) or applying a counter flow that opposes the ITP motion (counterflow ITP mode). Using enhanced green fluorescent protein (EGFP) as a model protein, we carry out an experimental optimization of the ITP-based immunoassay and demonstrate a 1300-fold improvement in limit of detection compared to a standard immunoassay, in a 6 min protein-antibody reaction. We discuss the design of buffer chemistries for other protein systems and, in concert with experiments, provide full analytical solutions for the two operation modes, elucidating the interplay between reaction, diffusion, and accumulation time scales and enabling the prediction and design of future immunoassays.

Imparting albumin-binding affinity to a human protein by mimicking the contact surface of a bacterial binding protein.

PubMed

Oshiro, Satoshi; Honda, Shinya

2014-04-18

Attachment of a bacterial albumin-binding protein module is an attractive strategy for extending the plasma residence time of protein therapeutics. However, a protein fused with such a bacterial module could induce unfavorable immune reactions. To address this, we designed an alternative binding protein by imparting albumin-binding affinity to a human protein using molecular surface grafting. The result was a series of human-derived 6 helix-bundle proteins, one of which specifically binds to human serum albumin (HSA) with adequate affinity (KD = 100 nM). The proteins were designed by transferring key binding residues of a bacterial albumin-binding module, Finegoldia magna protein G-related albumin-binding domain (GA) module, onto the human protein scaffold. Despite 13-15 mutations, the designed proteins maintain the original secondary structure by virtue of careful grafting based on structural informatics. Competitive binding assays and thermodynamic analyses of the best binders show that the binding mode resembles that of the GA module, suggesting that the contacting surface of the GA module is mimicked well on the designed protein. These results indicate that the designed protein may act as an alternative low-risk binding module to HSA. Furthermore, molecular surface grafting in combination with structural informatics is an effective approach for avoiding deleterious mutations on a target protein and for imparting the binding function of one protein onto another.

New strategy for protein interactions and application to structure-based drug design

NASA Astrophysics Data System (ADS)

Zou, Xiaoqin

One of the greatest challenges in computational biophysics is to predict interactions between biological molecules, which play critical roles in biological processes and rational design of therapeutic drugs. Biomolecular interactions involve delicate interplay between multiple interactions, including electrostatic interactions, van der Waals interactions, solvent effect, and conformational entropic effect. Accurate determination of these complex and subtle interactions is challenging. Moreover, a biological molecule such as a protein usually consists of thousands of atoms, and thus occupies a huge conformational space. The large degrees of freedom pose further challenges for accurate prediction of biomolecular interactions. Here, I will present our development of physics-based theory and computational modeling on protein interactions with other molecules. The major strategy is to extract microscopic energetics from the information embedded in the experimentally-determined structures of protein complexes. I will also present applications of the methods to structure-based therapeutic design. Supported by NSF CAREER Award DBI-0953839, NIH R01GM109980, and the American Heart Association (Midwest Affiliate) [13GRNT16990076].

DESIGN, SYNTHESIS, AND APPLICATION OF THE TRIMETHOPRIM-BASED CHEMICAL TAG FOR LIVE CELL IMAGING

PubMed Central

Jing, Chaoran; Cornish, Virginia W.

2013-01-01

Over the past decade chemical tags have been developed to complement the use of fluorescent proteins in live cell imaging. Chemical tags retain the specificity of protein labeling achieved with fluorescent proteins through genetic encoding, but provide smaller, more robust tags and modular use of organic fluorophores with high photon-output and tailored functionalities. The trimethoprim-based chemical tag (TMP-tag) was initially developed based on the high affinity interaction between E.coli dihydrofolatereductase and the antibiotic trimethoprim and subsequently rendered covalent and fluorogenic via proximity-induced protein labeling reactions. To date, the TMP-tag is one of the few chemical tags that enable intracellular protein labeling and high-resolution live cell imaging. Here we describe the general design, chemical synthesis, and application of TMP-tag for live cell imaging. Alternative protocols for synthesizing and using the covalent and the fluorogenic TMP-tags are also included. PMID:23839994

Design of Bioinorganic Materials at the Interface of Coordination and Biosupramolecular Chemistry.

PubMed

Maity, Basudev; Ueno, Takafumi

2017-04-01

Protein assemblies have recently become known as potential molecular scaffolds for applications in materials science and bio-nanotechnology. Efforts to design protein assemblies for construction of protein-based hybrid materials with metal ions, metal complexes, nanomaterials and proteins now represent a growing field with a common aim of providing novel functions and mimicking natural functions. However, the important roles of protein assemblies in coordination and biosupramolecular chemistry have not been systematically investigated and characterized. In this personal account, we focus on our recent progress in rational design of protein assemblies using bioinorganic chemistry for (1) exploration of unnatural reactions, (2) construction of functional protein architectures, and (3) in vivo applications. © 2017 The Chemical Society of Japan & Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

StaRProtein, A Web Server for Prediction of the Stability of Repeat Proteins

PubMed Central

Xu, Yongtao; Zhou, Xu; Huang, Meilan

2015-01-01

Repeat proteins have become increasingly important due to their capability to bind to almost any proteins and the potential as alternative therapy to monoclonal antibodies. In the past decade repeat proteins have been designed to mediate specific protein-protein interactions. The tetratricopeptide and ankyrin repeat proteins are two classes of helical repeat proteins that form different binding pockets to accommodate various partners. It is important to understand the factors that define folding and stability of repeat proteins in order to prioritize the most stable designed repeat proteins to further explore their potential binding affinities. Here we developed distance-dependant statistical potentials using two classes of alpha-helical repeat proteins, tetratricopeptide and ankyrin repeat proteins respectively, and evaluated their efficiency in predicting the stability of repeat proteins. We demonstrated that the repeat-specific statistical potentials based on these two classes of repeat proteins showed paramount accuracy compared with non-specific statistical potentials in: 1) discriminate correct vs. incorrect models 2) rank the stability of designed repeat proteins. In particular, the statistical scores correlate closely with the equilibrium unfolding free energies of repeat proteins and therefore would serve as a novel tool in quickly prioritizing the designed repeat proteins with high stability. StaRProtein web server was developed for predicting the stability of repeat proteins. PMID:25807112

Model-based high-throughput design of ion exchange protein chromatography.

PubMed

Khalaf, Rushd; Heymann, Julia; LeSaout, Xavier; Monard, Florence; Costioli, Matteo; Morbidelli, Massimo

2016-08-12

This work describes the development of a model-based high-throughput design (MHD) tool for the operating space determination of a chromatographic cation-exchange protein purification process. Based on a previously developed thermodynamic mechanistic model, the MHD tool generates a large amount of system knowledge and thereby permits minimizing the required experimental workload. In particular, each new experiment is designed to generate information needed to help refine and improve the model. Unnecessary experiments that do not increase system knowledge are avoided. Instead of aspiring to a perfectly parameterized model, the goal of this design tool is to use early model parameter estimates to find interesting experimental spaces, and to refine the model parameter estimates with each new experiment until a satisfactory set of process parameters is found. The MHD tool is split into four sections: (1) prediction, high throughput experimentation using experiments in (2) diluted conditions and (3) robotic automated liquid handling workstations (robotic workstation), and (4) operating space determination and validation. (1) Protein and resin information, in conjunction with the thermodynamic model, is used to predict protein resin capacity. (2) The predicted model parameters are refined based on gradient experiments in diluted conditions. (3) Experiments on the robotic workstation are used to further refine the model parameters. (4) The refined model is used to determine operating parameter space that allows for satisfactory purification of the protein of interest on the HPLC scale. Each section of the MHD tool is used to define the adequate experimental procedures for the next section, thus avoiding any unnecessary experimental work. We used the MHD tool to design a polishing step for two proteins, a monoclonal antibody and a fusion protein, on two chromatographic resins, in order to demonstrate it has the ability to strongly accelerate the early phases of process development. Copyright © 2016 Elsevier B.V. All rights reserved.

Distilling the essential features of a protein surface for improving protein-ligand docking, scoring, and virtual screening

NASA Astrophysics Data System (ADS)

Zavodszky, Maria I.; Sanschagrin, Paul C.; Kuhn, Leslie A.; Korde, Rajesh S.

2002-12-01

For the successful identification and docking of new ligands to a protein target by virtual screening, the essential features of the protein and ligand surfaces must be captured and distilled in an efficient representation. Since the running time for docking increases exponentially with the number of points representing the protein and each ligand candidate, it is important to place these points where the best interactions can be made between the protein and the ligand. This definition of favorable points of interaction can also guide protein structure-based ligand design, which typically focuses on which chemical groups provide the most energetically favorable contacts. In this paper, we present an alternative method of protein template and ligand interaction point design that identifies the most favorable points for making hydrophobic and hydrogen-bond interactions by using a knowledge base. The knowledge-based protein and ligand representations have been incorporated in version 2.0 of SLIDE and resulted in dockings closer to the crystal structure orientations when screening a set of 57 known thrombin and glutathione S-transferase (GST) ligands against the apo structures of these proteins. There was also improved scoring enrichment of the dockings, meaning better differentiation between the chemically diverse known ligands and a ˜15,000-molecule dataset of randomly-chosen small organic molecules. This approach for identifying the most important points of interaction between proteins and their ligands can equally well be used in other docking and design techniques. While much recent effort has focused on improving scoring functions for protein-ligand docking, our results indicate that improving the representation of the chemistry of proteins and their ligands is another avenue that can lead to significant improvements in the identification, docking, and scoring of ligands.

BcL-xL Conformational Changes upon Fragment Binding Revealed by NMR

PubMed Central

Aguirre, Clémentine; ten Brink, Tim; Walker, Olivier; Guillière, Florence; Davesne, Dany; Krimm, Isabelle

2013-01-01

Protein-protein interactions represent difficult but increasingly important targets for the design of therapeutic compounds able to interfere with biological processes. Recently, fragment-based strategies have been proposed as attractive approaches for the elaboration of protein-protein surface inhibitors from fragment-like molecules. One major challenge in targeting protein-protein interactions is related to the structural adaptation of the protein surface upon molecular recognition. Methods capable of identifying subtle conformational changes of proteins upon fragment binding are therefore required at the early steps of the drug design process. In this report we present a fast NMR method able to probe subtle conformational changes upon fragment binding. The approach relies on the comparison of experimental fragment-induced Chemical Shift Perturbation (CSP) of amine protons to CSP simulated for a set of docked fragment poses, considering the ring-current effect from fragment binding. We illustrate the method by the retrospective analysis of the complex between the anti-apoptotic Bcl-xL protein and the fragment 4′-fluoro-[1,1′-biphenyl]-4-carboxylic acid that was previously shown to bind one of the Bcl-xL hot spots. The CSP-based approach shows that the protein undergoes a subtle conformational rearrangement upon interaction, for residues located in helices 2, 3 and the very beginning of 5. Our observations are corroborated by residual dipolar coupling measurements performed on the free and fragment-bound forms of the Bcl-xL protein. These NMR-based results are in total agreement with previous molecular dynamic calculations that evidenced a high flexibility of Bcl-xL around the binding site. Here we show that CSP of protein amine protons are useful and reliable structural probes. Therefore, we propose to use CSP simulation to assess protein conformational changes upon ligand binding in the fragment-based drug design approach. PMID:23717610

The simulation study of protein-protein interfaces based on the 4-helix bundle structure

NASA Astrophysics Data System (ADS)

Fukuda, Masaki; Komatsu, Yu; Morikawa, Ryota; Miyakawa, Takeshi; Takasu, Masako; Akanuma, Satoshi; Yamagishi, Akihiko

2013-02-01

Docking of two protein molecules is induced by intermolecular interactions. Our purposes in this study are: designing binding interfaces on the two proteins, which specifically interact to each other; and inducing intermolecular interactions between the two proteins by mixing them. A 4-helix bundle structure was chosen as a scaffold on which binding interfaces were created. Based on this scaffold, we designed binding interfaces involving charged and nonpolar amino acid residues. We performed molecular dynamics (MD) simulation to identify suitable amino acid residues for the interfaces. We chose YciF protein as the scaffold for the protein-protein docking simulation. We observed the structure of two YciF protein molecules (I and II), and we calculated the distance between centroids (center of gravity) of the interfaces' surface planes of the molecules I and II. We found that the docking of the two protein molecules can be controlled by the number of hydrophobic and charged amino acid residues involved in the interfaces. Existence of six hydrophobic and five charged amino acid residues within an interface were most suitable for the protein-protein docking.

Molecular and Cellular Mechanisms for the Interaction between Gold Nanoparticles and Neuroimmune Cells Based on Size, Shape, and Charge

DTIC Science & Technology

2014-04-25

IgG secretion. 2.3 Designing of Synthetic peptide The immunogenic peptides against the foot and mouth disease virus ( FMDV ) were designed and...synthesized based on viral protein 1 of type O FMDV . The amino acid sequence for pFMDV is NGSSKYGDTSTNNVRGDLQVLAQKAERTLC. An extra cysteine was added...peptides were synthesized based on the amino acid sequence of the VP1 coat protein of the FMDV (table 1). The peptide pFMDVD (19 amino acids in length

"Print-n-Shrink" technology for the rapid production of microfluidic chips and protein microarrays.

PubMed

Sollier, Kevin; Mandon, Céline A; Heyries, Kevin A; Blum, Loïc J; Marquette, Christophe A

2009-12-21

An innovative method for the production of microfluidic chips integrating protein spots is described. The technology, called "Print-n-Shrink", is based on the screen-printing of a microfluidic design (using a dielectric ink) onto Polyshrink polystyrene sheets. The initial print which has a minimum size of 15 microm (height) x 230 microm (width) is thermally treated (30 seconds, 163 degrees C) to shrink and generate features of 85 microm (height) x 100 microm (width). Concomitantly, proteins such as monoclonal antibodies or cellular adhesion proteins are spotted onto the Polyshrink sheets and shrunk together with the microfluidic design, creating a complete biochip integrating both complex microfluidic designs and protein spots for bioanalytical applications.

Artificial enzymes with protein scaffolds: structural design and modification.

PubMed

Matsuo, Takashi; Hirota, Shun

2014-10-15

Recent development in biochemical experiment techniques and bioinformatics has enabled us to create a variety of artificial biocatalysts with protein scaffolds (namely 'artificial enzymes'). The construction methods of these catalysts include genetic mutation, chemical modification using synthetic molecules and/or a combination of these methods. Designed evolution strategy based on the structural information of host proteins has become more and more popular as an effective approach to construct artificial protein-based biocatalysts with desired reactivities. From the viewpoint of application of artificial enzymes for organic synthesis, recently constructed artificial enzymes mediating oxidation, reduction and C-C bond formation/cleavage are introduced in this review article. Copyright © 2014 Elsevier Ltd. All rights reserved.

Accurate computational design of multipass transmembrane proteins.

PubMed

Lu, Peilong; Min, Duyoung; DiMaio, Frank; Wei, Kathy Y; Vahey, Michael D; Boyken, Scott E; Chen, Zibo; Fallas, Jorge A; Ueda, George; Sheffler, William; Mulligan, Vikram Khipple; Xu, Wenqing; Bowie, James U; Baker, David

2018-03-02

The computational design of transmembrane proteins with more than one membrane-spanning region remains a major challenge. We report the design of transmembrane monomers, homodimers, trimers, and tetramers with 76 to 215 residue subunits containing two to four membrane-spanning regions and up to 860 total residues that adopt the target oligomerization state in detergent solution. The designed proteins localize to the plasma membrane in bacteria and in mammalian cells, and magnetic tweezer unfolding experiments in the membrane indicate that they are very stable. Crystal structures of the designed dimer and tetramer-a rocket-shaped structure with a wide cytoplasmic base that funnels into eight transmembrane helices-are very close to the design models. Our results pave the way for the design of multispan membrane proteins with new functions. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Protein based Block Copolymers

PubMed Central

Rabotyagova, Olena S.; Cebe, Peggy; Kaplan, David L.

2011-01-01

Advances in genetic engineering have led to the synthesis of protein-based block copolymers with control of chemistry and molecular weight, resulting in unique physical and biological properties. The benefits from incorporating peptide blocks into copolymer designs arise from the fundamental properties of proteins to adopt ordered conformations and to undergo self-assembly, providing control over structure formation at various length scales when compared to conventional block copolymers. This review covers the synthesis, structure, assembly, properties, and applications of protein-based block copolymers. PMID:21235251

Redesign of LAOBP to bind novel l-amino acid ligands.

PubMed

Banda-Vázquez, Jesús; Shanmugaratnam, Sooruban; Rodríguez-Sotres, Rogelio; Torres-Larios, Alfredo; Höcker, Birte; Sosa-Peinado, Alejandro

2018-05-01

Computational protein design is still a challenge for advancing structure-function relationships. While recent advances in this field are promising, more information for genuine predictions is needed. Here, we discuss different approaches applied to install novel glutamine (Gln) binding into the Lysine/Arginine/Ornithine binding protein (LAOBP) from Salmonella typhimurium. We studied the ligand binding behavior of two mutants: a binding pocket grafting design based on a structural superposition of LAOBP to the Gln binding protein QBP from Escherichia coli and a design based on statistical coupled positions. The latter showed the ability to bind Gln even though the protein was not very stable. Comparison of both approaches highlighted a nonconservative shared point mutation between LAOBP_graft and LAOBP_sca. This context dependent L117K mutation in LAOBP turned out to be sufficient for introducing Gln binding, as confirmed by different experimental techniques. Moreover, the crystal structure of LAOBP_L117K in complex with its ligand is reported. © 2018 The Protein Society.

GREEN: A program package for docking studies in rational drug design

NASA Astrophysics Data System (ADS)

Tomioka, Nobuo; Itai, Akiko

1994-08-01

A program package, GREEN, has been developed that enables docking studies between ligand molecules and a protein molecule. Based on the structure of the protein molecule, the physical and chemical environment of the ligand-binding site is expressed as three-dimensional grid-point data. The grid-point data are used for the real-time evaluation of the protein-ligand interaction energy, as well as for the graphical representation of the binding-site environment. The interactive docking operation is facilitated by various built-in functions, such as energy minimization, energy contribution analysis and logging of the manipulation trajectory. Interactive modeling functions are incorporated for designing new ligand molecules while considering the binding-site environment and the protein-ligand interaction. As an example of the application of GREEN, a docking study is presented on the complex between trypsin and a synthetic trypsin inhibitor. The program package will be useful for rational drug design, based on the 3D structure of the target protein.

Design of protein switches based on an ensemble model of allostery.

PubMed

Choi, Jay H; Laurent, Abigail H; Hilser, Vincent J; Ostermeier, Marc

2015-04-22

Switchable proteins that can be regulated through exogenous or endogenous inputs have a broad range of biotechnological and biomedical applications. Here we describe the design of switchable enzymes based on an ensemble allosteric model. First, we insert an enzyme domain into an effector-binding domain such that both domains remain functionally intact. Second, we induce the fusion to behave as a switch through the introduction of conditional conformational flexibility designed to increase the conformational entropy of the enzyme domain in a temperature- or pH-dependent fashion. We confirm the switching behaviour in vitro and in vivo. Structural and thermodynamic studies support the hypothesis that switching result from an increase in conformational entropy of the enzyme domain in the absence of effector. These results support the ensemble model of allostery and embody a strategy for the design of protein switches.

Optimizing Associative Experimental Design for Protein Crystallization Screening

PubMed Central

Dinç, Imren; Pusey, Marc L.; Aygün, Ramazan S.

2016-01-01

The goal of protein crystallization screening is the determination of the main factors of importance to crystallizing the protein under investigation. One of the major issues about determining these factors is that screening is often expanded to many hundreds or thousands of conditions to maximize combinatorial chemical space coverage for maximizing the chances of a successful (crystalline) outcome. In this paper, we propose an experimental design method called “Associative Experimental Design (AED)” and an optimization method includes eliminating prohibited combinations and prioritizing reagents based on AED analysis of results from protein crystallization experiments. AED generates candidate cocktails based on these initial screening results. These results are analyzed to determine those screening factors in chemical space that are most likely to lead to higher scoring outcomes, crystals. We have tested AED on three proteins derived from the hyperthermophile Thermococcus thioreducens, and we applied an optimization method to these proteins. Our AED method generated novel cocktails (count provided in parentheses) leading to crystals for three proteins as follows: Nucleoside diphosphate kinase (4), HAD superfamily hydrolase (2), Nucleoside kinase (1). After getting promising results, we have tested our optimization method on four different proteins. The AED method with optimization yielded 4, 3, and 20 crystalline conditions for holo Human Transferrin, archaeal exosome protein, and Nucleoside diphosphate kinase, respectively. PMID:26955046

Computational Redesign of Thioredoxin Is Hypersensitive toward Minor Conformational Changes in the Backbone Template

PubMed Central

Christensen, Signe; Horowitz, Scott; Bardwell, James C.A.; Olsen, Johan G.; Willemoës, Martin; Lindorff-Larsen, Kresten; Ferkinghoff-Borg, Jesper; Hamelryck, Thomas; Winther, Jakob R.

2017-01-01

Despite the development of powerful computational tools, the full-sequence design of proteins still remains a challenging task. To investigate the limits and capabilities of computational tools, we conducted a study of the ability of the program Rosetta to predict sequences that recreate the authentic fold of thioredoxin. Focusing on the influence of conformational details in the template structures, we based our study on 8 experimentally determined template structures and generated 120 designs from each. For experimental evaluation, we chose six sequences from each of the eight templates by objective criteria. The 48 selected sequences were evaluated based on their progressive ability to (1) produce soluble protein in Escherichia coli and (2) yield stable monomeric protein, and (3) on the ability of the stable, soluble proteins to adopt the target fold. Of the 48 designs, we were able to synthesize 32, 20 of which resulted in soluble protein. Of these, only two were sufficiently stable to be purified. An X-ray crystal structure was solved for one of the designs, revealing a close resemblance to the target structure. We found a significant difference among the eight template structures to realize the above three criteria despite their high structural similarity. Thus, in order to improve the success rate of computational full-sequence design methods, we recommend that multiple template structures are used. Furthermore, this study shows that special care should be taken when optimizing the geometry of a structure prior to computational design when using a method that is based on rigid conformations. PMID:27659562

Computational Redesign of Thioredoxin Is Hypersensitive toward Minor Conformational Changes in the Backbone Template.

PubMed

Johansson, Kristoffer E; Tidemand Johansen, Nicolai; Christensen, Signe; Horowitz, Scott; Bardwell, James C A; Olsen, Johan G; Willemoës, Martin; Lindorff-Larsen, Kresten; Ferkinghoff-Borg, Jesper; Hamelryck, Thomas; Winther, Jakob R

2016-10-23

Despite the development of powerful computational tools, the full-sequence design of proteins still remains a challenging task. To investigate the limits and capabilities of computational tools, we conducted a study of the ability of the program Rosetta to predict sequences that recreate the authentic fold of thioredoxin. Focusing on the influence of conformational details in the template structures, we based our study on 8 experimentally determined template structures and generated 120 designs from each. For experimental evaluation, we chose six sequences from each of the eight templates by objective criteria. The 48 selected sequences were evaluated based on their progressive ability to (1) produce soluble protein in Escherichia coli and (2) yield stable monomeric protein, and (3) on the ability of the stable, soluble proteins to adopt the target fold. Of the 48 designs, we were able to synthesize 32, 20 of which resulted in soluble protein. Of these, only two were sufficiently stable to be purified. An X-ray crystal structure was solved for one of the designs, revealing a close resemblance to the target structure. We found a significant difference among the eight template structures to realize the above three criteria despite their high structural similarity. Thus, in order to improve the success rate of computational full-sequence design methods, we recommend that multiple template structures are used. Furthermore, this study shows that special care should be taken when optimizing the geometry of a structure prior to computational design when using a method that is based on rigid conformations. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Structures of Life

ERIC Educational Resources Information Center

National Institute of General Medical Sciences (NIGMS), 2007

2007-01-01

This booklet reveals how structural biology provides insight into health and disease and is useful in developing new medications. It contains a general introduction to proteins, coverage of the techniques used to determine protein structures, and a chapter on structure-based drug design. The booklet features "Student Snapshots," designed to…

Protein-only, antimicrobial peptide-containing recombinant nanoparticles with inherent built-in antibacterial activity.

PubMed

Serna, Naroa; Sánchez-García, Laura; Sánchez-Chardi, Alejandro; Unzueta, Ugutz; Roldán, Mónica; Mangues, Ramón; Vázquez, Esther; Villaverde, Antonio

2017-09-15

The emergence of bacterial antibiotic resistances is a serious concern in human and animal health. In this context, naturally occurring cationic antimicrobial peptides (AMPs) might play a main role in a next generation of drugs against bacterial infections. Taking an innovative approach to design self-organizing functional proteins, we have generated here protein-only nanoparticles with intrinsic AMP microbicide activity. Using a recombinant version of the GWH1 antimicrobial peptide as building block, these materials show a wide antibacterial activity spectrum in absence of detectable toxicity on mammalian cells. The GWH1-based nanoparticles combine clinically appealing properties of nanoscale materials with full biocompatibility, structural and functional plasticity and biological efficacy exhibited by proteins. Because of the largely implemented biological fabrication of recombinant protein drugs, the protein-based platform presented here represents a novel and scalable strategy in antimicrobial drug design, that by solving some of the limitations of AMPs offers a promising alternative to conventional antibiotics. The low molecular weight antimicrobial peptide GWH1 has been engineered to oligomerize as self-assembling protein-only nanoparticles of around 50nm. In this form, the peptide exhibits potent and broad antibacterial activities against both Gram-positive and Gram-negative bacteria, without any harmful effect over mammalian cells. As a solid proof-of-concept, this finding strongly supports the design and biofabrication of nanoscale antimicrobial materials with in-built functionalities. The protein-based homogeneous composition offer advantages over alternative materials explored as antimicrobial agents, regarding biocompatibility, biodegradability and environmental suitability. Beyond the described prototype, this transversal engineering concept has wide applicability in the design of novel nanomedicines for advanced treatments of bacterial infections. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Rationally designed synthetic protein hydrogels with predictable mechanical properties.

PubMed

Wu, Junhua; Li, Pengfei; Dong, Chenling; Jiang, Heting; Bin Xue; Gao, Xiang; Qin, Meng; Wang, Wei; Bin Chen; Cao, Yi

2018-02-12

Designing synthetic protein hydrogels with tailored mechanical properties similar to naturally occurring tissues is an eternal pursuit in tissue engineering and stem cell and cancer research. However, it remains challenging to correlate the mechanical properties of protein hydrogels with the nanomechanics of individual building blocks. Here we use single-molecule force spectroscopy, protein engineering and theoretical modeling to prove that the mechanical properties of protein hydrogels are predictable based on the mechanical hierarchy of the cross-linkers and the load-bearing modules at the molecular level. These findings provide a framework for rationally designing protein hydrogels with independently tunable elasticity, extensibility, toughness and self-healing. Using this principle, we demonstrate the engineering of self-healable muscle-mimicking hydrogels that can significantly dissipate energy through protein unfolding. We expect that this principle can be generalized for the construction of protein hydrogels with customized mechanical properties for biomedical applications.

Structure of a designed protein cage that self-assembles into a highly porous cube

DOE PAGES

Lai, Yen-Ting; Reading, Eamonn; Hura, Greg L.; ...

2014-11-10

Natural proteins can be versatile building blocks for multimeric, self-assembling structures. Yet, creating protein-based assemblies with specific geometries and chemical properties remains challenging. Highly porous materials represent particularly interesting targets for designed assembly. Here we utilize a strategy of fusing two natural protein oligomers using a continuous alpha-helical linker to design a novel protein that self assembles into a 750 kDa, 225 Å diameter, cube-shaped cage with large openings into a 130 Å diameter inner cavity. A crystal structure of the cage showed atomic level agreement with the designed model, while electron microscopy, native mass spectrometry, and small angle x-raymore » scattering revealed alternate assembly forms in solution. These studies show that accurate design of large porous assemblies with specific shapes is feasible, while further specificity improvements will likely require limiting flexibility to select against alternative forms. Finally, these results provide a foundation for the design of advanced materials with applications in bionanotechnology, nanomedicine and material sciences.« less

Automated design evolution of stereochemically randomized protein foldamers

NASA Astrophysics Data System (ADS)

Ranbhor, Ranjit; Kumar, Anil; Patel, Kirti; Ramakrishnan, Vibin; Durani, Susheel

2018-05-01

Diversification of chain stereochemistry opens up the possibilities of an ‘in principle’ increase in the design space of proteins. This huge increase in the sequence and consequent structural variation is aimed at the generation of smart materials. To diversify protein structure stereochemically, we introduced L- and D-α-amino acids as the design alphabet. With a sequence design algorithm, we explored the usage of specific variables such as chirality and the sequence of this alphabet in independent steps. With molecular dynamics, we folded stereochemically diverse homopolypeptides and evaluated their ‘fitness’ for possible design as protein-like foldamers. We propose a fitness function to prune the most optimal fold among 1000 structures simulated with an automated repetitive simulated annealing molecular dynamics (AR-SAMD) approach. The highly scored poly-leucine fold with sequence lengths of 24 and 30 amino acids were later sequence-optimized using a Dead End Elimination cum Monte Carlo based optimization tool. This paper demonstrates a novel approach for the de novo design of protein-like foldamers.

Deoxycholate-Based Glycosides (DCGs) for Membrane Protein Stabilisation.

PubMed

Bae, Hyoung Eun; Gotfryd, Kamil; Thomas, Jennifer; Hussain, Hazrat; Ehsan, Muhammad; Go, Juyeon; Loland, Claus J; Byrne, Bernadette; Chae, Pil Seok

2015-07-06

Detergents are an absolute requirement for studying the structure of membrane proteins. However, many conventional detergents fail to stabilise denaturation-sensitive membrane proteins, such as eukaryotic proteins and membrane protein complexes. New amphipathic agents with enhanced efficacy in stabilising membrane proteins will be helpful in overcoming the barriers to studying membrane protein structures. We have prepared a number of deoxycholate-based amphiphiles with carbohydrate head groups, designated deoxycholate-based glycosides (DCGs). These DCGs are the hydrophilic variants of previously reported deoxycholate-based N-oxides (DCAOs). Membrane proteins in these agents, particularly the branched diglucoside-bearing amphiphiles DCG-1 and DCG-2, displayed favourable behaviour compared to previously reported parent compounds (DCAOs) and conventional detergents (LDAO and DDM). Given their excellent properties, these agents should have significant potential for membrane protein studies. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

[Crystal structure of SMU.2055 protein from Streptococcus mutans and its small molecule inhibitors design and selection].

PubMed

Xiaodan, Chen; Xiurong, Zhan; Xinyu, Wu; Chunyan, Zhao; Wanghong, Zhao

2015-04-01

The aim of this study is to analyze the three-dimensional crystal structure of SMU.2055 protein, a putative acetyltransferase from the major caries pathogen Streptococcus mutans (S. mutans). The design and selection of the structure-based small molecule inhibitors are also studied. The three-dimensional crystal structure of SMU.2055 protein was obtained by structural genomics research methods of gene cloning and expression, protein purification with Ni²⁺-chelating affinity chromatography, crystal screening, and X-ray diffraction data collection. An inhibitor virtual model matching with its target protein structure was set up using computer-aided drug design methods, virtual screening and fine docking, and Libdock and Autodock procedures. The crystal of SMU.2055 protein was obtained, and its three-dimensional crystal structure was analyzed. This crystal was diffracted to a resolution of 0.23 nm. It belongs to orthorhombic space group C222(1), with unit cell parameters of a = 9.20 nm, b = 9.46 nm, and c = 19.39 nm. The asymmetric unit contained four molecules, with a solvent content of 56.7%. Moreover, five small molecule compounds, whose structure matched with that of the target protein in high degree, were designed and selected. Protein crystallography research of S. mutans SMU.2055 helps to understand the structures and functions of proteins from S. mutans at the atomic level. These five compounds may be considered as effective inhibitors to SMU.2055. The virtual model of small molecule inhibitors we built will lay a foundation to the anticaries research based on the crystal structure of proteins.

Structure-based design of broadly protective group a streptococcal M protein-based vaccines.

PubMed

Dale, James B; Smeesters, Pierre R; Courtney, Harry S; Penfound, Thomas A; Hohn, Claudia M; Smith, Jeremy C; Baudry, Jerome Y

2017-01-03

A major obstacle to the development of broadly protective M protein-based group A streptococcal (GAS) vaccines is the variability within the N-terminal epitopes that evoke potent bactericidal antibodies. The concept of M type-specific protective immune responses has recently been challenged based on the observation that multivalent M protein vaccines elicited cross-reactive bactericidal antibodies against a number of non-vaccine M types of GAS. Additionally, a new "cluster-based" typing system of 175M proteins identified a limited number of clusters containing closely related M proteins. In the current study, we used the emm cluster typing system, in combination with computational structure-based peptide modeling, as a novel approach to the design of potentially broadly protective M protein-based vaccines. M protein sequences (AA 16-50) from the E4 cluster containing 17 emm types of GAS were analyzed using de novo 3-D structure prediction tools and the resulting structures subjected to chemical diversity analysis to identify sequences that were the most representative of the 3-D physicochemical properties of the M peptides in the cluster. Five peptides that spanned the range of physicochemical attributes of all 17 peptides were used to formulate synthetic and recombinant vaccines. Rabbit antisera were assayed for antibodies that cross-reacted with E4 peptides and whole bacteria by ELISA and for bactericidal activity against all E4GAS. The synthetic vaccine rabbit antisera reacted with all 17 E4M peptides and demonstrated bactericidal activity against 15/17 E4GAS. A recombinant hybrid vaccine containing the same E4 peptides also elicited antibodies that cross-reacted with all E4M peptides. Comprehensive studies using structure-based design may result in a broadly protective M peptide vaccine that will elicit cluster-specific and emm type-specific antibody responses against the majority of clinically relevant emm types of GAS. Copyright © 2016 Elsevier Ltd. All rights reserved.

Application of the a posteriori granddaughter design to the Holstein genome

USDA-ARS?s Scientific Manuscript database

An a posteriori granddaughter design was applied to determine haplotype effects for the Holstein genome. A total of 52 grandsire families, each with >=100 genotyped sons with genetic evaluations based on progeny tests, were analyzed for 33 traits (milk, fat, and protein yields; fat and protein perce...

Supramolecular Architectures and Mimics of Complex Natural Folds Derived from Rationally Designed alpha-Helical Protein Structures

NASA Astrophysics Data System (ADS)

Tavenor, Nathan Albert

Protein-based supramolecular polymers (SMPs) are a class of biomaterials which draw inspiration from and expand upon the many examples of complex protein quaternary structures observed in nature: collagen, microtubules, viral capsids, etc. Designing synthetic supramolecular protein scaffolds both increases our understanding of natural superstructures and allows for the creation of novel materials. Similar to small-molecule SMPs, protein-based SMPs form due to self-assembly driven by intermolecular interactions between monomers, and monomer structure determines the properties of the overall material. Using protein-based monomers takes advantage of the self-assembly and highly specific molecular recognition properties encodable in polypeptide sequences to rationally design SMP architectures. The central hypothesis underlying our work is that alpha-helical coiled coils, a well-studied protein quaternary folding motif, are well-suited to SMP design through the addition of synthetic linkers at solvent-exposed sites. Through small changes in the structures of the cross-links and/or peptide sequence, we have been able to control both the nanoscale organization and the macroscopic properties of the SMPs. Changes to the linker and hydrophobic core of the peptide can be used to control polymer rigidity, stability, and dimensionality. The gaps in knowledge that this thesis sought to fill on this project were 1) the relationship between the molecular structure of the cross-linked polypeptides and the macroscopic properties of the SMPs and 2) a means of creating materials exhibiting multi-dimensional net or framework topologies. Separate from the above efforts on supramolecular architectures was work on improving backbone modification strategies for an alpha-helix in the context of a complex protein tertiary fold. Earlier work in our lab had successfully incorporated unnatural building blocks into every major secondary structure (beta-sheet, alpha-helix, loops and beta-turns) of a small protein with a tertiary fold. Although the tertiary fold of the native sequence was mimicked by the resulting artificial protein, the thermodynamic stability was greatly compromised. Most of this energetic penalty derived from the modifications present in the alpha-helix. The contribution within this thesis was direct comparison of several alpha-helical design strategies and establishment of the thermodynamic consequences of each.

3D-SURFER: software for high-throughput protein surface comparison and analysis

PubMed Central

La, David; Esquivel-Rodríguez, Juan; Venkatraman, Vishwesh; Li, Bin; Sael, Lee; Ueng, Stephen; Ahrendt, Steven; Kihara, Daisuke

2009-01-01

Summary: We present 3D-SURFER, a web-based tool designed to facilitate high-throughput comparison and characterization of proteins based on their surface shape. As each protein is effectively represented by a vector of 3D Zernike descriptors, comparison times for a query protein against the entire PDB take, on an average, only a couple of seconds. The web interface has been designed to be as interactive as possible with displays showing animated protein rotations, CATH codes and structural alignments using the CE program. In addition, geometrically interesting local features of the protein surface, such as pockets that often correspond to ligand binding sites as well as protrusions and flat regions can also be identified and visualized. Availability: 3D-SURFER is a web application that can be freely accessed from: http://dragon.bio.purdue.edu/3d-surfer Contact: dkihara@purdue.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19759195

3D-SURFER: software for high-throughput protein surface comparison and analysis.

PubMed

La, David; Esquivel-Rodríguez, Juan; Venkatraman, Vishwesh; Li, Bin; Sael, Lee; Ueng, Stephen; Ahrendt, Steven; Kihara, Daisuke

2009-11-01

We present 3D-SURFER, a web-based tool designed to facilitate high-throughput comparison and characterization of proteins based on their surface shape. As each protein is effectively represented by a vector of 3D Zernike descriptors, comparison times for a query protein against the entire PDB take, on an average, only a couple of seconds. The web interface has been designed to be as interactive as possible with displays showing animated protein rotations, CATH codes and structural alignments using the CE program. In addition, geometrically interesting local features of the protein surface, such as pockets that often correspond to ligand binding sites as well as protrusions and flat regions can also be identified and visualized. 3D-SURFER is a web application that can be freely accessed from: http://dragon.bio.purdue.edu/3d-surfer dkihara@purdue.edu Supplementary data are available at Bioinformatics online.

Building blocks for protein interaction devices

PubMed Central

Grünberg, Raik; Ferrar, Tony S.; van der Sloot, Almer M.; Constante, Marco; Serrano, Luis

2010-01-01

Here, we propose a framework for the design of synthetic protein networks from modular protein–protein or protein–peptide interactions and provide a starter toolkit of protein building blocks. Our proof of concept experiments outline a general work flow for part–based protein systems engineering. We streamlined the iterative BioBrick cloning protocol and assembled 25 synthetic multidomain proteins each from seven standardized DNA fragments. A systematic screen revealed two main factors controlling protein expression in Escherichia coli: obstruction of translation initiation by mRNA secondary structure or toxicity of individual domains. Eventually, 13 proteins were purified for further characterization. Starting from well-established biotechnological tools, two general–purpose interaction input and two readout devices were built and characterized in vitro. Constitutive interaction input was achieved with a pair of synthetic leucine zippers. The second interaction was drug-controlled utilizing the rapamycin-induced binding of FRB(T2098L) to FKBP12. The interaction kinetics of both devices were analyzed by surface plasmon resonance. Readout was based on Förster resonance energy transfer between fluorescent proteins and was quantified for various combinations of input and output devices. Our results demonstrate the feasibility of parts-based protein synthetic biology. Additionally, we identify future challenges and limitations of modular design along with approaches to address them. PMID:20215443

Screening and structure-based modeling of T-cell epitopes of Nipah virus proteome: an immunoinformatic approach for designing peptide-based vaccine.

PubMed

Kamthania, Mohit; Sharma, D K

2015-12-01

Identification of Nipah virus (NiV) T-cell-specific antigen is urgently needed for appropriate diagnostic and vaccination. In the present study, prediction and modeling of T-cell epitopes of Nipah virus antigenic proteins nucleocapsid, phosphoprotein, matrix, fusion, glycoprotein, L protein, W protein, V protein and C protein followed by the binding simulation studies of predicted highest binding scorers with their corresponding MHC class I alleles were done. Immunoinformatic tool ProPred1 was used to predict the promiscuous MHC class I epitopes of viral antigenic proteins. The molecular modelings of the epitopes were done by PEPstr server. And alleles structure were predicted by MODELLER 9.10. Molecular dynamics (MD) simulation studies were performed through the NAMD graphical user interface embedded in visual molecular dynamics. Epitopes VPATNSPEL, NPTAVPFTL and LLFVFGPNL of Nucleocapsid, V protein and Fusion protein have considerable binding energy and score with HLA-B7, HLA-B*2705 and HLA-A2MHC class I allele, respectively. These three predicted peptides are highly potential to induce T-cell-mediated immune response and are expected to be useful in designing epitope-based vaccines against Nipah virus after further testing by wet laboratory studies.

Crossing borders to bind proteins--a new concept in protein recognition based on the conjugation of small organic molecules or short peptides to polypeptides from a designed set.

PubMed

Baltzer, Lars

2011-06-01

A new concept for protein recognition and binding is highlighted. The conjugation of small organic molecules or short peptides to polypeptides from a designed set provides binder molecules that bind proteins with high affinities, and with selectivities that are equal to those of antibodies. The small organic molecules or peptides need to bind the protein targets but only with modest affinities and selectivities, because conjugation to the polypeptides results in molecules with dramatically improved binder performance. The polypeptides are selected from a set of only sixteen sequences designed to bind, in principle, any protein. The small number of polypeptides used to prepare high-affinity binders contrasts sharply with the huge libraries used in binder technologies based on selection or immunization. Also, unlike antibodies and engineered proteins, the polypeptides have unordered three-dimensional structures and adapt to the proteins to which they bind. Binder molecules for the C-reactive protein, human carbonic anhydrase II, acetylcholine esterase, thymidine kinase 1, phosphorylated proteins, the D-dimer, and a number of antibodies are used as examples to demonstrate that affinities are achieved that are higher than those of the small molecules or peptides by as much as four orders of magnitude. Evaluation by pull-down experiments and ELISA-based tests in human serum show selectivities to be equal to those of antibodies. Small organic molecules and peptides are readily available from pools of endogenous ligands, enzyme substrates, inhibitors or products, from screened small molecule libraries, from phage display, and from mRNA display. The technology is an alternative to established binder concepts for applications in drug development, diagnostics, medical imaging, and protein separation.

Thiazolidine-2,4-dione derivatives: programmed chemical weapons for key protein targets of various pathological conditions.

PubMed

Chadha, Navriti; Bahia, Malkeet Singh; Kaur, Maninder; Silakari, Om

2015-07-01

Thiazolidine-2,4-dione is an extensively explored heterocyclic nucleus for designing of novel agents implicated for a wide variety of pathophysiological conditions, that is, diabetes, diabetic complications, cancer, arthritis, inflammation, microbial infection, and melanoma, etc. The current paradigm of drug development has shifted to the structure-based drug design, since high-throughput screenings have continued to generate disappointing results. The gap between hit generation and drug establishment can be narrowed down by investigation of ligand interactions with its receptor protein. Therefore, it would always be highly beneficial to gain knowledge of molecular level interactions between specific protein target and developed ligands; since this information can be maneuvered to design new molecules with improved protein fitting. Thus, considering this aspect, we have corroborated the information about molecular (target) level implementations of thiazolidine-2,4-diones (TZD) derivatives having therapeutic implementations such as, but not limited to, anti-diabetic (glitazones), anti-cancer, anti-arthritic, anti-inflammatory, anti-oxidant and anti-microbial, etc. The structure based SAR of TZD derivatives for various protein targets would serve as a benchmark for the alteration of existing ligands to design new ones with better binding interactions. Copyright © 2015 Elsevier Ltd. All rights reserved.

hBfl-1/hNOXA Interaction Studies Provide New Insights on the Role of Bfl-1 in Cancer Cell Resistance and for the Design of Novel Anticancer Agents

PubMed Central

2016-01-01

Upregulation of antiapoptotic Bcl-2 proteins in certain tumors confers cancer cell resistance to chemotherapy or radiations. Members of the antiapoptotic Bcl-2 proteins, including Bcl-2, Mcl-1, Bcl-xL, Bcl-w, and Bfl-1, inhibit apoptosis by selectively binding to conserved α-helical regions, named BH3 domains, of pro-apoptotic proteins such as Bim, tBid, Bad, or NOXA. Five antiapoptotic proteins have been identified that interact with various selectivity with BH3 containing pro-apoptotic counterparts. Cancer cells present various and variable levels of these proteins, making the design of effective apoptosis based therapeutics challenging. Recently, BH3 profiling was introduced as a method to classify cancer cells based on their ability to resist apoptosis following exposure to selected BH3 peptides. However, these studies were based on binding affinities measured with model BH3 peptides and Bcl-2-proteins taken from mouse sequences. While the majority of these interactions are conserved between mice and humans, we found surprisingly that human NOXA binds to human Bfl-1 potently and covalently via conserved Cys residues, with over 2 orders of magnitude increased affinity over hMcl-1. Our data suggest that some assumptions of the original BH3 profiling need to be revisited and that perhaps further targeting efforts should be redirected toward Bfl-1, for which no suitable specific inhibitors or pharmacological tools have been reported. In this regard, we also describe the initial design and characterizations of novel covalent BH3-based agents that potently target Bfl-1. These molecules could provide a novel platform on which to design effective Bfl-1 targeting therapeutics. PMID:28026162

Small-molecule-based protein-labeling technology in live cell studies: probe-design concepts and applications.

PubMed

Mizukami, Shin; Hori, Yuichiro; Kikuchi, Kazuya

2014-01-21

The use of genetic engineering techniques allows researchers to combine functional proteins with fluorescent proteins (FPs) to produce fusion proteins that can be visualized in living cells, tissues, and animals. However, several limitations of FPs, such as slow maturation kinetics or issues with photostability under laser illumination, have led researchers to examine new technologies beyond FP-based imaging. Recently, new protein-labeling technologies using protein/peptide tags and tag-specific probes have attracted increasing attention. Although several protein-labeling systems are com mercially available, researchers continue to work on addressing some of the limitations of this technology. To reduce the level of background fluorescence from unlabeled probes, researchers have pursued fluorogenic labeling, in which the labeling probes do not fluoresce until the target proteins are labeled. In this Account, we review two different fluorogenic protein-labeling systems that we have recently developed. First we give a brief history of protein labeling technologies and describe the challenges involved in protein labeling. In the second section, we discuss a fluorogenic labeling system based on a noncatalytic mutant of β-lactamase, which forms specific covalent bonds with β-lactam antibiotics such as ampicillin or cephalosporin. Based on fluorescence (or Förster) resonance energy transfer and other physicochemical principles, we have developed several types of fluorogenic labeling probes. To extend the utility of this labeling system, we took advantage of a hydrophobic β-lactam prodrug structure to achieve intracellular protein labeling. We also describe a small protein tag, photoactive yellow protein (PYP)-tag, and its probes. By utilizing a quenching mechanism based on close intramolecular contact, we incorporated a turn-on switch into the probes for fluorogenic protein labeling. One of these probes allowed us to rapidly image a protein while avoiding washout. In the future, we expect that protein-labeling systems with finely designed probes will lead to novel methodologies that allow researchers to image biomolecules and to perturb protein functions.

The application of SSADM to modelling the logical structure of proteins.

PubMed

Saldanha, J; Eccles, J

1991-10-01

A logical design that describes the overall structure of proteins, together with a more detailed design describing secondary and some supersecondary structures, has been constructed using the computer-aided software engineering (CASE) tool, Auto-mate. Auto-mate embodies the philosophy of the Structured Systems Analysis and Design Method (SSADM) which enables the logical design of computer systems. Our design will facilitate the building of large information systems, such as databases and knowledgebases in the field of protein structure, by the derivation of system requirements from our logical model prior to producing the final physical system. In addition, the study has highlighted the ease of employing SSADM as a formalism in which to conduct the transferral of concepts from an expert into a design for a knowledge-based system that can be implemented on a computer (the knowledge-engineering exercise). It has been demonstrated how SSADM techniques may be extended for the purpose of modelling the constituent Prolog rules. This facilitates the integration of the logical system design model with the derived knowledge-based system.

Computational design of water-soluble α-helical barrels.

PubMed

Thomson, Andrew R; Wood, Christopher W; Burton, Antony J; Bartlett, Gail J; Sessions, Richard B; Brady, R Leo; Woolfson, Derek N

2014-10-24

The design of protein sequences that fold into prescribed de novo structures is challenging. General solutions to this problem require geometric descriptions of protein folds and methods to fit sequences to these. The α-helical coiled coils present a promising class of protein for this and offer considerable scope for exploring hitherto unseen structures. For α-helical barrels, which have more than four helices and accessible central channels, many of the possible structures remain unobserved. Here, we combine geometrical considerations, knowledge-based scoring, and atomistic modeling to facilitate the design of new channel-containing α-helical barrels. X-ray crystal structures of the resulting designs match predicted in silico models. Furthermore, the observed channels are chemically defined and have diameters related to oligomer state, which present routes to design protein function. Copyright © 2014, American Association for the Advancement of Science.

Prediction of hot regions in protein-protein interaction by combining density-based incremental clustering with feature-based classification.

PubMed

Hu, Jing; Zhang, Xiaolong; Liu, Xiaoming; Tang, Jinshan

2015-06-01

Discovering hot regions in protein-protein interaction is important for drug and protein design, while experimental identification of hot regions is a time-consuming and labor-intensive effort; thus, the development of predictive models can be very helpful. In hot region prediction research, some models are based on structure information, and others are based on a protein interaction network. However, the prediction accuracy of these methods can still be improved. In this paper, a new method is proposed for hot region prediction, which combines density-based incremental clustering with feature-based classification. The method uses density-based incremental clustering to obtain rough hot regions, and uses feature-based classification to remove the non-hot spot residues from the rough hot regions. Experimental results show that the proposed method significantly improves the prediction performance of hot regions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Protein construct storage: Bayesian variable selection and prediction with mixtures.

PubMed

Clyde, M A; Parmigiani, G

1998-07-01

Determining optimal conditions for protein storage while maintaining a high level of protein activity is an important question in pharmaceutical research. A designed experiment based on a space-filling design was conducted to understand the effects of factors affecting protein storage and to establish optimal storage conditions. Different model-selection strategies to identify important factors may lead to very different answers about optimal conditions. Uncertainty about which factors are important, or model uncertainty, can be a critical issue in decision-making. We use Bayesian variable selection methods for linear models to identify important variables in the protein storage data, while accounting for model uncertainty. We also use the Bayesian framework to build predictions based on a large family of models, rather than an individual model, and to evaluate the probability that certain candidate storage conditions are optimal.

Conformational Transitions upon Ligand Binding: Holo-Structure Prediction from Apo Conformations

PubMed Central

Seeliger, Daniel; de Groot, Bert L.

2010-01-01

Biological function of proteins is frequently associated with the formation of complexes with small-molecule ligands. Experimental structure determination of such complexes at atomic resolution, however, can be time-consuming and costly. Computational methods for structure prediction of protein/ligand complexes, particularly docking, are as yet restricted by their limited consideration of receptor flexibility, rendering them not applicable for predicting protein/ligand complexes if large conformational changes of the receptor upon ligand binding are involved. Accurate receptor models in the ligand-bound state (holo structures), however, are a prerequisite for successful structure-based drug design. Hence, if only an unbound (apo) structure is available distinct from the ligand-bound conformation, structure-based drug design is severely limited. We present a method to predict the structure of protein/ligand complexes based solely on the apo structure, the ligand and the radius of gyration of the holo structure. The method is applied to ten cases in which proteins undergo structural rearrangements of up to 7.1 Å backbone RMSD upon ligand binding. In all cases, receptor models within 1.6 Å backbone RMSD to the target were predicted and close-to-native ligand binding poses were obtained for 8 of 10 cases in the top-ranked complex models. A protocol is presented that is expected to enable structure modeling of protein/ligand complexes and structure-based drug design for cases where crystal structures of ligand-bound conformations are not available. PMID:20066034

Hotspot-Centric De Novo Design of Protein Binders

PubMed Central

Fleishman, Sarel J.; Corn, Jacob E.; Strauch, Eva-Maria; Whitehead, Timothy A.; Karanicolas, John; Baker, David

2014-01-01

Protein–protein interactions play critical roles in biology, and computational design of interactions could be useful in a range of applications. We describe in detail a general approach to de novo design of protein interactions based on computed, energetically optimized interaction hotspots, which was recently used to produce high-affinity binders of influenza hemagglutinin. We present several alternative approaches to identify and build the key hotspot interactions within both core secondary structural elements and variable loop regions and evaluate the method's performance in natural-interface recapitulation. We show that the method generates binding surfaces that are more conformationally restricted than previous design methods, reducing opportunities for off-target interactions. PMID:21945116

Design, synthesis, and application of the trimethoprim-based chemical tag for live-cell imaging.

PubMed

Jing, Chaoran; Cornish, Virginia W

2013-01-01

Over the past decade, chemical tags have been developed to complement the use of fluorescent proteins in live-cell imaging. Chemical tags retain the specificity of protein labeling achieved with fluorescent proteins through genetic encoding, but provide smaller, more robust tags and modular use of organic fluorophores with high photon output and tailored functionalities. The trimethoprim-based chemical tag (TMP-tag) was initially developed based on the high affinity interaction between E. coli dihydrofolate reductase and the antibiotic trimethoprim and was subsequently rendered covalent and fluorogenic via proximity-induced protein labeling reactions. To date, the TMP-tag is one of the few chemical tags that enable intracellular protein labeling and high-resolution live-cell imaging. Here we describe the general design, chemical synthesis, and application of TMP-tag for live-cell imaging. Alternate protocols for synthesizing and using the covalent and the fluorogenic TMP-tags are also included. © 2013 by John Wiley & Sons, Inc.

WIWS: a protein structure bioinformatics Web service collection.

PubMed

Hekkelman, M L; Te Beek, T A H; Pettifer, S R; Thorne, D; Attwood, T K; Vriend, G

2010-07-01

The WHAT IF molecular-modelling and drug design program is widely distributed in the world of protein structure bioinformatics. Although originally designed as an interactive application, its highly modular design and inbuilt control language have recently enabled its deployment as a collection of programmatically accessible web services. We report here a collection of WHAT IF-based protein structure bioinformatics web services: these relate to structure quality, the use of symmetry in crystal structures, structure correction and optimization, adding hydrogens and optimizing hydrogen bonds and a series of geometric calculations. The freely accessible web services are based on the industry standard WS-I profile and the EMBRACE technical guidelines, and are available via both REST and SOAP paradigms. The web services run on a dedicated computational cluster; their function and availability is monitored daily.

Design of a single-chain polypeptide tetrahedron assembled from coiled-coil segments.

PubMed

Gradišar, Helena; Božič, Sabina; Doles, Tibor; Vengust, Damjan; Hafner-Bratkovič, Iva; Mertelj, Alenka; Webb, Ben; Šali, Andrej; Klavžar, Sandi; Jerala, Roman

2013-06-01

Protein structures evolved through a complex interplay of cooperative interactions, and it is still very challenging to design new protein folds de novo. Here we present a strategy to design self-assembling polypeptide nanostructured polyhedra based on modularization using orthogonal dimerizing segments. We designed and experimentally demonstrated the formation of the tetrahedron that self-assembles from a single polypeptide chain comprising 12 concatenated coiled coil-forming segments separated by flexible peptide hinges. The path of the polypeptide chain is guided by a defined order of segments that traverse each of the six edges of the tetrahedron exactly twice, forming coiled-coil dimers with their corresponding partners. The coincidence of the polypeptide termini in the same vertex is demonstrated by reconstituting a split fluorescent protein in the polypeptide with the correct tetrahedral topology. Polypeptides with a deleted or scrambled segment order fail to self-assemble correctly. This design platform provides a foundation for constructing new topological polypeptide folds based on the set of orthogonal interacting polypeptide segments.

Influence of Length and Amino Acid Composition on Dimer Formation of Immunoglobulin based Chimera.

PubMed

Manoj, Patidar; Naveen, Yadav; Dalai, Sarat Kumar

2017-10-18

The dimeric immunoglobulin (Ig) chimeras used for drug targeting and delivery are preferred biologics over their monomeric forms. Designing these Ig chimeras involves critical selection of a suitable Ig base that ensures dimer formation. In the present study, we systematically analyzed several factors that influence the formation of dimeric chimera. We designed and predicted 608 cytokine-Ig chimeras where we tested the contributions of (1) different domains of Ig constant heavy chain, (2) length of partner proteins, (3) amino acid (AA) composition and (4) position of cysteine in the formation of homodimer. The sequences of various Ig and cytokines were procured from Uniprot database, fused and submitted to COTH (CO-THreader) server for the prediction of dimer formation. Contributions of different domains of Ig constant heavy chain, length of chimeric proteins, AA composition and position of cysteine were tested to the homodimer formation of 608 cytokine-Ig chimeras. Various in silico approaches were adopted for validating the in silico findings. Experimentally we also validated our approach by expressing in CHO cells the chimeric design of shorter cytokine with Ig domain and analyzing the protein by SDS-PAGE. Our results advocate that while the CH1 region and the Hinge region of Ig heavy chain are critical, the length of partner proteins also crucially influences homodimer formation of the Ig-based chimera. We also report that the CH1 domain of Ig is not required for dimer formation of Ig based chimera in the presence of larger partner proteins. For shorter partner proteins fused to CH2-CH3, however, careful selection of partner sequence is critical, particularly the hydrophobic AA composition, cysteine content & their positions, disulphide bond formation property, and the linker sequences. We validated our in silico observation by various bioinformatics tools and checked the ability of chimeras to bind with the receptors of native protein by docking studies. As a proof of concept, we have expressed the chimeric proteins in CHO cells and found that our design favors the synthesis of dimeric proteins. Our structural prediction study suggests that extra amino acids in the range of 15-20 added to the CH2 domain of Ig is a critical requirement to make homodimer. This information from our study will have implication in designing efficacious homodimeric chimera. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Achievements and Challenges in Computational Protein Design.

PubMed

Samish, Ilan

2017-01-01

Computational protein design (CPD), a yet evolving field, includes computer-aided engineering for partial or full de novo designs of proteins of interest. Designs are defined by a requested structure, function, or working environment. This chapter describes the birth and maturation of the field by presenting 101 CPD examples in a chronological order emphasizing achievements and pending challenges. Integrating these aspects presents the plethora of CPD approaches with the hope of providing a "CPD 101". These reflect on the broader structural bioinformatics and computational biophysics field and include: (1) integration of knowledge-based and energy-based methods, (2) hierarchical designated approach towards local, regional, and global motifs and the integration of high- and low-resolution design schemes that fit each such region, (3) systematic differential approaches towards different protein regions, (4) identification of key hot-spot residues and the relative effect of remote regions, (5) assessment of shape-complementarity, electrostatics and solvation effects, (6) integration of thermal plasticity and functional dynamics, (7) negative design, (8) systematic integration of experimental approaches, (9) objective cross-assessment of methods, and (10) successful ranking of potential designs. Future challenges also include dissemination of CPD software to the general use of life-sciences researchers and the emphasis of success within an in vivo milieu. CPD increases our understanding of protein structure and function and the relationships between the two along with the application of such know-how for the benefit of mankind. Applied aspects range from biological drugs, via healthier and tastier food products to nanotechnology and environmentally friendly enzymes replacing toxic chemicals utilized in the industry.

CCBuilder 2.0: Powerful and accessible coiled-coil modeling.

PubMed

Wood, Christopher W; Woolfson, Derek N

2018-01-01

The increased availability of user-friendly and accessible computational tools for biomolecular modeling would expand the reach and application of biomolecular engineering and design. For protein modeling, one key challenge is to reduce the complexities of 3D protein folds to sets of parametric equations that nonetheless capture the salient features of these structures accurately. At present, this is possible for a subset of proteins, namely, repeat proteins. The α-helical coiled coil provides one such example, which represents ≈ 3-5% of all known protein-encoding regions of DNA. Coiled coils are bundles of α helices that can be described by a small set of structural parameters. Here we describe how this parametric description can be implemented in an easy-to-use web application, called CCBuilder 2.0, for modeling and optimizing both α-helical coiled coils and polyproline-based collagen triple helices. This has many applications from providing models to aid molecular replacement for X-ray crystallography, in silico model building and engineering of natural and designed protein assemblies, and through to the creation of completely de novo "dark matter" protein structures. CCBuilder 2.0 is available as a web-based application, the code for which is open-source and can be downloaded freely. http://coiledcoils.chm.bris.ac.uk/ccbuilder2. We have created CCBuilder 2.0, an easy to use web-based application that can model structures for a whole class of proteins, the α-helical coiled coil, which is estimated to account for 3-5% of all proteins in nature. CCBuilder 2.0 will be of use to a large number of protein scientists engaged in fundamental studies, such as protein structure determination, through to more-applied research including designing and engineering novel proteins that have potential applications in biotechnology. © 2017 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Free-Energy-Based Protein Design: Re-Engineering Cellular Retinoic Acid Binding Protein II Assisted by the Moveable-Type Approach.

PubMed

Zhong, Haizhen A; Santos, Elizabeth M; Vasileiou, Chrysoula; Zheng, Zheng; Geiger, James H; Borhan, Babak; Merz, Kenneth M

2018-03-14

How to fine-tune the binding free energy of a small-molecule to a receptor site by altering the amino acid residue composition is a key question in protein engineering. Indeed, the ultimate solution to this problem, to chemical accuracy (±1 kcal/mol), will result in profound and wide-ranging applications in protein design. Numerous tools have been developed to address this question using knowledge-based models to more computationally intensive molecular dynamics simulations-based free energy calculations, but while some success has been achieved there remains room for improvement in terms of overall accuracy and in the speed of the methodology. Here we report a fast, knowledge-based movable-type (MT)-based approach to estimate the absolute and relative free energy of binding as influenced by mutations in a small-molecule binding site in a protein. We retrospectively validate our approach using mutagenesis data for retinoic acid binding to the Cellular Retinoic Acid Binding Protein II (CRABPII) system and then make prospective predictions that are borne out experimentally. The overall performance of our approach is supported by its success in identifying mutants that show high or even sub-nano-molar binding affinities of retinoic acid to the CRABPII system.

Protein Crystallography in Vaccine Research and Development.

PubMed

Malito, Enrico; Carfi, Andrea; Bottomley, Matthew J

2015-06-09

The use of protein X-ray crystallography for structure-based design of small-molecule drugs is well-documented and includes several notable success stories. However, it is less well-known that structural biology has emerged as a major tool for the design of novel vaccine antigens. Here, we review the important contributions that protein crystallography has made so far to vaccine research and development. We discuss several examples of the crystallographic characterization of vaccine antigen structures, alone or in complexes with ligands or receptors. We cover the critical role of high-resolution epitope mapping by reviewing structures of complexes between antigens and their cognate neutralizing, or protective, antibody fragments. Most importantly, we provide recent examples where structural insights obtained via protein crystallography have been used to design novel optimized vaccine antigens. This review aims to illustrate the value of protein crystallography in the emerging discipline of structural vaccinology and its impact on the rational design of vaccines.

Protein Crystallography in Vaccine Research and Development

PubMed Central

Malito, Enrico; Carfi, Andrea; Bottomley, Matthew J.

2015-01-01

The use of protein X-ray crystallography for structure-based design of small-molecule drugs is well-documented and includes several notable success stories. However, it is less well-known that structural biology has emerged as a major tool for the design of novel vaccine antigens. Here, we review the important contributions that protein crystallography has made so far to vaccine research and development. We discuss several examples of the crystallographic characterization of vaccine antigen structures, alone or in complexes with ligands or receptors. We cover the critical role of high-resolution epitope mapping by reviewing structures of complexes between antigens and their cognate neutralizing, or protective, antibody fragments. Most importantly, we provide recent examples where structural insights obtained via protein crystallography have been used to design novel optimized vaccine antigens. This review aims to illustrate the value of protein crystallography in the emerging discipline of structural vaccinology and its impact on the rational design of vaccines. PMID:26068237

Lead identification for the K-Ras protein: virtual screening and combinatorial fragment-based approaches

PubMed Central

Pathan, Akbar Ali Khan; Panthi, Bhavana; Khan, Zahid; Koppula, Purushotham Reddy; Alanazi, Mohammed Saud; Sachchidanand; Parine, Narasimha Reddy; Chourasia, Mukesh

2016-01-01

Objective Kirsten rat sarcoma (K-Ras) protein is a member of Ras family belonging to the small guanosine triphosphatases superfamily. The members of this family share a conserved structure and biochemical properties, acting as binary molecular switches. The guanosine triphosphate-bound active K-Ras interacts with a range of effectors, resulting in the stimulation of downstream signaling pathways regulating cell proliferation, differentiation, and apoptosis. Efforts to target K-Ras have been unsuccessful until now, placing it among high-value molecules against which developing a therapy would have an enormous impact. K-Ras transduces signals when it binds to guanosine triphosphate by directly binding to downstream effector proteins, but in case of guanosine diphosphate-bound conformation, these interactions get disrupted. Methods In the present study, we targeted the nucleotide-binding site in the “on” and “off” state conformations of the K-Ras protein to find out suitable lead compounds. A structure-based virtual screening approach has been used to screen compounds from different databases, followed by a combinatorial fragment-based approach to design the apposite lead for the K-Ras protein. Results Interestingly, the designed compounds exhibit a binding preference for the “off” state over “on” state conformation of K-Ras protein. Moreover, the designed compounds’ interactions are similar to guanosine diphosphate and, thus, could presumably act as a potential lead for K-Ras. The predicted drug-likeness properties of these compounds suggest that these compounds follow the Lipinski’s rule of five and have tolerable absorption, distribution, metabolism, excretion and toxicity values. Conclusion Thus, through the current study, we propose targeting only “off” state conformations as a promising strategy for the design of reversible inhibitors to pharmacologically inhibit distinct conformations of K-Ras protein. PMID:27217775

Optimal protein library design using recombination or point mutations based on sequence-based scoring functions.

PubMed

Pantazes, Robert J; Saraf, Manish C; Maranas, Costas D

2007-08-01

In this paper, we introduce and test two new sequence-based protein scoring systems (i.e. S1, S2) for assessing the likelihood that a given protein hybrid will be functional. By binning together amino acids with similar properties (i.e. volume, hydrophobicity and charge) the scoring systems S1 and S2 allow for the quantification of the severity of mismatched interactions in the hybrids. The S2 scoring system is found to be able to significantly functionally enrich a cytochrome P450 library over other scoring methods. Given this scoring base, we subsequently constructed two separate optimization formulations (i.e. OPTCOMB and OPTOLIGO) for optimally designing protein combinatorial libraries involving recombination or mutations, respectively. Notably, two separate versions of OPTCOMB are generated (i.e. model M1, M2) with the latter allowing for position-dependent parental fragment skipping. Computational benchmarking results demonstrate the efficacy of models OPTCOMB and OPTOLIGO to generate high scoring libraries of a prespecified size.

Quantification of the transferability of a designed protein specificity switch reveals extensive epistasis in molecular recognition

DOE PAGES

Melero, Cristina; Ollikainen, Noah; Harwood, Ian; ...

2014-10-13

Re-engineering protein–protein recognition is an important route to dissecting and controlling complex interaction networks. Experimental approaches have used the strategy of “second-site suppressors,” where a functional interaction is inferred between two proteins if a mutation in one protein can be compensated by a mutation in the second. Mimicking this strategy, computational design has been applied successfully to change protein recognition specificity by predicting such sets of compensatory mutations in protein–protein interfaces. To extend this approach, it would be advantageous to be able to “transplant” existing engineered and experimentally validated specificity changes to other homologous protein–protein complexes. Here, we test thismore » strategy by designing a pair of mutations that modulates peptide recognition specificity in the Syntrophin PDZ domain, confirming the designed interaction biochemically and structurally, and then transplanting the mutations into the context of five related PDZ domain–peptide complexes. We find a wide range of energetic effects of identical mutations in structurally similar positions, revealing a dramatic context dependence (epistasis) of designed mutations in homologous protein–protein interactions. To better understand the structural basis of this context dependence, we apply a structure-based computational model that recapitulates these energetic effects and we use this model to make and validate forward predictions. The context dependence of these mutations is captured by computational predictions, our results both highlight the considerable difficulties in designing protein–protein interactions and provide challenging benchmark cases for the development of improved protein modeling and design methods that accurately account for the context.« less

Quantification of the transferability of a designed protein specificity switch reveals extensive epistasis in molecular recognition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Melero, Cristina; Ollikainen, Noah; Harwood, Ian

Re-engineering protein–protein recognition is an important route to dissecting and controlling complex interaction networks. Experimental approaches have used the strategy of “second-site suppressors,” where a functional interaction is inferred between two proteins if a mutation in one protein can be compensated by a mutation in the second. Mimicking this strategy, computational design has been applied successfully to change protein recognition specificity by predicting such sets of compensatory mutations in protein–protein interfaces. To extend this approach, it would be advantageous to be able to “transplant” existing engineered and experimentally validated specificity changes to other homologous protein–protein complexes. Here, we test thismore » strategy by designing a pair of mutations that modulates peptide recognition specificity in the Syntrophin PDZ domain, confirming the designed interaction biochemically and structurally, and then transplanting the mutations into the context of five related PDZ domain–peptide complexes. We find a wide range of energetic effects of identical mutations in structurally similar positions, revealing a dramatic context dependence (epistasis) of designed mutations in homologous protein–protein interactions. To better understand the structural basis of this context dependence, we apply a structure-based computational model that recapitulates these energetic effects and we use this model to make and validate forward predictions. The context dependence of these mutations is captured by computational predictions, our results both highlight the considerable difficulties in designing protein–protein interactions and provide challenging benchmark cases for the development of improved protein modeling and design methods that accurately account for the context.« less

Computational design of a Zn2+ receptor that controls bacterial gene expression

NASA Astrophysics Data System (ADS)

Dwyer, M. A.; Looger, L. L.; Hellinga, H. W.

2003-09-01

The control of cellular physiology and gene expression in response to extracellular signals is a basic property of living systems. We have constructed a synthetic bacterial signal transduction pathway in which gene expression is controlled by extracellular Zn2+. In this system a computationally designed Zn2+-binding periplasmic receptor senses the extracellular solute and triggers a two-component signal transduction pathway via a chimeric transmembrane protein, resulting in transcriptional up-regulation of a -galactosidase reporter gene. The Zn2+-binding site in the designed receptor is based on a four-coordinate, tetrahedral primary coordination sphere consisting of histidines and glutamates. In addition, mutations were introduced in a secondary coordination sphere to satisfy the residual hydrogen-bonding potential of the histidines coordinated to the metal. The importance of the secondary shell interactions is demonstrated by their effect on metal affinity and selectivity, as well as protein stability. Three designed protein sequences, comprising two distinct metal-binding positions, were all shown to bind Zn2+ and to function in the cell-based assay, indicating the generality of the design methodology. These experiments demonstrate that biological systems can be manipulated with computationally designed proteins that have drastically altered ligand-binding specificities, thereby extending the repertoire of genetic control by extracellular signals.

In search of new lead compounds for trypanosomiasis drug design: A protein structure-based linked-fragment approach

NASA Astrophysics Data System (ADS)

Verlinde, Christophe L. M. J.; Rudenko, Gabrielle; Hol, Wim G. J.

1992-04-01

A modular method for pursuing structure-based inhibitor design in the framework of a design cycle is presented. The approach entails four stages: (1) a design pathway is defined in the three-dimensional structure of a target protein; (2) this pathway is divided into subregions; (3) complementary building blocks, also called fragments, are designed in each subregion; complementarity is defined in terms of shape, hydrophobicity, hydrogen bond properties and electrostatics; and (4) fragments from different subregions are linked into potential lead compounds. Stages (3) and (4) are qualitatively guided by force-field calculations. In addition, the designed fragments serve as entries for retrieving existing compounds from chemical databases. This linked-fragment approach has been applied in the design of potentially selective inhibitors of triosephosphate isomerase from Trypanosoma brucei, the causative agent of sleeping sickness.

Structure-Based Rational Design of a Toll-like Receptor 4 (TLR4) Decoy Receptor with High Binding Affinity for a Target Protein

PubMed Central

Lee, Sang-Chul; Hong, Seungpyo; Park, Keunwan; Jeon, Young Ho; Kim, Dongsup; Cheong, Hae-Kap; Kim, Hak-Sung

2012-01-01

Repeat proteins are increasingly attracting much attention as alternative scaffolds to immunoglobulin antibodies due to their unique structural features. Nonetheless, engineering interaction interface and understanding molecular basis for affinity maturation of repeat proteins still remain a challenge. Here, we present a structure-based rational design of a repeat protein with high binding affinity for a target protein. As a model repeat protein, a Toll-like receptor4 (TLR4) decoy receptor composed of leucine-rich repeat (LRR) modules was used, and its interaction interface was rationally engineered to increase the binding affinity for myeloid differentiation protein 2 (MD2). Based on the complex crystal structure of the decoy receptor with MD2, we first designed single amino acid substitutions in the decoy receptor, and obtained three variants showing a binding affinity (KD) one-order of magnitude higher than the wild-type decoy receptor. The interacting modes and contributions of individual residues were elucidated by analyzing the crystal structures of the single variants. To further increase the binding affinity, single positive mutations were combined, and two double mutants were shown to have about 3000- and 565-fold higher binding affinities than the wild-type decoy receptor. Molecular dynamics simulations and energetic analysis indicate that an additive effect by two mutations occurring at nearby modules was the major contributor to the remarkable increase in the binding affinities. PMID:22363519

Methods in Enzymology: “Flexible backbone sampling methods to model and design protein alternative conformations”

PubMed Central

Ollikainen, Noah; Smith, Colin A.; Fraser, James S.; Kortemme, Tanja

2013-01-01

Sampling alternative conformations is key to understanding how proteins work and engineering them for new functions. However, accurately characterizing and modeling protein conformational ensembles remains experimentally and computationally challenging. These challenges must be met before protein conformational heterogeneity can be exploited in protein engineering and design. Here, as a stepping stone, we describe methods to detect alternative conformations in proteins and strategies to model these near-native conformational changes based on backrub-type Monte Carlo moves in Rosetta. We illustrate how Rosetta simulations that apply backrub moves improve modeling of point mutant side chain conformations, native side chain conformational heterogeneity, functional conformational changes, tolerated sequence space, protein interaction specificity, and amino acid co-variation across protein-protein interfaces. We include relevant Rosetta command lines and RosettaScripts to encourage the application of these types of simulations to other systems. Our work highlights that critical scoring and sampling improvements will be necessary to approximate conformational landscapes. Challenges for the future development of these methods include modeling conformational changes that propagate away from designed mutation sites and modulating backbone flexibility to predictively design functionally important conformational heterogeneity. PMID:23422426

Structure-based design and evaluation of novel N-phenyl-1H-indol-2-amine derivatives for fat mass and obesity-associated (FTO) protein inhibition.

PubMed

Padariya, Monikaben; Kalathiya, Umesh

2016-10-01

Fat mass and obesity-associated (FTO) protein contributes to non-syndromic human obesity which refers to excessive fat accumulation in human body and results in health risk. FTO protein has become a promising target for anti-obesity medicines as there is an immense need for the rational design of potent inhibitors to treat obesity. In our study, a new scaffold N-phenyl-1H-indol-2-amine was selected as a base for FTO protein inhibitors by applying scaffold hopping approach. Using this novel scaffold, different derivatives were designed by extending scaffold structure with potential functional groups. Molecular docking simulations were carried out by using two different docking algorithm implemented in CDOCKER (flexible docking) and AutoDock programs (rigid docking). Analyzing results of rigid and flexible docking, compound MU06 was selected based on different properties and predicted binding affinities for further analysis. Molecular dynamics simulation of FTO/MU06 complex was performed to characterize structure rationale and binding stability. Certainly, Arg96 and His231 residue of FTO protein showed stable interaction with inhibitor MU06 throughout the production dynamics phase. Three residues of FTO protein (Arg96, Asp233, and His231) were found common in making H-bond interactions with MU06 during molecular dynamics simulation and CDOCKER docking. Copyright © 2016 Elsevier Ltd. All rights reserved.

Energy design for protein-protein interactions

PubMed Central

Ravikant, D. V. S.; Elber, Ron

2011-01-01

Proteins bind to other proteins efficiently and specifically to carry on many cell functions such as signaling, activation, transport, enzymatic reactions, and more. To determine the geometry and strength of binding of a protein pair, an energy function is required. An algorithm to design an optimal energy function, based on empirical data of protein complexes, is proposed and applied. Emphasis is made on negative design in which incorrect geometries are presented to the algorithm that learns to avoid them. For the docking problem the search for plausible geometries can be performed exhaustively. The possible geometries of the complex are generated on a grid with the help of a fast Fourier transform algorithm. A novel formulation of negative design makes it possible to investigate iteratively hundreds of millions of negative examples while monotonically improving the quality of the potential. Experimental structures for 640 protein complexes are used to generate positive and negative examples for learning parameters. The algorithm designed in this work finds the correct binding structure as the lowest energy minimum in 318 cases of the 640 examples. Further benchmarks on independent sets confirm the significant capacity of the scoring function to recognize correct modes of interactions. PMID:21842951

Physics-based scoring of protein-ligand interactions: explicit polarizability, quantum mechanics and free energies.

PubMed

Bryce, Richard A

2011-04-01

The ability to accurately predict the interaction of a ligand with its receptor is a key limitation in computer-aided drug design approaches such as virtual screening and de novo design. In this article, we examine current strategies for a physics-based approach to scoring of protein-ligand affinity, as well as outlining recent developments in force fields and quantum chemical techniques. We also consider advances in the development and application of simulation-based free energy methods to study protein-ligand interactions. Fuelled by recent advances in computational algorithms and hardware, there is the opportunity for increased integration of physics-based scoring approaches at earlier stages in computationally guided drug discovery. Specifically, we envisage increased use of implicit solvent models and simulation-based scoring methods as tools for computing the affinities of large virtual ligand libraries. Approaches based on end point simulations and reference potentials allow the application of more advanced potential energy functions to prediction of protein-ligand binding affinities. Comprehensive evaluation of polarizable force fields and quantum mechanical (QM)/molecular mechanical and QM methods in scoring of protein-ligand interactions is required, particularly in their ability to address challenging targets such as metalloproteins and other proteins that make highly polar interactions. Finally, we anticipate increasingly quantitative free energy perturbation and thermodynamic integration methods that are practical for optimization of hits obtained from screened ligand libraries.

Protein crystallography and infectious diseases.

PubMed Central

Verlinde, C. L.; Merritt, E. A.; Van den Akker, F.; Kim, H.; Feil, I.; Delboni, L. F.; Mande, S. C.; Sarfaty, S.; Petra, P. H.; Hol, W. G.

1994-01-01

The current rapid growth in the number of known 3-dimensional protein structures is producing a database of structures that is increasingly useful as a starting point for the development of new medically relevant molecules such as drugs, therapeutic proteins, and vaccines. This development is beautifully illustrated in the recent book, Protein structure: New approaches to disease and therapy (Perutz, 1992). There is a great and growing promise for the design of molecules for the treatment or prevention of a wide variety of diseases, an endeavor made possible by the insights derived from the structure and function of crucial proteins from pathogenic organisms and from man. We present here 2 illustrations of structure-based drug design. The first is the prospect of developing antitrypanosomal drugs based on crystallographic, ligand-binding, and molecular modeling studies of glycolytic glycosomal enzymes from Trypanosomatidae. These unicellular organisms are responsible for several tropical diseases, including African and American trypanosomiases, as well as various forms of leishmaniasis. Because the target enzymes are also present in the human host, this project is a pioneering study in selective design. The second illustrative case is the prospect of designing anti-cholera drugs based on detailed analysis of the structure of cholera toxin and the closely related Escherichia coli heat-labile enterotoxin. Such potential drugs can be targeted either at inhibiting the toxin's receptor binding site or at blocking the toxin's intracellular catalytic activity. Study of the Vibrio cholerae and E. coli toxins serves at the same time as an example of a general approach to structure-based vaccine design. These toxins exhibit a remarkable ability to stimulate the mucosal immune system, and early results have suggested that this property can be maintained by engineered fusion proteins based on the native toxin structure. The challenge is thus to incorporate selected epitopes from foreign pathogens into the native framework of the toxin such that crucial features of both the epitope and the toxin are maintained. That is, the modified toxin must continue to evoke a strong mucosal immune response, and this response must be directed against an epitope conformation characteristic of the original pathogen. PMID:7849584

SUSTAINABLE PLASTICS: DESIGNING AND DEMONSTRATING RENEWABLE, BIODEGRADABLE PRODUCTS MADE OF SOY PROTEIN-BASED PLASTICS

EPA Science Inventory

We have found that soy protein plastics have flow properties that are comparable to fossil fuel-based plastics. Soy plastics are processed at much lower temperatures, however, yielding energy savings over synthetic plastics during processing. These comparable flow properties m...

Mapping of ligand-binding cavities in proteins.

PubMed

Andersson, C David; Chen, Brian Y; Linusson, Anna

2010-05-01

The complex interactions between proteins and small organic molecules (ligands) are intensively studied because they play key roles in biological processes and drug activities. Here, we present a novel approach to characterize and map the ligand-binding cavities of proteins without direct geometric comparison of structures, based on Principal Component Analysis of cavity properties (related mainly to size, polarity, and charge). This approach can provide valuable information on the similarities and dissimilarities, of binding cavities due to mutations, between-species differences and flexibility upon ligand-binding. The presented results show that information on ligand-binding cavity variations can complement information on protein similarity obtained from sequence comparisons. The predictive aspect of the method is exemplified by successful predictions of serine proteases that were not included in the model construction. The presented strategy to compare ligand-binding cavities of related and unrelated proteins has many potential applications within protein and medicinal chemistry, for example in the characterization and mapping of "orphan structures", selection of protein structures for docking studies in structure-based design, and identification of proteins for selectivity screens in drug design programs. 2009 Wiley-Liss, Inc.

Mapping of Ligand-Binding Cavities in Proteins

PubMed Central

Andersson, C. David; Chen, Brian Y.; Linusson, Anna

2010-01-01

The complex interactions between proteins and small organic molecules (ligands) are intensively studied because they play key roles in biological processes and drug activities. Here, we present a novel approach to characterise and map the ligand-binding cavities of proteins without direct geometric comparison of structures, based on Principal Component Analysis of cavity properties (related mainly to size, polarity and charge). This approach can provide valuable information on the similarities, and dissimilarities, of binding cavities due to mutations, between-species differences and flexibility upon ligand-binding. The presented results show that information on ligand-binding cavity variations can complement information on protein similarity obtained from sequence comparisons. The predictive aspect of the method is exemplified by successful predictions of serine proteases that were not included in the model construction. The presented strategy to compare ligand-binding cavities of related and unrelated proteins has many potential applications within protein and medicinal chemistry, for example in the characterisation and mapping of “orphan structures”, selection of protein structures for docking studies in structure-based design and identification of proteins for selectivity screens in drug design programs. PMID:20034113

Binding of small molecules at interface of protein-protein complex - A newer approach to rational drug design.

PubMed

Gurung, A B; Bhattacharjee, A; Ajmal Ali, M; Al-Hemaid, F; Lee, Joongku

2017-02-01

Protein-protein interaction is a vital process which drives many important physiological processes in the cell and has also been implicated in several diseases. Though the protein-protein interaction network is quite complex but understanding its interacting partners using both in silico as well as molecular biology techniques can provide better insights for targeting such interactions. Targeting protein-protein interaction with small molecules is a challenging task because of druggability issues. Nevertheless, several studies on the kinetics as well as thermodynamic properties of protein-protein interactions have immensely contributed toward better understanding of the affinity of these complexes. But, more recent studies on hot spots and interface residues have opened up new avenues in the drug discovery process. This approach has been used in the design of hot spot based modulators targeting protein-protein interaction with the objective of normalizing such interactions.

Toward rules relating zinc finger protein sequences and DNA binding site preferences.

PubMed

Desjarlais, J R; Berg, J M

1992-08-15

Zinc finger proteins of the Cys2-His2 type consist of tandem arrays of domains, where each domain appears to contact three adjacent base pairs of DNA through three key residues. We have designed and prepared a series of variants of the central zinc finger within the DNA binding domain of Sp1 by using information from an analysis of a large data base of zinc finger protein sequences. Through systematic variations at two of the three contact positions (underlined), relatively specific recognition of sequences of the form 5'-GGGGN(G or T)GGG-3' has been achieved. These results provide the basis for rules that may develop into a code that will allow the design of zinc finger proteins with preselected DNA site specificity.

A protein relational database and protein family knowledge bases to facilitate structure-based design analyses.

PubMed

Mobilio, Dominick; Walker, Gary; Brooijmans, Natasja; Nilakantan, Ramaswamy; Denny, R Aldrin; Dejoannis, Jason; Feyfant, Eric; Kowticwar, Rupesh K; Mankala, Jyoti; Palli, Satish; Punyamantula, Sairam; Tatipally, Maneesh; John, Reji K; Humblet, Christine

2010-08-01

The Protein Data Bank is the most comprehensive source of experimental macromolecular structures. It can, however, be difficult at times to locate relevant structures with the Protein Data Bank search interface. This is particularly true when searching for complexes containing specific interactions between protein and ligand atoms. Moreover, searching within a family of proteins can be tedious. For example, one cannot search for some conserved residue as residue numbers vary across structures. We describe herein three databases, Protein Relational Database, Kinase Knowledge Base, and Matrix Metalloproteinase Knowledge Base, containing protein structures from the Protein Data Bank. In Protein Relational Database, atom-atom distances between protein and ligand have been precalculated allowing for millisecond retrieval based on atom identity and distance constraints. Ring centroids, centroid-centroid and centroid-atom distances and angles have also been included permitting queries for pi-stacking interactions and other structural motifs involving rings. Other geometric features can be searched through the inclusion of residue pair and triplet distances. In Kinase Knowledge Base and Matrix Metalloproteinase Knowledge Base, the catalytic domains have been aligned into common residue numbering schemes. Thus, by searching across Protein Relational Database and Kinase Knowledge Base, one can easily retrieve structures wherein, for example, a ligand of interest is making contact with the gatekeeper residue.

Interrogation of an autofluorescence-based method for protein fingerprinting.

PubMed

Siddaramaiah, Manjunath; Rao, Bola Sadashiva S; Joshi, Manjunath B; Datta, Anirbit; Sandya, S; Vishnumurthy, Vasudha; Chandra, Subhash; Nayak, Subramanya G; Satyamoorthy, Kapaettu; Mahato, Krishna K

2018-03-14

In the present study, we have designed a laser-induced fluorescence (LIF) based instrumentation and developed a sensitive methodology for the effective separation, visualization, identification and analysis of proteins on a single platform. In this method, intrinsic fluorescence spectra of proteins were detected after separation on 1 or 2 dimensional Sodium Dodecyl Sulfate-Tris(2-carboxyethyl)phosphine (SDS-TCEP) polyacrylamide gel electrophoresis (PAGE) and the data were analyzed. The MATLAB assisted software was designed for the development of PAGE fingerprint for the visualization of protein after 1- and 2-dimensional protein separation. These provided objective parameters of intrinsic fluorescence intensity, emission peak, molecular weight and isoelectric point using a single platform. Further, the current architecture could differentiate the overlapping proteins in the PAGE gels which otherwise were not identifiable by conventional staining, imaging and tagging methods. Categorization of the proteins based on the presence or absence of tyrosine or tryptophan residues and assigning the corresponding emission peaks (309-356 nm) with pseudo colors allowed the detection of proportion of proteins within the given spectrum. The present methodology doesn't use stains or tags, hence amenable to couple with mass spectroscopic measurements. This technique may have relevance in the field of proteomics that is used for innumerable applications. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Applications of cell-free protein synthesis in synthetic biology: Interfacing bio-machinery with synthetic environments.

PubMed

Lee, Kyung-Ho; Kim, Dong-Myung

2013-11-01

Synthetic biology is built on the synthesis, engineering, and assembly of biological parts. Proteins are the first components considered for the construction of systems with designed biological functions because proteins carry out most of the biological functions and chemical reactions inside cells. Protein synthesis is considered to comprise the most basic levels of the hierarchical structure of synthetic biology. Cell-free protein synthesis has emerged as a powerful technology that can potentially transform the concept of bioprocesses. With the ability to harness the synthetic power of biology without many of the constraints of cell-based systems, cell-free protein synthesis enables the rapid creation of protein molecules from diverse sources of genetic information. Cell-free protein synthesis is virtually free from the intrinsic constraints of cell-based methods and offers greater flexibility in system design and manipulability of biological synthetic machinery. Among its potential applications, cell-free protein synthesis can be combined with various man-made devices for rapid functional analysis of genomic sequences. This review covers recent efforts to integrate cell-free protein synthesis with various reaction devices and analytical platforms. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Advances in Understanding Stimulus Responsive Phase Behavior of Intrinsically Disordered Protein Polymers.

PubMed

Ruff, Kiersten M; Roberts, Stefan; Chilkoti, Ashutosh; Pappu, Rohit V

2018-06-24

Proteins and synthetic polymers can undergo phase transitions in response to changes to intensive solution parameters such as temperature, proton chemical potentials (pH), and hydrostatic pressure. For proteins and protein-based polymers, the information required for stimulus responsive phase transitions is encoded in their amino acid sequence. Here, we review some of the key physical principles that govern the phase transitions of archetypal intrinsically disordered protein polymers (IDPPs). These are disordered proteins with highly repetitive amino acid sequences. Advances in recombinant technologies have enabled the design and synthesis of protein sequences of a variety of sequence complexities and lengths. We summarize insights that have been gleaned from the design and characterization of IDPPs that undergo thermo-responsive phase transitions and build on these insights to present a general framework for IDPPs with pH and pressure responsive phase behavior. In doing so, we connect the stimulus responsive phase behavior of IDPPs with repetitive sequences to the coil-to-globule transitions that these sequences undergo at the single chain level in response to changes in stimuli. The proposed framework and ongoing studies of stimulus responsive phase behavior of designed IDPPs have direct implications in bioengineering, where designing sequences with bespoke material properties broadens the spectrum of applications, and in biology and medicine for understanding the sequence-specific driving forces for the formation of protein-based membraneless organelles as well as biological matrices that act as scaffolds for cells and mediators of cell-to-cell communication. Copyright © 2018. Published by Elsevier Ltd.

Computational design of a red fluorophore ligase for site-specific protein labeling in living cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Daniel S.; Nivon, Lucas G.; Richter, Florian

In this study, chemical fluorophores offer tremendous size and photophysical advantages over fluorescent proteins but are much more challenging to target to specific cellular proteins. Here, we used Rosetta-based computation to design a fluorophore ligase that accepts the red dye resorufin, starting from Escherichia coli lipoic acid ligase. X-ray crystallography showed that the design closely matched the experimental structure. Resorufin ligase catalyzed the site-specific and covalent attachment of resorufin to various cellular proteins genetically fused to a 13-aa recognition peptide in multiple mammalian cell lines and in primary cultured neurons. We used resorufin ligase to perform superresolution imaging of themore » intermediate filament protein vimentin by stimulated emission depletion and electron microscopies. This work illustrates the power of Rosetta for major redesign of enzyme specificity and introduces a tool for minimally invasive, highly specific imaging of cellular proteins by both conventional and superresolution microscopies.« less

Computational design of a red fluorophore ligase for site-specific protein labeling in living cells

DOE PAGES

Liu, Daniel S.; Nivon, Lucas G.; Richter, Florian; ...

2014-10-13

In this study, chemical fluorophores offer tremendous size and photophysical advantages over fluorescent proteins but are much more challenging to target to specific cellular proteins. Here, we used Rosetta-based computation to design a fluorophore ligase that accepts the red dye resorufin, starting from Escherichia coli lipoic acid ligase. X-ray crystallography showed that the design closely matched the experimental structure. Resorufin ligase catalyzed the site-specific and covalent attachment of resorufin to various cellular proteins genetically fused to a 13-aa recognition peptide in multiple mammalian cell lines and in primary cultured neurons. We used resorufin ligase to perform superresolution imaging of themore » intermediate filament protein vimentin by stimulated emission depletion and electron microscopies. This work illustrates the power of Rosetta for major redesign of enzyme specificity and introduces a tool for minimally invasive, highly specific imaging of cellular proteins by both conventional and superresolution microscopies.« less

Multivalent small molecule pan-RAS inhibitors

PubMed Central

Welsch, Matthew E.; Kaplan, Anna; Chambers, Jennifer M.; Stokes, Michael E.; Bos, Pieter H.; Zask, Arie; Zhang, Yan; Sanchez-Martin, Marta; Badgley, Michael A.; Huang, Christine S.; Tran, Timothy H.; Akkiraju, Hemanth; Brown, Lewis M.; Nandakumar, Renu; Cremers, Serge; Yang, Wan S.; Tong, Liang; Olive, Kenneth P.; Ferrando, Adolfo; Stockwell, Brent R.

2017-01-01

SUMMARY Design of small molecules that disrupt protein-protein interactions, including the interaction of RAS proteins and their effectors, have potential use as chemical probes and therapeutic agents. We describe here the synthesis and testing of potential small molecule pan-RAS ligands, which were designed to interact with adjacent sites on the surface of oncogenic KRAS. One compound, termed 3144, was found to bind to RAS proteins using microscale thermophoresis, nuclear magnetic resonance spectroscopy and isothermal titration calorimetry, and to exhibit lethality in cells partially dependent on expression of RAS proteins. This compound was metabolically stable in liver microsomes and displayed anti-tumor activity in xenograft mouse cancer models. These findings suggest that pan-RAS inhibition may be an effective therapeutic strategy for some cancers, and that structure-based design of small molecules targeting multiple adjacent sites to create multivalent inhibitors may be effective for some proteins. PMID:28235199

Semiconductor quantum dots as Förster resonance energy transfer donors for intracellularly-based biosensors

NASA Astrophysics Data System (ADS)

Field, Lauren D.; Walper, Scott A.; Susumu, Kimihiro; Oh, Eunkeu; Medintz, Igor L.; Delehanty, James B.

2017-02-01

Förster resonance energy transfer (FRET)-based assemblies currently comprise a significant portion of intracellularly based sensors. Although extremely useful, the fluorescent protein pairs typically utilized in such sensors are still plagued by many photophysical issues including significant direct acceptor excitation, small changes in FRET efficiency, and limited photostability. Luminescent semiconductor nanocrystals or quantum dots (QDs) are characterized by many unique optical properties including size-tunable photoluminescence, broad excitation profiles coupled to narrow emission profiles, and resistance to photobleaching, which can cumulatively overcome many of the issues associated with use of fluorescent protein FRET donors. Utilizing QDs for intracellular FRET-based sensing still requires significant development in many areas including materials optimization, bioconjugation, cellular delivery and assay design and implementation. We are currently developing several QD-based FRET sensors for various intracellular applications. These include sensors targeting intracellular proteolytic activity along with those based on theranostic nanodevices for monitoring drug release. The protease sensor is based on a unique design where an intracellularly expressed fluorescent acceptor protein substrate assembles onto a QD donor following microinjection, forming an active complex that can be monitored in live cells over time. In the theranostic configuration, the QD is conjugated to a carrier protein-drug analogue complex to visualize real-time intracellular release of the drug from its carrier in response to an external stimulus. The focus of this talk will be on the design, properties, photophysical characterization and cellular application of these sensor constructs.

Protein-protein recognition control by modulating electrostatic interactions.

PubMed

Han, Song; Yin, Shijin; Yi, Hong; Mouhat, Stéphanie; Qiu, Su; Cao, Zhijian; Sabatier, Jean-Marc; Wu, Yingliang; Li, Wenxin

2010-06-04

Protein-protein control recognition remains a huge challenge, and its development depends on understanding the chemical and biological mechanisms by which these interactions occur. Here we describe a protein-protein control recognition technique based on the dominant electrostatic interactions occurring between the proteins. We designed a potassium channel inhibitor, BmP05-T, that was 90.32% identical to wild-type BmP05. Negatively charged residues were translocated from the nonbinding interface to the binding interface of BmP05 inhibitor, such that BmP05-T now used BmP05 nonbinding interface as the binding interface. This switch demonstrated that nonbinding interfaces were able to control the orientation of protein binding interfaces in the process of protein-protein recognition. The novel function findings of BmP05-T peptide suggested that the control recognition technique described here had the potential for use in designing and utilizing functional proteins in many biological scenarios.

Bioengineered protein-based nanocage for drug delivery.

PubMed

Lee, Eun Jung; Lee, Na Kyeong; Kim, In-San

2016-11-15

Nature, in its wonders, presents and assembles the most intricate and delicate protein structures and this remarkable phenomenon occurs in all kingdom and phyla of life. Of these proteins, cage-like multimeric proteins provide spatial control to biological processes and also compartmentalizes compounds that may be toxic or unstable and avoids their contact with the environment. Protein-based nanocages are of particular interest because of their potential applicability as drug delivery carriers and their perfect and complex symmetry and ideal physical properties, which have stimulated researchers to engineer, modify or mimic these qualities. This article reviews various existing types of protein-based nanocages that are used for therapeutic purposes, and outlines their drug-loading mechanisms and bioengineering strategies via genetic and chemical functionalization. Through a critical evaluation of recent advances in protein nanocage-based drug delivery in vitro and in vivo, an outlook for de novo and in silico nanocage design, and also protein-based nanocage preclinical and future clinical applications will be presented. Copyright © 2016 Elsevier B.V. All rights reserved.

Design and engineering of water-soluble light-harvesting protein maquettes

DOE PAGES

Kodali, Goutham; Mancini, Joshua A.; Solomon, Lee A.; ...

2017-01-01

Natural selection in photosynthesis has engineered tetrapyrrole based, nanometer scale, light harvesting and energy capture in light-induced charge separation. By designing and creating nanometer scale artificial light harvesting and charge separating proteins, we have the opportunity to reengineer and overcome the limitations of natural selection to extend energy capture to new wavelengths and to tailor efficient systems that better meet human as opposed to cellular energetic needs. While tetrapyrrole cofactor incorporation in natural proteins is complex and often assisted by accessory proteins for cofactor transport and insertion, artificial protein functionalization relies on a practical understanding of the basic physical chemistrymore » of protein and cofactors that drive nanometer scale self-assembly. Patterning and balancing of hydrophobic and hydrophilic tetrapyrrole substituents is critical to avoid natural or synthetic porphyrin and chlorin aggregation in aqueous media and speed cofactor partitioning into the non-polar core of a man-made water soluble protein designed according to elementary first principles of protein folding. In conclusion, this partitioning is followed by site-specific anchoring of tetrapyrroles to histidine ligands strategically placed for design control of rates and efficiencies of light energy and electron transfer while orienting at least one polar group towards the aqueous phase.« less

Design and engineering of water-soluble light-harvesting protein maquettes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kodali, Goutham; Mancini, Joshua A.; Solomon, Lee A.

Natural selection in photosynthesis has engineered tetrapyrrole based, nanometer scale, light harvesting and energy capture in light-induced charge separation. By designing and creating nanometer scale artificial light harvesting and charge separating proteins, we have the opportunity to reengineer and overcome the limitations of natural selection to extend energy capture to new wavelengths and to tailor efficient systems that better meet human as opposed to cellular energetic needs. While tetrapyrrole cofactor incorporation in natural proteins is complex and often assisted by accessory proteins for cofactor transport and insertion, artificial protein functionalization relies on a practical understanding of the basic physical chemistrymore » of protein and cofactors that drive nanometer scale self-assembly. Patterning and balancing of hydrophobic and hydrophilic tetrapyrrole substituents is critical to avoid natural or synthetic porphyrin and chlorin aggregation in aqueous media and speed cofactor partitioning into the non-polar core of a man-made water soluble protein designed according to elementary first principles of protein folding. In conclusion, this partitioning is followed by site-specific anchoring of tetrapyrroles to histidine ligands strategically placed for design control of rates and efficiencies of light energy and electron transfer while orienting at least one polar group towards the aqueous phase.« less

Knowledge-based design of a biosensor to quantify localized ERK activation in living cells

PubMed Central

Kummer, Lutz; Hsu, Chia-Wen; Dagliyan, Onur; MacNevin, Christopher; Kaufholz, Melanie; Zimmermann, Bastian; Dokholyan, Nikolay V.; Hahn, Klaus M.; Plückthun, Andreas

2014-01-01

Summary Investigation of protein activation in living cells is fundamental to understand how proteins are influenced by the full complement of upstream regulators they experience. We describe here the generation of a biosensor based on the Designed Ankyrin Repeat Protein (DARPin) binding scaffold suited for intracellular applications. Combining selection and evolution from libraries, knowledge-based design and efficient and rapid testing of conjugate candidates, we created an ERK activity biosensor by derivatizing a DARPin specific for phosphorylated ERK (pERK) with a solvatochromic merocyanine dye (mero87), whose fluorescence increases upon pERK binding. The biosensor specifically responded to pERK2, recognized by its conformation, but not to non-phosphorylated ERK2 or other closely related mitogen-activated kinases tested. Activated endogenous ERK was visualized in mouse embryo fibroblasts incubated in 2% serum, revealing greater activation in the nucleus, perinuclear regions, and especially the nucleoli. Activity was greatly reduced by the MEK1/2 inhibitor U0126. The DARPin-based biosensor will serve as useful tool for studying biological functions of ERK in vitro and in vivo. PMID:23790495

Multiple target drug cocktail design for attacking the core network markers of four cancers using ligand-based and structure-based virtual screening methods

PubMed Central

2015-01-01

Background Computer-aided drug design has a long history of being applied to discover new molecules to treat various cancers, but it has always been focused on single targets. The development of systems biology has let scientists reveal more hidden mechanisms of cancers, but attempts to apply systems biology to cancer therapies remain at preliminary stages. Our lab has successfully developed various systems biology models for several cancers. Based on these achievements, we present the first attempt to combine multiple-target therapy with systems biology. Methods In our previous study, we identified 28 significant proteins--i.e., common core network markers--of four types of cancers as house-keeping proteins of these cancers. In this study, we ranked these proteins by summing their carcinogenesis relevance values (CRVs) across the four cancers, and then performed docking and pharmacophore modeling to do virtual screening on the NCI database for anti-cancer drugs. We also performed pathway analysis on these proteins using Panther and MetaCore to reveal more mechanisms of these cancer house-keeping proteins. Results We designed several approaches to discover targets for multiple-target cocktail therapies. In the first one, we identified the top 20 drugs for each of the 28 cancer house-keeping proteins, and analyzed the docking pose to further understand the interaction mechanisms of these drugs. After screening for duplicates, we found that 13 of these drugs could target 11 proteins simultaneously. In the second approach, we chose the top 5 proteins with the highest summed CRVs and used them as the drug targets. We built a pharmacophore and applied it to do virtual screening against the Life-Chemical library for anti-cancer drugs. Based on these results, wet-lab bio-scientists could freely investigate combinations of these drugs for multiple-target therapy for cancers, in contrast to the traditional single target therapy. Conclusions Combination of systems biology with computer-aided drug design could help us develop novel drug cocktails with multiple targets. We believe this will enhance the efficiency of therapeutic practice and lead to new directions for cancer therapy. PMID:26680552

CCBuilder: an interactive web-based tool for building, designing and assessing coiled-coil protein assemblies.

PubMed

Wood, Christopher W; Bruning, Marc; Ibarra, Amaurys Á; Bartlett, Gail J; Thomson, Andrew R; Sessions, Richard B; Brady, R Leo; Woolfson, Derek N

2014-11-01

The ability to accurately model protein structures at the atomistic level underpins efforts to understand protein folding, to engineer natural proteins predictably and to design proteins de novo. Homology-based methods are well established and produce impressive results. However, these are limited to structures presented by and resolved for natural proteins. Addressing this problem more widely and deriving truly ab initio models requires mathematical descriptions for protein folds; the means to decorate these with natural, engineered or de novo sequences; and methods to score the resulting models. We present CCBuilder, a web-based application that tackles the problem for a defined but large class of protein structure, the α-helical coiled coils. CCBuilder generates coiled-coil backbones, builds side chains onto these frameworks and provides a range of metrics to measure the quality of the models. Its straightforward graphical user interface provides broad functionality that allows users to build and assess models, in which helix geometry, coiled-coil architecture and topology and protein sequence can be varied rapidly. We demonstrate the utility of CCBuilder by assembling models for 653 coiled-coil structures from the PDB, which cover >96% of the known coiled-coil types, and by generating models for rarer and de novo coiled-coil structures. CCBuilder is freely available, without registration, at http://coiledcoils.chm.bris.ac.uk/app/cc_builder/. © The Author 2014. Published by Oxford University Press.

Design of a novel class of protein-based magnetic resonance imaging contrast agents for the molecular imaging of cancer biomarkers

PubMed Central

Xue, Shenghui; Qiao, Jingjuan; Pu, Fan; Cameron, Mathew; Yang, Jenny J.

2014-01-01

Magnetic resonance imaging (MRI) of disease biomarkers, especially cancer biomarkers, could potentially improve our understanding of the disease and drug activity during preclinical and clinical drug treatment and patient stratification. MRI contrast agents with high relaxivity and targeting capability to tumor biomarkers are highly required. Extensive work has been done to develop MRI contrast agents. However, only a few limited literatures report that protein residues can function as ligands to bind Gd3+ with high binding affinity, selectivity, and relaxivity. In this paper, we focus on reporting our current progress on designing a novel class of protein-based Gd3+ MRI contrast agents (ProCAs) equipped with several desirable capabilities for in vivo application of MRI of tumor biomarkers. We will first discuss our strategy for improving the relaxivity by a novel protein-based design. We then discuss the effect of increased relaxivity of ProCAs on improving the detection limits for MRI contrast agent, especially for in vivo application. We will further report our efforts to improve in vivo imaging capability and our achievement in molecular imaging of cancer biomarkers with potential preclinical and clinical applications. PMID:23335551

Designing Light-Activated Charge-Separating Proteins with a Naphthoquinone Amino Acid

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lichtenstein, Bruce R.; Bialas, Chris; Cerda, José F.

2015-09-14

The first principles design of manmade redox-protein maquettes is used to clarify the physical/chemical engineering supporting the mechanisms of natural enzymes with a view to recapitulate and surpass natural performance. Herein, we use intein-based protein semisynthesis to pair a synthetic naphthoquinone amino acid (Naq) with histidine-ligated photoactive metal–tetrapyrrole cofactors, creating a 100 μs photochemical charge separation unit akin to photosynthetic reaction centers. By using propargyl groups to protect the redox-active para-quinone during synthesis and assembly while permitting selective activation, we gain the ability to employ the quinone amino acid redox cofactor with the full set of natural amino acids inmore » protein design. Direct anchoring of quinone to the protein backbone permits secure and adaptable control of intraprotein electron-tunneling distances and rates.« less

Allosteric Modulation of protein oligomerization: an emerging approach to drug design

NASA Astrophysics Data System (ADS)

Gabizon, Ronen; Friedler, Assaf

2014-03-01

Many disease-related proteins are in equilibrium between different oligomeric forms. The regulation of this equilibrium plays a central role in maintaining the activity of these proteins in vitro and in vivo. Modulation of the oligomerization equilibrium of proteins by molecules that bind preferentially to a specific oligomeric state is emerging as a potential therapeutic strategy that can be applied to many biological systems such as cancer and viral infections. The target proteins for such compounds are diverse in structure and sequence, and may require different approaches for shifting their oligomerization equilibrium. The discovery of such oligomerization-modulating compounds is thus achieved based on existing structural knowledge about the specific target proteins, as well as on their interactions with partner proteins or with ligands. In silico design and combinatorial tools such as peptide arrays and phage display are also used for discovering compounds that modulate protein oligomerization. The current review highlights some of the recent developments in the design of compounds aimed at modulating the oligomerization equilibrium of proteins, including the "shiftides" approach developed in our lab.

Benchmarking protein classification algorithms via supervised cross-validation.

PubMed

Kertész-Farkas, Attila; Dhir, Somdutta; Sonego, Paolo; Pacurar, Mircea; Netoteia, Sergiu; Nijveen, Harm; Kuzniar, Arnold; Leunissen, Jack A M; Kocsor, András; Pongor, Sándor

2008-04-24

Development and testing of protein classification algorithms are hampered by the fact that the protein universe is characterized by groups vastly different in the number of members, in average protein size, similarity within group, etc. Datasets based on traditional cross-validation (k-fold, leave-one-out, etc.) may not give reliable estimates on how an algorithm will generalize to novel, distantly related subtypes of the known protein classes. Supervised cross-validation, i.e., selection of test and train sets according to the known subtypes within a database has been successfully used earlier in conjunction with the SCOP database. Our goal was to extend this principle to other databases and to design standardized benchmark datasets for protein classification. Hierarchical classification trees of protein categories provide a simple and general framework for designing supervised cross-validation strategies for protein classification. Benchmark datasets can be designed at various levels of the concept hierarchy using a simple graph-theoretic distance. A combination of supervised and random sampling was selected to construct reduced size model datasets, suitable for algorithm comparison. Over 3000 new classification tasks were added to our recently established protein classification benchmark collection that currently includes protein sequence (including protein domains and entire proteins), protein structure and reading frame DNA sequence data. We carried out an extensive evaluation based on various machine-learning algorithms such as nearest neighbor, support vector machines, artificial neural networks, random forests and logistic regression, used in conjunction with comparison algorithms, BLAST, Smith-Waterman, Needleman-Wunsch, as well as 3D comparison methods DALI and PRIDE. The resulting datasets provide lower, and in our opinion more realistic estimates of the classifier performance than do random cross-validation schemes. A combination of supervised and random sampling was used to construct model datasets, suitable for algorithm comparison.

Computational methods in preformulation study for pharmaceutical solid dosage forms of therapeutic proteins

NASA Astrophysics Data System (ADS)

Majee, Sutapa Biswas; Biswas, Gopa Roy

2017-06-01

Design and delivery of protein-based biopharmaceuticals needs detailed planning and strict monitoring of intermediate processing steps, storage conditions and container-closure system to ensure a stable, elegant and biopharmaceutically acceptable dosage form. Selection of manufacturing process variables and conditions along with packaging specifications can be achieved through properly designed preformulation study protocol for the formulation. Thermodynamic stability and biological activity of therapeutic proteins depend on folding-unfolding and three-dimensional packing dynamics of amino acid network in the protein molecule. Lack of favourable environment may cause protein aggregation with loss in activity and even fatal immunological reaction. Although lyophilization can enhance the stability of protein-based formulations in the solid state, it can induce protein unfolding leading to thermodynamic instability. Formulation stabilizers such as preservatives can also result in aggregation of therapeutic proteins. Modern instrumental techniques in conjunction with computational tools enable rapid and accurate prediction of amino acid sequence, thermodynamic parameters associated with protein folding and detection of aggregation "hot-spots." Globular proteins pose a challenge during investigations on their aggregation propensity. Biobetter therapeutic monoclonal antibodies with enhanced stability, solubility and reduced immunogenic potential can be designed through mutation of aggregation-prone zones. The objective of the present review article is to focus on the various analytical methods and computational approaches used in the study of thermodynamic stability and aggregation tendency of therapeutic proteins, with an aim to develop optimal and marketable formulation. Knowledge of protein dynamics through application of computational tools will provide the essential inputs and relevant information for successful and meaningful completion of preformulation studies on solid dosage forms of therapeutic proteins.

New valve and bonding designs for microfluidic biochips containing proteins.

PubMed

Lu, Chunmeng; Xie, Yubing; Yang, Yong; Cheng, Mark M-C; Koh, Chee-Guan; Bai, Yunling; Lee, L James; Juang, Yi-Je

2007-02-01

Two major concerns in the design and fabrication of microfluidic biochips are protein binding on the channel surface and protein denaturing during device assembly. In this paper, we describe new methods to solve these problems. A "fishbone" microvalve design based on the concept of superhydrophobicity was developed to replace the capillary valve in applications where the chip surface requires protein blocking to prevent nonspecific binding. Our experimental results show that the valve functions well in a CD-like ELISA device. The packaging of biochips containing pre-loaded proteins is also a challenging task since conventional sealing methods often require the use of high temperatures, electric voltages, or organic solvents that are detrimental to the protein activity. Using CO2 gas to enhance the diffusion of polymer molecules near the device surface can result in good bonding at low temperatures and low pressure. This bonding method has little influence on the activity of the pre-loaded proteins after bonding.

CCBuilder 2.0: Powerful and accessible coiled‐coil modeling

PubMed Central

Wood, Christopher W.

2017-01-01

Abstract The increased availability of user‐friendly and accessible computational tools for biomolecular modeling would expand the reach and application of biomolecular engineering and design. For protein modeling, one key challenge is to reduce the complexities of 3D protein folds to sets of parametric equations that nonetheless capture the salient features of these structures accurately. At present, this is possible for a subset of proteins, namely, repeat proteins. The α‐helical coiled coil provides one such example, which represents ≈ 3–5% of all known protein‐encoding regions of DNA. Coiled coils are bundles of α helices that can be described by a small set of structural parameters. Here we describe how this parametric description can be implemented in an easy‐to‐use web application, called CCBuilder 2.0, for modeling and optimizing both α‐helical coiled coils and polyproline‐based collagen triple helices. This has many applications from providing models to aid molecular replacement for X‐ray crystallography, in silico model building and engineering of natural and designed protein assemblies, and through to the creation of completely de novo “dark matter” protein structures. CCBuilder 2.0 is available as a web‐based application, the code for which is open‐source and can be downloaded freely. http://coiledcoils.chm.bris.ac.uk/ccbuilder2. Lay Summary We have created CCBuilder 2.0, an easy to use web‐based application that can model structures for a whole class of proteins, the α‐helical coiled coil, which is estimated to account for 3–5% of all proteins in nature. CCBuilder 2.0 will be of use to a large number of protein scientists engaged in fundamental studies, such as protein structure determination, through to more‐applied research including designing and engineering novel proteins that have potential applications in biotechnology. PMID:28836317

Gene Composer: database software for protein construct design, codon engineering, and gene synthesis

PubMed Central

Lorimer, Don; Raymond, Amy; Walchli, John; Mixon, Mark; Barrow, Adrienne; Wallace, Ellen; Grice, Rena; Burgin, Alex; Stewart, Lance

2009-01-01

Background To improve efficiency in high throughput protein structure determination, we have developed a database software package, Gene Composer, which facilitates the information-rich design of protein constructs and their codon engineered synthetic gene sequences. With its modular workflow design and numerous graphical user interfaces, Gene Composer enables researchers to perform all common bio-informatics steps used in modern structure guided protein engineering and synthetic gene engineering. Results An interactive Alignment Viewer allows the researcher to simultaneously visualize sequence conservation in the context of known protein secondary structure, ligand contacts, water contacts, crystal contacts, B-factors, solvent accessible area, residue property type and several other useful property views. The Construct Design Module enables the facile design of novel protein constructs with altered N- and C-termini, internal insertions or deletions, point mutations, and desired affinity tags. The modifications can be combined and permuted into multiple protein constructs, and then virtually cloned in silico into defined expression vectors. The Gene Design Module uses a protein-to-gene algorithm that automates the back-translation of a protein amino acid sequence into a codon engineered nucleic acid gene sequence according to a selected codon usage table with minimal codon usage threshold, defined G:C% content, and desired sequence features achieved through synonymous codon selection that is optimized for the intended expression system. The gene-to-oligo algorithm of the Gene Design Module plans out all of the required overlapping oligonucleotides and mutagenic primers needed to synthesize the desired gene constructs by PCR, and for physically cloning them into selected vectors by the most popular subcloning strategies. Conclusion We present a complete description of Gene Composer functionality, and an efficient PCR-based synthetic gene assembly procedure with mis-match specific endonuclease error correction in combination with PIPE cloning. In a sister manuscript we present data on how Gene Composer designed genes and protein constructs can result in improved protein production for structural studies. PMID:19383142

Gene composer: database software for protein construct design, codon engineering, and gene synthesis.

PubMed

Lorimer, Don; Raymond, Amy; Walchli, John; Mixon, Mark; Barrow, Adrienne; Wallace, Ellen; Grice, Rena; Burgin, Alex; Stewart, Lance

2009-04-21

To improve efficiency in high throughput protein structure determination, we have developed a database software package, Gene Composer, which facilitates the information-rich design of protein constructs and their codon engineered synthetic gene sequences. With its modular workflow design and numerous graphical user interfaces, Gene Composer enables researchers to perform all common bio-informatics steps used in modern structure guided protein engineering and synthetic gene engineering. An interactive Alignment Viewer allows the researcher to simultaneously visualize sequence conservation in the context of known protein secondary structure, ligand contacts, water contacts, crystal contacts, B-factors, solvent accessible area, residue property type and several other useful property views. The Construct Design Module enables the facile design of novel protein constructs with altered N- and C-termini, internal insertions or deletions, point mutations, and desired affinity tags. The modifications can be combined and permuted into multiple protein constructs, and then virtually cloned in silico into defined expression vectors. The Gene Design Module uses a protein-to-gene algorithm that automates the back-translation of a protein amino acid sequence into a codon engineered nucleic acid gene sequence according to a selected codon usage table with minimal codon usage threshold, defined G:C% content, and desired sequence features achieved through synonymous codon selection that is optimized for the intended expression system. The gene-to-oligo algorithm of the Gene Design Module plans out all of the required overlapping oligonucleotides and mutagenic primers needed to synthesize the desired gene constructs by PCR, and for physically cloning them into selected vectors by the most popular subcloning strategies. We present a complete description of Gene Composer functionality, and an efficient PCR-based synthetic gene assembly procedure with mis-match specific endonuclease error correction in combination with PIPE cloning. In a sister manuscript we present data on how Gene Composer designed genes and protein constructs can result in improved protein production for structural studies.

Rapid Diagnostic Assay for Intact Influenza Virus Using a High Affinity Hemagglutinin Binding Protein.

PubMed

Anderson, Caitlin E; Holstein, Carly A; Strauch, Eva-Maria; Bennett, Steven; Chevalier, Aaron; Nelson, Jorgen; Fu, Elain; Baker, David; Yager, Paul

2017-06-20

Influenza is a ubiquitous and recurring infection that results in approximately 500 000 deaths globally each year. Commercially available rapid diagnostic tests are based upon detection of the influenza nucleoprotein, which are limited in that they are unable to differentiate by species and require an additional viral lysis step. Sample preprocessing can be minimized or eliminated by targeting the intact influenza virus, thereby reducing assay complexity and leveraging the large number of hemagglutinin proteins on the surface of each virus. Here, we report the development of a paper-based influenza assay that targets the hemagglutinin protein; the assay employs a combination of antibodies and novel computationally designed, recombinant affinity proteins as the capture and detection agents. This system leverages the customizability of recombinant protein design to target the conserved receptor-binding pocket of the hemagglutinin protein and to match the trimeric nature of hemagglutinin for improved avidity. Using this assay, we demonstrate the first instance of intact influenza virus detection using a combination of antibody and affinity proteins within a porous network. The recombinant head region binder based assays yield superior analytical sensitivity as compared to the antibody based assay, with lower limits of detection of 3.54 × 10 7 and 1.34 × 10 7 CEID 50 /mL for the mixed and all binder stacks, respectively. Not only does this work describe the development of a novel influenza assay, it also demonstrates the power of recombinant affinity proteins for use in rapid diagnostic assays.

Structure-based functional annotation of putative conserved proteins having lyase activity from Haemophilus influenzae.

PubMed

Shahbaaz, Mohd; Ahmad, Faizan; Imtaiyaz Hassan, Md

2015-06-01

Haemophilus influenzae is a small pleomorphic Gram-negative bacteria which causes several chronic diseases, including bacteremia, meningitis, cellulitis, epiglottitis, septic arthritis, pneumonia, and empyema. Here we extensively analyzed the sequenced genome of H. influenzae strain Rd KW20 using protein family databases, protein structure prediction, pathways and genome context methods to assign a precise function to proteins whose functions are unknown. These proteins are termed as hypothetical proteins (HPs), for which no experimental information is available. Function prediction of these proteins would surely be supportive to precisely understand the biochemical pathways and mechanism of pathogenesis of Haemophilus influenzae. During the extensive analysis of H. influenzae genome, we found the presence of eight HPs showing lyase activity. Subsequently, we modeled and analyzed three-dimensional structure of all these HPs to determine their functions more precisely. We found these HPs possess cystathionine-β-synthase, cyclase, carboxymuconolactone decarboxylase, pseudouridine synthase A and C, D-tagatose-1,6-bisphosphate aldolase and aminodeoxychorismate lyase-like features, indicating their corresponding functions in the H. influenzae. Lyases are actively involved in the regulation of biosynthesis of various hormones, metabolic pathways, signal transduction, and DNA repair. Lyases are also considered as a key player for various biological processes. These enzymes are critically essential for the survival and pathogenesis of H. influenzae and, therefore, these enzymes may be considered as a potential target for structure-based rational drug design. Our structure-function relationship analysis will be useful to search and design potential lead molecules based on the structure of these lyases, for drug design and discovery.

Design of metal cofactors activated by a protein–protein electron transfer system

PubMed Central

Ueno, Takafumi; Yokoi, Norihiko; Unno, Masaki; Matsui, Toshitaka; Tokita, Yuichi; Yamada, Masako; Ikeda-Saito, Masao; Nakajima, Hiroshi; Watanabe, Yoshihito

2006-01-01

Protein-to-protein electron transfer (ET) is a critical process in biological chemistry for which fundamental understanding is expected to provide a wealth of applications in biotechnology. Investigations of protein–protein ET systems in reductive activation of artificial cofactors introduced into proteins remains particularly challenging because of the complexity of interactions between the cofactor and the system contributing to ET. In this work, we construct an artificial protein–protein ET system, using heme oxygenase (HO), which is known to catalyze the conversion of heme to biliverdin. HO uses electrons provided from NADPH/cytochrome P450 reductase (CPR) through protein–protein complex formation during the enzymatic reaction. We report that a FeIII(Schiff-base), in the place of the active-site heme prosthetic group of HO, can be reduced by NADPH/CPR. The crystal structure of the Fe(10-CH2CH2COOH-Schiff-base)·HO composite indicates the presence of a hydrogen bond between the propionic acid carboxyl group and Arg-177 of HO. Furthermore, the ET rate from NADPH/CPR to the composite is 3.5-fold faster than that of Fe(Schiff-base)·HO, although the redox potential of Fe(10-CH2CH2COOH-Schiff-base)·HO (−79 mV vs. NHE) is lower than that of Fe(Schiff-base)·HO (+15 mV vs. NHE), where NHE is normal hydrogen electrode. This work describes a synthetic metal complex activated by means of a protein–protein ET system, which has not previously been reported. Moreover, the result suggests the importance of the hydrogen bond for the ET reaction of HO. Our Fe(Schiff-base)·HO composite model system may provide insights with regard to design of ET biosystems for sensors, catalysts, and electronics devices. PMID:16769893

Boosting protein stability with the computational design of β-sheet surfaces.

PubMed

Kim, Doo Nam; Jacobs, Timothy M; Kuhlman, Brian

2016-03-01

β-sheets often have one face packed against the core of the protein and the other facing solvent. Mutational studies have indicated that the solvent-facing residues can contribute significantly to protein stability, and that the preferred amino acid at each sequence position is dependent on the precise structure of the protein backbone and the identity of the neighboring amino acids. This suggests that the most advantageous methods for designing β-sheet surfaces will be approaches that take into account the multiple energetic factors at play including side chain rotamer preferences, van der Waals forces, electrostatics, and desolvation effects. Here, we show that the protein design software Rosetta, which models these energetic factors, can be used to dramatically increase protein stability by optimizing interactions on the surfaces of small β-sheet proteins. Two design variants of the β-sandwich protein from tenascin were made with 7 and 14 mutations respectively on its β-sheet surfaces. These changes raised the thermal midpoint for unfolding from 45°C to 64°C and 74°C. Additionally, we tested an empirical approach based on increasing the number of potential salt bridges on the surfaces of the β-sheets. This was not a robust strategy for increasing stability, as three of the four variants tested were unfolded. © 2016 The Protein Society.

Structure-based drug design, synthesis and biological assays of P. falciparum Atg3-Atg8 protein-protein interaction inhibitors

NASA Astrophysics Data System (ADS)

Villa, Stefania; Legnani, Laura; Colombo, Diego; Gelain, Arianna; Lammi, Carmen; Bongiorno, Daniele; Ilboudo, Denise P.; McGee, Kellen E.; Bosch, Jürgen; Grazioso, Giovanni

2018-03-01

The proteins involved in the autophagy (Atg) pathway have recently been considered promising targets for the development of new antimalarial drugs. In particular, inhibitors of the protein-protein interaction (PPI) between Atg3 and Atg8 of Plasmodium falciparum retarded the blood- and liver-stages of parasite growth. In this paper, we used computational techniques to design a new class of peptidomimetics mimicking the Atg3 interaction motif, which were then synthesized by click-chemistry. Surface plasmon resonance has been employed to measure the ability of these compounds to inhibit the Atg3-Atg8 reciprocal protein-protein interaction. Moreover, P. falciparum growth inhibition in red blood cell cultures was evaluated as well as the cyto-toxicity of the compounds.

Structure-based approach to the prediction of disulfide bonds in proteins.

PubMed

Salam, Noeris K; Adzhigirey, Matvey; Sherman, Woody; Pearlman, David A

2014-10-01

Protein engineering remains an area of growing importance in pharmaceutical and biotechnology research. Stabilization of a folded protein conformation is a frequent goal in projects that deal with affinity optimization, enzyme design, protein construct design, and reducing the size of functional proteins. Indeed, it can be desirable to assess and improve protein stability in order to avoid liabilities such as aggregation, degradation, and immunogenic response that may arise during development. One way to stabilize a protein is through the introduction of disulfide bonds. Here, we describe a method to predict pairs of protein residues that can be mutated to form a disulfide bond. We combine a physics-based approach that incorporates implicit solvent molecular mechanics with a knowledge-based approach. We first assign relative weights to the terms that comprise our scoring function using a genetic algorithm applied to a set of 75 wild-type structures that each contains a disulfide bond. The method is then tested on a separate set of 13 engineered proteins comprising 15 artificial stabilizing disulfides introduced via site-directed mutagenesis. We find that the native disulfide in the wild-type proteins is scored well, on average (within the top 6% of the reasonable pairs of residues that could form a disulfide bond) while 6 out of the 15 artificial stabilizing disulfides scored within the top 13% of ranked predictions. Overall, this suggests that the physics-based approach presented here can be useful for triaging possible pairs of mutations for disulfide bond formation to improve protein stability. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Designing ECM-mimetic Materials Using Protein Engineering

PubMed Central

Cai, Lei; Heilshorn, Sarah C.

2014-01-01

The natural extracellular matrix (ECM), with its multitude of evolved cell-instructive and cell-responsive properties, provides inspiration and guidelines for the design of engineered biomaterials. One strategy to create ECM-mimetic materials is the modular design of protein-based engineered ECM (eECM) scaffolds. This modular design strategy involves combining multiple protein domains with different functionalities into a single, modular polymer sequence, resulting in a multifunctional matrix with independent tunability of the individual domain functions. These eECMs often enable decoupled control over multiple material properties for fundamental studies of cell-matrix interactions. In addition, since the eECMs are frequently composed entirely of bioresorbable amino acids, these matrices have immense clinical potential for a variety of regenerative medicine applications. This brief review demonstrates how fundamental knowledge gained from structure-function studies of native proteins can be exploited in the design of novel protein-engineered biomaterials. While the field of protein-engineered biomaterials has existed for over 20 years, the community is only now beginning to fully explore the diversity of functional peptide modules that can be incorporated into these materials. We have chosen to highlight recent examples that either (1) demonstrate exemplary use as matrices with cell-instructive and cell-responsive properties or (2) demonstrate outstanding creativity in terms of novel molecular-level design and macro-level functionality. PMID:24365704

Automated Structure- and Sequence-Based Design of Proteins for High Bacterial Expression and Stability.

PubMed

Goldenzweig, Adi; Goldsmith, Moshe; Hill, Shannon E; Gertman, Or; Laurino, Paola; Ashani, Yacov; Dym, Orly; Unger, Tamar; Albeck, Shira; Prilusky, Jaime; Lieberman, Raquel L; Aharoni, Amir; Silman, Israel; Sussman, Joel L; Tawfik, Dan S; Fleishman, Sarel J

2016-07-21

Upon heterologous overexpression, many proteins misfold or aggregate, thus resulting in low functional yields. Human acetylcholinesterase (hAChE), an enzyme mediating synaptic transmission, is a typical case of a human protein that necessitates mammalian systems to obtain functional expression. We developed a computational strategy and designed an AChE variant bearing 51 mutations that improved core packing, surface polarity, and backbone rigidity. This variant expressed at ∼2,000-fold higher levels in E. coli compared to wild-type hAChE and exhibited 20°C higher thermostability with no change in enzymatic properties or in the active-site configuration as determined by crystallography. To demonstrate broad utility, we similarly designed four other human and bacterial proteins. Testing at most three designs per protein, we obtained enhanced stability and/or higher yields of soluble and active protein in E. coli. Our algorithm requires only a 3D structure and several dozen sequences of naturally occurring homologs, and is available at http://pross.weizmann.ac.il. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

Structure-based approach to rationally design a chimeric protein for an effective vaccine against Group B Streptococcus infections.

PubMed

Nuccitelli, Annalisa; Cozzi, Roberta; Gourlay, Louise J; Donnarumma, Danilo; Necchi, Francesca; Norais, Nathalie; Telford, John L; Rappuoli, Rino; Bolognesi, Martino; Maione, Domenico; Grandi, Guido; Rinaudo, C Daniela

2011-06-21

Structural vaccinology is an emerging strategy for the rational design of vaccine candidates. We successfully applied structural vaccinology to design a fully synthetic protein with multivalent protection activity. In Group B Streptococcus, cell-surface pili have aroused great interest because of their direct roles in virulence and importance as protective antigens. The backbone subunit of type 2a pilus (BP-2a) is present in six immunogenically different but structurally similar variants. We determined the 3D structure of one of the variants, and experimentally demonstrated that protective antibodies specifically recognize one of the four domains that comprise the protein. We therefore constructed a synthetic protein constituted by the protective domain of each one of the six variants and showed that the chimeric protein protects mice against the challenge with all of the type 2a pilus-carrying strains. This work demonstrates the power of structural vaccinology and will facilitate the development of an optimized, broadly protective pilus-based vaccine against Group B Streptococcus by combining the uniquely generated chimeric protein with protective pilin subunits from two other previously identified pilus types. In addition, this work describes a template procedure that can be followed to develop vaccines against other bacterial pathogens.

Ratiometric Matryoshka biosensors from a nested cassette of green- and orange-emitting fluorescent proteins.

PubMed

Ast, Cindy; Foret, Jessica; Oltrogge, Luke M; De Michele, Roberto; Kleist, Thomas J; Ho, Cheng-Hsun; Frommer, Wolf B

2017-09-05

Sensitivity, dynamic and detection range as well as exclusion of expression and instrumental artifacts are critical for the quantitation of data obtained with fluorescent protein (FP)-based biosensors in vivo. Current biosensors designs are, in general, unable to simultaneously meet all these criteria. Here, we describe a generalizable platform to create dual-FP biosensors with large dynamic ranges by employing a single FP-cassette, named GO-(Green-Orange) Matryoshka. The cassette nests a stable reference FP (large Stokes shift LSSmOrange) within a reporter FP (circularly permuted green FP). GO- Matryoshka yields green and orange fluorescence upon blue excitation. As proof of concept, we converted existing, single-emission biosensors into a series of ratiometric calcium sensors (MatryoshCaMP6s) and ammonium transport activity sensors (AmTryoshka1;3). We additionally identified the internal acid-base equilibrium as a key determinant of the GCaMP dynamic range. Matryoshka technology promises flexibility in the design of a wide spectrum of ratiometric biosensors and expanded in vivo applications.Single fluorescent protein biosensors are susceptible to expression and instrumental artifacts. Here Ast et al. describe a dual fluorescent protein design whereby a reference fluorescent protein is nested within a reporter fluorescent protein to control for such artifacts while preserving sensitivity and dynamic range.

A facile inhibitor screening of SARS coronavirus N protein using nanoparticle-based RNA oligonucleotide.

PubMed

Roh, Changhyun

2012-01-01

Hundreds of million people worldwide have been infected with severe acute respiratory syndrome (SARS), and the rate of global death from SARS has remarkably increased. Hence, the development of efficient drug treatments for the biological effects of SARS is highly needed. We have previously shown that quantum dots (QDs)-conjugated RNA oligonucleotide is sensitive to the specific recognition of the SARS-associated coronavirus (SARS-CoV) nucleocapsid (N) protein. In this study, we found that a designed biochip could analyze inhibitors of the SARS-CoV N protein using nanoparticle-based RNA oligonucleotide. Among the polyphenolic compounds examined, (-)-catechin gallate and (-)-gallocatechin gallate demonstrated a remarkable inhibition activity on SARS-CoV N protein. (-)-catechin gallate and (-)-gallocatechin gallate attenuated the binding affinity in a concentrated manner as evidenced by QDs-conjugated RNA oligonucleotide on a designed biochip. At a concentration of 0.05 μg mL(-1), (-)-catechin gallate and (-)-gallocatechin gallate showed more than 40% inhibition activity on a nanoparticle-based RNA oligonucleotide biochip system.

The development of a thermostable CiP (Coprinus cinereus peroxidase) through in silico design.

PubMed

Kim, Su Jin; Lee, Jeong Ah; Joo, Jeong Chan; Yoo, Young Je; Kim, Yong Hwan; Song, Bong Keun

2010-01-01

Protein thermostability is a crucial issue in the practical application of enzymes, such as inorganic synthesis and enzymatic polymerization of phenol derivatives. Much attention has been focused on the enhancement and numerous successes have been achieved through protein engineering methods. Despite fruitful results based on random mutagenesis, it was still necessary to develop a novel strategy that can reduce the time and effort involved in this process. In this study, a rapid and effective strategy is described for increasing the thermal stability of a protein. Instead of random mutagenesis, a rational strategy was adopted to theoretically stabilize the thermo labile residues of a protein using computational methods. Protein residues with high flexibility can be thermo labile due to their large range of movement. Here, residue B factor values were used to identify putatively thermo labile residues and the RosettaDesign program was applied to search for stable sequences. Coprinus cinereus (CiP) heme peroxidase was selected as a model protein for its importance in commercial applications, such as the polymerization of phenolic compounds. Eleven CiP residues with the highest B factor values were chosen as target mutation sites for thermostabilization, and then redesigned using RosettaDesign to identify sequences. Eight mutants based on the redesigns, were produced as functional enzymes and two of these (S323Y and E328D) showed increased thermal stability over the wild-type in addition to conserved catalytic activity. Thus, this strategy can be used as a rapid and effective in silico design tool for obtaining thermostable proteins. (c) 2010 American Institute of Chemical Engineers

Application of the fragment molecular orbital method analysis to fragment-based drug discovery of BET (bromodomain and extra-terminal proteins) inhibitors.

PubMed

Ozawa, Motoyasu; Ozawa, Tomonaga; Ueda, Kazuyoshi

2017-06-01

The molecular interactions of inhibitors of bromodomains (BRDs) were investigated. BRDs are protein interaction modules that recognizing ε-N-acetyl-lysine (εAc-Lys) motifs found in histone tails and are promising protein-protein interaction (PPI) targets. First, we analyzed a peptide ligand containing εAc-Lys to evaluate native PPIs. We then analyzed tetrahydroquinazoline-6-yl-benzensulfonamide derivatives found by fragment-based drug design (FBDD) and examined their interactions with the protein compared with the peptide ligand in terms of the inter-fragment interaction energy. In addition, we analyzed benzodiazepine derivatives that are high-affinity ligands for BRDs and examined differences in the CH/π interactions of the amino acid residues. We further surveyed changes in the charges of the amino acid residues among individual ligands, performed pair interaction energy decomposition analysis and estimated the water profile within the ligand binding site. Thus, useful insights for drug design were provided. Through these analyses and considerations, we show that the FMO method is a useful drug design tool to evaluate the process of FBDD and to explore PPI inhibitors. Copyright © 2017 Elsevier Inc. All rights reserved.

Development of a Dehalogenase-Based Protein Fusion Tag Capable of Rapid, Selective and Covalent Attachment to Customizable Ligands

PubMed Central

Encell, Lance P; Friedman Ohana, Rachel; Zimmerman, Kris; Otto, Paul; Vidugiris, Gediminas; Wood, Monika G; Los, Georgyi V; McDougall, Mark G; Zimprich, Chad; Karassina, Natasha; Learish, Randall D; Hurst, Robin; Hartnett, James; Wheeler, Sarah; Stecha, Pete; English, Jami; Zhao, Kate; Mendez, Jacqui; Benink, Hélène A; Murphy, Nancy; Daniels, Danette L; Slater, Michael R; Urh, Marjeta; Darzins, Aldis; Klaubert, Dieter H; Bulleit, Robert F; Wood, Keith V

2012-01-01

Our fundamental understanding of proteins and their biological significance has been enhanced by genetic fusion tags, as they provide a convenient method for introducing unique properties to proteins so that they can be examinedin isolation. Commonly used tags satisfy many of the requirements for applications relating to the detection and isolation of proteins from complex samples. However, their utility at low concentration becomes compromised if the binding affinity for a detection or capture reagent is not adequate to produce a stable interaction. Here, we describe HaloTag® (HT7), a genetic fusion tag based on a modified haloalkane dehalogenase designed and engineered to overcome the limitation of affinity tags by forming a high affinity, covalent attachment to a binding ligand. HT7 and its ligand have additional desirable features. The tag is relatively small, monomeric, and structurally compatible with fusion partners, while the ligand is specific, chemically simple, and amenable to modular synthetic design. Taken together, the design features and molecular evolution of HT7 have resulted in a superior alternative to common tags for the overexpression, detection, and isolation of target proteins. PMID:23248739

Structural interaction fingerprints: a new approach to organizing, mining, analyzing, and designing protein-small molecule complexes.

PubMed

Singh, Juswinder; Deng, Zhan; Narale, Gaurav; Chuaqui, Claudio

2006-01-01

The combination of advances in structure-based drug design efforts in the pharmaceutical industry in parallel with structural genomics initiatives in the public domain has led to an explosion in the number of structures of protein-small molecule complexes structures. This information has critical importance to both the understanding of the structural basis for molecular recognition in biological systems and the design of better drugs. A significant challenge exists in managing this vast amount of data and fully leveraging it. Here, we review our work to develop a simple, fast way to store, organize, mine, and analyze large numbers of protein-small molecule complexes. We illustrate the utility of the approach to the management of inhibitor complexes from the protein kinase family. Finally, we describe our recent efforts in applying this method to the design of target-focused chemical libraries.

Synthesis and characterization of recombinant abductin-based proteins.

PubMed

Su, Renay S-C; Renner, Julie N; Liu, Julie C

2013-12-09

Recombinant proteins are promising tools for tissue engineering and drug delivery applications. Protein-based biomaterials have several advantages over natural and synthetic polymers, including precise control over amino acid composition and molecular weight, modular swapping of functional domains, and tunable mechanical and physical properties. In this work, we describe recombinant proteins based on abductin, an elastomeric protein that is found in the inner hinge of bivalves and functions as a coil spring to keep shells open. We illustrate, for the first time, the design, cloning, expression, and purification of a recombinant protein based on consensus abductin sequences derived from Argopecten irradians . The molecular weight of the protein was confirmed by mass spectrometry, and the protein was 94% pure. Circular dichroism studies showed that the dominant structures of abductin-based proteins were polyproline II helix structures in aqueous solution and type II β-turns in trifluoroethanol. Dynamic light scattering studies illustrated that the abductin-based proteins exhibit reversible upper critical solution temperature behavior and irreversible aggregation behavior at high temperatures. A LIVE/DEAD assay revealed that human umbilical vein endothelial cells had a viability of 98 ± 4% after being cultured for two days on the abductin-based protein. Initial cell spreading on the abductin-based protein was similar to that on bovine serum albumin. These studies thus demonstrate the potential of abductin-based proteins in tissue engineering and drug delivery applications due to the cytocompatibility and its response to temperature.

Bio-Inspired Protein-Based Nanoformulations for Cancer Theranostics

PubMed Central

Gou, Yi; Miao, Dandan; Zhou, Min; Wang, Lijuan; Zhou, Hongyu; Su, Gaoxing

2018-01-01

Over the past decade, more interests have been aroused in engineering protein-based nanoformulations for cancer treatment. This excitement originates from the success of FDA approved Abraxane (Albumin-based paclitaxel nanoparticles) in 2005. The new generation of biocompatible endogenous protein-based nanoformulations is currently constructed through delivering cancer therapeutic and diagnostic agents simultaneously, as named potential theranostics. Protein nanoformulations are commonly incorporated with dyes, contrast agents, drug payloads or inorganic nanoclusters, serving as imaging-guided combinatorial cancer therapeutics. Employing the nature identity of proteins, the theranostics, escape the clearance by reticuloendothelial cells and have a long blood circulation time. The nanoscale sizet allows them to be penetrated deeply into tumor tissues. In addition, stimuli release and targeted molecules are incorporated to improve the delivery efficiency. The ongoing advancement of protein-based nanoformulations for cancer theranostics in recent 5 years is reviewed in this paper. Fine-designed nanoformulations based on albumin, ferritin, gelatin, and transferrin are highlighted from the literature. Finally, the current challenges are identified in translating protein-based nanoformulations from laboratory to clinical trials. PMID:29755355

Altering the orientation of a fused protein to the RNA-binding ribosomal protein L7Ae and its derivatives through circular permutation.

PubMed

Ohuchi, Shoji J; Sagawa, Fumihiko; Sakamoto, Taiichi; Inoue, Tan

2015-10-23

RNA-protein complexes (RNPs) are useful for constructing functional nano-objects because a variety of functional proteins can be displayed on a designed RNA scaffold. Here, we report circular permutations of an RNA-binding protein L7Ae based on the three-dimensional structure information to alter the orientation of the displayed proteins on the RNA scaffold. An electrophoretic mobility shift assay and atomic force microscopy (AFM) analysis revealed that most of the designed circular permutants formed an RNP nano-object. Moreover, the alteration of the enhanced green fluorescent protein (EGFP) orientation was confirmed with AFM by employing EGFP on the L7Ae permutant on the RNA. The results demonstrate that targeted fine-tuning of the stereo-specific fixation of a protein on a protein-binding RNA is feasible by using the circular permutation technique. Copyright © 2015 Elsevier Inc. All rights reserved.

Altering the orientation of a fused protein to the RNA-binding ribosomal protein L7Ae and its derivatives through circular permutation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ohuchi, Shoji J.; Sagawa, Fumihiko; Sakamoto, Taiichi

RNA-protein complexes (RNPs) are useful for constructing functional nano-objects because a variety of functional proteins can be displayed on a designed RNA scaffold. Here, we report circular permutations of an RNA-binding protein L7Ae based on the three-dimensional structure information to alter the orientation of the displayed proteins on the RNA scaffold. An electrophoretic mobility shift assay and atomic force microscopy (AFM) analysis revealed that most of the designed circular permutants formed an RNP nano-object. Moreover, the alteration of the enhanced green fluorescent protein (EGFP) orientation was confirmed with AFM by employing EGFP on the L7Ae permutant on the RNA. Themore » results demonstrate that targeted fine-tuning of the stereo-specific fixation of a protein on a protein-binding RNA is feasible by using the circular permutation technique.« less

Engineering and Application of LOV2-based Photoswitches

PubMed Central

Zimmerman, Seth Parker; Kuhlman, Brian; Yumerefendi, Hayretin

2017-01-01

Cellular optogenetic switches, a novel class of biological tools, have improved our understanding of biological phenomena that were previously intractable. While the design and engineering of these proteins has historically varied they are all based on borrowed elements from plant and bacterial photoreceptors. In general terms, each of the optogenetic switches designed to date exploits the endogenous light induced change in photoreceptor conformation while repurposing its effect to target a different biological phenomena. We focus on the well-characterized Light Oxygen Voltage 2 (LOV2) domain from Avena sativa phototropin 1 as our cornerstone for design. While the function of the LOV2 domain in the context of the phototropin protein is not fully elucidated, its thorough biophysical characterization as an isolated domain has created a strong foundation for engineering of photoswitches. In this chapter, we examine the biophysical characteristics of the LOV2 domain that may be exploited to produce an optogenetic protein and summarize previous design efforts to provide guidelines for an effective design. Furthermore, we provide protocols for assays including fluorescent polarization, phage display, and microscopy that are optimized for validating, improving, and using newly designed photoswitches. PMID:27586333

Rapid Design of Knowledge-Based Scoring Potentials for Enrichment of Near-Native Geometries in Protein-Protein Docking.

PubMed

Sasse, Alexander; de Vries, Sjoerd J; Schindler, Christina E M; de Beauchêne, Isaure Chauvot; Zacharias, Martin

2017-01-01

Protein-protein docking protocols aim to predict the structures of protein-protein complexes based on the structure of individual partners. Docking protocols usually include several steps of sampling, clustering, refinement and re-scoring. The scoring step is one of the bottlenecks in the performance of many state-of-the-art protocols. The performance of scoring functions depends on the quality of the generated structures and its coupling to the sampling algorithm. A tool kit, GRADSCOPT (GRid Accelerated Directly SCoring OPTimizing), was designed to allow rapid development and optimization of different knowledge-based scoring potentials for specific objectives in protein-protein docking. Different atomistic and coarse-grained potentials can be created by a grid-accelerated directly scoring dependent Monte-Carlo annealing or by a linear regression optimization. We demonstrate that the scoring functions generated by our approach are similar to or even outperform state-of-the-art scoring functions for predicting near-native solutions. Of additional importance, we find that potentials specifically trained to identify the native bound complex perform rather poorly on identifying acceptable or medium quality (near-native) solutions. In contrast, atomistic long-range contact potentials can increase the average fraction of near-native poses by up to a factor 2.5 in the best scored 1% decoys (compared to existing scoring), emphasizing the need of specific docking potentials for different steps in the docking protocol.

Rapid Sampling of Hydrogen Bond Networks for Computational Protein Design.

PubMed

Maguire, Jack B; Boyken, Scott E; Baker, David; Kuhlman, Brian

2018-05-08

Hydrogen bond networks play a critical role in determining the stability and specificity of biomolecular complexes, and the ability to design such networks is important for engineering novel structures, interactions, and enzymes. One key feature of hydrogen bond networks that makes them difficult to rationally engineer is that they are highly cooperative and are not energetically favorable until the hydrogen bonding potential has been satisfied for all buried polar groups in the network. Existing computational methods for protein design are ill-equipped for creating these highly cooperative networks because they rely on energy functions and sampling strategies that are focused on pairwise interactions. To enable the design of complex hydrogen bond networks, we have developed a new sampling protocol in the molecular modeling program Rosetta that explicitly searches for sets of amino acid mutations that can form self-contained hydrogen bond networks. For a given set of designable residues, the protocol often identifies many alternative sets of mutations/networks, and we show that it can readily be applied to large sets of residues at protein-protein interfaces or in the interior of proteins. The protocol builds on a recently developed method in Rosetta for designing hydrogen bond networks that has been experimentally validated for small symmetric systems but was not extensible to many larger protein structures and complexes. The sampling protocol we describe here not only recapitulates previously validated designs with performance improvements but also yields viable hydrogen bond networks for cases where the previous method fails, such as the design of large, asymmetric interfaces relevant to engineering protein-based therapeutics.

A Problem-Based Learning Design for Teaching Biochemistry.

ERIC Educational Resources Information Center

Dods, Richard F.

1996-01-01

Describes the design of a biochemistry course that uses problem-based learning. Provides opportunities for students to question, dispute, confirm, and disconfirm their understanding of basic concepts. Emphasizes self-correction through dialogue. Topics covered include amino acids, metabolic pathways and inherited disease, proteins, enzymes and…

OSPREY: protein design with ensembles, flexibility, and provable algorithms.

PubMed

Gainza, Pablo; Roberts, Kyle E; Georgiev, Ivelin; Lilien, Ryan H; Keedy, Daniel A; Chen, Cheng-Yu; Reza, Faisal; Anderson, Amy C; Richardson, David C; Richardson, Jane S; Donald, Bruce R

2013-01-01

We have developed a suite of protein redesign algorithms that improves realistic in silico modeling of proteins. These algorithms are based on three characteristics that make them unique: (1) improved flexibility of the protein backbone, protein side-chains, and ligand to accurately capture the conformational changes that are induced by mutations to the protein sequence; (2) modeling of proteins and ligands as ensembles of low-energy structures to better approximate binding affinity; and (3) a globally optimal protein design search, guaranteeing that the computational predictions are optimal with respect to the input model. Here, we illustrate the importance of these three characteristics. We then describe OSPREY, a protein redesign suite that implements our protein design algorithms. OSPREY has been used prospectively, with experimental validation, in several biomedically relevant settings. We show in detail how OSPREY has been used to predict resistance mutations and explain why improved flexibility, ensembles, and provability are essential for this application. OSPREY is free and open source under a Lesser GPL license. The latest version is OSPREY 2.0. The program, user manual, and source code are available at www.cs.duke.edu/donaldlab/software.php. osprey@cs.duke.edu. Copyright © 2013 Elsevier Inc. All rights reserved.

[Visualization and Functional Regulation of Live Cell Proteins Based on Labeling Probe Design].

PubMed

Mizukami, Shin; Kikuchi, Kazuya

2016-01-01

  There are several approaches to understanding the physiological roles of biomolecules: (1) by observing the localization or activities of biomolecules (based on microscopic imaging experiments with fluorescent proteins or fluorescent probes) and (2) by investigating the cellular response via activation or suppression of functions of the target molecule (by using inhibitors, antagonists, siRNAs, etc.). In this context, protein-labeling technology serves as a powerful tool that can be used in various experiments, such as for fluorescence imaging of target proteins. Recently, we developed a protein-labeling technology that uses a mutant β-lactamase (a bacterial hydrolase) as the tag protein. In this protein-labeling technology, also referred to as the BL-tag technology, various β-lactam compounds were used as specific ligands that were covalently labeled to the tag. One major advantage of this labeling technology is that various functions can be carried out by suitably designing both the functional moieties such as the fluorophore and the β-lactam ligand structure. In this review, we briefly introduce the BL-tag technology and describe our future outlook for this technology, such as in fluorescence imaging of biomolecules and functional regulation of cellular proteins in living cells.

Enzyme-Triggered Defined Protein Nanoarrays: Efficient Light-Harvesting Systems to Mimic Chloroplasts.

PubMed

Zhao, Linlu; Zou, Haoyang; Zhang, Hao; Sun, Hongcheng; Wang, Tingting; Pan, Tiezheng; Li, Xiumei; Bai, Yushi; Qiao, Shanpeng; Luo, Quan; Xu, Jiayun; Hou, Chunxi; Liu, Junqiu

2017-01-24

The elegance and efficiency by which chloroplasts harvest solar energy and conduct energy transfer have been a source of inspiration for chemists to mimic such process. However, precise manipulation to obtain orderly arranged antenna chromophores in constructing artificial chloroplast mimics was a great challenge, especially from the structural similarity and bioaffinity standpoints. Here we reported a design strategy that combined covalent and noncovalent interactions to prepare a protein-based light-harvesting system to mimic chloroplasts. Cricoid stable protein one (SP1) was utilized as a building block model. Under enzyme-triggered covalent protein assembly, mutant SP1 with tyrosine (Tyr) residues at the designated sites can couple together to form nanostructures. Through controlling the Tyr sites on the protein surface, we can manipulate the assembly orientation to respectively generate 1D nanotubes and 2D nanosheets. The excellent stability endowed the self-assembled protein architectures with promising applications. We further integrated quantum dots (QDs) possessing optical and electronic properties with the 2D nanosheets to fabricate chloroplast mimics. By attaching different sized QDs as donor and acceptor chromophores to the negatively charged surface of SP1-based protein nanosheets via electrostatic interactions, we successfully developed an artificial light-harvesting system. The assembled protein nanosheets structurally resembled the natural thylakoids, and the QDs can achieve pronounced FRET phenomenon just like the chlorophylls. Therefore, the coassembled system was meaningful to explore the photosynthetic process in vitro, as it was designed to mimic the natural chloroplast.

Rule-Based Design of Plant Expression Vectors Using GenoCAD.

PubMed

Coll, Anna; Wilson, Mandy L; Gruden, Kristina; Peccoud, Jean

2015-01-01

Plant synthetic biology requires software tools to assist on the design of complex multi-genic expression plasmids. Here a vector design strategy to express genes in plants is formalized and implemented as a grammar in GenoCAD, a Computer-Aided Design software for synthetic biology. It includes a library of plant biological parts organized in structural categories and a set of rules describing how to assemble these parts into large constructs. Rules developed here are organized and divided into three main subsections according to the aim of the final construct: protein localization studies, promoter analysis and protein-protein interaction experiments. The GenoCAD plant grammar guides the user through the design while allowing users to customize vectors according to their needs. Therefore the plant grammar implemented in GenoCAD will help plant biologists take advantage of methods from synthetic biology to design expression vectors supporting their research projects.

Computational design of trimeric influenza-neutralizing proteins targeting the hemagglutinin receptor binding site

DOE Office of Scientific and Technical Information (OSTI.GOV)

Strauch, Eva-Maria; Bernard, Steffen M.; La, David

Many viral surface glycoproteins and cell surface receptors are homo-oligomers1, 2, 3, 4, and thus can potentially be targeted by geometrically matched homo-oligomers that engage all subunits simultaneously to attain high avidity and/or lock subunits together. The adaptive immune system cannot generally employ this strategy since the individual antibody binding sites are not arranged with appropriate geometry to simultaneously engage multiple sites in a single target homo-oligomer. We describe a general strategy for the computational design of homo-oligomeric protein assemblies with binding functionality precisely matched to homo-oligomeric target sites5, 6, 7, 8. In the first step, a small protein ismore » designed that binds a single site on the target. In the second step, the designed protein is assembled into a homo-oligomer such that the designed binding sites are aligned with the target sites. We use this approach to design high-avidity trimeric proteins that bind influenza A hemagglutinin (HA) at its conserved receptor binding site. The designed trimers can both capture and detect HA in a paper-based diagnostic format, neutralizes influenza in cell culture, and completely protects mice when given as a single dose 24 h before or after challenge with influenza.« less

Structure-based design, synthesis and crystallization of 2-arylquinazolines as lipid pocket ligands of p38α MAPK

PubMed Central

Bührmann, Mike; Wiedemann, Bianca M.; Müller, Matthias P.; Hardick, Julia; Ecke, Maria

2017-01-01

In protein kinase research, identifying and addressing small molecule binding sites other than the highly conserved ATP-pocket are of intense interest because this line of investigation extends our understanding of kinase function beyond the catalytic phosphotransfer. Such alternative binding sites may be involved in altering the activation state through subtle conformational changes, control cellular enzyme localization, or in mediating and disrupting protein-protein interactions. Small organic molecules that target these less conserved regions might serve as tools for chemical biology research and to probe alternative strategies in targeting protein kinases in disease settings. Here, we present the structure-based design and synthesis of a focused library of 2-arylquinazoline derivatives to target the lipophilic C-terminal binding pocket in p38α MAPK, for which a clear biological function has yet to be identified. The interactions of the ligands with p38α MAPK was analyzed by SPR measurements and validated by protein X-ray crystallography. PMID:28892510

Super-secondary structure peptidomimetics: design and synthesis of an α-α hairpin analogue

PubMed Central

Nevola, Laura; Rodriguez, Johanna M.; Thompson, Sam; Hamilton, Andrew D.

2015-01-01

The α-α helix motif presents key recognition domains in protein-protein and protein-oligonucleotide binding, and is one of the most common super-secondary structures. Herein we describe the design, synthesis and structural characterization of an α-α hairpin analogue based on a tetra-coordinated Pd(II) bis-(iminoisoquinoline) complex as a template for the display of two α-helix mimics. This approach is exemplified by the attachment of two biphenyl peptidomimetics to reproduce the side-chains of the i and i+4 residues of two helices. PMID:26052191

Designing artificial enzymes from scratch: Experimental study and mesoscale simulation

NASA Astrophysics Data System (ADS)

Komarov, Pavel V.; Zaborina, Olga E.; Klimova, Tamara P.; Lozinsky, Vladimir I.; Khalatur, Pavel G.; Khokhlov, Alexey R.

2016-09-01

We present a new concept for designing biomimetic analogs of enzymatic proteins; these analogs are based on the synthetic protein-like copolymers. α-Chymotrypsin is used as a prototype of the artificial catalyst. Our experimental study shows that in the course of free radical copolymerization of hydrophobic and hydrophilic monomers the target globular nanostructures of a "core-shell" morphology appear in a selective solvent. Using a mesoscale computer simulation, we show that the protein-like globules can have a large number of catalytic centers located at the hydrophobic core/hydrophilic shell interface.

Influence of protein fold stability on immunogenicity and its implications for vaccine design

PubMed Central

Scheiblhofer, Sandra; Laimer, Josef; Machado, Yoan; Weiss, Richard; Thalhamer, Josef

2017-01-01

ABSTRACT Introduction: In modern vaccinology and immunotherapy, recombinant proteins more and more replace whole organisms to induce protective or curative immune responses. Structural stability of proteins is of crucial importance for efficient presentation of antigenic peptides on MHC, which plays a decisive role for triggering strong immune reactions. Areas covered: In this review, we discuss structural stability as a key factor for modulating the potency of recombinant vaccines and its importance for antigen proteolysis, presentation, and stimulation of B and T cells. Moreover, the impact of fold stability on downstream events determining the differentiation of T cells into effector cells is reviewed. We summarize studies investigating the impact of protein fold stability on the outcome of the immune response and provide an overview on computational methods to estimate the effects of point mutations on protein stability. Expert commentary: Based on this information, the rational design of up-to-date vaccines is discussed. A model for predicting immunogenicity of proteins based on their conformational stability at different pH values is proposed. PMID:28290225

Effects of protein or amino-acid supplementation on the physical growth of young children in low-income countries

PubMed Central

Arsenault, Joanne E; Brown, Kenneth H

2017-01-01

Abstract Child growth stunting is common in low-income countries, possibly due to insufficient protein intakes. Most previous studies have concluded that children’s protein intakes are adequate in relation to estimated requirements, but these studies did not consider issues of protein digestibility and effects of infection on dietary protein utilization. Using an alternative approach to assess the possible role of protein inadequacy in children’s growth restriction, the results of 18 intervention trials in which supplementary protein or amino acids were provided to children ages 6–35 months and growth outcomes were reviewed. Eight studies conducted in hospitalized children recovering from acute malnutrition found that the recommended protein intake levels for healthy children supported normal growth rates, but higher intakes were needed for accelerated rates of “catch-up” growth. Ten community-based studies did not demonstrate a consistent benefit of supplemental protein on children’s growth. However, weaknesses in the study designs limit the conclusions that can be drawn from these studies, and additional appropriately designed trials are needed to answer this question definitively. Recommendations for optimizing future study designs are provided herein. PMID:28938793

Prediction of allosteric sites on protein surfaces with an elastic-network-model-based thermodynamic method.

PubMed

Su, Ji Guo; Qi, Li Sheng; Li, Chun Hua; Zhu, Yan Ying; Du, Hui Jing; Hou, Yan Xue; Hao, Rui; Wang, Ji Hua

2014-08-01

Allostery is a rapid and efficient way in many biological processes to regulate protein functions, where binding of an effector at the allosteric site alters the activity and function at a distant active site. Allosteric regulation of protein biological functions provides a promising strategy for novel drug design. However, how to effectively identify the allosteric sites remains one of the major challenges for allosteric drug design. In the present work, a thermodynamic method based on the elastic network model was proposed to predict the allosteric sites on the protein surface. In our method, the thermodynamic coupling between the allosteric and active sites was considered, and then the allosteric sites were identified as those where the binding of an effector molecule induces a large change in the binding free energy of the protein with its ligand. Using the proposed method, two proteins, i.e., the 70 kD heat shock protein (Hsp70) and GluA2 alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptor, were studied and the allosteric sites on the protein surface were successfully identified. The predicted results are consistent with the available experimental data, which indicates that our method is a simple yet effective approach for the identification of allosteric sites on proteins.

Prediction of allosteric sites on protein surfaces with an elastic-network-model-based thermodynamic method

NASA Astrophysics Data System (ADS)

Su, Ji Guo; Qi, Li Sheng; Li, Chun Hua; Zhu, Yan Ying; Du, Hui Jing; Hou, Yan Xue; Hao, Rui; Wang, Ji Hua

2014-08-01

Allostery is a rapid and efficient way in many biological processes to regulate protein functions, where binding of an effector at the allosteric site alters the activity and function at a distant active site. Allosteric regulation of protein biological functions provides a promising strategy for novel drug design. However, how to effectively identify the allosteric sites remains one of the major challenges for allosteric drug design. In the present work, a thermodynamic method based on the elastic network model was proposed to predict the allosteric sites on the protein surface. In our method, the thermodynamic coupling between the allosteric and active sites was considered, and then the allosteric sites were identified as those where the binding of an effector molecule induces a large change in the binding free energy of the protein with its ligand. Using the proposed method, two proteins, i.e., the 70 kD heat shock protein (Hsp70) and GluA2 alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptor, were studied and the allosteric sites on the protein surface were successfully identified. The predicted results are consistent with the available experimental data, which indicates that our method is a simple yet effective approach for the identification of allosteric sites on proteins.

Fragment-based discovery of novel pentacyclic triterpenoid derivatives as cholesteryl ester transfer protein inhibitors.

PubMed

Chang, Yongzhi; Zhou, Shuxi; Li, Enqin; Zhao, Wenfeng; Ji, Yanpeng; Wen, Xiaoan; Sun, Hongbin; Yuan, Haoliang

2017-01-27

Cholesteryl Ester Transfer Protein (CETP) is an important therapeutic target for the treatment of atherosclerotic cardiovascular disease. Our molecular modeling study revealed that pentacyclic triterpenoid compounds could mimic the protein-ligand interactions of the endogenous ligand cholesteryl ester (CE) by occupying its binding site. Alignment of the docking conformations of oleanolic acid (OA), ursolic acid (UA) and the crystal conformations of known CETP inhibitor Torcetrapib in the active site proposed the applicability of fragment-based drug design (FBDD) approaches in this study. Accordingly, a series of pentacyclic triterpenoid derivatives have been designed and synthesized as novel CETP inhibitors. The most potent compound 12e (IC 50 :0.28 μM) validated our strategy for molecular design. Molecular dynamics simulations illustrated that the more stable hydrogen bond interaction of the UA derivative 12e with Ser191 and stronger hydrophobic interactions with Val198, Phe463 than those of OA derivative 12b mainly led to their significantly different CETP inhibitory activity. These novel potent CETP inhibitors based on ursane-type scaffold should deserve further investigation. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Using Symmetry to Design Self-Assembling Protein Cages and Nanomaterials on the Mid-Nanometer Scale

NASA Astrophysics Data System (ADS)

Yeates, Todd

Self-assembling molecular structures having diverse cellular functions are widespread in nature. Some of the largest and most sophisticated types are built from many copies of the same or similar protein molecules arranged following principles of symmetry. A long-standing engineering goal has been to design novel protein molecules to self-assemble into geometrically specific structures similar to the extraordinary structures that have evolved in Nature. Practical routes to this goal have been developed by using ideas in symmetry to articulate the minimum design requirements for achieving various types of symmetric architectures, including cages, extended two-dimensional layers, and three-dimensional crystalline materials. The key requirement is that two distinct self-associating interfaces, each conferring one element of rotational symmetry, have to be engineered into the protein molecule (or molecules), following particular geometric specifications. The main principle is that combining two separate symmetry elements into a single molecular entity produces a molecule that necessarily assembles into an architecture dictated by a symmetry group that is the product of the two simpler contributing symmetries. Recent experiments have demonstrated success using a variety of symmetry-based strategies. Strategic variations are emerging that differ from each other with respect to biophysical features such as flexibility vs rigidity in the assembled structures, and with respect to design aspects such as whether the protein interfaces are inherited from natural oligomeric proteins or are designed de novo by advanced computational methods. The success of these strategies has been proven by determining crystal structures of several giant, self-assembling protein cages and clusters (10-25 nm in diameter), created by design. The ability to create sophisticated supramolecular structures from designed protein subunits opens the way to broad applications in synthetic biology and nanotechnology.

Design and functional characterization of a novel, arrestin-biased designer G protein-coupled receptor.

PubMed

Nakajima, Ken-ichiro; Wess, Jürgen

2012-10-01

Mutational modification of distinct muscarinic receptor subtypes has yielded novel designer G protein-coupled receptors (GPCRs) that are unable to bind acetylcholine (ACh), the endogenous muscarinic receptor ligand, but can be efficiently activated by clozapine-N-oxide (CNO), an otherwise pharmacologically inert compound. These CNO-sensitive designer GPCRs [alternative name: designer receptors exclusively activated by designer drug (DREADDs)] have emerged as powerful new tools to dissect the in vivo roles of distinct G protein signaling pathways in specific cell types or tissues. As is the case with other GPCRs, CNO-activated DREADDs not only couple to heterotrimeric G proteins but can also recruit proteins of the arrestin family (arrestin-2 and -3). Accumulating evidence suggests that arrestins can act as scaffolding proteins to promote signaling through G protein-independent signaling pathways. To explore the physiological relevance of these arrestin-dependent signaling pathways, the availability of an arrestin-biased DREADD would be highly desirable. In this study, we describe the development of an M₃ muscarinic receptor-based DREADD [Rq(R165L)] that is no longer able to couple to G proteins but can recruit arrestins and promote extracellular signal-regulated kinase-1/2 phosphorylation in an arrestin- and CNO-dependent fashion. Moreover, CNO treatment of mouse insulinoma (MIN6) cells expressing the Rq(R165L) construct resulted in a robust, arrestin-dependent stimulation of insulin release, directly implicating arrestin signaling in the regulation of insulin secretion. This newly developed arrestin-biased DREADD represents an excellent novel tool to explore the physiological relevance of arrestin signaling pathways in distinct tissues and cell types.

Protein engineering and the use of molecular modeling and simulation: the case of heterodimeric Fc engineering.

PubMed

Spreter Von Kreudenstein, Thomas; Lario, Paula I; Dixit, Surjit B

2014-01-01

Computational and structure guided methods can make significant contributions to the development of solutions for difficult protein engineering problems, including the optimization of next generation of engineered antibodies. In this paper, we describe a contemporary industrial antibody engineering program, based on hypothesis-driven in silico protein optimization method. The foundational concepts and methods of computational protein engineering are discussed, and an example of a computational modeling and structure-guided protein engineering workflow is provided for the design of best-in-class heterodimeric Fc with high purity and favorable biophysical properties. We present the engineering rationale as well as structural and functional characterization data on these engineered designs. Copyright © 2013 Elsevier Inc. All rights reserved.

Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins

PubMed Central

Ma, Yue; Tuskan, Gerald A.

2018-01-01

The existence of complete genome sequences makes it important to develop different approaches for classification of large-scale data sets and to make extraction of biological insights easier. Here, we propose an approach for classification of complete proteomes/protein sets based on protein distributions on some basic attributes. We demonstrate the usefulness of this approach by determining protein distributions in terms of two attributes: protein lengths and protein intrinsic disorder contents (ID). The protein distributions based on L and ID are surveyed for representative proteome organisms and protein sets from the three domains of life. The two-dimensional maps (designated as fingerprints here) from the protein distribution densities in the LD space defined by ln(L) and ID are then constructed. The fingerprints for different organisms and protein sets are found to be distinct with each other, and they can therefore be used for comparative studies. As a test case, phylogenetic trees have been constructed based on the protein distribution densities in the fingerprints of proteomes of organisms without performing any protein sequence comparison and alignments. The phylogenetic trees generated are biologically meaningful, demonstrating that the protein distributions in the LD space may serve as unique phylogenetic signals of the organisms at the proteome level. PMID:29686995

BWM*: A Novel, Provable, Ensemble-based Dynamic Programming Algorithm for Sparse Approximations of Computational Protein Design.

PubMed

Jou, Jonathan D; Jain, Swati; Georgiev, Ivelin S; Donald, Bruce R

2016-06-01

Sparse energy functions that ignore long range interactions between residue pairs are frequently used by protein design algorithms to reduce computational cost. Current dynamic programming algorithms that fully exploit the optimal substructure produced by these energy functions only compute the GMEC. This disproportionately favors the sequence of a single, static conformation and overlooks better binding sequences with multiple low-energy conformations. Provable, ensemble-based algorithms such as A* avoid this problem, but A* cannot guarantee better performance than exhaustive enumeration. We propose a novel, provable, dynamic programming algorithm called Branch-Width Minimization* (BWM*) to enumerate a gap-free ensemble of conformations in order of increasing energy. Given a branch-decomposition of branch-width w for an n-residue protein design with at most q discrete side-chain conformations per residue, BWM* returns the sparse GMEC in O([Formula: see text]) time and enumerates each additional conformation in merely O([Formula: see text]) time. We define a new measure, Total Effective Search Space (TESS), which can be computed efficiently a priori before BWM* or A* is run. We ran BWM* on 67 protein design problems and found that TESS discriminated between BWM*-efficient and A*-efficient cases with 100% accuracy. As predicted by TESS and validated experimentally, BWM* outperforms A* in 73% of the cases and computes the full ensemble or a close approximation faster than A*, enumerating each additional conformation in milliseconds. Unlike A*, the performance of BWM* can be predicted in polynomial time before running the algorithm, which gives protein designers the power to choose the most efficient algorithm for their particular design problem.

Immobilizing affinity proteins to nitrocellulose: a toolbox for paper-based assay developers.

PubMed

Holstein, Carly A; Chevalier, Aaron; Bennett, Steven; Anderson, Caitlin E; Keniston, Karen; Olsen, Cathryn; Li, Bing; Bales, Brian; Moore, David R; Fu, Elain; Baker, David; Yager, Paul

2016-02-01

To enable enhanced paper-based diagnostics with improved detection capabilities, new methods are needed to immobilize affinity reagents to porous substrates, especially for capture molecules other than IgG. To this end, we have developed and characterized three novel methods for immobilizing protein-based affinity reagents to nitrocellulose membranes. We have demonstrated these methods using recombinant affinity proteins for the influenza surface protein hemagglutinin, leveraging the customizability of these recombinant "flu binders" for the design of features for immobilization. The three approaches shown are: (1) covalent attachment of thiolated affinity protein to an epoxide-functionalized nitrocellulose membrane, (2) attachment of biotinylated affinity protein through a nitrocellulose-binding streptavidin anchor protein, and (3) fusion of affinity protein to a novel nitrocellulose-binding anchor protein for direct coupling and immobilization. We also characterized the use of direct adsorption for the flu binders, as a point of comparison and motivation for these novel methods. Finally, we demonstrated that these novel methods can provide improved performance to an influenza hemagglutinin assay, compared to a traditional antibody-based capture system. Taken together, this work advances the toolkit available for the development of next-generation paper-based diagnostics.

High-Throughput Screening by Nuclear Magnetic Resonance (HTS by NMR) for the Identification of PPIs Antagonists.

PubMed

Wu, Bainan; Barile, Elisa; De, Surya K; Wei, Jun; Purves, Angela; Pellecchia, Maurizio

2015-01-01

In recent years the ever so complex field of drug discovery has embraced novel design strategies based on biophysical fragment screening (fragment-based drug design; FBDD) using nuclear magnetic resonance spectroscopy (NMR) and/or structure-guided approaches, most often using X-ray crystallography and computer modeling. Experience from recent years unveiled that these methods are more effective and less prone to artifacts compared to biochemical high-throughput screening (HTS) of large collection of compounds in designing protein inhibitors. Hence these strategies are increasingly becoming the most utilized in the modern pharmaceutical industry. Nonetheless, there is still an impending need to develop innovative and effective strategies to tackle other more challenging targets such as those involving protein-protein interactions (PPIs). While HTS strategies notoriously fail to identify viable hits against such targets, few successful examples of PPIs antagonists derived by FBDD strategies exist. Recently, we reported on a new strategy that combines some of the basic principles of fragment-based screening with combinatorial chemistry and NMR-based screening. The approach, termed HTS by NMR, combines the advantages of combinatorial chemistry and NMR-based screening to rapidly and unambiguously identify bona fide inhibitors of PPIs. This review will reiterate the critical aspects of the approach with examples of possible applications.

High-throughput screening by Nuclear Magnetic Resonance (HTS by NMR) for the identification of PPIs antagonists

PubMed Central

Wu, Bainan; Barile, Elisa; De, Surya K.; Wei, Jun; Purves, Angela; Pellecchia, Maurizio

2015-01-01

In recent years the ever so complex field of drug discovery has embraced novel design strategies based on biophysical fragment screening (fragment-based drug design; FBDD) using nuclear magnetic resonance spectroscopy (NMR) and/or structure-guided approaches, most often using X-ray crystallography and computer modeling. Experience from recent years unveiled that these methods are more effective and less prone to artifacts compared to biochemical high-throughput screening (HTS) of large collection of compounds in designing protein inhibitors. Hence these strategies are increasingly becoming the most utilized in the modern pharmaceutical industry. Nonetheless, there is still an impending need to develop innovative and effective strategies to tackle other more challenging targets such as those involving protein-protein interactions (PPIs). While HTS strategies notoriously fail to identify viable hits against such targets, few successful examples of PPIs antagonists derived by FBDD strategies exist. Recently, we reported on a new strategy that combines some of the basic principles of fragment-based screening with combinatorial chemistry and NMR-based screening. The approach, termed HTS by NMR, combines the advantages of combinatorial chemistry and NMR-based screening to rapidly and unambiguously identify bona fide inhibitors of PPIs. This review will reiterate the critical aspects of the approach with examples of possible applications. PMID:25986689

Computer-aided rational design of novel EBF analogues with an aromatic ring.

PubMed

Wang, Shanshan; Sun, Yufeng; Du, Shaoqing; Qin, Yaoguo; Duan, Hongxia; Yang, Xinling

2016-06-01

Odorant binding proteins (OBPs) are important in insect olfactory recognition. These proteins bind specifically to insect semiochemicals and induce their seeking, mating, and alarm behaviors. Molecular docking and molecular dynamics simulations were performed to provide computational insight into the interaction mode between AgamOBP7 and novel (E)-β-farnesene (EBF) analogues with an aromatic ring. The ligand-binding cavity in OBP7 was found to be mostly hydrophobic due to the presence of several nonpolar residues. The interactions between the EBF analogues and the hydrophobic residues in the binding cavity increased in strength as the distance between them decreased. The EBF analogues with an N-methyl formamide or ester linkage had higher docking scores than those with an amide linkage. Moreover, delocalized π-π and electrostatic interactions were found to contribute significantly to the binding between the ligand benzene ring and nearby protein residues. To design new compounds with higher activity, four EBF analogues D1-D4 with a benzene ring were synthesized and evaluated based on their docking scores and binding affinities. D2, which had an N-methyl formamide group linkage, exhibited stronger binding than D1, which had an amide linkage. D4 exhibited particularly strong binding due to multiple hydrophobic interactions with the protein. This study provides crucial foundations for designing novel EBF analogues based on the OBP structure. Graphical abstract The design strategy of new EBF analogues based on the OBP7 structure.

Detection of Protein Interactions in T3S Systems Using Yeast Two-Hybrid Analysis.

PubMed

Nilles, Matthew L

2017-01-01

Two-hybrid systems, sometimes termed interaction traps, are genetic systems designed to find and analyze interactions between proteins. The most common systems are yeast based (commonly Saccharomyces cerevisae) and rely on the functional reconstitution of the GAL4 transcriptional activator. Reporter genes, such as the lacZ gene of Escherichia coli (encodes β-galactosidase), are placed under GAL4-dependent transcriptional control to provide quick and reliable detection of protein interactions. In this method the use of a yeast-based two-hybrid system is described to study protein interactions between components of type III secretion systems.

Design and Use of Chimeric Proteins Containing a Collagen-Binding Domain for Wound Healing and Bone Regeneration.

PubMed

Addi, Cyril; Murschel, Frederic; De Crescenzo, Gregory

2017-04-01

Collagen-based biomaterials are widely used in the field of tissue engineering; they can be loaded with biomolecules such as growth factors (GFs) to modulate the biological response of the host and thus improve its potential for regeneration. Recombinant chimeric GFs fused to a collagen-binding domain (CBD) have been reported to improve their bioavailability and the host response, especially when combined with an appropriate collagen-based biomaterial. This review first provides an extensive description of the various CBDs that have been fused to proteins, with a focus on the need for accurate characterization of their interaction with collagen. The second part of the review highlights the benefits of various CBD/GF fusion proteins that have been designed for wound healing and bone regeneration.

Mixing and Matching Detergents for Membrane Protein NMR Structure Determination

DOE Office of Scientific and Technical Information (OSTI.GOV)

Columbus, Linda; Lipfert, Jan; Jambunathan, Kalyani

2009-10-21

One major obstacle to membrane protein structure determination is the selection of a detergent micelle that mimics the native lipid bilayer. Currently, detergents are selected by exhaustive screening because the effects of protein-detergent interactions on protein structure are poorly understood. In this study, the structure and dynamics of an integral membrane protein in different detergents is investigated by nuclear magnetic resonance (NMR) and electron paramagnetic resonance (EPR) spectroscopy and small-angle X-ray scattering (SAXS). The results suggest that matching of the micelle dimensions to the protein's hydrophobic surface avoids exchange processes that reduce the completeness of the NMR observations. Based onmore » these dimensions, several mixed micelles were designed that improved the completeness of NMR observations. These findings provide a basis for the rational design of mixed micelles that may advance membrane protein structure determination by NMR.« less

Recombinant and epitope-based vaccines on the road to the market and implications for vaccine design and production.

PubMed

Oyarzún, Patricio; Kobe, Bostjan

2016-03-03

Novel vaccination approaches based on rational design of B- and T-cell epitopes - epitope-based vaccines - are making progress in the clinical trial pipeline. The epitope-focused recombinant protein-based malaria vaccine (termed RTS,S) is a next-generation approach that successfully reached phase-III trials, and will potentially become the first commercial vaccine against a human parasitic disease. Progress made on methods such as recombinant DNA technology, advanced cell-culture techniques, immunoinformatics and rational design of immunogens are driving the development of these novel concepts. Synthetic recombinant proteins comprising both B- and T-cell epitopes can be efficiently produced through modern biotechnology and bioprocessing methods, and can enable the induction of large repertoires of immune specificities. In particular, the inclusion of appropriate CD4+ T-cell epitopes is increasingly considered a key vaccine component to elicit robust immune responses, as suggested by results coming from HIV-1 clinical trials. In silico strategies for vaccine design are under active development to address genetic variation in pathogens and several broadly protective "universal" influenza and HIV-1 vaccines are currently at different stages of clinical trials. Other methods focus on improving population coverage in target populations by rationally considering specificity and prevalence of the HLA proteins, though a proof-of-concept in humans has not been demonstrated yet. Overall, we expect immunoinformatics and bioprocessing methods to become a central part of the next-generation epitope-based vaccine development and production process.

Molecular chaperones: functional mechanisms and nanotechnological applications

NASA Astrophysics Data System (ADS)

Rosario Fernández-Fernández, M.; Sot, Begoña; María Valpuesta, José

2016-08-01

Molecular chaperones are a group of proteins that assist in protein homeostasis. They not only prevent protein misfolding and aggregation, but also target misfolded proteins for degradation. Despite differences in structure, all types of chaperones share a common general feature, a surface that recognizes and interacts with the misfolded protein. This and other, more specialized properties can be adapted for various nanotechnological purposes, by modification of the original biomolecules or by de novo design based on artificial structures.

An ALuc-Based Molecular Tension Probe for Sensing Intramolecular Protein-Protein Interactions.

PubMed

Kim, Sung-Bae; Nishihara, Ryo; Suzuki, Koji

2016-01-01

Optical imaging of protein-protein interactions (PPIs) facilitates comprehensive elucidation of intracellular molecular events. The present protocol demonstrates an optical measure for visualizing molecular tension triggered by any PPI in mammalian cells. A unique design of single-chain probes was fabricated, in which a full-length artificial luciferase (ALuc(®)) was sandwiched between two model proteins of interest, e.g., FKBP and FRB. A molecular tension probe comprising ALuc23 greatly enhances the bioluminescence in response to varying concentrations of rapamycin, and named "tension probe (TP)." The basic probe design can be further modified towards eliminating the C-terminal end of ALuc and was found to improve signal-to-background ratios, named "combinational probe." TPs may become an important addition to the tool box of bioassays in the determination of protein dynamics of interest in mammalian cells.

Design of Aminobenzothiazole Inhibitors of Rho Kinases 1 and 2 by Using Protein Kinase A as a Structure Surrogate.

PubMed

Judge, Russell A; Vasudevan, Anil; Scott, Victoria E; Simler, Gricelda H; Pratt, Steve D; Namovic, Marian T; Putman, C Brent; Aguirre, Ana; Stoll, Vincent S; Mamo, Mulugeta; Swann, Steven I; Cassar, Steven C; Faltynek, Connie R; Kage, Karen L; Boyce-Rustay, Janel M; Hobson, Adrian D

2018-03-16

We describe the design, synthesis, and structure-activity relationships (SARs) of a series of 2-aminobenzothiazole inhibitors of Rho kinases (ROCKs) 1 and 2, which were optimized to low nanomolar potencies by use of protein kinase A (PKA) as a structure surrogate to guide compound design. A subset of these molecules also showed robust activity in a cell-based myosin phosphatase assay and in a mechanical hyperalgesia in vivo pain model. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Coarse-grained sequences for protein folding and design.

PubMed

Brown, Scott; Fawzi, Nicolas J; Head-Gordon, Teresa

2003-09-16

We present the results of sequence design on our off-lattice minimalist model in which no specification of native-state tertiary contacts is needed. We start with a sequence that adopts a target topology and build on it through sequence mutation to produce new sequences that comprise distinct members within a target fold class. In this work, we use the alpha/beta ubiquitin fold class and design two new sequences that, when characterized through folding simulations, reproduce the differences in folding mechanism seen experimentally for proteins L and G. The primary implication of this work is that patterning of hydrophobic and hydrophilic residues is the physical origin for the success of relative contact-order descriptions of folding, and that these physics-based potentials provide a predictive connection between free energy landscapes and amino acid sequence (the original protein folding problem). We present results of the sequence mapping from a 20- to the three-letter code for determining a sequence that folds into the WW domain topology to illustrate future extensions to protein design.

Coarse-grained sequences for protein folding and design

PubMed Central

Brown, Scott; Fawzi, Nicolas J.; Head-Gordon, Teresa

2003-01-01

We present the results of sequence design on our off-lattice minimalist model in which no specification of native-state tertiary contacts is needed. We start with a sequence that adopts a target topology and build on it through sequence mutation to produce new sequences that comprise distinct members within a target fold class. In this work, we use the α/β ubiquitin fold class and design two new sequences that, when characterized through folding simulations, reproduce the differences in folding mechanism seen experimentally for proteins L and G. The primary implication of this work is that patterning of hydrophobic and hydrophilic residues is the physical origin for the success of relative contact-order descriptions of folding, and that these physics-based potentials provide a predictive connection between free energy landscapes and amino acid sequence (the original protein folding problem). We present results of the sequence mapping from a 20- to the three-letter code for determining a sequence that folds into the WW domain topology to illustrate future extensions to protein design. PMID:12963815

Activity, specificity, and probe design for the smallpox virus protease K7L.

PubMed

Aleshin, Alexander E; Drag, Marcin; Gombosuren, Naran; Wei, Ge; Mikolajczyk, Jowita; Satterthwait, Arnold C; Strongin, Alex Y; Liddington, Robert C; Salvesen, Guy S

2012-11-16

The K7L gene product of the smallpox virus is a protease implicated in the maturation of viral proteins. K7L belongs to protease Clan CE, which includes distantly related cysteine proteases from eukaryotes, pathogenic bacteria, and viruses. Here, we describe its recombinant high level expression, biochemical mechanism, substrate preference, and regulation. Earlier studies inferred that the orthologous I7L vaccinia protease cleaves at an AG-X motif in six viral proteins. Our data for K7L suggest that the AG-X motif is necessary but not sufficient for optimal cleavage activity. Thus, K7L requires peptides extended into the P7 and P8 positions for efficient substrate cleavage. Catalytic activity of K7L is substantially enhanced by homodimerization, by the substrate protein P25K as well as by glycerol. RNA and DNA also enhance cleavage of the P25K protein but not of synthetic peptides, suggesting that nucleic acids augment the interaction of K7L with its protein substrate. Library-based peptide preference analyses enabled us to design an activity-based probe that covalently and selectively labels K7L in lysates of transfected and infected cells. Our study thus provides proof-of-concept for the design of inhibitors and probes that may contribute both to a better understanding of the role of K7L in the virus life cycle and the design of novel anti-virals.

The multi-copy simultaneous search methodology: a fundamental tool for structure-based drug design.

PubMed

Schubert, Christian R; Stultz, Collin M

2009-08-01

Fragment-based ligand design approaches, such as the multi-copy simultaneous search (MCSS) methodology, have proven to be useful tools in the search for novel therapeutic compounds that bind pre-specified targets of known structure. MCSS offers a variety of advantages over more traditional high-throughput screening methods, and has been applied successfully to challenging targets. The methodology is quite general and can be used to construct functionality maps for proteins, DNA, and RNA. In this review, we describe the main aspects of the MCSS method and outline the general use of the methodology as a fundamental tool to guide the design of de novo lead compounds. We focus our discussion on the evaluation of MCSS results and the incorporation of protein flexibility into the methodology. In addition, we demonstrate on several specific examples how the information arising from the MCSS functionality maps has been successfully used to predict ligand binding to protein targets and RNA.

Using the [beta][subscript 2]-Adrenoceptor for Structure-Based Drug Design

ERIC Educational Resources Information Center

Manallack, David T.; Chalmers, David K.; Yuriev, Elizabeth

2010-01-01

The topics of molecular modeling and drug design are studied in a medicinal chemistry course. The recently reported structures of several G protein-coupled receptors (GPCR) with bound ligands have been used to develop a simple computer-based experiment employing molecular-modeling software. Knowledge of the specific interactions between a ligand…

Robust, synergistic regulation of human gene expression using TALE activators.

PubMed

Maeder, Morgan L; Linder, Samantha J; Reyon, Deepak; Angstman, James F; Fu, Yanfang; Sander, Jeffry D; Joung, J Keith

2013-03-01

Artificial activators designed using transcription activator-like effector (TALE) technology have broad utility, but previous studies suggest that these monomeric proteins often exhibit low activities. Here we demonstrate that TALE activators can robustly function individually or in synergistic combinations to increase expression of endogenous human genes over wide dynamic ranges. These findings will encourage applications of TALE activators for research and therapy, and guide design of monomeric TALE-based fusion proteins.

Computational enzyme design: transitioning from catalytic proteins to enzymes.

PubMed

Mak, Wai Shun; Siegel, Justin B

2014-08-01

The widespread interest in enzymes stem from their ability to catalyze chemical reactions under mild and ecologically friendly conditions with unparalleled catalytic proficiencies. While thousands of naturally occurring enzymes have been identified and characterized, there are still numerous important applications for which there are no biological catalysts capable of performing the desired chemical transformation. In order to engineer enzymes for which there is no natural starting point, efforts using a combination of quantum chemistry and force-field based protein molecular modeling have led to the design of novel proteins capable of catalyzing chemical reactions not catalyzed by naturally occurring enzymes. Here we discuss the current status and potential avenues to pursue as the field of computational enzyme design moves forward. Published by Elsevier Ltd.

Design and Functional Characterization of a Novel, Arrestin-Biased Designer G Protein-Coupled Receptor

PubMed Central

Nakajima, Ken-ichiro

2012-01-01

Mutational modification of distinct muscarinic receptor subtypes has yielded novel designer G protein-coupled receptors (GPCRs) that are unable to bind acetylcholine (ACh), the endogenous muscarinic receptor ligand, but can be efficiently activated by clozapine-N-oxide (CNO), an otherwise pharmacologically inert compound. These CNO-sensitive designer GPCRs [alternative name: designer receptors exclusively activated by designer drug (DREADDs)] have emerged as powerful new tools to dissect the in vivo roles of distinct G protein signaling pathways in specific cell types or tissues. As is the case with other GPCRs, CNO-activated DREADDs not only couple to heterotrimeric G proteins but can also recruit proteins of the arrestin family (arrestin-2 and -3). Accumulating evidence suggests that arrestins can act as scaffolding proteins to promote signaling through G protein-independent signaling pathways. To explore the physiological relevance of these arrestin-dependent signaling pathways, the availability of an arrestin-biased DREADD would be highly desirable. In this study, we describe the development of an M3 muscarinic receptor-based DREADD [Rq(R165L)] that is no longer able to couple to G proteins but can recruit arrestins and promote extracellular signal-regulated kinase-1/2 phosphorylation in an arrestin- and CNO-dependent fashion. Moreover, CNO treatment of mouse insulinoma (MIN6) cells expressing the Rq(R165L) construct resulted in a robust, arrestin-dependent stimulation of insulin release, directly implicating arrestin signaling in the regulation of insulin secretion. This newly developed arrestin-biased DREADD represents an excellent novel tool to explore the physiological relevance of arrestin signaling pathways in distinct tissues and cell types. PMID:22821234

Oral delivery of peptides and proteins using lipid-based drug delivery systems.

PubMed

Li, Ping; Nielsen, Hanne Mørck; Müllertz, Anette

2012-10-01

In order to successfully develop lipid-based drug delivery systems (DDS) for oral administration of peptides and proteins, it is important to gain an understanding of the colloid structures formed by these DDS, the mode of peptide and protein incorporation as well as the mechanism by which intestinal absorption of peptides and proteins is promoted. The present paper reviews the literature on lipid-based DDS, employed for oral delivery of peptides and proteins and highlights the mechanisms by which the different lipid-based carriers are expected to overcome the two most important barriers (extensive enzymatic degradation and poor transmucosal permeability). This paper also gives a clear-cut idea about advantages and drawbacks of using different lipidic colloidal carriers ((micro)emulsions, solid lipid core particles and liposomes) for oral delivery of peptides and proteins. Lipid-based DDS are safe and suitable for oral delivery of peptides and proteins. Significant progress has been made in this area with several technologies on clinical trials. However, a better understanding of the mechanism of action in vivo is needed in order to improve the design and development of lipid-based DDS with the desired bioavailability and therapeutic profile.

HDAPD: a web tool for searching the disease-associated protein structures

PubMed Central

2010-01-01

Background The protein structures of the disease-associated proteins are important for proceeding with the structure-based drug design to against a particular disease. Up until now, proteins structures are usually searched through a PDB id or some sequence information. However, in the HDAPD database presented here the protein structure of a disease-associated protein can be directly searched through the associated disease name keyed in. Description The search in HDAPD can be easily initiated by keying some key words of a disease, protein name, protein type, or PDB id. The protein sequence can be presented in FASTA format and directly copied for a BLAST search. HDAPD is also interfaced with Jmol so that users can observe and operate a protein structure with Jmol. The gene ontological data such as cellular components, molecular functions, and biological processes are provided once a hyperlink to Gene Ontology (GO) is clicked. Further, HDAPD provides a link to the KEGG map such that where the protein is placed and its relationship with other proteins in a metabolic pathway can be found from the map. The latest literatures namely titles, journals, authors, and abstracts searched from PubMed for the protein are also presented as a length controllable list. Conclusions Since the HDAPD data content can be routinely updated through a PHP-MySQL web page built, the new database presented is useful for searching the structures for some disease-associated proteins that may play important roles in the disease developing process for performing the structure-based drug design to against the diseases. PMID:20158919

Exploring representations of protein structure for automated remote homology detection and mapping of protein structure space

PubMed Central

2014-01-01

Background Due to rapid sequencing of genomes, there are now millions of deposited protein sequences with no known function. Fast sequence-based comparisons allow detecting close homologs for a protein of interest to transfer functional information from the homologs to the given protein. Sequence-based comparison cannot detect remote homologs, in which evolution has adjusted the sequence while largely preserving structure. Structure-based comparisons can detect remote homologs but most methods for doing so are too expensive to apply at a large scale over structural databases of proteins. Recently, fragment-based structural representations have been proposed that allow fast detection of remote homologs with reasonable accuracy. These representations have also been used to obtain linearly-reducible maps of protein structure space. It has been shown, as additionally supported from analysis in this paper that such maps preserve functional co-localization of the protein structure space. Methods Inspired by a recent application of the Latent Dirichlet Allocation (LDA) model for conducting structural comparisons of proteins, we propose higher-order LDA-obtained topic-based representations of protein structures to provide an alternative route for remote homology detection and organization of the protein structure space in few dimensions. Various techniques based on natural language processing are proposed and employed to aid the analysis of topics in the protein structure domain. Results We show that a topic-based representation is just as effective as a fragment-based one at automated detection of remote homologs and organization of protein structure space. We conduct a detailed analysis of the information content in the topic-based representation, showing that topics have semantic meaning. The fragment-based and topic-based representations are also shown to allow prediction of superfamily membership. Conclusions This work opens exciting venues in designing novel representations to extract information about protein structures, as well as organizing and mining protein structure space with mature text mining tools. PMID:25080993

Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins

DOE PAGES

Guo, Hao-Bo; Ma, Yue; Tuskan, Gerald A.; ...

2018-01-01

The existence of complete genome sequences makes it important to develop different approaches for classification of large-scale data sets and to make extraction of biological insights easier. Here, we propose an approach for classification of complete proteomes/protein sets based on protein distributions on some basic attributes. We demonstrate the usefulness of this approach by determining protein distributions in terms of two attributes: protein lengths and protein intrinsic disorder contents (ID). The protein distributions based on L and ID are surveyed for representative proteome organisms and protein sets from the three domains of life. The two-dimensional maps (designated as fingerprints here)more » from the protein distribution densities in the LD space defined by ln( L ) and ID are then constructed. The fingerprints for different organisms and protein sets are found to be distinct with each other, and they can therefore be used for comparative studies. As a test case, phylogenetic trees have been constructed based on the protein distribution densities in the fingerprints of proteomes of organisms without performing any protein sequence comparison and alignments. The phylogenetic trees generated are biologically meaningful, demonstrating that the protein distributions in the LD space may serve as unique phylogenetic signals of the organisms at the proteome level.« less

Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guo, Hao-Bo; Ma, Yue; Tuskan, Gerald A.

The existence of complete genome sequences makes it important to develop different approaches for classification of large-scale data sets and to make extraction of biological insights easier. Here, we propose an approach for classification of complete proteomes/protein sets based on protein distributions on some basic attributes. We demonstrate the usefulness of this approach by determining protein distributions in terms of two attributes: protein lengths and protein intrinsic disorder contents (ID). The protein distributions based on L and ID are surveyed for representative proteome organisms and protein sets from the three domains of life. The two-dimensional maps (designated as fingerprints here)more » from the protein distribution densities in the LD space defined by ln( L ) and ID are then constructed. The fingerprints for different organisms and protein sets are found to be distinct with each other, and they can therefore be used for comparative studies. As a test case, phylogenetic trees have been constructed based on the protein distribution densities in the fingerprints of proteomes of organisms without performing any protein sequence comparison and alignments. The phylogenetic trees generated are biologically meaningful, demonstrating that the protein distributions in the LD space may serve as unique phylogenetic signals of the organisms at the proteome level.« less

Designing pH induced fold switch in proteins

NASA Astrophysics Data System (ADS)

Baruah, Anupaul; Biswas, Parbati

2015-05-01

This work investigates the computational design of a pH induced protein fold switch based on a self-consistent mean-field approach by identifying the ensemble averaged characteristics of sequences that encode a fold switch. The primary challenge to balance the alternative sets of interactions present in both target structures is overcome by simultaneously optimizing two foldability criteria corresponding to two target structures. The change in pH is modeled by altering the residual charge on the amino acids. The energy landscape of the fold switch protein is found to be double funneled. The fold switch sequences stabilize the interactions of the sites with similar relative surface accessibility in both target structures. Fold switch sequences have low sequence complexity and hence lower sequence entropy. The pH induced fold switch is mediated by attractive electrostatic interactions rather than hydrophobic-hydrophobic contacts. This study may provide valuable insights to the design of fold switch proteins.

In Situ Cyclization of Native Proteins: Structure-Based Design of a Bicyclic Enzyme.

PubMed

Pelay-Gimeno, Marta; Bange, Tanja; Hennig, Sven; Grossmann, Tom N

2018-05-30

Increased tolerance of enzymes towards thermal and chemical stress is required for many applications and can be achieved by macrocyclization of the enzyme resulting in the stabilizing of its tertiary structure. So far, macrocyclization approaches utilize a very limited structural diversity which complicates the design process. Here, we report an approach that enables cyclization via the installation of modular crosslinks into native proteins composed entirely of proteinogenic amino acids. Our stabilization procedure involves the introduction of three surface exposed cysteines which are reacted with a triselectrophile resulting in the in situ cylization of the protein (INCYPRO). A bicyclic version of Sortase A was designed exhibiting increased tolerance towards thermal as well as chemical denaturation, and proved efficient in protein labeling under denaturing conditions. In addition, we applied INCYPRO to the KIX domain resulting in up to 24 °C increased thermal stability. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A global optimization algorithm for protein surface alignment

PubMed Central

2010-01-01

Background A relevant problem in drug design is the comparison and recognition of protein binding sites. Binding sites recognition is generally based on geometry often combined with physico-chemical properties of the site since the conformation, size and chemical composition of the protein surface are all relevant for the interaction with a specific ligand. Several matching strategies have been designed for the recognition of protein-ligand binding sites and of protein-protein interfaces but the problem cannot be considered solved. Results In this paper we propose a new method for local structural alignment of protein surfaces based on continuous global optimization techniques. Given the three-dimensional structures of two proteins, the method finds the isometric transformation (rotation plus translation) that best superimposes active regions of two structures. We draw our inspiration from the well-known Iterative Closest Point (ICP) method for three-dimensional (3D) shapes registration. Our main contribution is in the adoption of a controlled random search as a more efficient global optimization approach along with a new dissimilarity measure. The reported computational experience and comparison show viability of the proposed approach. Conclusions Our method performs well to detect similarity in binding sites when this in fact exists. In the future we plan to do a more comprehensive evaluation of the method by considering large datasets of non-redundant proteins and applying a clustering technique to the results of all comparisons to classify binding sites. PMID:20920230

Integration of molecular dynamics simulation and hotspot residues grafting for de novo scFv design against Salmonella Typhi TolC protein.

PubMed

Leong, Siew Wen; Lim, Theam Soon; Ismail, Asma; Choong, Yee Siew

2018-05-01

With the development of de novo binders for protein targets from non-related scaffolds, many possibilities for therapeutics and diagnostics have been created. In this study, we described the use of de novo design approach to create single-chain fragment variable (scFv) for Salmonella enterica subspecies enterica serovar Typhi TolC protein. Typhoid fever is a global health concern in developing and underdeveloped countries. Rapid typhoid diagnostics will improve disease management and therapy. In this work, molecular dynamics simulation was first performed on a homology model of TolC protein in POPE membrane bilayer to obtain the central structure that was subsequently used as the target for scFv design. Potential hotspot residues capable of anchoring the binders to the target were identified by docking "disembodied" amino acid residues against TolC surface. Next, scFv scaffolds were selected from Protein Data Bank to harbor the computed hotspot residues. The hotspot residues were then incorporated into the scFv scaffold complementarity determining regions. The designs recapitulated binding energy, shape complementarity, and interface surface area of natural protein-antibody interfaces. This approach has yielded 5 designs with high binding affinity against TolC that may be beneficial for the future development of antigen-based detection agents for typhoid diagnostics. Copyright © 2017 John Wiley & Sons, Ltd.

Teaching Foundational Topics and Scientific Skills in Biochemistry within the Conceptual Framework of HIV Protease

ERIC Educational Resources Information Center

Johnson, R. Jeremy

2014-01-01

HIV protease has served as a model protein for understanding protein structure, enzyme kinetics, structure-based drug design, and protein evolution. Inhibitors of HIV protease are also an essential part of effective HIV/AIDS treatment and have provided great societal benefits. The broad applications for HIV protease and its inhibitors make it a…

A Novel Active-Learning Protein Purification Exercise for Large-Enrollment Introductory Biochemistry Courses Using the CHROM Web Applet

ERIC Educational Resources Information Center

Barrette-Ng, Isabelle H.; Usher, Ken C.

2013-01-01

The CHROM Web applet has been used to create a new active-learning exercise in which students design a purification scheme for a recombinant protein using ion-exchange chromatography (IEC). To successfully complete the exercise, students are challenged to apply elementary concepts from acid-base chemistry as well as protein and amino acid…

Structure-based drug design: aiming for a perfect fit

PubMed Central

van Montfort, Rob L.M.; Workman, Paul

2017-01-01

Knowledge of the three-dimensional structure of therapeutically relevant targets has informed drug discovery since the first protein structures were determined using X-ray crystallography in the 1950s and 1960s. In this editorial we provide a brief overview of the powerful impact of structure-based drug design (SBDD), which has its roots in computational and structural biology, with major contributions from both academia and industry. We describe advances in the application of SBDD for integral membrane protein targets that have traditionally proved very challenging. We emphasize the major progress made in fragment-based approaches for which success has been exemplified by over 30 clinical drug candidates and importantly three FDA-approved drugs in oncology. We summarize the articles in this issue that provide an excellent snapshot of the current state of the field of SBDD and fragment-based drug design and which offer key insights into exciting new developments, such as the X-ray free-electron laser technology, cryo-electron microscopy, open science approaches and targeted protein degradation. We stress the value of SBDD in the design of high-quality chemical tools that are used to interrogate biology and disease pathology, and to inform target validation. We emphasize the need to maintain the scientific rigour that has been traditionally associated with structural biology and extend this to other methods used in drug discovery. This is particularly important because the quality and robustness of any form of contributory data determines its usefulness in accelerating drug design, and therefore ultimately in providing patient benefit. PMID:29118091

HIVprotI: an integrated web based platform for prediction and design of HIV proteins inhibitors.

PubMed

Qureshi, Abid; Rajput, Akanksha; Kaur, Gazaldeep; Kumar, Manoj

2018-03-09

A number of anti-retroviral drugs are being used for treating Human Immunodeficiency Virus (HIV) infection. Due to emergence of drug resistant strains, there is a constant quest to discover more effective anti-HIV compounds. In this endeavor, computational tools have proven useful in accelerating drug discovery. Although methods were published to design a class of compounds against a specific HIV protein, but an integrated web server for the same is lacking. Therefore, we have developed support vector machine based regression models using experimentally validated data from ChEMBL repository. Quantitative structure activity relationship based features were selected for predicting inhibition activity of a compound against HIV proteins namely protease (PR), reverse transcriptase (RT) and integrase (IN). The models presented a maximum Pearson correlation coefficient of 0.78, 0.76, 0.74 and 0.76, 0.68, 0.72 during tenfold cross-validation on IC 50 and percent inhibition datasets of PR, RT, IN respectively. These models performed equally well on the independent datasets. Chemical space mapping, applicability domain analyses and other statistical tests further support robustness of the predictive models. Currently, we have identified a number of chemical descriptors that are imperative in predicting the compound inhibition potential. HIVprotI platform ( http://bioinfo.imtech.res.in/manojk/hivproti ) would be useful in virtual screening of inhibitors as well as designing of new molecules against the important HIV proteins for therapeutics development.

In silico fragment-based drug design.

PubMed

Konteatis, Zenon D

2010-11-01

In silico fragment-based drug design (FBDD) is a relatively new approach inspired by the success of the biophysical fragment-based drug discovery field. Here, we review the progress made by this approach in the last decade and showcase how it complements and expands the capabilities of biophysical FBDD and structure-based drug design to generate diverse, efficient drug candidates. Advancements in several areas of research that have enabled the development of in silico FBDD and some applications in drug discovery projects are reviewed. The reader is introduced to various computational methods that are used for in silico FBDD, the fragment library composition for this technique, special applications used to identify binding sites on the surface of proteins and how to assess the druggability of these sites. In addition, the reader will gain insight into the proper application of this approach from examples of successful programs. In silico FBDD captures a much larger chemical space than high-throughput screening and biophysical FBDD increasing the probability of developing more diverse, patentable and efficient molecules that can become oral drugs. The application of in silico FBDD holds great promise for historically challenging targets such as protein-protein interactions. Future advances in force fields, scoring functions and automated methods for determining synthetic accessibility will all aid in delivering more successes with in silico FBDD.

Thermodynamic Characterization of Hydration Sites from Integral Equation-Derived Free Energy Densities: Application to Protein Binding Sites and Ligand Series.

PubMed

Güssregen, Stefan; Matter, Hans; Hessler, Gerhard; Lionta, Evanthia; Heil, Jochen; Kast, Stefan M

2017-07-24

Water molecules play an essential role for mediating interactions between ligands and protein binding sites. Displacement of specific water molecules can favorably modulate the free energy of binding of protein-ligand complexes. Here, the nature of water interactions in protein binding sites is investigated by 3D RISM (three-dimensional reference interaction site model) integral equation theory to understand and exploit local thermodynamic features of water molecules by ranking their possible displacement in structure-based design. Unlike molecular dynamics-based approaches, 3D RISM theory allows for fast and noise-free calculations using the same detailed level of solute-solvent interaction description. Here we correlate molecular water entities instead of mere site density maxima with local contributions to the solvation free energy using novel algorithms. Distinct water molecules and hydration sites are investigated in multiple protein-ligand X-ray structures, namely streptavidin, factor Xa, and factor VIIa, based on 3D RISM-derived free energy density fields. Our approach allows the semiquantitative assessment of whether a given structural water molecule can potentially be targeted for replacement in structure-based design. Finally, PLS-based regression models from free energy density fields used within a 3D-QSAR approach (CARMa - comparative analysis of 3D RISM Maps) are shown to be able to extract relevant information for the interpretation of structure-activity relationship (SAR) trends, as demonstrated for a series of serine protease inhibitors.

Directed evolution of the TALE N-terminal domain for recognition of all 5' bases.

PubMed

Lamb, Brian M; Mercer, Andrew C; Barbas, Carlos F

2013-11-01

Transcription activator-like effector (TALE) proteins can be designed to bind virtually any DNA sequence. General guidelines for design of TALE DNA-binding domains suggest that the 5'-most base of the DNA sequence bound by the TALE (the N0 base) should be a thymine. We quantified the N0 requirement by analysis of the activities of TALE transcription factors (TALE-TF), TALE recombinases (TALE-R) and TALE nucleases (TALENs) with each DNA base at this position. In the absence of a 5' T, we observed decreases in TALE activity up to >1000-fold in TALE-TF activity, up to 100-fold in TALE-R activity and up to 10-fold reduction in TALEN activity compared with target sequences containing a 5' T. To develop TALE architectures that recognize all possible N0 bases, we used structure-guided library design coupled with TALE-R activity selections to evolve novel TALE N-terminal domains to accommodate any N0 base. A G-selective domain and broadly reactive domains were isolated and characterized. The engineered TALE domains selected in the TALE-R format demonstrated modularity and were active in TALE-TF and TALEN architectures. Evolved N-terminal domains provide effective and unconstrained TALE-based targeting of any DNA sequence as TALE binding proteins and designer enzymes.

Recent advances in recombinant protein-based malaria vaccines

PubMed Central

Draper, Simon J.; Angov, Evelina; Horii, Toshihiro; Miller, Louis H.; Srinivasan, Prakash; Theisen, Michael; Biswas, Sumi

2015-01-01

Plasmodium parasites are the causative agent of human malaria, and the development of a highly effective vaccine against infection, disease and transmission remains a key priority. It is widely established that multiple stages of the parasite's complex lifecycle within the human host and mosquito vector are susceptible to vaccine-induced antibodies. The mainstay approach to antibody induction by subunit vaccination has been the delivery of protein antigen formulated in adjuvant. Extensive efforts have been made in this endeavor with respect to malaria vaccine development, especially with regard to target antigen discovery, protein expression platforms, adjuvant testing, and development of soluble and virus-like particle (VLP) delivery platforms. The breadth of approaches to protein-based vaccines is continuing to expand as innovative new concepts in next-generation subunit design are explored, with the prospects for the development of a highly effective multi-component/multi-stage/multi-antigen formulation seeming ever more likely. This review will focus on recent progress in protein vaccine design, development and/or clinical testing for a number of leading malaria antigens from the sporozoite-, merozoite- and sexual-stages of the parasite's lifecycle–including PfCelTOS, PfMSP1, PfAMA1, PfRH5, PfSERA5, PfGLURP, PfMSP3, Pfs48/45 and Pfs25. Future prospects and challenges for the development, production, human delivery and assessment of protein-based malaria vaccines are discussed. PMID:26458807

Structure-Based Virtual Screening of Protein Tyrosine Phosphatase Inhibitors: Significance, Challenges, and Solutions.

PubMed

Reddy, Rallabandi Harikrishna; Kim, Hackyoung; Cha, Seungbin; Lee, Bongsoo; Kim, Young Jun

2017-05-28

Phosphorylation, a critical mechanism in biological systems, is estimated to be indispensable for about 30% of key biological activities, such as cell cycle progression, migration, and division. It is synergistically balanced by kinases and phosphatases, and any deviation from this balance leads to disease conditions. Pathway or biological activity-based abnormalities in phosphorylation and the type of involved phosphatase influence the outcome, and cause diverse diseases ranging from diabetes, rheumatoid arthritis, and numerous cancers. Protein tyrosine phosphatases (PTPs) are of prime importance in the process of dephosphorylation and catalyze several biological functions. Abnormal PTP activities are reported to result in several human diseases. Consequently, there is an increased demand for potential PTP inhibitory small molecules. Several strategies in structure-based drug designing techniques for potential inhibitory small molecules of PTPs have been explored along with traditional drug designing methods in order to overcome the hurdles in PTP inhibitor discovery. In this review, we discuss druggable PTPs and structure-based virtual screening efforts for successful PTP inhibitor design.

Flexible Molybdenum Electrodes towards Designing Affinity Based Protein Biosensors.

PubMed

Kamakoti, Vikramshankar; Panneer Selvam, Anjan; Radha Shanmugam, Nandhinee; Muthukumar, Sriram; Prasad, Shalini

2016-07-18

Molybdenum electrode based flexible biosensor on porous polyamide substrates has been fabricated and tested for its functionality as a protein affinity based biosensor. The biosensor performance was evaluated using a key cardiac biomarker; cardiac Troponin-I (cTnI). Molybdenum is a transition metal and demonstrates electrochemical behavior upon interaction with an electrolyte. We have leveraged this property of molybdenum for designing an affinity based biosensor using electrochemical impedance spectroscopy. We have evaluated the feasibility of detection of cTnI in phosphate-buffered saline (PBS) and human serum (HS) by measuring impedance changes over a frequency window from 100 mHz to 1 MHz. Increasing changes to the measured impedance was correlated to the increased dose of cTnI molecules binding to the cTnI antibody functionalized molybdenum surface. We achieved cTnI detection limit of 10 pg/mL in PBS and 1 ng/mL in HS medium. The use of flexible substrates for designing the biosensor demonstrates promise for integration with a large-scale batch manufacturing process.

Discovery of Klotho peptide antagonists against Wnt3 and Wnt3a target proteins using combination of protein engineering, protein-protein docking, peptide docking and molecular dynamics simulations.

PubMed

Mirza, Shaher Bano; Ekhteiari Salmas, Ramin; Fatmi, M Qaiser; Durdagi, Serdar

2017-12-01

The Klotho is known as lifespan enhancing protein involved in antagonizing the effect of Wnt proteins. Wnt proteins are stem cell regulators, and uninterrupted exposure of Wnt proteins to the cell can cause stem and progenitor cell senescence, which may lead to aging. Keeping in mind the importance of Klotho in Wnt signaling, in silico approaches have been applied to study the important interactions between Klotho and Wnt3 and Wnt3a (wingless-type mouse mammary tumor virus (MMTV) integration site family members 3 and 3a). The main aim of the study is to identify important residues of the Klotho that help in designing peptides which can act as Wnt antagonists. For this aim, a protein engineering study is performed for Klotho, Wnt3 and Wnt3a. During the theoretical analysis of homology models, unexpected role of number of disulfide bonds and secondary structure elements has been witnessed in case of Wnt3 and Wnt3a proteins. Different in silico experiments were carried out to observe the effect of correct number of disulfide bonds on 3D protein models. For this aim, total of 10 molecular dynamics (MD) simulations were carried out for each system. Based on the protein-protein docking simulations of selected protein models of Klotho with Wnt3 and Wnt3a, different peptides derived from Klotho have been designed. Wnt3 and Wnt3a proteins have three important domains: Index finger, N-terminal domain and a patch of ∼10 residues on the solvent exposed surface of palm domain. Protein-peptide docking of designed peptides of Klotho against three important domains of palmitoylated Wnt3 and Wnt3a yields encouraging results and leads better understanding of the Wnt protein inhibition by proposed Klotho peptides. Further in vitro studies can be carried out to verify effects of novel designed peptides as Wnt antagonists.

Design principles for nuclease-deficient CRISPR-based transcriptional regulators.

PubMed

Jensen, Michael K

2018-06-01

The engineering of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-CRISPR-associated proteins continues to expand the toolkit available for genome editing, reprogramming gene regulation, genome visualisation and epigenetic studies of living organisms. In this review, the emerging design principles on the use of nuclease-deficient CRISPR-based reprogramming of gene expression will be presented. The review will focus on the designs implemented in yeast both at the level of CRISPR proteins and guide RNA (gRNA), but will lend due credits to the seminal studies performed in other species where relevant. In addition to design principles, this review also highlights applications benefitting from the use of CRISPR-mediated transcriptional regulation and discusses the future directions to further expand the toolkit for nuclease-deficient reprogramming of genomes. As such, this review should be of general interest for experimentalists to get familiarised with the parameters underlying the power of reprogramming genomic functions by use of nuclease-deficient CRISPR technologies.

The application of quantum mechanics in structure-based drug design.

PubMed

Mucs, Daniel; Bryce, Richard A

2013-03-01

Computational chemistry has become an established and valuable component in structure-based drug design. However the chemical complexity of many ligands and active sites challenges the accuracy of the empirical potentials commonly used to describe these systems. Consequently, there is a growing interest in utilizing electronic structure methods for addressing problems in protein-ligand recognition. In this review, the authors discuss recent progress in the development and application of quantum chemical approaches to modeling protein-ligand interactions. The authors specifically consider the development of quantum mechanics (QM) approaches for studying large molecular systems pertinent to biology, focusing on protein-ligand docking, protein-ligand binding affinities and ligand strain on binding. Although computation of binding energies remains a challenging and evolving area, current QM methods can underpin improved docking approaches and offer detailed insights into ligand strain and into the nature and relative strengths of complex active site interactions. The authors envisage that QM will become an increasingly routine and valued tool of the computational medicinal chemist.

Sequence signatures of allosteric proteins towards rational design.

PubMed

Namboodiri, Saritha; Verma, Chandra; Dhar, Pawan K; Giuliani, Alessandro; Nair, Achuthsankar S

2010-12-01

Allostery is the phenomenon of changes in the structure and activity of proteins that appear as a consequence of ligand binding at sites other than the active site. Studying mechanistic basis of allostery leading to protein design with predetermined functional endpoints is an important unmet need of synthetic biology. Here, we screened the amino acid sequence landscape in search of sequence-signatures of allostery using Recurrence Quantitative Analysis (RQA) method. A characteristic vector, comprised of 10 features extracted from RQA was defined for amino acid sequences. Using Principal Component Analysis, four factors were found to be important determinants of allosteric behavior. Our sequence-based predictor method shows 82.6% accuracy, 85.7% sensitivity and 77.9% specificity with the current dataset. Further, we show that Laminarity-Mean-hydrophobicity representing repeated hydrophobic patches is the most crucial indicator of allostery. To our best knowledge this is the first report that describes sequence determinants of allostery based on hydrophobicity. As an outcome of these findings, we plan to explore possibility of inducing allostery in proteins.

Sampling and energy evaluation challenges in ligand binding protein design.

PubMed

Dou, Jiayi; Doyle, Lindsey; Jr Greisen, Per; Schena, Alberto; Park, Hahnbeom; Johnsson, Kai; Stoddard, Barry L; Baker, David

2017-12-01

The steroid hormone 17α-hydroxylprogesterone (17-OHP) is a biomarker for congenital adrenal hyperplasia and hence there is considerable interest in development of sensors for this compound. We used computational protein design to generate protein models with binding sites for 17-OHP containing an extended, nonpolar, shape-complementary binding pocket for the four-ring core of the compound, and hydrogen bonding residues at the base of the pocket to interact with carbonyl and hydroxyl groups at the more polar end of the ligand. Eight of 16 designed proteins experimentally tested bind 17-OHP with micromolar affinity. A co-crystal structure of one of the designs revealed that 17-OHP is rotated 180° around a pseudo-two-fold axis in the compound and displays multiple binding modes within the pocket, while still interacting with all of the designed residues in the engineered site. Subsequent rounds of mutagenesis and binding selection improved the ligand affinity to nanomolar range, while appearing to constrain the ligand to a single bound conformation that maintains the same "flipped" orientation relative to the original design. We trace the discrepancy in the design calculations to two sources: first, a failure to model subtle backbone changes which alter the distribution of sidechain rotameric states and second, an underestimation of the energetic cost of desolvating the carbonyl and hydroxyl groups of the ligand. The difference between design model and crystal structure thus arises from both sampling limitations and energy function inaccuracies that are exacerbated by the near two-fold symmetry of the molecule. © 2017 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

αRep A3: A Versatile Artificial Scaffold for Metalloenzyme Design.

PubMed

Di Meo, Thibault; Ghattas, Wadih; Herrero, Christian; Velours, Christophe; Minard, Philippe; Mahy, Jean-Pierre; Ricoux, Rémy; Urvoas, Agathe

2017-07-26

αRep refers to a new family of artificial proteins based on a thermostable α-helical repeated motif. One of its members, αRep A3, forms a stable homo-dimer with a wide cleft that is able to accommodate metal complexes and thus appears to be suitable for generating new artificial biocatalysts. Based on the crystal structure of αRep A3, two positions (F119 and Y26) were chosen, and independently changed into cysteine residues. A phenanthroline ligand was covalently attached to the unique cysteine residue of each protein variant, and the corresponding biohybrids were purified and characterized. Once mutated and coupled to phenanthroline, the protein remained folded and dimeric. Copper(II) was specifically bound by the two biohybrids with two different binding modes. Furthermore, the holo-biohybrid A3F119NPH was found to be capable of enantioselectively catalyzing Diels-Alder (D-A) cycloadditions with up to 62 % ee. This study validates the choice of the αRep A3 dimer as a protein scaffold and provides a promising new route for the design and production of new enantioselective biohybrids based on entirely artificial proteins obtained from a highly diverse library. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Designer amphiphilic proteins as building blocks for the intracellular formation of organelle-like compartments

NASA Astrophysics Data System (ADS)

Huber, Matthias C.; Schreiber, Andreas; von Olshausen, Philipp; Varga, Balázs R.; Kretz, Oliver; Joch, Barbara; Barnert, Sabine; Schubert, Rolf; Eimer, Stefan; Kele, Péter; Schiller, Stefan M.

2015-01-01

Nanoscale biological materials formed by the assembly of defined block-domain proteins control the formation of cellular compartments such as organelles. Here, we introduce an approach to intentionally ‘program’ the de novo synthesis and self-assembly of genetically encoded amphiphilic proteins to form cellular compartments, or organelles, in Escherichia coli. These proteins serve as building blocks for the formation of artificial compartments in vivo in a similar way to lipid-based organelles. We investigated the formation of these organelles using epifluorescence microscopy, total internal reflection fluorescence microscopy and transmission electron microscopy. The in vivo modification of these protein-based de novo organelles, by means of site-specific incorporation of unnatural amino acids, allows the introduction of artificial chemical functionalities. Co-localization of membrane proteins results in the formation of functionalized artificial organelles combining artificial and natural cellular function. Adding these protein structures to the cellular machinery may have consequences in nanobiotechnology, synthetic biology and materials science, including the constitution of artificial cells and bio-based metamaterials.

Quantitative structure-activity relationship: promising advances in drug discovery platforms.

PubMed

Wang, Tao; Wu, Mian-Bin; Lin, Jian-Ping; Yang, Li-Rong

2015-12-01

Quantitative structure-activity relationship (QSAR) modeling is one of the most popular computer-aided tools employed in medicinal chemistry for drug discovery and lead optimization. It is especially powerful in the absence of 3D structures of specific drug targets. QSAR methods have been shown to draw public attention since they were first introduced. In this review, the authors provide a brief discussion of the basic principles of QSAR, model development and model validation. They also highlight the current applications of QSAR in different fields, particularly in virtual screening, rational drug design and multi-target QSAR. Finally, in view of recent controversies, the authors detail the challenges faced by QSAR modeling and the relevant solutions. The aim of this review is to show how QSAR modeling can be applied in novel drug discovery, design and lead optimization. QSAR should intentionally be used as a powerful tool for fragment-based drug design platforms in the field of drug discovery and design. Although there have been an increasing number of experimentally determined protein structures in recent years, a great number of protein structures cannot be easily obtained (i.e., membrane transport proteins and G-protein coupled receptors). Fragment-based drug discovery, such as QSAR, could be applied further and have a significant role in dealing with these problems. Moreover, along with the development of computer software and hardware, it is believed that QSAR will be increasingly important.

Experimental design based 3-D QSAR analysis of steroid-protein interactions: Application to human CBG complexes

NASA Astrophysics Data System (ADS)

Norinder, Ulf

1990-12-01

An experimental design based 3-D QSAR analysis using a combination of principal component and PLS analysis is presented and applied to human corticosteroid-binding globulin complexes. The predictive capability of the created model is good. The technique can also be used as guidance when selecting new compounds to be investigated.

A highly efficient dual-diazonium reagent for protein crosslinking and construction of a virus-based gel.

PubMed

Ma, Dejun; Zhang, Jie; Zhang, Changyu; Men, Yuwen; Sun, Hongyan; Li, Lu-Yuan; Yi, Long; Xi, Zhen

2018-05-09

A new bench-stable reagent with double diazonium sites was designed and synthesized for protein crosslinking. Based on the highly efficient diazonium-Tyr coupling reaction, a direct mixture of the reagent and tobacco mosaic virus led to the formation of a new hydrogel, which could be degraded by chemicals and could be used to encapsulate small molecules for sustained release. Because plant viruses exhibit many chemical characteristics like protein labelling and nucleic acid packaging, the virus-based hydrogel will have large chemical space for further functionalization. Besides, this dual-diazonium reagent should be a generally useful crosslinker for chemical biology and biomaterials.

Optimizing pH response of affinity between protein G and IgG Fc: how electrostatic modulations affect protein-protein interactions.

PubMed

Watanabe, Hideki; Matsumaru, Hiroyuki; Ooishi, Ayako; Feng, Yanwen; Odahara, Takayuki; Suto, Kyoko; Honda, Shinya

2009-05-01

Protein-protein interaction in response to environmental conditions enables sophisticated biological and biotechnological processes. Aiming toward the rational design of a pH-sensitive protein-protein interaction, we engineered pH-sensitive mutants of streptococcal protein G B1, a binder to the IgG constant region. We systematically introduced histidine residues into the binding interface to cause electrostatic repulsion on the basis of a rigid body model. Exquisite pH sensitivity of this interaction was confirmed by surface plasmon resonance and affinity chromatography employing a clinically used human IgG. The pH-sensitive mechanism of the interaction was analyzed and evaluated from kinetic, thermodynamic, and structural viewpoints. Histidine-mediated electrostatic repulsion resulted in significant loss of exothermic heat of the binding that decreased the affinity only at acidic conditions, thereby improving the pH sensitivity. The reduced binding energy was partly recovered by "enthalpy-entropy compensation." Crystal structures of the designed mutants confirmed the validity of the rigid body model on which the effective electrostatic repulsion was based. Moreover, our data suggested that the entropy gain involved exclusion of water molecules solvated in a space formed by the introduced histidine and adjacent tryptophan residue. Our findings concerning the mechanism of histidine-introduced interactions will provide a guideline for the rational design of pH-sensitive protein-protein recognition.

Two-level QSAR network (2L-QSAR) for peptide inhibitor design based on amino acid properties and sequence positions.

PubMed

Du, Q S; Ma, Y; Xie, N Z; Huang, R B

2014-01-01

In the design of peptide inhibitors the huge possible variety of the peptide sequences is of high concern. In collaboration with the fast accumulation of the peptide experimental data and database, a statistical method is suggested for peptide inhibitor design. In the two-level peptide prediction network (2L-QSAR) one level is the physicochemical properties of amino acids and the other level is the peptide sequence position. The activity contributions of amino acids are the functions of physicochemical properties and the sequence positions. In the prediction equation two weight coefficient sets {ak} and {bl} are assigned to the physicochemical properties and to the sequence positions, respectively. After the two coefficient sets are optimized based on the experimental data of known peptide inhibitors using the iterative double least square (IDLS) procedure, the coefficients are used to evaluate the bioactivities of new designed peptide inhibitors. The two-level prediction network can be applied to the peptide inhibitor design that may aim for different target proteins, or different positions of a protein. A notable advantage of the two-level statistical algorithm is that there is no need for host protein structural information. It may also provide useful insight into the amino acid properties and the roles of sequence positions.

Exploring codon context bias for synthetic gene design of a thermostable invertase in Escherichia coli.

PubMed

Pek, Han Bin; Klement, Maximilian; Ang, Kok Siong; Chung, Bevan Kai-Sheng; Ow, Dave Siak-Wei; Lee, Dong-Yup

2015-01-01

Various isoforms of invertases from prokaryotes, fungi, and higher plants has been expressed in Escherichia coli, and codon optimisation is a widely-adopted strategy for improvement of heterologous enzyme expression. Successful synthetic gene design for recombinant protein expression can be done by matching its translational elongation rate against heterologous host organisms via codon optimization. Amongst the various design parameters considered for the gene synthesis, codon context bias has been relatively overlooked compared to individual codon usage which is commonly adopted in most of codon optimization tools. In addition, matching the rates of transcription and translation based on secondary structure may lead to enhanced protein folding. In this study, we evaluated codon context fitness as design criterion for improving the expression of thermostable invertase from Thermotoga maritima in Escherichia coli and explored the relevance of secondary structure regions for folding and expression. We designed three coding sequences by using (1) a commercial vendor optimized gene algorithm, (2) codon context for the whole gene, and (3) codon context based on the secondary structure regions. Then, the codon optimized sequences were transformed and expressed in E. coli. From the resultant enzyme activities and protein yield data, codon context fitness proved to have the highest activity as compared to the wild-type control and other criteria while secondary structure-based strategy is comparable to the control. Codon context bias was shown to be a relevant parameter for enhancing enzyme production in Escherichia coli by codon optimization. Thus, we can effectively design synthetic genes within heterologous host organisms using this criterion. Copyright © 2015 Elsevier Inc. All rights reserved.

Structure-based design of peptides against HER2 with cytotoxicity on colon cancer.

PubMed

Cha, Nier; Han, Xiuhua; Jia, Baoqing; Liu, Yanheng; Wang, Xiaoli; Gao, Yanwei; Ren, Jun

2017-05-01

In this study, we found that four novel peptides designed by molecular modeling techniques were successfully applicated with cytotoxicity on colon cancer cells sw620. First, the interactions between the Herstatin and the HER2 were explored by ational-designed approaches, which were combined with homology modeling, protein/protein docking, and structural superimposition analysis. Then, based on the results derived from theoretical analysis, four novel peptides were designed, synthesized, and experimentally evaluated for biological function; it was found that they showed a remarkable enhancement on Herceptin to inhibit the genesis and development of colon cancers, and no significant side effects on normal colon cells NCM460 were observed but Doxorubicin had. These results indicated that it is a feasible way to use the well-designed peptides derived from Herstatin to enhance the efficacy of clinical drugs Herceptin and to kill colon cancer cells selectively without harming normal colon cells. We believe that our research might provide a new way to develop the potential therapies for colon cancers.

The rational design of a novel potent analogue of the 5’-AMP-activated protein kinase inhibitor compound C with improved selectivity and cellular activity

PubMed Central

Machrouhi, Fouzia; Ouhamou, Nouara; Laderoute, Keith; Calaoagan, Joy; Bukhtiyarova, Marina; Ehrlich, Paula J.; Klon, Anthony E.

2010-01-01

We have designed and synthesized analogues of compound C, a non-specific inhibitor of 5’-AMP-activated protein kinase (AMPK), using a computational fragment-based drug design (FBDD) approach. Synthesizing only twenty-seven analogues yielded a compound that was equipotent to compound C in the inhibition of the human AMPK (hAMPK) α2 subunit in the heterotrimeric complex in vitro, exhibited significantly improved selectivity against a subset of relevant kinases, and demonstrated enhanced cellular inhibition of AMPK. PMID:20932747

G-LoSA: An efficient computational tool for local structure-centric biological studies and drug design.

PubMed

Lee, Hui Sun; Im, Wonpil

2016-04-01

Molecular recognition by protein mostly occurs in a local region on the protein surface. Thus, an efficient computational method for accurate characterization of protein local structural conservation is necessary to better understand biology and drug design. We present a novel local structure alignment tool, G-LoSA. G-LoSA aligns protein local structures in a sequence order independent way and provides a GA-score, a chemical feature-based and size-independent structure similarity score. Our benchmark validation shows the robust performance of G-LoSA to the local structures of diverse sizes and characteristics, demonstrating its universal applicability to local structure-centric comparative biology studies. In particular, G-LoSA is highly effective in detecting conserved local regions on the entire surface of a given protein. In addition, the applications of G-LoSA to identifying template ligands and predicting ligand and protein binding sites illustrate its strong potential for computer-aided drug design. We hope that G-LoSA can be a useful computational method for exploring interesting biological problems through large-scale comparison of protein local structures and facilitating drug discovery research and development. G-LoSA is freely available to academic users at http://im.compbio.ku.edu/GLoSA/. © 2016 The Protein Society.

Development of a Green Fluorescent Protein-Based Laboratory Curriculum

ERIC Educational Resources Information Center

Larkin, Patrick D.; Hartberg, Yasha

2005-01-01

A laboratory curriculum has been designed for an undergraduate biochemistry course that focuses on the investigation of the green fluorescent protein (GFP). The sequence of procedures extends from analysis of the DNA sequence through PCR amplification, recombinant plasmid DNA synthesis, bacterial transformation, expression, isolation, and…

High performance transcription factor-DNA docking with GPU computing

PubMed Central

2012-01-01

Background Protein-DNA docking is a very challenging problem in structural bioinformatics and has important implications in a number of applications, such as structure-based prediction of transcription factor binding sites and rational drug design. Protein-DNA docking is very computational demanding due to the high cost of energy calculation and the statistical nature of conformational sampling algorithms. More importantly, experiments show that the docking quality depends on the coverage of the conformational sampling space. It is therefore desirable to accelerate the computation of the docking algorithm, not only to reduce computing time, but also to improve docking quality. Methods In an attempt to accelerate the sampling process and to improve the docking performance, we developed a graphics processing unit (GPU)-based protein-DNA docking algorithm. The algorithm employs a potential-based energy function to describe the binding affinity of a protein-DNA pair, and integrates Monte-Carlo simulation and a simulated annealing method to search through the conformational space. Algorithmic techniques were developed to improve the computation efficiency and scalability on GPU-based high performance computing systems. Results The effectiveness of our approach is tested on a non-redundant set of 75 TF-DNA complexes and a newly developed TF-DNA docking benchmark. We demonstrated that the GPU-based docking algorithm can significantly accelerate the simulation process and thereby improving the chance of finding near-native TF-DNA complex structures. This study also suggests that further improvement in protein-DNA docking research would require efforts from two integral aspects: improvement in computation efficiency and energy function design. Conclusions We present a high performance computing approach for improving the prediction accuracy of protein-DNA docking. The GPU-based docking algorithm accelerates the search of the conformational space and thus increases the chance of finding more near-native structures. To the best of our knowledge, this is the first ad hoc effort of applying GPU or GPU clusters to the protein-DNA docking problem. PMID:22759575

PyRosetta: a script-based interface for implementing molecular modeling algorithms using Rosetta.

PubMed

Chaudhury, Sidhartha; Lyskov, Sergey; Gray, Jeffrey J

2010-03-01

PyRosetta is a stand-alone Python-based implementation of the Rosetta molecular modeling package that allows users to write custom structure prediction and design algorithms using the major Rosetta sampling and scoring functions. PyRosetta contains Python bindings to libraries that define Rosetta functions including those for accessing and manipulating protein structure, calculating energies and running Monte Carlo-based simulations. PyRosetta can be used in two ways: (i) interactively, using iPython and (ii) script-based, using Python scripting. Interactive mode contains a number of help features and is ideal for beginners while script-mode is best suited for algorithm development. PyRosetta has similar computational performance to Rosetta, can be easily scaled up for cluster applications and has been implemented for algorithms demonstrating protein docking, protein folding, loop modeling and design. PyRosetta is a stand-alone package available at http://www.pyrosetta.org under the Rosetta license which is free for academic and non-profit users. A tutorial, user's manual and sample scripts demonstrating usage are also available on the web site.

PyRosetta: a script-based interface for implementing molecular modeling algorithms using Rosetta

PubMed Central

Chaudhury, Sidhartha; Lyskov, Sergey; Gray, Jeffrey J.

2010-01-01

Summary: PyRosetta is a stand-alone Python-based implementation of the Rosetta molecular modeling package that allows users to write custom structure prediction and design algorithms using the major Rosetta sampling and scoring functions. PyRosetta contains Python bindings to libraries that define Rosetta functions including those for accessing and manipulating protein structure, calculating energies and running Monte Carlo-based simulations. PyRosetta can be used in two ways: (i) interactively, using iPython and (ii) script-based, using Python scripting. Interactive mode contains a number of help features and is ideal for beginners while script-mode is best suited for algorithm development. PyRosetta has similar computational performance to Rosetta, can be easily scaled up for cluster applications and has been implemented for algorithms demonstrating protein docking, protein folding, loop modeling and design. Availability: PyRosetta is a stand-alone package available at http://www.pyrosetta.org under the Rosetta license which is free for academic and non-profit users. A tutorial, user's manual and sample scripts demonstrating usage are also available on the web site. Contact: pyrosetta@graylab.jhu.edu PMID:20061306

Fractal symmetry of protein interior: what have we learned?

PubMed

Banerji, Anirban; Ghosh, Indira

2011-08-01

The application of fractal dimension-based constructs to probe the protein interior dates back to the development of the concept of fractal dimension itself. Numerous approaches have been tried and tested over a course of (almost) 30 years with the aim of elucidating the various facets of symmetry of self-similarity prevalent in the protein interior. In the last 5 years especially, there has been a startling upsurge of research that innovatively stretches the limits of fractal-based studies to present an array of unexpected results on the biophysical properties of protein interior. In this article, we introduce readers to the fundamentals of fractals, reviewing the commonality (and the lack of it) between these approaches before exploring the patterns in the results that they produced. Clustering the approaches in major schools of protein self-similarity studies, we describe the evolution of fractal dimension-based methodologies. The genealogy of approaches (and results) presented here portrays a clear picture of the contemporary state of fractal-based studies in the context of the protein interior. To underline the utility of fractal dimension-based measures further, we have performed a correlation dimension analysis on all of the available non-redundant protein structures, both at the level of an individual protein and at the level of structural domains. In this investigation, we were able to separately quantify the self-similar symmetries in spatial correlation patterns amongst peptide-dipole units, charged amino acids, residues with the π-electron cloud and hydrophobic amino acids. The results revealed that electrostatic environments in the interiors of proteins belonging to 'α/α toroid' (all-α class) and 'PLP-dependent transferase-like' domains (α/β class) are highly conducive. In contrast, the interiors of 'zinc finger design' ('designed proteins') and 'knottins' ('small proteins') were identified as folds with the least conducive electrostatic environments. The fold 'conotoxins' (peptides) could be unambiguously identified as one type with the least stability. The same analyses revealed that peptide-dipoles in the α/β class of proteins, in general, are more correlated to each other than are the peptide-dipoles in proteins belonging to the all-α class. Highly favorable electrostatic milieu in the interiors of TIM-barrel, α/β-hydrolase structures could explain their remarkably conserved (evolutionary) stability from a new light. Finally, we point out certain inherent limitations of fractal constructs before attempting to identify the areas and problems where the implementation of fractal dimension-based constructs can be of paramount help to unearth latent information on protein structural properties.

NHLBI-AbDesigner: an online tool for design of peptide-directed antibodies.

PubMed

Pisitkun, Trairak; Hoffert, Jason D; Saeed, Fahad; Knepper, Mark A

2012-01-01

Investigation of physiological mechanisms at a cellular level often requires production of high-quality antibodies, frequently using synthetic peptides as immunogens. Here we describe a new, web-based software tool called NHLBI-AbDesigner that allows the user to visualize the information needed to choose optimal peptide sequences for peptide-directed antibody production (http://helixweb.nih.gov/AbDesigner/). The choice of an immunizing peptide is generally based on a need to optimize immunogenicity, antibody specificity, multispecies conservation, and robustness in the face of posttranslational modifications (PTMs). AbDesigner displays information relevant to these criteria as follows: 1) "Immunogenicity Score," based on hydropathy and secondary structure prediction; 2) "Uniqueness Score," a predictor of specificity of an antibody against all proteins expressed in the same species; 3) "Conservation Score," a predictor of ability of the antibody to recognize orthologs in other animal species; and 4) "Protein Features" that show structural domains, variable regions, and annotated PTMs that may affect antibody performance. AbDesigner displays the information online in an interactive graphical user interface, which allows the user to recognize the trade-offs that exist for alternative synthetic peptide choices and to choose the one that is best for a proposed application. Several examples of the use of AbDesigner for the display of such trade-offs are presented, including production of a new antibody to Slc9a3. We also used the program in large-scale mode to create a database listing the 15-amino acid peptides with the highest Immunogenicity Scores for all known proteins in five animal species, one plant species (Arabidopsis thaliana), and Saccharomyces cerevisiae.

An Inquiry into Protein Structure and Genetic Disease: Introducing Undergraduates to Bioinformatics in a Large Introductory Course

ERIC Educational Resources Information Center

Bednarski, April E.; Elgin, Sarah C. R.; Pakrasi, Himadri B.

2005-01-01

This inquiry-based lab is designed around genetic diseases with a focus on protein structure and function. To allow students to work on their own investigatory projects, 10 projects on 10 different proteins were developed. Students are grouped in sections of 20 and work in pairs on each of the projects. To begin their investigation, students are…

Elongational Flow Assists with the Assembly of Protein Nanofibrils

NASA Astrophysics Data System (ADS)

Mittal, Nitesh; Kamada, Ayaka; Lendel, Christofer; Lundell, Fredrik; Soderberg, Daniel

2016-11-01

Controlling the aggregation process of protein-based macromolecular structures in a confined environment using small-scale flow devices and understanding their assembly mechanisms is essential to develop bio-based materials. Whey protein, a protein mixture with β-lactoglobulin as main component, is able to self-assemble into amyloid-like protein nanofibers which are stabilized by hydrogen bonds. The conditions at which the fibrillation process occurs can affect the properties and morphology of the fibrils. Here, we show that the morphology of protein nanofibers greatly affects their assembly. We used elongational flow based double flow-focusing device for this study. In-situ behavior of the straight and flexible fibrils in the flow channel is determined using small-angle X-ray scattering (SAXS) technique. Our process combines hydrodynamic alignment with dispersion to gel-transition that produces homogeneous and smooth fibers. Moreover, successful alignment before gelation demands a proper separation of the time-scales involved, which we tried to identify in the current study. The presented approach combining small scale flow devices with in-situ synchrotron X-ray studies and protein engineering is a promising route to design high performance protein-based materials with controlled physical and chemical properties. We acknowledge the support from Wallenberg Wood Science Center.

Peptide-based Fluorescent Sensors of Protein Kinase Activity: Design and Applications

PubMed Central

Sharma, Vyas; Wang, Qunzhao; Lawrence, David S.

2009-01-01

Protein kinases control the flow of information through cell-signaling pathways. A detailed analysis of their behavior enhances our ability to understand normal cellular states and to devise therapeutic interventions for diseases. The design and application of “Environmentally-Sensitive”, “Deep-Quench” and “Self-Reporting” sensor systems for studying protein kinase activity are described. These sensors allow real-time activity measurements in a continuous manner for a wide variety of kinases. As these sensors can be adapted from an in vitro screen to imaging kinase activity in living cells, they support both preliminary and later stages of drug discovery. PMID:17881302

Protein loop modeling using a new hybrid energy function and its application to modeling in inaccurate structural environments.

PubMed

Park, Hahnbeom; Lee, Gyu Rie; Heo, Lim; Seok, Chaok

2014-01-01

Protein loop modeling is a tool for predicting protein local structures of particular interest, providing opportunities for applications involving protein structure prediction and de novo protein design. Until recently, the majority of loop modeling methods have been developed and tested by reconstructing loops in frameworks of experimentally resolved structures. In many practical applications, however, the protein loops to be modeled are located in inaccurate structural environments. These include loops in model structures, low-resolution experimental structures, or experimental structures of different functional forms. Accordingly, discrepancies in the accuracy of the structural environment assumed in development of the method and that in practical applications present additional challenges to modern loop modeling methods. This study demonstrates a new strategy for employing a hybrid energy function combining physics-based and knowledge-based components to help tackle this challenge. The hybrid energy function is designed to combine the strengths of each energy component, simultaneously maintaining accurate loop structure prediction in a high-resolution framework structure and tolerating minor environmental errors in low-resolution structures. A loop modeling method based on global optimization of this new energy function is tested on loop targets situated in different levels of environmental errors, ranging from experimental structures to structures perturbed in backbone as well as side chains and template-based model structures. The new method performs comparably to force field-based approaches in loop reconstruction in crystal structures and better in loop prediction in inaccurate framework structures. This result suggests that higher-accuracy predictions would be possible for a broader range of applications. The web server for this method is available at http://galaxy.seoklab.org/loop with the PS2 option for the scoring function.

Designed Proteins as Novel Imaging Reagents in Living Escherichia coli.

PubMed

Pratt, Susan E; Speltz, Elizabeth B; Mochrie, Simon G J; Regan, Lynne

2016-09-02

Fluorescence imaging is a powerful tool to study protein function in living cells. Here, we introduce a novel imaging strategy that is fully genetically encodable, does not require the use of exogenous substrates, and adds a minimally disruptive tag to the protein of interest (POI). Our method was based on a set of designed tetratricopeptide repeat affinity proteins (TRAPs) that specifically and reversibly interact with a short, extended peptide tag. We co-expressed the TRAPs fused to fluorescent proteins (FPs) and the peptide tags fused to the POIs. We illustrated the method using the Escherichia coli protein FtsZ and showed that our system could track distinct FtsZ structures under both low and high expression conditions in live cells. We anticipate that our imaging strategy will be a useful tool for imaging the subcellular localization of many proteins, especially those recalcitrant to imaging by direct tagging with FPs. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Rational design of a monomeric and photostable far-red fluorescent protein for fluorescence imaging in vivo.

PubMed

Yu, Dan; Dong, Zhiqiang; Gustafson, William Clay; Ruiz-González, Rubén; Signor, Luca; Marzocca, Fanny; Borel, Franck; Klassen, Matthew P; Makhijani, Kalpana; Royant, Antoine; Jan, Yuh-Nung; Weiss, William A; Guo, Su; Shu, Xiaokun

2016-02-01

Fluorescent proteins (FPs) are powerful tools for cell and molecular biology. Here based on structural analysis, a blue-shifted mutant of a recently engineered monomeric infrared fluorescent protein (mIFP) has been rationally designed. This variant, named iBlueberry, bears a single mutation that shifts both excitation and emission spectra by approximately 40 nm. Furthermore, iBlueberry is four times more photostable than mIFP, rendering it more advantageous for imaging protein dynamics. By tagging iBlueberry to centrin, it has been demonstrated that the fusion protein labels the centrosome in the developing zebrafish embryo. Together with GFP-labeled nucleus and tdTomato-labeled plasma membrane, time-lapse imaging to visualize the dynamics of centrosomes in radial glia neural progenitors in the intact zebrafish brain has been demonstrated. It is further shown that iBlueberry can be used together with mIFP in two-color protein labeling in living cells and in two-color tumor labeling in mice. © 2015 The Protein Society.

Two-colored fluorescence correlation spectroscopy screening for LC3-P62 interaction inhibitors.

PubMed

Tsuganezawa, Keiko; Shinohara, Yoshiyasu; Ogawa, Naoko; Tsuboi, Shun; Okada, Norihisa; Mori, Masumi; Yokoyama, Shigeyuki; Noda, Nobuo N; Inagaki, Fuyuhiko; Ohsumi, Yoshinori; Tanaka, Akiko

2013-10-01

The fluorescence correlation spectroscopy (FCS)-based competitive binding assay to screen for protein-protein interaction inhibitors is a highly sensitive method as compared with the fluorescent polarization assay used conventionally. However, the FCS assay identifies many false-positive compounds, which requires specifically designed orthogonal screenings. A two-colored application of the FCS-based screening was newly developed, and inhibitors of a protein-protein interaction, involving selective autophagy, were selected. We focused on the interaction of LC3 with the adaptor protein p62, because the interaction is crucial to degrade the specific target proteins recruited by p62. First, about 10,000 compounds were subjected to the FCS-based competitive assay using a TAMRA-labeled p62-derived probe, and 29 hit compounds were selected. Next, the obtained hits were evaluated by the second FCS assay, using an Alexa647-labeled p62-derived probe to remove the false-positive compounds, and six hit compounds inhibited the interaction. Finally, we tested all 29 compounds by surface plasmon resonance-based competitive binding assay to evaluate their inhibition of the LC3-p62 interaction and selected two inhibitors with IC50 values less than 2 µM. The two-colored FCS-based screening was shown to be effective to screen for protein-protein interaction inhibitors.

Development of an optical Zn 2+ probe based on a single fluorescent protein

DOE PAGES

Qin, Yan; Sammond, Deanne W.; Braselmann, Esther; ...

2016-07-28

Various fluorescent probes have been developed to reveal the biological functions of intracellular labile Zn 2+. Here we present Green Zinc Probe (GZnP), a novel genetically encoded Zn 2+ sensor design based on a single fluorescent protein (single-FP). The GZnP sensor is generated by attaching two zinc fingers (ZF) of the transcription factor Zap1 (ZF1 and ZF2) to the two ends of a circularly permuted green fluorescent protein (cpGFP). Formation of ZF folds induces interaction between the two ZFs, which induces a change in the cpGFP conformation, leading to an increase in fluorescence. A small sensor library is created tomore » include mutations in the ZFs, cpGFP and linkers between ZF and cpGFP to improve signal stability, sensor brightness and dynamic range based on rational protein engineering and computational design by Rosetta. Using a cell-based library screen, we identify sensor GZnP1 which demonstrates a stable maximum signal, decent brightness (QY = 0.42 at apo state), as well as specific and sensitive response to Zn 2+ in HeLa cells (F max/F min = 2.6, K d = 58 pM, pH 7.4). The subcellular localizing sensors mito-GZnP1 (in mitochondria matrix) and Lck-GZnP1 (on plasma membrane) display sensitivity to Zn 2+ (F max/F min = 2.2). In conclusion, this sensor design provides freedom to be used in combination with other optical indicators and optogenetic tools for simultaneous imaging and advancing our understanding of cellular Zn 2+ function.« less

Exploration of the relationship between topology and designability of conformations

NASA Astrophysics Data System (ADS)

Leelananda, Sumudu P.; Towfic, Fadi; Jernigan, Robert L.; Kloczkowski, Andrzej

2011-06-01

Protein structures are evolutionarily more conserved than sequences, and sequences with very low sequence identity frequently share the same fold. This leads to the concept of protein designability. Some folds are more designable and lots of sequences can assume that fold. Elucidating the relationship between protein sequence and the three-dimensional (3D) structure that the sequence folds into is an important problem in computational structural biology. Lattice models have been utilized in numerous studies to model protein folds and predict the designability of certain folds. In this study, all possible compact conformations within a set of two-dimensional and 3D lattice spaces are explored. Complementary interaction graphs are then generated for each conformation and are described using a set of graph features. The full HP sequence space for each lattice model is generated and contact energies are calculated by threading each sequence onto all the possible conformations. Unique conformation giving minimum energy is identified for each sequence and the number of sequences folding to each conformation (designability) is obtained. Machine learning algorithms are used to predict the designability of each conformation. We find that the highly designable structures can be distinguished from other non-designable conformations based on certain graphical geometric features of the interactions. This finding confirms the fact that the topology of a conformation is an important determinant of the extent of its designability and suggests that the interactions themselves are important for determining the designability.

A photo-cleavable biotin affinity tag for the facile release of a photo-crosslinked carbohydrate-binding protein.

PubMed

Chang, Tsung-Che; Adak, Avijit K; Lin, Ting-Wei; Li, Pei-Jhen; Chen, Yi-Ju; Lai, Chain-Hui; Liang, Chien-Fu; Chen, Yu-Ju; Lin, Chun-Cheng

2016-03-15

The use of photo-crosslinking glycoprobes represents a powerful strategy for the covalent capture of labile protein complexes and allows detailed characterization of carbohydrate-mediated interactions. The selective release of target proteins from solid support is a key step in functional proteomics. We envisaged that light activation can be exploited for releasing labeled protein in a dual photo-affinity probe-based strategy. To investigate this possibility, we designed a trifunctional, galactose-based, multivalent glycoprobe for affinity labeling of carbohydrate-binding proteins. The resulting covalent protein-probe adduct is attached to a photo-cleavable biotin affinity tag; the biotin moiety enables specific presentation of the conjugate on streptavidin-coated beads, and the photolabile linker allows the release of the labeled proteins. This dual probe promotes both the labeling and the facile cleavage of the target protein complexes from the solid surfaces and the remainder of the cell lysate in a completely unaltered form, thus eliminating many of the common pitfalls associated with traditional affinity-based purification methods. Copyright © 2016 Elsevier Ltd. All rights reserved.

SeqRate: sequence-based protein folding type classification and rates prediction

PubMed Central

2010-01-01

Background Protein folding rate is an important property of a protein. Predicting protein folding rate is useful for understanding protein folding process and guiding protein design. Most previous methods of predicting protein folding rate require the tertiary structure of a protein as an input. And most methods do not distinguish the different kinetic nature (two-state folding or multi-state folding) of the proteins. Here we developed a method, SeqRate, to predict both protein folding kinetic type (two-state versus multi-state) and real-value folding rate using sequence length, amino acid composition, contact order, contact number, and secondary structure information predicted from only protein sequence with support vector machines. Results We systematically studied the contributions of individual features to folding rate prediction. On a standard benchmark dataset, the accuracy of folding kinetic type classification is 80%. The Pearson correlation coefficient and the mean absolute difference between predicted and experimental folding rates (sec-1) in the base-10 logarithmic scale are 0.81 and 0.79 for two-state protein folders, and 0.80 and 0.68 for three-state protein folders. SeqRate is the first sequence-based method for protein folding type classification and its accuracy of fold rate prediction is improved over previous sequence-based methods. Its performance can be further enhanced with additional information, such as structure-based geometric contacts, as inputs. Conclusions Both the web server and software of predicting folding rate are publicly available at http://casp.rnet.missouri.edu/fold_rate/index.html. PMID:20438647

Use of designed sequences in protein structure recognition.

PubMed

Kumar, Gayatri; Mudgal, Richa; Srinivasan, Narayanaswamy; Sandhya, Sankaran

2018-05-09

Knowledge of the protein structure is a pre-requisite for improved understanding of molecular function. The gap in the sequence-structure space has increased in the post-genomic era. Grouping related protein sequences into families can aid in narrowing the gap. In the Pfam database, structure description is provided for part or full-length proteins of 7726 families. For the remaining 52% of the families, information on 3-D structure is not yet available. We use the computationally designed sequences that are intermediately related to two protein domain families, which are already known to share the same fold. These strategically designed sequences enable detection of distant relationships and here, we have employed them for the purpose of structure recognition of protein families of yet unknown structure. We first measured the success rate of our approach using a dataset of protein families of known fold and achieved a success rate of 88%. Next, for 1392 families of yet unknown structure, we made structural assignments for part/full length of the proteins. Fold association for 423 domains of unknown function (DUFs) are provided as a step towards functional annotation. The results indicate that knowledge-based filling of gaps in protein sequence space is a lucrative approach for structure recognition. Such sequences assist in traversal through protein sequence space and effectively function as 'linkers', where natural linkers between distant proteins are unavailable. This article was reviewed by Oliviero Carugo, Christine Orengo and Srikrishna Subramanian.

SCPRED: accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences.

PubMed

Kurgan, Lukasz; Cios, Krzysztof; Chen, Ke

2008-05-01

Protein structure prediction methods provide accurate results when a homologous protein is predicted, while poorer predictions are obtained in the absence of homologous templates. However, some protein chains that share twilight-zone pairwise identity can form similar folds and thus determining structural similarity without the sequence similarity would be desirable for the structure prediction. The folding type of a protein or its domain is defined as the structural class. Current structural class prediction methods that predict the four structural classes defined in SCOP provide up to 63% accuracy for the datasets in which sequence identity of any pair of sequences belongs to the twilight-zone. We propose SCPRED method that improves prediction accuracy for sequences that share twilight-zone pairwise similarity with sequences used for the prediction. SCPRED uses a support vector machine classifier that takes several custom-designed features as its input to predict the structural classes. Based on extensive design that considers over 2300 index-, composition- and physicochemical properties-based features along with features based on the predicted secondary structure and content, the classifier's input includes 8 features based on information extracted from the secondary structure predicted with PSI-PRED and one feature computed from the sequence. Tests performed with datasets of 1673 protein chains, in which any pair of sequences shares twilight-zone similarity, show that SCPRED obtains 80.3% accuracy when predicting the four SCOP-defined structural classes, which is superior when compared with over a dozen recent competing methods that are based on support vector machine, logistic regression, and ensemble of classifiers predictors. The SCPRED can accurately find similar structures for sequences that share low identity with sequence used for the prediction. The high predictive accuracy achieved by SCPRED is attributed to the design of the features, which are capable of separating the structural classes in spite of their low dimensionality. We also demonstrate that the SCPRED's predictions can be successfully used as a post-processing filter to improve performance of modern fold classification methods.

SCPRED: Accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences

PubMed Central

Kurgan, Lukasz; Cios, Krzysztof; Chen, Ke

2008-01-01

Background Protein structure prediction methods provide accurate results when a homologous protein is predicted, while poorer predictions are obtained in the absence of homologous templates. However, some protein chains that share twilight-zone pairwise identity can form similar folds and thus determining structural similarity without the sequence similarity would be desirable for the structure prediction. The folding type of a protein or its domain is defined as the structural class. Current structural class prediction methods that predict the four structural classes defined in SCOP provide up to 63% accuracy for the datasets in which sequence identity of any pair of sequences belongs to the twilight-zone. We propose SCPRED method that improves prediction accuracy for sequences that share twilight-zone pairwise similarity with sequences used for the prediction. Results SCPRED uses a support vector machine classifier that takes several custom-designed features as its input to predict the structural classes. Based on extensive design that considers over 2300 index-, composition- and physicochemical properties-based features along with features based on the predicted secondary structure and content, the classifier's input includes 8 features based on information extracted from the secondary structure predicted with PSI-PRED and one feature computed from the sequence. Tests performed with datasets of 1673 protein chains, in which any pair of sequences shares twilight-zone similarity, show that SCPRED obtains 80.3% accuracy when predicting the four SCOP-defined structural classes, which is superior when compared with over a dozen recent competing methods that are based on support vector machine, logistic regression, and ensemble of classifiers predictors. Conclusion The SCPRED can accurately find similar structures for sequences that share low identity with sequence used for the prediction. The high predictive accuracy achieved by SCPRED is attributed to the design of the features, which are capable of separating the structural classes in spite of their low dimensionality. We also demonstrate that the SCPRED's predictions can be successfully used as a post-processing filter to improve performance of modern fold classification methods. PMID:18452616

High-level expression of a synthetic gene encoding a sweet protein, monellin, in Escherichia coli.

PubMed

Chen, Zhongjun; Cai, Heng; Lu, Fuping; Du, Lianxiang

2005-11-01

The expression of a synthetic gene encoding monellin, a sweet protein, in E. coli under the control of T7 promoter from phage is described. The single-chain monellin gene was designed based on the biased codons of E. coli so as to optimize its expression. Monellin was produced and accounted for 45% of total soluble proteins. It was purified to yield 43 mg protein per g dry cell wt. The purity of the recombinant protein was confirmed by SDS-PAGE.

Germanium Plasmon Enhanced Resonators for Label-Free Terahertz Protein Sensing

NASA Astrophysics Data System (ADS)

Bettenhausen, Maximilian; Römer, Friedhard; Witzigmann, Bernd; Flesch, Julia; Kurre, Rainer; Korneev, Sergej; Piehler, Jacob; You, Changjiang; Kazmierczak, Marcin; Guha, Subhajit; Capellini, Giovanni; Schröder, Thomas

2018-03-01

A Terahertz protein sensing concept based on subwavelength Ge resonators is presented. Ge bowtie resonators, compatible with CMOS fabrication technology, have been designed and characterized with a resonance frequency of 0.5 THz and calculated local intensity enhancement of 10.000. Selective biofunctionalization of Ge resonators on Si wafer was achieved in one step using lipoic acid-HaloTag ligand (LA-HTL) for biofunctionalization and passivation. The results lay the foundation for future investigation of protein tertiary structure and the dynamics of protein hydration shell in response to protein conformation changes.

Construction of a Chassis for a Tripartite Protein-Based Molecular Motor.

PubMed

Small, Lara S R; Bruning, Marc; Thomson, Andrew R; Boyle, Aimee L; Davies, Roberta B; Curmi, Paul M G; Forde, Nancy R; Linke, Heiner; Woolfson, Derek N; Bromley, Elizabeth H C

2017-06-16

Improving our understanding of biological motors, both to fully comprehend their activities in vital processes, and to exploit their impressive abilities for use in bionanotechnology, is highly desirable. One means of understanding these systems is through the production of synthetic molecular motors. We demonstrate the use of orthogonal coiled-coil dimers (including both parallel and antiparallel coiled coils) as a hub for linking other components of a previously described synthetic molecular motor, the Tumbleweed. We use circular dichroism, analytical ultracentrifugation, dynamic light scattering, and disulfide rearrangement studies to demonstrate the ability of this six-peptide set to form the structure designed for the Tumbleweed motor. The successful formation of a suitable hub structure is both a test of the transferability of design rules for protein folding as well as an important step in the production of a synthetic protein-based molecular motor.

Benchmark analysis of native and artificial NAD+-dependent enzymes generated by a sequence based design method with or without phylogenetic data.

PubMed

Nakano, Shogo; Motoyama, Tomoharu; Miyashita, Yurina; Ishizuka, Yuki; Matsuo, Naoya; Tokiwa, Hiroaki; Shinoda, Suguru; Asano, Yasuhisa; Ito, Sohei

2018-05-22

The expansion of protein sequence databases has enabled us to design artificial proteins by sequence-based design methods, such as full consensus design (FCD) and ancestral sequence reconstruction (ASR). Artificial proteins with enhanced activity levels compared with native ones can potentially be generated by such methods, but successful design is rare because preparing a sequence library by curating the database and selecting a method is difficult. Utilizing a curated library prepared by reducing conservation energies, we successfully designed two artificial L-threonine 3-dehydrogenase (SDR-TDH) with higher activity levels than native SDR-TDH, FcTDH-N1 and AncTDH, using FCD and ASR, respectively. The artificial SDR-TDHs had excellent thermal stability and NAD+ recognition compared to native SDR-TDH from Cupriavidus necator (CnTDH): the melting temperatures of FcTDH-N1 and AncTDH were about 10 and 5°C higher than CnTDH, respectively, and the dissociation constants toward NAD+ of FcTDH-N1 and AncTDH were two- and seven-fold lower than that of CnTDH, respectively. Enzymatic efficiency of the artificial SDR-TDHs were comparable to that of CnTDH. Crystal structures of FcTDH-N1 and AncTDH were determined at 2.8 and 2.1 Å resolution, respectively. Structural and MD simulation analysis of the SDR-TDHs indicated that only the flexibility at specific regions was changed, suggesting that multiple mutations introduced in the artificial SDR-TDHs altered their flexibility and thereby affected their enzymatic properties. Benchmark analysis of the SDR-TDHs indicated that both FCD and ASR can generate highly functional proteins if a curated library is prepared appropriately.

Predicting Silk Fiber Mechanical Properties through Multiscale Simulation and Protein Design.

PubMed

Rim, Nae-Gyune; Roberts, Erin G; Ebrahimi, Davoud; Dinjaski, Nina; Jacobsen, Matthew M; Martín-Moldes, Zaira; Buehler, Markus J; Kaplan, David L; Wong, Joyce Y

2017-08-14

Silk is a promising material for biomedical applications, and much research is focused on how application-specific, mechanical properties of silk can be designed synthetically through proper amino acid sequences and processing parameters. This protocol describes an iterative process between research disciplines that combines simulation, genetic synthesis, and fiber analysis to better design silk fibers with specific mechanical properties. Computational methods are used to assess the protein polymer structure as it forms an interconnected fiber network through shearing and how this process affects fiber mechanical properties. Model outcomes are validated experimentally with the genetic design of protein polymers that match the simulation structures, fiber fabrication from these polymers, and mechanical testing of these fibers. Through iterative feedback between computation, genetic synthesis, and fiber mechanical testing, this protocol will enable a priori prediction capability of recombinant material mechanical properties via insights from the resulting molecular architecture of the fiber network based entirely on the initial protein monomer composition. This style of protocol may be applied to other fields where a research team seeks to design a biomaterial with biomedical application-specific properties. This protocol highlights when and how the three research groups (simulation, synthesis, and engineering) should be interacting to arrive at the most effective method for predictive design of their material.

ProXL (Protein Cross-Linking Database): A Platform for Analysis, Visualization, and Sharing of Protein Cross-Linking Mass Spectrometry Data

PubMed Central

2016-01-01

ProXL is a Web application and accompanying database designed for sharing, visualizing, and analyzing bottom-up protein cross-linking mass spectrometry data with an emphasis on structural analysis and quality control. ProXL is designed to be independent of any particular software pipeline. The import process is simplified by the use of the ProXL XML data format, which shields developers of data importers from the relative complexity of the relational database schema. The database and Web interfaces function equally well for any software pipeline and allow data from disparate pipelines to be merged and contrasted. ProXL includes robust public and private data sharing capabilities, including a project-based interface designed to ensure security and facilitate collaboration among multiple researchers. ProXL provides multiple interactive and highly dynamic data visualizations that facilitate structural-based analysis of the observed cross-links as well as quality control. ProXL is open-source, well-documented, and freely available at https://github.com/yeastrc/proxl-web-app. PMID:27302480

ProXL (Protein Cross-Linking Database): A Platform for Analysis, Visualization, and Sharing of Protein Cross-Linking Mass Spectrometry Data.

PubMed

Riffle, Michael; Jaschob, Daniel; Zelter, Alex; Davis, Trisha N

2016-08-05

ProXL is a Web application and accompanying database designed for sharing, visualizing, and analyzing bottom-up protein cross-linking mass spectrometry data with an emphasis on structural analysis and quality control. ProXL is designed to be independent of any particular software pipeline. The import process is simplified by the use of the ProXL XML data format, which shields developers of data importers from the relative complexity of the relational database schema. The database and Web interfaces function equally well for any software pipeline and allow data from disparate pipelines to be merged and contrasted. ProXL includes robust public and private data sharing capabilities, including a project-based interface designed to ensure security and facilitate collaboration among multiple researchers. ProXL provides multiple interactive and highly dynamic data visualizations that facilitate structural-based analysis of the observed cross-links as well as quality control. ProXL is open-source, well-documented, and freely available at https://github.com/yeastrc/proxl-web-app .

FAST: a framework for simulation and analysis of large-scale protein-silicon biosensor circuits.

PubMed

Gu, Ming; Chakrabartty, Shantanu

2013-08-01

This paper presents a computer aided design (CAD) framework for verification and reliability analysis of protein-silicon hybrid circuits used in biosensors. It is envisioned that similar to integrated circuit (IC) CAD design tools, the proposed framework will be useful for system level optimization of biosensors and for discovery of new sensing modalities without resorting to laborious fabrication and experimental procedures. The framework referred to as FAST analyzes protein-based circuits by solving inverse problems involving stochastic functional elements that admit non-linear relationships between different circuit variables. In this regard, FAST uses a factor-graph netlist as a user interface and solving the inverse problem entails passing messages/signals between the internal nodes of the netlist. Stochastic analysis techniques like density evolution are used to understand the dynamics of the circuit and estimate the reliability of the solution. As an example, we present a complete design flow using FAST for synthesis, analysis and verification of our previously reported conductometric immunoassay that uses antibody-based circuits to implement forward error-correction (FEC).

Systems Biology of Recombinant Protein Production in Bacillus megaterium

NASA Astrophysics Data System (ADS)

Biedendieck, Rebekka; Bunk, Boyke; Fürch, Tobias; Franco-Lara, Ezequiel; Jahn, Martina; Jahn, Dieter

Over the last two decades the Gram-positive bacterium Bacillus megaterium was systematically developed to a useful alternative protein production host. Multiple vector systems for high yield intra- and extracellular protein production were constructed. Strong inducible promoters were combined with DNA sequences for optimised ribosome binding sites, various leader peptides for protein export and N- as well as C-terminal affinity tags for affinity chromatographic purification of the desired protein. High cell density cultivation and recombinant protein production were successfully tested. For further system biology based control and optimisation of the production process the genomes of two B. megaterium strains were completely elucidated, DNA arrays designed, proteome, fluxome and metabolome analyses performed and all data integrated using the bioinformatics platform MEGABAC. Now, solid theoretical and experimental bases for primary modeling attempts of the production process are available.

Generic framework for mining cellular automata models on protein-folding simulations.

PubMed

Diaz, N; Tischer, I

2016-05-13

Cellular automata model identification is an important way of building simplified simulation models. In this study, we describe a generic architectural framework to ease the development process of new metaheuristic-based algorithms for cellular automata model identification in protein-folding trajectories. Our framework was developed by a methodology based on design patterns that allow an improved experience for new algorithms development. The usefulness of the proposed framework is demonstrated by the implementation of four algorithms, able to obtain extremely precise cellular automata models of the protein-folding process with a protein contact map representation. Dynamic rules obtained by the proposed approach are discussed, and future use for the new tool is outlined.

Proteinaceous Resin and Hydrophilic Encapsulation: A Self-Healing-Related Study

NASA Astrophysics Data System (ADS)

Zheng, Ting

Inspired by living organisms, self-healing materials have been designed as smart materials. Their automatic healing nature is achieved through the use of capsule in which the healing agent is encapsulated. The occurrence of cracks leads to ripping of the capsule, along with crack propagation and release of the healing agent that wets the crack surface to eventually heal (bond) the crack. Such automatic repair of the crack significantly extends the service life of the material. A vast majority of existing self-healing systems have been designed for the epoxy matrix - the most common commercially used thermoset - that possesses low crack resistance. Currently, self-healing systems have not yet been introduced for fully protein-based materials, despite their great potential to replace currently used synthesis precursors for the latter and the eco-friendly nature of self-healing materials. This has been probably due to two major obstacles: poor mechanical properties of the protein-based matrix, and extreme difficulty associated with the encapsulation of hydrophilic healing agents suitable for the protein-based matrix. This study provides possible solutions towards addressing both these obstacles. To improve the inherent mechanical properties of protein-based resin, soy protein isolate (SPI) was chosen as the model in this study. Dialdehyde carboxymethyl cellulose (DCMC) was synthesized and used as the crosslinking agent to modify the SPI film. As-synthesized DCMC - a fully bio-based material - exhibited high mechanical strength, excellent thermal stability, and reduced moisture sensitivity. Good compatibility and effective crosslinking were believed to be the key reasons for such property enhancements. However, these were accompanied by poor crack resistance, where self-healing is a pertinent solution. A novel healing system for the protein matrix was designed in this work via the use of formaldehyde as a healing agent. Subsequently, the well-acknowledged challenge, e.g. hydrophilic agent encapsulation, was addressed through the development of novel polyurethane-Poly(melamine-formaldehyde) (PU-PMF) dual-component capsules. Remarkably, the external PU insulation layer was fabricated through interfacial polymerization based on a water-in-oil-in-oil (W/O/O) emulsion template. Surface tension was identified as the main driving factor for the formation of the external oil phase. The internal PMF layer was observed to strongly influence the internal morphology of the capsule. A protocol was developed, and a typical capsule with dense and neat shell morphology with a shell/capsule diameter (around 3 %) was fabricated. This study provides solutions for the two aforementioned obstacles related to the development of the healing system for the protein-based materials.

Dissecting fragment-based lead discovery at the von Hippel-Lindau protein:hypoxia inducible factor 1α protein-protein interface.

PubMed

Van Molle, Inge; Thomann, Andreas; Buckley, Dennis L; So, Ernest C; Lang, Steffen; Crews, Craig M; Ciulli, Alessio

2012-10-26

Fragment screening is widely used to identify attractive starting points for drug design. However, its potential and limitations to assess the tractability of often challenging protein:protein interfaces have been underexplored. Here, we address this question by means of a systematic deconstruction of lead-like inhibitors of the pVHL:HIF-1α interaction into their component fragments. Using biophysical techniques commonly employed for screening, we could only detect binding of fragments that violate the Rule of Three, are more complex than those typically screened against classical druggable targets, and occupy two adjacent binding subsites at the interface rather than just one. Analyses based on ligand and group lipophilicity efficiency of anchored fragments were applied to dissect the individual subsites and probe for binding hot spots. The implications of our findings for targeting protein interfaces by fragment-based approaches are discussed. Copyright © 2012 Elsevier Ltd. All rights reserved.

Recent advances in recombinant protein-based malaria vaccines.

PubMed

Draper, Simon J; Angov, Evelina; Horii, Toshihiro; Miller, Louis H; Srinivasan, Prakash; Theisen, Michael; Biswas, Sumi

2015-12-22

Plasmodium parasites are the causative agent of human malaria, and the development of a highly effective vaccine against infection, disease and transmission remains a key priority. It is widely established that multiple stages of the parasite's complex lifecycle within the human host and mosquito vector are susceptible to vaccine-induced antibodies. The mainstay approach to antibody induction by subunit vaccination has been the delivery of protein antigen formulated in adjuvant. Extensive efforts have been made in this endeavor with respect to malaria vaccine development, especially with regard to target antigen discovery, protein expression platforms, adjuvant testing, and development of soluble and virus-like particle (VLP) delivery platforms. The breadth of approaches to protein-based vaccines is continuing to expand as innovative new concepts in next-generation subunit design are explored, with the prospects for the development of a highly effective multi-component/multi-stage/multi-antigen formulation seeming ever more likely. This review will focus on recent progress in protein vaccine design, development and/or clinical testing for a number of leading malaria antigens from the sporozoite-, merozoite- and sexual-stages of the parasite's lifecycle-including PfCelTOS, PfMSP1, PfAMA1, PfRH5, PfSERA5, PfGLURP, PfMSP3, Pfs48/45 and Pfs25. Future prospects and challenges for the development, production, human delivery and assessment of protein-based malaria vaccines are discussed. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Exploring the Molecular Design of Protein Interaction Sites with Molecular Dynamics Simulations and Free Energy Calculations†

PubMed Central

Liang, Shide; Li, Liwei; Hsu, Wei-Lun; Pilcher, Meaghan N.; Uversky, Vladimir; Zhou, Yaoqi; Dunker, A. Keith; Meroueh, Samy O.

2009-01-01

The significant work that has been invested toward understanding protein–protein interaction has not translated into significant advances in structure-based predictions. In particular redesigning protein surfaces to bind to unrelated receptors remains a challenge, partly due to receptor flexibility, which is often neglected in these efforts. In this work, we computationally graft the binding epitope of various small proteins obtained from the RCSB database to bind to barnase, lysozyme, and trypsin using a previously derived and validated algorithm. In an effort to probe the protein complexes in a realistic environment, all native and designer complexes were subjected to a total of nearly 400 ns of explicit-solvent molecular dynamics (MD) simulation. The MD data led to an unexpected observation: some of the designer complexes were highly unstable and decomposed during the trajectories. In contrast, the native and a number of designer complexes remained consistently stable. The unstable conformers provided us with a unique opportunity to define the structural and energetic factors that lead to unproductive protein–protein complexes. To that end we used free energy calculations following the MM-PBSA approach to determine the role of nonpolar effects, electrostatics and entropy in binding. Remarkably, we found that a majority of unstable complexes exhibited more favorable electrostatics than native or stable designer complexes, suggesting that favorable electrostatic interactions are not prerequisite for complex formation between proteins. However, nonpolar effects remained consistently more favorable in native and stable designer complexes reinforcing the importance of hydrophobic effects in protein–protein binding. While entropy systematically opposed binding in all cases, there was no observed trend in the entropy difference between native and designer complexes. A series of alanine scanning mutations of hot-spot residues at the interface of native and designer complexes showed less than optimal contacts of hot-spot residues with their surroundings in the unstable conformers, resulting in more favorable entropy for these complexes. Finally, disorder predictions revealed that secondary structures at the interface of unstable complexes exhibited greater disorder than the stable complexes. PMID:19113835

Protein-like Nanoparticles Based on Orthogonal Self-Assembly of Chimeric Peptides.

PubMed

Jiang, Linhai; Xu, Dawei; Namitz, Kevin E; Cosgrove, Michael S; Lund, Reidar; Dong, He

2016-10-01

A novel two-component self-assembling chimeric peptide is designed where two orthogonal protein folding motifs are linked side by side with precisely defined position relative to one another. The self-assembly is driven by a combination of symmetry controlled molecular packing, intermolecular interactions, and geometric constraint to limit the assembly into compact dodecameric protein nanoparticles. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Protein-based flexible whispering gallery mode resonators

NASA Astrophysics Data System (ADS)

Yilmaz, Huzeyfe; Pena-Francesch, Abdon; Xu, Linhua; Shreiner, Robert; Jung, Huihun; Huang, Steven H.; Özdemir, Sahin K.; Demirel, Melik C.; Yang, Lan

2016-02-01

The idea of creating photonics tools for sensing, imaging and material characterization has long been pursued and many achievements have been made. Approaching the level of solutions provided by nature however is hindered by routine choice of materials. To this end recent years have witnessed a great effort to engineer mechanically flexible photonic devices using polymer substrates. On the other hand, biodegradability and biocompatibility still remains to be incorporated. Hence biomimetics holds the key to overcome the limitations of traditional materials in photonics design. Natural proteins such as sucker ring teeth (SRT) and silk for instance have remarkable mechanical and optical properties that exceed the endeavors of most synthetic and natural polymers. Here we demonstrate for the first time, toroidal whispering gallery mode resonators (WGMR) fabricated entirely from protein structures such as SRT of Loligo vulgaris (European squid) and silk from Bombyx mori. We provide here complete optical and material characterization of proteinaceous WGMRs, revealing high quality factors in microscale and enhancement of Raman signatures by a microcavity. We also present a most simple application of a WGMR as a natural protein add-drop filter, made of SRT protein. Our work shows that with protein-based materials, optical, mechanical and thermal properties can be devised at the molecular level and it lays the groundwork for future eco-friendly, flexible photonics device design.

Synthetic (polymer) biology (membrane): functionalization of polymer scaffolds for membrane proteins.

PubMed

Hu, Zhaolong; Ho, James C S; Nallani, Madhavan

2017-08-01

A plethora of polymer-based scaffolds have been designed to facilitate biochemical and biophysical investigation of membrane proteins, with a common goal to stabilize and present them in a functional format. In this review, an up-to-date account of such polymer-based supports and incorporation methodologies are presented. Furthermore, conceptual and imminent technological advances, with associated technical challenges are proposed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Directed evolution of the TALE N-terminal domain for recognition of all 5′ bases

PubMed Central

Lamb, Brian M.; Mercer, Andrew C.; Barbas, Carlos F.

2013-01-01

Transcription activator-like effector (TALE) proteins can be designed to bind virtually any DNA sequence. General guidelines for design of TALE DNA-binding domains suggest that the 5′-most base of the DNA sequence bound by the TALE (the N0 base) should be a thymine. We quantified the N0 requirement by analysis of the activities of TALE transcription factors (TALE-TF), TALE recombinases (TALE-R) and TALE nucleases (TALENs) with each DNA base at this position. In the absence of a 5′ T, we observed decreases in TALE activity up to >1000-fold in TALE-TF activity, up to 100-fold in TALE-R activity and up to 10-fold reduction in TALEN activity compared with target sequences containing a 5′ T. To develop TALE architectures that recognize all possible N0 bases, we used structure-guided library design coupled with TALE-R activity selections to evolve novel TALE N-terminal domains to accommodate any N0 base. A G-selective domain and broadly reactive domains were isolated and characterized. The engineered TALE domains selected in the TALE-R format demonstrated modularity and were active in TALE-TF and TALEN architectures. Evolved N-terminal domains provide effective and unconstrained TALE-based targeting of any DNA sequence as TALE binding proteins and designer enzymes. PMID:23980031

Physical and molecular bases of protein thermal stability and cold adaptation.

PubMed

Pucci, Fabrizio; Rooman, Marianne

2017-02-01

The molecular bases of thermal and cold stability and adaptation, which allow proteins to remain folded and functional in the temperature ranges in which their host organisms live and grow, are still only partially elucidated. Indeed, both experimental and computational studies fail to yield a fully precise and global physical picture, essentially because all effects are context-dependent and thus quite intricate to unravel. We present a snapshot of the current state of knowledge of this highly complex and challenging issue, whose resolution would enable large-scale rational protein design. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cost Function Network-based Design of Protein-Protein Interactions: predicting changes in binding affinity.

PubMed

Viricel, Clément; de Givry, Simon; Schiex, Thomas; Barbe, Sophie

2018-02-20

Accurate and economic methods to predict change in protein binding free energy upon mutation are imperative to accelerate the design of proteins for a wide range of applications. Free energy is defined by enthalpic and entropic contributions. Following the recent progresses of Artificial Intelligence-based algorithms for guaranteed NP-hard energy optimization and partition function computation, it becomes possible to quickly compute minimum energy conformations and to reliably estimate the entropic contribution of side-chains in the change of free energy of large protein interfaces. Using guaranteed Cost Function Network algorithms, Rosetta energy functions and Dunbrack's rotamer library, we developed and assessed EasyE and JayZ, two methods for binding affinity estimation that ignore or include conformational entropic contributions on a large benchmark of binding affinity experimental measures. If both approaches outperform most established tools, we observe that side-chain conformational entropy brings little or no improvement on most systems but becomes crucial in some rare cases. as open-source Python/C ++ code at sourcesup.renater.fr/projects/easy-jayz. thomas.schiex@inra.fr and sophie.barbe@insa-toulouse.fr. Supplementary data are available at Bioinformatics online.

Comparing Proteolytic Fingerprints of Antigen-Presenting Cells during Allergen Processing.

PubMed

Hofer, Heidi; Weidinger, Tamara; Briza, Peter; Asam, Claudia; Wolf, Martin; Twaroch, Teresa E; Stolz, Frank; Neubauer, Angela; Dall, Elfriede; Hammerl, Peter; Jacquet, Alain; Wallner, Michael

2017-06-08

Endolysosomal processing has a critical influence on immunogenicity as well as immune polarization of protein antigens. In industrialized countries, allergies affect around 25% of the population. For the rational design of protein-based allergy therapeutics for immunotherapy, a good knowledge of T cell-reactive regions on allergens is required. Thus, we sought to analyze endolysosomal degradation patterns of inhalant allergens. Four major allergens from ragweed, birch, as well as house dust mites were produced as recombinant proteins. Endolysosomal proteases were purified by differential centrifugation from dendritic cells, macrophages, and B cells, and combined with allergens for proteolytic processing. Thereafter, endolysosomal proteolysis was monitored by protein gel electrophoresis and mass spectrometry. We found that the overall proteolytic activity of specific endolysosomal fractions differed substantially, whereas the degradation patterns of the four model allergens obtained with the different proteases were extremely similar. Moreover, previously identified T cell epitopes were assigned to endolysosomal peptides and indeed showed a good overlap with known T cell epitopes for all four candidate allergens. Thus, we propose that the degradome assay can be used as a predictor to determine antigenic peptides as potential T cell epitopes, which will help in the rational design of protein-based allergy vaccine candidates.

Comparing Proteolytic Fingerprints of Antigen-Presenting Cells during Allergen Processing

PubMed Central

Hofer, Heidi; Weidinger, Tamara; Briza, Peter; Asam, Claudia; Wolf, Martin; Twaroch, Teresa E.; Stolz, Frank; Neubauer, Angela; Dall, Elfriede; Hammerl, Peter; Jacquet, Alain; Wallner, Michael

2017-01-01

Endolysosomal processing has a critical influence on immunogenicity as well as immune polarization of protein antigens. In industrialized countries, allergies affect around 25% of the population. For the rational design of protein-based allergy therapeutics for immunotherapy, a good knowledge of T cell-reactive regions on allergens is required. Thus, we sought to analyze endolysosomal degradation patterns of inhalant allergens. Four major allergens from ragweed, birch, as well as house dust mites were produced as recombinant proteins. Endolysosomal proteases were purified by differential centrifugation from dendritic cells, macrophages, and B cells, and combined with allergens for proteolytic processing. Thereafter, endolysosomal proteolysis was monitored by protein gel electrophoresis and mass spectrometry. We found that the overall proteolytic activity of specific endolysosomal fractions differed substantially, whereas the degradation patterns of the four model allergens obtained with the different proteases were extremely similar. Moreover, previously identified T cell epitopes were assigned to endolysosomal peptides and indeed showed a good overlap with known T cell epitopes for all four candidate allergens. Thus, we propose that the degradome assay can be used as a predictor to determine antigenic peptides as potential T cell epitopes, which will help in the rational design of protein-based allergy vaccine candidates. PMID:28594355

Recent progress in biopolymer nanoparticle and microparticle formation by heat-treating electrostatic protein-polysaccharide complexes.

PubMed

Jones, Owen G; McClements, David Julian

2011-09-14

Functional biopolymer nanoparticles or microparticles can be formed by heat treatment of globular protein-ionic polysaccharide electrostatic complexes under appropriate solution conditions. These biopolymer particles can be used as encapsulation and delivery systems, fat mimetics, lightening agents, or texture modifiers. This review highlights recent progress in the design and fabrication of biopolymer particles based on heating globular protein-ionic polysaccharide complexes above the thermal denaturation temperature of the proteins. The influence of biopolymer type, protein-polysaccharide ratio, pH, ionic strength, and thermal history on the characteristics of the biopolymer particles formed is reviewed. Our current understanding of the underlying physicochemical mechanisms of particle formation and properties is given. The information provided in this review should facilitate the rational design of biopolymer particles with specific physicochemical and functional attributes, as well as stimulate further research in identifying the physicochemical origin of particle formation. Copyright © 2010 Elsevier B.V. All rights reserved.

G‐LoSA: An efficient computational tool for local structure‐centric biological studies and drug design

PubMed Central

2016-01-01

Abstract Molecular recognition by protein mostly occurs in a local region on the protein surface. Thus, an efficient computational method for accurate characterization of protein local structural conservation is necessary to better understand biology and drug design. We present a novel local structure alignment tool, G‐LoSA. G‐LoSA aligns protein local structures in a sequence order independent way and provides a GA‐score, a chemical feature‐based and size‐independent structure similarity score. Our benchmark validation shows the robust performance of G‐LoSA to the local structures of diverse sizes and characteristics, demonstrating its universal applicability to local structure‐centric comparative biology studies. In particular, G‐LoSA is highly effective in detecting conserved local regions on the entire surface of a given protein. In addition, the applications of G‐LoSA to identifying template ligands and predicting ligand and protein binding sites illustrate its strong potential for computer‐aided drug design. We hope that G‐LoSA can be a useful computational method for exploring interesting biological problems through large‐scale comparison of protein local structures and facilitating drug discovery research and development. G‐LoSA is freely available to academic users at http://im.compbio.ku.edu/GLoSA/. PMID:26813336

Dramatic secretion of recombinant protein expressed in tobacco cells with a designer glycopeptide tag is highly impacted by medium composition.

PubMed

Zhang, Ningning; Dolan, Maureen; Wu, Di; Phillips, Gregory C; Xu, Jianfeng

2016-12-01

Cell growth medium composition has profound impacts on the O -glycosylation of a "designer" arabinogalactan protein-based module; full glycosylation is essential in directing efficient extracellular secretion of the tagged recombinant protein. Expression of recombinant proteins in plant cells as fusion with a de novo designed hydroxyproline (Hyp)-O-glycosylated peptide (HypGP) tag, termed HypGP engineering technology, resulted in dramatically increased secreted protein yields. This is due to the function of the HypGP tag as a molecular carrier in promoting efficient transport of conjoined proteins into culture media. To optimize the cell culture to achieve the best secreted protein yields, the medium effects on the cell growth and protein secretion were investigated using as a model system the tobacco BY-2 cell expressing enhanced green fluorescence protein (EGFP) fused with a (SP) 32 tag (32 tandem repeats of "Ser-Pro" motif). The (SP) 32 tag was found to undergo two-stage Hyp-O-glycosylation in plant cells with the dramatic secretion of the conjoined EGFP correlating with the triggering of the second-stage glycosylation. The BY-2 cell culture in SH medium generated a high secreted protein yield (125 mg/L) with a low cell biomass accumulation (~7.5 gDW/L). In contrast, very low secreted protein yields (~1.5 mg/L) with a high cell biomass accumulation (13.5 gDW/L) were obtained in MS medium. The macronutrients, specifically, the nitrogen supply greatly impacted the glycosylation of the (SP) 32 tag and subsequent protein secretion. Modified MS medium with reduced nitrogen levels boosted the secreted EGFP yields to 168 mg/L. This study demonstrates the profound impacts of medium composition on the secreted yields of a HypGP-tagged protein, and provides a basis for medium design to achieve the highest productivity of the HypGP engineering technology.

Complementarity of stability patches at the interfaces of protein complexes: Implication for the structural organization of energetic hot spots.

PubMed

Kuttner, Yosef Y; Engel, Stanislav

2018-02-01

A rational design of protein complexes with defined functionalities and of drugs aimed at disrupting protein-protein interactions requires fundamental understanding of the mechanisms underlying the formation of specific protein complexes. Efforts to develop efficient small-molecule or protein-based binders often exploit energetic hot spots on protein surfaces, namely, the interfacial residues that provide most of the binding free energy in the complex. The molecular basis underlying the unusually high energy contribution of the hot spots remains obscure, and its elucidation would facilitate the design of interface-targeted drugs. To study the nature of the energetic hot spots, we analyzed the backbone dynamic properties of contact surfaces in several protein complexes. We demonstrate that, in most complexes, the backbone dynamic landscapes of interacting surfaces form complementary "stability patches," in which static areas from the opposing surfaces superimpose, and that these areas are predominantly located near the geometric center of the interface. We propose that a diminished enthalpy-entropy compensation effect augments the degree to which residues positioned within the complementary stability patches contribute to complex affinity, thereby giving rise to the energetic hot spots. These findings offer new insights into the nature of energetic hot spots and the role that backbone dynamics play in facilitating intermolecular recognition. Mapping the interfacial stability patches may provide guidance for protein engineering approaches aimed at improving the stability of protein complexes and could facilitate the design of ligands that target complex interfaces. © 2017 Wiley Periodicals, Inc.

Robust enzyme design: bioinformatic tools for improved protein stability.

PubMed

Suplatov, Dmitry; Voevodin, Vladimir; Švedas, Vytas

2015-03-01

The ability of proteins and enzymes to maintain a functionally active conformation under adverse environmental conditions is an important feature of biocatalysts, vaccines, and biopharmaceutical proteins. From an evolutionary perspective, robust stability of proteins improves their biological fitness and allows for further optimization. Viewed from an industrial perspective, enzyme stability is crucial for the practical application of enzymes under the required reaction conditions. In this review, we analyze bioinformatic-driven strategies that are used to predict structural changes that can be applied to wild type proteins in order to produce more stable variants. The most commonly employed techniques can be classified into stochastic approaches, empirical or systematic rational design strategies, and design of chimeric proteins. We conclude that bioinformatic analysis can be efficiently used to study large protein superfamilies systematically as well as to predict particular structural changes which increase enzyme stability. Evolution has created a diversity of protein properties that are encoded in genomic sequences and structural data. Bioinformatics has the power to uncover this evolutionary code and provide a reproducible selection of hotspots - key residues to be mutated in order to produce more stable and functionally diverse proteins and enzymes. Further development of systematic bioinformatic procedures is needed to organize and analyze sequences and structures of proteins within large superfamilies and to link them to function, as well as to provide knowledge-based predictions for experimental evaluation. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Enabling Large-Scale Design, Synthesis and Validation of Small Molecule Protein-Protein Antagonists

PubMed Central

Koes, David; Khoury, Kareem; Huang, Yijun; Wang, Wei; Bista, Michal; Popowicz, Grzegorz M.; Wolf, Siglinde; Holak, Tad A.; Dömling, Alexander; Camacho, Carlos J.

2012-01-01

Although there is no shortage of potential drug targets, there are only a handful known low-molecular-weight inhibitors of protein-protein interactions (PPIs). One problem is that current efforts are dominated by low-yield high-throughput screening, whose rigid framework is not suitable for the diverse chemotypes present in PPIs. Here, we developed a novel pharmacophore-based interactive screening technology that builds on the role anchor residues, or deeply buried hot spots, have in PPIs, and redesigns these entry points with anchor-biased virtual multicomponent reactions, delivering tens of millions of readily synthesizable novel compounds. Application of this approach to the MDM2/p53 cancer target led to high hit rates, resulting in a large and diverse set of confirmed inhibitors, and co-crystal structures validate the designed compounds. Our unique open-access technology promises to expand chemical space and the exploration of the human interactome by leveraging in-house small-scale assays and user-friendly chemistry to rationally design ligands for PPIs with known structure. PMID:22427896

Near-infrared fluorescence probes for enzymes based on binding affinity modulation of squarylium dye scaffold.

PubMed

Oushiki, Daihi; Kojima, Hirotatsu; Takahashi, Yuki; Komatsu, Toru; Terai, Takuya; Hanaoka, Kenjiro; Nishikawa, Makiya; Takakura, Yoshinobu; Nagano, Tetsuo

2012-05-15

We present a novel design strategy for near-infrared (NIR) fluorescence probes utilizing dye-protein interaction as a trigger for fluorescence enhancement. The design principle involves modification of a polymethine dye with cleavable functional groups that reduce the dye's protein-binding affinity. When these functional groups are removed by specific interaction with the target enzymes, the dye's protein affinity is restored, protein binding occurs, and the dye's fluorescence is strongly enhanced. To validate this strategy, we first designed and synthesized an alkaline phosphatase (ALP) sensor by introducing phosphate into the squarylium dye scaffold; this sensor was able to detect ALP-labeled secondary antibodies in Western blotting analysis. Second, we synthesized a probe for β-galactosidase (widely used as a reporter of gene expression) by means of β-galactosyl substitution of the squarylium scaffold; this sensor was able to visualize β-galactosidase activity both in vitro and in vivo. Our strategy should be applicable to obtain NIR fluorescence probes for a wide range of target enzymes.

Integrating linear optimization with structural modeling to increase HIV neutralization breadth.

PubMed

Sevy, Alexander M; Panda, Swetasudha; Crowe, James E; Meiler, Jens; Vorobeychik, Yevgeniy

2018-02-01

Computational protein design has been successful in modeling fixed backbone proteins in a single conformation. However, when modeling large ensembles of flexible proteins, current methods in protein design have been insufficient. Large barriers in the energy landscape are difficult to traverse while redesigning a protein sequence, and as a result current design methods only sample a fraction of available sequence space. We propose a new computational approach that combines traditional structure-based modeling using the Rosetta software suite with machine learning and integer linear programming to overcome limitations in the Rosetta sampling methods. We demonstrate the effectiveness of this method, which we call BROAD, by benchmarking the performance on increasing predicted breadth of anti-HIV antibodies. We use this novel method to increase predicted breadth of naturally-occurring antibody VRC23 against a panel of 180 divergent HIV viral strains and achieve 100% predicted binding against the panel. In addition, we compare the performance of this method to state-of-the-art multistate design in Rosetta and show that we can outperform the existing method significantly. We further demonstrate that sequences recovered by this method recover known binding motifs of broadly neutralizing anti-HIV antibodies. Finally, our approach is general and can be extended easily to other protein systems. Although our modeled antibodies were not tested in vitro, we predict that these variants would have greatly increased breadth compared to the wild-type antibody.

Initial investigation of dietitian perception of plant-based protein quality.

PubMed

Hughes, Glenna J; Kress, Kathleen S; Armbrecht, Eric S; Mukherjea, Ratna; Mattfeldt-Beman, Mildred

2014-07-01

Interest in plant-based diets is increasing, evidenced by scientific and regulatory recommendations, including Dietary Guidelines for Americans. Dietitians provide guidance in dietary protein selection but little is known about how familiar dietitians are with the quality of plant versus animal proteins or methods for measuring protein quality. Likewise, there is a need to explore their beliefs related to dietary recommendations. The aim of this study was to assess dietitians' perceptions of plant-based protein quality and to determine if these are affected by demographic factors such as age and dietary practice group (DPG) membership. This was a cross-sectional design using an online survey. The survey was sent to all members of the Missouri Dietetic Association. All completed surveys (136) were analyzed. The main outcome measures were responses to belief and knowledge questions about the protein quality of plant-based diets, along with demographic information including age and DPG membership. Descriptive statistics and frequencies were determined, and chi-square analysis was used to determine the associations between belief and knowledge responses and demographic characteristics. Responses to belief statements suggested a high level of support for plant-based diets. No associations were found between any of the belief questions and demographic factors. A majority of respondents were not familiar with protein quality determination methods that are currently recognized by global regulatory and advisory agencies. Potential barriers identified in shifting to a more plant-based diet were lack of interest and perceived difficulty. Knowledge among dietitians of plant-based protein quality in general, and methods of protein quality measurement more specifically, needs to be addressed to enhance their knowledge base for making dietary protein recommendations. Two potential avenues for training are university curricula and continuing education opportunities provided to practitioners who provide dietary advice.

Improving Classification of Protein Interaction Articles Using Context Similarity-Based Feature Selection.

PubMed

Chen, Yifei; Sun, Yuxing; Han, Bing-Qing

2015-01-01

Protein interaction article classification is a text classification task in the biological domain to determine which articles describe protein-protein interactions. Since the feature space in text classification is high-dimensional, feature selection is widely used for reducing the dimensionality of features to speed up computation without sacrificing classification performance. Many existing feature selection methods are based on the statistical measure of document frequency and term frequency. One potential drawback of these methods is that they treat features separately. Hence, first we design a similarity measure between the context information to take word cooccurrences and phrase chunks around the features into account. Then we introduce the similarity of context information to the importance measure of the features to substitute the document and term frequency. Hence we propose new context similarity-based feature selection methods. Their performance is evaluated on two protein interaction article collections and compared against the frequency-based methods. The experimental results reveal that the context similarity-based methods perform better in terms of the F1 measure and the dimension reduction rate. Benefiting from the context information surrounding the features, the proposed methods can select distinctive features effectively for protein interaction article classification.

A quantitative framework for the forward design of synthetic miRNA circuits.

PubMed

Bloom, Ryan J; Winkler, Sally M; Smolke, Christina D

2014-11-01

Synthetic genetic circuits incorporating regulatory components based on RNA interference (RNAi) have been used in a variety of systems. A comprehensive understanding of the parameters that determine the relationship between microRNA (miRNA) and target expression levels is lacking. We describe a quantitative framework supporting the forward engineering of gene circuits that incorporate RNAi-based regulatory components in mammalian cells. We developed a model that captures the quantitative relationship between miRNA and target gene expression levels as a function of parameters, including mRNA half-life and miRNA target-site number. We extended the model to synthetic circuits that incorporate protein-responsive miRNA switches and designed an optimized miRNA-based protein concentration detector circuit that noninvasively measures small changes in the nuclear concentration of β-catenin owing to induction of the Wnt signaling pathway. Our results highlight the importance of methods for guiding the quantitative design of genetic circuits to achieve robust, reliable and predictable behaviors in mammalian cells.

Architectural Insight into Inovirus-Associated Vectors (IAVs) and Development of IAV-Based Vaccines Inducing Humoral and Cellular Responses: Implications in HIV-1 Vaccines

PubMed Central

Hassapis, Kyriakos A.; Stylianou, Dora C.; Kostrikis, Leondios G.

2014-01-01

Inovirus-associated vectors (IAVs) are engineered, non-lytic, filamentous bacteriophages that are assembled primarily from thousands of copies of the major coat protein gp8 and just five copies of each of the four minor coat proteins gp3, gp6, gp7 and gp9. Inovirus display studies have shown that the architecture of inoviruses makes all coat proteins of the inoviral particle accessible to the outside. This particular feature of IAVs allows foreign antigenic peptides to be displayed on the outer surface of the virion fused to its coat proteins and for more than two decades has been exploited in many applications including antibody or peptide display libraries, drug design, and vaccine development against infectious and non-infectious diseases. As vaccine carriers, IAVs have been shown to elicit both a cellular and humoral response against various pathogens through the display of antibody epitopes on their coat proteins. Despite their high immunogenicity, the goal of developing an effective vaccine against HIV-1 has not yet materialized. One possible limitation of previous efforts was the use of broadly neutralizing antibodies, which exhibited autoreactivity properties. In the past five years, however, new, more potent broadly neutralizing antibodies that do not exhibit autoreactivity properties have been isolated from HIV-1 infected individuals, suggesting that vaccination strategies aimed at producing such broadly neutralizing antibodies may confer protection against infection. The utilization of these new, broadly neutralizing antibodies in combination with the architectural traits of IAVs have driven the current developments in the design of an inovirus-based vaccine against HIV-1. This article reviews the applications of IAVs in vaccine development, with particular emphasis on the design of inoviral-based vaccines against HIV-1. PMID:25525909

Architectural insight into inovirus-associated vectors (IAVs) and development of IAV-based vaccines inducing humoral and cellular responses: implications in HIV-1 vaccines.

PubMed

Hassapis, Kyriakos A; Stylianou, Dora C; Kostrikis, Leondios G

2014-12-17

Inovirus-associated vectors (IAVs) are engineered, non-lytic, filamentous bacteriophages that are assembled primarily from thousands of copies of the major coat protein gp8 and just five copies of each of the four minor coat proteins gp3, gp6, gp7 and gp9. Inovirus display studies have shown that the architecture of inoviruses makes all coat proteins of the inoviral particle accessible to the outside. This particular feature of IAVs allows foreign antigenic peptides to be displayed on the outer surface of the virion fused to its coat proteins and for more than two decades has been exploited in many applications including antibody or peptide display libraries, drug design, and vaccine development against infectious and non-infectious diseases. As vaccine carriers, IAVs have been shown to elicit both a cellular and humoral response against various pathogens through the display of antibody epitopes on their coat proteins. Despite their high immunogenicity, the goal of developing an effective vaccine against HIV-1 has not yet materialized. One possible limitation of previous efforts was the use of broadly neutralizing antibodies, which exhibited autoreactivity properties. In the past five years, however, new, more potent broadly neutralizing antibodies that do not exhibit autoreactivity properties have been isolated from HIV-1 infected individuals, suggesting that vaccination strategies aimed at producing such broadly neutralizing antibodies may confer protection against infection. The utilization of these new, broadly neutralizing antibodies in combination with the architectural traits of IAVs have driven the current developments in the design of an inovirus-based vaccine against HIV-1. This article reviews the applications of IAVs in vaccine development, with particular emphasis on the design of inoviral-based vaccines against HIV-1.

Dynamics Govern Specificity of a Protein-Protein Interface: Substrate Recognition by Thrombin.

PubMed

Fuchs, Julian E; Huber, Roland G; Waldner, Birgit J; Kahler, Ursula; von Grafenstein, Susanne; Kramer, Christian; Liedl, Klaus R

2015-01-01

Biomolecular recognition is crucial in cellular signal transduction. Signaling is mediated through molecular interactions at protein-protein interfaces. Still, specificity and promiscuity of protein-protein interfaces cannot be explained using simplistic static binding models. Our study rationalizes specificity of the prototypic protein-protein interface between thrombin and its peptide substrates relying solely on binding site dynamics derived from molecular dynamics simulations. We find conformational selection and thus dynamic contributions to be a key player in biomolecular recognition. Arising entropic contributions complement chemical intuition primarily reflecting enthalpic interaction patterns. The paradigm "dynamics govern specificity" might provide direct guidance for the identification of specific anchor points in biomolecular recognition processes and structure-based drug design.

Prevention of IcaA regulated poly N-acetyl glucosamine formation in Staphylococcus aureus biofilm through new-drug like inhibitors: In silico approach and MD simulation study.

PubMed

Gupta, Ayushi; Mishra, Swechha; Singh, Sangeeta; Mishra, Sonali

2017-09-01

The effectiveness of various ligands against the protein structure of IcaA of the IcaABCD gene locus of Staphylococcus aureus were examined using the approach of structure based drug designing in reference with the protein's efficiency to form biofilms. Four compounds CID42738592, CID90468752, CID24277882, and CID6435208 were secluded from a database of 31,242 inhibitory ligands on the justification of the evaluated values falling under the four - tier structure based virtual screening. Under this principle value of least binding energy, human oral absorption and ADME properties were taken into consideration. Using the Glide module of Schrödinger, the above mentioned ligands showed an effective action against the protein IcaA which showed reduced activity as a glucosaminyl transferase. The complex of protein and ligand with best docking score was chosen for simulation studies. Structure based drug designing for the protein IcaA has given us potential leads as anti - biofilm agents. These screened out ligands might enable the development of new therapeutic strategies aimed at disrupting Staphylococcus aureus biofilms. The complex was showing stability towards the end of time for which it has been put for simulation. Thus molecule could be considered for making of biofilms. Copyright © 2017 Elsevier Ltd. All rights reserved.

Trends in the Design and Development of Specific Aptamers Against Peptides and Proteins.

PubMed

Tabarzad, Maryam; Jafari, Marzieh

2016-04-01

Aptamers are single stranded oligonucleotides, comparable to monoclonal antibodies (mAbs) in selectivity and affinity and have significant strategic properties in design, development and applications more than mAbs. Ease of design and development, simple chemical modification and the attachment of functional groups, easily handling and more adaptability with analytical methods, small size and adaptation with nanostructures are the valuable characteristics of aptamers in comparison to large protein based ligands. Among a broad range of targets that their specific aptamers developed, proteins and peptides have significant position according to the number of related studies performed so far. Since proteins control many of important physiological and pathological incidents in the living organisms, particularly human beings and because of the benefits of aptamers in clinical and analytical applications, aptamer related technologies in the field of proteins and peptides are under progress, exclusively. Currently, there is only one FDA approved therapeutic aptamer in the pharmaceutical market, which is specific to vascular endothelial growth factor and is prescribed for age related macular degenerative disease. Additionally, there are several aptamers in the different phases of clinical trials. Almost all of these aptamers are specific to clinically important peptide or protein targets. In addition, the application of protein specific aptamers in the design and development of targeted drug delivery systems and diagnostic biosensors is another interesting field of aptamer technology. In this review, significant efforts related to development and applications of aptamer technologies in proteins and peptides sciences were considered to emphasis on the importance of aptamers in medicinal and clinical applications.

Shape-specific nanostructured protein mimics from de novo designed chimeric peptides.

PubMed

Jiang, Linhai; Yang, Su; Lund, Reidar; Dong, He

2018-01-30

Natural proteins self-assemble into highly-ordered nanoscaled architectures to perform specific functions. The intricate functions of proteins have provided great impetus for researchers to develop strategies for designing and engineering synthetic nanostructures as protein mimics. Compared to the success in engineering fibrous protein mimetics, the design of discrete globular protein-like nanostructures has been challenging mainly due to the lack of precise control over geometric packing and intermolecular interactions among synthetic building blocks. In this contribution, we report an effective strategy to construct shape-specific nanostructures based on the self-assembly of chimeric peptides consisting of a coiled coil dimer and a collagen triple helix folding motif. Under salt-free conditions, we showed spontaneous self-assembly of the chimeric peptides into monodisperse, trigonal bipyramidal-like nanoparticles with precise control over the stoichiometry of two folding motifs and the geometrical arrangements relative to one another. Three coiled coil dimers are interdigitated on the equatorial plane while the two collagen triple helices are located in the axial position, perpendicular to the coiled coil plane. A detailed molecular model was proposed and further validated by small angle X-ray scattering experiments and molecular dynamics (MD) simulation. The results from this study indicated that the molecular folding of each motif within the chimeric peptides and their geometric packing played important roles in the formation of discrete protein-like nanoparticles. The peptide design and self-assembly mechanism may open up new routes for the construction of highly organized, discrete self-assembling protein-like nanostructures with greater levels of control over assembly accuracy.

Graph-based optimization of epitope coverage for vaccine antigen design

DOE PAGES

Theiler, James Patrick; Korber, Bette Tina Marie

2017-01-29

Epigraph is a recently developed algorithm that enables the computationally efficient design of single or multi-antigen vaccines to maximize the potential epitope coverage for a diverse pathogen population. Potential epitopes are defined as short contiguous stretches of proteins, comparable in length to T-cell epitopes. This optimal coverage problem can be formulated in terms of a directed graph, with candidate antigens represented as paths that traverse this graph. Epigraph protein sequences can also be used as the basis for designing peptides for experimental evaluation of immune responses in natural infections to highly variable proteins. The epigraph tool suite also enables rapidmore » characterization of populations of diverse sequences from an immunological perspective. Fundamental distance measures are based on immunologically relevant shared potential epitope frequencies, rather than simple Hamming or phylogenetic distances. Here, we provide a mathematical description of the epigraph algorithm, include a comparison of different heuristics that can be used when graphs are not acyclic, and we describe an additional tool we have added to the web-based epigraph tool suite that provides frequency summaries of all distinct potential epitopes in a population. Lastly, we also show examples of the graphical output and summary tables that can be generated using the epigraph tool suite and explain their content and applications.« less

Graph-based optimization of epitope coverage for vaccine antigen design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Theiler, James Patrick; Korber, Bette Tina Marie

Epigraph is a recently developed algorithm that enables the computationally efficient design of single or multi-antigen vaccines to maximize the potential epitope coverage for a diverse pathogen population. Potential epitopes are defined as short contiguous stretches of proteins, comparable in length to T-cell epitopes. This optimal coverage problem can be formulated in terms of a directed graph, with candidate antigens represented as paths that traverse this graph. Epigraph protein sequences can also be used as the basis for designing peptides for experimental evaluation of immune responses in natural infections to highly variable proteins. The epigraph tool suite also enables rapidmore » characterization of populations of diverse sequences from an immunological perspective. Fundamental distance measures are based on immunologically relevant shared potential epitope frequencies, rather than simple Hamming or phylogenetic distances. Here, we provide a mathematical description of the epigraph algorithm, include a comparison of different heuristics that can be used when graphs are not acyclic, and we describe an additional tool we have added to the web-based epigraph tool suite that provides frequency summaries of all distinct potential epitopes in a population. Lastly, we also show examples of the graphical output and summary tables that can be generated using the epigraph tool suite and explain their content and applications.« less

Blind test of physics-based prediction of protein structures.

PubMed

Shell, M Scott; Ozkan, S Banu; Voelz, Vincent; Wu, Guohong Albert; Dill, Ken A

2009-02-01

We report here a multiprotein blind test of a computer method to predict native protein structures based solely on an all-atom physics-based force field. We use the AMBER 96 potential function with an implicit (GB/SA) model of solvation, combined with replica-exchange molecular-dynamics simulations. Coarse conformational sampling is performed using the zipping and assembly method (ZAM), an approach that is designed to mimic the putative physical routes of protein folding. ZAM was applied to the folding of six proteins, from 76 to 112 monomers in length, in CASP7, a community-wide blind test of protein structure prediction. Because these predictions have about the same level of accuracy as typical bioinformatics methods, and do not utilize information from databases of known native structures, this work opens up the possibility of predicting the structures of membrane proteins, synthetic peptides, or other foldable polymers, for which there is little prior knowledge of native structures. This approach may also be useful for predicting physical protein folding routes, non-native conformations, and other physical properties from amino acid sequences.

Blind Test of Physics-Based Prediction of Protein Structures

PubMed Central

Shell, M. Scott; Ozkan, S. Banu; Voelz, Vincent; Wu, Guohong Albert; Dill, Ken A.

2009-01-01

We report here a multiprotein blind test of a computer method to predict native protein structures based solely on an all-atom physics-based force field. We use the AMBER 96 potential function with an implicit (GB/SA) model of solvation, combined with replica-exchange molecular-dynamics simulations. Coarse conformational sampling is performed using the zipping and assembly method (ZAM), an approach that is designed to mimic the putative physical routes of protein folding. ZAM was applied to the folding of six proteins, from 76 to 112 monomers in length, in CASP7, a community-wide blind test of protein structure prediction. Because these predictions have about the same level of accuracy as typical bioinformatics methods, and do not utilize information from databases of known native structures, this work opens up the possibility of predicting the structures of membrane proteins, synthetic peptides, or other foldable polymers, for which there is little prior knowledge of native structures. This approach may also be useful for predicting physical protein folding routes, non-native conformations, and other physical properties from amino acid sequences. PMID:19186130

Flexible Molybdenum Electrodes towards Designing Affinity Based Protein Biosensors

PubMed Central

Kamakoti, Vikramshankar; Panneer Selvam, Anjan; Radha Shanmugam, Nandhinee; Muthukumar, Sriram; Prasad, Shalini

2016-01-01

Molybdenum electrode based flexible biosensor on porous polyamide substrates has been fabricated and tested for its functionality as a protein affinity based biosensor. The biosensor performance was evaluated using a key cardiac biomarker; cardiac Troponin-I (cTnI). Molybdenum is a transition metal and demonstrates electrochemical behavior upon interaction with an electrolyte. We have leveraged this property of molybdenum for designing an affinity based biosensor using electrochemical impedance spectroscopy. We have evaluated the feasibility of detection of cTnI in phosphate-buffered saline (PBS) and human serum (HS) by measuring impedance changes over a frequency window from 100 mHz to 1 MHz. Increasing changes to the measured impedance was correlated to the increased dose of cTnI molecules binding to the cTnI antibody functionalized molybdenum surface. We achieved cTnI detection limit of 10 pg/mL in PBS and 1 ng/mL in HS medium. The use of flexible substrates for designing the biosensor demonstrates promise for integration with a large-scale batch manufacturing process. PMID:27438863

Symmetry based assembly of a 2 dimensional protein lattice

DOE Office of Scientific and Technical Information (OSTI.GOV)

Poulos, Sandra; Agah, Sayeh; Jallah, Nikardi

2017-04-18

The design of proteins that self-assemble into higher order architectures is of great interest due to their potential application in nanotechnology. Specifically, the self-assembly of proteins into ordered lattices is of special interest to the field of structural biology. Here we designed a 2 dimensional (2D) protein lattice using a fusion of a tandem repeat of three TelSAM domains (TTT) to the Ferric uptake regulator (FUR) domain. We determined the structure of the designed (TTT-FUR) fusion protein to 2.3 Å by X-ray crystallographic methods. In agreement with the design, a 2D lattice composed of TelSAM fibers interdigitated by the FURmore » domain was observed. As expected, the fusion of a tandem repeat of three TelSAM domains formed 21 screw axis, and the self-assembly of the ordered oligomer was under pH control. We demonstrated that the fusion of TTT to a domain having a 2-fold symmetry, such as the FUR domain, can produce an ordered 2D lattice. The TTT-FUR system combines features from the rotational symmetry matching approach with the oligomer driven crystallization method. This TTT-FUR fusion was amenable to X-ray crystallographic methods, and is a promising crystallization chaperone.« less

The design and characterization of protein based block polymers

NASA Astrophysics Data System (ADS)

Haghpanah, Jennifer Shorah

Over the past decades, protein engineering has provided noteworthy advances in basic science as well as in medicine and industry. Protein engineers are currently focusing their efforts on developing elementary rules to design proteins with a specific structure and function. Proteins derived from natural sources have been used generate a plethora of materials with remarkable structural and functional properties. In the first chapter, we show how we can fabricate protein polymers comprised of two different self-assembling domains (SADs). From our studies, we discover that SADs in different orientations have a large impact on their overall microscopic and macroscopic features. In the second chapter, we explore the impact of cellulose (Tc) on the diblocks EC and CE. We discover that Tc is able to selectively impact the mechanical propertied of CE because CE has smaller particle sizes and more E domain exposed on its surface at RT. In the third chapter, we appended an extra C domain to CE to generate CEC with improved mechanical properties, structure and small molecule recognition.

Multidisciplinary perspectives for Alzheimer's and Parkinson's diseases: hydrogels for protein delivery and cell-based drug delivery as therapeutic strategies.

PubMed

Giordano, Carmen; Albani, Diego; Gloria, Antonio; Tunesi, Marta; Batelli, Sara; Russo, Teresa; Forloni, Gianluigi; Ambrosio, Luigi; Cigada, Alberto

2009-12-01

This review presents two intriguing multidisciplinary strategies that might make the difference in the treatment of neurodegenerative disorders such as Alzheimer's and Parkinson's diseases. The first proposed strategy is based on the controlled delivery of recombinant proteins known to play a key role in these neurodegenerative disorders that are released in situ by optimized polymer-based systems. The second strategy is the use of engineered cells, encapsulated and delivered in situ by suitable polymer-based systems, that act as drug reservoirs and allow the delivery of selected molecules to be used in the treatment of Alzheimer's and Parkinson's diseases. In both these scenarios, the design and development of optimized polymer-based drug delivery and cell housing systems for central nervous system applications represent a key requirement. Materials science provides suitable hydrogel-based tools to be optimized together with suitably designed recombinant proteins or drug delivering-cells that, once in situ, can provide an effective treatment for these neurodegenerative disorders. In this scenario, only interdisciplinary research that fully integrates biology, biochemistry, medicine and materials science can provide a springboard for the development of suitable therapeutic tools, not only for the treatment of Alzheimer's and Parkinson's diseases but also, prospectively, for a wide range of severe neurodegenerative disorders.

Structural Biology and the Design of New Therapeutics: From HIV and Cancer to Mycobacterial Infections: A Paper Dedicated to John Kendrew.

PubMed

Thomas, Sherine E; Mendes, Vitor; Kim, So Yeon; Malhotra, Sony; Ochoa-Montaño, Bernardo; Blaszczyk, Michal; Blundell, Tom L

2017-08-18

Interest in applications of protein crystallography to medicine was evident, as the first high-resolution structures emerged in the 50s and 60s. In Cambridge, Max Perutz and John Kendrew sought to understand mutations in sickle cell and other genetic diseases related to hemoglobin, while in Oxford, the group of Dorothy Hodgkin became interested in long-lasting zinc-insulin crystals for treatment of diabetes and later considered insulin redesign, as synthetic insulins became possible. The use of protein crystallography in structure-guided drug discovery emerged as enzyme structures allowed the identification of potential inhibitor-binding sites and optimization of interactions of hits using the structure of the target protein. Early examples of this approach were the use of the structure of renin to design antihypertensives and the structure of HIV protease in design of AIDS antivirals. More recently, use of structure-guided design with fragment-based drug discovery, which reduces the size of screening libraries by decreasing complexity, has improved ligand efficiency in drug design and has been used to progress three oncology drugs through clinical trials to FDA approval. We exemplify current developments in structure-guided target identification and fragment-based lead discovery with efforts to develop new antimicrobials for mycobacterial infections. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Recent advances in automated protein design and its future challenges.

PubMed

Setiawan, Dani; Brender, Jeffrey; Zhang, Yang

2018-04-25

Protein function is determined by protein structure which is in turn determined by the corresponding protein sequence. If the rules that cause a protein to adopt a particular structure are understood, it should be possible to refine or even redefine the function of a protein by working backwards from the desired structure to the sequence. Automated protein design attempts to calculate the effects of mutations computationally with the goal of more radical or complex transformations than are accessible by experimental techniques. Areas covered: The authors give a brief overview of the recent methodological advances in computer-aided protein design, showing how methodological choices affect final design and how automated protein design can be used to address problems considered beyond traditional protein engineering, including the creation of novel protein scaffolds for drug development. Also, the authors address specifically the future challenges in the development of automated protein design. Expert opinion: Automated protein design holds potential as a protein engineering technique, particularly in cases where screening by combinatorial mutagenesis is problematic. Considering solubility and immunogenicity issues, automated protein design is initially more likely to make an impact as a research tool for exploring basic biology in drug discovery than in the design of protein biologics.

Strong underwater adhesives made by self-assembling multi-protein nanofibres.

PubMed

Zhong, Chao; Gurry, Thomas; Cheng, Allen A; Downey, Jordan; Deng, Zhengtao; Stultz, Collin M; Lu, Timothy K

2014-10-01

Many natural underwater adhesives harness hierarchically assembled amyloid nanostructures to achieve strong and robust interfacial adhesion under dynamic and turbulent environments. Despite recent advances, our understanding of the molecular design, self-assembly and structure-function relationships of these natural amyloid fibres remains limited. Thus, designing biomimetic amyloid-based adhesives remains challenging. Here, we report strong and multi-functional underwater adhesives obtained from fusing mussel foot proteins (Mfps) of Mytilus galloprovincialis with CsgA proteins, the major subunit of Escherichia coli amyloid curli fibres. These hybrid molecular materials hierarchically self-assemble into higher-order structures, in which, according to molecular dynamics simulations, disordered adhesive Mfp domains are exposed on the exterior of amyloid cores formed by CsgA. Our fibres have an underwater adhesion energy approaching 20.9 mJ m(-2), which is 1.5 times greater than the maximum of bio-inspired and bio-derived protein-based underwater adhesives reported thus far. Moreover, they outperform Mfps or curli fibres taken on their own and exhibit better tolerance to auto-oxidation than Mfps at pH ≥ 7.0.

EpiSweep: Computationally Driven Reengineering of Therapeutic Proteins to Reduce Immunogenicity While Maintaining Function.

PubMed

Choi, Yoonjoo; Verma, Deeptak; Griswold, Karl E; Bailey-Kellogg, Chris

2017-01-01

Therapeutic proteins are yielding ever more advanced and efficacious new drugs, but the biological origins of these highly effective therapeutics render them subject to immune surveillance within the patient's body. When recognized by the immune system as a foreign agent, protein drugs elicit a coordinated response that can manifest a range of clinical complications including rapid drug clearance, loss of functionality and efficacy, delayed infusion-like allergic reactions, more serious anaphylactic shock, and even induced auto-immunity. It is thus often necessary to deimmunize an exogenous protein in order to enable its clinical application; critically, the deimmunization process must also maintain the desired therapeutic activity.To meet the growing need for effective, efficient, and broadly applicable protein deimmunization technologies, we have developed the EpiSweep suite of protein design algorithms. EpiSweep seamlessly integrates computational prediction of immunogenic T cell epitopes with sequence- or structure-based assessment of the impacts of mutations on protein stability and function, in order to select combinations of mutations that make Pareto optimal trade-offs between the competing goals of low immunogenicity and high-level function. The methods are applicable both to the design of individual functionally deimmunized variants as well as the design of combinatorial libraries enriched in functionally deimmunized variants. After validating EpiSweep in a series of retrospective case studies providing comparisons to conventional approaches to T cell epitope deletion, we have experimentally demonstrated it to be highly effective in prospective application to deimmunization of a number of different therapeutic candidates. We conclude that our broadly applicable computational protein design algorithms guide the engineer towards the most promising deimmunized therapeutic candidates, and thereby have the potential to accelerate development of new protein drugs by shortening time frames and improving hit rates.

EpiSweep: Computationally-driven Reengineering of Therapeutic Proteins to Reduce immunogenicity while Maintaining Function

PubMed Central

Choi, Yoonjoo; Verma, Deeptak; Griswold, Karl E.; Bailey-Kellogg, Chris

2016-01-01

Therapeutic proteins are yielding ever more advanced and efficacious new drugs, but the biological origins of these highly effective therapeutics renders them subject to immune surveillance within the patient’s body. When recognized by the immune system as a foreign agent, protein drugs elicit a coordinated response that can manifest a range of clinical complications including rapid drug clearance, loss of functionality and efficacy, delayed infusion-like allergic reactions, more serious anaphylactic shock, and even induced auto-immunity. It is thus often necessary to deimmunize an exogenous protein in order to enable its clinical application; critically, the deimmunization process must also maintain the desired therapeutic activity. To meet the growing need for effective, efficient, and broadly applicable protein deimmunization technologies, we have developed the EpiSweep suite of protein design algorithms. EpiSweep seamlessly integrates computational prediction of immunogenic T cell epitopes with sequence- or structure- based assessment of the impacts of mutations on protein stability and function, in order to select combinations of mutations that make Pareto optimal trade-offs between the competing goals of low immunogenicity and high-level function. The methods are applicable both to the design of individual functionally deimmunized variants as well as the design of combinatorial libraries enriched in functionally deimmunized variants. After validating EpiSweep in a series of retrospective case studies providing comparisons to conventional approaches to T cell epitope deletion, we have experimentally demonstrated it to be highly effective in prospective application to deimmunization of a number of different therapeutic candidates. We conclude that our broadly applicable computational protein design algorithms guide the engineer towards the most promising deimmunized therapeutic candidates, and thereby have the potential to accelerate development of new protein drugs by shortening time frames and improving hit rates. PMID:27914063

Molecular design of new aggrecanases-2 inhibitors.

PubMed

Shan, Zhi Jie; Zhai, Hong Lin; Huang, Xiao Yan; Li, Li Na; Zhang, Xiao Yun

2013-10-01

Aggrecanases-2 is a very important potential drug target for the treatment of osteoarthritis. In this study, a series of known aggrecanases-2 inhibitors was analyzed by the technologies of three-dimensional quantitative structure-activity relationships (3D-QSAR) and molecular docking. Two 3D-QSAR models, which based on comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) methods, were established. Molecular docking was employed to explore the details of the interaction between inhibitors and aggrecanases-2 protein. According to the analyses for these models, several new potential inhibitors with higher activity predicted were designed, and were supported by the simulation of molecular docking. This work propose the fast and effective approach to design and prediction for new potential inhibitors, and the study of the interaction mechanism provide a better understanding for the inhibitors binding into the target protein, which will be useful for the structure-based drug design and modifications. Copyright © 2013 Elsevier Ltd. All rights reserved.

Design principles for nuclease-deficient CRISPR-based transcriptional regulators

PubMed Central

Jensen, Michael K

2018-01-01

Abstract The engineering of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-CRISPR-associated proteins continues to expand the toolkit available for genome editing, reprogramming gene regulation, genome visualisation and epigenetic studies of living organisms. In this review, the emerging design principles on the use of nuclease-deficient CRISPR-based reprogramming of gene expression will be presented. The review will focus on the designs implemented in yeast both at the level of CRISPR proteins and guide RNA (gRNA), but will lend due credits to the seminal studies performed in other species where relevant. In addition to design principles, this review also highlights applications benefitting from the use of CRISPR-mediated transcriptional regulation and discusses the future directions to further expand the toolkit for nuclease-deficient reprogramming of genomes. As such, this review should be of general interest for experimentalists to get familiarised with the parameters underlying the power of reprogramming genomic functions by use of nuclease-deficient CRISPR technologies. PMID:29726937

Co-complex protein membership evaluation using Maximum Entropy on GO ontology and InterPro annotation.

PubMed

Armean, Irina M; Lilley, Kathryn S; Trotter, Matthew W B; Pilkington, Nicholas C V; Holden, Sean B

2018-06-01

Protein-protein interactions (PPI) play a crucial role in our understanding of protein function and biological processes. The standardization and recording of experimental findings is increasingly stored in ontologies, with the Gene Ontology (GO) being one of the most successful projects. Several PPI evaluation algorithms have been based on the application of probabilistic frameworks or machine learning algorithms to GO properties. Here, we introduce a new training set design and machine learning based approach that combines dependent heterogeneous protein annotations from the entire ontology to evaluate putative co-complex protein interactions determined by empirical studies. PPI annotations are built combinatorically using corresponding GO terms and InterPro annotation. We use a S.cerevisiae high-confidence complex dataset as a positive training set. A series of classifiers based on Maximum Entropy and support vector machines (SVMs), each with a composite counterpart algorithm, are trained on a series of training sets. These achieve a high performance area under the ROC curve of ≤0.97, outperforming go2ppi-a previously established prediction tool for protein-protein interactions (PPI) based on Gene Ontology (GO) annotations. https://github.com/ima23/maxent-ppi. sbh11@cl.cam.ac.uk. Supplementary data are available at Bioinformatics online.

Prediction of Protein Configurational Entropy (Popcoen).

PubMed

Goethe, Martin; Gleixner, Jan; Fita, Ignacio; Rubi, J Miguel

2018-03-13

A knowledge-based method for configurational entropy prediction of proteins is presented; this methodology is extremely fast, compared to previous approaches, because it does not involve any type of configurational sampling. Instead, the configurational entropy of a query fold is estimated by evaluating an artificial neural network, which was trained on molecular-dynamics simulations of ∼1000 proteins. The predicted entropy can be incorporated into a large class of protein software based on cost-function minimization/evaluation, in which configurational entropy is currently neglected for performance reasons. Software of this type is used for all major protein tasks such as structure predictions, proteins design, NMR and X-ray refinement, docking, and mutation effect predictions. Integrating the predicted entropy can yield a significant accuracy increase as we show exemplarily for native-state identification with the prominent protein software FoldX. The method has been termed Popcoen for Prediction of Protein Configurational Entropy. An implementation is freely available at http://fmc.ub.edu/popcoen/ .

OSPREY Predicts Resistance Mutations Using Positive and Negative Computational Protein Design.

PubMed

Ojewole, Adegoke; Lowegard, Anna; Gainza, Pablo; Reeve, Stephanie M; Georgiev, Ivelin; Anderson, Amy C; Donald, Bruce R

2017-01-01

Drug resistance in protein targets is an increasingly common phenomenon that reduces the efficacy of both existing and new antibiotics. However, knowledge of future resistance mutations during pre-clinical phases of drug development would enable the design of novel antibiotics that are robust against not only known resistant mutants, but also against those that have not yet been clinically observed. Computational structure-based protein design (CSPD) is a transformative field that enables the prediction of protein sequences with desired biochemical properties such as binding affinity and specificity to a target. The use of CSPD to predict previously unseen resistance mutations represents one of the frontiers of computational protein design. In a recent study (Reeve et al. Proc Natl Acad Sci U S A 112(3):749-754, 2015), we used our OSPREY (Open Source Protein REdesign for You) suite of CSPD algorithms to prospectively predict resistance mutations that arise in the active site of the dihydrofolate reductase enzyme from methicillin-resistant Staphylococcus aureus (SaDHFR) in response to selective pressure from an experimental competitive inhibitor. We demonstrated that our top predicted candidates are indeed viable resistant mutants. Since that study, we have significantly enhanced the capabilities of OSPREY with not only improved modeling of backbone flexibility, but also efficient multi-state design, fast sparse approximations, partitioned continuous rotamers for more accurate energy bounds, and a computationally efficient representation of molecular-mechanics and quantum-mechanical energy functions. Here, using SaDHFR as an example, we present a protocol for resistance prediction using the latest version of OSPREY. Specifically, we show how to use a combination of positive and negative design to predict active site escape mutations that maintain the enzyme's catalytic function but selectively ablate binding of an inhibitor.

Pharmacophore modeling using Site-Identification by Ligand Competitive Saturation (SILCS) with multiple probe molecules

PubMed Central

Yu, Wenbo; Lakkaraju, Sirish Kaushik; Raman, E. Prabhu; Fang, Lei; MacKerell, Alexander D.

2015-01-01

Receptor-based pharmacophore modeling is an efficient computer-aided drug design technique that uses the structure of the target protein to identify novel leads. However, most methods consider protein flexibility and desolvation effects in a very approximate way, which may limit their use in practice. The Site-Identification by Ligand Competitive Saturation (SILCS) assisted pharmacophore modeling protocol (SILCS-Pharm) was introduced recently to address these issues as SILCS naturally takes both protein flexibility and desolvation effects into account by using full MD simulations to determine 3D maps of the functional group-affinity patterns on a target receptor. In the present work, the SILCS-Pharm protocol is extended to use a wider range of probe molecules including benzene, propane, methanol, formamide, acetaldehyde, methylammonium, acetate and water. This approach removes the previous ambiguity brought by using water as both the hydrogen-bond donor and acceptor probe molecule. The new SILCS-Pharm protocol is shown to yield improved screening results as compared to the previous approach based on three target proteins. Further validation of the new protocol using five additional protein targets showed improved screening compared to those using common docking methods, further indicating improvements brought by the explicit inclusion of additional feature types associated with the wider collection of probe molecules in the SILCS simulations. The advantage of using complementary features and volume constraints, based on exclusion maps of the protein defined from the SILCS simulations, is presented. In addition, re-ranking using SILCS-based ligand grid free energies is shown to enhance the diversity of identified ligands for the majority of targets. These results suggest that the SILCS-Pharm protocol will be of utility in rational drug design. PMID:25622696

A set of ligation-independent in vitro translation vectors for eukaryotic protein production.

PubMed

Bardóczy, Viola; Géczi, Viktória; Sawasaki, Tatsuya; Endo, Yaeta; Mészáros, Tamás

2008-03-27

The last decade has brought the renaissance of protein studies and accelerated the development of high-throughput methods in all aspects of proteomics. Presently, most protein synthesis systems exploit the capacity of living cells to translate proteins, but their application is limited by several factors. A more flexible alternative protein production method is the cell-free in vitro protein translation. Currently available in vitro translation systems are suitable for high-throughput robotic protein production, fulfilling the requirements of proteomics studies. Wheat germ extract based in vitro translation system is likely the most promising method, since numerous eukaryotic proteins can be cost-efficiently synthesized in their native folded form. Although currently available vectors for wheat embryo in vitro translation systems ensure high productivity, they do not meet the requirements of state-of-the-art proteomics. Target genes have to be inserted using restriction endonucleases and the plasmids do not encode cleavable affinity purification tags. We designed four ligation independent cloning (LIC) vectors for wheat germ extract based in vitro protein translation. In these constructs, the RNA transcription is driven by T7 or SP6 phage polymerase and two TEV protease cleavable affinity tags can be added to aid protein purification. To evaluate our improved vectors, a plant mitogen activated protein kinase was cloned in all four constructs. Purification of this eukaryotic protein kinase demonstrated that all constructs functioned as intended: insertion of PCR fragment by LIC worked efficiently, affinity purification of translated proteins by GST-Sepharose or MagneHis particles resulted in high purity kinase, and the affinity tags could efficiently be removed under different reaction conditions. Furthermore, high in vitro kinase activity testified of proper folding of the purified protein. Four newly designed in vitro translation vectors have been constructed which allow fast and parallel cloning and protein purification, thus representing useful molecular tools for high-throughput production of eukaryotic proteins.

Protein-ligand interfaces are polarized: discovery of a strong trend for intermolecular hydrogen bonds to favor donors on the protein side with implications for predicting and designing ligand complexes.

PubMed

Raschka, Sebastian; Wolf, Alex J; Bemister-Buffington, Joseph; Kuhn, Leslie A

2018-04-01

Understanding how proteins encode ligand specificity is fascinating and similar in importance to deciphering the genetic code. For protein-ligand recognition, the combination of an almost infinite variety of interfacial shapes and patterns of chemical groups makes the problem especially challenging. Here we analyze data across non-homologous proteins in complex with small biological ligands to address observations made in our inhibitor discovery projects: that proteins favor donating H-bonds to ligands and avoid using groups with both H-bond donor and acceptor capacity. The resulting clear and significant chemical group matching preferences elucidate the code for protein-native ligand binding, similar to the dominant patterns found in nucleic acid base-pairing. On average, 90% of the keto and carboxylate oxygens occurring in the biological ligands formed direct H-bonds to the protein. A two-fold preference was found for protein atoms to act as H-bond donors and ligand atoms to act as acceptors, and 76% of all intermolecular H-bonds involved an amine donor. Together, the tight chemical and geometric constraints associated with satisfying donor groups generate a hydrogen-bonding lock that can be matched only by ligands bearing the right acceptor-rich key. Measuring an index of H-bond preference based on the observed chemical trends proved sufficient to predict other protein-ligand complexes and can be used to guide molecular design. The resulting Hbind and Protein Recognition Index software packages are being made available for rigorously defining intermolecular H-bonds and measuring the extent to which H-bonding patterns in a given complex match the preference key.

Protein-ligand interfaces are polarized: discovery of a strong trend for intermolecular hydrogen bonds to favor donors on the protein side with implications for predicting and designing ligand complexes

NASA Astrophysics Data System (ADS)

Raschka, Sebastian; Wolf, Alex J.; Bemister-Buffington, Joseph; Kuhn, Leslie A.

2018-02-01

Understanding how proteins encode ligand specificity is fascinating and similar in importance to deciphering the genetic code. For protein-ligand recognition, the combination of an almost infinite variety of interfacial shapes and patterns of chemical groups makes the problem especially challenging. Here we analyze data across non-homologous proteins in complex with small biological ligands to address observations made in our inhibitor discovery projects: that proteins favor donating H-bonds to ligands and avoid using groups with both H-bond donor and acceptor capacity. The resulting clear and significant chemical group matching preferences elucidate the code for protein-native ligand binding, similar to the dominant patterns found in nucleic acid base-pairing. On average, 90% of the keto and carboxylate oxygens occurring in the biological ligands formed direct H-bonds to the protein. A two-fold preference was found for protein atoms to act as H-bond donors and ligand atoms to act as acceptors, and 76% of all intermolecular H-bonds involved an amine donor. Together, the tight chemical and geometric constraints associated with satisfying donor groups generate a hydrogen-bonding lock that can be matched only by ligands bearing the right acceptor-rich key. Measuring an index of H-bond preference based on the observed chemical trends proved sufficient to predict other protein-ligand complexes and can be used to guide molecular design. The resulting Hbind and Protein Recognition Index software packages are being made available for rigorously defining intermolecular H-bonds and measuring the extent to which H-bonding patterns in a given complex match the preference key.

Thermostabilisation of membrane proteins for structural studies

PubMed Central

Magnani, Francesca; Serrano-Vega, Maria J.; Shibata, Yoko; Abdul-Hussein, Saba; Lebon, Guillaume; Miller-Gallacher, Jennifer; Singhal, Ankita; Strege, Annette; Thomas, Jennifer A.; Tate, Christopher G.

2017-01-01

The thermostability of an integral membrane protein in detergent solution is a key parameter that dictates the likelihood of obtaining well-diffracting crystals suitable for structure determination. However, many mammalian membrane proteins are too unstable for crystallisation. We developed a thermostabilisation strategy based on systematic mutagenesis coupled to a radioligand-binding thermostability assay that can be applied to receptors, ion channels and transporters. It takes approximately 6-12 months to thermostabilise a G protein-coupled receptor (GPCR) containing 300 amino acid residues. The resulting thermostabilised membrane proteins are more easily crystallised and result in high-quality structures. This methodology has facilitated structure-based drug design applied to GPCRs, because it is possible to determine multiple structures of the thermostabilised receptors bound to low affinity ligands. Protocols and advice are given on how to develop thermostability assays for membrane proteins and how to combine mutations to make an optimally stable mutant suitable for structural studies. PMID:27466713

JAXA protein crystallization in space: ongoing improvements for growing high-quality crystals

PubMed Central

Takahashi, Sachiko; Ohta, Kazunori; Furubayashi, Naoki; Yan, Bin; Koga, Misako; Wada, Yoshio; Yamada, Mitsugu; Inaka, Koji; Tanaka, Hiroaki; Miyoshi, Hiroshi; Kobayashi, Tomoyuki; Kamigaichi, Shigeki

2013-01-01

The Japan Aerospace Exploration Agency (JAXA) started a high-quality protein crystal growth project, now called JAXA PCG, on the International Space Station (ISS) in 2002. Using the counter-diffusion technique, 14 sessions of experiments have been performed as of 2012 with 580 proteins crystallized in total. Over the course of these experiments, a user-friendly interface framework for high accessibility has been constructed and crystallization techniques improved; devices to maximize the use of the microgravity environment have been designed, resulting in some high-resolution crystal growth. If crystallization conditions were carefully fixed in ground-based experiments, high-quality protein crystals grew in microgravity in many experiments on the ISS, especially when a highly homogeneous protein sample and a viscous crystallization solution were employed. In this article, the current status of JAXA PCG is discussed, and a rational approach to high-quality protein crystal growth in microgravity based on numerical analyses is explained. PMID:24121350

[In vitro availability of minerals in infant foods with different protein source].

PubMed

Pérez-Llamas, F; Larqué, E; Marín, J F; Zamora, S

2001-01-01

As the result of the digestion process, it is produced at gastrointestinal level interactions between proteins-minerals and minerals-minerals that might modify the bioavailability of the nutrients initially designed for an adequate nutrition in infant formulas. The aim of the present study is to compare the in vitro availability of some minerals and trace elements (calcium, phosphorus, magnesium, iron and zinc) in infant formulas of initiation elaborated with different protein sources: formulas based on cow milk protein (whey-casein) versus vegetal protein (soy-based infant formulas). Also, for evaluating the effects of the different mineral supplementation in the availability of minerals, it was used infant formulas from two different manufacturers. Milk-protein based infant formulas showed for both manufacturers higher dialysis percentage (%) of phosphorus and zinc than the soy-protein based formulas. The availability of iron in the soy formula of the manufacturer A lowered significantly (P < 0.05) respect to the whey-casein based formula (9.6 +/- 2.3 versus 4.6 +/- 0.8), but not respect to the whey-casein formula of manufacturer B (9.6 +/- 1.1 versus 9.0 +/- 0.7), which might be due to the lowest proportion of phytic acid in this last commercial formula. Dialysability of all the minerals analysed from soy-protein based formulas showed significant differences depending on the manufacturer. The purification processes of the soy protein have a high repercussion in the mineral availability of soy-based infant formulas. It could be more interesting to use soy proteins more purified, with low level of phytic acid, in the elaboration of soy infants formulas, than the supplementation them with high amounts of minerals.

Structure-Based Virtual Screening for Drug Discovery: Principles, Applications and Recent Advances

PubMed Central

Lionta, Evanthia; Spyrou, George; Vassilatis, Demetrios K.; Cournia, Zoe

2014-01-01

Structure-based drug discovery (SBDD) is becoming an essential tool in assisting fast and cost-efficient lead discovery and optimization. The application of rational, structure-based drug design is proven to be more efficient than the traditional way of drug discovery since it aims to understand the molecular basis of a disease and utilizes the knowledge of the three-dimensional structure of the biological target in the process. In this review, we focus on the principles and applications of Virtual Screening (VS) within the context of SBDD and examine different procedures ranging from the initial stages of the process that include receptor and library pre-processing, to docking, scoring and post-processing of topscoring hits. Recent improvements in structure-based virtual screening (SBVS) efficiency through ensemble docking, induced fit and consensus docking are also discussed. The review highlights advances in the field within the framework of several success studies that have led to nM inhibition directly from VS and provides recent trends in library design as well as discusses limitations of the method. Applications of SBVS in the design of substrates for engineered proteins that enable the discovery of new metabolic and signal transduction pathways and the design of inhibitors of multifunctional proteins are also reviewed. Finally, we contribute two promising VS protocols recently developed by us that aim to increase inhibitor selectivity. In the first protocol, we describe the discovery of micromolar inhibitors through SBVS designed to inhibit the mutant H1047R PI3Kα kinase. Second, we discuss a strategy for the identification of selective binders for the RXRα nuclear receptor. In this protocol, a set of target structures is constructed for ensemble docking based on binding site shape characterization and clustering, aiming to enhance the hit rate of selective inhibitors for the desired protein target through the SBVS process. PMID:25262799

Structure-Based Design of Inhibitors of Protein–Protein Interactions: Mimicking Peptide Binding Epitopes

PubMed Central

Pelay-Gimeno, Marta; Glas, Adrian; Koch, Oliver; Grossmann, Tom N

2015-01-01

Protein–protein interactions (PPIs) are involved at all levels of cellular organization, thus making the development of PPI inhibitors extremely valuable. The identification of selective inhibitors is challenging because of the shallow and extended nature of PPI interfaces. Inhibitors can be obtained by mimicking peptide binding epitopes in their bioactive conformation. For this purpose, several strategies have been evolved to enable a projection of side chain functionalities in analogy to peptide secondary structures, thereby yielding molecules that are generally referred to as peptidomimetics. Herein, we introduce a new classification of peptidomimetics (classes A–D) that enables a clear assignment of available approaches. Based on this classification, the Review summarizes strategies that have been applied for the structure-based design of PPI inhibitors through stabilizing or mimicking turns, β-sheets, and helices. PMID:26119925

Effective Design of Multifunctional Peptides by Combining Compatible Functions

PubMed Central

Diener, Christian; Garza Ramos Martínez, Georgina; Moreno Blas, Daniel; Castillo González, David A.; Corzo, Gerardo; Castro-Obregon, Susana; Del Rio, Gabriel

2016-01-01

Multifunctionality is a common trait of many natural proteins and peptides, yet the rules to generate such multifunctionality remain unclear. We propose that the rules defining some protein/peptide functions are compatible. To explore this hypothesis, we trained a computational method to predict cell-penetrating peptides at the sequence level and learned that antimicrobial peptides and DNA-binding proteins are compatible with the rules of our predictor. Based on this finding, we expected that designing peptides for CPP activity may render AMP and DNA-binding activities. To test this prediction, we designed peptides that embedded two independent functional domains (nuclear localization and yeast pheromone activity), linked by optimizing their composition to fit the rules characterizing cell-penetrating peptides. These peptides presented effective cell penetration, DNA-binding, pheromone and antimicrobial activities, thus confirming the effectiveness of our computational approach to design multifunctional peptides with potential therapeutic uses. Our computational implementation is available at http://bis.ifc.unam.mx/en/software/dcf. PMID:27096600

Meals based on vegetable protein sources (beans and peas) are more satiating than meals based on animal protein sources (veal and pork) – a randomized cross-over meal test study

PubMed Central

Kristensen, Marlene D.; Bendsen, Nathalie T.; Christensen, Sheena M.; Astrup, Arne; Raben, Anne

2016-01-01

Background Recent nutrition recommendations advocate a reduction in protein from animal sources (pork, beef) because of environmental concerns. Instead, protein from vegetable sources (beans, peas) should be increased. However, little is known about the effect of these vegetable protein sources on appetite regulation. Objective To examine whether meals based on vegetable protein sources (beans/peas) are comparable to meals based on animal protein sources (veal/pork) regarding meal-induced appetite sensations. Design In total, 43 healthy, normal-weight, young men completed this randomized, double-blind, placebo-controlled, three-way, cross-over meal test. The meals (all 3.5 MJ, 28 energy-% (E%) fat) were either high protein based on veal and pork meat, HP-Meat (19 E% protein, 53 E% carbohydrate, 6 g fiber/100 g); high protein based on legumes (beans and peas), HP-Legume (19 E% protein, 53 E% carbohydrate, 25 g fiber/100 g); or low-protein based on legumes, LP-Legume (9 E% protein, 62 E% carbohydrate, 10 g fiber/100 g). Subjective appetite sensations were recorded at baseline and every half hour using visual analog scales until the ad libitum meal 3 h after the test meal. Repeated measurements analyses and summary analyses were performed using ANCOVA (SAS). Results HP-Legume induced lower composite appetite score, hunger, prospective food consumption, and higher fullness compared to HP-Meat and LP-Legume (p<0.05). Furthermore, satiety was higher after HP-Legume than HP-Meat (p<0.05). When adjusting for palatability, HP-Legume still resulted in lower composite appetite scores, hunger, prospective consumption, and higher fullness compared to HP-Meat (p<0.05). Furthermore, HP-Legume induced higher fullness than LP-Legume (p<0.05). A 12% and 13% lower energy intake, respectively, was seen after HP-Legume compared to HP-Meat or LP-Legume (p<0.01). Conclusion Vegetable-based meals (beans/peas) influenced appetite sensations favorably compared to animal-based meals (pork/veal) with similar energy and protein content, but lower fiber content. Interestingly, a vegetable-based meal with low protein content was as satiating and palatable as an animal-based meal with high protein content. PMID:27765144

Silk-based delivery systems of bioactive molecules

PubMed Central

Numata, Keiji; Kaplan, David L

2010-01-01

Silks are biodegradable, biocompatible, self-assemblying proteins that can also be tailored via genetic engineering to contain specific chemical features, offering utility for drug and gene delivery. Silkworm silk has been used in biomedical sutures for decades and has recently achieved Food and Drug Administration approval for expanded biomaterials device utility. With the diversity and control of size, structure and chemistry, modified or recombinant silk proteins can be designed and utilized in various biomedical application, such as for the delivery of bioactive molecules. This review focuses on the biosynthesis and applications of silk-based multi-block copolymer systems and related silk protein drug delivery systems. The utility of these systems for the delivery of small molecule drugs, proteins and genes are reviewed. PMID:20298729

Pulse Detecting Genetic Circuit – A New Design Approach

PubMed Central

Inniss, Mara; Iba, Hitoshi; Way, Jeffrey C.

2016-01-01

A robust cellular counter could enable synthetic biologists to design complex circuits with diverse behaviors. The existing synthetic-biological counters, responsive to the beginning of the pulse, are sensitive to the pulse duration. Here we present a pulse detecting circuit that responds only at the falling edge of a pulse–analogous to negative edge triggered electric circuits. As biological events do not follow precise timing, use of such a pulse detector would enable the design of robust asynchronous counters which can count the completion of events. This transcription-based pulse detecting circuit depends on the interaction of two co-expressed lambdoid phage-derived proteins: the first is unstable and inhibits the regulatory activity of the second, stable protein. At the end of the pulse the unstable inhibitor protein disappears from the cell and the second protein triggers the recording of the event completion. Using stochastic simulation we showed that the proposed design can detect the completion of the pulse irrespective to the pulse duration. In our simulation we also showed that fusing the pulse detector with a phage lambda memory element we can construct a counter which can be extended to count larger numbers. The proposed design principle is a new control mechanism for synthetic biology which can be integrated in different circuits for identifying the completion of an event. PMID:27907045

Pulse Detecting Genetic Circuit - A New Design Approach.

PubMed

Noman, Nasimul; Inniss, Mara; Iba, Hitoshi; Way, Jeffrey C

2016-01-01

A robust cellular counter could enable synthetic biologists to design complex circuits with diverse behaviors. The existing synthetic-biological counters, responsive to the beginning of the pulse, are sensitive to the pulse duration. Here we present a pulse detecting circuit that responds only at the falling edge of a pulse-analogous to negative edge triggered electric circuits. As biological events do not follow precise timing, use of such a pulse detector would enable the design of robust asynchronous counters which can count the completion of events. This transcription-based pulse detecting circuit depends on the interaction of two co-expressed lambdoid phage-derived proteins: the first is unstable and inhibits the regulatory activity of the second, stable protein. At the end of the pulse the unstable inhibitor protein disappears from the cell and the second protein triggers the recording of the event completion. Using stochastic simulation we showed that the proposed design can detect the completion of the pulse irrespective to the pulse duration. In our simulation we also showed that fusing the pulse detector with a phage lambda memory element we can construct a counter which can be extended to count larger numbers. The proposed design principle is a new control mechanism for synthetic biology which can be integrated in different circuits for identifying the completion of an event.

PDB to AMPL Conversion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anna Johnston, SNL 9215

2002-09-01

PDB to AMPL Conversion was written to convert protein data base files to AMPL files. The protein data bases on the internet contain a wealth of information about the structue and makeup of proteins. Each file contains information derived by one or more experiments and contains information on how the experiment waw performed, the amino acid building blocks of each chain, and often the three-dimensional structure of the protein extracted from the experiments. The way a protein folds determines much about its function. Thus, studying the three-dimensional structure of the protein is of great interest. Analysing the contact maps ismore » one way to examine the structure. A contact map is a graph which has a linear back bone of amino acids for nodes (i.e., adjacent amino acids are always connected) and vertices between non-adjacent nodes if they are close enough to be considered in contact. If the graphs are similar then the folds of the protein and their function should also be similar. This software extracts the contact maps from a protein data base file and puts in into AMPL data format. This format is designed for use in AMPL, a programming language for simplifying linear programming formulations.« less

Ion transport across the biological membrane by computational protein design

NASA Astrophysics Data System (ADS)

Grigoryan, Gevorg

The cellular membrane is impermeable to most of the chemicals the cell needs to take in or discard to survive. Therefore, transporters-a class of transmembrane proteins tasked with shuttling cargo chemicals in and out of the cell-are essential to all cellular life. From existing crystal structures, we know transporters to be complex machines, exquisitely tuned for specificity and controllability. But how could membrane-bound life have evolved if it needed such complex machines to exist first? To shed light onto this question, we considered the task of designing a transporter de novo. As our guiding principle, we took the ``alternating-access model''-a conceptual mechanism stating that transporters work by rocking between two conformations, each exposing the cargo-binding site to either the intra- or the extra-cellular environment. A computational design framework was developed to encode an anti-parallel four-helix bundle that rocked between two alternative states to orchestrate the movement of Zn(II) ions across the membrane. The ensemble nature of both states was accounted for using a free energy-based approach, and sequences were chosen based on predicted formation of the targeted topology in the membrane and bi-stability. A single sequence was prepared experimentally and shown to function as a Zn(II) transporter in lipid vesicles. Further, transport was specific to Zn(II) ions and several control peptides supported the underlying design principles. This included a mutant designed to retain all properties but with reduced rocking, which showed greatly depressed transport ability. These results suggest that early transporters could have evolved in the context of simple topologies, to be later tuned by evolution for improved properties and controllability. Our study also serves as an important advance in computational protein design, showing the feasibility of designing functional membrane proteins and of tuning conformational landscapes for desired function. Alfred P. Sloan Foundation Research Fellowship.

Two-color SERS microscopy for protein co-localization in prostate tissue with primary antibody-protein A/G-gold nanocluster conjugates

NASA Astrophysics Data System (ADS)

Salehi, Mohammad; Schneider, Lilli; Ströbel, Philipp; Marx, Alexander; Packeisen, Jens; Schlücker, Sebastian

2014-01-01

SERS microscopy is a novel staining technique in immunohistochemistry, which is based on antibodies labeled with functionalized noble metal colloids called SERS labels or nanotags for optical detection. Conventional covalent bioconjugation of these SERS labels cannot prevent blocking of the antigen recognition sites of the antibody. We present a rational chemical design for SERS label-antibody conjugates which addresses this issue. Highly sensitive, silica-coated gold nanoparticle clusters as SERS labels are non-covalently conjugated to primary antibodies by using the chimeric protein A/G, which selectively recognizes the Fc part of antibodies and therefore prevents blocking of the antigen recognition sites. In proof-of-concept two-color imaging experiments for the co-localization of p63 and PSA on non-neoplastic prostate tissue FFPE specimens, we demonstrate the specificity and signal brightness of these rationally designed primary antibody-protein A/G-gold nanocluster conjugates.SERS microscopy is a novel staining technique in immunohistochemistry, which is based on antibodies labeled with functionalized noble metal colloids called SERS labels or nanotags for optical detection. Conventional covalent bioconjugation of these SERS labels cannot prevent blocking of the antigen recognition sites of the antibody. We present a rational chemical design for SERS label-antibody conjugates which addresses this issue. Highly sensitive, silica-coated gold nanoparticle clusters as SERS labels are non-covalently conjugated to primary antibodies by using the chimeric protein A/G, which selectively recognizes the Fc part of antibodies and therefore prevents blocking of the antigen recognition sites. In proof-of-concept two-color imaging experiments for the co-localization of p63 and PSA on non-neoplastic prostate tissue FFPE specimens, we demonstrate the specificity and signal brightness of these rationally designed primary antibody-protein A/G-gold nanocluster conjugates. Electronic supplementary information (ESI) available. See DOI: 10.1039/c3nr05890e

Towards novel therapeutics for HIV through fragment-based screening and drug design.

PubMed

Tiefendbrunn, Theresa; Stout, C David

2014-01-01

Fragment-based drug discovery has been applied with varying levels of success to a number of proteins involved in the HIV (Human Immunodeficiency Virus) life cycle. Fragment-based approaches have led to the discovery of novel binding sites within protease, reverse transcriptase, integrase, and gp41. Novel compounds that bind to known pockets within CCR5 have also been identified via fragment screening, and a fragment-based approach to target the TAR-Tat interaction was explored. In the context of HIV-1 reverse transcriptase (RT), fragment-based approaches have yielded fragment hits with mid-μM activity in an in vitro activity assay, as well as fragment hits that are active against drug-resistant variants of RT. Fragment-based drug discovery is a powerful method to elucidate novel binding sites within proteins, and the method has had significant success in the context of HIV proteins.

Automated production of plant-based vaccines and pharmaceuticals.

PubMed

Wirz, Holger; Sauer-Budge, Alexis F; Briggs, John; Sharpe, Aaron; Shu, Sudong; Sharon, Andre

2012-12-01

A fully automated "factory" was developed that uses tobacco plants to produce large quantities of vaccines and other therapeutic biologics within weeks. This first-of-a-kind factory takes advantage of a plant viral vector technology to produce specific proteins within the leaves of rapidly growing plant biomass. The factory's custom-designed robotic machines plant seeds, nurture the growing plants, introduce a viral vector that directs the plant to produce a target protein, and harvest the biomass once the target protein has accumulated in the plants-all in compliance with Food and Drug Administration (FDA) guidelines (e.g., current Good Manufacturing Practices). The factory was designed to be time, cost, and space efficient. The plants are grown in custom multiplant trays. Robots ride up and down a track, servicing the plants and delivering the trays from the lighted, irrigated growth modules to each processing station as needed. Using preprogrammed robots and processing equipment eliminates the need for human contact, preventing potential contamination of the process and economizing the operation. To quickly produce large quantities of protein-based medicines, we transformed a laboratory-based biological process and scaled it into an industrial process. This enables quick, safe, and cost-effective vaccine production that would be required in case of a pandemic.

Gold nanoparticles-based electrochemical method for the detection of protein kinase with a peptide-like inhibitor as the bioreceptor

PubMed Central

Sun, Kai; Chang, Yong; Zhou, Binbin; Wang, Xiaojin; Liu, Lin

2017-01-01

This article presents a general method for the detection of protein kinase with a peptide-like kinase inhibitor as the bioreceptor, and it was done by converting gold nanoparticles (AuNPs)-based colorimetric assay into sensitive electrochemical analysis. In the colorimetric assay, the kinase-specific aptameric peptide triggered the aggregation of AuNPs in solution. However, the specific binding of peptide to the target protein (kinase) inhibited its ability to trigger the assembly of AuNPs. In the electrochemical analysis, peptides immobilized on a gold electrode and presented as solution triggered together the in situ formation of AuNPs-based network architecture on the electrode surface. Nevertheless, the formation of peptide–kinase complex on the electrode surface made the peptide-triggered AuNPs assembly difficult. Electrochemical impedance spectroscopy was used to measure the change in surface property in the binding events. When a ferrocene-labeled peptide (Fc-peptide) was used in this design, the network of AuNPs/Fc-peptide produced a good voltammetric signal. The competitive assay allowed for the detection of protein kinase A with a detection limit of 20 mU/mL. This work should be valuable for designing novel optical or electronic biosensors and likely lead to many detection applications. PMID:28331314

Chemical synthesis and X-ray structure of a heterochiral {D-protein antagonist plus vascular endothelial growth factor} protein complex by racemic crystallography.

PubMed

Mandal, Kalyaneswar; Uppalapati, Maruti; Ault-Riché, Dana; Kenney, John; Lowitz, Joshua; Sidhu, Sachdev S; Kent, Stephen B H

2012-09-11

Total chemical synthesis was used to prepare the mirror image (D-protein) form of the angiogenic protein vascular endothelial growth factor (VEGF-A). Phage display against D-VEGF-A was used to screen designed libraries based on a unique small protein scaffold in order to identify a high affinity ligand. Chemically synthesized D- and L- forms of the protein ligand showed reciprocal chiral specificity in surface plasmon resonance binding experiments: The L-protein ligand bound only to D-VEGF-A, whereas the D-protein ligand bound only to L-VEGF-A. The D-protein ligand, but not the L-protein ligand, inhibited the binding of natural VEGF(165) to the VEGFR1 receptor. Racemic protein crystallography was used to determine the high resolution X-ray structure of the heterochiral complex consisting of {D-protein antagonist + L-protein form of VEGF-A}. Crystallization of a racemic mixture of these synthetic proteins in appropriate stoichiometry gave a racemic protein complex of more than 73 kDa containing six synthetic protein molecules. The structure of the complex was determined to a resolution of 1.6 Å. Detailed analysis of the interaction between the D-protein antagonist and the VEGF-A protein molecule showed that the binding interface comprised a contact surface area of approximately 800 Å(2) in accord with our design objectives, and that the D-protein antagonist binds to the same region of VEGF-A that interacts with VEGFR1-domain 2.

Characterization of extended channel bioreactors for continuous-flow protein production

DOE PAGES

Timm, Andrea C.; Shankles, Peter G.; Foster, Carmen M.; ...

2015-10-02

In this paper, protein based therapeutics are an important class of drugs, used to treat a variety of medical conditions including cancer and autoimmune diseases. Requiring continuous cold storage, and having a limited shelf life, the ability to produce such therapeutics at the point-of-care would open up new opportunities in distributing medicines and treating patients in more remote locations. Here, the authors describe the first steps in the development of a microfluidic platform that can be used for point-of-care protein synthesis. While biologic medicines, including therapeutic proteins, are commonly produced using recombinant deoxyribonucleic acid (DNA) technology in large batch cellmore » cultures, the system developed here utilizes cell-free protein synthesis (CFPS) technology. CFPS is a scalable technology that uses cell extracts containing the biological machinery required for transcription and translation and combines those extracts with DNA, encoding a specific gene, and the additional metabolites required to produce proteins in vitro. While CFPS reactions are typically performed in batch or fed-batch reactions, a well-engineered reaction scheme may improve both the rate of protein production and the economic efficiency of protein synthesis reactions, as well as enable a more streamlined method for subsequent purification of the protein product—all necessary requirements for point-of-care protein synthesis. In this work, the authors describe a new bioreactor design capable of continuous production of protein using cell-free protein synthesis. The bioreactors were designed with three inlets to separate reactive components prior to on-chip mixing, which lead into a long, narrow, serpentine channel. These multiscale, serpentine channel bioreactors were designed to take advantage of microscale diffusion distances across narrow channels in reactors containing enough volume to produce a therapeutic dose of protein, and open the possibility of performing these reactions continuously and in line with downstream purification modules. Here, the authors demonstrate the capability to produce protein over time with continuous-flow reactions and examine basic design features and operation specifications fundamental to continuous microfluidic protein synthesis.« less

Medicinal Chemistry Projects Requiring Imaginative Structure-Based Drug Design Methods.

PubMed

Moitessier, Nicolas; Pottel, Joshua; Therrien, Eric; Englebienne, Pablo; Liu, Zhaomin; Tomberg, Anna; Corbeil, Christopher R

2016-09-20

Computational methods for docking small molecules to proteins are prominent in drug discovery. There are hundreds, if not thousands, of documented examples-and several pertinent cases within our research program. Fifteen years ago, our first docking-guided drug design project yielded nanomolar metalloproteinase inhibitors and illustrated the potential of structure-based drug design. Subsequent applications of docking programs to the design of integrin antagonists, BACE-1 inhibitors, and aminoglycosides binding to bacterial RNA demonstrated that available docking programs needed significant improvement. At that time, docking programs primarily considered flexible ligands and rigid proteins. We demonstrated that accounting for protein flexibility, employing displaceable water molecules, and using ligand-based pharmacophores improved the docking accuracy of existing methods-enabling the design of bioactive molecules. The success prompted the development of our own program, Fitted, implementing all of these aspects. The primary motivation has always been to respond to the needs of drug design studies; the majority of the concepts behind the evolution of Fitted are rooted in medicinal chemistry projects and collaborations. Several examples follow: (1) Searching for HDAC inhibitors led us to develop methods considering drug-zinc coordination and its effect on the pKa of surrounding residues. (2) Targeting covalent prolyl oligopeptidase (POP) inhibitors prompted an update to Fitted to identify reactive groups and form bonds with a given residue (e.g., a catalytic residue) when the geometry allows it. Fitted-the first fully automated covalent docking program-was successfully applied to the discovery of four new classes of covalent POP inhibitors. As a result, efficient stereoselective syntheses of a few screening hits were prioritized rather than synthesizing large chemical libraries-yielding nanomolar inhibitors. (3) In order to study the metabolism of POP inhibitors by cytochrome P450 enzymes (CYPs)-for toxicology studies-the program Impacts was derived from Fitted and helped us to reveal a complex metabolism with unforeseen stereocenter isomerizations. These efforts, combined with those of other docking software developers, have strengthened our understanding of the complex drug-protein binding process while providing the medicinal chemistry community with useful tools that have led to drug discoveries. In this Account, we describe our contributions over the past 15 years-within their historical context-to the design of drug candidates, including BACE-1 inhibitors, POP covalent inhibitors, G-quadruplex binders, and aminoglycosides binding to nucleic acids. We also remark the necessary developments of docking programs, specifically Fitted, that enabled structure-based design to flourish and yielded multiple fruitful, rational medicinal chemistry campaigns.

Modular protein switches derived from antibody mimetic proteins.

PubMed

Nicholes, N; Date, A; Beaujean, P; Hauk, P; Kanwar, M; Ostermeier, M

2016-02-01

Protein switches have potential applications as biosensors and selective protein therapeutics. Protein switches built by fusion of proteins with the prerequisite input and output functions are currently developed using an ad hoc process. A modular switch platform in which existing switches could be readily adapted to respond to any ligand would be advantageous. We investigated the feasibility of a modular protein switch platform based on fusions of the enzyme TEM-1 β-lactamase (BLA) with two different antibody mimetic proteins: designed ankyrin repeat proteins (DARPins) and monobodies. We created libraries of random insertions of the gene encoding BLA into genes encoding a DARPin or a monobody designed to bind maltose-binding protein (MBP). From these libraries, we used a genetic selection system for β-lactamase activity to identify genes that conferred MBP-dependent ampicillin resistance to Escherichia coli. Some of these selected genes encoded switch proteins whose enzymatic activity increased up to 14-fold in the presence of MBP. We next introduced mutations into the antibody mimetic domain of these switches that were known to cause binding to different ligands. To different degrees, introduction of the mutations resulted in switches with the desired specificity, illustrating the potential modularity of these platforms. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Random heteropolymers preserve protein function in foreign environments

NASA Astrophysics Data System (ADS)

Panganiban, Brian; Qiao, Baofu; Jiang, Tao; DelRe, Christopher; Obadia, Mona M.; Nguyen, Trung Dac; Smith, Anton A. A.; Hall, Aaron; Sit, Izaac; Crosby, Marquise G.; Dennis, Patrick B.; Drockenmuller, Eric; Olvera de la Cruz, Monica; Xu, Ting

2018-03-01

The successful incorporation of active proteins into synthetic polymers could lead to a new class of materials with functions found only in living systems. However, proteins rarely function under the conditions suitable for polymer processing. On the basis of an analysis of trends in protein sequences and characteristic chemical patterns on protein surfaces, we designed four-monomer random heteropolymers to mimic intrinsically disordered proteins for protein solubilization and stabilization in non-native environments. The heteropolymers, with optimized composition and statistical monomer distribution, enable cell-free synthesis of membrane proteins with proper protein folding for transport and enzyme-containing plastics for toxin bioremediation. Controlling the statistical monomer distribution in a heteropolymer, rather than the specific monomer sequence, affords a new strategy to interface with biological systems for protein-based biomaterials.

Crystal structure of an EfPDF complex with Met-Ala-Ser based on crystallographic packing.

PubMed

Nam, Ki Hyun; Kim, Kook-Han; Kim, Eunice Eun Kyeong; Hwang, Kwang Yeon

2009-04-17

PDF (peptide deformylase) plays a critical role in the production of mature proteins by removing the N-formyl polypeptide of nascent proteins in the prokaryote cell system. This protein is essential for bacterial growth, making it an attractive target for the design of new antibiotics. Accordingly, PDF has been evaluated as a drug target; however, architectural mechanism studies of PDF have not yet fully elucidated its molecular function. We recently reported the crystal structure of PDF produced by Enterococcus faecium [K.H. Nam, J.I. Ham, A. Priyadarshi, E.E. Kim, N. Chung, K.Y. Hwang, "Insight into the antibacterial drug design and architectural mechanism of peptide recognition from the E. faecium peptide deformylase structure", Proteins 74 (2009) 261-265]. Here, we present the crystal structure of the EfPDF complex with MAS (Met-Ser-Ala), thereby not only delineating the architectural mechanism for the recognition of mimic-peptides by N-terminal cleaved expression peptide, but also suggesting possible targets for rational design of antibacterial drugs. In addition to their implications for drug design, these structural studies will facilitate elucidation of the architectural mechanism responsible for the peptide recognition of PDF.

Feed additive production by fermentation of herb Polygonum hydropiper L. and cassava pulp with simultaneous flavonoid dissolution.

PubMed

Song, Zhen-Tao; Zhu, Ming-Jun

2017-03-01

Fermentation of herb Polygonum hydropiper L. (PHL) and cassava pulp (CP) for feed additive production with simultaneous flavonoid dissolution was investigated, and a two-stage response surface methodology (RSM) based on Plackett-Burman factorial design (PB design) was used to optimize the flavonoid dissolution and protein content. Using the screening function of PB design, four different significant factors for the two response variables were acquired: factors A (CP) and B (PHL) for the flavonoid dissolution versus factors G (inoculum size) and H (fermentation time) for protein content. Then, two RSMs were used sequentially to improve the values of the two response variables separately. The mutual corroboration of the experimental results in the present study confirmed the validity of the associated experimental design. The validation experiment showed a flavonoid dissolution rate of 94.00%, and a protein content of 18.20%, gaining an increase in 21.20% and 199.10% over the control, respectively. The present study confirms the feasibility of feed additive production by Saccharomyces cerevisiae with CP and PHL and simultaneous optimization of flavonoid dissolution and protein content using a two-stage RSM. © 2016 International Union of Biochemistry and Molecular Biology, Inc.

Computational 3D structures of drug-targeting proteins in the 2009-H1N1 influenza A virus

NASA Astrophysics Data System (ADS)

Du, Qi-Shi; Wang, Shu-Qing; Huang, Ri-Bo; Chou, Kuo-Chen

2010-01-01

The neuraminidase (NA) and M2 proton channel of influenza virus are the drug-targeting proteins, based on which several drugs were developed. However these once powerful drugs encountered drug-resistant problem to the H5N1 and H1N1 flu. To address this problem, the computational 3D structures of NA and M2 proteins of 2009-H1N1 influenza virus were built using the molecular modeling technique and computational chemistry method. Based on the models the structure features of NA and M2 proteins were analyzed, the docking structures of drug-protein complexes were computed, and the residue mutations were annotated. The results may help to solve the drug-resistant problem and stimulate designing more effective drugs against 2009-H1N1 influenza pandemic.

Identifying essential proteins based on sub-network partition and prioritization by integrating subcellular localization information.

PubMed

Li, Min; Li, Wenkai; Wu, Fang-Xiang; Pan, Yi; Wang, Jianxin

2018-06-14

Essential proteins are important participants in various life activities and play a vital role in the survival and reproduction of living organisms. Identification of essential proteins from protein-protein interaction (PPI) networks has great significance to facilitate the study of human complex diseases, the design of drugs and the development of bioinformatics and computational science. Studies have shown that highly connected proteins in a PPI network tend to be essential. A series of computational methods have been proposed to identify essential proteins by analyzing topological structures of PPI networks. However, the high noise in the PPI data can degrade the accuracy of essential protein prediction. Moreover, proteins must be located in the appropriate subcellular localization to perform their functions, and only when the proteins are located in the same subcellular localization, it is possible that they can interact with each other. In this paper, we propose a new network-based essential protein discovery method based on sub-network partition and prioritization by integrating subcellular localization information, named SPP. The proposed method SPP was tested on two different yeast PPI networks obtained from DIP database and BioGRID database. The experimental results show that SPP can effectively reduce the effect of false positives in PPI networks and predict essential proteins more accurately compared with other existing computational methods DC, BC, CC, SC, EC, IC, NC. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Designed Peptide Targets Two Types of Modifications of p53 with Anti-cancer Activity.

PubMed

Liang, Lunxi; Wang, Huanbin; Shi, Hubing; Li, Zhaoli; Yao, Han; Bu, Zhigao; Song, Ningning; Li, Chushu; Xiang, Dabin; Zhang, Yao; Wang, Jilin; Hu, Ye; Xu, Qi; Ma, Yanlei; Cheng, Zhongyi; Wang, Yingchao; Zhao, Shuliang; Qian, Jin; Chen, Yingxuan; Fang, Jing-Yuan; Xu, Jie

2018-06-21

Many cancer-related proteins are controlled by composite post-translational modifications (PTMs), but prevalent strategies only target one type of modification. Here we describe a designed peptide that controls two types of modifications of the p53 tumor suppressor, based on the discovery of a protein complex that suppresses p53 (suppresome). We found that Morn3, a cancer-testis antigen, recruits different PTM enzymes, such as sirtuin deacetylase and ubiquitin ligase, to confer composite modifications on p53. The molecular functions of Morn3 were validated through in vivo assays and chemico-biological intervention. A rationally designed Morn3-targeting peptide (Morncide) successfully activated p53 and suppressed tumor growth. These findings shed light on the regulation of protein PTMs and present a strategy for targeting two modifications with one molecule. Copyright © 2018 Elsevier Ltd. All rights reserved.

Dynamics Govern Specificity of a Protein-Protein Interface: Substrate Recognition by Thrombin

PubMed Central

Fuchs, Julian E.; Huber, Roland G.; Waldner, Birgit J.; Kahler, Ursula; von Grafenstein, Susanne; Kramer, Christian; Liedl, Klaus R.

2015-01-01

Biomolecular recognition is crucial in cellular signal transduction. Signaling is mediated through molecular interactions at protein-protein interfaces. Still, specificity and promiscuity of protein-protein interfaces cannot be explained using simplistic static binding models. Our study rationalizes specificity of the prototypic protein-protein interface between thrombin and its peptide substrates relying solely on binding site dynamics derived from molecular dynamics simulations. We find conformational selection and thus dynamic contributions to be a key player in biomolecular recognition. Arising entropic contributions complement chemical intuition primarily reflecting enthalpic interaction patterns. The paradigm “dynamics govern specificity” might provide direct guidance for the identification of specific anchor points in biomolecular recognition processes and structure-based drug design. PMID:26496636

Rational design of a colorimetric pH sensor from a soluble retinoic acid chaperone.

PubMed

Berbasova, Tetyana; Nosrati, Meisam; Vasileiou, Chrysoula; Wang, Wenjing; Lee, Kin Sing Stephen; Yapici, Ipek; Geiger, James H; Borhan, Babak

2013-10-30

Reengineering of cellular retinoic acid binding protein II (CRABPII) to be capable of binding retinal as a protonated Schiff base is described. Through rational alterations of the binding pocket, electrostatic perturbations of the embedded retinylidene chromophore that favor delocalization of the iminium charge lead to exquisite control in the regulation of chromophoric absorption properties, spanning the visible spectrum (474-640 nm). The pKa of the retinylidene protonated Schiff base was modulated from 2.4 to 8.1, giving rise to a set of proteins of varying colors and pH sensitivities. These proteins were used to demonstrate a concentration-independent, ratiometric pH sensor.

Towards microfluidic reactors for cell-free protein synthesis at the point-of-care

DOE PAGES

Timm, Andrea C.; Shankles, Peter G.; Foster, Carmen M.; ...

2015-12-22

Cell-free protein synthesis (CFPS) is a powerful technology that allows for optimization of protein production without maintenance of a living system. Integrated within micro- and nano-fluidic architectures, CFPS can be optimized for point-of care use. Here, we describe the development of a microfluidic bioreactor designed to facilitate the production of a single-dose of a therapeutic protein, in a small footprint device at the point-of-care. This new design builds on the use of a long, serpentine channel bioreactor and is enhanced by integrating a nanofabricated membrane to allow exchange of materials between parallel reactor and feeder channels. This engineered membrane facilitatesmore » the exchange of metabolites, energy, and inhibitory species, prolonging the CFPS reaction and increasing protein yield. Membrane permeability can be altered by plasma-enhanced chemical vapor deposition and atomic layer deposition to tune the exchange rate of small molecules. This allows for extended reaction times and improved yields. Further, the reaction product and higher molecular weight components of the transcription/translation machinery in the reactor channel can be retained. As a result, we show that the microscale bioreactor design produces higher protein yields than conventional tube-based batch formats, and that product yields can be dramatically improved by facilitating small molecule exchange within the dual-channel bioreactor.« less

Towards microfluidic reactors for cell-free protein synthesis at the point-of-care

DOE Office of Scientific and Technical Information (OSTI.GOV)

Timm, Andrea C.; Shankles, Peter G.; Foster, Carmen M.

Cell-free protein synthesis (CFPS) is a powerful technology that allows for optimization of protein production without maintenance of a living system. Integrated within micro- and nano-fluidic architectures, CFPS can be optimized for point-of care use. Here, we describe the development of a microfluidic bioreactor designed to facilitate the production of a single-dose of a therapeutic protein, in a small footprint device at the point-of-care. This new design builds on the use of a long, serpentine channel bioreactor and is enhanced by integrating a nanofabricated membrane to allow exchange of materials between parallel reactor and feeder channels. This engineered membrane facilitatesmore » the exchange of metabolites, energy, and inhibitory species, prolonging the CFPS reaction and increasing protein yield. Membrane permeability can be altered by plasma-enhanced chemical vapor deposition and atomic layer deposition to tune the exchange rate of small molecules. This allows for extended reaction times and improved yields. Further, the reaction product and higher molecular weight components of the transcription/translation machinery in the reactor channel can be retained. As a result, we show that the microscale bioreactor design produces higher protein yields than conventional tube-based batch formats, and that product yields can be dramatically improved by facilitating small molecule exchange within the dual-channel bioreactor.« less

Applying graph theory to protein structures: an atlas of coiled coils.

PubMed

Heal, Jack W; Bartlett, Gail J; Wood, Christopher W; Thomson, Andrew R; Woolfson, Derek N

2018-05-02

To understand protein structure, folding and function fully and to design proteins de novo reliably, we must learn from natural protein structures that have been characterised experimentally. The number of protein structures available is large and growing exponentially, which makes this task challenging. Indeed, computational resources are becoming increasingly important for classifying and analysing this resource. Here, we use tools from graph theory to define an atlas classification scheme for automatically categorising certain protein substructures. Focusing on the α-helical coiled coils, which are ubiquitous protein-structure and protein-protein interaction motifs, we present a suite of computational resources designed for analysing these assemblies. iSOCKET enables interactive analysis of side-chain packing within proteins to identify coiled coils automatically and with considerable user control. Applying a graph theory-based atlas classification scheme to structures identified by iSOCKET gives the Atlas of Coiled Coils, a fully automated, updated overview of extant coiled coils. The utility of this approach is illustrated with the first formal classification of an emerging subclass of coiled coils called α-helical barrels. Furthermore, in the Atlas, the known coiled-coil universe is presented alongside a partial enumeration of the 'dark matter' of coiled-coil structures; i.e., those coiled-coil architectures that are theoretically possible but have not been observed to date, and thus present defined targets for protein design. iSOCKET is available as part of the open-source GitHub repository associated with this work (https://github.com/woolfson-group/isocket). This repository also contains all the data generated when classifying the protein graphs. The Atlas of Coiled Coils is available at: http://coiledcoils.chm.bris.ac.uk/atlas/app.

Fibrinogen and fibrin based micro and nano scaffolds incorporated with drugs, proteins, cells and genes for therapeutic biomedical applications

PubMed Central

Rajangam, Thanavel; An, Seong Soo A

2013-01-01

Over the past two decades, many types of natural and synthetic polymer-based micro- and nanocarriers, with exciting properties and applications, have been developed for application in various types of tissue regeneration, including bone, cartilage, nerve, blood vessels, and skin. The development of suitable polymers scaffold designs to aid the repair of specific cell types have created diverse and important potentials in tissue restoration. Fibrinogen (Fbg)- and fibrin (Fbn)-based micro- and nanostructures can provide suitable natural matrix environments. Since these primary materials are abundantly available in blood as the main coagulation proteins, they can easily interact with damaged tissues and cells through native biochemical interactions. Fbg- and Fbn-based micro and nanostructures can also be consecutively furnished/or encapsulated and specifically delivered, with multiple growth factors, proteins, and stem cells, in structures designed to aid in specific phases of the tissue regeneration process. The present review has been carried out to demonstrate the progress made with micro and nanoscaffold applications and features a number of applications of Fbg- and Fbn-based carriers in the field of biomaterials, including the delivery of drugs, active biomolecules, cells, and genes, that have been effectively used in tissue engineering and regenerative medicine. PMID:24106425

Automated clustering of probe molecules from solvent mapping of protein surfaces: new algorithms applied to hot-spot mapping and structure-based drug design

NASA Astrophysics Data System (ADS)

Lerner, Michael G.; Meagher, Kristin L.; Carlson, Heather A.

2008-10-01

Use of solvent mapping, based on multiple-copy minimization (MCM) techniques, is common in structure-based drug discovery. The minima of small-molecule probes define locations for complementary interactions within a binding pocket. Here, we present improved methods for MCM. In particular, a Jarvis-Patrick (JP) method is outlined for grouping the final locations of minimized probes into physical clusters. This algorithm has been tested through a study of protein-protein interfaces, showing the process to be robust, deterministic, and fast in the mapping of protein "hot spots." Improvements in the initial placement of probe molecules are also described. A final application to HIV-1 protease shows how our automated technique can be used to partition data too complicated to analyze by hand. These new automated methods may be easily and quickly extended to other protein systems, and our clustering methodology may be readily incorporated into other clustering packages.

Protein Structure and Function: An Interdisciplinary Multimedia-Based Guided-Inquiry Education Module for the High School Science Classroom

ERIC Educational Resources Information Center

Bethel, Casey M.; Lieberman, Raquel L.

2014-01-01

Here we present a multidisciplinary educational unit intended for general, advanced placement, or international baccalaureate-level high school science, focused on the three-dimensional structure of proteins and their connection to function and disease. The lessons are designed within the framework of the Next Generation Science Standards to make…

ProteMiner-SSM: a web server for efficient analysis of similar protein tertiary substructures.

PubMed

Chang, Darby Tien-Hau; Chen, Chien-Yu; Chung, Wen-Chin; Oyang, Yen-Jen; Juan, Hsueh-Fen; Huang, Hsuan-Cheng

2004-07-01

Analysis of protein-ligand interactions is a fundamental issue in drug design. As the detailed and accurate analysis of protein-ligand interactions involves calculation of binding free energy based on thermodynamics and even quantum mechanics, which is highly expensive in terms of computing time, conformational and structural analysis of proteins and ligands has been widely employed as a screening process in computer-aided drug design. In this paper, a web server called ProteMiner-SSM designed for efficient analysis of similar protein tertiary substructures is presented. In one experiment reported in this paper, the web server has been exploited to obtain some clues about a biochemical hypothesis. The main distinction in the software design of the web server is the filtering process incorporated to expedite the analysis. The filtering process extracts the residues located in the caves of the protein tertiary structure for analysis and operates with O(nlogn) time complexity, where n is the number of residues in the protein. In comparison, the alpha-hull algorithm, which is a widely used algorithm in computer graphics for identifying those instances that are on the contour of a three-dimensional object, features O(n2) time complexity. Experimental results show that the filtering process presented in this paper is able to speed up the analysis by a factor ranging from 3.15 to 9.37 times. The ProteMiner-SSM web server can be found at http://proteminer.csie.ntu.edu.tw/. There is a mirror site at http://p4.sbl.bc.sinica.edu.tw/proteminer/.

Lessons learned in induced fit docking and metadynamics in the Drug Design Data Resource Grand Challenge 2

NASA Astrophysics Data System (ADS)

Baumgartner, Matthew P.; Evans, David A.

2018-01-01

Two of the major ongoing challenges in computational drug discovery are predicting the binding pose and affinity of a compound to a protein. The Drug Design Data Resource Grand Challenge 2 was developed to address these problems and to drive development of new methods. The challenge provided the 2D structures of compounds for which the organizers help blinded data in the form of 35 X-ray crystal structures and 102 binding affinity measurements and challenged participants to predict the binding pose and affinity of the compounds. We tested a number of pose prediction methods as part of the challenge; we found that docking methods that incorporate protein flexibility (Induced Fit Docking) outperformed methods that treated the protein as rigid. We also found that using binding pose metadynamics, a molecular dynamics based method, to score docked poses provided the best predictions of our methods with an average RMSD of 2.01 Å. We tested both structure-based (e.g. docking) and ligand-based methods (e.g. QSAR) in the affinity prediction portion of the competition. We found that our structure-based methods based on docking with Smina (Spearman ρ = 0.614), performed slightly better than our ligand-based methods (ρ = 0.543), and had equivalent performance with the other top methods in the competition. Despite the overall good performance of our methods in comparison to other participants in the challenge, there exists significant room for improvement especially in cases such as these where protein flexibility plays such a large role.

Thermodynamically balanced inside-out (TBIO) PCR-based gene synthesis: a novel method of primer design for high-fidelity assembly of longer gene sequences

PubMed Central

Gao, Xinxin; Yo, Peggy; Keith, Andrew; Ragan, Timothy J.; Harris, Thomas K.

2003-01-01

A novel thermodynamically-balanced inside-out (TBIO) method of primer design was developed and compared with a thermodynamically-balanced conventional (TBC) method of primer design for PCR-based gene synthesis of codon-optimized gene sequences for the human protein kinase B-2 (PKB2; 1494 bp), p70 ribosomal S6 subunit protein kinase-1 (S6K1; 1622 bp) and phosphoinositide-dependent protein kinase-1 (PDK1; 1712 bp). Each of the 60mer TBIO primers coded for identical nucleotide regions that the 60mer TBC primers covered, except that half of the TBIO primers were reverse complement sequences. In addition, the TBIO and TBC primers contained identical regions of temperature- optimized primer overlaps. The TBC method was optimized to generate sequential overlapping fragments (∼0.4–0.5 kb) for each of the gene sequences, and simultaneous and sequential combinations of overlapping fragments were tested for their ability to be assembled under an array of PCR conditions. However, no fully synthesized gene sequences could be obtained by this approach. In contrast, the TBIO method generated an initial central fragment (∼0.4–0.5 kb), which could be gel purified and used for further inside-out bidirectional elongation by additional increments of 0.4–0.5 kb. By using the newly developed TBIO method of PCR-based gene synthesis, error-free synthetic genes for the human protein kinases PKB2, S6K1 and PDK1 were obtained with little or no corrective mutagenesis. PMID:14602936

A combination of feature extraction methods with an ensemble of different classifiers for protein structural class prediction problem.

PubMed

Dehzangi, Abdollah; Paliwal, Kuldip; Sharma, Alok; Dehzangi, Omid; Sattar, Abdul

2013-01-01

Better understanding of structural class of a given protein reveals important information about its overall folding type and its domain. It can also be directly used to provide critical information on general tertiary structure of a protein which has a profound impact on protein function determination and drug design. Despite tremendous enhancements made by pattern recognition-based approaches to solve this problem, it still remains as an unsolved issue for bioinformatics that demands more attention and exploration. In this study, we propose a novel feature extraction model that incorporates physicochemical and evolutionary-based information simultaneously. We also propose overlapped segmented distribution and autocorrelation-based feature extraction methods to provide more local and global discriminatory information. The proposed feature extraction methods are explored for 15 most promising attributes that are selected from a wide range of physicochemical-based attributes. Finally, by applying an ensemble of different classifiers namely, Adaboost.M1, LogitBoost, naive Bayes, multilayer perceptron (MLP), and support vector machine (SVM) we show enhancement of the protein structural class prediction accuracy for four popular benchmarks.

High yield bacterial expression, purification and characterisation of bioactive Human Tousled-like Kinase 1B involved in cancer.

PubMed

Bhoir, Siddhant; Shaik, Althaf; Thiruvenkatam, Vijay; Kirubakaran, Sivapriya

2018-03-19

Human Tousled-like kinases (TLKs) are highly conserved serine/threonine protein kinases responsible for cell proliferation, DNA repair, and genome surveillance. Their possible involvement in cancer via efficient DNA repair mechanisms have made them clinically relevant molecular targets for anticancer therapy. Innovative approaches in chemical biology have played a key role in validating the importance of kinases as molecular targets. However, the detailed understanding of the protein structure and the mechanisms of protein-drug interaction through biochemical and biophysical techniques demands a method for the production of an active protein of exceptional stability and purity on a large scale. We have designed a bacterial expression system to express and purify biologically active, wild-type Human Tousled-like Kinase 1B (hTLK1B) by co-expression with the protein phosphatase from bacteriophage λ. We have obtained remarkably high amounts of the soluble and homogeneously dephosphorylated form of biologically active hTLK1B with our unique, custom-built vector design strategy. The recombinant hTLK1B can be used for the structural studies and may further facilitate the development of new TLK inhibitors for anti-cancer therapy using a structure-based drug design approach.

Small Scaffolds, Big Potential: Developing Miniature Proteins as Therapeutic Agents.

PubMed

Holub, Justin M

2017-09-01

Preclinical Research Miniature proteins are a class of oligopeptide characterized by their short sequence lengths and ability to adopt well-folded, three-dimensional structures. Because of their biomimetic nature and synthetic tractability, miniature proteins have been used to study a range of biochemical processes including fast protein folding, signal transduction, catalysis and molecular transport. Recently, miniature proteins have been gaining traction as potential therapeutic agents because their small size and ability to fold into defined tertiary structures facilitates their development as protein-based drugs. This research overview discusses emerging developments involving the use of miniature proteins as scaffolds to design novel therapeutics for the treatment and study of human disease. Specifically, this review will explore strategies to: (i) stabilize miniature protein tertiary structure; (ii) optimize biomolecular recognition by grafting functional epitopes onto miniature protein scaffolds; and (iii) enhance cytosolic delivery of miniature proteins through the use of cationic motifs that facilitate endosomal escape. These objectives are discussed not only to address challenges in developing effective miniature protein-based drugs, but also to highlight the tremendous potential miniature proteins hold for combating and understanding human disease. Drug Dev Res 78 : 268-282, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Artificial neural networks for efficient clustering of conformational ensembles and their potential for medicinal chemistry.

PubMed

Pandini, Alessandro; Fraccalvieri, Domenico; Bonati, Laura

2013-01-01

The biological function of proteins is strictly related to their molecular flexibility and dynamics: enzymatic activity, protein-protein interactions, ligand binding and allosteric regulation are important mechanisms involving protein motions. Computational approaches, such as Molecular Dynamics (MD) simulations, are now routinely used to study the intrinsic dynamics of target proteins as well as to complement molecular docking approaches. These methods have also successfully supported the process of rational design and discovery of new drugs. Identification of functionally relevant conformations is a key step in these studies. This is generally done by cluster analysis of the ensemble of structures in the MD trajectory. Recently Artificial Neural Network (ANN) approaches, in particular methods based on Self-Organising Maps (SOMs), have been reported performing more accurately and providing more consistent results than traditional clustering algorithms in various data-mining problems. In the specific case of conformational analysis, SOMs have been successfully used to compare multiple ensembles of protein conformations demonstrating a potential in efficiently detecting the dynamic signatures central to biological function. Moreover, examples of the use of SOMs to address problems relevant to other stages of the drug-design process, including clustering of docking poses, have been reported. In this contribution we review recent applications of ANN algorithms in analysing conformational and structural ensembles and we discuss their potential in computer-based approaches for medicinal chemistry.

Development of an automated large-scale protein-crystallization and monitoring system for high-throughput protein-structure analyses.

PubMed

Hiraki, Masahiko; Kato, Ryuichi; Nagai, Minoru; Satoh, Tadashi; Hirano, Satoshi; Ihara, Kentaro; Kudo, Norio; Nagae, Masamichi; Kobayashi, Masanori; Inoue, Michio; Uejima, Tamami; Oda, Shunichiro; Chavas, Leonard M G; Akutsu, Masato; Yamada, Yusuke; Kawasaki, Masato; Matsugaki, Naohiro; Igarashi, Noriyuki; Suzuki, Mamoru; Wakatsuki, Soichi

2006-09-01

Protein crystallization remains one of the bottlenecks in crystallographic analysis of macromolecules. An automated large-scale protein-crystallization system named PXS has been developed consisting of the following subsystems, which proceed in parallel under unified control software: dispensing precipitants and protein solutions, sealing crystallization plates, carrying robot, incubators, observation system and image-storage server. A sitting-drop crystallization plate specialized for PXS has also been designed and developed. PXS can set up 7680 drops for vapour diffusion per hour, which includes time for replenishing supplies such as disposable tips and crystallization plates. Images of the crystallization drops are automatically recorded according to a preprogrammed schedule and can be viewed by users remotely using web-based browser software. A number of protein crystals were successfully produced and several protein structures could be determined directly from crystals grown by PXS. In other cases, X-ray quality crystals were obtained by further optimization by manual screening based on the conditions found by PXS.

Quantum mechanics implementation in drug-design workflows: does it really help?

PubMed

Arodola, Olayide A; Soliman, Mahmoud Es

2017-01-01

The pharmaceutical industry is progressively operating in an era where development costs are constantly under pressure, higher percentages of drugs are demanded, and the drug-discovery process is a trial-and-error run. The profit that flows in with the discovery of new drugs has always been the motivation for the industry to keep up the pace and keep abreast with the endless demand for medicines. The process of finding a molecule that binds to the target protein using in silico tools has made computational chemistry a valuable tool in drug discovery in both academic research and pharmaceutical industry. However, the complexity of many protein-ligand interactions challenges the accuracy and efficiency of the commonly used empirical methods. The usefulness of quantum mechanics (QM) in drug-protein interaction cannot be overemphasized; however, this approach has little significance in some empirical methods. In this review, we discuss recent developments in, and application of, QM to medically relevant biomolecules. We critically discuss the different types of QM-based methods and their proposed application to incorporating them into drug-design and -discovery workflows while trying to answer a critical question: are QM-based methods of real help in drug-design and -discovery research and industry?

Stacking interactions in PUF-RNA complexes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yiling Koh, Yvonne; Wang, Yeming; Qiu, Chen

2012-07-02

Stacking interactions between amino acids and bases are common in RNA-protein interactions. Many proteins that regulate mRNAs interact with single-stranded RNA elements in the 3' UTR (3'-untranslated region) of their targets. PUF proteins are exemplary. Here we focus on complexes formed between a Caenorhabditis elegans PUF protein, FBF, and its cognate RNAs. Stacking interactions are particularly prominent and involve every RNA base in the recognition element. To assess the contribution of stacking interactions to formation of the RNA-protein complex, we combine in vivo selection experiments with site-directed mutagenesis, biochemistry, and structural analysis. Our results reveal that the identities of stackingmore » amino acids in FBF affect both the affinity and specificity of the RNA-protein interaction. Substitutions in amino acid side chains can restrict or broaden RNA specificity. We conclude that the identities of stacking residues are important in achieving the natural specificities of PUF proteins. Similarly, in PUF proteins engineered to bind new RNA sequences, the identity of stacking residues may contribute to 'target' versus 'off-target' interactions, and thus be an important consideration in the design of proteins with new specificities.« less

NMR screening in fragment-based drug design: a practical guide.

PubMed

Kim, Hai-Young; Wyss, Daniel F

2015-01-01

Fragment-based drug design (FBDD) comprises both fragment-based screening (FBS) to find hits and elaboration of these hits to lead compounds. Typical fragment hits have lower molecular weight (<300-350 Da) and lower initial potency but higher ligand efficiency when compared to those from high-throughput screening. NMR spectroscopy has been widely used for FBDD since it identifies and localizes the binding site of weakly interacting hits on the target protein. Here we describe ligand-based NMR methods for hit identification from fragment libraries and for functional cross-validation of primary hits.

F2Dock: Fast Fourier Protein-Protein Docking

PubMed Central

Bajaj, Chandrajit; Chowdhury, Rezaul; Siddavanahalli, Vinay

2009-01-01

The functions of proteins is often realized through their mutual interactions. Determining a relative transformation for a pair of proteins and their conformations which form a stable complex, reproducible in nature, is known as docking. It is an important step in drug design, structure determination and understanding function and structure relationships. In this paper we extend our non-uniform fast Fourier transform docking algorithm to include an adaptive search phase (both translational and rotational) and thereby speed up its execution. We have also implemented a multithreaded version of the adaptive docking algorithm for even faster execution on multicore machines. We call this protein-protein docking code F2Dock (F2 = Fast Fourier). We have calibrated F2Dock based on an extensive experimental study on a list of benchmark complexes and conclude that F2Dock works very well in practice. Though all docking results reported in this paper use shape complementarity and Coulombic potential based scores only, F2Dock is structured to incorporate Lennard-Jones potential and re-ranking docking solutions based on desolvation energy. PMID:21071796

Cullin3 - BTB Interface: A Novel Target for Stapled Peptides

PubMed Central

Palmieri, Maddalena; Balasco, Nicole; Esposito, Luciana; Russo, Luigi; Mazzà, Daniela; Di Marcotullio, Lucia; Di Gaetano, Sonia; Malgieri, Gaetano; Vitagliano, Luigi; Pedone, Emilia; Zaccaro, Laura

2015-01-01

Cullin3 (Cul3), a key factor of protein ubiquitination, is able to interact with dozens of different proteins containing a BTB (Bric-a-brac, Tramtrack and Broad Complex) domain. We here targeted the Cul3–BTB interface by using the intriguing approach of stabilizing the α-helical conformation of Cul3-based peptides through the “stapling” with a hydrocarbon cross-linker. In particular, by combining theoretical and experimental techniques, we designed and characterized stapled Cul3-based peptides embedding the helix 2 of the protein (residues 49–68). Intriguingly, CD and NMR experiments demonstrate that these stapled peptides were able to adopt the helical structure that the fragment assumes in the parent protein. We also show that some of these peptides were able to bind to the BTB of the tetrameric KCTD11, a substrate adaptor involved in HDAC1 degradation, with high affinity (~ 300–600 nM). Cul3-derived staple peptides are also able to bind the BTB of the pentameric KCTD5. Interestingly, the affinity of these peptides is of the same order of magnitude of that reported for the interaction of full-length Cul3 with some BTB containing proteins. Moreover, present data indicate that stapling endows these peptides with an increased serum stability. Altogether, these findings indicate that the designed stapled peptides can efficiently mimic protein-protein interactions and are potentially able to modulate fundamental biological processes involving Cul3. PMID:25848797

CHIPMUNK: A Virtual Synthesizable Small-Molecule Library for Medicinal Chemistry, Exploitable for Protein-Protein Interaction Modulators.

PubMed

Humbeck, Lina; Weigang, Sebastian; Schäfer, Till; Mutzel, Petra; Koch, Oliver

2018-03-20

A common issue during drug design and development is the discovery of novel scaffolds for protein targets. On the one hand the chemical space of purchasable compounds is rather limited; on the other hand artificially generated molecules suffer from a grave lack of accessibility in practice. Therefore, we generated a novel virtual library of small molecules which are synthesizable from purchasable educts, called CHIPMUNK (CHemically feasible In silico Public Molecular UNiverse Knowledge base). Altogether, CHIPMUNK covers over 95 million compounds and encompasses regions of the chemical space that are not covered by existing databases. The coverage of CHIPMUNK exceeds the chemical space spanned by the Lipinski rule of five to foster the exploration of novel and difficult target classes. The analysis of the generated property space reveals that CHIPMUNK is well suited for the design of protein-protein interaction inhibitors (PPIIs). Furthermore, a recently developed structural clustering algorithm (StruClus) for big data was used to partition the sub-libraries into meaningful subsets and assist scientists to process the large amount of data. These clustered subsets also contain the target space based on ChEMBL data which was included during clustering. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimization of phase feeding of starter, grower, and finisher diets for male broilers by mixture experimental design: forty-eight-day production period.

PubMed

Roush, W B; Boykin, D; Branton, S L

2004-08-01

A mixture experiment, a variant of response surface methodology, was designed to determine the proportion of time to feed broiler starter (23% protein), grower (20% protein), and finisher (18% protein) diets to optimize production and processing variables based on a total production time of 48 d. Mixture designs are useful for proportion problems where the components of the experiment (i.e., length of time the diets were fed) add up to a unity (48 d). The experiment was conducted with day-old male Ross x Ross broiler chicks. The birds were placed 50 birds per pen in each of 60 pens. The experimental design was a 10-point augmented simplex-centroid (ASC) design with 6 replicates of each point. Each design point represented the portion(s) of the 48 d that each of the diets was fed. Formulation of the diets was based on NRC standards. At 49 d, each pen of birds was evaluated for production data including BW, feed conversion, and cost of feed consumed. Then, 6 birds were randomly selected from each pen for processing data. Processing variables included live weight, hot carcass weight, dressing percentage, fat pad percentage, and breast yield (pectoralis major and pectoralis minor weights). Production and processing data were fit to simplex regression models. Model terms determined not to be significant (P > 0.05) were removed. The models were found to be statistically adequate for analysis of the response surfaces. A compromise solution was calculated based on optimal constraints designated for the production and processing data. The results indicated that broilers fed a starter and finisher diet for 30 and 18 d, respectively, would meet the production and processing constraints. Trace plots showed that the production and processing variables were not very sensitive to the grower diet.

Protein design to understand peptide ligand recognition by tetratricopeptide repeat proteins.

PubMed

Cortajarena, Aitziber L; Kajander, Tommi; Pan, Weilan; Cocco, Melanie J; Regan, Lynne

2004-04-01

Protein design aims to understand the fundamentals of protein structure by creating novel proteins with pre-specified folds. An equally important goal is to understand protein function by creating novel proteins with pre-specified activities. Here we describe the design and characterization of a tetratricopeptide (TPR) protein, which binds to the C-terminal peptide of the eukaryotic chaperone Hsp90. The design emphasizes the importance of both direct, short-range protein-peptide interactions and of long-range electrostatic optimization. We demonstrate that the designed protein binds specifically to the desired peptide and discriminates between it and the similar C-terminal peptide of Hsp70.

Development of a Novel Six-Month Nutrition Intervention for a Randomized Trial in Older Men with Mobility Limitations.

PubMed

Apovian, C M; Singer, M R; Campbell, W W; Bhasin, S; McCarthy, A C; Shah, M; Basaria, S; Moore, L L

2017-01-01

Nutrition impacts the development of sarcopenia and protein intake is an important modulator of skeletal muscle mass loss in older people. The Optimizing Protein Intake in Older Men with Mobility Limitation (OPTIMEN) Trial was designed to assess the independent and combined effects of higher protein intake and a promyogenic agent, testosterone, on lean body mass, muscle strength and physical function in older men with mobility disability. The purpose of this paper is to describe the experimental design and nutrition intervention, including techniques used by research dietitians to develop and deliver energy and protein-specific meals to the homes of community-dwelling participants. Strategies to enhance long-term dietary compliance are detailed. Randomized, double-blind, placebo-controlled six-month intervention trial. Participants were recruited from Boston MA USA and surrounding communities. Older men who were mobility-limited (Short Physical Performance Battery (SPPB) 3-10) and consuming less protein (<0.83 g/kg/day) were recruited for this study. Here we report the successful implementation of a double-blind, placebo-controlled, parallel group, randomized controlled trial with a 6-month intervention period among community-living men, age 65 years and older with a mobility limitation. A controlled feeding plan was used to deliver required energy intakes and prescribed protein quantities of 0.8 or 1.3 grams/kilogram/day (g/kg/d) in three meals plus snacks and supplements. A 2x2 factorial design was used to assess the effects of protein level alone and in combination with testosterone (vs. placebo) on changes in lean body mass (primary outcome), muscle strength, and physical function. A total of 154 men met the eligibility criteria; 112 completed a 2-week run-in period designed to evaluate compliance with the nutrition intervention. Of these, 92 subjects met compliance eligibility criteria and agreed to be randomized; 85% completed the full trial. The study successfully delivered three meals per day to subjects, with a high degree of compliance and subject satisfaction. Overall self-reported compliance rates were 80% and 93% for the meals and supplements, respectively. Details of compliance strategies are discussed. This community-based study design may serve as a model for longer-term nutritional interventions requiring monitoring of dietary compliance in a home-based feeding and supplementation trial.

Show Yourself, Asparaginase: An Enzymatic Reaction Explained through a Hands-On Interactive Activity

PubMed Central

2017-01-01

Determining the catalytic activity of an enzyme can be the perfect method for its identification, for example during purification procedures or for isolation purposes. Herein, we used a pharmaceutically relevant protein to bring the concept of enzymatic activity to the classroom. We designed a hands-on interactive activity in which a medically relevant enzyme, asparaginase, was distinguished from a nonenzymatic protein based on its specific enzymatic activity. The experiment was carried out in the classroom, designed to impact different educational levels from elementary to high school. Our main purposes were to promote the emerging field of protein-based drugs as a source of scientific careers in bionanotechnology and to show the students an image of a “scientist” as that of a common and educated person working in an exciting profession. In addition of being inexpensive, this activity proved to be adaptable for various educational levels and can be easily implemented in different scenarios, for example, scientific fairs, some schools, and so forth. PMID:29599566

Empirical Estimation of Local Dielectric Constants: Toward Atomistic Design of Collagen Mimetic Peptides

PubMed Central

Pike, Douglas H.; Nanda, Vikas

2017-01-01

One of the key challenges in modeling protein energetics is the treatment of solvent interactions. This is particularly important in the case of peptides, where much of the molecule is highly exposed to solvent due to its small size. In this study, we develop an empirical method for estimating the local dielectric constant based on an additive model of atomic polarizabilities. Calculated values match reported apparent dielectric constants for a series of Staphylococcus aureus nuclease mutants. Calculated constants are used to determine screening effects on Coulombic interactions and to determine solvation contributions based on a modified Generalized Born model. These terms are incorporated into the protein modeling platform protCAD, and benchmarked on a data set of collagen mimetic peptides for which experimentally determined stabilities are available. Computing local dielectric constants using atomistic protein models and the assumption of additive atomic polarizabilities is a rapid and potentially useful method for improving electrostatics and solvation calculations that can be applied in the computational design of peptides. PMID:25784456

Engineering growth factors for regenerative medicine applications.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mitchell, Aaron C.; Briquez, Priscilla S.; Hubbell, Jeffrey A.

Growth factors are important morphogenetic proteins that instruct cell behavior and guide tissue repair and renewal. Although their therapeutic potential holds great promise in regenerative medicine applications, translation of growth factors into clinical treatments has been hindered by limitations including poor protein stability, low recombinant expression yield, and suboptimal efficacy. This review highlights current tools, technologies, and approaches to design integrated and effective growth factor-based therapies for regenerative medicine applications. The first section describes rational and combinatorial protein engineering approaches that have been utilized to improve growth factor stability, expression yield, biodistribution, and serum half-life, or alter their cell traffickingmore » behavior or receptor binding affinity. The second section highlights elegant biomaterial-based systems, inspired by the natural extracellular matrix milieu, that have been developed for effective spatial and temporal delivery of growth factors to cell surface receptors. Although appearing distinct, these two approaches are highly complementary and involve principles of molecular design and engineering to be considered in parallel when developing optimal materials for clinical applications.« less

Protein thermal stability enhancement by designing salt bridges: a combined computational and experimental study.

PubMed

Lee, Chi-Wen; Wang, Hsiu-Jung; Hwang, Jenn-Kang; Tseng, Ching-Ping

2014-01-01

Protein thermal stability is an important factor considered in medical and industrial applications. Many structural characteristics related to protein thermal stability have been elucidated, and increasing salt bridges is considered as one of the most efficient strategies to increase protein thermal stability. However, the accurate simulation of salt bridges remains difficult. In this study, a novel method for salt-bridge design was proposed based on the statistical analysis of 10,556 surface salt bridges on 6,493 X-ray protein structures. These salt bridges were first categorized based on pairing residues, secondary structure locations, and Cα-Cα distances. Pairing preferences generalized from statistical analysis were used to construct a salt-bridge pair index and utilized in a weighted electrostatic attraction model to find the effective pairings for designing salt bridges. The model was also coupled with B-factor, weighted contact number, relative solvent accessibility, and conservation prescreening to determine the residues appropriate for the thermal adaptive design of salt bridges. According to our method, eight putative salt-bridges were designed on a mesophilic β-glucosidase and 24 variants were constructed to verify the predictions. Six putative salt-bridges leaded to the increase of the enzyme thermal stability. A significant increase in melting temperature of 8.8, 4.8, 3.7, 1.3, 1.2, and 0.7°C of the putative salt-bridges N437K-D49, E96R-D28, E96K-D28, S440K-E70, T231K-D388, and Q277E-D282 was detected, respectively. Reversing the polarity of T231K-D388 to T231D-D388K resulted in a further increase in melting temperatures by 3.6°C, which may be caused by the transformation of an intra-subunit electrostatic interaction into an inter-subunit one depending on the local environment. The combination of the thermostable variants (N437K, E96R, T231D and D388K) generated a melting temperature increase of 15.7°C. Thus, this study demonstrated a novel method for the thermal adaptive design of salt bridges through inference of suitable positions and substitutions.

Poly(oligoethylene glycol methacrylate) dip-coating: turning cellulose paper into a protein-repellent platform for biosensors.

PubMed

Deng, Xudong; Smeets, Niels M B; Sicard, Clémence; Wang, Jingyun; Brennan, John D; Filipe, Carlos D M; Hoare, Todd

2014-09-17

The passivation of nonspecific protein adsorption to paper is a major barrier to the use of paper as a platform for microfluidic bioassays. Herein we describe a simple, scalable protocol based on adsorption and cross-linking of poly(oligoethylene glycol methacrylate) (POEGMA) derivatives that reduces nonspecific adsorption of a range of proteins to filter paper by at least 1 order of magnitude without significantly changing the fiber morphology or paper macroporosity. A lateral-flow test strip coated with POEGMA facilitates effective protein transport while also confining the colorimetric reporting signal for easier detection, giving improved performance relative to bovine serum albumin (BSA)-blocked paper. Enzyme-linked immunosorbent assays based on POEGMA-coated paper also achieve lower blank values, higher sensitivities, and lower detection limits relative to ones based on paper blocked with BSA or skim milk. We anticipate that POEGMA-coated paper can function as a platform for the design of portable, disposable, and low-cost paper-based biosensors.

Production in Pichia pastoris of protein-based polymers with small heterodimer-forming blocks.

PubMed

Domeradzka, Natalia E; Werten, Marc W T; de Vries, Renko; de Wolf, Frits A

2016-05-01

Some combinations of leucine zipper peptides are capable of forming α-helical heterodimeric coiled coils with very high affinity. These can be used as physical cross-linkers in the design of protein-based polymers that form supramolecular structures, for example hydrogels, upon mixing solutions containing the complementary blocks. Such two-component physical networks are of interest for many applications in biomedicine, pharmaceutics, and diagnostics. This article describes the efficient secretory production of A and B type leucine zipper peptides fused to protein-based polymers in Pichia pastoris. By adjusting the fermentation conditions, we were able to significantly reduce undesirable proteolytic degradation. The formation of A-B heterodimers in mixtures of the purified products was confirmed by size exclusion chromatography. Our results demonstrate that protein-based polymers incorporating functional heterodimer-forming blocks can be produced with P. pastoris in sufficient quantities for use in future supramolecular self-assembly studies and in various applications. © 2015 Wiley Periodicals, Inc.

Computational approaches for rational design of proteins with novel functionalities

PubMed Central

Tiwari, Manish Kumar; Singh, Ranjitha; Singh, Raushan Kumar; Kim, In-Won; Lee, Jung-Kul

2012-01-01

Proteins are the most multifaceted macromolecules in living systems and have various important functions, including structural, catalytic, sensory, and regulatory functions. Rational design of enzymes is a great challenge to our understanding of protein structure and physical chemistry and has numerous potential applications. Protein design algorithms have been applied to design or engineer proteins that fold, fold faster, catalyze, catalyze faster, signal, and adopt preferred conformational states. The field of de novo protein design, although only a few decades old, is beginning to produce exciting results. Developments in this field are already having a significant impact on biotechnology and chemical biology. The application of powerful computational methods for functional protein designing has recently succeeded at engineering target activities. Here, we review recently reported de novo functional proteins that were developed using various protein design approaches, including rational design, computational optimization, and selection from combinatorial libraries, highlighting recent advances and successes. PMID:24688643

DARPin-Based Crystallization Chaperones Exploit Molecular Geometry as a Screening Dimension in Protein Crystallography.

PubMed

Batyuk, Alexander; Wu, Yufan; Honegger, Annemarie; Heberling, Matthew M; Plückthun, Andreas

2016-04-24

DARPin libraries, based on a Designed Ankyrin Repeat Protein consensus framework, are a rich source of binding partners for a wide variety of proteins. Their modular structure, stability, ease of in vitro selection and high production yields make DARPins an ideal starting point for further engineering. The X-ray structures of around 30 different DARPin complexes demonstrate their ability to facilitate crystallization of their target proteins by restricting flexibility and preventing undesired interactions of the target molecule. However, their small size (18 kDa), very hydrophilic surface and repetitive structure can limit the DARPins' ability to provide essential crystal contacts and their usefulness as a search model for addressing the crystallographic phase problem in molecular replacement. To optimize DARPins for their application as crystallization chaperones, rigid domain-domain fusions of the DARPins to larger proteins, proven to yield high-resolution crystal structures, were generated. These fusions were designed in such a way that they affect only one of the terminal capping repeats of the DARPin and do not interfere with residues involved in target binding, allowing to exchange at will the binding specificities of the DARPin in the fusion construct. As a proof of principle, we designed rigid fusions of a stabilized version of Escherichia coli TEM-1 β-lactamase to the C-terminal capping repeat of various DARPins in six different relative domain orientations. Five crystal structures representing four different fusion constructs, alone or in complex with the cognate target, show the predicted relative domain orientations and prove the validity of the concept. Copyright © 2016 Elsevier Ltd. All rights reserved.

Closing the door on flaviviruses: entry as a target for antiviral drug design.

PubMed

Perera, Rushika; Khaliq, Mansoora; Kuhn, Richard J

2008-10-01

With the emergence and rapid spread of West Nile virus in the United States since 1999, and the 50-100 million infections per year caused by dengue virus globally, the threat of flaviviruses as re-emerging human pathogens has become a reality. To support the efforts that are currently being pursued to develop effective vaccines against these viruses, researchers are also actively pursuing the development of small molecule compounds that target various aspects of the virus life cycle. Recent advances in the structural characterization of the flaviviruses have provided a strong foundation towards these efforts. These studies have provided the pseudo-atomic structures of virions from several members of the genus as well as atomic resolution structures of several viral proteins. Most importantly, these studies have highlighted specific structural rearrangements that occur within the virion that are necessary for the virus to complete its life cycle. These rearrangements occur when the virus must transition from immature, to mature, to fusion-active states and rely heavily on the conformational flexibility of the envelope (E) protein that forms the outer glycoprotein shell of the virus. Analysis of these conformational changes can suggest promising targets for structure-based antiviral design. For instance, by targeting the flexibility of the E protein, it might be possible to inhibit required rearrangements of this protein and trap the virus in a specific state. This would interfere with a productive flaviviral infection. This review presents a structural perspective of the flavivirus life cycle and focuses on the role of the E protein as an opportune target for structure-based antiviral drug design.

A strategy for detecting the conservation of folding-nucleus residues in protein superfamilies.

PubMed

Michnick, S W; Shakhnovich, E

1998-01-01

Nucleation-growth theory predicts that fast-folding peptide sequences fold to their native structure via structures in a transition-state ensemble that share a small number of native contacts (the folding nucleus). Experimental and theoretical studies of proteins suggest that residues participating in folding nuclei are conserved among homologs. We attempted to determine if this is true in proteins with highly diverged sequences but identical folds (superfamilies). We describe a strategy based on comparisons of residue conservation in natural superfamily sequences with simulated sequences (generated with a Monte-Carlo sequence design strategy) for the same proteins. The basic assumptions of the strategy were that natural sequences will conserve residues needed for folding and stability plus function, the simulated sequences contain no functional conservation, and nucleus residues make native contacts with each other. Based on these assumptions, we identified seven potential nucleus residues in ubiquitin superfamily members. Non-nucleus conserved residues were also identified; these are proposed to be involved in stabilizing native interactions. We found that all superfamily members conserved the same potential nucleus residue positions, except those for which the structural topology is significantly different. Our results suggest that the conservation of the nucleus of a specific fold can be predicted by comparing designed simulated sequences with natural highly diverged sequences that fold to the same structure. We suggest that such a strategy could be used to help plan protein folding and design experiments, to identify new superfamily members, and to subdivide superfamilies further into classes having a similar folding mechanism.

Sampling and energy evaluation challenges in ligand binding protein design

PubMed Central

Dou, Jiayi; Doyle, Lindsey; Jr. Greisen, Per; Schena, Alberto; Park, Hahnbeom; Johnsson, Kai; Stoddard, Barry L.

2017-01-01

Abstract The steroid hormone 17α‐hydroxylprogesterone (17‐OHP) is a biomarker for congenital adrenal hyperplasia and hence there is considerable interest in development of sensors for this compound. We used computational protein design to generate protein models with binding sites for 17‐OHP containing an extended, nonpolar, shape‐complementary binding pocket for the four‐ring core of the compound, and hydrogen bonding residues at the base of the pocket to interact with carbonyl and hydroxyl groups at the more polar end of the ligand. Eight of 16 designed proteins experimentally tested bind 17‐OHP with micromolar affinity. A co‐crystal structure of one of the designs revealed that 17‐OHP is rotated 180° around a pseudo‐two‐fold axis in the compound and displays multiple binding modes within the pocket, while still interacting with all of the designed residues in the engineered site. Subsequent rounds of mutagenesis and binding selection improved the ligand affinity to nanomolar range, while appearing to constrain the ligand to a single bound conformation that maintains the same “flipped” orientation relative to the original design. We trace the discrepancy in the design calculations to two sources: first, a failure to model subtle backbone changes which alter the distribution of sidechain rotameric states and second, an underestimation of the energetic cost of desolvating the carbonyl and hydroxyl groups of the ligand. The difference between design model and crystal structure thus arises from both sampling limitations and energy function inaccuracies that are exacerbated by the near two‐fold symmetry of the molecule. PMID:28980354

Molecular tandem repeat strategy for elucidating mechanical properties of high-strength proteins

PubMed Central

Jung, Huihun; Pena-Francesch, Abdon; Saadat, Alham; Sebastian, Aswathy; Kim, Dong Hwan; Hamilton, Reginald F.; Albert, Istvan; Allen, Benjamin D.; Demirel, Melik C.

2016-01-01

Many globular and structural proteins have repetitions in their sequences or structures. However, a clear relationship between these repeats and their contribution to the mechanical properties remains elusive. We propose a new approach for the design and production of synthetic polypeptides that comprise one or more tandem copies of a single unit with distinct amorphous and ordered regions. Our designed sequences are based on a structural protein produced in squid suction cups that has a segmented copolymer structure with amorphous and crystalline domains. We produced segmented polypeptides with varying repeat number, while keeping the lengths and compositions of the amorphous and crystalline regions fixed. We showed that mechanical properties of these synthetic proteins could be tuned by modulating their molecular weights. Specifically, the toughness and extensibility of synthetic polypeptides increase as a function of the number of tandem repeats. This result suggests that the repetitions in native squid proteins could have a genetic advantage for increased toughness and flexibility. PMID:27222581

Exploring protein kinase conformation using swarm-enhanced sampling molecular dynamics.

PubMed

Atzori, Alessio; Bruce, Neil J; Burusco, Kepa K; Wroblowski, Berthold; Bonnet, Pascal; Bryce, Richard A

2014-10-27

Protein plasticity, while often linked to biological function, also provides opportunities for rational design of selective and potent inhibitors of their function. The application of computational methods to the prediction of concealed protein concavities is challenging, as the motions involved can be significant and occur over long time scales. Here we introduce the swarm-enhanced sampling molecular dynamics (sesMD) method as a tool to improve sampling of conformational landscapes. In this approach, a swarm of replica simulations interact cooperatively via a set of pairwise potentials incorporating attractive and repulsive components. We apply the sesMD approach to explore the conformations of the DFG motif in the protein p38α mitogen-activated protein kinase. In contrast to multiple MD simulations, sesMD trajectories sample a range of DFG conformations, some of which map onto existing crystal structures. Simulated structures intermediate between the DFG-in and DFG-out conformations are predicted to have druggable pockets of interest for structure-based ligand design.

Self-Assembled Protein Nanofilter for Trapping Polysulfides and Promoting Li+ Transport in Lithium-Sulfur Batteries.

PubMed

Fu, Xuewei; Li, Chunhui; Wang, Yu; Scudiero, Louis; Liu, Jin; Zhong, Wei-Hong

2018-05-17

The diffusion of polysulfides in lithium-sulfur (Li-S) batteries represents a critical issue deteriorating the electrochemical performance. Here, borrowing the concepts from air filtration, we design and fabricate a protein-based nanofilter for effectively trapping polysulfides but facilitating Li + transport. The unique porous structures are formed through a protein-directed self-assembly process, and the surfaces are functionalized by the protein residues. The experiments and molecular simulation results demonstrate that our polysulfide nanofilter can effectively trap the dissolved polysulfides and promote Li + transport in Li-S batteries. When the polysulfide nanofilter is added in a Li-S battery, the electrochemical performance of the battery is significantly improved. Moreover, the contribution of the protein nanofilter to the ion transport is further analyzed by correlating filter properties and battery performance. This study is of universal significance for the understanding, design, and fabrication of advanced battery interlayers that can help realize good management of the ion transport inside advanced energy storage devices.

Design of sweet protein based sweeteners: hints from structure-function relationships.

PubMed

Rega, Michele Fortunato; Di Monaco, Rossella; Leone, Serena; Donnarumma, Federica; Spadaccini, Roberta; Cavella, Silvana; Picone, Delia

2015-04-15

Sweet proteins represent a class of natural molecules, which are extremely interesting regarding their potential use as safe low-calories sweeteners for individuals who need to control sugar intake, such as obese or diabetic subjects. Punctual mutations of amino acid residues of MNEI, a single chain derivative of the natural sweet protein monellin, allow the modulation of its taste. In this study we present a structural and functional comparison between MNEI and a sweeter mutant Y65R, containing an extra positive charge on the protein surface, in conditions mimicking those of typical beverages. Y65R exhibits superior sweetness in all the experimental conditions tested, has a better solubility at mild acidic pH and preserves a significant thermal stability in a wide range of pH conditions, although slightly lower than MNEI. Our findings confirm the advantages of structure-guided protein engineering to design improved low-calorie sweeteners and excipients for food and pharmaceutical preparations. Copyright © 2014 Elsevier Ltd. All rights reserved.

The synergistic use of computation, chemistry and biology to discover novel peptide-based drugs: the time is right.

PubMed

Audie, J; Boyd, C

2010-01-01

The case for peptide-based drugs is compelling. Due to their chemical, physical and conformational diversity, and relatively unproblematic toxicity and immunogenicity, peptides represent excellent starting material for drug discovery. Nature has solved many physiological and pharmacological problems through the use of peptides, polypeptides and proteins. If nature could solve such a diversity of challenging biological problems through the use of peptides, it seems reasonable to infer that human ingenuity will prove even more successful. And this, indeed, appears to be the case, as a number of scientific and methodological advances are making peptides and peptide-based compounds ever more promising pharmacological agents. Chief among these advances are powerful chemical and biological screening technologies for lead identification and optimization, methods for enhancing peptide in vivo stability, bioavailability and cell-permeability, and new delivery technologies. Other advances include the development and experimental validation of robust computational methods for peptide lead identification and optimization. Finally, scientific analysis, biology and chemistry indicate the prospect of designing relatively small peptides to therapeutically modulate so-called 'undruggable' protein-protein interactions. Taken together a clear picture is emerging: through the synergistic use of the scientific imagination and the computational, chemical and biological methods that are currently available, effective peptide therapeutics for novel targets can be designed that surpass even the proven peptidic designs of nature.

Visualization portal for genetic variation (VizGVar): a tool for interactive visualization of SNPs and somatic mutations in exons, genes and protein domains.

PubMed

Solano-Román, Antonio; Alfaro-Arias, Verónica; Cruz-Castillo, Carlos; Orozco-Solano, Allan

2018-03-15

VizGVar was designed to meet the growing need of the research community for improved genomic and proteomic data viewers that benefit from better information visualization. We implemented a new information architecture and applied user centered design principles to provide a new improved way of visualizing genetic information and protein data related to human disease. VizGVar connects the entire database of Ensembl protein motifs, domains, genes and exons with annotated SNPs and somatic variations from PharmGKB and COSMIC. VizGVar precisely represents genetic variations and their respective location by colored curves to designate different types of variations. The structured hierarchy of biological data is reflected in aggregated patterns through different levels, integrating several layers of information at once. VizGVar provides a new interactive, web-based JavaScript visualization of somatic mutations and protein variation, enabling fast and easy discovery of clinically relevant variation patterns. VizGVar is accessible at http://vizport.io/vizgvar; http://vizport.io/vizgvar/doc/. asolano@broadinstitute.org or allan.orozcosolano@ucr.ac.cr.

Molecular Dynamics Driven Design of pH-Stabilized Mutants of MNEI, a Sweet Protein.

PubMed

Leone, Serena; Picone, Delia

2016-01-01

MNEI is a single chain derivative of monellin, a plant protein that can interact with the human sweet taste receptor, being therefore perceived as sweet. This unusual physiological activity makes MNEI a potential template for the design of new sugar replacers for the food and beverage industry. Unfortunately, applications of MNEI have been so far limited by its intrinsic sensitivity to some pH and temperature conditions, which could occur in industrial processes. Changes in physical parameters can, in fact, lead to irreversible protein denaturation, as well as aggregation and precipitation. It has been previously shown that the correlation between pH and stability in MNEI derives from the presence of a single glutamic residue in a hydrophobic pocket of the protein. We have used molecular dynamics to study the consequences, at the atomic level, of the protonation state of such residue and have identified the network of intramolecular interactions responsible for MNEI stability at acidic pH. Based on this information, we have designed a pH-independent, stabilized mutant of MNEI and confirmed its increased stability by both molecular modeling and experimental techniques.

PL-PatchSurfer: a novel molecular local surface-based method for exploring protein-ligand interactions.

PubMed

Hu, Bingjie; Zhu, Xiaolei; Monroe, Lyman; Bures, Mark G; Kihara, Daisuke

2014-08-27

Structure-based computational methods have been widely used in exploring protein-ligand interactions, including predicting the binding ligands of a given protein based on their structural complementarity. Compared to other protein and ligand representations, the advantages of a surface representation include reduced sensitivity to subtle changes in the pocket and ligand conformation and fast search speed. Here we developed a novel method named PL-PatchSurfer (Protein-Ligand PatchSurfer). PL-PatchSurfer represents the protein binding pocket and the ligand molecular surface as a combination of segmented surface patches. Each patch is characterized by its geometrical shape and the electrostatic potential, which are represented using the 3D Zernike descriptor (3DZD). We first tested PL-PatchSurfer on binding ligand prediction and found it outperformed the pocket-similarity based ligand prediction program. We then optimized the search algorithm of PL-PatchSurfer using the PDBbind dataset. Finally, we explored the utility of applying PL-PatchSurfer to a larger and more diverse dataset and showed that PL-PatchSurfer was able to provide a high early enrichment for most of the targets. To the best of our knowledge, PL-PatchSurfer is the first surface patch-based method that treats ligand complementarity at protein binding sites. We believe that using a surface patch approach to better understand protein-ligand interactions has the potential to significantly enhance the design of new ligands for a wide array of drug-targets.

PL-PatchSurfer: A Novel Molecular Local Surface-Based Method for Exploring Protein-Ligand Interactions

PubMed Central

Hu, Bingjie; Zhu, Xiaolei; Monroe, Lyman; Bures, Mark G.; Kihara, Daisuke

2014-01-01

Structure-based computational methods have been widely used in exploring protein-ligand interactions, including predicting the binding ligands of a given protein based on their structural complementarity. Compared to other protein and ligand representations, the advantages of a surface representation include reduced sensitivity to subtle changes in the pocket and ligand conformation and fast search speed. Here we developed a novel method named PL-PatchSurfer (Protein-Ligand PatchSurfer). PL-PatchSurfer represents the protein binding pocket and the ligand molecular surface as a combination of segmented surface patches. Each patch is characterized by its geometrical shape and the electrostatic potential, which are represented using the 3D Zernike descriptor (3DZD). We first tested PL-PatchSurfer on binding ligand prediction and found it outperformed the pocket-similarity based ligand prediction program. We then optimized the search algorithm of PL-PatchSurfer using the PDBbind dataset. Finally, we explored the utility of applying PL-PatchSurfer to a larger and more diverse dataset and showed that PL-PatchSurfer was able to provide a high early enrichment for most of the targets. To the best of our knowledge, PL-PatchSurfer is the first surface patch-based method that treats ligand complementarity at protein binding sites. We believe that using a surface patch approach to better understand protein-ligand interactions has the potential to significantly enhance the design of new ligands for a wide array of drug-targets. PMID:25167137

Selection of specific interactors from phage display library based on sea lamprey variable lymphocyte receptor sequences.

PubMed

Wezner-Ptasinska, Magdalena; Otlewski, Jacek

2015-12-01

Variable lymphocyte receptors (VLRs) are non-immunoglobulin components of adaptive immunity in jawless vertebrates. These proteins composed of leucine-rich repeat modules offer some advantages over antibodies in target binding and therefore are attractive candidates for biotechnological applications. In this paper we report the design and characterization of a phage display library based on a previously proposed dVLR scaffold containing six LRR modules [Wezner-Ptasinska et al., 2011]. Our library was designed based on a consensus approach in which the randomization scheme reflects the frequencies of amino acids naturally occurring in respective positions responsible for antigen recognition. We demonstrate general applicability of the scaffold by selecting dVLRs specific for lysozyme and S100A7 protein with KD values in the micromolar range. The dVLR library could be used as a convenient alternative to antibodies for effective isolation of high affinity binders.

A hybrid network-based method for the detection of disease-related genes

NASA Astrophysics Data System (ADS)

Cui, Ying; Cai, Meng; Dai, Yang; Stanley, H. Eugene

2018-02-01

Detecting disease-related genes is crucial in disease diagnosis and drug design. The accepted view is that neighbors of a disease-causing gene in a molecular network tend to cause the same or similar diseases, and network-based methods have been recently developed to identify novel hereditary disease-genes in available biomedical networks. Despite the steady increase in the discovery of disease-associated genes, there is still a large fraction of disease genes that remains under the tip of the iceberg. In this paper we exploit the topological properties of the protein-protein interaction (PPI) network to detect disease-related genes. We compute, analyze, and compare the topological properties of disease genes with non-disease genes in PPI networks. We also design an improved random forest classifier based on these network topological features, and a cross-validation test confirms that our method performs better than previous similar studies.

A multiplex protein-free lateral flow assay for detection of microRNAs based on unmodified molecular beacons.

PubMed

Javani, Atefeh; Javadi-Zarnaghi, Fatemeh; Rasaee, Mohammad Javad

2017-11-15

Lateral flow assays (LFAs) have promising potentials for point-of-care applications. Recently, many LFAs have been reported that are based on hybridization of oligonucleotide strands. Mostly, biotinylated capture DNAs are immobilized on the surface of a nitrocellulose membrane via streptavidin interactions. During the assay, stable colorful complexes get formed that are visible by naked eyes. Here, we present an inexpensive and unique design of LFA that applies unmodified oligonucleotides at capture lines. The presented LFA do not utilize streptavidin or any other affinity protein. We employ structural switch of molecular beacons (MB) in combination with base stacking hybridization (BSH) phenomenon. The unique design of the reported LFA provided high selectivity for target oligonucleotides. We validated potential applications of the system for detection of DNA mimics of two microRNAs in multiplex assays. Copyright © 2017 Elsevier Inc. All rights reserved.

Designing protein-based biomaterials for medical applications.

PubMed

Gagner, Jennifer E; Kim, Wookhyun; Chaikof, Elliot L

2014-04-01

Biomaterials produced by nature have been honed through billions of years, evolving exquisitely precise structure-function relationships that scientists strive to emulate. Advances in genetic engineering have facilitated extensive investigations to determine how changes in even a single peptide within a protein sequence can produce biomaterials with unique thermal, mechanical and biological properties. Elastin, a naturally occurring protein polymer, serves as a model protein to determine the relationship between specific structural elements and desirable material characteristics. The modular, repetitive nature of the protein facilitates the formation of well-defined secondary structures with the ability to self-assemble into complex three-dimensional architectures on a variety of length scales. Furthermore, many opportunities exist to incorporate other protein-based motifs and inorganic materials into recombinant protein-based materials, extending the range and usefulness of these materials in potential biomedical applications. Elastin-like polypeptides (ELPs) can be assembled into 3-D architectures with precise control over payload encapsulation, mechanical and thermal properties, as well as unique functionalization opportunities through both genetic and enzymatic means. An overview of current protein-based materials, their properties and uses in biomedicine will be provided, with a focus on the advantages of ELPs. Applications of these biomaterials as imaging and therapeutic delivery agents will be discussed. Finally, broader implications and future directions of these materials as diagnostic and therapeutic systems will be explored. Copyright © 2013 Elsevier Ltd. All rights reserved.

Designing Protein-Based Biomaterials for Medical Applications

PubMed Central

Gagner, Jennifer E.; Kim, Wookhyun; Chaikof, Elliot L.

2013-01-01

Biomaterials produced by nature have been honed through billions of years, evolving exquisitely precise structure-function relationships that scientists strive to emulate. Advances in genetic engineering have facilitated extensive investigations to determine how changes in even a single peptide within a protein sequence can produce biomaterials with unique thermal, mechanical and biological properties. Elastin, a naturally occurring protein polymer, serves as a model protein to determine the relationship between specific structural elements and desirable material characteristics. The modular, repetitive nature of the protein facilitates the formation of well-defined secondary structures with the ability to self-assemble into complex three-dimensional architectures on a variety of length scales. Furthermore, many opportunities exist to incorporate other protein-based motifs and inorganic materials into recombinant protein-based materials, extending the range and usefulness of these materials in potential biomedical applications. Elastin-like polypeptides can be assembled into 3D architectures with precise control over payload encapsulation, mechanical and thermal properties, as well as unique functionalization opportunities through both genetic and enzymatic means. An overview of current protein-based materials, their properties and uses in biomedicine will be provided, with a focus on the advantages of elastin-like polypeptides. Applications of these biomaterials as imaging and therapeutic delivery agents will be discussed. Finally, broader implications and future directions of these materials as diagnostic and therapeutic systems will be explored. PMID:24121196

Structure-based energetics of protein interfaces guide Foot-and-Mouth Disease virus vaccine design

PubMed Central

Scott, Katherine; Burman, Alison; Loureiro, Silvia; Ren, Jingshan; Porta, Claudine; Ginn, Helen M.; Jackson, Terry; Perez-Martin, Eva; Siebert, C. Alistair; Paul, Guntram; Huiskonen, Juha T.; Jones, Ian M.; Esnouf, Robert M.; Fry, Elizabeth E.; Maree, Francois F.; Charleston, Bryan; Stuart, David I.

2018-01-01

Summary Virus capsids are primed for disassembly yet capsid integrity is key to generating a protective immune response. Here we devise a computational method to assess relative stability of protein-protein interfaces and use it to design improved candidate vaccines for two of the least stable, but globally important, serotypes of Foot-and-Mouth Disease virus (FMDV), O and SAT2. FMDV capsids comprise identical pentameric protein subunits held together by tenuous non-covalent interactions, and are often unstable. Chemically inactivated or recombinant empty capsids, which could form the basis of future vaccines, are even less stable than live virus. We use a novel restrained molecular dynamics strategy, to rank mutations predicted to strengthen the pentamer interfaces to produce stabilized capsids. Structural analyses and stability assays confirmed the predictions, and vaccinated animals generated improved neutralising antibody responses to stabilised particles over parental viruses and wild-type capsids. PMID:26389739

Structural basis for activity of highly efficient RNA mimics of green fluorescent protein

PubMed Central

Warner, Katherine Deigan; Chen, Michael C.; Song, Wenjiao; Strack, Rita L.; Thorn, Andrea; Jaffrey, Samie R.; Ferré-D’Amaré, Adrian R.

2014-01-01

Green fluorescent protein (GFP) and its derivatives revolutionized the study of proteins. Spinach is a recently reported in vitro evolved RNA mimic of GFP, which as genetically encoded fusions, makes possible live-cell, real-time imaging of biological RNAs, without resorting to large RNA-binding protein-GFP fusions. To elucidate the molecular basis of Spinach fluorescence, we have solved its co-crystal structure bound to its cognate exogenous chromophore, revealing that Spinach activates the small molecule by immobilizing it between a base triple, a G-quadruplex, and an unpaired guanine. Mutational and NMR analyses indicate that the G-quadruplex is essential for Spinach fluorescence, is also present in other fluorogenic RNAs, and may represent a general strategy for RNAs to induce fluorescence of chromophores. The structure has guided the design of a miniaturized 'Baby Spinach', and provides the foundation for structure-driven design and tuning of fluorescent RNAs. PMID:25026079

Chemical functionalization of bioceramics to enhance endothelial cells adhesion for tissue engineering.

PubMed

Borcard, Françoise; Staedler, Davide; Comas, Horacio; Juillerat, Franziska Krauss; Sturzenegger, Philip N; Heuberger, Roman; Gonzenbach, Urs T; Juillerat-Jeanneret, Lucienne; Gerber-Lemaire, Sandrine

2012-09-27

To control the selective adhesion of human endothelial cells and human serum proteins to bioceramics of different compositions, a multifunctional ligand containing a cyclic arginine-glycine-aspartate (RGD) peptide, a tetraethylene glycol spacer, and a gallate moiety was designed, synthesized, and characterized. The binding of this ligand to alumina-based, hydroxyapatite-based, and calcium phosphate-based bioceramics was demonstrated. The conjugation of this ligand to the bioceramics induced a decrease in the nonselective and integrin-selective binding of human serum proteins, whereas the binding and adhesion of human endothelial cells was enhanced, dependent on the particular bioceramics.

Silk-based delivery systems of bioactive molecules.

PubMed

Numata, Keiji; Kaplan, David L

2010-12-30

Silks are biodegradable, biocompatible, self-assembling proteins that can also be tailored via genetic engineering to contain specific chemical features, offering utility for drug and gene delivery. Silkworm silk has been used in biomedical sutures for decades and has recently achieved Food and Drug Administration approval for expanded biomaterials device utility. With the diversity and control of size, structure and chemistry, modified or recombinant silk proteins can be designed and utilized in various biomedical application, such as for the delivery of bioactive molecules. This review focuses on the biosynthesis and applications of silk-based multi-block copolymer systems and related silk protein drug delivery systems. The utility of these systems for the delivery of small molecule drugs, proteins and genes is reviewed. Copyright © 2010 Elsevier B.V. All rights reserved.

Knowledge-based fragment binding prediction.

PubMed

Tang, Grace W; Altman, Russ B

2014-04-01

Target-based drug discovery must assess many drug-like compounds for potential activity. Focusing on low-molecular-weight compounds (fragments) can dramatically reduce the chemical search space. However, approaches for determining protein-fragment interactions have limitations. Experimental assays are time-consuming, expensive, and not always applicable. At the same time, computational approaches using physics-based methods have limited accuracy. With increasing high-resolution structural data for protein-ligand complexes, there is now an opportunity for data-driven approaches to fragment binding prediction. We present FragFEATURE, a machine learning approach to predict small molecule fragments preferred by a target protein structure. We first create a knowledge base of protein structural environments annotated with the small molecule substructures they bind. These substructures have low-molecular weight and serve as a proxy for fragments. FragFEATURE then compares the structural environments within a target protein to those in the knowledge base to retrieve statistically preferred fragments. It merges information across diverse ligands with shared substructures to generate predictions. Our results demonstrate FragFEATURE's ability to rediscover fragments corresponding to the ligand bound with 74% precision and 82% recall on average. For many protein targets, it identifies high scoring fragments that are substructures of known inhibitors. FragFEATURE thus predicts fragments that can serve as inputs to fragment-based drug design or serve as refinement criteria for creating target-specific compound libraries for experimental or computational screening.

Knowledge-based Fragment Binding Prediction

PubMed Central

Tang, Grace W.; Altman, Russ B.

2014-01-01

Target-based drug discovery must assess many drug-like compounds for potential activity. Focusing on low-molecular-weight compounds (fragments) can dramatically reduce the chemical search space. However, approaches for determining protein-fragment interactions have limitations. Experimental assays are time-consuming, expensive, and not always applicable. At the same time, computational approaches using physics-based methods have limited accuracy. With increasing high-resolution structural data for protein-ligand complexes, there is now an opportunity for data-driven approaches to fragment binding prediction. We present FragFEATURE, a machine learning approach to predict small molecule fragments preferred by a target protein structure. We first create a knowledge base of protein structural environments annotated with the small molecule substructures they bind. These substructures have low-molecular weight and serve as a proxy for fragments. FragFEATURE then compares the structural environments within a target protein to those in the knowledge base to retrieve statistically preferred fragments. It merges information across diverse ligands with shared substructures to generate predictions. Our results demonstrate FragFEATURE's ability to rediscover fragments corresponding to the ligand bound with 74% precision and 82% recall on average. For many protein targets, it identifies high scoring fragments that are substructures of known inhibitors. FragFEATURE thus predicts fragments that can serve as inputs to fragment-based drug design or serve as refinement criteria for creating target-specific compound libraries for experimental or computational screening. PMID:24762971

Structural Chemistry of Human RNA Methyltransferases.

PubMed

Schapira, Matthieu

2016-03-18

RNA methyltransferases (RNMTs) play important roles in RNA stability, splicing, and epigenetic mechanisms. They constitute a promising target class that is underexplored by the medicinal chemistry community. Information of relevance to drug design can be extracted from the rich structural coverage of human RNMTs. In this work, the structural chemistry of this protein family is analyzed in depth. Unlike most methyltransferases, RNMTs generally feature a substrate-binding site that is largely open on the cofactor-binding pocket, favoring the design of bisubstrate inhibitors. Substrate purine or pyrimidines are often sandwiched between hydrophobic walls that can accommodate planar ring systems. When the substrate base is laying on a shallow surface, a 5' flanking base is sometimes anchored in a druggable cavity. The cofactor-binding site is structurally more diverse than in protein methyltransferases and more druggable in SPOUT than in Rossman-fold enzymes. Finally, conformational plasticity observed both at the substrate and cofactor binding sites may be a challenge for structure-based drug design. The landscape drawn here may inform ongoing efforts toward the discovery of the first human RNMT inhibitors.

Custom-designed proteins as novel therapeutic tools? The case of arrestins

PubMed Central

Gurevich, Vsevolod V.; Gurevich, Eugenia V.

2010-01-01

Multiple genetic disorders can be associated with excessive signalling by mutant G-protein-coupled receptors (GPCRs) that are either constitutively active or have lost sites where phosphorylation by GPCR kinases is necessary for desensitisation by cognate arrestins. Phosphorylation-independent arrestin1 can compensate for defects in phosphorylation of the GPCR rhodopsin in retinal rod cells, facilitating recovery, improving light responsiveness, and promoting photoreceptor survival. These proof-of-principle experiments show that, based on mechanistic understanding of the inner workings of a protein, one can modify its functional characteristics to generate custom-designed mutants that improve the balance of signalling in congenital and acquired disorders. Manipulations of arrestin elements responsible for scaffolding mitogen-activated protein kinase cascades and binding other signalling proteins involved in life-or-death decisions in the cell are likely to yield mutants that affect cell survival and proliferation in the desired direction. Although this approach is still in its infancy, targeted redesign of individual functions of many proteins offers a promise of a completely new therapeutic toolbox with huge potential. PMID:20412604

Chemical synthesis and X-ray structure of a heterochiral {D-protein antagonist plus vascular endothelial growth factor} protein complex by racemic crystallography

PubMed Central

Mandal, Kalyaneswar; Uppalapati, Maruti; Ault-Riché, Dana; Kenney, John; Lowitz, Joshua; Sidhu, Sachdev S.; Kent, Stephen B.H.

2012-01-01

Total chemical synthesis was used to prepare the mirror image (D-protein) form of the angiogenic protein vascular endothelial growth factor (VEGF-A). Phage display against D-VEGF-A was used to screen designed libraries based on a unique small protein scaffold in order to identify a high affinity ligand. Chemically synthesized D- and L- forms of the protein ligand showed reciprocal chiral specificity in surface plasmon resonance binding experiments: The L-protein ligand bound only to D-VEGF-A, whereas the D-protein ligand bound only to L-VEGF-A. The D-protein ligand, but not the L-protein ligand, inhibited the binding of natural VEGF165 to the VEGFR1 receptor. Racemic protein crystallography was used to determine the high resolution X-ray structure of the heterochiral complex consisting of {D-protein antagonist + L-protein form ofVEGF-A}. Crystallization of a racemic mixture of these synthetic proteins in appropriate stoichiometry gave a racemic protein complex of more than 73 kDa containing six synthetic protein molecules. The structure of the complex was determined to a resolution of 1.6 Å. Detailed analysis of the interaction between the D-protein antagonist and the VEGF-A protein molecule showed that the binding interface comprised a contact surface area of approximately 800 Å2 in accord with our design objectives, and that the D-protein antagonist binds to the same region of VEGF-A that interacts with VEGFR1-domain 2. PMID:22927390

Drug target identification in protozoan parasites.

PubMed

Müller, Joachim; Hemphill, Andrew

2016-08-01

Despite the fact that diseases caused by protozoan parasites represent serious challenges for public health, animal production and welfare, only a limited panel of drugs has been marketed for clinical applications. Herein, the authors investigate two strategies, namely whole organism screening and target-based drug design. The present pharmacopoeia has resulted from whole organism screening, and the mode of action and targets of selected drugs are discussed. However, the more recent extensive genome sequencing efforts and the development of dry and wet lab genomics and proteomics that allow high-throughput screening of interactions between micromolecules and recombinant proteins has resulted in target-based drug design as the predominant focus in anti-parasitic drug development. Selected examples of target-based drug design studies are presented, and calcium-dependent protein kinases, important drug targets in apicomplexan parasites, are discussed in more detail. Despite the enormous efforts in target-based drug development, this approach has not yet generated market-ready antiprotozoal drugs. However, whole-organism screening approaches, comprising of both in vitro and in vivo investigations, should not be disregarded. The repurposing of already approved and marketed drugs could be a suitable strategy to avoid fastidious approval procedures, especially in the case of neglected or veterinary parasitoses.

A Participant-Oriented, Research-Based Approach for Design of a Biochemistry Workshop for Faculty at Undergraduate Institutions

ERIC Educational Resources Information Center

Owen, Rebecca L.; Breyer, Emelita D.

2005-01-01

The Molecular Genetics and Protein Structure and Function workshop is one of a series of workshops offered by the National Science Foundation-funded Center for Workshops in the Chemical Sciences. The workshop provides a hands-on introduction to current topics and techniques in molecular genetics and protein structure/function as applied to…

LiGRO: a graphical user interface for protein-ligand molecular dynamics.

PubMed

Kagami, Luciano Porto; das Neves, Gustavo Machado; da Silva, Alan Wilter Sousa; Caceres, Rafael Andrade; Kawano, Daniel Fábio; Eifler-Lima, Vera Lucia

2017-10-04

To speed up the drug-discovery process, molecular dynamics (MD) calculations performed in GROMACS can be coupled to docking simulations for the post-screening analyses of large compound libraries. This requires generating the topology of the ligands in different software, some basic knowledge of Linux command lines, and a certain familiarity in handling the output files. LiGRO-the python-based graphical interface introduced here-was designed to overcome these protein-ligand parameterization challenges by allowing the graphical (non command line-based) control of GROMACS (MD and analysis), ACPYPE (ligand topology builder) and PLIP (protein-binder interactions monitor)-programs that can be used together to fully perform and analyze the outputs of complex MD simulations (including energy minimization and NVT/NPT equilibration). By allowing the calculation of linear interaction energies in a simple and quick fashion, LiGRO can be used in the drug-discovery pipeline to select compounds with a better protein-binding interaction profile. The design of LiGRO allows researchers to freely download and modify the software, with the source code being available under the terms of a GPLv3 license from http://www.ufrgs.br/lasomfarmacia/ligro/ .

Predicting Ligand Binding Sites on Protein Surfaces by 3-Dimensional Probability Density Distributions of Interacting Atoms

PubMed Central

Jian, Jhih-Wei; Elumalai, Pavadai; Pitti, Thejkiran; Wu, Chih Yuan; Tsai, Keng-Chang; Chang, Jeng-Yih; Peng, Hung-Pin; Yang, An-Suei

2016-01-01

Predicting ligand binding sites (LBSs) on protein structures, which are obtained either from experimental or computational methods, is a useful first step in functional annotation or structure-based drug design for the protein structures. In this work, the structure-based machine learning algorithm ISMBLab-LIG was developed to predict LBSs on protein surfaces with input attributes derived from the three-dimensional probability density maps of interacting atoms, which were reconstructed on the query protein surfaces and were relatively insensitive to local conformational variations of the tentative ligand binding sites. The prediction accuracy of the ISMBLab-LIG predictors is comparable to that of the best LBS predictors benchmarked on several well-established testing datasets. More importantly, the ISMBLab-LIG algorithm has substantial tolerance to the prediction uncertainties of computationally derived protein structure models. As such, the method is particularly useful for predicting LBSs not only on experimental protein structures without known LBS templates in the database but also on computationally predicted model protein structures with structural uncertainties in the tentative ligand binding sites. PMID:27513851

In Situ Formation of an Azo Bridge on Proteins Controllable by Visible Light.

PubMed

Hoppmann, Christian; Maslennikov, Innokentiy; Choe, Senyon; Wang, Lei

2015-09-09

Optical modulation of proteins provides superior spatiotemporal resolution for understanding biological processes, and photoswitches built on light-sensitive proteins have been significantly advancing neuronal and cellular studies. Small molecule photoswitches could complement protein-based switches by mitigating potential interference and affording high specificity for modulation sites. However, genetic encodability and responsiveness to nonultraviolet light, two desired properties possessed by protein photoswitches, are challenging to be engineered into small molecule photoswitches. Here we developed a small molecule photoswitch that can be genetically installed onto proteins in situ and controlled by visible light. A pentafluoro azobenzene-based photoswitchable click amino acid (F-PSCaa) was designed to isomerize in response to visible light. After genetic incorporation into proteins via the expansion of the genetic code, F-PSCaa reacts with a nearby cysteine within the protein generating an azo bridge in situ. The resultant bridge is switchable by visible light and allows conformation and binding of CaM to be regulated by such light. This photoswitch should prove valuable in optobiology for its minimal interference, site flexibility, genetic encodability, and response to the more biocompatible visible light.

PROTERAN: animated terrain evolution for visual analysis of patterns in protein folding trajectory.

PubMed

Zhou, Ruhong; Parida, Laxmi; Kapila, Kush; Mudur, Sudhir

2007-01-01

The mechanism of protein folding remains largely a mystery in molecular biology, despite the enormous effort from many groups in the past decades. Currently, the protein folding mechanism is often characterized by calculating the free energy landscape versus various reaction coordinates such as the fraction of native contacts, the radius of gyration and so on. In this paper, we present an integrated approach towards understanding the folding process via visual analysis of patterns of these reaction coordinates. The three disparate processes (1) protein folding simulation, (2) pattern elicitation and (3) visualization of patterns, work in tandem. Thus as the protein folds, the changing landscape in the pattern space can be viewed via the visualization tool, PROTERAN, a program we developed for this purpose. We first present an incremental (on-line) trie-based pattern discovery algorithm to elicit the patterns and then describe the terrain metaphor based visualization tool. Using two example small proteins, a beta-hairpin and a designed protein Trp-cage, we next demonstrate that this combined pattern discovery and visualization approach extracts crucial information about protein folding intermediates and mechanism.

Computational Design of Self-Assembling Protein Nanomaterials with Atomic Level Accuracy

DOE Office of Scientific and Technical Information (OSTI.GOV)

King, Neil P.; Sheffler, William; Sawaya, Michael R.

2015-09-17

We describe a general computational method for designing proteins that self-assemble to a desired symmetric architecture. Protein building blocks are docked together symmetrically to identify complementary packing arrangements, and low-energy protein-protein interfaces are then designed between the building blocks in order to drive self-assembly. We used trimeric protein building blocks to design a 24-subunit, 13-nm diameter complex with octahedral symmetry and a 12-subunit, 11-nm diameter complex with tetrahedral symmetry. The designed proteins assembled to the desired oligomeric states in solution, and the crystal structures of the complexes revealed that the resulting materials closely match the design models. The method canmore » be used to design a wide variety of self-assembling protein nanomaterials.« less

Crystal structures of ASK1-inhibtor complexes provide a platform for structure-based drug design

PubMed Central

Singh, Onkar; Shillings, Anthony; Craggs, Peter; Wall, Ian; Rowland, Paul; Skarzynski, Tadeusz; Hobbs, Clare I; Hardwick, Phil; Tanner, Rob; Blunt, Michelle; Witty, David R; Smith, Kathrine J

2013-01-01

ASK1, a member of the MAPK Kinase Kinase family of proteins has been shown to play a key role in cancer, neurodegeneration and cardiovascular diseases and is emerging as a possible drug target. Here we describe a ‘replacement-soaking’ method that has enabled the high-throughput X-ray structure determination of ASK1/ligand complexes. Comparison of the X-ray structures of five ASK1/ligand complexes from 3 different chemotypes illustrates that the ASK1 ATP binding site is able to accommodate a range of chemical diversity and different binding modes. The replacement-soaking system is also able to tolerate some protein flexibility. This crystal system provides a robust platform for ASK1/ligand structure determination and future structure based drug design. PMID:23776076

Engineering molecular machines

NASA Astrophysics Data System (ADS)

Erman, Burak

2016-04-01

Biological molecular motors use chemical energy, mostly in the form of ATP hydrolysis, and convert it to mechanical energy. Correlated thermal fluctuations are essential for the function of a molecular machine and it is the hydrolysis of ATP that modifies the correlated fluctuations of the system. Correlations are consequences of the molecular architecture of the protein. The idea that synthetic molecular machines may be constructed by designing the proper molecular architecture is challenging. In their paper, Sarkar et al (2016 New J. Phys. 18 043006) propose a synthetic molecular motor based on the coarse grained elastic network model of proteins and show by numerical simulations that motor function is realized, ranging from deterministic to thermal, depending on temperature. This work opens up a new range of possibilities of molecular architecture based engine design.

The mechanical role of metal ions in biogenic protein-based materials.

PubMed

Degtyar, Elena; Harrington, Matthew J; Politi, Yael; Fratzl, Peter

2014-11-03

Protein-metal interactions--traditionally regarded for roles in metabolic processes--are now known to enhance the performance of certain biogenic materials, influencing properties such as hardness, toughness, adhesion, and self-healing. Design principles elucidated through thorough study of such materials are yielding vital insights for the design of biomimetic metallopolymers with industrial and biomedical applications. Recent advances in the understanding of the biological structure-function relationships are highlighted here with a specific focus on materials such as arthropod biting parts, mussel byssal threads, and sandcastle worm cement. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The 'retro-design' concept for novel kinase inhibitors.

PubMed

Müller, Gerhard; Sennhenn, Peter C; Woodcock, Timothy; Neumann, Lars

2010-07-01

Protein kinases are among the most attractive therapeutic targets for a broad range of diseases. This feature review highlights and classifies the main design principles employed to generate active and selective kinase inhibitors. In particular, emphasis is focused on a fragment-based lead-generation approach, which constitutes a novel design method for developing type II kinase inhibitors with distinct binding kinetic attributes. This 'retro-design' strategy relies on a customized fragment library, and contrasts the traditional approach used in the design of type II inhibitors.

Non-interacting surface solvation and dynamics in protein-protein interactions.

PubMed

Visscher, Koen M; Kastritis, Panagiotis L; Bonvin, Alexandre M J J

2015-03-01

Protein-protein interactions control a plethora of cellular processes, including cell proliferation, differentiation, apoptosis, and signal transduction. Understanding how and why proteins interact will inevitably lead to novel structure-based drug design methods, as well as design of de novo binders with preferred interaction properties. At a structural and molecular level, interface and rim regions are not enough to fully account for the energetics of protein-protein binding, even for simple lock-and-key rigid binders. As we have recently shown, properties of the global surface might also play a role in protein-protein interactions. Here, we report on molecular dynamics simulations performed to understand solvent effects on protein-protein surfaces. We compare properties of the interface, rim, and non-interacting surface regions for five different complexes and their free components. Interface and rim residues become, as expected, less mobile upon complexation. However, non-interacting surface appears more flexible in the complex. Fluctuations of polar residues are always lower compared with charged ones, independent of the protein state. Further, stable water molecules are often observed around polar residues, in contrast to charged ones. Our analysis reveals that (a) upon complexation, the non-interacting surface can have a direct entropic compensation for the lower interface and rim entropy and (b) the mobility of the first hydration layer, which is linked to the stability of the protein-protein complex, is influenced by the local chemical properties of the surface. These findings corroborate previous hypotheses on the role of the hydration layer in shielding protein-protein complexes from unintended protein-protein interactions. © 2014 Wiley Periodicals, Inc.

Identification of Conserved Water Sites in Protein Structures for Drug Design.

PubMed

Jukič, Marko; Konc, Janez; Gobec, Stanislav; Janežič, Dušanka

2017-12-26

Identification of conserved waters in protein structures is a challenging task with applications in molecular docking and protein stability prediction. As an alternative to computationally demanding simulations of proteins in water, experimental cocrystallized waters in the Protein Data Bank (PDB) in combination with a local structure alignment algorithm can be used for reliable prediction of conserved water sites. We developed the ProBiS H2O approach based on the previously developed ProBiS algorithm, which enables identification of conserved water sites in proteins using experimental protein structures from the PDB or a set of custom protein structures available to the user. With a protein structure, a binding site, or an individual water molecule as a query, ProBiS H2O collects similar proteins from the PDB and performs local or binding site-specific superimpositions of the query structure with similar proteins using the ProBiS algorithm. It collects the experimental water molecules from the similar proteins and transposes them to the query protein. Transposed waters are clustered by their mutual proximity, which enables identification of discrete sites in the query protein with high water conservation. ProBiS H2O is a robust and fast new approach that uses existing experimental structural data to identify conserved water sites on the interfaces of protein complexes, for example protein-small molecule interfaces, and elsewhere on the protein structures. It has been successfully validated in several reported proteins in which conserved water molecules were found to play an important role in ligand binding with applications in drug design.

A novel method based on new adaptive LVQ neural network for predicting protein-protein interactions from protein sequences.

PubMed

Yousef, Abdulaziz; Moghadam Charkari, Nasrollah

2013-11-07

Protein-Protein interaction (PPI) is one of the most important data in understanding the cellular processes. Many interesting methods have been proposed in order to predict PPIs. However, the methods which are based on the sequence of proteins as a prior knowledge are more universal. In this paper, a sequence-based, fast, and adaptive PPI prediction method is introduced to assign two proteins to an interaction class (yes, no). First, in order to improve the presentation of the sequences, twelve physicochemical properties of amino acid have been used by different representation methods to transform the sequence of protein pairs into different feature vectors. Then, for speeding up the learning process and reducing the effect of noise PPI data, principal component analysis (PCA) is carried out as a proper feature extraction algorithm. Finally, a new and adaptive Learning Vector Quantization (LVQ) predictor is designed to deal with different models of datasets that are classified into balanced and imbalanced datasets. The accuracy of 93.88%, 90.03%, and 89.72% has been found on S. cerevisiae, H. pylori, and independent datasets, respectively. The results of various experiments indicate the efficiency and validity of the method. © 2013 Published by Elsevier Ltd.

Bio-AIMS Collection of Chemoinformatics Web Tools based on Molecular Graph Information and Artificial Intelligence Models.

PubMed

Munteanu, Cristian R; Gonzalez-Diaz, Humberto; Garcia, Rafael; Loza, Mabel; Pazos, Alejandro

2015-01-01

The molecular information encoding into molecular descriptors is the first step into in silico Chemoinformatics methods in Drug Design. The Machine Learning methods are a complex solution to find prediction models for specific biological properties of molecules. These models connect the molecular structure information such as atom connectivity (molecular graphs) or physical-chemical properties of an atom/group of atoms to the molecular activity (Quantitative Structure - Activity Relationship, QSAR). Due to the complexity of the proteins, the prediction of their activity is a complicated task and the interpretation of the models is more difficult. The current review presents a series of 11 prediction models for proteins, implemented as free Web tools on an Artificial Intelligence Model Server in Biosciences, Bio-AIMS (http://bio-aims.udc.es/TargetPred.php). Six tools predict protein activity, two models evaluate drug - protein target interactions and the other three calculate protein - protein interactions. The input information is based on the protein 3D structure for nine models, 1D peptide amino acid sequence for three tools and drug SMILES formulas for two servers. The molecular graph descriptor-based Machine Learning models could be useful tools for in silico screening of new peptides/proteins as future drug targets for specific treatments.

SPIRE: Systematic protein investigative research environment.

PubMed

Kolker, Eugene; Higdon, Roger; Morgan, Phil; Sedensky, Margaret; Welch, Dean; Bauman, Andrew; Stewart, Elizabeth; Haynes, Winston; Broomall, William; Kolker, Natali

2011-12-10

The SPIRE (Systematic Protein Investigative Research Environment) provides web-based experiment-specific mass spectrometry (MS) proteomics analysis (https://www.proteinspire.org). Its emphasis is on usability and integration of the best analytic tools. SPIRE provides an easy to use web-interface and generates results in both interactive and simple data formats. In contrast to run-based approaches, SPIRE conducts the analysis based on the experimental design. It employs novel methods to generate false discovery rates and local false discovery rates (FDR, LFDR) and integrates the best and complementary open-source search and data analysis methods. The SPIRE approach of integrating X!Tandem, OMSSA and SpectraST can produce an increase in protein IDs (52-88%) over current combinations of scoring and single search engines while also providing accurate multi-faceted error estimation. One of SPIRE's primary assets is combining the results with data on protein function, pathways and protein expression from model organisms. We demonstrate some of SPIRE's capabilities by analyzing mitochondrial proteins from the wild type and 3 mutants of C. elegans. SPIRE also connects results to publically available proteomics data through its Model Organism Protein Expression Database (MOPED). SPIRE can also provide analysis and annotation for user supplied protein ID and expression data. Copyright © 2011. Published by Elsevier B.V.

Regulation of protein activity with small-molecule-controlled inteins

PubMed Central

Skretas, Georgios; Wood, David W.

2005-01-01

Inteins are the protein analogs of self-splicing RNA introns, as they post-translationally excise themselves from a variety of protein hosts. Intein insertion abolishes, in general, the activity of its host protein, which is subsequently restored upon intein excision. These protein elements therefore have the potential to be used as general molecular “switches” for the control of arbitrary target proteins. Based on rational design, an intein-based protein switch has been constructed whose splicing activity is conditionally triggered in vivo by the presence of thyroid hormone or synthetic analogs. This modified intein was used in Escherichia coli to demonstrate that a number of different proteins can be inactivated by intein insertion and then reactivated by the addition of thyroid hormone via ligand-induced splicing. This conditional activation was also found to occur in a dose-dependent manner. Rational protein engineering was then combined with genetic selection to evolve an additional intein whose activity is controlled by the presence of synthetic estrogen ligands. The ability to regulate protein function post-translationally through the use of ligand-controlled intein splicing will most likely find applications in metabolic engineering, drug discovery and delivery, biosensing, molecular computation, as well as many additional areas of biotechnology. PMID:15632292

Improving protein production of indigenous microalga Chlorella vulgaris FSP-E by photobioreactor design and cultivation strategies.

PubMed

Chen, Chun-Yen; Lee, Po-Jen; Tan, Chung Hong; Lo, Yung-Chung; Huang, Chieh-Chen; Show, Pau Loke; Lin, Chih-Hung; Chang, Jo-Shu

2015-06-01

Fish meal is currently the major protein source for commercial aquaculture feed. Due to its unstable supply and increasing price, fish meal is becoming more expensive and its availability is expected to face significant challenges in the near future. Therefore, feasible alternatives to fish meal are urgently required. Microalgae have been recognized as the most promising candidates to replace fish meal because the protein composition of microalgae is similar to fish meal and the supply of microalgae-based proteins is sustainable. In this study, an indigenous microalga (Chlorella vulgaris FSP-E) with high protein content was selected, and its feasibility as an aquaculture protein source was explored. An innovative photobioreactor (PBR) utilizing cold cathode fluorescent lamps as an internal light source was designed to cultivate the FSP-E strain for protein production. This PBR could achieve a maximum biomass and protein productivity of 699 and 365 mg/L/day, respectively, under an optimum urea and iron concentration of 12.4 mM and 90 μM, respectively. In addition, amino acid analysis of the microalgal protein showed that up to 70% of the proteins in this microalgal strain consist of indispensable amino acids. Thus, C. vulgaris FSP-E appears to be a viable alternative protein source for the aquaculture industry. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Roles of glutamates and metal ions in a rationally designed nitric oxide reductase based on myoglobin

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Y.W.; Robinson, H.; Yeung, N.

2010-05-11

A structural and functional model of bacterial nitric oxide reductase (NOR) has been designed by introducing two glutamates (Glu) and three histidines (His) in sperm whale myoglobin. X-ray structural data indicate that the three His and one Glu (V68E) residues bind iron, mimicking the putative FeB site in NOR, while the second Glu (I107E) interacts with a water molecule and forms a hydrogen bonding network in the designed protein. Unlike the first Glu (V68E), which lowered the heme reduction potential by {approx}110 mV, the second Glu has little effect on the heme potential, suggesting that the negatively charged Glu hasmore » a different role in redox tuning. More importantly, introducing the second Glu resulted in a {approx}100% increase in NOR activity, suggesting the importance of a hydrogen bonding network in facilitating proton delivery during NOR reactivity. In addition, EPR and X-ray structural studies indicate that the designed protein binds iron, copper, or zinc in the FeB site, each with different effects on the structures and NOR activities, suggesting that both redox activity and an intermediate five-coordinate heme-NO species are important for high NOR activity. The designed protein offers an excellent model for NOR and demonstrates the power of using designed proteins as a simpler and more well-defined system to address important chemical and biological issues.« less

Roles of Glutamates and Metal ions in a Rationally Designed Nitric Oxide Reductase Based on Myoglobin

DOE Office of Scientific and Technical Information (OSTI.GOV)

Y Lin; N Yeung; Y Gao

2011-12-31

A structural and functional model of bacterial nitric oxide reductase (NOR) has been designed by introducing two glutamates (Glu) and three histidines (His) in sperm whale myoglobin. X-ray structural data indicate that the three His and one Glu (V68E) residues bind iron, mimicking the putative FeB site in NOR, while the second Glu (I107E) interacts with a water molecule and forms a hydrogen bonding network in the designed protein. Unlike the first Glu (V68E), which lowered the heme reduction potential by {approx}110 mV, the second Glu has little effect on the heme potential, suggesting that the negatively charged Glu hasmore » a different role in redox tuning. More importantly, introducing the second Glu resulted in a {approx}100% increase in NOR activity, suggesting the importance of a hydrogen bonding network in facilitating proton delivery during NOR reactivity. In addition, EPR and X-ray structural studies indicate that the designed protein binds iron, copper, or zinc in the FeB site, each with different effects on the structures and NOR activities, suggesting that both redox activity and an intermediate five-coordinate heme-NO species are important for high NOR activity. The designed protein offers an excellent model for NOR and demonstrates the power of using designed proteins as a simpler and more well-defined system to address important chemical and biological issues.« less

UDoNC: An Algorithm for Identifying Essential Proteins Based on Protein Domains and Protein-Protein Interaction Networks.

PubMed

Peng, Wei; Wang, Jianxin; Cheng, Yingjiao; Lu, Yu; Wu, Fangxiang; Pan, Yi

2015-01-01

Prediction of essential proteins which are crucial to an organism's survival is important for disease analysis and drug design, as well as the understanding of cellular life. The majority of prediction methods infer the possibility of proteins to be essential by using the network topology. However, these methods are limited to the completeness of available protein-protein interaction (PPI) data and depend on the network accuracy. To overcome these limitations, some computational methods have been proposed. However, seldom of them solve this problem by taking consideration of protein domains. In this work, we first analyze the correlation between the essentiality of proteins and their domain features based on data of 13 species. We find that the proteins containing more protein domain types which rarely occur in other proteins tend to be essential. Accordingly, we propose a new prediction method, named UDoNC, by combining the domain features of proteins with their topological properties in PPI network. In UDoNC, the essentiality of proteins is decided by the number and the frequency of their protein domain types, as well as the essentiality of their adjacent edges measured by edge clustering coefficient. The experimental results on S. cerevisiae data show that UDoNC outperforms other existing methods in terms of area under the curve (AUC). Additionally, UDoNC can also perform well in predicting essential proteins on data of E. coli.

Specifically targeted delivery of protein to phagocytic macrophages

PubMed Central

Yu, Min; Chen, Zeming; Guo, Wenjun; Wang, Jin; Feng, Yupeng; Kong, Xiuqi; Hong, Zhangyong

2015-01-01

Macrophages play important roles in the pathogenesis of various diseases, and are important potential therapeutic targets. Furthermore, macrophages are key antigen-presenting cells and important in vaccine design. In this study, we report on the novel formulation (bovine serum albumin [BSA]-loaded glucan particles [GMP-BSA]) based on β-glucan particles from cell walls of baker’s yeast for the targeted delivery of protein to macrophages. Using this formulation, chitosan, tripolyphosphate, and alginate were used to fabricate colloidal particles with the model protein BSA via electrostatic interactions, which were caged and incorporated BSA very tightly within the β-glucan particle shells. The prepared GMP-BSA exhibited good protein-release behavior and avoided protein leakage. The particles were also highly specific to phagocytic macrophages, such as Raw 264.7 cells, primary bone marrow-derived macrophages, and peritoneal exudate macrophages, whereas the particles were not taken up by nonphagocytic cells, including NIH3T3, AD293, HeLa, and Caco-2. We hypothesize that these tightly encapsulated protein-loaded glucan particles deliver various types of proteins to macrophages with notably high selectivity, and may have broad applications in targeted drug delivery or vaccine design against macrophages. PMID:25784802

Lactobacillus helveticus MIMLh5-Specific Antibodies for Detection of S-Layer Protein in Grana Padano Protected-Designation-of-Origin Cheese

PubMed Central

Brockmann, Eeva-Christine; Huovinen, Tuomas; Guglielmetti, Simone; Mora, Diego; Taverniti, Valentina; Arioli, Stefania; De Noni, Ivano; Lamminmäki, Urpo

2014-01-01

Single-chain variable-fragment antibodies (scFvs) have considerable potential in immunological detection and localization of bacterial surface structures. In this study, synthetic phage-displayed antibody libraries were used to select scFvs against immunologically active S-layer protein of Lactobacillus helveticus MIMLh5. After three rounds of panning, five relevant phage clones were obtained, of which four were specific for the S-layer protein of L. helveticus MIMLh5 and one was also capable of binding to the S-layer protein of L. helveticus ATCC 15009. All five anti-S-layer scFvs were expressed in Escherichia coli XL1-Blue, and their specificity profiles were characterized by Western blotting. The anti-S-layer scFv PolyH4, with the highest specificity for the S-layer protein of L. helveticus MIMLh5, was used to detect the S-layer protein in Grana Padano protected-designation-of-origin (PDO) cheese extracts by Western blotting. These results showed promising applications of this monoclonal antibody for the detection of immunomodulatory S-layer protein in dairy (and dairy-based) foods. PMID:24242242

Monolayers of derivatized poly(l-lysine)-grafted poly(ethylene glycol) on metal oxides as a class of biomolecular interfaces

PubMed Central

Ruiz-Taylor, L. A.; Martin, T. L.; Zaugg, F. G.; Witte, K.; Indermuhle, P.; Nock, S.; Wagner, P.

2001-01-01

We report on the design and characterization of a class of biomolecular interfaces based on derivatized poly(l-lysine)-grafted poly(ethylene glycol) copolymers adsorbed on negatively charged surfaces. As a model system, we synthesized biotin-derivatized poly(l-lysine)-grafted poly(ethylene glycol) copolymers, PLL-g-[(PEGm)(1−x) (PEG-biotin)x], where x varies from 0 to 1. Monolayers were produced on titanium dioxide substrates and characterized by x-ray photoelectron spectroscopy. The specific biorecognition properties of these biotinylated surfaces were investigated with the use of radiolabeled streptavidin alone and within complex protein mixtures. The PLL-g-PEG-biotin monolayers specifically capture streptavidin, even from a complex protein mixture, while still preventing nonspecific adsorption of other proteins. This streptavidin layer can subsequently capture biotinylated proteins. Finally, with the use of microfluidic networks and protein arraying, we demonstrate the potential of this class of biomolecular interfaces for applications based on protein patterning. PMID:11158560

A discriminative method for protein remote homology detection and fold recognition combining Top-n-grams and latent semantic analysis.

PubMed

Liu, Bin; Wang, Xiaolong; Lin, Lei; Dong, Qiwen; Wang, Xuan

2008-12-01

Protein remote homology detection and fold recognition are central problems in bioinformatics. Currently, discriminative methods based on support vector machine (SVM) are the most effective and accurate methods for solving these problems. A key step to improve the performance of the SVM-based methods is to find a suitable representation of protein sequences. In this paper, a novel building block of proteins called Top-n-grams is presented, which contains the evolutionary information extracted from the protein sequence frequency profiles. The protein sequence frequency profiles are calculated from the multiple sequence alignments outputted by PSI-BLAST and converted into Top-n-grams. The protein sequences are transformed into fixed-dimension feature vectors by the occurrence times of each Top-n-gram. The training vectors are evaluated by SVM to train classifiers which are then used to classify the test protein sequences. We demonstrate that the prediction performance of remote homology detection and fold recognition can be improved by combining Top-n-grams and latent semantic analysis (LSA), which is an efficient feature extraction technique from natural language processing. When tested on superfamily and fold benchmarks, the method combining Top-n-grams and LSA gives significantly better results compared to related methods. The method based on Top-n-grams significantly outperforms the methods based on many other building blocks including N-grams, patterns, motifs and binary profiles. Therefore, Top-n-gram is a good building block of the protein sequences and can be widely used in many tasks of the computational biology, such as the sequence alignment, the prediction of domain boundary, the designation of knowledge-based potentials and the prediction of protein binding sites.

Biotin-tagged proteins: Reagents for efficient ELISA-based serodiagnosis and phage display-based affinity selection

PubMed Central

Verma, Vaishali; Kaur, Charanpreet; Grover, Payal; Gupta, Amita

2018-01-01

The high-affinity interaction between biotin and streptavidin has opened avenues for using recombinant proteins with site-specific biotinylation to achieve efficient and directional immobilization. The site-specific biotinylation of proteins carrying a 15 amino acid long Biotin Acceptor Peptide tag (BAP; also known as AviTag) is effected on a specific lysine either by co-expressing the E. coli BirA enzyme in vivo or by using purified recombinant E. coli BirA enzyme in the presence of ATP and biotin in vitro. In this paper, we have designed a T7 promoter-lac operator-based expression vector for rapid and efficient cloning, and high-level cytosolic expression of proteins carrying a C-terminal BAP tag in E. coli with TEV protease cleavable N-terminal deca-histidine tag, useful for initial purification. Furthermore, a robust three-step purification pipeline integrated with well-optimized protocols for TEV protease-based H10 tag removal, and recombinant BirA enzyme-based site-specific in vitro biotinylation is described to obtain highly pure biotinylated proteins. Most importantly, the paper demonstrates superior sensitivities in indirect ELISA with directional and efficient immobilization of biotin-tagged proteins on streptavidin-coated surfaces in comparison to passive immobilization. The use of biotin-tagged proteins through specific immobilization also allows more efficient selection of binders from a phage-displayed naïve antibody library. In addition, for both these applications, specific immobilization requires much less amount of protein as compared to passive immobilization and can be easily multiplexed. The simplified strategy described here for the production of highly pure biotin-tagged proteins will find use in numerous applications, including those, which may require immobilization of multiple proteins simultaneously on a solid surface. PMID:29360877

Biotin-tagged proteins: Reagents for efficient ELISA-based serodiagnosis and phage display-based affinity selection.

PubMed

Verma, Vaishali; Kaur, Charanpreet; Grover, Payal; Gupta, Amita; Chaudhary, Vijay K

2018-01-01

The high-affinity interaction between biotin and streptavidin has opened avenues for using recombinant proteins with site-specific biotinylation to achieve efficient and directional immobilization. The site-specific biotinylation of proteins carrying a 15 amino acid long Biotin Acceptor Peptide tag (BAP; also known as AviTag) is effected on a specific lysine either by co-expressing the E. coli BirA enzyme in vivo or by using purified recombinant E. coli BirA enzyme in the presence of ATP and biotin in vitro. In this paper, we have designed a T7 promoter-lac operator-based expression vector for rapid and efficient cloning, and high-level cytosolic expression of proteins carrying a C-terminal BAP tag in E. coli with TEV protease cleavable N-terminal deca-histidine tag, useful for initial purification. Furthermore, a robust three-step purification pipeline integrated with well-optimized protocols for TEV protease-based H10 tag removal, and recombinant BirA enzyme-based site-specific in vitro biotinylation is described to obtain highly pure biotinylated proteins. Most importantly, the paper demonstrates superior sensitivities in indirect ELISA with directional and efficient immobilization of biotin-tagged proteins on streptavidin-coated surfaces in comparison to passive immobilization. The use of biotin-tagged proteins through specific immobilization also allows more efficient selection of binders from a phage-displayed naïve antibody library. In addition, for both these applications, specific immobilization requires much less amount of protein as compared to passive immobilization and can be easily multiplexed. The simplified strategy described here for the production of highly pure biotin-tagged proteins will find use in numerous applications, including those, which may require immobilization of multiple proteins simultaneously on a solid surface.

Ligand design by a combinatorial approach based on modeling and experiment: application to HLA-DR4

NASA Astrophysics Data System (ADS)

Evensen, Erik; Joseph-McCarthy, Diane; Weiss, Gregory A.; Schreiber, Stuart L.; Karplus, Martin

2007-07-01

Combinatorial synthesis and large scale screening methods are being used increasingly in drug discovery, particularly for finding novel lead compounds. Although these "random" methods sample larger areas of chemical space than traditional synthetic approaches, only a relatively small percentage of all possible compounds are practically accessible. It is therefore helpful to select regions of chemical space that have greater likelihood of yielding useful leads. When three-dimensional structural data are available for the target molecule this can be achieved by applying structure-based computational design methods to focus the combinatorial library. This is advantageous over the standard usage of computational methods to design a small number of specific novel ligands, because here computation is employed as part of the combinatorial design process and so is required only to determine a propensity for binding of certain chemical moieties in regions of the target molecule. This paper describes the application of the Multiple Copy Simultaneous Search (MCSS) method, an active site mapping and de novo structure-based design tool, to design a focused combinatorial library for the class II MHC protein HLA-DR4. Methods for the synthesizing and screening the computationally designed library are presented; evidence is provided to show that binding was achieved. Although the structure of the protein-ligand complex could not be determined, experimental results including cross-exclusion of a known HLA-DR4 peptide ligand (HA) by a compound from the library. Computational model building suggest that at least one of the ligands designed and identified by the methods described binds in a mode similar to that of native peptides.

Computational Fragment-Based Drug Design: Current Trends, Strategies, and Applications.

PubMed

Bian, Yuemin; Xie, Xiang-Qun Sean

2018-04-09

Fragment-based drug design (FBDD) has become an effective methodology for drug development for decades. Successful applications of this strategy brought both opportunities and challenges to the field of Pharmaceutical Science. Recent progress in the computational fragment-based drug design provide an additional approach for future research in a time- and labor-efficient manner. Combining multiple in silico methodologies, computational FBDD possesses flexibilities on fragment library selection, protein model generation, and fragments/compounds docking mode prediction. These characteristics provide computational FBDD superiority in designing novel and potential compounds for a certain target. The purpose of this review is to discuss the latest advances, ranging from commonly used strategies to novel concepts and technologies in computational fragment-based drug design. Particularly, in this review, specifications and advantages are compared between experimental and computational FBDD, and additionally, limitations and future prospective are discussed and emphasized.

De Novo Design of Protein Mimics of B-DNA

PubMed Central

Yüksel, Deniz; Bianco, Piero R.; Kumar, Krishna

2015-01-01

Structural mimicry of DNA is utilized in nature as a strategy to evade molecular defences mounted by host organisms. One such example is the protein Ocr – the first translation product to be expressed as the bacteriophage T7 infects E. coli. The structure of Ocr reveals an intricate and deliberate arrangement of negative charges that endows it with the ability to mimic ∼24 base pair stretches of B–DNA. This uncanny resemblance to DNA enables Ocr to compete in binding the type I restriction modification (R/M) system, and neutralizes the threat of hydrolytic cleavage of viral genomic material. Here, we report the de novo design and biophysical characterization of DNA mimicking peptides, and describe the inhibitory action of the designed helical bundles on a type I R/M enzyme, EcoR124I. This work validates the use of charge patterning as a design principle for creation of protein mimics of DNA, and serves as a starting point for development of therapeutic peptide inhibitors against human pathogens that employ molecular camouflage as part of their invasion stratagem. PMID:26568416

Design of high productivity antibody capture by protein A chromatography using an integrated experimental and modeling approach.

PubMed

Ng, Candy K S; Osuna-Sanchez, Hector; Valéry, Eric; Sørensen, Eva; Bracewell, Daniel G

2012-06-15

An integrated experimental and modeling approach for the design of high productivity protein A chromatography is presented to maximize productivity in bioproduct manufacture. The approach consists of four steps: (1) small-scale experimentation, (2) model parameter estimation, (3) productivity optimization and (4) model validation with process verification. The integrated use of process experimentation and modeling enables fewer experiments to be performed, and thus minimizes the time and materials required in order to gain process understanding, which is of key importance during process development. The application of the approach is demonstrated for the capture of antibody by a novel silica-based high performance protein A adsorbent named AbSolute. In the example, a series of pulse injections and breakthrough experiments were performed to develop a lumped parameter model, which was then used to find the best design that optimizes the productivity of a batch protein A chromatographic process for human IgG capture. An optimum productivity of 2.9 kg L⁻¹ day⁻¹ for a column of 5mm diameter and 8.5 cm length was predicted, and subsequently verified experimentally, completing the whole process design approach in only 75 person-hours (or approximately 2 weeks). Copyright © 2012 Elsevier B.V. All rights reserved.

Computational design of cyclic peptides for the customized oriented immobilization of globular proteins.

PubMed

Soler, Miguel A; Rodriguez, Alex; Russo, Anna; Adedeji, Abimbola Feyisara; Dongmo Foumthuim, Cedrix J; Cantarutti, Cristina; Ambrosetti, Elena; Casalis, Loredana; Corazza, Alessandra; Scoles, Giacinto; Marasco, Daniela; Laio, Alessandro; Fortuna, Sara

2017-01-25

The oriented immobilization of proteins, key for the development of novel responsive biomaterials, relies on the availability of effective probes. These are generally provided by standard approaches based on in vivo maturation and in vitro selection of antibodies and/or aptamers. These techniques can suffer technical problems when a non-immunogenic epitope needs to be targeted. Here we propose a strategy to circumvent this issue by in silico design. In our method molecular binders, in the form of cyclic peptides, are computationally evolved by stochastically exploring their sequence and structure space to identify high-affinity peptides for a chosen epitope of a target globular protein: here a solvent-exposed site of β2-microglobulin (β2m). Designed sequences were screened by explicit solvent molecular dynamics simulations (MD) followed by experimental validation. Five candidates gave dose-response surface plasmon resonance signals with dissociation constants in the micromolar range. One of them was further analyzed by means of isothermal titration calorimetry, nuclear magnetic resonance, and 250 ns of MD. Atomic-force microscopy imaging showed that this peptide is able to immobilize β2m on a gold surface. In short, we have shown by a variety of experimental techniques that it is possible to capture a protein through an epitope of choice by computational design.

Designing and Testing Broadly-Protective Filoviral Vaccines Optimized for Cytotoxic T-Lymphocyte Epitope Coverage

PubMed Central

Fenimore, Paul W.; Foley, Brian T.; Bakken, Russell R.; Thurmond, James R.; Yusim, Karina; Yoon, Hyejin; Parker, Michael; Hart, Mary Kate; Dye, John M.; Korber, Bette; Kuiken, Carla

2012-01-01

We report the rational design and in vivo testing of mosaic proteins for a polyvalent pan-filoviral vaccine using a computational strategy designed for the Human Immunodeficiency Virus type 1 (HIV-1) but also appropriate for Hepatitis C virus (HCV) and potentially other diverse viruses. Mosaics are sets of artificial recombinant proteins that are based on natural proteins. The recombinants are computationally selected using a genetic algorithm to optimize the coverage of potential cytotoxic T lymphocyte (CTL) epitopes. Because evolutionary history differs markedly between HIV-1 and filoviruses, we devised an adapted computational technique that is effective for sparsely sampled taxa; our first significant result is that the mosaic technique is effective in creating high-quality mosaic filovirus proteins. The resulting coverage of potential epitopes across filovirus species is superior to coverage by any natural variants, including current vaccine strains with demonstrated cross-reactivity. The mosaic cocktails are also robust: mosaics substantially outperformed natural strains when computationally tested against poorly sampled species and more variable genes. Furthermore, in a computational comparison of cross-reactive potential a design constructed prior to the Bundibugyo outbreak performed nearly as well against all species as an updated design that included Bundibugyo. These points suggest that the mosaic designs would be more resilient than natural-variant vaccines against future Ebola outbreaks dominated by novel viral variants. We demonstrate in vivo immunogenicity and protection against a heterologous challenge in a mouse model. This design work delineates the likely requirements and limitations on broadly-protective filoviral CTL vaccines. PMID:23056184

Macromolecular Crystal Growth by Means of Microfluidics

NASA Technical Reports Server (NTRS)

vanderWoerd, Mark; Ferree, Darren; Spearing, Scott; Monaco, Lisa; Molho, Josh; Spaid, Michael; Brasseur, Mike; Curreri, Peter A. (Technical Monitor)

2002-01-01

We have performed a feasibility study in which we show that chip-based, microfluidic (LabChip(TM)) technology is suitable for protein crystal growth. This technology allows for accurate and reliable dispensing and mixing of very small volumes while minimizing bubble formation in the crystallization mixture. The amount of (protein) solution remaining after completion of an experiment is minimal, which makes this technique efficient and attractive for use with proteins, which are difficult or expensive to obtain. The nature of LabChip(TM) technology renders it highly amenable to automation. Protein crystals obtained in our initial feasibility studies were of excellent quality as determined by X-ray diffraction. Subsequent to the feasibility study, we designed and produced the first LabChip(TM) device specifically for protein crystallization in batch mode. It can reliably dispense and mix from a range of solution constituents into two independent growth wells. We are currently testing this design to prove its efficacy for protein crystallization optimization experiments. In the near future we will expand our design to incorporate up to 10 growth wells per LabChip(TM) device. Upon completion, additional crystallization techniques such as vapor diffusion and liquid-liquid diffusion will be accommodated. Macromolecular crystallization using microfluidic technology is envisioned as a fully automated system, which will use the 'tele-science' concept of remote operation and will be developed into a research facility for the International Space Station as well as on the ground.

Theoretical model to investigate the alkyl chain and anion dependent interactions of gemini surfactant with bovine serum albumin.

PubMed

Vishvakarma, Vijay K; Kumari, Kamlesh; Patel, Rajan; Dixit, V S; Singh, Prashant; Mehrotra, Gopal K; Chandra, Ramesh; Chakrawarty, Anand Kumar

2015-05-15

Surfactants are used to prevent the irreversible aggregation of partially refolded proteins and they also assist in protein refolding. We have reported the design and screening of gemini surfactant to stabilize bovine serum albumin (BSA) with the help of computational tool (iGEMDOCK). A series of gemini surfactant has been designed based on bis-N-alkyl nicotinate dianion via varying the alkyl group and anion. On changing the alkyl group and anion of the surfactant, the value of Log P changes means polarity of surfactant can be tuned. Further, the virtual screening of the gemini surfactant has been carried out based on generic evolutionary method. Herein, thermodynamic data was studied to determine the potential of gemini surfactant as BSA stabilizer. Computational tools help to find out the efficient gemini surfactant to stabilize the BSA rather than to use the surfactant randomly and directionless for the stabilization. It can be confirmed through the experimental techniques. Previously, researcher synthesized one of the designed and used gemini surfactant to stabilize the BSA and their interactions were confirmed through various techniques and computational docking. But herein, the authors find the most competent gemini surfactant to stabilize BSA using computational tools on the basis of energy score. Different from the single chain surfactant, the gemini surfactants exhibit much stronger electrostatic and hydrophobic interactions with the protein and are thus effective at much lower concentrations. Based on the present study, it is expected that gemini surfactants may prove useful in the protein stabilization operations and may thus be effectively employed to circumvent the problem of misfolding and aggregation. Copyright © 2015 Elsevier B.V. All rights reserved.

Theoretical model to investigate the alkyl chain and anion dependent interactions of gemini surfactant with bovine serum albumin

NASA Astrophysics Data System (ADS)

Vishvakarma, Vijay K.; Kumari, Kamlesh; Patel, Rajan; Dixit, V. S.; Singh, Prashant; Mehrotra, Gopal K.; Chandra, Ramesh; Chakrawarty, Anand Kumar

2015-05-01

Surfactants are used to prevent the irreversible aggregation of partially refolded proteins and they also assist in protein refolding. We have reported the design and screening of gemini surfactant to stabilize bovine serum albumin (BSA) with the help of computational tool (iGEMDOCK). A series of gemini surfactant has been designed based on bis-N-alkyl nicotinate dianion via varying the alkyl group and anion. On changing the alkyl group and anion of the surfactant, the value of Log P changes means polarity of surfactant can be tuned. Further, the virtual screening of the gemini surfactant has been carried out based on generic evolutionary method. Herein, thermodynamic data was studied to determine the potential of gemini surfactant as BSA stabilizer. Computational tools help to find out the efficient gemini surfactant to stabilize the BSA rather than to use the surfactant randomly and directionless for the stabilization. It can be confirmed through the experimental techniques. Previously, researcher synthesized one of the designed and used gemini surfactant to stabilize the BSA and their interactions were confirmed through various techniques and computational docking. But herein, the authors find the most competent gemini surfactant to stabilize BSA using computational tools on the basis of energy score. Different from the single chain surfactant, the gemini surfactants exhibit much stronger electrostatic and hydrophobic interactions with the protein and are thus effective at much lower concentrations. Based on the present study, it is expected that gemini surfactants may prove useful in the protein stabilization operations and may thus be effectively employed to circumvent the problem of misfolding and aggregation.

Insights from molecular dynamics simulations for computational protein design.

PubMed

Childers, Matthew Carter; Daggett, Valerie

2017-02-01

A grand challenge in the field of structural biology is to design and engineer proteins that exhibit targeted functions. Although much success on this front has been achieved, design success rates remain low, an ever-present reminder of our limited understanding of the relationship between amino acid sequences and the structures they adopt. In addition to experimental techniques and rational design strategies, computational methods have been employed to aid in the design and engineering of proteins. Molecular dynamics (MD) is one such method that simulates the motions of proteins according to classical dynamics. Here, we review how insights into protein dynamics derived from MD simulations have influenced the design of proteins. One of the greatest strengths of MD is its capacity to reveal information beyond what is available in the static structures deposited in the Protein Data Bank. In this regard simulations can be used to directly guide protein design by providing atomistic details of the dynamic molecular interactions contributing to protein stability and function. MD simulations can also be used as a virtual screening tool to rank, select, identify, and assess potential designs. MD is uniquely poised to inform protein design efforts where the application requires realistic models of protein dynamics and atomic level descriptions of the relationship between dynamics and function. Here, we review cases where MD simulations was used to modulate protein stability and protein function by providing information regarding the conformation(s), conformational transitions, interactions, and dynamics that govern stability and function. In addition, we discuss cases where conformations from protein folding/unfolding simulations have been exploited for protein design, yielding novel outcomes that could not be obtained from static structures.

Insights from molecular dynamics simulations for computational protein design

PubMed Central

Childers, Matthew Carter; Daggett, Valerie

2017-01-01

A grand challenge in the field of structural biology is to design and engineer proteins that exhibit targeted functions. Although much success on this front has been achieved, design success rates remain low, an ever-present reminder of our limited understanding of the relationship between amino acid sequences and the structures they adopt. In addition to experimental techniques and rational design strategies, computational methods have been employed to aid in the design and engineering of proteins. Molecular dynamics (MD) is one such method that simulates the motions of proteins according to classical dynamics. Here, we review how insights into protein dynamics derived from MD simulations have influenced the design of proteins. One of the greatest strengths of MD is its capacity to reveal information beyond what is available in the static structures deposited in the Protein Data Bank. In this regard simulations can be used to directly guide protein design by providing atomistic details of the dynamic molecular interactions contributing to protein stability and function. MD simulations can also be used as a virtual screening tool to rank, select, identify, and assess potential designs. MD is uniquely poised to inform protein design efforts where the application requires realistic models of protein dynamics and atomic level descriptions of the relationship between dynamics and function. Here, we review cases where MD simulations was used to modulate protein stability and protein function by providing information regarding the conformation(s), conformational transitions, interactions, and dynamics that govern stability and function. In addition, we discuss cases where conformations from protein folding/unfolding simulations have been exploited for protein design, yielding novel outcomes that could not be obtained from static structures. PMID:28239489

Protein Engineering Approaches in the Post-Genomic Era.

PubMed

Singh, Raushan K; Lee, Jung-Kul; Selvaraj, Chandrabose; Singh, Ranjitha; Li, Jinglin; Kim, Sang-Yong; Kalia, Vipin C

2018-01-01

Proteins are one of the most multifaceted macromolecules in living systems. Proteins have evolved to function under physiological conditions and, therefore, are not usually tolerant of harsh experimental and environmental conditions. The growing use of proteins in industrial processes as a greener alternative to chemical catalysts often demands constant innovation to improve their performance. Protein engineering aims to design new proteins or modify the sequence of a protein to create proteins with new or desirable functions. With the emergence of structural and functional genomics, protein engineering has been invigorated in the post-genomic era. The three-dimensional structures of proteins with known functions facilitate protein engineering approaches to design variants with desired properties. There are three major approaches of protein engineering research, namely, directed evolution, rational design, and de novo design. Rational design is an effective method of protein engineering when the threedimensional structure and mechanism of the protein is well known. In contrast, directed evolution does not require extensive information and a three-dimensional structure of the protein of interest. Instead, it involves random mutagenesis and selection to screen enzymes with desired properties. De novo design uses computational protein design algorithms to tailor synthetic proteins by using the three-dimensional structures of natural proteins and their folding rules. The present review highlights and summarizes recent protein engineering approaches, and their challenges and limitations in the post-genomic era. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Global analysis of protein folding using massively parallel design, synthesis and testing

PubMed Central

Rocklin, Gabriel J.; Chidyausiku, Tamuka M.; Goreshnik, Inna; Ford, Alex; Houliston, Scott; Lemak, Alexander; Carter, Lauren; Ravichandran, Rashmi; Mulligan, Vikram K.; Chevalier, Aaron; Arrowsmith, Cheryl H.; Baker, David

2017-01-01

Proteins fold into unique native structures stabilized by thousands of weak interactions that collectively overcome the entropic cost of folding. Though these forces are “encoded” in the thousands of known protein structures, “decoding” them is challenging due to the complexity of natural proteins that have evolved for function, not stability. Here we combine computational protein design, next-generation gene synthesis, and a high-throughput protease susceptibility assay to measure folding and stability for over 15,000 de novo designed miniproteins, 1,000 natural proteins, 10,000 point-mutants, and 30,000 negative control sequences, identifying over 2,500 new stable designed proteins in four basic folds. This scale—three orders of magnitude greater than that of previous studies of design or folding—enabled us to systematically examine how sequence determines folding and stability in uncharted protein space. Iteration between design and experiment increased the design success rate from 6% to 47%, produced stable proteins unlike those found in nature for topologies where design was initially unsuccessful, and revealed subtle contributions to stability as designs became increasingly optimized. Our approach achieves the long-standing goal of a tight feedback cycle between computation and experiment, and promises to transform computational protein design into a data-driven science. PMID:28706065

A High Performance Cloud-Based Protein-Ligand Docking Prediction Algorithm

PubMed Central

Chen, Jui-Le; Yang, Chu-Sing

2013-01-01

The potential of predicting druggability for a particular disease by integrating biological and computer science technologies has witnessed success in recent years. Although the computer science technologies can be used to reduce the costs of the pharmaceutical research, the computation time of the structure-based protein-ligand docking prediction is still unsatisfied until now. Hence, in this paper, a novel docking prediction algorithm, named fast cloud-based protein-ligand docking prediction algorithm (FCPLDPA), is presented to accelerate the docking prediction algorithm. The proposed algorithm works by leveraging two high-performance operators: (1) the novel migration (information exchange) operator is designed specially for cloud-based environments to reduce the computation time; (2) the efficient operator is aimed at filtering out the worst search directions. Our simulation results illustrate that the proposed method outperforms the other docking algorithms compared in this paper in terms of both the computation time and the quality of the end result. PMID:23762864

An ensemble framework for clustering protein-protein interaction networks.

PubMed

Asur, Sitaram; Ucar, Duygu; Parthasarathy, Srinivasan

2007-07-01

Protein-Protein Interaction (PPI) networks are believed to be important sources of information related to biological processes and complex metabolic functions of the cell. The presence of biologically relevant functional modules in these networks has been theorized by many researchers. However, the application of traditional clustering algorithms for extracting these modules has not been successful, largely due to the presence of noisy false positive interactions as well as specific topological challenges in the network. In this article, we propose an ensemble clustering framework to address this problem. For base clustering, we introduce two topology-based distance metrics to counteract the effects of noise. We develop a PCA-based consensus clustering technique, designed to reduce the dimensionality of the consensus problem and yield informative clusters. We also develop a soft consensus clustering variant to assign multifaceted proteins to multiple functional groups. We conduct an empirical evaluation of different consensus techniques using topology-based, information theoretic and domain-specific validation metrics and show that our approaches can provide significant benefits over other state-of-the-art approaches. Our analysis of the consensus clusters obtained demonstrates that ensemble clustering can (a) produce improved biologically significant functional groupings; and (b) facilitate soft clustering by discovering multiple functional associations for proteins. Supplementary data are available at Bioinformatics online.

Physics and evolution of thermophilic adaptation.

PubMed

Berezovsky, Igor N; Shakhnovich, Eugene I

2005-09-06

Analysis of structures and sequences of several hyperthermostable proteins from various sources reveals two major physical mechanisms of their thermostabilization. The first mechanism is "structure-based," whereby some hyperthermostable proteins are significantly more compact than their mesophilic homologues, while no particular interaction type appears to cause stabilization; rather, a sheer number of interactions is responsible for thermostability. Other hyperthermostable proteins employ an alternative, "sequence-based" mechanism of their thermal stabilization. They do not show pronounced structural differences from mesophilic homologues. Rather, a small number of apparently strong interactions is responsible for high thermal stability of these proteins. High-throughput comparative analysis of structures and complete genomes of several hyperthermophilic archaea and bacteria revealed that organisms develop diverse strategies of thermophilic adaptation by using, to a varying degree, two fundamental physical mechanisms of thermostability. The choice of a particular strategy depends on the evolutionary history of an organism. Proteins from organisms that originated in an extreme environment, such as hyperthermophilic archaea (Pyrococcus furiosus), are significantly more compact and more hydrophobic than their mesophilic counterparts. Alternatively, organisms that evolved as mesophiles but later recolonized a hot environment (Thermotoga maritima) relied in their evolutionary strategy of thermophilic adaptation on "sequence-based" mechanism of thermostability. We propose an evolutionary explanation of these differences based on physical concepts of protein designability.

Structure-wise discrimination of cytosine, thymine, and uracil by proteins in terms of their nonbonded interactions.

PubMed

Usha, S; Selvaraj, S

2014-01-01

The molecular recognition and discrimination of very similar ligand moieties by proteins are important subjects in protein-ligand interaction studies. Specificity in the recognition of molecules is determined by the arrangement of protein and ligand atoms in space. The three pyrimidine bases, viz. cytosine, thymine, and uracil, are structurally similar, but the proteins that bind to them are able to discriminate them and form interactions. Since nonbonded interactions are responsible for molecular recognition processes in biological systems, our work attempts to understand some of the underlying principles of such recognition of pyrimidine molecular structures by proteins. The preferences of the amino acid residues to contact the pyrimidine bases in terms of nonbonded interactions; amino acid residue-ligand atom preferences; main chain and side chain atom contributions of amino acid residues; and solvent-accessible surface area of ligand atoms when forming complexes are analyzed. Our analysis shows that the amino acid residues, tyrosine and phenyl alanine, are highly involved in the pyrimidine interactions. Arginine prefers contacts with the cytosine base. The similarities and differences that exist between the interactions of the amino acid residues with each of the three pyrimidine base atoms in our analysis provide insights that can be exploited in designing specific inhibitors competitive to the ligands.

Predicting and analyzing DNA-binding domains using a systematic approach to identifying a set of informative physicochemical and biochemical properties

PubMed Central

2011-01-01

Background Existing methods of predicting DNA-binding proteins used valuable features of physicochemical properties to design support vector machine (SVM) based classifiers. Generally, selection of physicochemical properties and determination of their corresponding feature vectors rely mainly on known properties of binding mechanism and experience of designers. However, there exists a troublesome problem for designers that some different physicochemical properties have similar vectors of representing 20 amino acids and some closely related physicochemical properties have dissimilar vectors. Results This study proposes a systematic approach (named Auto-IDPCPs) to automatically identify a set of physicochemical and biochemical properties in the AAindex database to design SVM-based classifiers for predicting and analyzing DNA-binding domains/proteins. Auto-IDPCPs consists of 1) clustering 531 amino acid indices in AAindex into 20 clusters using a fuzzy c-means algorithm, 2) utilizing an efficient genetic algorithm based optimization method IBCGA to select an informative feature set of size m to represent sequences, and 3) analyzing the selected features to identify related physicochemical properties which may affect the binding mechanism of DNA-binding domains/proteins. The proposed Auto-IDPCPs identified m=22 features of properties belonging to five clusters for predicting DNA-binding domains with a five-fold cross-validation accuracy of 87.12%, which is promising compared with the accuracy of 86.62% of the existing method PSSM-400. For predicting DNA-binding sequences, the accuracy of 75.50% was obtained using m=28 features, where PSSM-400 has an accuracy of 74.22%. Auto-IDPCPs and PSSM-400 have accuracies of 80.73% and 82.81%, respectively, applied to an independent test data set of DNA-binding domains. Some typical physicochemical properties discovered are hydrophobicity, secondary structure, charge, solvent accessibility, polarity, flexibility, normalized Van Der Waals volume, pK (pK-C, pK-N, pK-COOH and pK-a(RCOOH)), etc. Conclusions The proposed approach Auto-IDPCPs would help designers to investigate informative physicochemical and biochemical properties by considering both prediction accuracy and analysis of binding mechanism simultaneously. The approach Auto-IDPCPs can be also applicable to predict and analyze other protein functions from sequences. PMID:21342579

Structure-Based Design of N-Substituted 1-Hydroxy-4-sulfamoyl-2-naphthoates as Selective Inhibitors of the Mcl-1 Oncoprotein

PubMed Central

Lanning, Maryanna E.; Yu, Wenbo; Yap, Jeremy L.; Chauhan, Jay; Chen, Lijia; Whiting, Ellis; Pidugu, Lakshmi S.; Atkinson, Tyler; Bailey, Hala; Li, Willy; Roth, Braden M.; Hynicka, Lauren; Chesko, Kirsty; Toth, Eric A.; Shapiro, Paul; MacKerell, Alexander D.; Wilder, Paul T.; Fletcher, Steven

2016-01-01

Structure-based drug design was utilized to develop novel, 1-hydroxy-2-naphthoate-based small-molecule inhibitors of Mcl-1. Ligand design was driven by exploiting a salt bridge with R263 and interactions with the p2 and p3 pockets of the protein. Significantly, target molecules were accessed in just two synthetic steps, suggesting further optimization will require minimal synthetic effort. Molecular modeling using the Site-Identification by Ligand Competitive Saturation (SILCS) approach was used to qualitatively direct ligand design as well as develop quantitative models for inhibitor binding affinity to Mcl-1 and the Bcl-2 relative Bcl-xL as well as for the specificity of binding to the two proteins. Results indicated hydrophobic interactions with the p2 pockets dominate the affinity of the most favourable binding ligand (3bl: Ki = 31 nM). Compounds were up to 20-fold selective for Mcl-1 over Bcl-xL. Selectivity of the inhibitors was driven by interactions with the deeper p2 pocket in Mcl-1 versus Bcl-xL. The SILCS-based SAR of the present compounds represents the foundation for the development of Mcl-1 specific inhibitors with the potential to treat a wide range of solid tumours and hematological cancers, including acute myeloid leukaemia. PMID:26985630

Petri Net-Based Model of Helicobacter pylori Mediated Disruption of Tight Junction Proteins in Stomach Lining during Gastric Carcinoma

PubMed Central

Naz, Anam; Obaid, Ayesha; Awan, Faryal M.; Ikram, Aqsa; Ahmad, Jamil; Ali, Amjad

2017-01-01

Tight junctions help prevent the passage of digestive enzymes and microorganisms through the space between adjacent epithelial cells lining. However, Helicobacter pylori encoded virulence factors negatively regulate these tight junctions and contribute to dysfunction of gastric mucosa. Here, we have predicted the regulation of important tight junction proteins, such as Zonula occludens-1, Claudin-2 and Connexin32 in the presence of pathogenic proteins. Molecular events such as post translational modifications and crosstalk between phosphorylation, O-glycosylation, palmitoylation and methylation are explored which may compromise the integrity of these tight junction proteins. Furthermore, the signaling pathways disrupted by dysregulated kinases, proteins and post-translational modifications are reviewed to design an abstracted computational model showing the situation-dependent dynamic behaviors of these biological processes and entities. A qualitative hybrid Petri Net model is therefore constructed showing the altered host pathways in the presence of virulence factor cytotoxin-associated gene A, leading to the disruption of tight junction proteins. The model is qualitative logic-based, which does not depend on any kinetic parameter and quantitative data and depends on knowledge derived from experiments. The designed model provides insights into the tight junction disruption and disease progression. Model is then verified by the available experimental data, nevertheless formal in vitro experimentation is a promising way to ensure its validation. The major findings propose that H. pylori activated kinases are responsible to trigger specific post translational modifications within tight junction proteins, at specific sites. These modifications may favor alterations in gastric barrier and provide a route to bacterial invasion into host cells. PMID:28932213

Petri Net-Based Model of Helicobacter pylori Mediated Disruption of Tight Junction Proteins in Stomach Lining during Gastric Carcinoma.

PubMed

Naz, Anam; Obaid, Ayesha; Awan, Faryal M; Ikram, Aqsa; Ahmad, Jamil; Ali, Amjad

2017-01-01

Tight junctions help prevent the passage of digestive enzymes and microorganisms through the space between adjacent epithelial cells lining. However, Helicobacter pylori encoded virulence factors negatively regulate these tight junctions and contribute to dysfunction of gastric mucosa. Here, we have predicted the regulation of important tight junction proteins, such as Zonula occludens-1, Claudin-2 and Connexin32 in the presence of pathogenic proteins. Molecular events such as post translational modifications and crosstalk between phosphorylation, O-glycosylation, palmitoylation and methylation are explored which may compromise the integrity of these tight junction proteins. Furthermore, the signaling pathways disrupted by dysregulated kinases, proteins and post-translational modifications are reviewed to design an abstracted computational model showing the situation-dependent dynamic behaviors of these biological processes and entities. A qualitative hybrid Petri Net model is therefore constructed showing the altered host pathways in the presence of virulence factor cytotoxin-associated gene A, leading to the disruption of tight junction proteins. The model is qualitative logic-based, which does not depend on any kinetic parameter and quantitative data and depends on knowledge derived from experiments. The designed model provides insights into the tight junction disruption and disease progression. Model is then verified by the available experimental data, nevertheless formal in vitro experimentation is a promising way to ensure its validation. The major findings propose that H. pylori activated kinases are responsible to trigger specific post translational modifications within tight junction proteins, at specific sites. These modifications may favor alterations in gastric barrier and provide a route to bacterial invasion into host cells.

HLPI-Ensemble: Prediction of human lncRNA-protein interactions based on ensemble strategy.

PubMed

Hu, Huan; Zhang, Li; Ai, Haixin; Zhang, Hui; Fan, Yetian; Zhao, Qi; Liu, Hongsheng

2018-03-27

LncRNA plays an important role in many biological and disease progression by binding to related proteins. However, the experimental methods for studying lncRNA-protein interactions are time-consuming and expensive. Although there are a few models designed to predict the interactions of ncRNA-protein, they all have some common drawbacks that limit their predictive performance. In this study, we present a model called HLPI-Ensemble designed specifically for human lncRNA-protein interactions. HLPI-Ensemble adopts the ensemble strategy based on three mainstream machine learning algorithms of Support Vector Machines (SVM), Random Forests (RF) and Extreme Gradient Boosting (XGB) to generate HLPI-SVM Ensemble, HLPI-RF Ensemble and HLPI-XGB Ensemble, respectively. The results of 10-fold cross-validation show that HLPI-SVM Ensemble, HLPI-RF Ensemble and HLPI-XGB Ensemble achieved AUCs of 0.95, 0.96 and 0.96, respectively, in the test dataset. Furthermore, we compared the performance of the HLPI-Ensemble models with the previous models through external validation dataset. The results show that the false positives (FPs) of HLPI-Ensemble models are much lower than that of the previous models, and other evaluation indicators of HLPI-Ensemble models are also higher than those of the previous models. It is further showed that HLPI-Ensemble models are superior in predicting human lncRNA-protein interaction compared with previous models. The HLPI-Ensemble is publicly available at: http://ccsipb.lnu.edu.cn/hlpiensemble/ .

Computational analysis of protein-protein interfaces involving an alpha helix: insights for terphenyl-like molecules binding.

PubMed

Isvoran, Adriana; Craciun, Dana; Martiny, Virginie; Sperandio, Olivier; Miteva, Maria A

2013-06-14

Protein-Protein Interactions (PPIs) are key for many cellular processes. The characterization of PPI interfaces and the prediction of putative ligand binding sites and hot spot residues are essential to design efficient small-molecule modulators of PPI. Terphenyl and its derivatives are small organic molecules known to mimic one face of protein-binding alpha-helical peptides. In this work we focus on several PPIs mediated by alpha-helical peptides. We performed computational sequence- and structure-based analyses in order to evaluate several key physicochemical and surface properties of proteins known to interact with alpha-helical peptides and/or terphenyl and its derivatives. Sequence-based analysis revealed low sequence identity between some of the analyzed proteins binding alpha-helical peptides. Structure-based analysis was performed to calculate the volume, the fractal dimension roughness and the hydrophobicity of the binding regions. Besides the overall hydrophobic character of the binding pockets, some specificities were detected. We showed that the hydrophobicity is not uniformly distributed in different alpha-helix binding pockets that can help to identify key hydrophobic hot spots. The presence of hydrophobic cavities at the protein surface with a more complex shape than the entire protein surface seems to be an important property related to the ability of proteins to bind alpha-helical peptides and low molecular weight mimetics. Characterization of similarities and specificities of PPI binding sites can be helpful for further development of small molecules targeting alpha-helix binding proteins.

Encompassing receptor flexibility in virtual screening using ensemble docking-based hybrid QSAR: discovery of novel phytochemicals for BACE1 inhibition.

PubMed

Chakraborty, Sandipan; Ramachandran, Balaji; Basu, Soumalee

2014-10-01

Mimicking receptor flexibility during receptor-ligand binding is a challenging task in computational drug design since it is associated with a large increase in the conformational search space. In the present study, we have devised an in silico design strategy incorporating receptor flexibility in virtual screening to identify potential lead compounds as inhibitors for flexible proteins. We have considered BACE1 (β-secretase), a key target protease from a therapeutic perspective for Alzheimer's disease, as the highly flexible receptor. The protein undergoes significant conformational transitions from open to closed form upon ligand binding, which makes it a difficult target for inhibitor design. We have designed a hybrid structure-activity model containing both ligand based descriptors and energetic descriptors obtained from molecular docking based on a dataset of structurally diverse BACE1 inhibitors. An ensemble of receptor conformations have been used in the docking study, further improving the prediction ability of the model. The designed model that shows significant prediction ability judged by several statistical parameters has been used to screen an in house developed 3-D structural library of 731 phytochemicals. 24 highly potent, novel BACE1 inhibitors with predicted activity (Ki) ≤ 50 nM have been identified. Detailed analysis reveals pharmacophoric features of these novel inhibitors required to inhibit BACE1.

Struct2Net: a web service to predict protein–protein interactions using a structure-based approach

PubMed Central

Singh, Rohit; Park, Daniel; Xu, Jinbo; Hosur, Raghavendra; Berger, Bonnie

2010-01-01

Struct2Net is a web server for predicting interactions between arbitrary protein pairs using a structure-based approach. Prediction of protein–protein interactions (PPIs) is a central area of interest and successful prediction would provide leads for experiments and drug design; however, the experimental coverage of the PPI interactome remains inadequate. We believe that Struct2Net is the first community-wide resource to provide structure-based PPI predictions that go beyond homology modeling. Also, most web-resources for predicting PPIs currently rely on functional genomic data (e.g. GO annotation, gene expression, cellular localization, etc.). Our structure-based approach is independent of such methods and only requires the sequence information of the proteins being queried. The web service allows multiple querying options, aimed at maximizing flexibility. For the most commonly studied organisms (fly, human and yeast), predictions have been pre-computed and can be retrieved almost instantaneously. For proteins from other species, users have the option of getting a quick-but-approximate result (using orthology over pre-computed results) or having a full-blown computation performed. The web service is freely available at http://struct2net.csail.mit.edu. PMID:20513650

Architecture effects on multivalent interactions by polypeptide-based multivalent ligands

NASA Astrophysics Data System (ADS)

Liu, Shuang

Multivalent interactions are characterized by the simultaneous binding between multiple ligands and multiple binding sites, either in solutions or at interfaces. In biological systems, most multivalent interactions occur between protein receptors and carbohydrate ligands through hydrogen-bonding and hydrophobic interactions. Compared with weak affinity binding between one ligand and one binding site, i.e. monovalent interaction, multivalent interactioins provide greater avidity and specificity, and therefore play unique roles in a broad range of biological activities. Moreover, the studies of multivalent interactions are also essential for producing effective inhibitors and effectors of biological processes that could have important therapeutic applications. Synthetic multivalent ligands have been designed to mimic the biological functions of natural multivalent interactions, and various types of scaffolds have been used to display multiple ligands, including small molecules, linear polymers, dendrimers, nanoparticle surfaces, monolayer surfaces and liposomes. Studies have shown that multivalent interactions can be highly affected by various architectural parameters of these multivalent ligands, including ligand identities, valencies, spacing, ligand densities, nature of linker arms, scaffold length and scaffold conformation. Most of these multivalent ligands are chemically synthesized and have limitations of controlling over sequence and conformation, which is a barrier for mimicking ordered and controlled natural biological systems. Therefore, multivalent ligands with precisely controlled architecture are required for improved structure-function relationship studies. Protein engineering methods with subsequent chemical coupling of ligands provide significant advantages of controlling over backbone conformation and functional group placement, and therefore have been used to synthesize recombinant protein-based materials with desired properties similar to natural protein materials, including structural as well as functional proteins. Therefore, polypeptide-based multivalent scaffolds are used to display ligands to assess the contribution of different architectural parameters to the multivalent binding events. In this work, a family of alanine-rich alpha-helical glycopolypeptides was designed and synthesized by a combination of protein engineering and chemical coupling, to display two types of saccharide ligands for two different multivalent binding systems. The valencies, chain length and spacing between adjacent ligands of these multivalent ligands were designed in order to study architecture effects on multivalent interactions. The polypeptides and their glycoconjugates were characterized via various methods, including SDS-PAGE, NMR, HPLC, amino acid analysis (AAA), MALDI, circular dichroism (CD) and GPC. In the first multivalent binding system, cholera toxin B pentamer (CT B5) was chosen to be the protein receptor due to its well-characterized structure, lack of significant steric interference of binding to multiple binding sites, and requirement of only simple monosaccharide as ligands. Galactopyranoside was incorporated into polypeptide scaffolds through amine-carboxylic acid coupling to the side chains of glutamic acid residues. The inhibition and binding to CT B5 of these glycopolypeptide ligands were evaluated by direct enzyme-linked assay (DELA). As a complement method, weak affinity chromatography (WAC) was also used to evaluate glycopolypeptides binding to a CT B5 immobilized column. The architecture effects on CT B 5 inhibition are discussed. In the second system, cell surface receptor L-selectin was targeted by polypeptide-based multivalent ligands containing disulfated galactopyranoside ligands, due to its important roles in various immunological activities. The effects of glycopolypeptide architectural variables L-selectin shedding were evaluated via ELISA-based assays. These polypeptide-based multivalent ligands are suggested to be useful for elucidating architecture effects on multivalent interactions, manipulating multivalent interactions and the subsequent cellular responses in different systems. These materials have great potential applications in therapeutics and could also provide guidelines for design of multivalent ligands for other protein receptors.

Methods for improving simulations of biological systems: systemic computation and fractal proteins

PubMed Central

Bentley, Peter J.

2009-01-01

Modelling and simulation are becoming essential for new fields such as synthetic biology. Perhaps the most important aspect of modelling is to follow a clear design methodology that will help to highlight unwanted deficiencies. The use of tools designed to aid the modelling process can be of benefit in many situations. In this paper, the modelling approach called systemic computation (SC) is introduced. SC is an interaction-based language, which enables individual-based expression and modelling of biological systems, and the interactions between them. SC permits a precise description of a hypothetical mechanism to be written using an intuitive graph-based or a calculus-based notation. The same description can then be directly run as a simulation, merging the hypothetical mechanism and the simulation into the same entity. However, even when using well-designed modelling tools to produce good models, the best model is not always the most accurate one. Frequently, computational constraints or lack of data make it infeasible to model an aspect of biology. Simplification may provide one way forward, but with inevitable consequences of decreased accuracy. Instead of attempting to replace an element with a simpler approximation, it is sometimes possible to substitute the element with a different but functionally similar component. In the second part of this paper, this modelling approach is described and its advantages are summarized using an exemplar: the fractal protein model. Finally, the paper ends with a discussion of good biological modelling practice by presenting lessons learned from the use of SC and the fractal protein model. PMID:19324681

NIAS-Server: Neighbors Influence of Amino acids and Secondary Structures in Proteins.

PubMed

Borguesan, Bruno; Inostroza-Ponta, Mario; Dorn, Márcio

2017-03-01

The exponential growth in the number of experimentally determined three-dimensional protein structures provide a new and relevant knowledge about the conformation of amino acids in proteins. Only a few of probability densities of amino acids are publicly available for use in structure validation and prediction methods. NIAS (Neighbors Influence of Amino acids and Secondary structures) is a web-based tool used to extract information about conformational preferences of amino acid residues and secondary structures in experimental-determined protein templates. This information is useful, for example, to characterize folds and local motifs in proteins, molecular folding, and can help the solution of complex problems such as protein structure prediction, protein design, among others. The NIAS-Server and supplementary data are available at http://sbcb.inf.ufrgs.br/nias .

In silico design of a DNA-based HIV-1 multi-epitope vaccine for Chinese populations

PubMed Central

Yang, Yi; Sun, Weilai; Guo, Jingjing; Zhao, Guangyu; Sun, Shihui; Yu, Hong; Guo, Yan; Li, Jungfeng; Jin, Xia; Du, Lanying; Jiang, Shibo; Kou, Zhihua; Zhou, Yusen

2015-01-01

The development of an HIV-1 vaccine that is capable of inducing effective and broadly cross-reactive humoral and cellular immune responses remains a challenging task because of the extensive diversity of HIV-1, the difference of virus subtypes (clades) in different geographical regions, and the polymorphism of human leukocyte antigens (HLA). We performed an in silico design of 3 DNA vaccines, designated pJW4303-MEG1, pJW4303-MEG2 and pJW4303-MEG3, encoding multi-epitopes that are highly conserved within the HIV-1 subtypes most prevalent in China and can be recognized through HLA alleles dominant in China. The pJW4303-MEG1-encoded protein consisted of one Th epitope in Env, and one, 2, and 6 epitopes in Pol, Env, and Gag proteins, respectively, with a GGGS linker sequence between epitopes. The pJW4303-MEG2-encoded protein contained similar epitopes in a different order, but with the same linker as pJW4303-MEG1. The pJW4303-MEG3-encoded protein contained the same epitopes in the same order as that of pJW4303-MEG2, but with a different linker sequence (AAY). To evaluate immunogenicity, mice were immunized intramuscularly with these DNA vaccines. Both pJW4303-MEG1 and pJW4303-MEG2 vaccines induced equally potent humoral and cellular immune responses in the vaccinated mice, while pJW4303-MEG3 did not induce immune responses. These results indicate that both epitope and linker sequences are important in designing effective epitope-based vaccines against HIV-1 and other viruses. PMID:25839222

Immunoglobulin domain interface exchange as a platform technology for the generation of Fc heterodimers and bispecific antibodies.

PubMed

Skegro, Darko; Stutz, Cian; Ollier, Romain; Svensson, Emelie; Wassmann, Paul; Bourquin, Florence; Monney, Thierry; Gn, Sunitha; Blein, Stanislas

2017-06-09

Bispecific antibodies (bsAbs) are of significant importance to the development of novel antibody-based therapies, and heavy chain (Hc) heterodimers represent a major class of bispecific drug candidates. Current technologies for the generation of Hc heterodimers are suboptimal and often suffer from contamination by homodimers posing purification challenges. Here, we introduce a new technology based on biomimicry wherein the protein-protein interfaces of two different immunoglobulin (Ig) constant domain pairs are exchanged in part or fully to design new heterodimeric domains. The method can be applied across Igs to design Fc heterodimers and bsAbs. We investigated interfaces from human IgA CH3, IgD CH3, IgG1 CH3, IgM CH4, T-cell receptor (TCR) α/β, and TCR γ/δ constant domain pairs, and we found that they successfully drive human IgG1 CH3 or IgM CH4 heterodimerization to levels similar to or above those of reference methods. A comprehensive interface exchange between the TCR α/β constant domain pair and the IgG1 CH3 homodimer was evidenced by X-ray crystallography and used to engineer examples of bsAbs for cancer therapy. Parental antibody pairs were rapidly reformatted into scalable bsAbs that were free of homodimer traces by combining interface exchange, asymmetric Protein A binding, and the scFv × Fab format. In summary, we successfully built several new CH3- or CH4-based heterodimers that may prove useful for designing new bsAb-based therapeutics, and we anticipate that our approach could be broadly implemented across the Ig constant domain family. To our knowledge, CH4-based heterodimers have not been previously reported. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Flume Computer-Aided Design (CAD): Integrated CAD for Microflume Components and Systems

DTIC Science & Technology

2002-04-01

31 3.3: Matching the Mix Ratio (Part B...sizes) will be optimized based on the required flow rates and mixing ratios of the different species. The influence of etch depth is investigated on a...Inhibition Study In this network, the target protein is mixed with protease (i.e. enzyme that cleaves the target protein) and the protease inhibitor (the

Large-scale protein/antibody patterning with limiting unspecific adsorption

NASA Astrophysics Data System (ADS)

Fedorenko, Viktoriia; Bechelany, Mikhael; Janot, Jean-Marc; Smyntyna, Valentyn; Balme, Sebastien

2017-10-01

A simple synthetic route based on nanosphere lithography has been developed in order to design a large-scale nanoarray for specific control of protein anchoring. This technique based on two-dimensional (2D) colloidal crystals composed of polystyrene spheres allows the easy and inexpensive fabrication of large arrays (up to several centimeters) by reducing the cost. A silicon wafer coated with a thin adhesion layer of chromium (15 nm) and a layer of gold (50 nm) is used as a substrate. PS spheres are deposited on the gold surface using the floating-transferring technique. The PS spheres were then functionalized with PEG-biotin and the defects by self-assembly monolayer (SAM) PEG to prevent unspecific adsorption. Using epifluorescence microscopy, we show that after immersion of sample on target protein (avidin and anti-avidin) solution, the latter are specifically located on polystyrene spheres. Thus, these results are meaningful for exploration of devices based on a large-scale nanoarray of PS spheres and can be used for detection of target proteins or simply to pattern a surface with specific proteins.

MOWGLI: prediction of protein-MannOse interacting residues With ensemble classifiers usinG evoLutionary Information.

PubMed

Pai, Priyadarshini P; Mondal, Sukanta

2016-10-01

Proteins interact with carbohydrates to perform various cellular interactions. Of the many carbohydrate ligands that proteins bind with, mannose constitute an important class, playing important roles in host defense mechanisms. Accurate identification of mannose-interacting residues (MIR) may provide important clues to decipher the underlying mechanisms of protein-mannose interactions during infections. This study proposes an approach using an ensemble of base classifiers for prediction of MIR using their evolutionary information in the form of position-specific scoring matrix. The base classifiers are random forests trained by different subsets of training data set Dset128 using 10-fold cross-validation. The optimized ensemble of base classifiers, MOWGLI, is then used to predict MIR on protein chains of the test data set Dtestset29 which showed a promising performance with 92.0% accurate prediction. An overall improvement of 26.6% in precision was observed upon comparison with the state-of-art. It is hoped that this approach, yielding enhanced predictions, could be eventually used for applications in drug design and vaccine development.

A rapid, generally applicable method to engineer zinc fingers illustrated by targeting the HIV-1 promoter.

PubMed

Isalan, M; Klug, A; Choo, Y

2001-07-01

DNA-binding domains with predetermined sequence specificity are engineered by selection of zinc finger modules using phage display, allowing the construction of customized transcription factors. Despite remarkable progress in this field, the available protein-engineering methods are deficient in many respects, thus hampering the applicability of the technique. Here we present a rapid and convenient method that can be used to design zinc finger proteins against a variety of DNA-binding sites. This is based on a pair of pre-made zinc finger phage-display libraries, which are used in parallel to select two DNA-binding domains each of which recognizes given 5 base pair sequences, and whose products are recombined to produce a single protein that recognizes a composite (9 base pair) site of predefined sequence. Engineering using this system can be completed in less than two weeks and yields proteins that bind sequence-specifically to DNA with Kd values in the nanomolar range. To illustrate the technique, we have selected seven different proteins to bind various regions of the human immunodeficiency virus 1 (HIV-1) promoter.

Collagen peptide-based biomaterials for protein delivery and peptide-promoted self-assembly of gold nanoparticles

NASA Astrophysics Data System (ADS)

Ernenwein, Dawn M.

2011-12-01

Bottom-up self-assembly of peptides has driven the research progress for the following two projects: protein delivery vehicles of collagen microflorettes and the assembly of gold nanoparticles with coiled-coil peptides. Collagen is the most abundant protein in the mammals yet due to immunogenic responses, batch-to-batch variability and lack of sequence modifications, synthetic collagen has been designed to self-assemble into native collagen-like structures. In particular with this research, metal binding ligands were incorporated on the termini of collagen-like peptides to generate micron-sized particles, microflorettes. The over-arching goal of the first research project is to engineer MRI-active microflorettes, loaded with His-tagged growth factors with differential release rates while bound to stem cells that can be implemented toward regenerative cell-based therapies. His-tagged proteins, such as green fluorescent protein, have successfully been incorporated on the surface and throughout the microflorettes. Protein release was monitored under physiological conditions and was related to particle degradation. In human plasma full release was obtained within six days. Stability of the microflorettes under physiological conditions was also examined for the development of a therapeutically relevant delivery agent. Additionally, MRI active microflorettes have been generated through the incorporation of a gadolinium binding ligand, DOTA within the collagen-based peptide sequence. To probe peptide-promoted self-assemblies of gold nanoparticles (GNPs) by non-covalent, charge complementary interactions, a highly anionic coiled-coil peptide was designed and synthesized. Upon formation of peptide-GNP interactions, the hydrophobic domain of the coiled-coil were shown to promote the self-assembly of peptide-GNPs clustering. Hydrophobic forces were found to play an important role in the assembly process, as a peptide with an equally overall negative charge, but lacking an ordered hydrophobic face had no effect on GNP assembly. The self-assembly system herein is advantageous due to its reversible nature upon addition of high salt concentrations which masks the surface charge. There is great potential for using this uniquely designed self-assembled peptide-gold nanoparticle system for exploring the interplay between peptide ligation and GNP self-assembly.

A simple tagging system for protein encapsulation.

PubMed

Seebeck, Florian P; Woycechowsky, Kenneth J; Zhuang, Wei; Rabe, Jürgen P; Hilvert, Donald

2006-04-12

Molecular containers that encapsulate specific cargo can be useful for many natural and non-natural processes. We report a simple system, based on charge complementarity, for the encapsulation of appropriately tagged proteins within an engineered, proteinaceous capsid. Four negative charges per monomer were added to the lumazine synthase from Aquifex aeolicus (AaLS). The capsids formed by the engineered AaLS associate with green fluorescent protein bearing a positively charged deca-arginine tag upon coproduction in Escherichia coli. Analytical ultracentrifugation and scanning force microscopy studies indicated that the engineered AaLS retains the ability to form capsids, but that their average size was substantially increased. The success of this strategy demonstrates that both the container and guest components of protein-based encapsulation systems can be convergently designed in a straightforward manner, which may help to extend their versatility.

The application of polysaccharide-based nanogels in peptides/proteins and anticancer drugs delivery.

PubMed

Zhang, Lin; Pan, Jifei; Dong, Shibo; Li, Zhaoming

2017-09-01

Finding adequate carriers for proteins/peptides and anticancer drugs delivery has become an urgent need, owing to the growing number of therapeutic macromolecules and the increasing amount of cancer incidence. Polysaccharide-based nanogels have attracted interest as carriers for proteins/peptides and anticancer drugs because of their characteristic properties like biodegradability, biocompatibility, stimuli-responsive behaviour, softness and swelling to help achieve a controlled, triggered response at the target site. In addition, the groups of the polysaccharide backbone are able to be modified to develop functional nanogels. Some polysaccharides have the intrinsic ability to recognise specific cell types, allowing the design of targeted drug delivery systems through receptor-mediated endocytosis. This review is aimed at describing and exploring the potential of polysaccharides that are used in nanogels which can help to deliver proteins/peptides and anticancer drugs.

Deciphering mRNA Sequence Determinants of Protein Production Rate

NASA Astrophysics Data System (ADS)

Szavits-Nossan, Juraj; Ciandrini, Luca; Romano, M. Carmen

2018-03-01

One of the greatest challenges in biophysical models of translation is to identify coding sequence features that affect the rate of translation and therefore the overall protein production in the cell. We propose an analytic method to solve a translation model based on the inhomogeneous totally asymmetric simple exclusion process, which allows us to unveil simple design principles of nucleotide sequences determining protein production rates. Our solution shows an excellent agreement when compared to numerical genome-wide simulations of S. cerevisiae transcript sequences and predicts that the first 10 codons, which is the ribosome footprint length on the mRNA, together with the value of the initiation rate, are the main determinants of protein production rate under physiological conditions. Finally, we interpret the obtained analytic results based on the evolutionary role of the codons' choice for regulating translation rates and ribosome densities.

Optical system for the Protein Crystallisation Diagnostics Facility (PCDF) on board the ISS

NASA Astrophysics Data System (ADS)

Joannes, Luc; Dupont, Olivier; Dewandel, Jean-Luc; Ligot, Renaud; Algrain, Hervé

2004-06-01

The Protein Crystallisation Diagnostic Facility (PCDF) is a multi-user facility to study the protein crystallisation under the conditions of micro-gravity onboard the International Space Station (ISS) Columbus facility. Large size protein crystals will growth under reduced gravity in thermally controlled reactors. A combination of diagnostic tools like video system, microscope, interferometer, and light scattering device shall help to understand the growth phenomena. Common methods of protein crystallisation shall be performed in PCDF: Dialysis where the protein solution and the salt solution are separated by a semi-permeable membrane. Extended Length Dialysis Batch where the saturation to get crystals is achieved by changing the concentration of the protein in the sample liquid. The overall ESA project is leaded by EADS Space Transportation, Friedrichshafen, Germany. Lambda-X is responsible for the Optical System (OS), with Verhaert Design and Development as sub-contractor for the mechanical design. The OS includes different compact parts: Original illumination systems based on LEDs of difference colours; Quantitative Mach-Zehnder interferometers to measure the concentration distribution around crystals; Imaging assemblies to visualize the protein volume with different field of views. The paper concentrates on the description of each part, and in particular on the imaging assembly which allow switching from one field of view to another by passive elements only.

Protein Crystal Growth With the Aid of Microfluidics

NASA Technical Reports Server (NTRS)

vanderWoerd, Mark

2003-01-01

Protein crystallography is one of three well-known methods to obtain the structure of proteins. A major rate limiting step in protein crystallography is protein crystal nucleation and growth, which is still largely a process conducted by trial-and-error methods. Many attempts have been made to improve protein crystal growth by performing growth in microgravity. Although the use of microgravity appears to improve crystal quality in some attempts, this method has been inefficient because several reasons: we lack a fundamental understanding of macromolecular crystal growth in general and of the influence of microgravity in particular, we have to start with crystal growth conditions in microgravity based on conditions on the ground and finally the hardware does not allow for experimental iteration without reloading samples on the ground. To partially accommodate the disadvantages of the current hardware, we have used microfluidic technology (Lab-on-a-Chip devices) to design the concept of a more efficient crystallization device, suitable for use on the International Space Station and in high-throughput applications on the ground. The concept and properties of microfluidics, the application design process, and the advances in protein crystal growth hardware will be discussed in this presentation. Some examples of proteins crystallized in the new hardware will be discussed, including the differences between conventional crystallization versus crystallization in microfluidics.

How To Design a Successful p53-MDM2/X Interaction Inhibitor: A Thorough Overview Based on Crystal Structures.

PubMed

Estrada-Ortiz, Natalia; Neochoritis, Constantinos G; Dömling, Alexander

2016-04-19

A recent therapeutic strategy in oncology is based on blocking the protein-protein interaction between the murine double minute (MDM) homologues MDM2/X and the tumor-suppressor protein p53. Inhibiting the binding between wild-type (WT) p53 and its negative regulators MDM2 and/or MDMX has become an important target in oncology to restore the antitumor activity of p53, the so-called guardian of our genome. Interestingly, based on the multiple disclosed compound classes and structural analysis of small-molecule-MDM2 adducts, the p53-MDM2 complex is perhaps the best studied and most targeted protein-protein interaction. Several classes of small molecules have been identified as potent, selective, and efficient inhibitors of the p53-MDM2/X interaction, and many co-crystal structures with the protein are available. Herein we review the properties as well as preclinical and clinical studies of these small molecules and peptides, categorized by scaffold type. A particular emphasis is made on crystallographic structures and the observed binding modes of these compounds, including conserved water molecules present. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Prediction and redesign of protein–protein interactions

PubMed Central

Lua, Rhonald C.; Marciano, David C.; Katsonis, Panagiotis; Adikesavan, Anbu K.; Wilkins, Angela D.; Lichtarge, Olivier

2014-01-01

Understanding the molecular basis of protein function remains a central goal of biology, with the hope to elucidate the role of human genes in health and in disease, and to rationally design therapies through targeted molecular perturbations. We review here some of the computational techniques and resources available for characterizing a critical aspect of protein function – those mediated by protein–protein interactions (PPI). We describe several applications and recent successes of the Evolutionary Trace (ET) in identifying molecular events and shapes that underlie protein function and specificity in both eukaryotes and prokaryotes. ET is a part of analytical approaches based on the successes and failures of evolution that enable the rational control of PPI. PMID:24878423

Systematic Prediction of Scaffold Proteins Reveals New Design Principles in Scaffold-Mediated Signal Transduction

PubMed Central

Hu, Jianfei; Neiswinger, Johnathan; Zhang, Jin; Zhu, Heng; Qian, Jiang

2015-01-01

Scaffold proteins play a crucial role in facilitating signal transduction in eukaryotes by bringing together multiple signaling components. In this study, we performed a systematic analysis of scaffold proteins in signal transduction by integrating protein-protein interaction and kinase-substrate relationship networks. We predicted 212 scaffold proteins that are involved in 605 distinct signaling pathways. The computational prediction was validated using a protein microarray-based approach. The predicted scaffold proteins showed several interesting characteristics, as we expected from the functionality of scaffold proteins. We found that the scaffold proteins are likely to interact with each other, which is consistent with previous finding that scaffold proteins tend to form homodimers and heterodimers. Interestingly, a single scaffold protein can be involved in multiple signaling pathways by interacting with other scaffold protein partners. Furthermore, we propose two possible regulatory mechanisms by which the activity of scaffold proteins is coordinated with their associated pathways through phosphorylation process. PMID:26393507

Single chain Fc-dimer-human growth hormone fusion protein for improved drug delivery.

PubMed

Zhou, Li; Wang, Hsuan-Yao; Tong, Shanshan; Okamoto, Curtis T; Shen, Wei-Chiang; Zaro, Jennica L

2017-02-01

Fc fusion protein technology has been successfully used to generate long-acting forms of several protein therapeutics. In this study, a novel Fc-based drug carrier, single chain Fc-dimer (sc(Fc) 2 ), was designed to contain two Fc domains recombinantly linked via a flexible linker. Since the Fc dimeric structure is maintained through the flexible linker, the hinge region was omitted to further stabilize it against proteolysis and reduce FcγR-related effector functions. The resultant sc(Fc) 2 candidate preserved the neonatal Fc receptor (FcRn) binding. sc(Fc) 2 -mediated delivery was then evaluated using a therapeutic protein with a short plasma half-life, human growth hormone (hGH), as the protein drug cargo. This novel carrier protein showed a prolonged in vivo half-life and increased hGH-mediated bioactivity compared to the traditional Fc-based drug carrier. sc(Fc) 2 technology has the potential to greatly advance and expand the use of Fc-technology for improving the pharmacokinetics and bioactivity of protein therapeutics. Copyright © 2016 Elsevier Ltd. All rights reserved.

Epitope-based recombinant diagnostic antigen to distinguish natural infection from vaccination with hepatitis A virus vaccines.

PubMed

Su, Qiudong; Guo, Minzhuo; Jia, Zhiyuan; Qiu, Feng; Lu, Xuexin; Gao, Yan; Meng, Qingling; Tian, Ruiguang; Bi, Shengli; Yi, Yao

2016-07-01

Hepatitis A virus (HAV) infection can stimulate the production of antibodies to structural and non-structural proteins of the virus. However, vaccination with an inactivated or attenuated HAV vaccine produces antibodies mainly against structural proteins, whereas no or very limited antibodies are produced against the non-structural proteins. Current diagnostic assays to determine exposure to HAV, such as the Abbott HAV AB test, detect antibodies only to the structural proteins and so are not able to distinguish a natural infection from vaccination with an inactivated or attenuated virus. Here, we constructed a recombinant tandem multi-epitope diagnostic antigen (designated 'H1') based on the immune-dominant epitopes of the non-structural proteins of HAV to distinguish the two situations. H1 protein expressed in Escherichia coli and purified by affinity and anion exchange chromatography was applied in a double-antigen sandwich ELISA for the detection of anti-non-structural HAV proteins, which was confirmed to distinguish a natural infection from vaccination with an inactivated or attenuated HAV vaccine. Copyright © 2016 Elsevier B.V. All rights reserved.

Design and construction of a first-generation high-throughput integrated robotic molecular biology platform for bioenergy applications.

PubMed

Hughes, Stephen R; Butt, Tauseef R; Bartolett, Scott; Riedmuller, Steven B; Farrelly, Philip

2011-08-01

The molecular biological techniques for plasmid-based assembly and cloning of gene open reading frames are essential for elucidating the function of the proteins encoded by the genes. High-throughput integrated robotic molecular biology platforms that have the capacity to rapidly clone and express heterologous gene open reading frames in bacteria and yeast and to screen large numbers of expressed proteins for optimized function are an important technology for improving microbial strains for biofuel production. The process involves the production of full-length complementary DNA libraries as a source of plasmid-based clones to express the desired proteins in active form for determination of their functions. Proteins that were identified by high-throughput screening as having desired characteristics are overexpressed in microbes to enable them to perform functions that will allow more cost-effective and sustainable production of biofuels. Because the plasmid libraries are composed of several thousand unique genes, automation of the process is essential. This review describes the design and implementation of an automated integrated programmable robotic workcell capable of producing complementary DNA libraries, colony picking, isolating plasmid DNA, transforming yeast and bacteria, expressing protein, and performing appropriate functional assays. These operations will allow tailoring microbial strains to use renewable feedstocks for production of biofuels, bioderived chemicals, fertilizers, and other coproducts for profitable and sustainable biorefineries. Published by Elsevier Inc.

Challenges and Opportunities for Small-Molecule Fluorescent Probes in Redox Biology Applications.

PubMed

Jiang, Xiqian; Wang, Lingfei; Carroll, Shaina L; Chen, Jianwei; Wang, Meng C; Wang, Jin

2018-02-16

The concentrations of reactive oxygen/nitrogen species (ROS/RNS) are critical to various biochemical processes. Small-molecule fluorescent probes have been widely used to detect and/or quantify ROS/RNS in many redox biology studies and serve as an important complementary to protein-based sensors with unique applications. Recent Advances: New sensing reactions have emerged in probe development, allowing more selective and quantitative detection of ROS/RNS, especially in live cells. Improvements have been made in sensing reactions, fluorophores, and bioavailability of probe molecules. In this review, we will not only summarize redox-related small-molecule fluorescent probes but also lay out the challenges of designing probes to help redox biologists independently evaluate the quality of reported small-molecule fluorescent probes, especially in the chemistry literature. We specifically highlight the advantages of reversibility in sensing reactions and its applications in ratiometric probe design for quantitative measurements in living cells. In addition, we compare the advantages and disadvantages of small-molecule probes and protein-based probes. The low physiological relevant concentrations of most ROS/RNS call for new sensing reactions with better selectivity, kinetics, and reversibility; fluorophores with high quantum yield, wide wavelength coverage, and Stokes shifts; and structural design with good aqueous solubility, membrane permeability, low protein interference, and organelle specificity. Antioxid. Redox Signal. 00, 000-000.

Targeting the Allosteric Site of Oncoprotein BCR-ABL as an Alternative Strategy for Effective Target Protein Degradation.

PubMed

Shimokawa, Kenichiro; Shibata, Norihito; Sameshima, Tomoya; Miyamoto, Naoki; Ujikawa, Osamu; Nara, Hiroshi; Ohoka, Nobumichi; Hattori, Takayuki; Cho, Nobuo; Naito, Mikihiko

2017-10-12

Protein degradation technology based on hybrid small molecules is an emerging drug modality that has significant potential in drug discovery and as a unique method of post-translational protein knockdown in the field of chemical biology. Here, we report the first example of a novel and potent protein degradation inducer that binds to an allosteric site of the oncogenic BCR-ABL protein. BCR-ABL allosteric ligands were incorporated into the SNIPER (Specific and Nongenetic inhibitor of apoptosis protein [IAP]-dependent Protein Erasers) platform, and a series of in vitro biological assays of binding affinity, target protein modulation, signal transduction, and growth inhibition were carried out. One of the designed compounds, 6 (SNIPER(ABL)-062), showed desirable binding affinities against ABL1, cIAP1/2, and XIAP and consequently caused potent BCR-ABL degradation.

Production of membrane proteins without cells or detergents.

PubMed

Rajesh, Sundaresan; Knowles, Timothy; Overduin, Michael

2011-04-30

The production of membrane proteins in cellular systems is besieged by several problems due to their hydrophobic nature which often causes misfolding, protein aggregation and cytotoxicity, resulting in poor yields of stable proteins. Cell-free expression has emerged as one of the most versatile alternatives for circumventing these obstacles by producing membrane proteins directly into designed hydrophobic environments. Efficient optimisation of expression and solubilisation conditions using a variety of detergents, membrane mimetics and lipids has yielded structurally and functionally intact membrane proteins, with yields several fold above the levels possible from cell-based systems. Here we review recently developed techniques available to produce functional membrane proteins, and discuss amphipols, nanodisc and styrene maleic acid lipid particle (SMALP) technologies that can be exploited alongside cell-free expression of membrane proteins. Copyright © 2010 Elsevier B.V. All rights reserved.

The Structure and Function of Non-Collagenous Bone Proteins

NASA Technical Reports Server (NTRS)

Hook, Magnus; McQuillan, David J.

1997-01-01

The research done under the cooperative research agreement for the project titled 'The structure and function of non-collagenous bone proteins' represented the first phase of an ongoing program to define the structural and functional relationships of the principal noncollagenous proteins in bone. An ultimate goal of this research is to enable design and execution of useful pharmacological compounds that will have a beneficial effect in treatment of osteoporosis, both land-based and induced by long-duration space travel. The goals of the now complete first phase were as follows: 1. Establish and/or develop powerful recombinant protein expression systems; 2. Develop and refine isolation and purification of recombinant proteins; 3. Express wild-type non-collagenous bone proteins; 4. Express site-specific mutant proteins and domains of wild-type proteins to enhance likelihood of crystal formation for subsequent solution of structure.

Quality by design approach for viral clearance by protein a chromatography

PubMed Central

Zhang, Min; Miesegaes, George R; Lee, Michael; Coleman, Daniel; Yang, Bin; Trexler-Schmidt, Melody; Norling, Lenore; Lester, Philip; Brorson, Kurt A; Chen, Qi

2014-01-01

Protein A chromatography is widely used as a capture step in monoclonal antibody (mAb) purification processes. Antibodies and Fc fusion proteins can be efficiently purified from the majority of other complex components in harvested cell culture fluid (HCCF). Protein A chromatography is also capable of removing modest levels of viruses and is often validated for viral clearance. Historical data mining of Genentech and FDA/CDER databases systematically evaluated the removal of model viruses by Protein A chromatography. First, we found that for each model virus, removal by Protein A chromatography varies significantly across mAbs, while remains consistent within a specific mAb product, even across the acceptable ranges of the process parameters. In addition, our analysis revealed a correlation between retrovirus and parvovirus removal, with retrovirus data generally possessing a greater clearance factor. Finally, we describe a multivariate approach used to evaluate process parameter impacts on viral clearance, based on the levels of retrovirus-like particles (RVLP) present among process characterization study samples. It was shown that RVLP removal by Protein A is robust, that is, parameter effects were not observed across the ranges tested. Robustness of RVLP removal by Protein A also correlates with that for other model viruses such as X-MuLV, MMV, and SV40. The data supports that evaluating RVLP removal using process characterization study samples can establish multivariate acceptable ranges for virus removal by the protein A step for QbD. By measuring RVLP instead of a model retrovirus, it may alleviate some of the technical and economic challenges associated with performing large, design-of-experiment (DoE)—type virus spiking studies. This approach could also serve to provide useful insight when designing strategies to ensure viral safety in the manufacturing of a biopharmaceutical product. PMID:23860745

A highly efficient approach to protein interactome mapping based on collaborative filtering framework.

PubMed

Luo, Xin; You, Zhuhong; Zhou, Mengchu; Li, Shuai; Leung, Hareton; Xia, Yunni; Zhu, Qingsheng

2015-01-09

The comprehensive mapping of protein-protein interactions (PPIs) is highly desired for one to gain deep insights into both fundamental cell biology processes and the pathology of diseases. Finely-set small-scale experiments are not only very expensive but also inefficient to identify numerous interactomes despite their high accuracy. High-throughput screening techniques enable efficient identification of PPIs; yet the desire to further extract useful knowledge from these data leads to the problem of binary interactome mapping. Network topology-based approaches prove to be highly efficient in addressing this problem; however, their performance deteriorates significantly on sparse putative PPI networks. Motivated by the success of collaborative filtering (CF)-based approaches to the problem of personalized-recommendation on large, sparse rating matrices, this work aims at implementing a highly efficient CF-based approach to binary interactome mapping. To achieve this, we first propose a CF framework for it. Under this framework, we model the given data into an interactome weight matrix, where the feature-vectors of involved proteins are extracted. With them, we design the rescaled cosine coefficient to model the inter-neighborhood similarity among involved proteins, for taking the mapping process. Experimental results on three large, sparse datasets demonstrate that the proposed approach outperforms several sophisticated topology-based approaches significantly.

A Highly Efficient Approach to Protein Interactome Mapping Based on Collaborative Filtering Framework

PubMed Central

Luo, Xin; You, Zhuhong; Zhou, Mengchu; Li, Shuai; Leung, Hareton; Xia, Yunni; Zhu, Qingsheng

2015-01-01

The comprehensive mapping of protein-protein interactions (PPIs) is highly desired for one to gain deep insights into both fundamental cell biology processes and the pathology of diseases. Finely-set small-scale experiments are not only very expensive but also inefficient to identify numerous interactomes despite their high accuracy. High-throughput screening techniques enable efficient identification of PPIs; yet the desire to further extract useful knowledge from these data leads to the problem of binary interactome mapping. Network topology-based approaches prove to be highly efficient in addressing this problem; however, their performance deteriorates significantly on sparse putative PPI networks. Motivated by the success of collaborative filtering (CF)-based approaches to the problem of personalized-recommendation on large, sparse rating matrices, this work aims at implementing a highly efficient CF-based approach to binary interactome mapping. To achieve this, we first propose a CF framework for it. Under this framework, we model the given data into an interactome weight matrix, where the feature-vectors of involved proteins are extracted. With them, we design the rescaled cosine coefficient to model the inter-neighborhood similarity among involved proteins, for taking the mapping process. Experimental results on three large, sparse datasets demonstrate that the proposed approach outperforms several sophisticated topology-based approaches significantly. PMID:25572661

A Highly Efficient Approach to Protein Interactome Mapping Based on Collaborative Filtering Framework

NASA Astrophysics Data System (ADS)

Luo, Xin; You, Zhuhong; Zhou, Mengchu; Li, Shuai; Leung, Hareton; Xia, Yunni; Zhu, Qingsheng

2015-01-01

The comprehensive mapping of protein-protein interactions (PPIs) is highly desired for one to gain deep insights into both fundamental cell biology processes and the pathology of diseases. Finely-set small-scale experiments are not only very expensive but also inefficient to identify numerous interactomes despite their high accuracy. High-throughput screening techniques enable efficient identification of PPIs; yet the desire to further extract useful knowledge from these data leads to the problem of binary interactome mapping. Network topology-based approaches prove to be highly efficient in addressing this problem; however, their performance deteriorates significantly on sparse putative PPI networks. Motivated by the success of collaborative filtering (CF)-based approaches to the problem of personalized-recommendation on large, sparse rating matrices, this work aims at implementing a highly efficient CF-based approach to binary interactome mapping. To achieve this, we first propose a CF framework for it. Under this framework, we model the given data into an interactome weight matrix, where the feature-vectors of involved proteins are extracted. With them, we design the rescaled cosine coefficient to model the inter-neighborhood similarity among involved proteins, for taking the mapping process. Experimental results on three large, sparse datasets demonstrate that the proposed approach outperforms several sophisticated topology-based approaches significantly.

Manipulating fatty acid biosynthesis in microalgae for biofuel through protein-protein interactions.

PubMed

Blatti, Jillian L; Beld, Joris; Behnke, Craig A; Mendez, Michael; Mayfield, Stephen P; Burkart, Michael D

2012-01-01

Microalgae are a promising feedstock for renewable fuels, and algal metabolic engineering can lead to crop improvement, thus accelerating the development of commercially viable biodiesel production from algae biomass. We demonstrate that protein-protein interactions between the fatty acid acyl carrier protein (ACP) and thioesterase (TE) govern fatty acid hydrolysis within the algal chloroplast. Using green microalga Chlamydomonas reinhardtii (Cr) as a model, a structural simulation of docking CrACP to CrTE identifies a protein-protein recognition surface between the two domains. A virtual screen reveals plant TEs with similar in silico binding to CrACP. Employing an activity-based crosslinking probe designed to selectively trap transient protein-protein interactions between the TE and ACP, we demonstrate in vitro that CrTE must functionally interact with CrACP to release fatty acids, while TEs of vascular plants show no mechanistic crosslinking to CrACP. This is recapitulated in vivo, where overproduction of the endogenous CrTE increased levels of short-chain fatty acids and engineering plant TEs into the C. reinhardtii chloroplast did not alter the fatty acid profile. These findings highlight the critical role of protein-protein interactions in manipulating fatty acid biosynthesis for algae biofuel engineering as illuminated by activity-based probes.

Manipulating Fatty Acid Biosynthesis in Microalgae for Biofuel through Protein-Protein Interactions

PubMed Central

Blatti, Jillian L.; Beld, Joris; Behnke, Craig A.; Mendez, Michael; Mayfield, Stephen P.; Burkart, Michael D.

2012-01-01

Microalgae are a promising feedstock for renewable fuels, and algal metabolic engineering can lead to crop improvement, thus accelerating the development of commercially viable biodiesel production from algae biomass. We demonstrate that protein-protein interactions between the fatty acid acyl carrier protein (ACP) and thioesterase (TE) govern fatty acid hydrolysis within the algal chloroplast. Using green microalga Chlamydomonas reinhardtii (Cr) as a model, a structural simulation of docking CrACP to CrTE identifies a protein-protein recognition surface between the two domains. A virtual screen reveals plant TEs with similar in silico binding to CrACP. Employing an activity-based crosslinking probe designed to selectively trap transient protein-protein interactions between the TE and ACP, we demonstrate in vitro that CrTE must functionally interact with CrACP to release fatty acids, while TEs of vascular plants show no mechanistic crosslinking to CrACP. This is recapitulated in vivo, where overproduction of the endogenous CrTE increased levels of short-chain fatty acids and engineering plant TEs into the C. reinhardtii chloroplast did not alter the fatty acid profile. These findings highlight the critical role of protein-protein interactions in manipulating fatty acid biosynthesis for algae biofuel engineering as illuminated by activity-based probes. PMID:23028438

Illustrating and homology modeling the proteins of the Zika virus

PubMed Central

Ekins, Sean; Liebler, John; Neves, Bruno J.; Lewis, Warren G.; Coffee, Megan; Bienstock, Rachelle; Southan, Christopher; Andrade, Carolina H.

2016-01-01

The Zika virus (ZIKV) is a flavivirus of the family Flaviviridae, which is similar to dengue virus, yellow fever and West Nile virus. Recent outbreaks in South America, Latin America, the Caribbean and in particular Brazil have led to concern for the spread of the disease and potential to cause Guillain-Barré syndrome and microcephaly. Although ZIKV has been known of for over 60 years there is very little in the way of knowledge of the virus with few publications and no crystal structures. No antivirals have been tested against it either in vitro or in vivo. ZIKV therefore epitomizes a neglected disease. Several suggested steps have been proposed which could be taken to initiate ZIKV antiviral drug discovery using both high throughput screens as well as structure-based design based on homology models for the key proteins. We now describe preliminary homology models created for NS5, FtsJ, NS4B, NS4A, HELICc, DEXDc, peptidase S7, NS2B, NS2A, NS1, E stem, glycoprotein M, propeptide, capsid and glycoprotein E using SWISS-MODEL. Eleven out of 15 models pass our model quality criteria for their further use. While a ZIKV glycoprotein E homology model was initially described in the immature conformation as a trimer, we now describe the mature dimer conformer which allowed the construction of an illustration of the complete virion. By comparing illustrations of ZIKV based on this new homology model and the dengue virus crystal structure we propose potential differences that could be exploited for antiviral and vaccine design. The prediction of sites for glycosylation on this protein may also be useful in this regard. While we await a cryo-EM structure of ZIKV and eventual crystal structures of the individual proteins, these homology models provide the community with a starting point for structure-based design of drugs and vaccines as well as a for computational virtual screening. PMID:27746901

Predicting "Hot" and "Warm" Spots for Fragment Binding.

PubMed

Rathi, Prakash Chandra; Ludlow, R Frederick; Hall, Richard J; Murray, Christopher W; Mortenson, Paul N; Verdonk, Marcel L

2017-05-11

Computational fragment mapping methods aim to predict hotspots on protein surfaces where small fragments will bind. Such methods are popular for druggability assessment as well as structure-based design. However, to date researchers developing or using such tools have had no clear way of assessing the performance of these methods. Here, we introduce the first diverse, high quality validation set for computational fragment mapping. The set contains 52 diverse examples of fragment binding "hot" and "warm" spots from the Protein Data Bank (PDB). Additionally, we describe PLImap, a novel protocol for fragment mapping based on the Protein-Ligand Informatics force field (PLIff). We evaluate PLImap against the new fragment mapping test set, and compare its performance to that of simple shape-based algorithms and fragment docking using GOLD. PLImap is made publicly available from https://bitbucket.org/AstexUK/pli .

Nanocellulose-based biosensors: design, preparation, and activity of peptide-linked cotton cellulose nanocrystals having fluorimetric and colorimetric elastase detection sensitivity

USDA-ARS?s Scientific Manuscript database

Nanocrystalline cellulose is an amphiphilic, high surface area material that can be easily functionalized and is biocom-patible and eco-friendly. It has been used singularly and in combination with other nanomaterials to optimize biosensor design. The attachment of peptides and proteins to nanocryst...

Artemisinin activity-based probes identify multiple molecular targets within the asexual stage of the malaria parasites Plasmodium falciparum 3D7

PubMed Central

Ismail, Hanafy M.; Barton, Victoria; Phanchana, Matthew; Charoensutthivarakul, Sitthivut; Wong, Michael H. L.; Hemingway, Janet; Biagini, Giancarlo A.; O’Neill, Paul M.; Ward, Stephen A.

2016-01-01

The artemisinin (ART)-based antimalarials have contributed significantly to reducing global malaria deaths over the past decade, but we still do not know how they kill parasites. To gain greater insight into the potential mechanisms of ART drug action, we developed a suite of ART activity-based protein profiling probes to identify parasite protein drug targets in situ. Probes were designed to retain biological activity and alkylate the molecular target(s) of Plasmodium falciparum 3D7 parasites in situ. Proteins tagged with the ART probe can then be isolated using click chemistry before identification by liquid chromatography–MS/MS. Using these probes, we define an ART proteome that shows alkylated targets in the glycolytic, hemoglobin degradation, antioxidant defense, and protein synthesis pathways, processes essential for parasite survival. This work reveals the pleiotropic nature of the biological functions targeted by this important class of antimalarial drugs. PMID:26858419