Challenges and advances in validating enzyme design proposals: the case of kemp eliminase catalysis.

PubMed

Frushicheva, Maria P; Cao, Jie; Warshel, Arieh

2011-05-10

One of the fundamental challenges in biotechnology and biochemistry is the ability to design effective enzymes. Despite recent progress, most of the advances on this front have been made by placing the reacting fragments in the proper places, rather than by optimizing the preorganization of the environment, which is the key factor in enzyme catalysis. Thus, rational improvement of the preorganization would require approaches capable of evaluating reliably the actual catalytic effect. This work considers the catalytic effects in different Kemp eliminases as a benchmark for a computer-aided enzyme design. It is shown that the empirical valence bond provides a powerful screening tool, with significant advantages over current alternative strategies. The insights provided by the empirical valence bond calculations are discussed with an emphasis on the ability to analyze the difference between the linear free energy relationships obtained in solution and those found in the enzymes. We also point out the trade-off between the reliability and speed of the calculations and try to determine what it takes to realize reliable computer-aided screening.

Role of conformational dynamics in the evolution of novel enzyme function.

PubMed

Maria-Solano, Miguel A; Serrano-Hervás, Eila; Romero-Rivera, Adrian; Iglesias-Fernández, Javier; Osuna, Sílvia

2018-05-21

The free energy landscape concept that describes enzymes as an ensemble of differently populated conformational sub-states in dynamic equilibrium is key for evaluating enzyme activity, enantioselectivity, and specificity. Mutations introduced in the enzyme sequence can alter the populations of the pre-existing conformational states, thus strongly modifying the enzyme ability to accommodate alternative substrates, revert its enantiopreferences, and even increase the activity for some residual promiscuous reactions. In this feature article, we present an overview of the current experimental and computational strategies to explore the conformational free energy landscape of enzymes. We provide a series of recent publications that highlight the key role of conformational dynamics for the enzyme evolution towards new functions and substrates, and provide some perspectives on how conformational dynamism should be considered in future computational enzyme design protocols.

Computer-generated Model of Purine Nucleoside Phosphorylase (PNP)

NASA Technical Reports Server (NTRS)

1987-01-01

Purine Nucleoside Phosphorylase (PNP) is an important target enzyme for the design of anti-cancer and immunosuppressive drugs. Bacterial PNP, which is slightly different from the human enzyme, is used to synthesize chemotherapuautic agents. Knowledge of the three-dimensional structure of the bacterial PNP molecule is useful in efforts to engineer different types of PNP enzymes, that can be used to produce new chemotherapeutic agents. This picture shows a computer model of bacterial PNP, which looks a lot like a display of colorful ribbons. Principal Investigator was Charles Bugg.

Optimization of the in silico designed Kemp eliminase KE70 by computational design and directed evolution

PubMed Central

Khersonsky, Olga; Röthlisberger, Daniela; Wollacott, Andrew M.; Murphy, Paul; Dym, Orly; Albeck, Shira; Kiss, Gert; Houk, K. N.; Baker, David; Tawfik, Dan S.

2013-01-01

Although de novo computational enzyme design has been shown to be feasible, the field is still in its infancy: the kinetic parameters of designed enzymes are still orders of magnitude lower than those of naturally occurring ones. Nonetheless, designed enzymes can be improved by directed evolution, as recently exemplified for the designed Kemp eliminase KE07. Random mutagenesis and screening resulted in variants with >200-fold higher catalytic efficiency, and provided insights about features missing in the designed enzyme. Here we describe the optimization of KE70, another designed Kemp eliminase. Amino acid substitutions predicted to improve catalysis in design calculations involving extensive backbone sampling were individually tested. Those proven beneficial were combinatorially incorporated into the originally designed KE70 along with random mutations, and the resulting libraries were screened for improved eliminase activity. Nine rounds of mutation and selection resulted in >400-fold improvement in the catalytic efficiency of the original KE70 design, reflected in both higher kcat and lower KM values, with the best variants exhibiting kcat/KM values of >5x104 s−1M−1. The optimized KE70 variants were characterized structurally and biochemically providing insights into the origins of the improvements in catalysis. Three primary contributions were identified: first, the reshaping of the active site cavity to achieve tighter substrate binding; second, the fine-tuning of the electrostatics around the catalytic His-Asp dyad; and third, stabilization of the active-site dyad in a conformation optimal for catalysis. PMID:21277311

De Novo Computational Design of Retro-Aldol Enzymes

PubMed Central

Jiang, Lin; Althoff, Eric A.; Clemente, Fernando R.; Doyle, Lindsey; Röthlisberger, Daniela; Zanghellini, Alexandre; Gallaher, Jasmine L.; Betker, Jamie L.; Tanaka, Fujie; Barbas, Carlos F.; Hilvert, Donald; Houk, Kendall N.; Stoddard, Barry L.; Baker, David

2012-01-01

The creation of enzymes capable of catalyzing any desired chemical reaction is a grand challenge for computational protein design. Using new algorithms that rely on hashing techniques to construct active sites for multistep reactions, we designed retro-aldolases that use four different catalytic motifs to catalyze the breaking of a carbon-carbon bond in a nonnatural substrate. Of the 72 designs that were experimentally characterized, 32, spanning a range of protein folds, had detectable retro-aldolase activity. Designs that used an explicit water molecule to mediate proton shuffling were significantly more successful, with rate accelerations of up to four orders of magnitude and multiple turnovers, than those involving charged side-chain networks. The atomic accuracy of the design process was confirmed by the x-ray crystal structure of active designs embedded in two protein scaffolds, both of which were nearly superimposable on the design model. PMID:18323453

Integrative genomic mining for enzyme function to enable engineering of a non-natural biosynthetic pathway.

PubMed

Mak, Wai Shun; Tran, Stephen; Marcheschi, Ryan; Bertolani, Steve; Thompson, James; Baker, David; Liao, James C; Siegel, Justin B

2015-11-24

The ability to biosynthetically produce chemicals beyond what is commonly found in Nature requires the discovery of novel enzyme function. Here we utilize two approaches to discover enzymes that enable specific production of longer-chain (C5-C8) alcohols from sugar. The first approach combines bioinformatics and molecular modelling to mine sequence databases, resulting in a diverse panel of enzymes capable of catalysing the targeted reaction. The median catalytic efficiency of the computationally selected enzymes is 75-fold greater than a panel of naively selected homologues. This integrative genomic mining approach establishes a unique avenue for enzyme function discovery in the rapidly expanding sequence databases. The second approach uses computational enzyme design to reprogramme specificity. Both approaches result in enzymes with >100-fold increase in specificity for the targeted reaction. When enzymes from either approach are integrated in vivo, longer-chain alcohol production increases over 10-fold and represents >95% of the total alcohol products.

Hybrid schemes based on quantum mechanics/molecular mechanics simulations goals to success, problems, and perspectives.

PubMed

Ferrer, Silvia; Ruiz-Pernía, Javier; Martí, Sergio; Moliner, Vicent; Tuñón, Iñaki; Bertrán, Juan; Andrés, Juan

2011-01-01

The development of characterization techniques, advanced synthesis methods, as well as molecular modeling has transformed the study of systems in a well-established research field. The current research challenges in biocatalysis and biotransformation evolve around enzyme discovery, design, and optimization. How can we find or create enzymes that catalyze important synthetic reactions, even reactions that may not exist in nature? What is the source of enzyme catalytic power? To answer these and other related questions, the standard strategies have evolved from trial-and-error methodologies based on chemical knowledge, accumulated experience, and common sense into a clearly multidisciplinary science that allows one to reach the molecular design of tailor-made enzyme catalysts. This is even more so when one refers to enzyme catalysts, for which the detailed structure and composition are known and can be manipulated to introduce well-defined residues which can be implicated in the chemical rearrangements taking place in the active site. The methods and techniques of theoretical and computational chemistry are becoming more and more important in both understanding the fundamental biological roles of enzymes and facilitating their utilization in biotechnology. Improvement of the catalytic function of enzymes is important from scientific and industrial viewpoints, and to put this fact in the actual perspective as well as the potentialities, we recommend the very recent report of Sanderson [Sanderson, K. (2011). Chemistry: enzyme expertise. Nature 471, 397.]. Great fundamental advances have been made toward the ab initio design of enzyme catalysts based on molecular modeling. This has been based on the molecular mechanistic knowledge of the reactions to be catalyzed, together with the development of advanced synthesis and characterization techniques. The corresponding molecular mechanism can be studied by means of powerful quantum chemical calculations. The catalytic active site can be optimized to improve the transition state analogues (TSA) and to enhance the catalytic activity, even improve the active site to favor a desired direction of some promiscuous enzymes. In this chapter, we give a brief introduction, the state of the art, and future prospects and implications of enzyme design. Current computational tools to assist experimentalists for the design and engineering of proteins with desired catalytic properties are described. The interplay between enzyme design, molecular simulations, and experiments will be presented to emphasize the interdisciplinary nature of this research field. This text highlights the recent advances and examples selected from our laboratory are shown, of how the applications of these tools are a first attempt to de novo design of protein active sites. Identification of neutral/advantageous/deleterious mutation platforms can be exploited to penetrate some of Nature's closely guarded secrets of chemical reactivity. In this chapter, we give a brief introduction, the state of the art, and future prospects and implications of enzyme design. The first part describes briefly how the molecular modeling is carried out. Then, we discuss the requirements of hybrid quantum mechanical/molecular mechanics molecular dynamics (QM/MM MD) simulations, analyzing what are the basis of these theoretical methodologies, how we can use them with a view to its application in the study of enzyme catalysis, and what are the best methodologies for assessing its catalytic potential. In the second part, we focus on some selected examples, taking as a common guide the chorismate to prephenate rearrangement, studying the corresponding molecular mechanism in vacuo, in solution and in an enzyme environment. In addition, examples involving catalytic antibodies (CAs) and promiscuous enzymes will be presented. Finally, a special emphasis is made to provide some hints about the logical evolution that can be anticipated in this research field. Moreover, it helps in understanding the open directions in this area of knowledge and highlights the importance of computational approaches in discovering specific drugs and the impact on the rational design of tailor-made enzymes. Copyright © 2011 Elsevier Inc. All rights reserved.

Computational protein design with backbone plasticity

PubMed Central

MacDonald, James T.; Freemont, Paul S.

2016-01-01

The computational algorithms used in the design of artificial proteins have become increasingly sophisticated in recent years, producing a series of remarkable successes. The most dramatic of these is the de novo design of artificial enzymes. The majority of these designs have reused naturally occurring protein structures as ‘scaffolds’ onto which novel functionality can be grafted without having to redesign the backbone structure. The incorporation of backbone flexibility into protein design is a much more computationally challenging problem due to the greatly increased search space, but promises to remove the limitations of reusing natural protein scaffolds. In this review, we outline the principles of computational protein design methods and discuss recent efforts to consider backbone plasticity in the design process. PMID:27911735

Computational approach for designing thermostable Candida antarctica lipase B by molecular dynamics simulation.

PubMed

Park, Hyun June; Park, Kyungmoon; Kim, Yong Hwan; Yoo, Young Je

2014-12-20

Candida antarctica lipase B (CalB) is one of the most useful enzyme for various reactions and bioconversions. Enhancing thermostability of CalB is required for industrial applications. In this study, we propose a computational design strategy to improve the thermostability of CalB. Molecular dynamics simulations at various temperatures were used to investigate the common fluctuation sites in CalB, which are considered to be thermally weak points. The RosettaDesign algorithm was used to design the selected residues. The redesigned CalB was simulated to verify both the enhancement of intramolecular interactions and the lowering of the overall root-mean-square deviation (RMSD) values. The A251E mutant designed using this strategy showed a 2.5-fold higher thermostability than the wild-type CalB. This strategy could apply to other industry applicable enzymes. Copyright © 2014 Elsevier B.V. All rights reserved.

Design of activated serine-containing catalytic triads with atomic level accuracy

PubMed Central

Rajagopalan, Sridharan; Wang, Chu; Yu, Kai; Kuzin, Alexandre P.; Richter, Florian; Lew, Scott; Miklos, Aleksandr E.; Matthews, Megan L.; Seetharaman, Jayaraman; Su, Min; Hunt, John. F.; Cravatt, Benjamin F.; Baker, David

2014-01-01

A challenge in the computational design of enzymes is that multiple properties must be simultaneously optimized -- substrate-binding, transition state stabilization, and product release -- and this has limited the absolute activity of successful designs. Here, we focus on a single critical property of many enzymes: the nucleophilicity of an active site residue that initiates catalysis. We design proteins with idealized serine-containing catalytic triads, and assess their nucleophilicity directly in native biological systems using activity-based organophosphate probes. Crystal structures of the most successful designs show unprecedented agreement with computational models, including extensive hydrogen bonding networks between the catalytic triad (or quartet) residues, and mutagenesis experiments demonstrate that these networks are critical for serine activation and organophosphate-reactivity. Following optimization by yeast-display, the designs react with organophosphate probes at rates comparable to natural serine hydrolases. Co-crystal structures with diisopropyl fluorophosphate bound to the serine nucleophile suggest the designs could provide the basis for a new class of organophosphate captures agents. PMID:24705591

Redesigning the specificity of protein-DNA interactions with Rosetta.

PubMed

Thyme, Summer; Baker, David

2014-01-01

Building protein tools that can selectively bind or cleave specific DNA sequences requires efficient technologies for modifying protein-DNA interactions. Computational design is one method for accomplishing this goal. In this chapter, we present the current state of protein-DNA interface design with the Rosetta macromolecular modeling program. The LAGLIDADG endonuclease family of DNA-cleaving enzymes, under study as potential gene therapy reagents, has been the main testing ground for these in silico protocols. At this time, the computational methods are most useful for designing endonuclease variants that can accommodate small numbers of target site substitutions. Attempts to engineer for more extensive interface changes will likely benefit from an approach that uses the computational design results in conjunction with a high-throughput directed evolution or screening procedure. The family of enzymes presents an engineering challenge because their interfaces are highly integrated and there is significant coordination between the binding and catalysis events. Future developments in the computational algorithms depend on experimental feedback to improve understanding and modeling of these complex enzymatic features. This chapter presents both the basic method of design that has been successfully used to modulate specificity and more advanced procedures that incorporate DNA flexibility and other properties that are likely necessary for reliable modeling of more extensive target site changes.

DockScreen: A database of in silico biomolecular interactions to support computational toxicology

EPA Science Inventory

We have developed DockScreen, a database of in silico biomolecular interactions designed to enable rational molecular toxicological insight within a computational toxicology framework. This database is composed of chemical/target (receptor and enzyme) binding scores calculated by...

Substrate tunnels in enzymes: structure-function relationships and computational methodology.

PubMed

Kingsley, Laura J; Lill, Markus A

2015-04-01

In enzymes, the active site is the location where incoming substrates are chemically converted to products. In some enzymes, this site is deeply buried within the core of the protein, and, in order to access the active site, substrates must pass through the body of the protein via a tunnel. In many systems, these tunnels act as filters and have been found to influence both substrate specificity and catalytic mechanism. Identifying and understanding how these tunnels exert such control has been of growing interest over the past several years because of implications in fields such as protein engineering and drug design. This growing interest has spurred the development of several computational methods to identify and analyze tunnels and how ligands migrate through these tunnels. The goal of this review is to outline how tunnels influence substrate specificity and catalytic efficiency in enzymes with buried active sites and to provide a brief summary of the computational tools used to identify and evaluate these tunnels. © 2015 Wiley Periodicals, Inc.

Substrate Tunnels in Enzymes: Structure-Function Relationships and Computational Methodology

PubMed Central

Kingsley, Laura J.; Lill, Markus A.

2015-01-01

In enzymes, the active site is the location where incoming substrates are chemically converted to products. In some enzymes, this site is deeply buried within the core of the protein and in order to access the active site, substrates must pass through the body of the protein via a tunnel. In many systems, these tunnels act as filters and have been found to influence both substrate specificity and catalytic mechanism. Identifying and understanding how these tunnels exert such control has been of growing interest over the past several years due to implications in fields such as protein engineering and drug design. This growing interest has spurred the development of several computational methods to identify and analyze tunnels and how ligands migrate through these tunnels. The goal of this review is to outline how tunnels influence substrate specificity and catalytic efficiency in enzymes with tunnels and to provide a brief summary of the computational tools used to identify and evaluate these tunnels. PMID:25663659

Identification of metabolic engineering targets for the enhancement of 1,4-butanediol production in recombinant E. coli using large-scale kinetic models.

PubMed

Andreozzi, Stefano; Chakrabarti, Anirikh; Soh, Keng Cher; Burgard, Anthony; Yang, Tae Hoon; Van Dien, Stephen; Miskovic, Ljubisa; Hatzimanikatis, Vassily

2016-05-01

Rational metabolic engineering methods are increasingly employed in designing the commercially viable processes for the production of chemicals relevant to pharmaceutical, biotechnology, and food and beverage industries. With the growing availability of omics data and of methodologies capable to integrate the available data into models, mathematical modeling and computational analysis are becoming important in designing recombinant cellular organisms and optimizing cell performance with respect to desired criteria. In this contribution, we used the computational framework ORACLE (Optimization and Risk Analysis of Complex Living Entities) to analyze the physiology of recombinant Escherichia coli producing 1,4-butanediol (BDO) and to identify potential strategies for improved production of BDO. The framework allowed us to integrate data across multiple levels and to construct a population of large-scale kinetic models despite the lack of available information about kinetic properties of every enzyme in the metabolic pathways. We analyzed these models and we found that the enzymes that primarily control the fluxes leading to BDO production are part of central glycolysis, the lower branch of tricarboxylic acid (TCA) cycle and the novel BDO production route. Interestingly, among the enzymes between the glucose uptake and the BDO pathway, the enzymes belonging to the lower branch of TCA cycle have been identified as the most important for improving BDO production and yield. We also quantified the effects of changes of the target enzymes on other intracellular states like energy charge, cofactor levels, redox state, cellular growth, and byproduct formation. Independent earlier experiments on this strain confirmed that the computationally obtained conclusions are consistent with the experimentally tested designs, and the findings of the present studies can provide guidance for future work on strain improvement. Overall, these studies demonstrate the potential and effectiveness of ORACLE for the accelerated design of microbial cell factories. Copyright © 2016 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Improving thermal and detergent stability of Bacillus stearothermophilus neopullulanase by rational enzyme design.

PubMed

Ece, Selin; Evran, Serap; Janda, Jan-Oliver; Merkl, Rainer; Sterner, Reinhard

2015-06-01

Neopullulanase, a glycosyl hydrolase from Bacillus stearothermophilus (bsNpl), is a potentially valuable enzyme for starch and detergent industries. However, as the protein is not active at elevated temperatures and high surfactant concentrations, we aimed to increase its stability by rational enzyme design. Nine potentially destabilizing cavities were identified in the crystal structure of the enzyme. Based on computational predictions, these cavities were filled by residues with bulkier side chains. The five Asp46Glu, Val239Leu, Val404Leu, Ser407Thr and Ala566Leu exchanges resulted in a drastic stabilization of bsNpl against inactivation by heat and detergents. The catalytic activity of the variants was identical to the wild-type enzyme. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Computational Glycobiology: Mechanistic Studies of Carbohydrate-Active Enzymes and Implication for Inhibitor Design.

PubMed

Montgomery, Andrew P; Xiao, Kela; Wang, Xingyong; Skropeta, Danielle; Yu, Haibo

2017-01-01

Carbohydrate-active enzymes (CAZymes) are families of essential and structurally related enzymes, which catalyze the creation, modification, and degradation of glycosidic bonds in carbohydrates to maintain essentially all kingdoms of life. CAZymes play a key role in many biological processes underpinning human health and diseases (e.g., cancer, diabetes, Alzheimer's diseases, AIDS) and have thus emerged as important drug targets in the fight against pathogenesis. The realization of the full potential of CAZymes remains a significant challenge, relying on a deeper understanding of the molecular mechanisms of catalysis. Considering numerous unsettled questions in the literature, while with a large amount of structural, kinetic, and mutagenesis data available for CAZymes, there is a pressing need and an abundant opportunity for collaborative computational and experimental investigations with the aim to unlock the secrets of CAZyme catalysis at an atomic level. In this review, we briefly survey key methodology development in computational studies of CAZyme catalysis. This is complemented by selected case studies highlighting mechanistic insights provided by computational glycobiology. Implication for inhibitor design by mimicking the transition state is also illustrated for both glycoside hydrolases and glycosyltransferases. The challenges for such studies will be noted and finally an outlook for future directions will be provided. © 2017 Elsevier Inc. All rights reserved.

Inhibitor design strategy based on an enzyme structural flexibility: a case of bacterial MurD ligase.

PubMed

Perdih, Andrej; Hrast, Martina; Barreteau, Hélène; Gobec, Stanislav; Wolber, Gerhard; Solmajer, Tom

2014-05-27

Increasing bacterial resistance to available antibiotics stimulated the discovery of novel efficacious antibacterial agents. The biosynthesis of the bacterial peptidoglycan, where the MurD enzyme is involved in the intracellular phase of the UDP-MurNAc-pentapeptide formation, represents a collection of highly selective targets for novel antibacterial drug design. In our previous computational studies, the C-terminal domain motion of the MurD ligase was investigated using Targeted Molecular Dynamic (TMD) simulation and the Off-Path Simulation (OPS) technique. In this study, we present a drug design strategy using multiple protein structures for the identification of novel MurD ligase inhibitors. Our main focus was the ATP-binding site of the MurD enzyme. In the first stage, three MurD protein conformations were selected based on the obtained OPS/TMD data as the initial criterion. Subsequently, a two-stage virtual screening approach was utilized combining derived structure-based pharmacophores with molecular docking calculations. Selected compounds were then assayed in the established enzyme binding assays, and compound 3 from the aminothiazole class was discovered to act as a dual MurC/MurD inhibitor in the micomolar range. A steady-state kinetic study was performed on the MurD enzyme to provide further information about the mechanistic aspects of its inhibition. In the final stage, all used conformations of the MurD enzyme with compound 3 were simulated in classical molecular dynamics (MD) simulations providing atomistic insights of the experimental results. Overall, the study depicts several challenges that need to be addressed when trying to hit a flexible moving target such as the presently studied bacterial MurD enzyme and show the possibilities of how computational tools can be proficiently used at all stages of the drug discovery process.

Exploring the combinatorial space of complete pathways to chemicals.

PubMed

Wang, Lin; Ng, Chiam Yu; Dash, Satyakam; Maranas, Costas D

2018-04-06

Computational pathway design tools often face the challenges of balancing the stoichiometry of co-metabolites and cofactors, and dealing with reaction rule utilization in a single workflow. To this end, we provide an overview of two complementary stoichiometry-based pathway design tools optStoic and novoStoic developed in our group to tackle these challenges. optStoic is designed to determine the stoichiometry of overall conversion first which optimizes a performance criterion (e.g. high carbon/energy efficiency) and ensures a comprehensive search of co-metabolites and cofactors. The procedure then identifies the minimum number of intervening reactions to connect the source and sink metabolites. We also further the pathway design procedure by expanding the search space to include both known and hypothetical reactions, represented by reaction rules, in a new tool termed novoStoic. Reaction rules are derived based on a mixed-integer linear programming (MILP) compatible reaction operator, which allow us to explore natural promiscuous enzymes, engineer candidate enzymes that are not already promiscuous as well as design de novo enzymes. The identified biochemical reaction rules then guide novoStoic to design routes that expand the currently known biotransformation space using a single MILP modeling procedure. We demonstrate the use of the two computational tools in pathway elucidation by designing novel synthetic routes for isobutanol. © 2018 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

Quantum mechanical design of enzyme active sites.

PubMed

Zhang, Xiyun; DeChancie, Jason; Gunaydin, Hakan; Chowdry, Arnab B; Clemente, Fernando R; Smith, Adam J T; Handel, T M; Houk, K N

2008-02-01

The design of active sites has been carried out using quantum mechanical calculations to predict the rate-determining transition state of a desired reaction in presence of the optimal arrangement of catalytic functional groups (theozyme). Eleven versatile reaction targets were chosen, including hydrolysis, dehydration, isomerization, aldol, and Diels-Alder reactions. For each of the targets, the predicted mechanism and the rate-determining transition state (TS) of the uncatalyzed reaction in water is presented. For the rate-determining TS, a catalytic site was designed using naturalistic catalytic units followed by an estimation of the rate acceleration provided by a reoptimization of the catalytic site. Finally, the geometries of the sites were compared to the X-ray structures of related natural enzymes. Recent advances in computational algorithms and power, coupled with successes in computational protein design, have provided a powerful context for undertaking such an endeavor. We propose that theozymes are excellent candidates to serve as the active site models for design processes.

The Application of the Weighted k-Partite Graph Problem to the Multiple Alignment for Metabolic Pathways.

PubMed

Chen, Wenbin; Hendrix, William; Samatova, Nagiza F

2017-12-01

The problem of aligning multiple metabolic pathways is one of very challenging problems in computational biology. A metabolic pathway consists of three types of entities: reactions, compounds, and enzymes. Based on similarities between enzymes, Tohsato et al. gave an algorithm for aligning multiple metabolic pathways. However, the algorithm given by Tohsato et al. neglects the similarities among reactions, compounds, enzymes, and pathway topology. How to design algorithms for the alignment problem of multiple metabolic pathways based on the similarity of reactions, compounds, and enzymes? It is a difficult computational problem. In this article, we propose an algorithm for the problem of aligning multiple metabolic pathways based on the similarities among reactions, compounds, enzymes, and pathway topology. First, we compute a weight between each pair of like entities in different input pathways based on the entities' similarity score and topological structure using Ay et al.'s methods. We then construct a weighted k-partite graph for the reactions, compounds, and enzymes. We extract a mapping between these entities by solving the maximum-weighted k-partite matching problem by applying a novel heuristic algorithm. By analyzing the alignment results of multiple pathways in different organisms, we show that the alignments found by our algorithm correctly identify common subnetworks among multiple pathways.

Microgravity

NASA Image and Video Library

1987-02-01

Purine Nucleoside Phosphorylase (PNP) is an important target enzyme for the design of anti-cancer and immunosuppressive drugs. Bacterial PNP, which is slightly different from the human enzyme, is used to synthesize chemotherapuautic agents. Knowledge of the three-dimensional structure of the bacterial PNP molecule is useful in efforts to engineer different types of PNP enzymes, that can be used to produce new chemotherapeutic agents. This picture shows a computer model of bacterial PNP, which looks a lot like a display of colorful ribbons. Principal Investigator was Charles Bugg.

Unraveling Entropic Rate Acceleration Induced by Solvent Dynamics in Membrane Enzymes.

PubMed

Kürten, Charlotte; Syrén, Per-Olof

2016-01-16

Enzyme catalysis evolved in an aqueous environment. The influence of solvent dynamics on catalysis is, however, currently poorly understood and usually neglected. The study of water dynamics in enzymes and the associated thermodynamical consequences is highly complex and has involved computer simulations, nuclear magnetic resonance (NMR) experiments, and calorimetry. Water tunnels that connect the active site with the surrounding solvent are key to solvent displacement and dynamics. The protocol herein allows for the engineering of these motifs for water transport, which affects specificity, activity and thermodynamics. By providing a biophysical framework founded on theory and experiments, the method presented herein can be used by researchers without previous expertise in computer modeling or biophysical chemistry. The method will advance our understanding of enzyme catalysis on the molecular level by measuring the enthalpic and entropic changes associated with catalysis by enzyme variants with obstructed water tunnels. The protocol can be used for the study of membrane-bound enzymes and other complex systems. This will enhance our understanding of the importance of solvent reorganization in catalysis as well as provide new catalytic strategies in protein design and engineering.

Validation of RetroPath, a computer-aided design tool for metabolic pathway engineering.

PubMed

Fehér, Tamás; Planson, Anne-Gaëlle; Carbonell, Pablo; Fernández-Castané, Alfred; Grigoras, Ioana; Dariy, Ekaterina; Perret, Alain; Faulon, Jean-Loup

2014-11-01

Metabolic engineering has succeeded in biosynthesis of numerous commodity or high value compounds. However, the choice of pathways and enzymes used for production was many times made ad hoc, or required expert knowledge of the specific biochemical reactions. In order to rationalize the process of engineering producer strains, we developed the computer-aided design (CAD) tool RetroPath that explores and enumerates metabolic pathways connecting the endogenous metabolites of a chassis cell to the target compound. To experimentally validate our tool, we constructed 12 top-ranked enzyme combinations producing the flavonoid pinocembrin, four of which displayed significant yields. Namely, our tool queried the enzymes found in metabolic databases based on their annotated and predicted activities. Next, it ranked pathways based on the predicted efficiency of the available enzymes, the toxicity of the intermediate metabolites and the calculated maximum product flux. To implement the top-ranking pathway, our procedure narrowed down a list of nine million possible enzyme combinations to 12, a number easily assembled and tested. One round of metabolic network optimization based on RetroPath output further increased pinocembrin titers 17-fold. In total, 12 out of the 13 enzymes tested in this work displayed a relative performance that was in accordance with its predicted score. These results validate the ranking function of our CAD tool, and open the way to its utilization in the biosynthesis of novel compounds. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Design of a prototype flow microreactor for synthetic biology in vitro.

PubMed

Boehm, Christian R; Freemont, Paul S; Ces, Oscar

2013-09-07

As a reference platform for in vitro synthetic biology, we have developed a prototype flow microreactor for enzymatic biosynthesis. We report the design, implementation, and computer-aided optimisation of a three-step model pathway within a microfluidic reactor. A packed bed format was shown to be optimal for enzyme compartmentalisation after experimental evaluation of several approaches. The specific substrate conversion efficiency could significantly be improved by an optimised parameter set obtained by computational modelling. Our microreactor design provides a platform to explore new in vitro synthetic biology solutions for industrial biosynthesis.

Computational Design of a Thermostable Mutant of Cocaine Esterase via Molecular Dynamics Simulations

PubMed Central

Huang, Xiaoqin; Gao, Daquan; Zhan, Chang-Guo

2015-01-01

Cocaine esterase (CocE) has been known as the most efficient native enzyme for metabolizing the naturally occurring cocaine. A major obstacle to the clinical application of CocE is the thermoinstability of native CocE with a half-life of only ~11 min at physiological temperature (37°C). It is highly desirable to develop a thermostable mutant of CocE for therapeutic treatment of cocaine overdose and addiction. To establish a structure-thermostability relationship, we carried out molecular dynamics (MD) simulations at 400 K on wild-type CocE and previously known thermostable mutants, demonstrating that the thermostability of the active form of the enzyme correlates with the fluctuation (characterized as the RMSD and RMSF of atomic positions) of the catalytic residues (Y44, S117, Y118, H287, and D259) in the simulated enzyme. In light of the structure-thermostability correlation, further computational modeling including MD simulations at 400 K predicted that the active site structure of the L169K mutant should be more thermostable. The prediction has been confirmed by wet experimental tests showing that the active form of the L169K mutant had a half-life of 570 min at 37°C, which is significantly longer than those of the wild-type and previously known thermostable mutants. The encouraging outcome suggests that the high-temperature MD simulations and the structure-thermostability may be considered as a valuable tool for computational design of thermostable mutants of an enzyme. PMID:21373712

Design, synthesis and bioactivity evaluation of tribactam beta lactamase inhibitors.

PubMed

Copar, Anton; Prevec, Tadeja; Anzic, Borut; Mesar, Tomaz; Selic, Lovro; Vilar, Mateja; Solmajer, Tom

2002-03-25

Known carbapenem compounds with inhibitory effect towards beta-lactamase enzymes are formed from bicyclical beta lactam structural scaffolds. On the basis of results from theoretical computational methods and molecular modelling we have designed and developed a synthetic route towards novel, biologically active tricyclic derivatives of carbapenems.

Prediction of the solvent affecting site and the computational design of stable Candida antarctica lipase B in a hydrophilic organic solvent.

PubMed

Park, Hyun June; Joo, Jeong Chan; Park, Kyungmoon; Kim, Yong Hwan; Yoo, Young Je

2013-02-10

Enzyme reactions in organic solvent such as for organic synthesis have great industrial potential. However, enzymes lose their stability in hydrophilic organic solvents due to the deformation of the enzyme by the solvent. It is thus important to enhance the stability of enzymes in hydrophilic organic solvents. Previous approaches have not considered on the interaction between enzymes and solvents due to the lack of information. In this study, the structural motions of the enzyme in methanol cosolvent and the interaction between the enzyme surface and the solvent molecule were investigated using molecular dynamics simulation (MD). By analyzing the MD simulation results, the surface residues of Candida antarctica lipase B (CalB) with higher root mean square deviation (RMSD) in a methanol solvent were considered as methanol affecting site and selected for site-directed mutagenesis. The methanol affecting site was computationally redesigned by lowering the RMSD. Among the candidate mutants, the A8T, A92E, N97Q and T245S mutants showed higher organic solvent stability at various methanol concentrations. The rational approach developed in this study could be applied to the stabilization of other industrial enzymes used in organic solvents. Copyright © 2012 Elsevier B.V. All rights reserved.

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

A new test of computational protein design: predicting posttranslational modification specificity for the enzyme SMYD2.

PubMed

Reynolds, Kimberly A

2015-01-06

In this issue of Structure, Lanouette and colleagues use a combination of computation and experiment to define a specificity motif for the lysine methyltransferase SMYD2. Using this motif, they predict and experimentally verify four new SMYD2 substrates. Copyright © 2015 Elsevier Ltd. All rights reserved.

Molecular Dynamics Studies of Proton Transport in Hydrogenase and Hydrogenase Mimics.

PubMed

Ginovska, B; Raugei, S; Shaw, W J

2016-01-01

There is extensive interest in hydrogenases based on their ability to rapidly and efficiently interconvert H2 with protons and electrons, and their (typically) superior function relative to molecular mimics. Understanding the function of enzymes is one approach to implementing design features to make better catalysts and is an approach we have implemented in our work. In this review, we will discuss our efforts to develop design principles from enzymes, with specific focus on proton transport. We will also present computational studies of the mimics we have investigated with similar methodologies. We will discuss the mechanisms used by small scaffolds on molecular mimics which in many cases are surprisingly similar to those used by nature, while in other cases, computational analysis allowed us to reveal an unexpected role. Computational methods provide one of the best ways, and in some cases, the only way, to gain insight into the mechanistic details of enzymes. In this review, we illustrate the general computational strategy we used to study the proton pathway of [FeFe]-hydrogenase, and the similar strategy to investigate small molecules. We present the main results we obtained and how our computational work stimulated or worked in concert with experimental investigations. We also focus on estimation of errors and convergence of properties in the simulations. These studies demonstrate the powerful results that can be obtained by the close pairing of experimental and theoretical approaches. Copyright © 2016 Elsevier Inc. All rights reserved. Battelle, operator of PNNL, under Contract No: DE-AC05-76RL01830 with US DoE.

Evolution of a designed retro-aldolase leads to complete active site remodeling

PubMed Central

Giger, Lars; Caner, Sami; Obexer, Richard; Kast, Peter; Baker, David; Ban, Nenad; Hilvert, Donald

2013-01-01

Evolutionary advances are often fueled by unanticipated innovation. Directed evolution of a computationally designed enzyme suggests that dramatic molecular changes can also drive the optimization of primitive protein active sites. The specific activity of an artificial retro-aldolase was boosted >4,400 fold by random mutagenesis and screening, affording catalytic efficiencies approaching those of natural enzymes. However, structural and mechanistic studies reveal that the engineered catalytic apparatus, consisting of a reactive lysine and an ordered water molecule, was unexpectedly abandoned in favor of a new lysine residue in a substrate binding pocket created during the optimization process. Structures of the initial in silico design, a mechanistically promiscuous intermediate, and one of the most evolved variants highlight the importance of loop mobility and supporting functional groups in the emergence of the new catalytic center. Such internal competition between alternative reactive sites may have characterized the early evolution of many natural enzymes. PMID:23748672

Molecular Docking of Enzyme Inhibitors: A Computational Tool for Structure-Based Drug Design

ERIC Educational Resources Information Center

Rudnitskaya, Aleksandra; Torok, Bela; Torok, Marianna

2010-01-01

Molecular docking is a frequently used method in structure-based rational drug design. It is used for evaluating the complex formation of small ligands with large biomolecules, predicting the strength of the bonding forces and finding the best geometrical arrangements. The major goal of this advanced undergraduate biochemistry laboratory exercise…

A Quantitative Measure of Conformational Changes in Apo, Holo and Ligand-Bound Forms of Enzymes.

PubMed

Singh, Satendra; Singh, Atul Kumar; Wadhwa, Gulshan; Singh, Dev Bukhsh; Dwivedi, Seema; Gautam, Budhayash; Ramteke, Pramod W

2016-06-01

Determination of the native geometry of the enzymes and ligand complexes is a key step in the process of structure-based drug designing. Enzymes and ligands show flexibility in structural behavior as they come in contact with each other. When ligand binds with active site of the enzyme, in the presence of cofactor some structural changes are expected to occur in the active site. Motivation behind this study is to determine the nature of conformational changes as well as regions where such changes are more pronounced. To measure the structural changes due to cofactor and ligand complex, enzyme in apo, holo and ligand-bound forms is selected. Enzyme data set was retrieved from protein data bank. Fifteen triplet groups were selected for the analysis of structural changes based on selection criteria. Structural features for selected enzymes were compared at the global as well as local region. Accessible surface area for the enzymes in entire triplet set was calculated, which describes the change in accessible surface area upon binding of cofactor and ligand with the enzyme. It was observed that some structural changes take place during binding of ligand in the presence of cofactor. This study will helps in understanding the level of flexibility in protein-ligand interaction for computer-aided drug designing.

Comparison of designed and randomly generated catalysts for simple chemical reactions.

PubMed

Kipnis, Yakov; Baker, David

2012-09-01

There has been recent success in designing enzymes for simple chemical reactions using a two-step protocol. In the first step, a geometric matching algorithm is used to identify naturally occurring protein scaffolds at which predefined idealized active sites can be realized. In the second step, the residues surrounding the transition state model are optimized to increase transition state binding affinity and to bolster the primary catalytic side chains. To improve the design methodology, we investigated how the set of solutions identified by the design calculations relate to the overall set of solutions for two different chemical reactions. Using a TIM barrel scaffold in which catalytically active Kemp eliminase and retroaldolase designs were obtained previously, we carried out activity screens of random libraries made to be compositionally similar to active designs. A small number of active catalysts were found in screens of 10³ variants for each of the two reactions, which differ from the computational designs in that they reuse charged residues already present in the native scaffold. The results suggest that computational design considerably increases the frequency of catalyst generation for active sites involving newly introduced catalytic residues, highlighting the importance of interaction cooperativity in enzyme active sites. Copyright © 2012 The Protein Society.

Computational design of a thermostable mutant of cocaine esterase via molecular dynamics simulations.

PubMed

Huang, Xiaoqin; Gao, Daquan; Zhan, Chang-Guo

2011-06-07

Cocaine esterase (CocE) has been known as the most efficient native enzyme for metabolizing naturally occurring cocaine. A major obstacle to the clinical application of CocE is the thermoinstability of native CocE with a half-life of only ∼11 min at physiological temperature (37 °C). It is highly desirable to develop a thermostable mutant of CocE for therapeutic treatment of cocaine overdose and addiction. To establish a structure-thermostability relationship, we carried out molecular dynamics (MD) simulations at 400 K on wild-type CocE and previously known thermostable mutants, demonstrating that the thermostability of the active form of the enzyme correlates with the fluctuation (characterized as the root-mean square deviation and root-mean square fluctuation of atomic positions) of the catalytic residues (Y44, S117, Y118, H287, and D259) in the simulated enzyme. In light of the structure-thermostability correlation, further computational modelling including MD simulations at 400 K predicted that the active site structure of the L169K mutant should be more thermostable. The prediction has been confirmed by wet experimental tests showing that the active form of the L169K mutant had a half-life of 570 min at 37 °C, which is significantly longer than those of the wild-type and previously known thermostable mutants. The encouraging outcome suggests that the high-temperature MD simulations and the structure-thermostability relationship may be considered as a valuable tool for the computational design of thermostable mutants of an enzyme.

Engineering improved thermostability of the GH11 xylanase from Neocallimastix patriciarum via computational library design.

PubMed

Bu, Yifan; Cui, Yinglu; Peng, Ying; Hu, Meirong; Tian, Yu'e; Tao, Yong; Wu, Bian

2018-04-01

Xylanases, which cleave the β-1,4-glycosidic bond between xylose residues to release xylooligosaccharides (XOS), are widely used as food additives, animal feeds, and pulp bleaching agents. However, the thermally unstable nature of xylanases would hamper their industrial application. In this study, we used in silico design in a glycoside hydrolase family (GH) 11 xylanase to stabilize the enzyme. A combination of the best mutations increased the apparent melting temperature by 14 °C and significantly enhanced thermostability and thermoactivation. The variant also showed an upward-shifted optimal temperature for catalysis without compromising its activity at low temperatures. Moreover, a 10-fold higher XOS production yield was obtained at 70 °C, which compensated the low yield obtained with the wild-type enzyme. Collectively, the variant constructed by the computational strategy can be used as an efficient biocatalyst for XOS production at industrially viable conditions.

Computational design of enzyme-ligand binding using a combined energy function and deterministic sequence optimization algorithm.

PubMed

Tian, Ye; Huang, Xiaoqiang; Zhu, Yushan

2015-08-01

Enzyme amino-acid sequences at ligand-binding interfaces are evolutionarily optimized for reactions, and the natural conformation of an enzyme-ligand complex must have a low free energy relative to alternative conformations in native-like or non-native sequences. Based on this assumption, a combined energy function was developed for enzyme design and then evaluated by recapitulating native enzyme sequences at ligand-binding interfaces for 10 enzyme-ligand complexes. In this energy function, the electrostatic interaction between polar or charged atoms at buried interfaces is described by an explicitly orientation-dependent hydrogen-bonding potential and a pairwise-decomposable generalized Born model based on the general side chain in the protein design framework. The energy function is augmented with a pairwise surface-area based hydrophobic contribution for nonpolar atom burial. Using this function, on average, 78% of the amino acids at ligand-binding sites were predicted correctly in the minimum-energy sequences, whereas 84% were predicted correctly in the most-similar sequences, which were selected from the top 20 sequences for each enzyme-ligand complex. Hydrogen bonds at the enzyme-ligand binding interfaces in the 10 complexes were usually recovered with the correct geometries. The binding energies calculated using the combined energy function helped to discriminate the active sequences from a pool of alternative sequences that were generated by repeatedly solving a series of mixed-integer linear programming problems for sequence selection with increasing integer cuts.

Elucidating sequence and solvent specific design targets to protect and stabilize enzymes for biocatalysis in ionic liquids.

PubMed

Sprenger, K G; Plaks, J G; Kaar, J L; Pfaendtner, J

2017-07-05

For many different frameworks, the structure, function, and dynamics of an enzyme is largely determined by the nature of its interactions with the surrounding host environment, thus a molecular level understanding of enzyme/host interactions is essential to the design of new processes and applications. Ionic liquid (IL) solvents are a popular class of solvents in which to study enzyme behavior, yet it is still not possible to predict how a given enzyme will behave in a given IL solvent. Furthermore, a dearth of experimental data with which to evaluate simulation force fields has prevented the full integration of experimental and computational techniques to gain a complete picture of enzyme/IL interactions. Utilizing recently published crystallographic data of an enzyme in complex with an IL, this study aims to validate the use of current molecular force fields for studying enzyme/IL interactions, and to provide new mechanistic insight into enzyme stabilization in IL solvents. Classical molecular dynamics (MD) simulations have been performed on both the folded and unfolded state of Bacillus subtilis lipase A and a quadruple-mutant version of lipase A, in solutions of aqueous 1-butyl-3-methylimidazolium chloride. Results show classical MD simulations can predict the preferred surface binding locations of IL cations as well as reductions in IL anion binding to mutated surface residues with high accuracy. The results also point to a mechanistic difference between IL binding to the folded and unfolded state of an enzyme, which we call the "counter-ion effect". These findings could have important implications for future rational design efforts to stabilize enzymes in non-conventional media.

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.

Elfin: An algorithm for the computational design of custom three-dimensional structures from modular repeat protein building blocks.

PubMed

Yeh, Chun-Ting; Brunette, T J; Baker, David; McIntosh-Smith, Simon; Parmeggiani, Fabio

2018-02-01

Computational protein design methods have enabled the design of novel protein structures, but they are often still limited to small proteins and symmetric systems. To expand the size of designable proteins while controlling the overall structure, we developed Elfin, a genetic algorithm for the design of novel proteins with custom shapes using structural building blocks derived from experimentally verified repeat proteins. By combining building blocks with compatible interfaces, it is possible to rapidly build non-symmetric large structures (>1000 amino acids) that match three-dimensional geometric descriptions provided by the user. A run time of about 20min on a laptop computer for a 3000 amino acid structure makes Elfin accessible to users with limited computational resources. Protein structures with controlled geometry will allow the systematic study of the effect of spatial arrangement of enzymes and signaling molecules, and provide new scaffolds for functional nanomaterials. Copyright © 2017 Elsevier Inc. All rights reserved.

Enzyme stabilization via computationally guided protein stapling.

PubMed

Moore, Eric J; Zorine, Dmitri; Hansen, William A; Khare, Sagar D; Fasan, Rudi

2017-11-21

Thermostabilization represents a critical and often obligatory step toward enhancing the robustness of enzymes for organic synthesis and other applications. While directed evolution methods have provided valuable tools for this purpose, these protocols are laborious and time-consuming and typically require the accumulation of several mutations, potentially at the expense of catalytic function. Here, we report a minimally invasive strategy for enzyme stabilization that relies on the installation of genetically encoded, nonreducible covalent staples in a target protein scaffold using computational design. This methodology enables the rapid development of myoglobin-based cyclopropanation biocatalysts featuring dramatically enhanced thermostability (Δ T m = +18.0 °C and Δ T 50 = +16.0 °C) as well as increased stability against chemical denaturation [Δ C m (GndHCl) = 0.53 M], without altering their catalytic efficiency and stereoselectivity properties. In addition, the stabilized variants offer superior performance and selectivity compared with the parent enzyme in the presence of a high concentration of organic cosolvents, enabling the more efficient cyclopropanation of a water-insoluble substrate. This work introduces and validates an approach for protein stabilization which should be applicable to a variety of other proteins and enzymes.

Computational design of a Diels-Alderase from a thermophilic esterase: the importance of dynamics

NASA Astrophysics Data System (ADS)

Linder, Mats; Johansson, Adam Johannes; Olsson, Tjelvar S. G.; Liebeschuetz, John; Brinck, Tore

2012-09-01

A novel computational Diels-Alderase design, based on a relatively rare form of carboxylesterase from Geobacillus stearothermophilus, is presented and theoretically evaluated. The structure was found by mining the PDB for a suitable oxyanion hole-containing structure, followed by a combinatorial approach to find suitable substrates and rational mutations. Four lead designs were selected and thoroughly modeled to obtain realistic estimates of substrate binding and prearrangement. Molecular dynamics simulations and DFT calculations were used to optimize and estimate binding affinity and activation energies. A large quantum chemical model was used to capture the salient interactions in the crucial transition state (TS). Our quantitative estimation of kinetic parameters was validated against four experimentally characterized Diels-Alderases with good results. The final designs in this work are predicted to have rate enhancements of ≈103-106 and high predicted proficiencies. This work emphasizes the importance of considering protein dynamics in the design approach, and provides a quantitative estimate of the how the TS stabilization observed in most de novo and redesigned enzymes is decreased compared to a minimal, `ideal' model. The presented design is highly interesting for further optimization and applications since it is based on a thermophilic enzyme ( T opt = 70 °C).

Computational Elucidation of Selectivities and Mechanisms Performed by Organometallic and Bioinorganic Catalysts

NASA Astrophysics Data System (ADS)

Grandner, Jessica Marie

Computational methods were used to determine the mechanisms and selectivities of organometallic-catalyzed reactions. The first half of the dissertation focuses on the study of metathesis catalysts in collaboration with the Grubbs group at CalTech. Chapter 1 describes the studies of the decomposition modes of several ruthenium-based metathesis catalysts. These studies were performed to better understand the decomposition of such catalysts in order to prevent decomposition (Chapter 1.2) or utilize decomposed catalysts for alternative reactions (Chapter 1.1). Chapter 2.1 describes the computational investigation of the origins of stereoretentive metathesis with ruthenium-based metathesis catalysts. These findings were then used to computationally design E-selective metathesis catalysts (Chapter 2.2). While the first half of the dissertation was centered around ruthenium catalysts, the second half of the dissertation pertains to iron-catalyzed reaction, in particular, iron-catalyzed reactions by P450 enzymes. The elements of Chapter 3 concentrate on the stereo- and chemo-selectivity of P450-catalyzed C-H hydroxylations. By combining multiple computational methods, the inherent activity of the iron-oxo catalyst and the influence of the active site on such reactions were illuminated. These discoveries allow for the engineering of new substrates and mutant enzymes for tailored C-H hydroxylation. While the mechanism of C-H hydroxylations catalyzed by P450 enzymes has been well studied, there are several P450-catalyzed transformations for which the mechanism is unknown. The components of Chapter 4 describe the use of computations to determine the mechanisms of complex, multi-step reactions catalyzed by P450s. The determination of these mechanisms elucidates how these enzymes react with various functional groups and substrate architectures and allows for a better understanding of how drug-like compounds may be broken down by human P450s.

The Use of Multiscale Molecular Simulations in Understanding a Relationship between the Structure and Function of Biological Systems of the Brain: The Application to Monoamine Oxidase Enzymes

PubMed Central

Vianello, Robert; Domene, Carmen; Mavri, Janez

2016-01-01

HIGHLIGHTS Computational techniques provide accurate descriptions of the structure and dynamics of biological systems, contributing to their understanding at an atomic level.Classical MD simulations are a precious computational tool for the processes where no chemical reactions take place.QM calculations provide valuable information about the enzyme activity, being able to distinguish among several mechanistic pathways, provided a carefully selected cluster model of the enzyme is considered.Multiscale QM/MM simulation is the method of choice for the computational treatment of enzyme reactions offering quantitative agreement with experimentally determined reaction parameters.Molecular simulation provide insight into the mechanism of both the catalytic activity and inhibition of monoamine oxidases, thus aiding in the rational design of their inhibitors that are all employed and antidepressants and antiparkinsonian drugs. Aging society and therewith associated neurodegenerative and neuropsychiatric diseases, including depression, Alzheimer's disease, obsessive disorders, and Parkinson's disease, urgently require novel drug candidates. Targets include monoamine oxidases A and B (MAOs), acetylcholinesterase (AChE), butyrylcholinesterase (BChE), and various receptors and transporters. For rational drug design it is particularly important to combine experimental synthetic, kinetic, toxicological, and pharmacological information with structural and computational work. This paper describes the application of various modern computational biochemistry methods in order to improve the understanding of a relationship between the structure and function of large biological systems including ion channels, transporters, receptors, and metabolic enzymes. The methods covered stem from classical molecular dynamics simulations to understand the physical basis and the time evolution of the structures, to combined QM, and QM/MM approaches to probe the chemical mechanisms of enzymatic activities and their inhibition. As an illustrative example, the later will focus on the monoamine oxidase family of enzymes, which catalyze the degradation of amine neurotransmitters in various parts of the brain, the imbalance of which is associated with the development and progression of a range of neurodegenerative disorders. Inhibitors that act mainly on MAO A are used in the treatment of depression, due to their ability to raise serotonin concentrations, while MAO B inhibitors decrease dopamine degradation and improve motor control in patients with Parkinson disease. Our results give strong support that both MAO isoforms, A and B, operate through the hydride transfer mechanism. Relevance of MAO catalyzed reactions and MAO inhibition in the context of neurodegeneration will be discussed. PMID:27471444

Activity loss by H46A mutation in Mycobacterium tuberculosis isocitrate lyase is due to decrease in structural plasticity and collective motions of the active site.

PubMed

Shukla, Rohit; Shukla, Harish; Tripathi, Timir

2018-01-01

Mycobacterium tuberculosis isocitrate lyase (MtbICL) is a crucial enzyme of the glyoxylate cycle and is a validated anti-tuberculosis drug target. Structurally distant, non-active site mutation (H46A) in MtbICL has been found to cause loss of enzyme activity. The aim of the present work was to explore the structural alterations induced by H46A mutation that caused the loss of enzyme activity. The structural and dynamic consequences of H46A mutation were studied using multiple computational methods such as docking, molecular dynamics simulation and residue interaction network analysis (RIN). Principal component analysis and cross correlation analysis revealed the difference in conformational flexibility and collective modes of motions between the wild-type and mutant enzyme, particularly in the active site region. RIN analysis revealed that the active site geometry was disturbed in the mutant enzyme. Thus, the dynamic perturbation of the active site led to enzyme transition from its active form to inactive form upon mutation. The computational analyses elucidated the mutant-specific conformational alterations, differential dominant motions, and anomalous residue level interactions that contributed to the abrogated function of mutant MtbICL. An understanding of interactions of mutant enzymes may help in modifying the existing drugs and designing improved drugs for successful control of tuberculosis. Copyright © 2017 Elsevier Ltd. All rights reserved.

CAZyme discovery and design for sweet dreams.

PubMed

André, Isabelle; Potocki-Véronèse, Gabrielle; Barbe, Sophie; Moulis, Claire; Remaud-Siméon, Magali

2014-04-01

Development of synthetic routes to complex carbohydrates and glyco-conjugates is often hampered by the lack of enzymes with requisite properties or specificities. Indeed, assembly or degradation of carbohydrates requires carbohydrate-active enzymes (CAZymes) able to act on a vast range of glycosidic monomers, oligomers or polymers in a regio-specific or stereo-specific manner in order to produce the desired structure. Sequence-based analyses allow finding the most original enzymes. Novel screening methods have emerged that enable a more efficient exploitation of the CAZyme diversity found in the microbial world or generated by protein engineering. Computational biology methods also play a prominent role in the success of CAZyme design. Such progress allows circumventing current limitations of carbohydrate synthesis and opens new opportunities related to the synthetic biology field. Copyright © 2014 Elsevier Ltd. All rights reserved.

Protein Conformational Populations and Functionally Relevant Sub-states

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

Agarwal, Pratul K; Burger, Virginia; Savol, Andrej

2013-01-01

Functioning proteins do not remain fixed in a unique structure, but instead they sample a range of conformations facilitated by motions within the protein. Even in the native state, a protein exists as a collection of interconverting conformations driven by thermodynamic fluctuations. Motions on the fast time scale allow a protein to sample conformations in the nearby area of its conformational landscape, while motions on slower time scales give it access to conformations in distal areas of the landscape. Emerging evidence indicates that protein landscapes contain conformational substates with dynamic and structural features that support the designated function of themore » protein. Nuclear magnetic resonance (NMR) experiments provide information about conformational ensembles of proteins. X-ray crystallography allows researchers to identify the most populated states along the landscape, and computational simulations give atom-level information about the conformational substates of different proteins. This ability to characterize and obtain quantitative information about the conformational substates and the populations of proteins within them is allowing researchers to better understand the relationship between protein structure and dynamics and the mechanisms of protein function. In this Account, we discuss recent developments and challenges in the characterization of functionally relevant conformational populations and substates of proteins. In some enzymes, the sampling of functionally relevant conformational substates is connected to promoting the overall mechanism of catalysis. For example, the conformational landscape of the enzyme dihydrofolate reductase has multiple substates, which facilitate the binding and the release of the cofactor and substrate and catalyze the hydride transfer. For the enzyme cyclophilin A, computational simulations reveal that the long time scale conformational fluctuations enable the enzyme to access conformational substates that allow it to attain the transition state, therefore promoting the reaction mechanism. In the long term, this emerging view of proteins with conformational substates has broad implications for improving our understanding of enzymes, enzyme engineering, and better drug design. Researchers have already used photoactivation to modulate protein conformations as a strategy to develop a hypercatalytic enzyme. In addition, the alteration of the conformational substates through binding of ligands at locations other than the active site provides the basis for the design of new medicines through allosteric modulation.« less

Quantum mechanical approaches to in silico enzyme characterization and drug design

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

Nilmeier, J P; Fattebert, J L; Jacobson, M P

2012-01-17

The astonishing, exponentially increasing rates of genome sequencing has led to one of the most significant challenges for the biological and computational sciences in the 21st century: assigning the likely functions of the encoded proteins. Enzymes represent a particular challenge, and a critical one, because the universe of enzymes is likely to contain many novel functions that may be useful for synthetic biology, or as drug targets. Current approaches to protein annotation are largely based on bioinformatics. At the simplest level, this annotation involves transferring the annotations of characterized enzymes to related sequences. In practice, however, there is no simple,more » sequence based criterion for transferring annotations, and bioinformatics alone cannot propose new enzymatic functions. Structure-based computational methods have the potential to address these limitations, by identifying potential substrates of enzymes, as we and others have shown. One successful approach has used in silico 'docking' methods, more commonly applied in structure-based drug design, to identify possible metabolite substrates. A major limitation of this approach is that it only considers substrate binding, and does not directly assess the potential of the enzyme to catalyze a particular reaction using a particular substrate. That is, substrate binding affinity is necessary but not sufficient to assign function. A reaction profile is ultimately what is needed for a more complete quantitative description of function. To address this rather fundamental limitation, they propose to use quantum mechanical methods to explicitly compute transition state barriers that govern the rates of catalysis. Although quantum mechanical, and mixed quantum/classical (QM/MM), methods have been used extensively to investigate enzymatic reactions, the focus has been primarily on elucidating complex reaction mechanisms. Here, the key catalytic steps are known, and they use these methods quantify substrate specificity. That is, we bring the power of quantum mechanics to bear on the problem of annotating enzyme function, which is a novel approach. Although it has been clear to us at the Jacobson group for some time that enzyme specificity may be encoded in transition states, rather than simply substrate recognition, the main limitation has always been computational expense. Using a hierarchy of different methods, they can reduce the list of plausible substrates of an enzyme to a small number in most cases, but even identifying the transition states for a dozen plausible substrates requires significant computational effort, beyond what is practical using standard QM/MM methods. For this project, they have chosen two enzyme superfamilies which they have used as 'model systems' for functional assignment. The enolase superfamily is a large group of {alpha}-{beta} barrel enzymes with highly diverse substrates and chemical transformations. Despite decades of work, over a third of the superfamily remains unassigned, which means that the remaining cases are by definition difficult to assign. They have focused on acid sugar dehydratases, and have considerable expertise on the matter. They are also interested in the isoprenoid synthase superfamily, which is of central interest to the synthetic biology community, because these enzymes are used by nature to create complex rare natural products of medicinal value. the most notable example of this is the artemisinin, an antimalarial compound that is found in trace amounts in the wormwod root. From the standpoint of enzyme function assignment, these enzymes are intriguing because they use a small number of chemically simple substrates to generate, potentially, tens of thousands of different products. Hence, substrate binding specificity is only a small part of the challenge; the key is determining how the enzyme directs the carbocation chemistry to specific products. These more complex modeling approaches clearly require quantum mechanical methods.« less

Evolution of cyclohexadienyl dehydratase from an ancestral solute-binding protein.

PubMed

Clifton, Ben E; Kaczmarski, Joe A; Carr, Paul D; Gerth, Monica L; Tokuriki, Nobuhiko; Jackson, Colin J

2018-04-23

The emergence of enzymes through the neofunctionalization of noncatalytic proteins is ultimately responsible for the extraordinary range of biological catalysts observed in nature. Although the evolution of some enzymes from binding proteins can be inferred by homology, we have a limited understanding of the nature of the biochemical and biophysical adaptations along these evolutionary trajectories and the sequence in which they occurred. Here we reconstructed and characterized evolutionary intermediate states linking an ancestral solute-binding protein to the extant enzyme cyclohexadienyl dehydratase. We show how the intrinsic reactivity of a desolvated general acid was harnessed by a series of mutations radiating from the active site, which optimized enzyme-substrate complementarity and transition-state stabilization and minimized sampling of noncatalytic conformations. Our work reveals the molecular evolutionary processes that underlie the emergence of enzymes de novo, which are notably mirrored by recent examples of computational enzyme design and directed evolution.

An accurate binding interaction model in de novo computational protein design of interactions: if you build it, they will bind.

PubMed

London, Nir; Ambroggio, Xavier

2014-02-01

Computational protein design efforts aim to create novel proteins and functions in an automated manner and, in the process, these efforts shed light on the factors shaping natural proteins. The focus of these efforts has progressed from the interior of proteins to their surface and the design of functions, such as binding or catalysis. Here we examine progress in the development of robust methods for the computational design of non-natural interactions between proteins and molecular targets such as other proteins or small molecules. This problem is referred to as the de novo computational design of interactions. Recent successful efforts in de novo enzyme design and the de novo design of protein-protein interactions open a path towards solving this problem. We examine the common themes in these efforts, and review recent studies aimed at understanding the nature of successes and failures in the de novo computational design of interactions. While several approaches culminated in success, the use of a well-defined structural model for a specific binding interaction in particular has emerged as a key strategy for a successful design, and is therefore reviewed with special consideration. Copyright © 2013 Elsevier Inc. All rights reserved.

A Flow Cytometric and Computational Approaches to Carbapenems Affinity to the Different Types of Carbapenemases

PubMed Central

Pina-Vaz, Cidália; Silva, Ana P.; Faria-Ramos, Isabel; Teixeira-Santos, Rita; Moura, Daniel; Vieira, Tatiana F.; Sousa, Sérgio F.; Costa-de-Oliveira, Sofia; Cantón, Rafael; Rodrigues, Acácio G.

2016-01-01

The synergy of carbapenem combinations regarding Enterobacteriaceae producing different types of carbapenemases was study through different approaches: flow cytometry and computational analysis. Ten well characterized Enterobacteriaceae (KPC, verona integron-encoded metallo-β-lactamases –VIM and OXA-48-like enzymes) were selected for the study. The cells were incubated with a combination of ertapenem with imipenem, meropenem, or doripenem and killing kinetic curves performed with and without reinforcements of the drugs. A cephalosporin was also used in combination with ertapenem. A flow cytometric assay with DiBAC4-(3), a membrane potential dye, was developed in order to evaluate the cellular lesion after 2 h incubation. A chemical computational study was performed to understand the affinity of the different drugs to the different types of enzymes. Flow cytometric analysis and time-kill assays showed a synergic effect against KPC and OXA-48 producing-bacteria with all combinations; only ertapenem with imipenem was synergic against VIM producing-bacteria. A bactericidal effect was observed in OXA-48-like enzymes. Ceftazidime plus ertapenem was synergic against ESBL-negative KPC producing-bacteria. Ertapenem had the highest affinity for those enzymes according to chemical computational study. The synergic effect between ertapenem and others carbapenems against different carbapenemase-producing bacteria, representing a therapeutic choice, was described for the first time. Easier and faster laboratorial methods for carbapenemase characterization are urgently needed. The design of an ertapenem derivative with similar affinity to carbapenemases but exhibiting more stable bonds was demonstrated as highly desirable. PMID:27555844

Computational methods in metabolic engineering for strain design.

PubMed

Long, Matthew R; Ong, Wai Kit; Reed, Jennifer L

2015-08-01

Metabolic engineering uses genetic approaches to control microbial metabolism to produce desired compounds. Computational tools can identify new biological routes to chemicals and the changes needed in host metabolism to improve chemical production. Recent computational efforts have focused on exploring what compounds can be made biologically using native, heterologous, and/or enzymes with broad specificity. Additionally, computational methods have been developed to suggest different types of genetic modifications (e.g. gene deletion/addition or up/down regulation), as well as suggest strategies meeting different criteria (e.g. high yield, high productivity, or substrate co-utilization). Strategies to improve the runtime performances have also been developed, which allow for more complex metabolic engineering strategies to be identified. Future incorporation of kinetic considerations will further improve strain design algorithms. Copyright © 2015 Elsevier Ltd. All rights reserved.

A novel allosteric mechanism in the cysteine peptidase cathepsin K discovered by computational methods

NASA Astrophysics Data System (ADS)

Novinec, Marko; Korenč, Matevž; Caflisch, Amedeo; Ranganathan, Rama; Lenarčič, Brigita; Baici, Antonio

2014-02-01

Allosteric modifiers have the potential to fine-tune enzyme activity. Therefore, targeting allosteric sites is gaining increasing recognition as a strategy in drug design. Here we report the use of computational methods for the discovery of the first small-molecule allosteric inhibitor of the collagenolytic cysteine peptidase cathepsin K, a major target for the treatment of osteoporosis. The molecule NSC13345 is identified by high-throughput docking of compound libraries to surface sites on the peptidase that are connected to the active site by an evolutionarily conserved network of residues (protein sector). The crystal structure of the complex shows that NSC13345 binds to a novel allosteric site on cathepsin K. The compound acts as a hyperbolic mixed modifier in the presence of a synthetic substrate, it completely inhibits collagen degradation and has good selectivity for cathepsin K over related enzymes. Altogether, these properties qualify our methodology and NSC13345 as promising candidates for allosteric drug design.

Novel N-substituted aminobenzamide scaffold derivatives targeting the dipeptidyl peptidase-IV enzyme.

PubMed

Al-Balas, Qosay A; Sowaileh, Munia F; Hassan, Mohammad A; Qandil, Amjad M; Alzoubi, Karem H; Mhaidat, Nizar M; Almaaytah, Ammar M; Khabour, Omar F

2014-01-01

The dipeptidyl peptidase-IV (DPP-IV) enzyme is considered a pivotal target for controlling normal blood sugar levels in the body. Incretins secreted in response to ingestion of meals enhance insulin release to the blood, and DPP-IV inactivates these incretins within a short period and stops their action. Inhibition of this enzyme escalates the action of incretins and induces more insulin to achieve better glucose control in diabetic patients. Thus, inhibition of this enzyme will lead to better control of blood sugar levels. In this study, computer-aided drug design was used to help establish a novel N-substituted aminobenzamide scaffold as a potential inhibitor of DPP-IV. CDOCKER software available from Discovery Studio 3.5 was used to evaluate a series of designed compounds and assess their mode of binding to the active site of the DPP-IV enzyme. The designed compounds were synthesized and tested against a DPP-IV enzyme kit provided by Enzo Life Sciences. The synthesized compounds were characterized using proton and carbon nuclear magnetic resonance, mass spectrometry, infrared spectroscopy, and determination of melting point. Sixty-nine novel compounds having an N-aminobenzamide scaffold were prepared, with full characterization. Ten of these compounds showed more in vitro activity against DPP-IV than the reference compounds, with the most active compounds scoring 38% activity at 100 μM concentration. The N-aminobenzamide scaffold was shown in this study to be a valid scaffold for inhibiting the DPP-IV enzyme. Continuing work could unravel more active compounds possessing the same scaffold.

Biomolecular computers with multiple restriction enzymes.

PubMed

Sakowski, Sebastian; Krasinski, Tadeusz; Waldmajer, Jacek; Sarnik, Joanna; Blasiak, Janusz; Poplawski, Tomasz

2017-01-01

The development of conventional, silicon-based computers has several limitations, including some related to the Heisenberg uncertainty principle and the von Neumann "bottleneck". Biomolecular computers based on DNA and proteins are largely free of these disadvantages and, along with quantum computers, are reasonable alternatives to their conventional counterparts in some applications. The idea of a DNA computer proposed by Ehud Shapiro's group at the Weizmann Institute of Science was developed using one restriction enzyme as hardware and DNA fragments (the transition molecules) as software and input/output signals. This computer represented a two-state two-symbol finite automaton that was subsequently extended by using two restriction enzymes. In this paper, we propose the idea of a multistate biomolecular computer with multiple commercially available restriction enzymes as hardware. Additionally, an algorithmic method for the construction of transition molecules in the DNA computer based on the use of multiple restriction enzymes is presented. We use this method to construct multistate, biomolecular, nondeterministic finite automata with four commercially available restriction enzymes as hardware. We also describe an experimental applicaton of this theoretical model to a biomolecular finite automaton made of four endonucleases.

Four new type I restriction enzymes identified in Escherichia coli clinical isolates

PubMed Central

Kasarjian, Julie K. A.; Kodama, Yoshiaki; Iida, Masatake; Matsuda, Katsura; Ryu, Junichi

2005-01-01

Using a plasmid transformation method and the RM search computer program, four type I restriction enzymes with new recognition sites and two isoschizomers (EcoBI and Eco377I) were identified in a collection of clinical Escherichia coli isolates. These new enzymes were designated Eco394I, Eco826I, Eco851I and Eco912I. Their recognition sequences were determined to be GAC(5N)RTAAY, GCA(6N)CTGA, GTCA(6N)TGAY and CAC(5N)TGGC, respectively. A methylation sensitivity assay, using various synthetic oligonucleotides, was used to identify the adenines that prevent cleavage when methylated (underlined). These results suggest that type I enzymes are abundant in E.coli and many other bacteria, as has been inferred from bacterial genome sequencing projects. PMID:16040596

Identification of a new binding site in E. coli FabH using Molecular dynamics simulations: validation by computational alanine mutagenesis and docking studies.

PubMed

Ramamoorthy, Divya; Turos, Edward; Guida, Wayne C

2013-05-24

FabH (Fatty acid biosynthesis, enzyme H, also referred to as β-ketoacyl-ACP-synthase III) is a key condensing enzyme in the type II fatty acid synthesis (FAS) system. The FAS pathway in bacteria is essential for growth and survival and vastly differs from the human FAS pathway. Enzymes involved in this pathway have arisen as promising biomolecular targets for discovery of new antibacterial drugs. However, currently there are no clinical drugs that selectively target FabH, and known inhibitors of FabH all act within the active site. FabH exerts its catalytic function as a dimer, which could potentially be exploited in developing new strategies for inhibitor design. The aim of this study was to elucidate structural details of the dimer interface region by means of computational modeling, including molecular dynamics (MD) simulations, in order to derive information for the structure-based design of new FabH inhibitors. The dimer interface region was analyzed by MD simulations, trajectory snapshots were collected for further analyses, and docking studies were performed with potential small molecule disruptors. Alanine mutation and docking studies strongly suggest that the dimer interface could be a potential target for anti-infection drug discovery.

Evolutionarily conserved linkage between enzyme fold, flexibility, and catalysis.

PubMed

Ramanathan, Arvind; Agarwal, Pratul K

2011-11-01

Proteins are intrinsically flexible molecules. The role of internal motions in a protein's designated function is widely debated. The role of protein structure in enzyme catalysis is well established, and conservation of structural features provides vital clues to their role in function. Recently, it has been proposed that the protein function may involve multiple conformations: the observed deviations are not random thermodynamic fluctuations; rather, flexibility may be closely linked to protein function, including enzyme catalysis. We hypothesize that the argument of conservation of important structural features can also be extended to identification of protein flexibility in interconnection with enzyme function. Three classes of enzymes (prolyl-peptidyl isomerase, oxidoreductase, and nuclease) that catalyze diverse chemical reactions have been examined using detailed computational modeling. For each class, the identification and characterization of the internal protein motions coupled to the chemical step in enzyme mechanisms in multiple species show identical enzyme conformational fluctuations. In addition to the active-site residues, motions of protein surface loop regions (>10 Å away) are observed to be identical across species, and networks of conserved interactions/residues connect these highly flexible surface regions to the active-site residues that make direct contact with substrates. More interestingly, examination of reaction-coupled motions in non-homologous enzyme systems (with no structural or sequence similarity) that catalyze the same biochemical reaction shows motions that induce remarkably similar changes in the enzyme-substrate interactions during catalysis. The results indicate that the reaction-coupled flexibility is a conserved aspect of the enzyme molecular architecture. Protein motions in distal areas of homologous and non-homologous enzyme systems mediate similar changes in the active-site enzyme-substrate interactions, thereby impacting the mechanism of catalyzed chemistry. These results have implications for understanding the mechanism of allostery, and for protein engineering and drug design.

Computational design and experimental study of tighter binding peptides to an inactivated mutant of HIV-1 protease

PubMed Central

Altman, Michael D.; Nalivaika, Ellen A.; Prabu-Jeyabalan, Moses; Schiffer, Celia A.; Tidor, Bruce

2009-01-01

Drug resistance in HIV-1 protease, a barrier to effective treatment, is generally caused by mutations in the enzyme that disrupt inhibitor binding but still allow for substrate processing. Structural studies with mutant, inactive enzyme, have provided detailed information regarding how the substrates bind to the protease yet avoid resistance mutations; insights obtained inform the development of next generation therapeutics. Although structures have been obtained of complexes between substrate peptide and inactivated (D25N) protease, thermodynamic studies of peptide binding have been challenging due to low affinity. Peptides that bind tighter to the inactivated protease than the natural substrates would be valuable for thermodynamic studies as well as to explore whether the structural envelope observed for substrate peptides is a function of weak binding. Here, two computational methods — namely, charge optimization and protein design — were applied to identify peptide sequences predicted to have higher binding affinity to the inactivated protease, starting from an RT–RH derived substrate peptide. Of the candidate designed peptides, three were tested for binding with isothermal titration calorimetry, with one, containing a single threonine to valine substitution, measured to have more than a ten-fold improvement over the tightest binding natural substrate. Crystal structures were also obtained for the same three designed peptide complexes; they show good agreement with computational prediction. Thermodynamic studies show that binding is entropically driven, more so for designed affinity enhanced variants than for the starting substrate. Structural studies show strong similarities between natural and tighter-binding designed peptide complexes, which may have implications in understanding the molecular mechanisms of drug resistance in HIV-1 protease. PMID:17729291

Computational multiscale modeling in protein--ligand docking.

PubMed

Taufer, Michela; Armen, Roger; Chen, Jianhan; Teller, Patricia; Brooks, Charles

2009-01-01

In biological systems, the binding of small molecule ligands to proteins is a crucial process for almost every aspect of biochemistry and molecular biology. Enzymes are proteins that function by catalyzing specific biochemical reactions that convert reactants into products. Complex organisms are typically composed of cells in which thousands of enzymes participate in complex and interconnected biochemical pathways. Some enzymes serve as sequential steps in specific pathways (such as energy metabolism), while others function to regulate entire pathways and cellular functions [1]. Small molecule ligands can be designed to bind to a specific enzyme and inhibit the biochemical reaction. Inhibiting the activity of key enzymes may result in the entire biochemical pathways being turned on or off [2], [3]. Many small molecule drugs marketed today function in this generic way as enzyme inhibitors. If research identifies a specific enzyme as being crucial to the progress of disease, then this enzyme may be targeted with an inhibitor, which may slow down or reverse the progress of disease. In this way, enzymes are targeted from specific pathogens (e.g., virus, bacteria, fungi) for infectious diseases [4], [5], and human enzymes are targeted for noninfectious diseases such as cardiovascular disease, cancer, diabetes, and neurodegenerative diseases [6].

Catalysis by a de novo zinc-mediated protein interface: implications for natural enzyme evolution and rational enzyme engineering.

PubMed

Der, Bryan S; Edwards, David R; Kuhlman, Brian

2012-05-08

Here we show that a recent computationally designed zinc-mediated protein interface is serendipitously capable of catalyzing carboxyester and phosphoester hydrolysis. Although the original motivation was to design a de novo zinc-mediated protein-protein interaction (called MID1-zinc), we observed in the homodimer crystal structure a small cleft and open zinc coordination site. We investigated if the cleft and zinc site at the designed interface were sufficient for formation of a primitive active site that can perform hydrolysis. MID1-zinc hydrolyzes 4-nitrophenyl acetate with a rate acceleration of 10(5) and a k(cat)/K(M) of 630 M(-1) s(-1) and 4-nitrophenyl phosphate with a rate acceleration of 10(4) and a k(cat)/K(M) of 14 M(-1) s(-1). These rate accelerations by an unoptimized active site highlight the catalytic power of zinc and suggest that the clefts formed by protein-protein interactions are well-suited for creating enzyme active sites. This discovery has implications for protein evolution and engineering: from an evolutionary perspective, three-coordinated zinc at a homodimer interface cleft represents a simple evolutionary path to nascent enzymatic activity; from a protein engineering perspective, future efforts in de novo design of enzyme active sites may benefit from exploring clefts at protein interfaces for active site placement.

Biomolecular computers with multiple restriction enzymes

PubMed Central

Sakowski, Sebastian; Krasinski, Tadeusz; Waldmajer, Jacek; Sarnik, Joanna; Blasiak, Janusz; Poplawski, Tomasz

2017-01-01

Abstract The development of conventional, silicon-based computers has several limitations, including some related to the Heisenberg uncertainty principle and the von Neumann “bottleneck”. Biomolecular computers based on DNA and proteins are largely free of these disadvantages and, along with quantum computers, are reasonable alternatives to their conventional counterparts in some applications. The idea of a DNA computer proposed by Ehud Shapiro’s group at the Weizmann Institute of Science was developed using one restriction enzyme as hardware and DNA fragments (the transition molecules) as software and input/output signals. This computer represented a two-state two-symbol finite automaton that was subsequently extended by using two restriction enzymes. In this paper, we propose the idea of a multistate biomolecular computer with multiple commercially available restriction enzymes as hardware. Additionally, an algorithmic method for the construction of transition molecules in the DNA computer based on the use of multiple restriction enzymes is presented. We use this method to construct multistate, biomolecular, nondeterministic finite automata with four commercially available restriction enzymes as hardware. We also describe an experimental applicaton of this theoretical model to a biomolecular finite automaton made of four endonucleases. PMID:29064510

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

Ramanathan, Arvind; Agarwal, Pratul K

Proteins are intrinsically flexible molecules. The role of internal motions in a protein's designated function is widely debated. The role of protein structure in enzyme catalysis is well established, and conservation of structural features provides vital clues to their role in function. Recently, it has been proposed that the protein function may involve multiple conformations: the observed deviations are not random thermodynamic fluctuations; rather, flexibility may be closely linked to protein function, including enzyme catalysis. We hypothesize that the argument of conservation of important structural features can also be extended to identification of protein flexibility in interconnection with enzyme function.more » Three classes of enzymes (prolyl-peptidyl isomerase, oxidoreductase, and nuclease) that catalyze diverse chemical reactions have been examined using detailed computational modeling. For each class, the identification and characterization of the internal protein motions coupled to the chemical step in enzyme mechanisms in multiple species show identical enzyme conformational fluctuations. In addition to the active-site residues, motions of protein surface loop regions (>10 away) are observed to be identical across species, and networks of conserved interactions/residues connect these highly flexible surface regions to the active-site residues that make direct contact with substrates. More interestingly, examination of reaction-coupled motions in non-homologous enzyme systems (with no structural or sequence similarity) that catalyze the same biochemical reaction shows motions that induce remarkably similar changes in the enzyme substrate interactions during catalysis. The results indicate that the reaction-coupled flexibility is a conserved aspect of the enzyme molecular architecture. Protein motions in distal areas of homologous and non-homologous enzyme systems mediate similar changes in the active-site enzyme substrate interactions, thereby impacting the mechanism of catalyzed chemistry. These results have implications for understanding the mechanism of allostery, and for protein engineering and drug design.« less

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

A spatially localized architecture for fast and modular DNA computing

NASA Astrophysics Data System (ADS)

Chatterjee, Gourab; Dalchau, Neil; Muscat, Richard A.; Phillips, Andrew; Seelig, Georg

2017-09-01

Cells use spatial constraints to control and accelerate the flow of information in enzyme cascades and signalling networks. Synthetic silicon-based circuitry similarly relies on spatial constraints to process information. Here, we show that spatial organization can be a similarly powerful design principle for overcoming limitations of speed and modularity in engineered molecular circuits. We create logic gates and signal transmission lines by spatially arranging reactive DNA hairpins on a DNA origami. Signal propagation is demonstrated across transmission lines of different lengths and orientations and logic gates are modularly combined into circuits that establish the universality of our approach. Because reactions preferentially occur between neighbours, identical DNA hairpins can be reused across circuits. Co-localization of circuit elements decreases computation time from hours to minutes compared to circuits with diffusible components. Detailed computational models enable predictive circuit design. We anticipate our approach will motivate using spatial constraints for future molecular control circuit designs.

Enzyme-based logic gates and circuits-analytical applications and interfacing with electronics.

PubMed

Katz, Evgeny; Poghossian, Arshak; Schöning, Michael J

2017-01-01

The paper is an overview of enzyme-based logic gates and their short circuits, with specific examples of Boolean AND and OR gates, and concatenated logic gates composed of multi-step enzyme-biocatalyzed reactions. Noise formation in the biocatalytic reactions and its decrease by adding a "filter" system, converting convex to sigmoid response function, are discussed. Despite the fact that the enzyme-based logic gates are primarily considered as components of future biomolecular computing systems, their biosensing applications are promising for immediate practical use. Analytical use of the enzyme logic systems in biomedical and forensic applications is discussed and exemplified with the logic analysis of biomarkers of various injuries, e.g., liver injury, and with analysis of biomarkers characteristic of different ethnicity found in blood samples on a crime scene. Interfacing of enzyme logic systems with modified electrodes and semiconductor devices is discussed, giving particular attention to the interfaces functionalized with signal-responsive materials. Future perspectives in the design of the biomolecular logic systems and their applications are discussed in the conclusion. Graphical Abstract Various applications and signal-transduction methods are reviewed for enzyme-based logic systems.

Expanding the Catalytic Triad in Epoxide Hydrolases and Related Enzymes.

PubMed

Amrein, Beat A; Bauer, Paul; Duarte, Fernanda; Janfalk Carlsson, Åsa; Naworyta, Agata; Mowbray, Sherry L; Widersten, Mikael; Kamerlin, Shina C L

2015-10-02

Potato epoxide hydrolase 1 exhibits rich enantio- and regioselectivity in the hydrolysis of a broad range of substrates. The enzyme can be engineered to increase the yield of optically pure products as a result of changes in both enantio- and regioselectivity. It is thus highly attractive in biocatalysis, particularly for the generation of enantiopure fine chemicals and pharmaceuticals. The present work aims to establish the principles underlying the activity and selectivity of the enzyme through a combined computational, structural, and kinetic study using the substrate trans -stilbene oxide as a model system. Extensive empirical valence bond simulations have been performed on the wild-type enzyme together with several experimentally characterized mutants. We are able to computationally reproduce the differences between the activities of different stereoisomers of the substrate and the effects of mutations of several active-site residues. In addition, our results indicate the involvement of a previously neglected residue, H104, which is electrostatically linked to the general base H300. We find that this residue, which is highly conserved in epoxide hydrolases and related hydrolytic enzymes, needs to be in its protonated form in order to provide charge balance in an otherwise negatively charged active site. Our data show that unless the active-site charge balance is correctly treated in simulations, it is not possible to generate a physically meaningful model for the enzyme that can accurately reproduce activity and selectivity trends. We also expand our understanding of other catalytic residues, demonstrating in particular the role of a noncanonical residue, E35, as a "backup base" in the absence of H300. Our results provide a detailed view of the main factors driving catalysis and regioselectivity in this enzyme and identify targets for subsequent enzyme design efforts.

Evolutionarily Conserved Linkage between Enzyme Fold, Flexibility, and Catalysis

PubMed Central

Ramanathan, Arvind; Agarwal, Pratul K.

2011-01-01

Proteins are intrinsically flexible molecules. The role of internal motions in a protein's designated function is widely debated. The role of protein structure in enzyme catalysis is well established, and conservation of structural features provides vital clues to their role in function. Recently, it has been proposed that the protein function may involve multiple conformations: the observed deviations are not random thermodynamic fluctuations; rather, flexibility may be closely linked to protein function, including enzyme catalysis. We hypothesize that the argument of conservation of important structural features can also be extended to identification of protein flexibility in interconnection with enzyme function. Three classes of enzymes (prolyl-peptidyl isomerase, oxidoreductase, and nuclease) that catalyze diverse chemical reactions have been examined using detailed computational modeling. For each class, the identification and characterization of the internal protein motions coupled to the chemical step in enzyme mechanisms in multiple species show identical enzyme conformational fluctuations. In addition to the active-site residues, motions of protein surface loop regions (>10 Å away) are observed to be identical across species, and networks of conserved interactions/residues connect these highly flexible surface regions to the active-site residues that make direct contact with substrates. More interestingly, examination of reaction-coupled motions in non-homologous enzyme systems (with no structural or sequence similarity) that catalyze the same biochemical reaction shows motions that induce remarkably similar changes in the enzyme–substrate interactions during catalysis. The results indicate that the reaction-coupled flexibility is a conserved aspect of the enzyme molecular architecture. Protein motions in distal areas of homologous and non-homologous enzyme systems mediate similar changes in the active-site enzyme–substrate interactions, thereby impacting the mechanism of catalyzed chemistry. These results have implications for understanding the mechanism of allostery, and for protein engineering and drug design. PMID:22087074

A cyber-linked undergraduate research experience in computational biomolecular structure prediction and design

PubMed Central

Alford, Rebecca F.; Dolan, Erin L.

2017-01-01

Computational biology is an interdisciplinary field, and many computational biology research projects involve distributed teams of scientists. To accomplish their work, these teams must overcome both disciplinary and geographic barriers. Introducing new training paradigms is one way to facilitate research progress in computational biology. Here, we describe a new undergraduate program in biomolecular structure prediction and design in which students conduct research at labs located at geographically-distributed institutions while remaining connected through an online community. This 10-week summer program begins with one week of training on computational biology methods development, transitions to eight weeks of research, and culminates in one week at the Rosetta annual conference. To date, two cohorts of students have participated, tackling research topics including vaccine design, enzyme design, protein-based materials, glycoprotein modeling, crowd-sourced science, RNA processing, hydrogen bond networks, and amyloid formation. Students in the program report outcomes comparable to students who participate in similar in-person programs. These outcomes include the development of a sense of community and increases in their scientific self-efficacy, scientific identity, and science values, all predictors of continuing in a science research career. Furthermore, the program attracted students from diverse backgrounds, which demonstrates the potential of this approach to broaden the participation of young scientists from backgrounds traditionally underrepresented in computational biology. PMID:29216185

A cyber-linked undergraduate research experience in computational biomolecular structure prediction and design.

PubMed

Alford, Rebecca F; Leaver-Fay, Andrew; Gonzales, Lynda; Dolan, Erin L; Gray, Jeffrey J

2017-12-01

Computational biology is an interdisciplinary field, and many computational biology research projects involve distributed teams of scientists. To accomplish their work, these teams must overcome both disciplinary and geographic barriers. Introducing new training paradigms is one way to facilitate research progress in computational biology. Here, we describe a new undergraduate program in biomolecular structure prediction and design in which students conduct research at labs located at geographically-distributed institutions while remaining connected through an online community. This 10-week summer program begins with one week of training on computational biology methods development, transitions to eight weeks of research, and culminates in one week at the Rosetta annual conference. To date, two cohorts of students have participated, tackling research topics including vaccine design, enzyme design, protein-based materials, glycoprotein modeling, crowd-sourced science, RNA processing, hydrogen bond networks, and amyloid formation. Students in the program report outcomes comparable to students who participate in similar in-person programs. These outcomes include the development of a sense of community and increases in their scientific self-efficacy, scientific identity, and science values, all predictors of continuing in a science research career. Furthermore, the program attracted students from diverse backgrounds, which demonstrates the potential of this approach to broaden the participation of young scientists from backgrounds traditionally underrepresented in computational biology.

Emergence of a catalytic tetrad during evolution of a highly active artificial aldolase.

PubMed

Obexer, Richard; Godina, Alexei; Garrabou, Xavier; Mittl, Peer R E; Baker, David; Griffiths, Andrew D; Hilvert, Donald

2017-01-01

Designing catalysts that achieve the rates and selectivities of natural enzymes is a long-standing goal in protein chemistry. Here, we show that an ultrahigh-throughput droplet-based microfluidic screening platform can be used to improve a previously optimized artificial aldolase by an additional factor of 30 to give a >10 9 rate enhancement that rivals the efficiency of class I aldolases. The resulting enzyme catalyses a reversible aldol reaction with high stereoselectivity and tolerates a broad range of substrates. Biochemical and structural studies show that catalysis depends on a Lys-Tyr-Asn-Tyr tetrad that emerged adjacent to a computationally designed hydrophobic pocket during directed evolution. This constellation of residues is poised to activate the substrate by Schiff base formation, promote mechanistically important proton transfers and stabilize multiple transition states along a complex reaction coordinate. The emergence of such a sophisticated catalytic centre shows that there is nothing magical about the catalytic activities or mechanisms of naturally occurring enzymes, or the evolutionary process that gave rise to them.

Enzyme-regulated the changes of pH values for assembling a colorimetric and multistage interconnection logic network with multiple readouts.

PubMed

Huang, Yanyan; Ran, Xiang; Lin, Youhui; Ren, Jinsong; Qu, Xiaogang

2015-04-22

Based on enzymatic reactions-triggered changes of pH values and biocomputing, a novel and multistage interconnection biological network with multiple easy-detectable signal outputs has been developed. Compared with traditional chemical computing, the enzyme-based biological system could overcome the interference between reactions or the incompatibility of individual computing gates and offer a unique opportunity to assemble multicomponent/multifunctional logic circuitries. Our system included four enzyme inputs: β-galactosidase (β-gal), glucose oxidase (GOx), esterase (Est) and urease (Ur). With the assistance of two signal transducers (gold nanoparticles and acid-base indicators) or pH meter, the outputs of the biological network could be conveniently read by the naked eyes. In contrast to current methods, the approach present here could realize cost-effective, label-free and colorimetric logic operations without complicated instrument. By designing a series of Boolean logic operations, we could logically make judgment of the compositions of the samples on the basis of visual output signals. Our work offered a promising paradigm for future biological computing technology and might be highly useful in future intelligent diagnostics, prodrug activation, smart drug delivery, process control, and electronic applications. Copyright © 2015 Elsevier B.V. All rights reserved.

Can enzyme engineering benefit from the modulation of protein motions? Lessons learned from NMR relaxation dispersion experiments.

PubMed

Doucet, Nicolas

2011-04-01

Despite impressive progress in protein engineering and design, our ability to create new and efficient enzyme activities remains a laborious and time-consuming endeavor. In the past few years, intricate combinations of rational mutagenesis, directed evolution and computational methods have paved the way to exciting engineering examples and are now offering a new perspective on the structural requirements of enzyme activity. However, these structure-function analyses are usually guided by the time-averaged static models offered by enzyme crystal structures, which often fail to describe the functionally relevant 'invisible states' adopted by proteins in space and time. To alleviate such limitations, NMR relaxation dispersion experiments coupled to mutagenesis studies have recently been applied to the study of enzyme catalysis, effectively complementing 'structure-function' analyses with 'flexibility-function' investigations. In addition to offering quantitative, site-specific information to help characterize residue motion, these NMR methods are now being applied to enzyme engineering purposes, providing a powerful tool to help characterize the effects of controlling long-range networks of flexible residues affecting enzyme function. Recent advancements in this emerging field are presented here, with particular attention to mutagenesis reports highlighting the relevance of NMR relaxation dispersion tools in enzyme engineering.

Computational Biochemistry-Enzyme Mechanisms Explored.

PubMed

Culka, Martin; Gisdon, Florian J; Ullmann, G Matthias

2017-01-01

Understanding enzyme mechanisms is a major task to achieve in order to comprehend how living cells work. Recent advances in biomolecular research provide huge amount of data on enzyme kinetics and structure. The analysis of diverse experimental results and their combination into an overall picture is, however, often challenging. Microscopic details of the enzymatic processes are often anticipated based on several hints from macroscopic experimental data. Computational biochemistry aims at creation of a computational model of an enzyme in order to explain microscopic details of the catalytic process and reproduce or predict macroscopic experimental findings. Results of such computations are in part complementary to experimental data and provide an explanation of a biochemical process at the microscopic level. In order to evaluate the mechanism of an enzyme, a structural model is constructed which can be analyzed by several theoretical approaches. Several simulation methods can and should be combined to get a reliable picture of the process of interest. Furthermore, abstract models of biological systems can be constructed combining computational and experimental data. In this review, we discuss structural computational models of enzymatic systems. We first discuss various models to simulate enzyme catalysis. Furthermore, we review various approaches how to characterize the enzyme mechanism both qualitatively and quantitatively using different modeling approaches. © 2017 Elsevier Inc. All rights reserved.

Valence bond and enzyme catalysis: a time to break down and a time to build up.

PubMed

Sharir-Ivry, Avital; Varatharaj, Rajapandian; Shurki, Avital

2015-05-04

Understanding enzyme catalysis and developing ability to control of it are two great challenges in biochemistry. A few successful examples of computational-based enzyme design have proved the fantastic potential of computational approaches in this field, however, relatively modest rate enhancements have been reported and the further development of complementary methods is still required. Herein we propose a conceptually simple scheme to identify the specific role that each residue plays in catalysis. The scheme is based on a breakdown of the total catalytic effect into contributions of individual protein residues, which are further decomposed into chemically interpretable components by using valence bond theory. The scheme is shown to shed light on the origin of catalysis in wild-type haloalkane dehalogenase (wt-DhlA) and its mutants. Furthermore, the understanding gained through our scheme is shown to have great potential in facilitating the selection of non-optimal sites for catalysis and suggesting effective mutations to enhance the enzymatic rate. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

ENZVU--An Enzyme Kinetics Computer Simulation Based upon a Conceptual Model of Enzyme Action.

ERIC Educational Resources Information Center

Graham, Ian

1985-01-01

Discusses a simulation on enzyme kinetics based upon the ability of computers to generate random numbers. The program includes: (1) enzyme catalysis in a restricted two-dimensional grid; (2) visual representation of catalysis; and (3) storage and manipulation of data. Suggested applications and conclusions are also discussed. (DH)

Computational protein design and protein-ligand interaction studies for the improvement of organophosphorus degrading potential of Deinococcus radiodurans.

PubMed

Manoharan, Prabu; Sridhar, J

2018-05-01

The organophosphorus hydrolase enzyme is involved in the catalyzing reaction that involve hydrolysis of organophosphate toxic compounds. An enzyme from Deinococcus radiodurans reported as homologous to phosphotriesterase and show activity against organophosphate. In the past activity of this enzyme is low and efforts made to improve the activity by experimental mutation study. However only very few organophosphates tested against very few catalytic site mutations. In order to improve the catalytic power of the organophosphorus hydrolase enzyme, we carried out systematic functional hotspot based protein engineering strategy. The mutants tested against 46 know organophosphate compounds using molecular docking study. Finally, we carried out an extensive molecular docking study to predict the binding of 46 organophosphate compounds to wild-type protein and mutant organophosphorus hydrolase enzyme. At the end we are able to improve the degrading potential of organophosphorus hydrolase enzyme against organophosphate toxic compounds. This preliminary study and the outcome would be useful guide for the experimental scientist involved in the bioremediation of toxic organophosphate compounds. Copyright © 2018 Elsevier Inc. All rights reserved.

Directed evolution: tailoring biocatalysts for industrial applications.

PubMed

Kumar, Ashwani; Singh, Suren

2013-12-01

Current challenges and promises of white biotechnology encourage protein engineers to use a directed evolution approach to generate novel and useful biocatalysts for various sets of applications. Different methods of enzyme engineering have been used in the past in an attempt to produce enzymes with improved functions and properties. Recent advancement in the field of random mutagenesis, screening, selection and computational design increased the versatility and the rapid development of enzymes under strong selection pressure with directed evolution experiments. Techniques of directed evolution improve enzymes fitness without understanding them in great detail and clearly demonstrate its future role in adapting enzymes for use in industry. Despite significant advances to date regarding biocatalyst improvement, there still remains a need to improve mutagenesis strategies and development of easy screening and selection tools without significant human intervention. This review covers fundamental and major development of directed evolution techniques, and highlights the advances in mutagenesis, screening and selection methods with examples of enzymes developed by using these approaches. Several commonly used methods for creating molecular diversity with their advantages and disadvantages including some recently used strategies are also discussed.

Forces, energetics, and dynamics of conjugated-carbon ring tethers adhered to CNTs: a computational investigation.

PubMed

Filla, Nicholas; Ramasamy, Ramaraja; Wang, Xianqiao

2018-04-25

The strength and nature of the interactions between carbon nanotubes (CNTs) and molecular tethers plays a vital role in technology such as CNT-enzyme sensors. Tethers that attach noncovalently to CNTs are ideal for retaining the electrical properties of the CNTs since they do not degrade the CNT surface and effect its electrical conductivity. However, leaching due to weak CNT-tether attachment is very common when using noncovalent tethers, and this has limited their use in commercial products including biosensors. Thus, understanding the fundamental mechanics governing the strength of CNT-tether adhesion is crucial for the design of highly sensitive, viable sensors. Here, we computationally investigate the adhesion strength of CNT-tether complexes with 8 different tethering molecules designed to adhere noncovalently to the CNT surface. We study the effects of CNT diameter, CNT chirality, and the size/geometry of the tethering molecule on the adhesion energy and force. Our results show an asymptotic relationship between adhesion strength and CNT diameter. Calculations show that noncovalent tethers tested here can reach adhesion forces and energies that are up to 21% and 54% of the strength of the carbon-carbon single bond force and bond energy respectively. We anticipate our results will help guide CNT-enzyme sensor design to produce sensors with high sensitivity and minimal leaching.

Subsite mapping of enzymes. Depolymerase computer modelling.

PubMed Central

Allen, J D; Thoma, J A

1976-01-01

We have developed a depolymerase computer model that uses a minimization routine. The model is designed so that, given experimental bond-cleavage frequencies for oligomeric substrates and experimental Michaelis parameters as a function of substrate chain length, the optimum subsite map is generated. The minimized sum of the weighted-squared residuals of the experimental and calculated data is used as a criterion of the goodness-of-fit for the optimized subsite map. The application of the minimization procedure to subsite mapping is explored through the use of simulated data. A procedure is developed whereby the minimization model can be used to determine the number of subsites in the enzymic binding region and to locate the position of the catalytic amino acids among these subsites. The degree of propagation of experimental variance into the subsite-binding energies is estimated. The question of whether hydrolytic rate coefficients are constant or a function of the number of filled subsites is examined. PMID:999629

Advances in quantum and molecular mechanical (QM/MM) simulations for organic and enzymatic reactions.

PubMed

Acevedo, Orlando; Jorgensen, William L

2010-01-19

Application of combined quantum and molecular mechanical (QM/MM) methods focuses on predicting activation barriers and the structures of stationary points for organic and enzymatic reactions. Characterization of the factors that stabilize transition structures in solution and in enzyme active sites provides a basis for design and optimization of catalysts. Continued technological advances allowed for expansion from prototypical cases to mechanistic studies featuring detailed enzyme and condensed-phase environments with full integration of the QM calculations and configurational sampling. This required improved algorithms featuring fast QM methods, advances in computing changes in free energies including free-energy perturbation (FEP) calculations, and enhanced configurational sampling. In particular, the present Account highlights development of the PDDG/PM3 semi-empirical QM method, computation of multi-dimensional potentials of mean force (PMF), incorporation of on-the-fly QM in Monte Carlo (MC) simulations, and a polynomial quadrature method for efficient modeling of proton-transfer reactions. The utility of this QM/MM/MC/FEP methodology is illustrated for a variety of organic reactions including substitution, decarboxylation, elimination, and pericyclic reactions. A comparison to experimental kinetic results on medium effects has verified the accuracy of the QM/MM approach in the full range of solvents from hydrocarbons to water to ionic liquids. Corresponding results from ab initio and density functional theory (DFT) methods with continuum-based treatments of solvation reveal deficiencies, particularly for protic solvents. Also summarized in this Account are three specific QM/MM applications to biomolecular systems: (1) a recent study that clarified the mechanism for the reaction of 2-pyrone derivatives catalyzed by macrophomate synthase as a tandem Michael-aldol sequence rather than a Diels-Alder reaction, (2) elucidation of the mechanism of action of fatty acid amide hydrolase (FAAH), an unusual Ser-Ser-Lys proteolytic enzyme, and (3) the construction of enzymes for Kemp elimination of 5-nitrobenzisoxazole that highlights the utility of QM/MM in the design of artificial enzymes.

Ensemble Architecture for Prediction of Enzyme-ligand Binding Residues Using Evolutionary Information.

PubMed

Pai, Priyadarshini P; Dattatreya, Rohit Kadam; Mondal, Sukanta

2017-11-01

Enzyme interactions with ligands are crucial for various biochemical reactions governing life. Over many years attempts to identify these residues for biotechnological manipulations have been made using experimental and computational techniques. The computational approaches have gathered impetus with the accruing availability of sequence and structure information, broadly classified into template-based and de novo methods. One of the predominant de novo methods using sequence information involves application of biological properties for supervised machine learning. Here, we propose a support vector machines-based ensemble for prediction of protein-ligand interacting residues using one of the most important discriminative contributing properties in the interacting residue neighbourhood, i. e., evolutionary information in the form of position-specific- scoring matrix (PSSM). The study has been performed on a non-redundant dataset comprising of 9269 interacting and 91773 non-interacting residues for prediction model generation and further evaluation. Of the various PSSM-based models explored, the proposed method named ROBBY (pRediction Of Biologically relevant small molecule Binding residues on enzYmes) shows an accuracy of 84.0 %, Matthews Correlation Coefficient of 0.343 and F-measure of 39.0 % on 78 test enzymes. Further, scope of adding domain knowledge such as pocket information has also been investigated; results showed significant enhancement in method precision. Findings are hoped to boost the reliability of small-molecule ligand interaction prediction for enzyme applications and drug design. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

SABER: A computational method for identifying active sites for new reactions

PubMed Central

Nosrati, Geoffrey R; Houk, K N

2012-01-01

A software suite, SABER (Selection of Active/Binding sites for Enzyme Redesign), has been developed for the analysis of atomic geometries in protein structures, using a geometric hashing algorithm (Barker and Thornton, Bioinformatics 2003;19:1644–1649). SABER is used to explore the Protein Data Bank (PDB) to locate proteins with a specific 3D arrangement of catalytic groups to identify active sites that might be redesigned to catalyze new reactions. As a proof-of-principle test, SABER was used to identify enzymes that have the same catalytic group arrangement present in o-succinyl benzoate synthase (OSBS). Among the highest-scoring scaffolds identified by the SABER search for enzymes with the same catalytic group arrangement as OSBS were l-Ala d/l-Glu epimerase (AEE) and muconate lactonizing enzyme II (MLE), both of which have been redesigned to become effective OSBS catalysts, demonstrated by experiments. Next, we used SABER to search for naturally existing active sites in the PDB with catalytic groups similar to those present in the designed Kemp elimination enzyme KE07. From over 2000 geometric matches to the KE07 active site, SABER identified 23 matches that corresponded to residues from known active sites. The best of these matches, with a 0.28 Å catalytic atom RMSD to KE07, was then redesigned to be compatible with the Kemp elimination using RosettaDesign. We also used SABER to search for potential Kemp eliminases using a theozyme predicted to provide a greater rate acceleration than the active site of KE07, and used Rosetta to create a design based on the proteins identified. PMID:22492397

PChopper: high throughput peptide prediction for MRM/SRM transition design.

PubMed

Afzal, Vackar; Huang, Jeffrey T-J; Atrih, Abdel; Crowther, Daniel J

2011-08-15

The use of selective reaction monitoring (SRM) based LC-MS/MS analysis for the quantification of phosphorylation stoichiometry has been rapidly increasing. At the same time, the number of sites that can be monitored in a single LC-MS/MS experiment is also increasing. The manual processes associated with running these experiments have highlighted the need for computational assistance to quickly design MRM/SRM candidates. PChopper has been developed to predict peptides that can be produced via enzymatic protein digest; this includes single enzyme digests, and combinations of enzymes. It also allows digests to be simulated in 'batch' mode and can combine information from these simulated digests to suggest the most appropriate enzyme(s) to use. PChopper also allows users to define the characteristic of their target peptides, and can automatically identify phosphorylation sites that may be of interest. Two application end points are available for interacting with the system; the first is a web based graphical tool, and the second is an API endpoint based on HTTP REST. Service oriented architecture was used to rapidly develop a system that can consume and expose several services. A graphical tool was built to provide an easy to follow workflow that allows scientists to quickly and easily identify the enzymes required to produce multiple peptides in parallel via enzymatic digests in a high throughput manner.

What makes proteins work: exploring life in P-T-X

NASA Astrophysics Data System (ADS)

Ichiye, Toshiko

2016-12-01

Although considerable progress has been made in the molecular biophysics of proteins, it is still not possible to reliably design an enzyme for a given function. The current understanding of enzyme function is that both structure and flexibility are important. Much attention has been focused recently on protein folding and thus structure, spurred on by insights from the folding funnel concept. For experimental studies of protein folding, variations in temperature (T) and chemical composition (X) of the solution have been traditionally exploited, although more recent studies using variations in pressure (P) made possible through new instrumentation have led to a deeper understanding of the energy landscape of protein folding. Other work has shown that flexibility is also essential for enzymes, although it is still not clear what type is important. Another avenue has been to take advantage of ‘Nature’s laboratory’ by exploring homologous proteins from organisms that live in extreme conditions, or ‘extremophiles’. While the most studied extremophiles live at extremes of T and X, recent exploration of deep-sea environments has led to the discovery of organisms living under high P, or ‘piezophiles’. An exploration of targeted enzymes from organisms with various P-T-X growth conditions coupled with advances in biophysical instrumentation and computer simulations that allow studies of these enzymes at different P-T-X conditions may lead to a better understanding of ‘flexibility’ and to general design criteria for active enzymes. Preface. Kamal Shukla’s great contribution to science has been his vision that physical sciences could bring new insights to biological sciences, and that the marriage of methodologies, particularly theoretical/computational with experimental, was needed to tackle the complexities of biology. Furthermore, his openness to new methods and different ideas outside the current fad has helped make his vision a reality. In my remarks below, I have not tried to limit myself to projects that I know Kamal had sponsored, nor have I tried to highlight all that he has sponsored. Instead, everything I mention has been influenced directly or indirectly by his efforts. Perhaps the indirect influences are most telling, because they would not have happened without Kamal.

Dual-radiolabeled nanoparticle probes for depth-independent in vivo imaging of enzyme activation

NASA Astrophysics Data System (ADS)

Black, Kvar C. L.; Zhou, Mingzhou; Sarder, Pinaki; Kuchuk, Maryna; Al-Yasiri, Amal Y.; Gunsten, Sean P.; Liang, Kexian; Hennkens, Heather M.; Akers, Walter J.; Laforest, Richard; Brody, Steven L.; Cutler, Cathy S.; Achilefu, Samuel

2018-02-01

Quantitative and noninvasive measurement of protease activities has remained an imaging challenge in deep tissues such as the lungs. Here, we designed a dual-radiolabeled probe for reporting the activities of proteases such as matrix metalloproteinases (MMPs) with multispectral single photon emission computed tomography (SPECT) imaging. A gold nanoparticle (NP) was radiolabeled with 125I and 111In and functionalized with an MMP9-cleavable peptide to form a multispectral SPECT imaging contrast agent. In another design, incorporation of 199Au radionuclide into the metal crystal structure of gold NPs provided a superior and stable reference signal in lungs, and 111In was linked to the NP surface via a protease-cleavable substrate, which can serve as an enzyme activity reporter. This work reveals strategies to correlate protease activities with diverse pathologies in a tissue-depth independent manner.

Network design and analysis for multi-enzyme biocatalysis.

PubMed

Blaß, Lisa Katharina; Weyler, Christian; Heinzle, Elmar

2017-08-10

As more and more biological reaction data become available, the full exploration of the enzymatic potential for the synthesis of valuable products opens up exciting new opportunities but is becoming increasingly complex. The manual design of multi-step biosynthesis routes involving enzymes from different organisms is very challenging. To harness the full enzymatic potential, we developed a computational tool for the directed design of biosynthetic production pathways for multi-step catalysis with in vitro enzyme cascades, cell hydrolysates and permeabilized cells. We present a method which encompasses the reconstruction of a genome-scale pan-organism metabolic network, path-finding and the ranking of the resulting pathway candidates for proposing suitable synthesis pathways. The network is based on reaction and reaction pair data from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and the thermodynamics calculator eQuilibrator. The pan-organism network is especially useful for finding the most suitable pathway to a target metabolite from a thermodynamic or economic standpoint. However, our method can be used with any network reconstruction, e.g. for a specific organism. We implemented a path-finding algorithm based on a mixed-integer linear program (MILP) which takes into account both topology and stoichiometry of the underlying network. Unlike other methods we do not specify a single starting metabolite, but our algorithm searches for pathways starting from arbitrary start metabolites to a target product of interest. Using a set of biochemical ranking criteria including pathway length, thermodynamics and other biological characteristics such as number of heterologous enzymes or cofactor requirement, it is possible to obtain well-designed meaningful pathway alternatives. In addition, a thermodynamic profile, the overall reactant balance and potential side reactions as well as an SBML file for visualization are generated for each pathway alternative. We present an in silico tool for the design of multi-enzyme biosynthetic production pathways starting from a pan-organism network. The method is highly customizable and each module can be adapted to the focus of the project at hand. This method is directly applicable for (i) in vitro enzyme cascades, (ii) cell hydrolysates and (iii) permeabilized cells.

Biosensors with Built-In Biomolecular Logic Gates for Practical Applications

PubMed Central

Lai, Yu-Hsuan; Sun, Sin-Cih; Chuang, Min-Chieh

2014-01-01

Molecular logic gates, designs constructed with biological and chemical molecules, have emerged as an alternative computing approach to silicon-based logic operations. These molecular computers are capable of receiving and integrating multiple stimuli of biochemical significance to generate a definitive output, opening a new research avenue to advanced diagnostics and therapeutics which demand handling of complex factors and precise control. In molecularly gated devices, Boolean logic computations can be activated by specific inputs and accurately processed via bio-recognition, bio-catalysis, and selective chemical reactions. In this review, we survey recent advances of the molecular logic approaches to practical applications of biosensors, including designs constructed with proteins, enzymes, nucleic acids, nanomaterials, and organic compounds, as well as the research avenues for future development of digitally operating “sense and act” schemes that logically process biochemical signals through networked circuits to implement intelligent control systems. PMID:25587423

β-Amino acid catalyzed asymmetric Michael additions: design of organocatalysts with catalytic acid/base dyad inspired by serine proteases.

PubMed

Yang, Hui; Wong, Ming Wah

2011-09-16

A new type of chiral β-amino acid catalyst has been computationally designed, mimicking the enzyme catalysis of serine proteases. Our catalyst approach is based on the bioinspired catalytic acid/base dyad, namely, a carboxyl and imidazole pair. DFT calculations predict that this designed organocatalyst catalyzes Michael additions of aldehydes to nitroalkenes with excellent enantioselectivities and remarkably high anti diastereoselectivities. The unusual stacked geometry of the enamine intermediate, hydrogen bonding network, and the adoption of an exo transition state are the keys to understand the stereoselectivity. © 2011 American Chemical Society

Principles of Protein Stability and Their Application in Computational Design.

PubMed

Goldenzweig, Adi; Fleishman, Sarel

2018-01-26

Proteins are increasingly used in basic and applied biomedical research.Many proteins, however, are only marginally stable and can be expressed in limited amounts, thus hampering research and applications. Research has revealed the thermodynamic, cellular, and evolutionary principles and mechanisms that underlie marginal stability. With this growing understanding, computational stability design methods have advanced over the past two decades starting from methods that selectively addressed only some aspects of marginal stability. Current methods are more general and, by combining phylogenetic analysis with atomistic design, have shown drastic improvements in solubility, thermal stability, and aggregation resistance while maintaining the protein's primary molecular activity. Stability design is opening the way to rational engineering of improved enzymes, therapeutics, and vaccines and to the application of protein design methodology to large proteins and molecular activities that have proven challenging in the past. Expected final online publication date for the Annual Review of Biochemistry Volume 87 is June 20, 2018. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Discriminating between stabilizing and destabilizing protein design mutations via recombination and simulation.

PubMed

Johnson, Lucas B; Gintner, Lucas P; Park, Sehoo; Snow, Christopher D

2015-08-01

Accuracy of current computational protein design (CPD) methods is limited by inherent approximations in energy potentials and sampling. These limitations are often used to qualitatively explain design failures; however, relatively few studies provide specific examples or quantitative details that can be used to improve future CPD methods. Expanding the design method to include a library of sequences provides data that is well suited for discriminating between stabilizing and destabilizing design elements. Using thermophilic endoglucanase E1 from Acidothermus cellulolyticus as a model enzyme, we computationally designed a sequence with 60 mutations. The design sequence was rationally divided into structural blocks and recombined with the wild-type sequence. Resulting chimeras were assessed for activity and thermostability. Surprisingly, unlike previous chimera libraries, regression analysis based on one- and two-body effects was not sufficient for predicting chimera stability. Analysis of molecular dynamics simulations proved helpful in distinguishing stabilizing and destabilizing mutations. Reverting to the wild-type amino acid at destabilized sites partially regained design stability, and introducing predicted stabilizing mutations in wild-type E1 significantly enhanced thermostability. The ability to isolate stabilizing and destabilizing elements in computational design offers an opportunity to interpret previous design failures and improve future CPD methods. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

PREvaIL, an integrative approach for inferring catalytic residues using sequence, structural, and network features in a machine-learning framework.

PubMed

Song, Jiangning; Li, Fuyi; Takemoto, Kazuhiro; Haffari, Gholamreza; Akutsu, Tatsuya; Chou, Kuo-Chen; Webb, Geoffrey I

2018-04-14

Determining the catalytic residues in an enzyme is critical to our understanding the relationship between protein sequence, structure, function, and enhancing our ability to design novel enzymes and their inhibitors. Although many enzymes have been sequenced, and their primary and tertiary structures determined, experimental methods for enzyme functional characterization lag behind. Because experimental methods used for identifying catalytic residues are resource- and labor-intensive, computational approaches have considerable value and are highly desirable for their ability to complement experimental studies in identifying catalytic residues and helping to bridge the sequence-structure-function gap. In this study, we describe a new computational method called PREvaIL for predicting enzyme catalytic residues. This method was developed by leveraging a comprehensive set of informative features extracted from multiple levels, including sequence, structure, and residue-contact network, in a random forest machine-learning framework. Extensive benchmarking experiments on eight different datasets based on 10-fold cross-validation and independent tests, as well as side-by-side performance comparisons with seven modern sequence- and structure-based methods, showed that PREvaIL achieved competitive predictive performance, with an area under the receiver operating characteristic curve and area under the precision-recall curve ranging from 0.896 to 0.973 and from 0.294 to 0.523, respectively. We demonstrated that this method was able to capture useful signals arising from different levels, leveraging such differential but useful types of features and allowing us to significantly improve the performance of catalytic residue prediction. We believe that this new method can be utilized as a valuable tool for both understanding the complex sequence-structure-function relationships of proteins and facilitating the characterization of novel enzymes lacking functional annotations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Comprehensive restriction enzyme lists to update any DNA sequence computer program.

PubMed

Raschke, E

1993-04-01

Restriction enzyme lists are presented for the practical working geneticist to update any DNA computer program. These lists combine formerly scattered information and contain all presently known restriction enzymes with a unique recognition sequence, a cut site, or methylation (in)sensitivity. The lists are in the shortest possible form to also be functional with small DNA computer programs, and will produce clear restriction maps without any redundancy or loss of information. The lists discern between commercial and noncommercial enzymes, and prototype enzymes and different isoschizomers are cross-referenced. Differences in general methylation sensitivities and (in)sensitivities against Dam and Dcm methylases of Escherichia coli are indicated. Commercial methylases and intron-encoded endonucleases are included. An address list is presented to contact commercial suppliers. The lists are constantly updated and available in electronic form as pure US ASCII files, and in formats for the DNA computer programs DNA-Strider for Apple Macintosh, and DNAsis for IBM personal computers or compatibles via e-mail from the internet address: NETSERV@EMBL-HEIDELBERG.DE by sending only the message HELP RELIBRARY.

Energetics and Structural Characterization of the large-scale Functional Motion of Adenylate Kinase

PubMed Central

Formoso, Elena; Limongelli, Vittorio; Parrinello, Michele

2015-01-01

Adenylate Kinase (AK) is a signal transducing protein that regulates cellular energy homeostasis balancing between different conformations. An alteration of its activity can lead to severe pathologies such as heart failure, cancer and neurodegenerative diseases. A comprehensive elucidation of the large-scale conformational motions that rule the functional mechanism of this enzyme is of great value to guide rationally the development of new medications. Here using a metadynamics-based computational protocol we elucidate the thermodynamics and structural properties underlying the AK functional transitions. The free energy estimation of the conformational motions of the enzyme allows characterizing the sequence of events that regulate its action. We reveal the atomistic details of the most relevant enzyme states, identifying residues such as Arg119 and Lys13, which play a key role during the conformational transitions and represent druggable spots to design enzyme inhibitors. Our study offers tools that open new areas of investigation on large-scale motion in proteins. PMID:25672826

Energetics and Structural Characterization of the large-scale Functional Motion of Adenylate Kinase

NASA Astrophysics Data System (ADS)

Formoso, Elena; Limongelli, Vittorio; Parrinello, Michele

2015-02-01

Adenylate Kinase (AK) is a signal transducing protein that regulates cellular energy homeostasis balancing between different conformations. An alteration of its activity can lead to severe pathologies such as heart failure, cancer and neurodegenerative diseases. A comprehensive elucidation of the large-scale conformational motions that rule the functional mechanism of this enzyme is of great value to guide rationally the development of new medications. Here using a metadynamics-based computational protocol we elucidate the thermodynamics and structural properties underlying the AK functional transitions. The free energy estimation of the conformational motions of the enzyme allows characterizing the sequence of events that regulate its action. We reveal the atomistic details of the most relevant enzyme states, identifying residues such as Arg119 and Lys13, which play a key role during the conformational transitions and represent druggable spots to design enzyme inhibitors. Our study offers tools that open new areas of investigation on large-scale motion in proteins.

Integrative computational approach for genome-based study of microbial lipid-degrading enzymes.

PubMed

Vorapreeda, Tayvich; Thammarongtham, Chinae; Laoteng, Kobkul

2016-07-01

Lipid-degrading or lipolytic enzymes have gained enormous attention in academic and industrial sectors. Several efforts are underway to discover new lipase enzymes from a variety of microorganisms with particular catalytic properties to be used for extensive applications. In addition, various tools and strategies have been implemented to unravel the functional relevance of the versatile lipid-degrading enzymes for special purposes. This review highlights the study of microbial lipid-degrading enzymes through an integrative computational approach. The identification of putative lipase genes from microbial genomes and metagenomic libraries using homology-based mining is discussed, with an emphasis on sequence analysis of conserved motifs and enzyme topology. Molecular modelling of three-dimensional structure on the basis of sequence similarity is shown to be a potential approach for exploring the structural and functional relationships of candidate lipase enzymes. The perspectives on a discriminative framework of cutting-edge tools and technologies, including bioinformatics, computational biology, functional genomics and functional proteomics, intended to facilitate rapid progress in understanding lipolysis mechanism and to discover novel lipid-degrading enzymes of microorganisms are discussed.

SABER: a computational method for identifying active sites for new reactions.

PubMed

Nosrati, Geoffrey R; Houk, K N

2012-05-01

A software suite, SABER (Selection of Active/Binding sites for Enzyme Redesign), has been developed for the analysis of atomic geometries in protein structures, using a geometric hashing algorithm (Barker and Thornton, Bioinformatics 2003;19:1644-1649). SABER is used to explore the Protein Data Bank (PDB) to locate proteins with a specific 3D arrangement of catalytic groups to identify active sites that might be redesigned to catalyze new reactions. As a proof-of-principle test, SABER was used to identify enzymes that have the same catalytic group arrangement present in o-succinyl benzoate synthase (OSBS). Among the highest-scoring scaffolds identified by the SABER search for enzymes with the same catalytic group arrangement as OSBS were L-Ala D/L-Glu epimerase (AEE) and muconate lactonizing enzyme II (MLE), both of which have been redesigned to become effective OSBS catalysts, demonstrated by experiments. Next, we used SABER to search for naturally existing active sites in the PDB with catalytic groups similar to those present in the designed Kemp elimination enzyme KE07. From over 2000 geometric matches to the KE07 active site, SABER identified 23 matches that corresponded to residues from known active sites. The best of these matches, with a 0.28 Å catalytic atom RMSD to KE07, was then redesigned to be compatible with the Kemp elimination using RosettaDesign. We also used SABER to search for potential Kemp eliminases using a theozyme predicted to provide a greater rate acceleration than the active site of KE07, and used Rosetta to create a design based on the proteins identified. Copyright © 2012 The Protein Society.

A novel stimuli-synchronized alloy-treated matrix for space-defined gastrointestinal delivery of mesalamine in the Large White pig model.

PubMed

Bawa, Priya; Choonara, Yahya E; du Toit, Lisa C; Kumar, Pradeep; Ndesendo, Valence M K; Meyer, Leith C R; Pillay, Viness

2013-03-28

The study focussed on designing a Stimuli-Synchronized Matrix (SSM) for space-defined colonic delivery of the anti-inflammatory drug mesalamine. The configured matrix provided time-independent delivery and stimuli targeting. Formulations were optimized according to a Box-Behnken experimental design that constituted mesalamine-loaded BaSO4-crosslinked chitosan dispersed within a pectin, carboxymethylcellulose and xanthan gum complex. The complex was compressed into matrices and subsequently alloy-treated with pectin and ethylcellulose. In vitro drug release was determined in the presence and absence of colonic enzymes and the mean dissolution time was used for formulation optimization. To mechanistically elucidate the synchronous catalytic action of the enzymes pectinase and glucosidase on the matrix, computer-aided 3D modelling of active fractions of the enzyme-substrate complexes was generated to predict the orientation of residues affecting the substrate domain. Drug release profiles revealed distinct colonic enzyme responsiveness with fractions of 0.402 and 0.152 of mesalamine released in the presence and absence of enzymes, respectively after 24h. The commercial comparator product showed irreproducible release profiles over the same period (SD=0.550) compared to the SSM formulation (SD=0.037). FTIR spectra of alloy-treated matrices showed no peaks from 1589 to 1512cm(-1) after colonic enzyme exposure. With increasing enzyme exposure there were also no peaks between 1646 and 1132cm(-1). This indicated polymeric enzyme cleavage for controlled and space-defined release of mesalamine. Plasma concentration profiles in the Large White pig model produced a Cmax of 3.77±1.375μg/mL compared to 10.604±2.846μg/mL for the comparator formulation. The SSM formulation proved superior over the comparator product by providing superiorly controlled enzyme-responsive colonic drug delivery. Copyright © 2012 Elsevier B.V. All rights reserved.

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

Molecular Modeling in Drug Design for the Development of Organophosphorus Antidotes/Prophylactics.

DTIC Science & Technology

1986-06-01

multidimensional statistical QSAR analysis techniques to suggest new structures for synthesis and evaluation. C. Application of quantum chemical techniques to...compounds for synthesis and testing for antidotal potency. E. Use of computer-assisted methods to determine the steric constraints at the active site...modeling techniques to model the enzyme acetylcholinester-se. H. Suggestion of some novel compounds for synthesis and testing for reactivating

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

Discovering Novel Alternaria solani Succinate Dehydrogenase Inhibitors by In Silico Modeling and Virtual Screening Strategies to Combat Early Blight

NASA Astrophysics Data System (ADS)

Iftikhar, Sehrish; Shahid, Ahmad A.; Halim, Sobia A.; Wolters, Pieter J.; Vleeshouwers, Vivianne G. A. A.; Khan, Ajmal; Al-Harrasi, Ahmed; Ahmad, Shahbaz

2017-11-01

Alternaria blight is an important foliage disease caused by Alternaria solani. The enzyme Succinate dehydrogenase (SDH) is a potential drug target because of its role in tricarboxylic acid cycle. Hence targeting Alternaria solani SDH enzyme could be efficient tool to design novel fungicides against A. solani. We employed computational methodologies to design new SDH inhibitors using homology modeling; pharmacophore modeling and structure based virtual screening protocol. The three dimensional SDH model showed good stereo-chemical and structural properties. Based on virtual screening results twelve commercially available compounds were purchased and tested in vitro and in vivo. The compounds were found to inhibit mycelial growth of A. solani. Moreover in vitro trials showed that inhibitory effects were enhanced with increase in concentrations. Similarly increased disease control was observed in pre-treated potato tubers. Hence the applied in silico strategy led us to identify new and novel fungicides.

Discovering Novel Alternaria solani Succinate Dehydrogenase Inhibitors by in Silico Modeling and Virtual Screening Strategies to Combat Early Blight

PubMed Central

Iftikhar, Sehrish; Shahid, Ahmad A.; Halim, Sobia A.; Wolters, Pieter J.; Vleeshouwers, Vivianne G. A. A.; Khan, Ajmal; Al-Harrasi, Ahmed; Ahmad, Shahbaz

2017-01-01

Alternaria blight is an important foliage disease caused by Alternaria solani. The enzyme Succinate dehydrogenase (SDH) is a potential drug target because of its role in tricarboxylic acid cycle. Hence targeting Alternaria solani SDH enzyme could be efficient tool to design novel fungicides against A. solani. We employed computational methodologies to design new SDH inhibitors using homology modeling; pharmacophore modeling and structure based virtual screening. The three dimensional SDH model showed good stereo-chemical and structural properties. Based on virtual screening results twelve commercially available compounds were purchased and tested in vitro and in vivo. The compounds were found to inhibit mycelial growth of A. solani. Moreover in vitro trials showed that inhibitory effects were enhanced with increase in concentrations. Similarly increased disease control was observed in pre-treated potato tubers. Hence the applied in silico strategy led us to identify novel fungicides. PMID:29204422

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.

Principles for computational design of binding antibodies

PubMed Central

Pszolla, M. Gabriele; Lapidoth, Gideon D.; Norn, Christoffer; Dym, Orly; Unger, Tamar; Albeck, Shira; Tyka, Michael D.; Fleishman, Sarel J.

2017-01-01

Natural proteins must both fold into a stable conformation and exert their molecular function. To date, computational design has successfully produced stable and atomically accurate proteins by using so-called “ideal” folds rich in regular secondary structures and almost devoid of loops and destabilizing elements, such as cavities. Molecular function, such as binding and catalysis, however, often demands nonideal features, including large and irregular loops and buried polar interaction networks, which have remained challenging for fold design. Through five design/experiment cycles, we learned principles for designing stable and functional antibody variable fragments (Fvs). Specifically, we (i) used sequence-design constraints derived from antibody multiple-sequence alignments, and (ii) during backbone design, maintained stabilizing interactions observed in natural antibodies between the framework and loops of complementarity-determining regions (CDRs) 1 and 2. Designed Fvs bound their ligands with midnanomolar affinities and were as stable as natural antibodies, despite having >30 mutations from mammalian antibody germlines. Furthermore, crystallographic analysis demonstrated atomic accuracy throughout the framework and in four of six CDRs in one design and atomic accuracy in the entire Fv in another. The principles we learned are general, and can be implemented to design other nonideal folds, generating stable, specific, and precise antibodies and enzymes. PMID:28973872

Enzyme Informatics

PubMed Central

Alderson, Rosanna G.; Ferrari, Luna De; Mavridis, Lazaros; McDonagh, James L.; Mitchell, John B. O.; Nath, Neetika

2012-01-01

Over the last 50 years, sequencing, structural biology and bioinformatics have completely revolutionised biomolecular science, with millions of sequences and tens of thousands of three dimensional structures becoming available. The bioinformatics of enzymes is well served by, mostly free, online databases. BRENDA describes the chemistry, substrate specificity, kinetics, preparation and biological sources of enzymes, while KEGG is valuable for understanding enzymes and metabolic pathways. EzCatDB, SFLD and MACiE are key repositories for data on the chemical mechanisms by which enzymes operate. At the current rate of genome sequencing and manual annotation, human curation will never finish the functional annotation of the ever-expanding list of known enzymes. Hence there is an increasing need for automated annotation, though it is not yet widespread for enzyme data. In contrast, functional ontologies such as the Gene Ontology already profit from automation. Despite our growing understanding of enzyme structure and dynamics, we are only beginning to be able to design novel enzymes. One can now begin to trace the functional evolution of enzymes using phylogenetics. The ability of enzymes to perform secondary functions, albeit relatively inefficiently, gives clues as to how enzyme function evolves. Substrate promiscuity in enzymes is one example of imperfect specificity in protein-ligand interactions. Similarly, most drugs bind to more than one protein target. This may sometimes result in helpful polypharmacology as a drug modulates plural targets, but also often leads to adverse side-effects. Many cheminformatics approaches can be used to model the interactions between druglike molecules and proteins in silico. We can even use quantum chemical techniques like DFT and QM/MM to compute the structural and energetic course of enzyme catalysed chemical reaction mechanisms, including a full description of bond making and breaking. PMID:23116471

Examinations of the Chemical Step in Enzyme Catalysis.

PubMed

Singh, P; Islam, Z; Kohen, A

2016-01-01

Advances in computational and experimental methods in enzymology have aided comprehension of enzyme-catalyzed chemical reactions. The main difficulty in comparing computational findings to rate measurements is that the first examines a single energy barrier, while the second frequently reflects a combination of many microscopic barriers. We present here intrinsic kinetic isotope effects and their temperature dependence as a useful experimental probe of a single chemical step in a complex kinetic cascade. Computational predictions are tested by this method for two model enzymes: dihydrofolate reductase and thymidylate synthase. The description highlights the significance of collaboration between experimentalists and theoreticians to develop a better understanding of enzyme-catalyzed chemical conversions. © 2016 Elsevier Inc. All rights reserved.

Computer-assisted enzyme immunoassays and simplified immunofluorescence assays: applications for the diagnostic laboratory and the veterinarian's office.

PubMed

Jacobson, R H; Downing, D R; Lynch, T J

1982-11-15

A computer-assisted enzyme-linked immunosorbent assay (ELISA) system, based on kinetics of the reaction between substrate and enzyme molecules, was developed for testing large numbers of sera in laboratory applications. Systematic and random errors associated with conventional ELISA technique were identified leading to results formulated on a statistically validated, objective, and standardized basis. In a parallel development, an inexpensive system for field and veterinary office applications contained many of the qualities of the computer-assisted ELISA. This system uses a fluorogenic indicator (rather than the enzyme-substrate interaction) in a rapid test (15 to 20 minutes' duration) which promises broad application in serodiagnosis.

Quantum Mechanical Modeling: A Tool for the Understanding of Enzyme Reactions

PubMed Central

Náray-Szabó, Gábor; Oláh, Julianna; Krámos, Balázs

2013-01-01

Most enzyme reactions involve formation and cleavage of covalent bonds, while electrostatic effects, as well as dynamics of the active site and surrounding protein regions, may also be crucial. Accordingly, special computational methods are needed to provide an adequate description, which combine quantum mechanics for the reactive region with molecular mechanics and molecular dynamics describing the environment and dynamic effects, respectively. In this review we intend to give an overview to non-specialists on various enzyme models as well as established computational methods and describe applications to some specific cases. For the treatment of various enzyme mechanisms, special approaches are often needed to obtain results, which adequately refer to experimental data. As a result of the spectacular progress in the last two decades, most enzyme reactions can be quite precisely treated by various computational methods. PMID:24970187

A Novel Semi-biosynthetic Route for Artemisinin Production Using Engineered Substrate-Promiscuous P450BM3

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

Dietrich, Jeffrey; Yoshikuni, Yasuo; Fisher, Karl

2009-11-30

Production of fine heterologus pathways in microbial hosts is frequently hindered by insufficient knowledge of the native metabolic pathway and its cognate enzymes; often the pathway is unresolved and enzymes lack detailed characterization. An alternative paradigm to using native pathways is de novo pathway design using well-characterized, substrate-promiscuous enzymes. We demonstrate this concept using P450BM3 from Bacillus megaterium. Using a computer model, we illustrate how key P450BM3 activ site mutations enable binding of non-native substrate amorphadiene, incorporating these mutations into P450BM3 enabled the selective oxidation of amorphadiene arteminsinic-11s,12-epoxide, at titers of 250 mg L"1 in E. coli. We also demonstratemore » high-yeilding, selective transformations to dihydroartemisinic acid, the immediate precursor to the high value anti-malarial drug artemisinin.« less

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.

Applying Knowledge of Enzyme Biochemistry to the Prediction of Functional Sites for Aiding Drug Discovery.

PubMed

Pai, Priyadarshini P; Mondal, Sukanta

2017-01-01

Enzymes are biological catalysts that play an important role in determining the patterns of chemical transformations pertaining to life. Many milestones have been achieved in unraveling the mechanisms in which the enzymes orchestrate various cellular processes using experimental and computational approaches. Experimental studies generating nearly all possible mutations of target enzymes have been aided by rapid computational approaches aiming at enzyme functional classification, understanding domain organization, functional site identification. The functional architecture, essentially, is involved in binding or interaction with ligands including substrates, products, cofactors, inhibitors, providing for their function, such as in catalysis, ligand mediated cell signaling, allosteric regulation and post-translational modifications. With the increasing availability of enzyme information and advances in algorithm development, computational approaches have now become more capable of providing precise inputs for enzyme engineering, and in the process also making it more efficient. This has led to interesting findings, especially in aberrant enzyme interactions, such as hostpathogen interactions in infection, neurodegenerative diseases, cancer and diabetes. This review aims to summarize in retrospection - the mined knowledge, vivid perspectives and challenging strides in using available experimentally validated enzyme information for characterization. An analytical outlook is presented on the scope of exploring future directions. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Synthesis of Vibegron Enabled by a Ketoreductase Rationally Designed for High pH Dynamic Kinetic Reduction.

PubMed

Xu, Feng; Kosjek, Birgit; Cabirol, Fabien L; Chen, Haibin; Desmond, Richard; Park, Jeonghan; Gohel, Anupam P; Collier, Steven J; Smith, Derek J; Liu, Zhuqing; Janey, Jacob M; Chung, John Y L; Alvizo, Oscar

2018-06-04

Described here is an efficient stereoselective synthesis of vibegron enabled by an enzymatic dynamic kinetic reduction that proceeds in a high-pH environment. To overcome enzyme performance limitations under these conditions, a ketoreductase was evolved by a computationally and structurally aided strategy to increase cofactor stability through tighter binding. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Theoretical study of Escherichia coli peptide deformylase inhibition by several drugs.

PubMed

Chikhi, Abdelouahab; Bensegueni, Abderrahmane; Boulahrouf, Abderrahmane; Bencharif, Mustapha

2006-01-01

Because peptide deformylase (PDF) is essential for the initiation of translation in eubacteria but not in eukaryotes, it is a potentially interesting target for antibiotics. Computer simulation using docking software can be used to model protein-ligand interactions, and in this brief report we describe its use in optimizing the design in PDF-directed inhibitors. PDF was used as target for a set of five inhibitors with substantial structural differences. Docking results show that the compound 1BB2 (actinonin) binds with high affinity to the enzyme and produces the most stable complex, forming nine hydrogen bonds with the enzyme active site. Its binding energy is DeltaG = -31.880 kJ/mol. The modeling study shows that when the methyl group of 1BB2 is replaced with an amine group, the binding energy is increased to -35.316 kJ/mole. This enhancement is more marked (DeltaG = -41.141 kJ/mol) when the propyl group and the five-membered ring of 1BB2 are replaced by an amide group and a phenyl ring, respectively. We describe an attempt to design better antibiotics on the basis of a computer-aided simulation of the interaction between a drug and its target molecule.

Model-Based Design of Biochemical Microreactors

PubMed Central

Elbinger, Tobias; Gahn, Markus; Neuss-Radu, Maria; Hante, Falk M.; Voll, Lars M.; Leugering, Günter; Knabner, Peter

2016-01-01

Mathematical modeling of biochemical pathways is an important resource in Synthetic Biology, as the predictive power of simulating synthetic pathways represents an important step in the design of synthetic metabolons. In this paper, we are concerned with the mathematical modeling, simulation, and optimization of metabolic processes in biochemical microreactors able to carry out enzymatic reactions and to exchange metabolites with their surrounding medium. The results of the reported modeling approach are incorporated in the design of the first microreactor prototypes that are under construction. These microreactors consist of compartments separated by membranes carrying specific transporters for the input of substrates and export of products. Inside the compartments of the reactor multienzyme complexes assembled on nano-beads by peptide adapters are used to carry out metabolic reactions. The spatially resolved mathematical model describing the ongoing processes consists of a system of diffusion equations together with boundary and initial conditions. The boundary conditions model the exchange of metabolites with the neighboring compartments and the reactions at the surface of the nano-beads carrying the multienzyme complexes. Efficient and accurate approaches for numerical simulation of the mathematical model and for optimal design of the microreactor are developed. As a proof-of-concept scenario, a synthetic pathway for the conversion of sucrose to glucose-6-phosphate (G6P) was chosen. In this context, the mathematical model is employed to compute the spatio-temporal distributions of the metabolite concentrations, as well as application relevant quantities like the outflow rate of G6P. These computations are performed for different scenarios, where the number of beads as well as their loading capacity are varied. The computed metabolite distributions show spatial patterns, which differ for different experimental arrangements. Furthermore, the total output of G6P increases for scenarios where microcompartimentation of enzymes occurs. These results show that spatially resolved models are needed in the description of the conversion processes. Finally, the enzyme stoichiometry on the nano-beads is determined, which maximizes the production of glucose-6-phosphate. PMID:26913283

Predicting novel substrates for enzymes with minimal experimental effort with active learning

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

Pertusi, Dante A.; Moura, Matthew E.; Jeffryes, James G.

Enzymatic substrate promiscuity is more ubiquitous than previously thought, with significant consequences for understanding metabolism and its application to biocatalysis. This realization has given rise to the need for efficient characterization of enzyme promiscuity. Enzyme promiscuity is currently characterized with a limited number of human-selected compounds that may not be representative of the enzyme's versatility. While testing large numbers of compounds may be impractical, computational approaches can exploit existing data to determine the most informative substrates to test next, thereby more thoroughly exploring an enzyme's versatility. To demonstrate this, we used existing studies and tested compounds for four different enzymes,more » developed support vector machine (SVM) models using these datasets, and selected additional compounds for experiments using an active learning approach. SVMs trained on a chemically diverse set of compounds were discovered to achieve maximum accuracies of similar to 80% using similar to 33% fewer compounds than datasets based on all compounds tested in existing studies. Active learning-selected compounds for testing resolved apparent conflicts in the existing training data, while adding diversity to the dataset. The application of these algorithms to wide arrays of metabolic enzymes would result in a library of SVMs that can predict high-probability promiscuous enzymatic reactions and could prove a valuable resource for the design of novel metabolic pathways.« less

iEzy-Drug: A Web Server for Identifying the Interaction between Enzymes and Drugs in Cellular Networking

PubMed Central

Min, Jian-Liang; Chou, Kuo-Chen

2013-01-01

With the features of extremely high selectivity and efficiency in catalyzing almost all the chemical reactions in cells, enzymes play vitally important roles for the life of an organism and hence have become frequent targets for drug design. An essential step in developing drugs by targeting enzymes is to identify drug-enzyme interactions in cells. It is both time-consuming and costly to do this purely by means of experimental techniques alone. Although some computational methods were developed in this regard based on the knowledge of the three-dimensional structure of enzyme, unfortunately their usage is quite limited because three-dimensional structures of many enzymes are still unknown. Here, we reported a sequence-based predictor, called “iEzy-Drug,” in which each drug compound was formulated by a molecular fingerprint with 258 feature components, each enzyme by the Chou's pseudo amino acid composition generated via incorporating sequential evolution information and physicochemical features derived from its sequence, and the prediction engine was operated by the fuzzy K-nearest neighbor algorithm. The overall success rate achieved by iEzy-Drug via rigorous cross-validations was about 91%. Moreover, to maximize the convenience for the majority of experimental scientists, a user-friendly web server was established, by which users can easily obtain their desired results. PMID:24371828

Predicting novel substrates for enzymes with minimal experimental effort with active learning.

PubMed

Pertusi, Dante A; Moura, Matthew E; Jeffryes, James G; Prabhu, Siddhant; Walters Biggs, Bradley; Tyo, Keith E J

2017-11-01

Enzymatic substrate promiscuity is more ubiquitous than previously thought, with significant consequences for understanding metabolism and its application to biocatalysis. This realization has given rise to the need for efficient characterization of enzyme promiscuity. Enzyme promiscuity is currently characterized with a limited number of human-selected compounds that may not be representative of the enzyme's versatility. While testing large numbers of compounds may be impractical, computational approaches can exploit existing data to determine the most informative substrates to test next, thereby more thoroughly exploring an enzyme's versatility. To demonstrate this, we used existing studies and tested compounds for four different enzymes, developed support vector machine (SVM) models using these datasets, and selected additional compounds for experiments using an active learning approach. SVMs trained on a chemically diverse set of compounds were discovered to achieve maximum accuracies of ~80% using ~33% fewer compounds than datasets based on all compounds tested in existing studies. Active learning-selected compounds for testing resolved apparent conflicts in the existing training data, while adding diversity to the dataset. The application of these algorithms to wide arrays of metabolic enzymes would result in a library of SVMs that can predict high-probability promiscuous enzymatic reactions and could prove a valuable resource for the design of novel metabolic pathways. Copyright © 2017 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Irreversible covalent modification of type I dehydroquinase with a stable Schiff base.

PubMed

Tizón, Lorena; Maneiro, María; Peón, Antonio; Otero, José M; Lence, Emilio; Poza, Sergio; van Raaij, Mark J; Thompson, Paul; Hawkins, Alastair R; González-Bello, Concepción

2015-01-21

The irreversible inhibition of type I dehydroquinase (DHQ1), the third enzyme of the shikimic acid pathway, is investigated by structural, biochemical and computational studies. Two epoxides, which are mimetics of the natural substrate, were designed as irreversible inhibitors of the DHQ1 enzyme and to study the binding requirements of the linkage to the enzyme. The epoxide with the S configuration caused the covalent modification of the protein whereas no reaction was obtained with its epimer. The first crystal structure of DHQ1 from Salmonella typhi covalently modified by the S epoxide, which is reported at 1.4 Å, revealed that the modified ligand is surprisingly covalently attached to the essential Lys170 by the formation of a stable Schiff base. The experimental and molecular dynamics simulation studies reported here highlight the huge importance of the conformation of the C3 carbon of the ligand for covalent linkage to this type of aldolase I enzyme, revealed the key role played by the essential His143 as a Lewis acid in this process and show the need for a neatly closed active site for catalysis.

Targeted prodrugs in oral drug delivery: the modern molecular biopharmaceutical approach.

PubMed

Dahan, Arik; Khamis, Mustafa; Agbaria, Riad; Karaman, Rafik

2012-08-01

The molecular revolution greatly impacted the field of drug design and delivery in general, and the utilization of the prodrug approach in particular. The increasing understanding of membrane transporters has promoted a novel 'targeted-prodrug' approach utilizing carrier-mediated transport to increase intestinal permeability, as well as specific enzymes to promote activation to the parent drug. This article provides the reader with a concise overview of this modern approach to prodrug design. Targeting the oligopeptide transporter PEPT1 for absorption and the serine hydrolase valacyclovirase for activation will be presented as examples for the successful utilization of this approach. Additionally, the use of computational approaches, such as DFT and ab initio molecular orbital methods, in modern prodrugs design will be discussed. Overall, in the coming years, more and more information will undoubtedly become available regarding intestinal transporters and potential enzymes that may be exploited for the targeted modern prodrug approach. Hence, the concept of prodrug design can no longer be viewed as merely a chemical modification to solve problems associated with parent compounds. Rather, it opens promising opportunities for precise and efficient drug delivery, as well as enhancement of treatment options and therapeutic efficacy.

A novel method for fabrication of continuous-relief optical elements

NASA Astrophysics Data System (ADS)

Guo, Xiaowei; Du, Jinglei; Chen, Mingyong; Ma, Yanqin; Zhu, Jianhua; Peng, Qinjun; Guo, Yongkang; Du, Chunlei

2005-08-01

A novel method for the fabrication of continuous micro-optical components is presented in this paper. It employs a computer controlled spatial-light-modulator (SLM) as a switchable projection mask and silver-halide sensitized gelatin (SHSG) as recording material. By etching SHSG with enzyme solution, the micro-optical components with relief modulation can be generated through special processing procedures. The principles of digital SLM-based lithography and enzyme etching SHSG are discussed in detail, and microlens arrays, micro axicon-lens arrays and gratings with good profile were achieved. This method is simple, cheap and the aberration in processing procedures can be in-situ corrected in the step of designing mask, so it is a practical method to fabricate continuous profile for low-volume production.

The Protein Cost of Metabolic Fluxes: Prediction from Enzymatic Rate Laws and Cost Minimization.

PubMed

Noor, Elad; Flamholz, Avi; Bar-Even, Arren; Davidi, Dan; Milo, Ron; Liebermeister, Wolfram

2016-11-01

Bacterial growth depends crucially on metabolic fluxes, which are limited by the cell's capacity to maintain metabolic enzymes. The necessary enzyme amount per unit flux is a major determinant of metabolic strategies both in evolution and bioengineering. It depends on enzyme parameters (such as kcat and KM constants), but also on metabolite concentrations. Moreover, similar amounts of different enzymes might incur different costs for the cell, depending on enzyme-specific properties such as protein size and half-life. Here, we developed enzyme cost minimization (ECM), a scalable method for computing enzyme amounts that support a given metabolic flux at a minimal protein cost. The complex interplay of enzyme and metabolite concentrations, e.g. through thermodynamic driving forces and enzyme saturation, would make it hard to solve this optimization problem directly. By treating enzyme cost as a function of metabolite levels, we formulated ECM as a numerically tractable, convex optimization problem. Its tiered approach allows for building models at different levels of detail, depending on the amount of available data. Validating our method with measured metabolite and protein levels in E. coli central metabolism, we found typical prediction fold errors of 4.1 and 2.6, respectively, for the two kinds of data. This result from the cost-optimized metabolic state is significantly better than randomly sampled metabolite profiles, supporting the hypothesis that enzyme cost is important for the fitness of E. coli. ECM can be used to predict enzyme levels and protein cost in natural and engineered pathways, and could be a valuable computational tool to assist metabolic engineering projects. Furthermore, it establishes a direct connection between protein cost and thermodynamics, and provides a physically plausible and computationally tractable way to include enzyme kinetics into constraint-based metabolic models, where kinetics have usually been ignored or oversimplified.

Toward Engineering Synthetic Microbial Metabolism

PubMed Central

McArthur, George H.; Fong, Stephen S.

2010-01-01

The generation of well-characterized parts and the formulation of biological design principles in synthetic biology are laying the foundation for more complex and advanced microbial metabolic engineering. Improvements in de novo DNA synthesis and codon-optimization alone are already contributing to the manufacturing of pathway enzymes with improved or novel function. Further development of analytical and computer-aided design tools should accelerate the forward engineering of precisely regulated synthetic pathways by providing a standard framework for the predictable design of biological systems from well-characterized parts. In this review we discuss the current state of synthetic biology within a four-stage framework (design, modeling, synthesis, analysis) and highlight areas requiring further advancement to facilitate true engineering of synthetic microbial metabolism. PMID:20037734

Application of computational methods for the design of BACE-1 inhibitors: validation of in silico modelling.

PubMed

Bajda, Marek; Jończyk, Jakub; Malawska, Barbara; Filipek, Sławomir

2014-03-24

β-Secretase (BACE-1) constitutes an important target for search of anti-Alzheimer's drugs. The first inhibitors of this enzyme were peptidic compounds with high molecular weight and low bioavailability. Therefore, the search for new efficient non-peptidic inhibitors has been undertaken by many scientific groups. We started our work from the development of in silico methodology for the design of novel BACE-1 ligands. It was validated on the basis of crystal structures of complexes with inhibitors, redocking, cross-docking and training/test sets of reference ligands. The presented procedure of assessment of the novel compounds as β-secretase inhibitors could be widely used in the design process.

A redox-mediated Kemp eliminase

NASA Astrophysics Data System (ADS)

Li, Aitao; Wang, Binju; Ilie, Adriana; Dubey, Kshatresh D.; Bange, Gert; Korendovych, Ivan V.; Shaik, Sason; Reetz, Manfred T.

2017-03-01

The acid/base-catalysed Kemp elimination of 5-nitro-benzisoxazole forming 2-cyano-4-nitrophenol has long served as a design platform of enzymes with non-natural reactions, providing new mechanistic insights in protein science. Here we describe an alternative concept based on redox catalysis by P450-BM3, leading to the same Kemp product via a fundamentally different mechanism. QM/MM computations show that it involves coordination of the substrate's N-atom to haem-Fe(II) with electron transfer and concomitant N-O heterolysis liberating an intermediate having a nitrogen radical moiety Fe(III)-N. and a phenoxyl anion. Product formation occurs by bond rotation and H-transfer. Two rationally chosen point mutations cause a notable increase in activity. The results shed light on the prevailing mechanistic uncertainties in human P450-catalysed metabolism of the immunomodulatory drug leflunomide, which likewise undergoes redox-mediated Kemp elimination by P450-BM3. Other isoxazole-based pharmaceuticals are probably also metabolized by a redox mechanism. Our work provides a basis for designing future artificial enzymes.

qPIPSA: Relating enzymatic kinetic parameters and interaction fields

PubMed Central

Gabdoulline, Razif R; Stein, Matthias; Wade, Rebecca C

2007-01-01

Background The simulation of metabolic networks in quantitative systems biology requires the assignment of enzymatic kinetic parameters. Experimentally determined values are often not available and therefore computational methods to estimate these parameters are needed. It is possible to use the three-dimensional structure of an enzyme to perform simulations of a reaction and derive kinetic parameters. However, this is computationally demanding and requires detailed knowledge of the enzyme mechanism. We have therefore sought to develop a general, simple and computationally efficient procedure to relate protein structural information to enzymatic kinetic parameters that allows consistency between the kinetic and structural information to be checked and estimation of kinetic constants for structurally and mechanistically similar enzymes. Results We describe qPIPSA: quantitative Protein Interaction Property Similarity Analysis. In this analysis, molecular interaction fields, for example, electrostatic potentials, are computed from the enzyme structures. Differences in molecular interaction fields between enzymes are then related to the ratios of their kinetic parameters. This procedure can be used to estimate unknown kinetic parameters when enzyme structural information is available and kinetic parameters have been measured for related enzymes or were obtained under different conditions. The detailed interaction of the enzyme with substrate or cofactors is not modeled and is assumed to be similar for all the proteins compared. The protein structure modeling protocol employed ensures that differences between models reflect genuine differences between the protein sequences, rather than random fluctuations in protein structure. Conclusion Provided that the experimental conditions and the protein structural models refer to the same protein state or conformation, correlations between interaction fields and kinetic parameters can be established for sets of related enzymes. Outliers may arise due to variation in the importance of different contributions to the kinetic parameters, such as protein stability and conformational changes. The qPIPSA approach can assist in the validation as well as estimation of kinetic parameters, and provide insights into enzyme mechanism. PMID:17919319

Methods for Creating and Animating a Computer Model Depicting the Structure and Function of the Sarcoplasmic Reticulum Calcium ATPase Enzyme.

ERIC Educational Resources Information Center

Chen, Alice Y.; McKee, Nancy

1999-01-01

Describes the developmental process used to visualize the calcium ATPase enzyme of the sarcoplasmic reticulum which involves evaluating scientific information, consulting scientists, model making, storyboarding, and creating and editing in a computer medium. (Author/CCM)

Evaluation of designed ligands by a multiple screening method: Application to glycogen phosphorylase inhibitors constructed with a variety of approaches

NASA Astrophysics Data System (ADS)

So, Sung-Sau; Karplus, Martin

2001-07-01

Glycogen phosphorylase (GP) is an important enzyme that regulates blood glucose level and a key therapeutic target for the treatment of type II diabetes. In this study, a number of potential GP inhibitors are designed with a variety of computational approaches. They include the applications of MCSS, LUDI and CoMFA to identify additional fragments that can be attached to existing lead molecules; the use of 2D and 3D similarity-based QSAR models (HQSAR and SMGNN) and of the LUDI program to identify novel molecules that may bind to the glucose binding site. The designed ligands are evaluated by a multiple screening method, which is a combination of commercial and in-house ligand-receptor binding affinity prediction programs used in a previous study (So and Karplus, J. Comp.-Aid. Mol. Des., 13 (1999), 243-258). Each method is used at an appropriate point in the screening, as determined by both the accuracy of the calculations and the computational cost. A comparison of the strengths and weaknesses of the ligand design approaches is made.

Engineering a hyper-catalytic enzyme by photo-activated conformation modulation

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

Agarwal, Pratul K

2012-01-01

Enzyme engineering for improved catalysis has wide implications. We describe a novel chemical modification of Candida antarctica lipase B that allows modulation of the enzyme conformation to promote catalysis. Computational modeling was used to identify dynamical enzyme regions that impact the catalytic mechanism. Surface loop regions located distal to active site but showing dynamical coupling to the reaction were connected by a chemical bridge between Lys136 and Pro192, containing a derivative of azobenzene. The conformational modulation of the enzyme was achieved using two sources of light that alternated the azobenzene moiety in cis and trans conformations. Computational model predicted thatmore » mechanical energy from the conformational fluctuations facilitate the reaction in the active-site. The results were consistent with predictions as the activity of the engineered enzyme was found to be enhanced with photoactivation. Preliminary estimations indicate that the engineered enzyme achieved 8-52 fold better catalytic activity than the unmodulated enzyme.« less

De novo design of a four-fold symmetric TIM-barrel protein with atomic-level accuracy

PubMed Central

Parmeggiani, Fabio; Velasco, D. Alejandro Fernandez; Höcker, Birte; Baker, David

2015-01-01

Despite efforts for over 25 years, de novo protein design has not succeeded in achieving the TIM-barrel fold. Here we describe the computational design of 4-fold symmetrical (β/α)8-barrels guided by geometrical and chemical principles. Experimental characterization of 33 designs revealed the importance of sidechain-backbone hydrogen bonding for defining the strand register between repeat units. The X-ray crystal structure of a designed thermostable 184-residue protein is nearly identical with the designed TIM-barrel model. PSI-BLAST searches do not identify sequence similarities to known TIM-barrel proteins, and sensitive profile-profile searches indicate that the design sequence is distant from other naturally occurring TIM-barrel superfamilies, suggesting that Nature has only sampled a subset of the sequence space available to the TIM-barrel fold. The ability to de novo design TIM-barrels opens new possibilities for custom-made enzymes. PMID:26595462

Enzyme reactor design under thermal inactivation.

PubMed

Illanes, Andrés; Wilson, Lorena

2003-01-01

Temperature is a very relevant variable for any bioprocess. Temperature optimization of bioreactor operation is a key aspect for process economics. This is especially true for enzyme-catalyzed processes, because enzymes are complex, unstable catalysts whose technological potential relies on their operational stability. Enzyme reactor design is presented with a special emphasis on the effect of thermal inactivation. Enzyme thermal inactivation is a very complex process from a mechanistic point of view. However, for the purpose of enzyme reactor design, it has been oversimplified frequently, considering one-stage first-order kinetics of inactivation and data gathered under nonreactive conditions that poorly represent the actual conditions within the reactor. More complex mechanisms are frequent, especially in the case of immobilized enzymes, and most important is the effect of catalytic modulators (substrates and products) on enzyme stability under operation conditions. This review focuses primarily on reactor design and operation under modulated thermal inactivation. It also presents a scheme for bioreactor temperature optimization, based on validated temperature-explicit functions for all the kinetic and inactivation parameters involved. More conventional enzyme reactor design is presented merely as a background for the purpose of highlighting the need for a deeper insight into enzyme inactivation for proper bioreactor design.

Computational active site analysis of molecular pathways to improve functional classification of enzymes.

PubMed

Ozyurt, A Sinem; Selby, Thomas L

2008-07-01

This study describes a method to computationally assess the function of homologous enzymes through small molecule binding interaction energy. Three experimentally determined X-ray structures and four enzyme models from ornithine cyclo-deaminase, alanine dehydrogenase, and mu-crystallin were used in combination with nine small molecules to derive a function score (FS) for each enzyme-model combination. While energy values varied for a single molecule-enzyme combination due to differences in the active sites, we observe that the binding energies for the entire pathway were proportional for each set of small molecules investigated. This proportionality of energies for a reaction pathway appears to be dependent on the amino acids in the active site and their direct interactions with the small molecules, which allows a function score (FS) to be calculated to assess the specificity of each enzyme. Potential of mean force (PMF) calculations were used to obtain the energies, and the resulting FS values demonstrate that a measurement of function may be obtained using differences between these PMF values. Additionally, limitations of this method are discussed based on: (a) larger substrates with significant conformational flexibility; (b) low homology enzymes; and (c) open active sites. This method should be useful in accurately predicting specificity for single enzymes that have multiple steps in their reactions and in high throughput computational methods to accurately annotate uncharacterized proteins based on active site interaction analysis. 2008 Wiley-Liss, Inc.

Ionizable side chains at catalytic active sites of enzymes.

PubMed

Jimenez-Morales, David; Liang, Jie; Eisenberg, Bob

2012-05-01

Catalytic active sites of enzymes of known structure can be well defined by a modern program of computational geometry. The CASTp program was used to define and measure the volume of the catalytic active sites of 573 enzymes in the Catalytic Site Atlas database. The active sites are identified as catalytic because the amino acids they contain are known to participate in the chemical reaction catalyzed by the enzyme. Acid and base side chains are reliable markers of catalytic active sites. The catalytic active sites have 4 acid and 5 base side chains, in an average volume of 1,072 Å(3). The number density of acid side chains is 8.3 M (in chemical units); the number density of basic side chains is 10.6 M. The catalytic active site of these enzymes is an unusual electrostatic and steric environment in which side chains and reactants are crowded together in a mixture more like an ionic liquid than an ideal infinitely dilute solution. The electrostatics and crowding of reactants and side chains seems likely to be important for catalytic function. In three types of analogous ion channels, simulation of crowded charges accounts for the main properties of selectivity measured in a wide range of solutions and concentrations. It seems wise to use mathematics designed to study interacting complex fluids when making models of the catalytic active sites of enzymes.

Ionizable Side Chains at Catalytic Active Sites of Enzymes

PubMed Central

Jimenez-Morales, David; Liang, Jie

2012-01-01

Catalytic active sites of enzymes of known structure can be well defined by a modern program of computational geometry. The CASTp program was used to define and measure the volume of the catalytic active sites of 573 enzymes in the Catalytic Site Atlas database. The active sites are identified as catalytic because the amino acids they contain are known to participate in the chemical reaction catalyzed by the enzyme. Acid and base side chains are reliable markers of catalytic active sites. The catalytic active sites have 4 acid and 5 base side chains, in an average volume of 1072 Å3. The number density of acid side chains is 8.3 M (in chemical units); the number density of basic side chains is 10.6 M. The catalytic active site of these enzymes is an unusual electrostatic and steric environment in which side chains and reactants are crowded together in a mixture more like an ionic liquid than an ideal infinitely dilute solution. The electrostatics and crowding of reactants and side chains seems likely to be important for catalytic function. In three types of analogous ion channels, simulation of crowded charges accounts for the main properties of selectivity measured in a wide range of solutions and concentrations. It seems wise to use mathematics designed to study interacting complex fluids when making models of the catalytic active sites of enzymes. PMID:22484856

In silico and in vitro inhibition of cytochrome P450 3A by synthetic stilbenoids.

PubMed

Basheer, Loai; Schultz, Keren; Guttman, Yelena; Kerem, Zohar

2017-12-15

Inhibition of cytochrome P450 3A4 (CYP3A4), the major drug metabolizing enzyme, by dietary compounds has recently attracted increased attention. Evaluating the potency of the many known inhibitory compounds is a tedious and time consuming task, yet it can be achieved using computing tools. Here, CDOCKER and Glide served to design model inhibitors in order to characterize molecular features of an inhibitor. Assessing nitro-stilbenoids, both approaches suggested nitrostilbene to be a weaker inhibitor of CYP3A4 than resveratrol, and stronger than dimethoxy-nitrostilbene. Nitrostilbene and resveratrol, but not dimethoxy-nitrostilbene, engage electrostatic interactions in the enzyme cavity, and with the haem. In vitro assessment of the inhibitory capacity supported the in silico predictions, suggesting that evaluating the electrostatic interactions of a compound with the prosthetic group allows the prediction of inhibitory potency. Since both programs yielded related results, it is suggested that for CYP3A4, computing tools may allow rapid identification of potent dietary inhibitors. Copyright © 2017 Elsevier Ltd. All rights reserved.

Microgravity

NASA Image and Video Library

2004-04-15

Ribbons is a program developed at UAB used worldwide to graphically depict complicated protein structures in a simplified format. The program uses sophisticated computer systems to understand the implications of protein structures. The Influenza virus remains a major causative agent for a large number of deaths among the elderly and young children and huge economic losses due to illness. Finding a cure will have a general impact both on the basic research of viral pathologists of fast evolving infectious agents and clinical treatment of influenza virus infection. The reproduction process of all strains of influenza are dependent on the same enzyme neuraminidase. Shown here is a segmented representation of the neuraminidase inhibitor compound sitting inside a cave-like contour of the neuraminidase enzyme surface. This cave-like formation present in every neuraminidase enzyme is the active site crucial to the flu's ability to infect. The space-grown crystals of neuraminidase have provided significant new details about the three-dimensional characteristics of this active site thus allowing researchers to design drugs that fit tighter into the site. Principal Investigator: Dr. Larry DeLucas

Enhancing the cellular anti-proliferation activity of pyridazinones as c-met inhibitors using docking analysis.

PubMed

Xing, Weiqiang; Ai, Jing; Jin, Shiyu; Shi, Zhangxing; Peng, Xia; Wang, Lang; Ji, Yinchun; Lu, Dong; Liu, Yang; Geng, Meiyu; Hu, Youhong

2015-05-05

A series of 2, 6-disubstituted pyridazinone derivatives were evaluated and optimized for their c-Met inhibitory activity in enzyme and cellular assay. An analysis of the SAR results arising from computer modeling analysis of members of the library led to the proposal that in order to obtain optimal inhibitory activity in cellular systems the lipophilic/hydrophilic properties of individual structural fragments in the inhibitors need to match those of corresponding binding pockets in the enzyme. Guided by this proposal, the quinoline-pyridazinone 8a, containing hydrophobic 6-indolyl pyridazinone and quinoline moieties along with a hydrophilic morpholine terminal group, was designed and synthesized. The results of studies with this substance showed that it is a selective c-Met inhibitor with both a high enzyme inhibition IC50 value of 4.2 nM and a high EBC-1 cell proliferation inhibition IC50 value of 17 nM. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Molecular dynamics explorations of active site structure in designed and evolved enzymes.

PubMed

Osuna, Sílvia; Jiménez-Osés, Gonzalo; Noey, Elizabeth L; Houk, K N

2015-04-21

This Account describes the use of molecular dynamics (MD) simulations to reveal how mutations alter the structure and organization of enzyme active sites. As proposed by Pauling about 70 years ago and elaborated by many others since then, biocatalysis is efficient when functional groups in the active site of an enzyme are in optimal positions for transition state stabilization. Changes in mechanism and covalent interactions are often critical parts of enzyme catalysis. We describe our explorations of the dynamical preorganization of active sites using MD, studying the fluctuations between active and inactive conformations normally concealed to static crystallography. MD shows how the various arrangements of active site residues influence the free energy of the transition state and relates the populations of the catalytic conformational ensemble to the enzyme activity. This Account is organized around three case studies from our laboratory. We first describe the importance of dynamics in evaluating a series of computationally designed and experimentally evolved enzymes for the Kemp elimination, a popular subject in the enzyme design field. We find that the dynamics of the active site is influenced not only by the original sequence design and subsequent mutations but also by the nature of the ligand present in the active site. In the second example, we show how microsecond MD has been used to uncover the role of remote mutations in the active site dynamics and catalysis of a transesterase, LovD. This enzyme was evolved by Tang at UCLA and Codexis, Inc., and is a useful commercial catalyst for the production of the drug simvastatin. X-ray analysis of inactive and active mutants did not reveal differences in the active sites, but relatively long time scale MD in solution showed that the active site of the wild-type enzyme preorganizes only upon binding of the acyl carrier protein (ACP) that delivers the natural acyl group to the active site. In the absence of bound ACP, a noncatalytic arrangement of the catalytic triad is dominant. Unnatural truncated substrates are inactive because of the lack of protein-protein interactions provided by the ACP. Directed evolution is able to gradually restore the catalytic organization of the active site by motion of the protein backbone that alters the active site geometry. In the third case, we demonstrate the key role of MD in combination with crystallography to identify the origins of substrate-dependent stereoselectivities in a number of Codexis-engineered ketoreductases, one of which is used commercially for the production of the antibiotic sulopenem. Here, mutations alter the shape of the active site as well as the accessibility of water to different regions of it. Each of these examples reveals something different about how mutations can influence enzyme activity and shows that directed evolution, like natural evolution, can increase catalytic activity in a variety of remarkable and often subtle ways.

Molecular determinants of enzyme cold adaptation: comparative structural and computational studies of cold- and warm-adapted enzymes.

PubMed

Papaleo, Elena; Tiberti, Matteo; Invernizzi, Gaetano; Pasi, Marco; Ranzani, Valeria

2011-11-01

The identification of molecular mechanisms underlying enzyme cold adaptation is a hot-topic both for fundamental research and industrial applications. In the present contribution, we review the last decades of structural computational investigations on cold-adapted enzymes in comparison to their warm-adapted counterparts. Comparative sequence and structural studies allow the definition of a multitude of adaptation strategies. Different enzymes carried out diverse mechanisms to adapt to low temperatures, so that a general theory for enzyme cold adaptation cannot be formulated. However, some common features can be traced in dynamic and flexibility properties of these enzymes, as well as in their intra- and inter-molecular interaction networks. Interestingly, the current data suggest that a family-centered point of view is necessary in the comparative analyses of cold- and warm-adapted enzymes. In fact, enzymes belonging to the same family or superfamily, thus sharing at least the three-dimensional fold and common features of the functional sites, have evolved similar structural and dynamic patterns to overcome the detrimental effects of low temperatures.

Enhanced Thermostability of Glucose Oxidase through Computer-Aided Molecular Design.

PubMed

Ning, Xiaoyan; Zhang, Yanli; Yuan, Tiantian; Li, Qingbin; Tian, Jian; Guan, Weishi; Liu, Bo; Zhang, Wei; Xu, Xinxin; Zhang, Yuhong

2018-01-31

Glucose oxidase (GOD, EC.1.1.3.4) specifically catalyzes the reaction of β-d-glucose to gluconic acid and hydrogen peroxide in the presence of oxygen, which has become widely used in the food industry, gluconic acid production and the feed industry. However, the poor thermostability of the current commercial GOD is a key limiting factor preventing its widespread application. In the present study, amino acids closely related to the thermostability of glucose oxidase from Penicillium notatum were predicted with a computer-aided molecular simulation analysis, and mutant libraries were established following a saturation mutagenesis strategy. Two mutants with significantly improved thermostabilities, S100A and D408W, were subsequently obtained. Their protein denaturing temperatures were enhanced by about 4.4 °C and 1.2 °C, respectively, compared with the wild-type enzyme. Treated at 55 °C for 3 h, the residual activities of the mutants were greater than 72%, while that of the wild-type enzyme was only 20%. The half-lives of S100A and D408W were 5.13- and 4.41-fold greater, respectively, than that of the wild-type enzyme at the same temperature. This work provides novel and efficient approaches for enhancing the thermostability of GOD by reducing the protein free unfolding energy or increasing the interaction of amino acids with the coenzyme.

Enhanced Thermostability of Glucose Oxidase through Computer-Aided Molecular Design

PubMed Central

Ning, Xiaoyan; Zhang, Yanli; Yuan, Tiantian; Li, Qingbin; Tian, Jian; Guan, Weishi; Liu, Bo; Zhang, Wei; Xu, Xinxin

2018-01-01

Glucose oxidase (GOD, EC.1.1.3.4) specifically catalyzes the reaction of β-d-glucose to gluconic acid and hydrogen peroxide in the presence of oxygen, which has become widely used in the food industry, gluconic acid production and the feed industry. However, the poor thermostability of the current commercial GOD is a key limiting factor preventing its widespread application. In the present study, amino acids closely related to the thermostability of glucose oxidase from Penicillium notatum were predicted with a computer-aided molecular simulation analysis, and mutant libraries were established following a saturation mutagenesis strategy. Two mutants with significantly improved thermostabilities, S100A and D408W, were subsequently obtained. Their protein denaturing temperatures were enhanced by about 4.4 °C and 1.2 °C, respectively, compared with the wild-type enzyme. Treated at 55 °C for 3 h, the residual activities of the mutants were greater than 72%, while that of the wild-type enzyme was only 20%. The half-lives of S100A and D408W were 5.13- and 4.41-fold greater, respectively, than that of the wild-type enzyme at the same temperature. This work provides novel and efficient approaches for enhancing the thermostability of GOD by reducing the protein free unfolding energy or increasing the interaction of amino acids with the coenzyme. PMID:29385094

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

Karp, Peter D.

Pathway Tools is a systems-biology software package written by SRI International (SRI) that produces Pathway/Genome Databases (PGDBs) for organisms with a sequenced genome. Pathway Tools also provides a wide range of capabilities for analyzing predicted metabolic networks and user-generated omics data. More than 5,000 academic, industrial, and government groups have licensed Pathway Tools. This user community includes researchers at all three DOE bioenergy centers, as well as academic and industrial metabolic engineering (ME) groups. An integral part of the Pathway Tools software is MetaCyc, a large, multiorganism database of metabolic pathways and enzymes that SRI and its academic collaborators manuallymore » curate. This project included two main goals: I. Enhance the MetaCyc content of bioenergy-related enzymes and pathways. II. Develop computational tools for engineering metabolic pathways that satisfy specified design goals, in particular for bioenergy-related pathways. In part I, SRI proposed to significantly expand the coverage of bioenergy-related metabolic information in MetaCyc, followed by the generation of organism-specific PGDBs for all energy-relevant organisms sequenced at the DOE Joint Genome Institute (JGI). Part I objectives included: 1: Expand the content of MetaCyc to include bioenergy-related enzymes and pathways. 2: Enhance the Pathway Tools software to enable display of complex polymer degradation processes. 3: Create new PGDBs for the energy-related organisms sequenced by JGI, update existing PGDBs with new MetaCyc content, and make these data available to JBEI via the BioCyc website. In part II, SRI proposed to develop an efficient computational tool for the engineering of metabolic pathways. Part II objectives included: 4: Develop computational tools for generating metabolic pathways that satisfy specified design goals, enabling users to specify parameters such as starting and ending compounds, and preferred or disallowed intermediate compounds. The pathways were to be generated using metabolic reactions from a reference database (DB). 5: Develop computational tools for ranking the pathways generated in objective (4) according to their optimality. The ranking criteria include stoichiometric yield, the number and cost of additional inputs and the cofactor compounds required by the pathway, pathway length, and pathway energetics. 6: Develop tools for visualizing generated pathways to facilitate the evaluation of a large space of generated pathways.« less

Designing Second Generation Anti-Alzheimer Compounds as Inhibitors of Human Acetylcholinesterase: Computational Screening of Synthetic Molecules and Dietary Phytochemicals

PubMed Central

Amat-ur-Rasool, Hafsa; Ahmed, Mehboob

2015-01-01

Alzheimer's disease (AD), a big cause of memory loss, is a progressive neurodegenerative disorder. The disease leads to irreversible loss of neurons that result in reduced level of acetylcholine neurotransmitter (ACh). The reduction of ACh level impairs brain functioning. One aspect of AD therapy is to maintain ACh level up to a safe limit, by blocking acetylcholinesterase (AChE), an enzyme that is naturally responsible for its degradation. This research presents an in-silico screening and designing of hAChE inhibitors as potential anti-Alzheimer drugs. Molecular docking results of the database retrieved (synthetic chemicals and dietary phytochemicals) and self-drawn ligands were compared with Food and Drug Administration (FDA) approved drugs against AD as controls. Furthermore, computational ADME studies were performed on the hits to assess their safety. Human AChE was found to be most approptiate target site as compared to commonly used Torpedo AChE. Among the tested dietry phytochemicals, berberastine, berberine, yohimbine, sanguinarine, elemol and naringenin are the worth mentioning phytochemicals as potential anti-Alzheimer drugs The synthetic leads were mostly dual binding site inhibitors with two binding subunits linked by a carbon chain i.e. second generation AD drugs. Fifteen new heterodimers were designed that were computationally more efficient inhibitors than previously reported compounds. Using computational methods, compounds present in online chemical databases can be screened to design more efficient and safer drugs against cognitive symptoms of AD. PMID:26325402

Designing Second Generation Anti-Alzheimer Compounds as Inhibitors of Human Acetylcholinesterase: Computational Screening of Synthetic Molecules and Dietary Phytochemicals.

PubMed

Amat-Ur-Rasool, Hafsa; Ahmed, Mehboob

2015-01-01

Alzheimer's disease (AD), a big cause of memory loss, is a progressive neurodegenerative disorder. The disease leads to irreversible loss of neurons that result in reduced level of acetylcholine neurotransmitter (ACh). The reduction of ACh level impairs brain functioning. One aspect of AD therapy is to maintain ACh level up to a safe limit, by blocking acetylcholinesterase (AChE), an enzyme that is naturally responsible for its degradation. This research presents an in-silico screening and designing of hAChE inhibitors as potential anti-Alzheimer drugs. Molecular docking results of the database retrieved (synthetic chemicals and dietary phytochemicals) and self-drawn ligands were compared with Food and Drug Administration (FDA) approved drugs against AD as controls. Furthermore, computational ADME studies were performed on the hits to assess their safety. Human AChE was found to be most approptiate target site as compared to commonly used Torpedo AChE. Among the tested dietry phytochemicals, berberastine, berberine, yohimbine, sanguinarine, elemol and naringenin are the worth mentioning phytochemicals as potential anti-Alzheimer drugs The synthetic leads were mostly dual binding site inhibitors with two binding subunits linked by a carbon chain i.e. second generation AD drugs. Fifteen new heterodimers were designed that were computationally more efficient inhibitors than previously reported compounds. Using computational methods, compounds present in online chemical databases can be screened to design more efficient and safer drugs against cognitive symptoms of AD.

The Protein Cost of Metabolic Fluxes: Prediction from Enzymatic Rate Laws and Cost Minimization

PubMed Central

Noor, Elad; Flamholz, Avi; Bar-Even, Arren; Davidi, Dan; Milo, Ron; Liebermeister, Wolfram

2016-01-01

Bacterial growth depends crucially on metabolic fluxes, which are limited by the cell’s capacity to maintain metabolic enzymes. The necessary enzyme amount per unit flux is a major determinant of metabolic strategies both in evolution and bioengineering. It depends on enzyme parameters (such as kcat and KM constants), but also on metabolite concentrations. Moreover, similar amounts of different enzymes might incur different costs for the cell, depending on enzyme-specific properties such as protein size and half-life. Here, we developed enzyme cost minimization (ECM), a scalable method for computing enzyme amounts that support a given metabolic flux at a minimal protein cost. The complex interplay of enzyme and metabolite concentrations, e.g. through thermodynamic driving forces and enzyme saturation, would make it hard to solve this optimization problem directly. By treating enzyme cost as a function of metabolite levels, we formulated ECM as a numerically tractable, convex optimization problem. Its tiered approach allows for building models at different levels of detail, depending on the amount of available data. Validating our method with measured metabolite and protein levels in E. coli central metabolism, we found typical prediction fold errors of 4.1 and 2.6, respectively, for the two kinds of data. This result from the cost-optimized metabolic state is significantly better than randomly sampled metabolite profiles, supporting the hypothesis that enzyme cost is important for the fitness of E. coli. ECM can be used to predict enzyme levels and protein cost in natural and engineered pathways, and could be a valuable computational tool to assist metabolic engineering projects. Furthermore, it establishes a direct connection between protein cost and thermodynamics, and provides a physically plausible and computationally tractable way to include enzyme kinetics into constraint-based metabolic models, where kinetics have usually been ignored or oversimplified. PMID:27812109

A Computational Methodology to Screen Activities of Enzyme Variants

PubMed Central

Hediger, Martin R.; De Vico, Luca; Svendsen, Allan; Besenmatter, Werner; Jensen, Jan H.

2012-01-01

We present a fast computational method to efficiently screen enzyme activity. In the presented method, the effect of mutations on the barrier height of an enzyme-catalysed reaction can be computed within 24 hours on roughly 10 processors. The methodology is based on the PM6 and MOZYME methods as implemented in MOPAC2009, and is tested on the first step of the amide hydrolysis reaction catalyzed by the Candida Antarctica lipase B (CalB) enzyme. The barrier heights are estimated using adiabatic mapping and shown to give barrier heights to within 3 kcal/mol of B3LYP/6-31G(d)//RHF/3-21G results for a small model system. Relatively strict convergence criteria (0.5 kcal/(molÅ)), long NDDO cutoff distances within the MOZYME method (15 Å) and single point evaluations using conventional PM6 are needed for reliable results. The generation of mutant structures and subsequent setup of the semiempirical calculations are automated so that the effect on barrier heights can be estimated for hundreds of mutants in a matter of weeks using high performance computing. PMID:23284627

Biosynthesis of Taxadiene in Saccharomyces cerevisiae : Selection of Geranylgeranyl Diphosphate Synthase Directed by a Computer-Aided Docking Strategy

PubMed Central

Li, Lin-feng; Zhai, Fang; Shang, Lu-qing; Yin, Zheng; Yuan, Ying-jin

2014-01-01

Identification of efficient key enzymes in biosynthesis pathway and optimization of the fitness between functional modules and chassis are important for improving the production of target compounds. In this study, the taxadiene biosynthesis pathway was firstly constructed in yeast by transforming ts gene and overexpressing erg20 and thmgr. Then, the catalytic capabilities of six different geranylgeranyl diphosphate synthases (GGPPS), the key enzyme in mevalonic acid (MVA) pathway catalyzing famesyl diphosphate (FPP) to geranylgeranyl diphosphate (GGPP), were predicted using enzyme-substrate docking strategy. GGPPSs from Taxus baccata x Taxus cuspidate (GGPPSbc), Erwinia herbicola (GGPPSeh), and S. cerevisiae (GGPPSsc) which ranked 1st, 4th and 6th in docking with FPP were selected for construction. The experimental results were consistent with the computer prediction that the engineered yeast with GGPPSbc exhibited the highest production. In addition, two chassis YSG50 and W303-1A were chosen, and the titer of taxadiene reached 72.8 mg/L in chassis YSG50 with GGPPSbc. Metabolomic study revealed that the contents of tricarboxylic acid cycle (TCA) intermediates and their precursor amino acids in chassis YSG50 was lower than those in W303-1A, indicating less carbon flux was divided into TCA cycle. Furthermore, the levels of TCA intermediates in the taxadiene producing yeasts were lower than those in chassis YSG50. Thus, it may result in more carbon flux in MVA pathway in chassis YSG50, which suggested that YSG50 was more suitable for engineering the taxadiene producing yeast. These results indicated that computer-aided protein modeling directed isoenzyme selection strategy and metabolomic study could guide the rational design of terpenes biosynthetic cells. PMID:25295588

Computational Enzymology and Organophosphorus Degrading Enzymes: Promising Approaches Toward Remediation Technologies of Warfare Agents and Pesticides.

PubMed

Ramalho, Teodorico C; de Castro, Alexandre A; Silva, Daniela R; Silva, Maria Cristina; Franca, Tanos C C; Bennion, Brian J; Kuca, Kamil

2016-01-01

The re-emergence of chemical weapons as a global threat in hands of terrorist groups, together with an increasing number of pesticides intoxications and environmental contaminations worldwide, has called the attention of the scientific community for the need of improvement in the technologies for detoxification of organophosphorus (OP) compounds. A compelling strategy is the use of bioremediation by enzymes that are able to hydrolyze these molecules to harmless chemical species. Several enzymes have been studied and engineered for this purpose. However, their mechanisms of action are not well understood. Theoretical investigations may help elucidate important aspects of these mechanisms and help in the development of more efficient bio-remediators. In this review, we point out the major contributions of computational methodologies applied to enzyme based detoxification of OPs. Furthermore, we highlight the use of PTE, PON, DFP, and BuChE as enzymes used in OP detoxification process and how computational tools such as molecular docking, molecular dynamics simulations and combined quantum mechanical/molecular mechanics have and will continue to contribute to this very important area of research.

Subsite mapping of enzymes. Application of the depolymerase computer model to two alpha-amylases.

PubMed Central

Allen, J D; Thoma, J A

1976-01-01

In the preceding paper (Allen and Thoma, 1976) we developed a depolymerase computer model, which uses a minimization routine to establish a subsite map for a depolymerase. In the present paper we show how the model is applied to experimental data for two alpha-amylases. Michaelis parameters and bond-cleavage frequencies for substrates of chain lengths up to twelve glucosyl units have been reported for Bacillus amyloliquefaciens, and a subsite map has been proposed for this enzyme [Thoma et al. (1971) J. Biol. Chem. 246, 5621-5635]. By applying the computer model to the experimental data, we have arrived at a ten-subsite map. We find that a significant improvement in this map is achieved by allowing the hydrolytic rate coefficient to vary as a function of the number of occupied subsites comprising the enzyme-binding region. The bond-cleavage frequencies, the enzyme is found to have eight subsites. A partial subsite map is arrived at, but the entire binding region cannot be mapped because Michaelis parameters are complicated by transglycosylation reactions. The hydrolytic rate coefficients for this enzyme are not constant. PMID:999630

Gliptins in managing diabetes - Reviewing computational strategy.

PubMed

Sneha, P; Doss, C George Priya

2016-12-01

The pace of anti-diabetic drug discovery is very slow in spite of increasing rate of prevalence of Type 2 Diabetes which remains a major public health concern. Though extensive research steps are taken in the past decade, yet craves for better new treatment strategies to overcome the current scenario. One such general finding is the evolution of gliptins which discriminately inhibits DPP4 (Dipeptidyl peptidase-4) enzyme. Although the mechanism of action of gliptin is highly target oriented and accurate, still its long-term use stands unknown. This step calls for a fast, flexible, and cost-effective strategies to meet the demands of producing arrays of high-content lead compounds with improved efficiency for better clinical success. The present review highlights the available gliptins in the market and also other naturally occurring DPP4 enzyme inhibitors. Along with describing the known inhibitors and their origin in this review, we attempted to identify a probable new lead compounds using advanced computational techniques. In this context, computational methods that integrate the knowledge of proteins and drug responses were utilized in prioritizing targets and designing drugs towards clinical trials with better efficacy. The compounds obtained as a result of virtual screening were compared with the commercially available gliptin in the market to have better efficiency in the identification and validation of the potential DPP4 inhibitors. The combinatorial computational methods used in the present study identified Compound 1: 25022354 as promising inhibitor. Copyright © 2016 Elsevier Inc. All rights reserved.

Perspectives on electrostatics and conformational motions in enzyme catalysis.

PubMed

Hanoian, Philip; Liu, C Tony; Hammes-Schiffer, Sharon; Benkovic, Stephen

2015-02-17

CONSPECTUS: Enzymes are essential for all living organisms, and their effectiveness as chemical catalysts has driven more than a half century of research seeking to understand the enormous rate enhancements they provide. Nevertheless, a complete understanding of the factors that govern the rate enhancements and selectivities of enzymes remains elusive, due to the extraordinary complexity and cooperativity that are the hallmarks of these biomolecules. We have used a combination of site-directed mutagenesis, pre-steady-state kinetics, X-ray crystallography, nuclear magnetic resonance (NMR), vibrational and fluorescence spectroscopies, resonance energy transfer, and computer simulations to study the implications of conformational motions and electrostatic interactions on enzyme catalysis in the enzyme dihydrofolate reductase (DHFR). We have demonstrated that modest equilibrium conformational changes are functionally related to the hydride transfer reaction. Results obtained for mutant DHFRs illustrated that reductions in hydride transfer rates are correlated with altered conformational motions, and analysis of the evolutionary history of DHFR indicated that mutations appear to have occurred to preserve both the hydride transfer rate and the associated conformational changes. More recent results suggested that differences in local electrostatic environments contribute to finely tuning the substrate pKa in the initial protonation step. Using a combination of primary and solvent kinetic isotope effects, we demonstrated that the reaction mechanism is consistent across a broad pH range, and computer simulations suggested that deprotonation of the active site Tyr100 may play a crucial role in substrate protonation at high pH. Site-specific incorporation of vibrational thiocyanate probes into the ecDHFR active site provided an experimental tool for interrogating these microenvironments and for investigating changes in electrostatics along the DHFR catalytic cycle. Complementary molecular dynamics simulations in conjunction with mixed quantum mechanical/molecular mechanical calculations accurately reproduced the vibrational frequency shifts in these probes and provided atomic-level insight into the residues influencing these changes. Our findings indicate that conformational and electrostatic changes are intimately related and functionally essential. This approach can be readily extended to the study of other enzyme systems to identify more general trends in the relationship between conformational fluctuations and electrostatic interactions. These results are relevant to researchers seeking to design novel enzymes as well as those seeking to develop therapeutic agents that function as enzyme inhibitors.

Perspectives on Electrostatics and Conformational Motions in Enzyme Catalysis

PubMed Central

2016-01-01

Conspectus Enzymes are essential for all living organisms, and their effectiveness as chemical catalysts has driven more than a half century of research seeking to understand the enormous rate enhancements they provide. Nevertheless, a complete understanding of the factors that govern the rate enhancements and selectivities of enzymes remains elusive, due to the extraordinary complexity and cooperativity that are the hallmarks of these biomolecules. We have used a combination of site-directed mutagenesis, pre-steady-state kinetics, X-ray crystallography, nuclear magnetic resonance (NMR), vibrational and fluorescence spectroscopies, resonance energy transfer, and computer simulations to study the implications of conformational motions and electrostatic interactions on enzyme catalysis in the enzyme dihydrofolate reductase (DHFR). We have demonstrated that modest equilibrium conformational changes are functionally related to the hydride transfer reaction. Results obtained for mutant DHFRs illustrated that reductions in hydride transfer rates are correlated with altered conformational motions, and analysis of the evolutionary history of DHFR indicated that mutations appear to have occurred to preserve both the hydride transfer rate and the associated conformational changes. More recent results suggested that differences in local electrostatic environments contribute to finely tuning the substrate pKa in the initial protonation step. Using a combination of primary and solvent kinetic isotope effects, we demonstrated that the reaction mechanism is consistent across a broad pH range, and computer simulations suggested that deprotonation of the active site Tyr100 may play a crucial role in substrate protonation at high pH. Site-specific incorporation of vibrational thiocyanate probes into the ecDHFR active site provided an experimental tool for interrogating these microenvironments and for investigating changes in electrostatics along the DHFR catalytic cycle. Complementary molecular dynamics simulations in conjunction with mixed quantum mechanical/molecular mechanical calculations accurately reproduced the vibrational frequency shifts in these probes and provided atomic-level insight into the residues influencing these changes. Our findings indicate that conformational and electrostatic changes are intimately related and functionally essential. This approach can be readily extended to the study of other enzyme systems to identify more general trends in the relationship between conformational fluctuations and electrostatic interactions. These results are relevant to researchers seeking to design novel enzymes as well as those seeking to develop therapeutic agents that function as enzyme inhibitors. PMID:25565178

Simulation of an enzyme-based glucose sensor

NASA Astrophysics Data System (ADS)

Sha, Xianzheng; Jablecki, Michael; Gough, David A.

2001-09-01

An important biosensor application is the continuous monitoring blood or tissue fluid glucose concentration in people with diabetes. Our research focuses on the development of a glucose sensor based on potentiostatic oxygen electrodes and immobilized glucose oxidase for long- term application as an implant in tissues. As the sensor signal depends on many design variables, a trial-and-error approach to sensor optimization can be time-consuming. Here, the properties of an implantable glucose sensor are optimized by a systematic computational simulation approach.

Computational Redesign of Acyl-ACP Thioesterase with Improved Selectivity toward Medium-Chain-Length Fatty Acids

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

Grisewood, Matthew J.; Hernández-Lozada, Néstor J.; Thoden, James B.

Enzyme and metabolic engineering offer the potential to develop biocatalysts for converting natural resources to a wide range of chemicals. To broaden the scope of potential products beyond natural metabolites, methods of engineering enzymes to accept alternative substrates and/or perform novel chemistries must be developed. DNA synthesis can create large libraries of enzyme-coding sequences, but most biochemistries lack a simple assay to screen for promising enzyme variants. Our solution to this challenge is structure-guided mutagenesis, in which optimization algorithms select the best sequences from libraries based on specified criteria (i.e., binding selectivity). We demonstrate this approach by identifying medium-chain (C8–C12)more » acyl-ACP thioesterases through structure-guided mutagenesis. Medium-chain fatty acids, which are products of thioesterase-catalyzed hydrolysis, are limited in natural abundance, compared to long-chain fatty acids; the limited supply leads to high costs of C6–C10 oleochemicals such as fatty alcohols, amines, and esters. Here, we applied computational tools to tune substrate binding of the highly active ‘TesA thioesterase in Escherichia coli. We used the IPRO algorithm to design thioesterase variants with enhanced C12 or C8 specificity, while maintaining high activity. After four rounds of structure-guided mutagenesis, we identified 3 variants with enhanced production of dodecanoic acid (C12) and 27 variants with enhanced production of octanoic acid (C8). The top variants reached up to 49% C12 and 50% C8 while exceeding native levels of total free fatty acids. A comparably sized library created by random mutagenesis failed to identify promising mutants. The chain length-preference of ‘TesA and the best mutant were confirmed in vitro using acyl-CoA substrates. Molecular dynamics simulations, confirmed by resolved crystal structures, of ‘TesA variants suggest that hydrophobic forces govern ‘TesA substrate specificity. Finally, we expect the design rules that we uncovered and the thioesterase variants that we identified will be useful to metabolic engineering projects aimed at sustainable production of medium-chain-length oleochemicals.« less

Computational Redesign of Acyl-ACP Thioesterase with Improved Selectivity toward Medium-Chain-Length Fatty Acids

DOE PAGES

Grisewood, Matthew J.; Hernández-Lozada, Néstor J.; Thoden, James B.; ...

2017-04-20

Enzyme and metabolic engineering offer the potential to develop biocatalysts for converting natural resources to a wide range of chemicals. To broaden the scope of potential products beyond natural metabolites, methods of engineering enzymes to accept alternative substrates and/or perform novel chemistries must be developed. DNA synthesis can create large libraries of enzyme-coding sequences, but most biochemistries lack a simple assay to screen for promising enzyme variants. Our solution to this challenge is structure-guided mutagenesis, in which optimization algorithms select the best sequences from libraries based on specified criteria (i.e., binding selectivity). We demonstrate this approach by identifying medium-chain (C8–C12)more » acyl-ACP thioesterases through structure-guided mutagenesis. Medium-chain fatty acids, which are products of thioesterase-catalyzed hydrolysis, are limited in natural abundance, compared to long-chain fatty acids; the limited supply leads to high costs of C6–C10 oleochemicals such as fatty alcohols, amines, and esters. Here, we applied computational tools to tune substrate binding of the highly active ‘TesA thioesterase in Escherichia coli. We used the IPRO algorithm to design thioesterase variants with enhanced C12 or C8 specificity, while maintaining high activity. After four rounds of structure-guided mutagenesis, we identified 3 variants with enhanced production of dodecanoic acid (C12) and 27 variants with enhanced production of octanoic acid (C8). The top variants reached up to 49% C12 and 50% C8 while exceeding native levels of total free fatty acids. A comparably sized library created by random mutagenesis failed to identify promising mutants. The chain length-preference of ‘TesA and the best mutant were confirmed in vitro using acyl-CoA substrates. Molecular dynamics simulations, confirmed by resolved crystal structures, of ‘TesA variants suggest that hydrophobic forces govern ‘TesA substrate specificity. Finally, we expect the design rules that we uncovered and the thioesterase variants that we identified will be useful to metabolic engineering projects aimed at sustainable production of medium-chain-length oleochemicals.« less

Ensemble Generation and the Influence of Protein Flexibility on Geometric Tunnel Prediction in Cytochrome P450 Enzymes

PubMed Central

Kingsley, Laura J.; Lill, Markus A.

2014-01-01

Computational prediction of ligand entry and egress paths in proteins has become an emerging topic in computational biology and has proven useful in fields such as protein engineering and drug design. Geometric tunnel prediction programs, such as Caver3.0 and MolAxis, are computationally efficient methods to identify potential ligand entry and egress routes in proteins. Although many geometric tunnel programs are designed to accommodate a single input structure, the increasingly recognized importance of protein flexibility in tunnel formation and behavior has led to the more widespread use of protein ensembles in tunnel prediction. However, there has not yet been an attempt to directly investigate the influence of ensemble size and composition on geometric tunnel prediction. In this study, we compared tunnels found in a single crystal structure to ensembles of various sizes generated using different methods on both the apo and holo forms of cytochrome P450 enzymes CYP119, CYP2C9, and CYP3A4. Several protein structure clustering methods were tested in an attempt to generate smaller ensembles that were capable of reproducing the data from larger ensembles. Ultimately, we found that by including members from both the apo and holo data sets, we could produce ensembles containing less than 15 members that were comparable to apo or holo ensembles containing over 100 members. Furthermore, we found that, in the absence of either apo or holo crystal structure data, pseudo-apo or –holo ensembles (e.g. adding ligand to apo protein throughout MD simulations) could be used to resemble the structural ensembles of the corresponding apo and holo ensembles, respectively. Our findings not only further highlight the importance of including protein flexibility in geometric tunnel prediction, but also suggest that smaller ensembles can be as capable as larger ensembles at capturing many of the protein motions important for tunnel prediction at a lower computational cost. PMID:24956479

Computational optimization of AG18051 inhibitor for amyloid-beta binding alcohol dehydrogenase enzyme

NASA Astrophysics Data System (ADS)

Marques, Alexandra T.; Antunes, Agostinho; Fernandes, Pedro A.; Ramos, Maria J.

Amyloid-beta (Abeta) binding alcohol dehydrogenase (ABAD) is a multifunctional enzyme involved in maintaining the homeostasis. The enzyme can also mediate some diseases, including genetic diseases, Alzheimer's disease, and possibly some prostate cancers. Potent inhibitors of ABAD might facilitate a better clarification of the functions of the enzyme under normal and pathogenic conditions and might also be used for therapeutic intervention in disease conditions mediated by the enzyme. The AG18051 is the only presently available inhibitor of ABAD. It binds in the active-site cavity of the enzyme and reacts with the NAD+ cofactor to form a covalent adduct. In this work, we use computational methods to perform a rational optimization of the AG18051 inhibitor, through the introduction of chemical substitutions directed to improve the affinity of the inhibitor to the enzyme. The molecular mechanics-Poisson-Boltzmann surface area methodology was used to predict the relative free binding energy of the different modified inhibitor-NAD-enzyme complexes. We show that it is possible to increase significantly the affinity of the inhibitor to the enzyme with small modifications, without changing the overall structure and ADME (absorption, distribution, metabolism, and excretion) properties of the original inhibitor.

Computational Enzymology and Organophosphorus Degrading Enzymes: Promising Approaches Toward Remediation Technologies of Warfare Agents and Pesticides

DOE PAGES

Ramalho, Teodorico C.; DeCastro, Alexandre A.; Silva, Daniela R.; ...

2015-08-26

The re-emergence of chemical weapons as a global threat in hands of terrorist groups, together with an increasing number of pesticides intoxications and environmental contaminations worldwide, has called the attention of the scientific community for the need of improvement in the technologies for detoxification of organophosphorus (OP) compounds. A compelling strategy is the use of bioremediation by enzymes that are able to hydrolyze these molecules to harmless chemical species. Several enzymes have been studied and engineered for this purpose. However, their mechanisms of action are not well understood. Theoretical investigations may help elucidate important aspects of these mechanisms and helpmore » in the development of more efficient bio-remediators. In this review, we point out the major contributions of computational methodologies applied to enzyme based detoxification of OPs. Furthermore, we highlight the use of PTE, PON, DFP, and BuChE as enzymes used in OP detoxification process and how computational tools such as molecular docking, molecular dynamics simulations and combined quantum mechanical/molecular mechanics have and will continue to contribute to this very important area of research.The re-emergence of chemical weapons as a global threat in hands of terrorist groups, together with an increasing number of pesticides intoxications and environmental contaminations worldwide, has called the attention of the scientific community for the need of improvement in the technologies for detoxification of organophosphorus (OP) compounds. A compelling strategy is the use of bioremediation by enzymes that are able to hydrolyze these molecules to harmless chemical species. Several enzymes have been studied and engineered for this purpose. However, their mechanisms of action are not well understood. Theoretical investigations may help elucidate important aspects of these mechanisms and help in the development of more efficient bio-remediators. In this review, we point out the major contributions of computational methodologies applied to enzyme based detoxification of OPs. Furthermore, we highlight the use of PTE, PON, DFP, and BuChE as enzymes used in OP detoxification process and how computational tools such as molecular docking, molecular dynamics simulations and combined quantum mechanical/molecular mechanics have and will continue to contribute to this very important area of research.« less

Computational Enzymology and Organophosphorus Degrading Enzymes: Promising Approaches Toward Remediation Technologies of Warfare Agents and Pesticides

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

Ramalho, Teodorico C.; DeCastro, Alexandre A.; Silva, Daniela R.

The re-emergence of chemical weapons as a global threat in hands of terrorist groups, together with an increasing number of pesticides intoxications and environmental contaminations worldwide, has called the attention of the scientific community for the need of improvement in the technologies for detoxification of organophosphorus (OP) compounds. A compelling strategy is the use of bioremediation by enzymes that are able to hydrolyze these molecules to harmless chemical species. Several enzymes have been studied and engineered for this purpose. However, their mechanisms of action are not well understood. Theoretical investigations may help elucidate important aspects of these mechanisms and helpmore » in the development of more efficient bio-remediators. In this review, we point out the major contributions of computational methodologies applied to enzyme based detoxification of OPs. Furthermore, we highlight the use of PTE, PON, DFP, and BuChE as enzymes used in OP detoxification process and how computational tools such as molecular docking, molecular dynamics simulations and combined quantum mechanical/molecular mechanics have and will continue to contribute to this very important area of research.The re-emergence of chemical weapons as a global threat in hands of terrorist groups, together with an increasing number of pesticides intoxications and environmental contaminations worldwide, has called the attention of the scientific community for the need of improvement in the technologies for detoxification of organophosphorus (OP) compounds. A compelling strategy is the use of bioremediation by enzymes that are able to hydrolyze these molecules to harmless chemical species. Several enzymes have been studied and engineered for this purpose. However, their mechanisms of action are not well understood. Theoretical investigations may help elucidate important aspects of these mechanisms and help in the development of more efficient bio-remediators. In this review, we point out the major contributions of computational methodologies applied to enzyme based detoxification of OPs. Furthermore, we highlight the use of PTE, PON, DFP, and BuChE as enzymes used in OP detoxification process and how computational tools such as molecular docking, molecular dynamics simulations and combined quantum mechanical/molecular mechanics have and will continue to contribute to this very important area of research.« less

KINEXP: Computer Simulation in Enzyme Kinetics.

ERIC Educational Resources Information Center

Gelpi, Josep Lluis; Domenech, Carlos

1988-01-01

Describes a program which allows students to identify and characterize several kinetic inhibitory mechanisms. Uses the generic model of reversible inhibition of a monosubstrate enzyme but can be easily modified to run other models such as bisubstrate enzymes. Uses MS-DOS BASIC. (MVL)

Coupling Protein Side-Chain and Backbone Flexibility Improves the Re-design of Protein-Ligand Specificity.

PubMed

Ollikainen, Noah; de Jong, René M; Kortemme, Tanja

2015-01-01

Interactions between small molecules and proteins play critical roles in regulating and facilitating diverse biological functions, yet our ability to accurately re-engineer the specificity of these interactions using computational approaches has been limited. One main difficulty, in addition to inaccuracies in energy functions, is the exquisite sensitivity of protein-ligand interactions to subtle conformational changes, coupled with the computational problem of sampling the large conformational search space of degrees of freedom of ligands, amino acid side chains, and the protein backbone. Here, we describe two benchmarks for evaluating the accuracy of computational approaches for re-engineering protein-ligand interactions: (i) prediction of enzyme specificity altering mutations and (ii) prediction of sequence tolerance in ligand binding sites. After finding that current state-of-the-art "fixed backbone" design methods perform poorly on these tests, we develop a new "coupled moves" design method in the program Rosetta that couples changes to protein sequence with alterations in both protein side-chain and protein backbone conformations, and allows for changes in ligand rigid-body and torsion degrees of freedom. We show significantly increased accuracy in both predicting ligand specificity altering mutations and binding site sequences. These methodological improvements should be useful for many applications of protein-ligand design. The approach also provides insights into the role of subtle conformational adjustments that enable functional changes not only in engineering applications but also in natural protein evolution.

A gas-liquid system for enzyme kinetic studies of volatile organic chemicals. Determination of enzyme kinetic constants and partition coefficients of trichloroethylene.

PubMed

Hwang, I Y; Reardon, K F; Tessari, J D; Yang, R S

1996-04-01

A gas-liquid system was developed for enzyme kinetic study with volatile organic chemicals (VOCs) by modification of the gas uptake method for the in vivo physiologically based pharmacokinetic experiment. This gas-liquid system, designed in our laboratory, is composed of: 1) a diffusion chamber for adjusting initial vapor concentration by mixing ambient air and the VOCs; 2) a condenser for maintaining the liquid level in the incubation chamber; 3) a stainless-steel metal bellows pump for recirculating vapor in this system; 4) a gas chromatograph equipped with an autosampler and a flame ionization detector; and 5) a computer for controlling automation and data processing. Trichloroethylene (TCE) was used as a model chemical, and enzyme kinetics were studied by measuring the depletion of TCE in the gas phase of the system. TCE-at initial concentrations of 56, 620, and 1240 ppm-was incubated with rat liver microsomes and a NADPH regenerating system in a 100-ml round-bottom flask. Based on parallel enzyme assays using p-nitrophenol as a substrate, cytochrome P450IIE1, activity remained stable up to 3 hr under the incubation conditions (37 degrees C and pH 7.4) whereas addition of glutathione into the incubation mixture did not affect TCE metabolism. Kinetic constants were analyzed using a two-compartment pharmacokinetic model and the computer software SimuSolv. Statistical optimization using the maximum-likelihood method produced apparent in vitro Vmax and KM values of 0.55 nmol/mg protein/min and 0.9 microM, respectively. In addition, this newly developed methodology has a number of advantages over those reported in the literature, including the potential utility of determining tissue partition coefficients of VOCs for physiologically based pharmacokinetic modeling. We conclude that this gas-liquid system is suitable for determination of kinetic constants near realistic environmental concentrations of VOCs including TCE.

A complete thermodynamic analysis of enzyme turnover links the free energy landscape to enzyme catalysis.

PubMed

Jones, Hannah B L; Wells, Stephen A; Prentice, Erica J; Kwok, Anthony; Liang, Liyin L; Arcus, Vickery L; Pudney, Christopher R

2017-09-01

Our understanding of how enzymes work is coloured by static structure depictions where the enzyme scaffold is presented as either immobile, or in equilibrium between well-defined static conformations. Proteins, however, exhibit a large degree of motion over a broad range of timescales and magnitudes and this is defined thermodynamically by the enzyme free energy landscape (FEL). The role and importance of enzyme motion is extremely contentious. Much of the challenge is in the experimental detection of so called 'conformational sampling' involved in enzyme turnover. Herein we apply combined pressure and temperature kinetics studies to elucidate the full suite of thermodynamic parameters defining an enzyme FEL as it relates to enzyme turnover. We find that the key thermodynamic parameters governing vibrational modes related to enzyme turnover are the isobaric expansivity term and the change in heat capacity for enzyme catalysis. Variation in the enzyme FEL affects these terms. Our analysis is supported by a range of biophysical and computational approaches that specifically capture information on protein vibrational modes and the FEL (all atom flexibility calculations, red edge excitation shift spectroscopy and viscosity studies) that provide independent evidence for our findings. Our data suggest that restricting the enzyme FEL may be a powerful strategy when attempting to rationally engineer enzymes, particularly to alter thermal activity. Moreover, we demonstrate how rational predictions can be made with a rapid computational approach. © 2017 Federation of European Biochemical Societies.

Nuclear quantum effects and kinetic isotope effects in enzyme reactions.

PubMed

Vardi-Kilshtain, Alexandra; Nitoker, Neta; Major, Dan Thomas

2015-09-15

Enzymes are extraordinarily effective catalysts evolved to perform well-defined and highly specific chemical transformations. Studying the nature of rate enhancements and the mechanistic strategies in enzymes is very important, both from a basic scientific point of view, as well as in order to improve rational design of biomimetics. Kinetic isotope effect (KIE) is a very important tool in the study of chemical reactions and has been used extensively in the field of enzymology. Theoretically, the prediction of KIEs in condensed phase environments such as enzymes is challenging due to the need to include nuclear quantum effects (NQEs). Herein we describe recent progress in our group in the development of multi-scale simulation methods for the calculation of NQEs and accurate computation of KIEs. We also describe their application to several enzyme systems. In particular we describe the use of combined quantum mechanics/molecular mechanics (QM/MM) methods in classical and quantum simulations. The development of various novel path-integral methods is reviewed. These methods are tailor suited to enzyme systems, where only a few degrees of freedom involved in the chemistry need to be quantized. The application of the hybrid QM/MM quantum-classical simulation approach to three case studies is presented. The first case involves the proton transfer in alanine racemase. The second case presented involves orotidine 5'-monophosphate decarboxylase where multidimensional free energy simulations together with kinetic isotope effects are combined in the study of the reaction mechanism. Finally, we discuss the proton transfer in nitroalkane oxidase, where the enzyme employs tunneling as a catalytic fine-tuning tool. Copyright © 2015 Elsevier Inc. All rights reserved.

Optimisation of synergistic biomass-degrading enzyme systems for efficient rice straw hydrolysis using an experimental mixture design.

PubMed

Suwannarangsee, Surisa; Bunterngsook, Benjarat; Arnthong, Jantima; Paemanee, Atchara; Thamchaipenet, Arinthip; Eurwilaichitr, Lily; Laosiripojana, Navadol; Champreda, Verawat

2012-09-01

Synergistic enzyme system for the hydrolysis of alkali-pretreated rice straw was optimised based on the synergy of crude fungal enzyme extracts with a commercial cellulase (Celluclast™). Among 13 enzyme extracts, the enzyme preparation from Aspergillus aculeatus BCC 199 exhibited the highest level of synergy with Celluclast™. This synergy was based on the complementary cellulolytic and hemicellulolytic activities of the BCC 199 enzyme extract. A mixture design was used to optimise the ternary enzyme complex based on the synergistic enzyme mixture with Bacillus subtilis expansin. Using the full cubic model, the optimal formulation of the enzyme mixture was predicted to the percentage of Celluclast™: BCC 199: expansin=41.4:37.0:21.6, which produced 769 mg reducing sugar/g biomass using 2.82 FPU/g enzymes. This work demonstrated the use of a systematic approach for the design and optimisation of a synergistic enzyme mixture of fungal enzymes and expansin for lignocellulosic degradation. Copyright © 2012 Elsevier Ltd. All rights reserved.

Homology modeling, molecular docking and electrostatic potential analysis of MurF ligase from Klebsiella pneumonia

PubMed Central

Sivaramakrishnan, Venkatabalasubramanian; Thiyagarajan, Chinnaiyan; Kalaivanan, Sivakumaran; Selvakumar, Raj; Anusuyadevi, Muthuswamy; Jayachandran, Kesavan Swaminathan

2012-01-01

In spite of availability of moderately protective vaccine and antibiotics, new antibacterial agents are urgently needed to decrease the global incidence of Klebsiella pneumonia infections. MurF ligase, a key enzyme, which participates in the bacterial cell wall assembly, is indispensable to existence of K. pneumonia. MurF ligase lack mammalian vis-à-vis and have high specificity, uniqueness, and occurrence only in eubacteria, epitomizing them as promising therapeutic targets for intervention. In this study, we present a unified approach involving homology modeling and molecular docking studies on MurF ligase enzyme. As part of this study, a homology model of K. pneumonia (MurF ligase) enzyme was predicted for the first time in order to carry out structurebased drug design. The accuracy of the model was further validated using different computational approaches. The comparative molecular docking study on this enzyme was undertaken using different phyto-ligands from Desmodium sp. and a known antibiotic Ciprofloxacin. The docking analysis indicated the importance of hotspots (HIS 281 and ASN 282) within the MurF binding pocket. The Lipinski's rule of five was analyzed for all ligands considered for this study by calculating the ADME/Tox, drug likeliness using Qikprop simulation. Only ten ligands were found to comply with the Lipinski rule of five. Based on the molecular docking results and Lipinki values 6-Methyltetrapterol A was confirmed as a promising lead compound. The present study should therefore play a guiding role in the experimental design and development of 6-Methyltetrapterol A as a bactericidal agent. PMID:22715301

Computational analysis of aspartic protease plasmepsin II complexed with EH58 inhibitor: a QM/MM MD study.

PubMed

de Farias Silva, Natália; Lameira, Jerônimo; Alves, Cláudio Nahum

2011-10-01

Plasmepsin (PM) II is one of four enzymes in the food vacuole of Plasmodium falciparum. It has become an attractive target for combating malaria through research regarding its importance in the P. falciparum metabolism and life cycle, making it the target of choice for structure-based drug design. This paper reports the results of hybrid quantum mechanics / molecular mechanics (QM/MM) molecular dynamics (MD) simulations employed to study the details of the interactions established between PM II and N-(3-{(2-benzo[1, 3]dioxol-5-yl-ethyl)[3-(1-methyl-3-oxo-1,3-dihydro-isoindol-2-yl) propionyl]-amino}-1-benzyl-2-(hydroxyl-propyl)-4-benzyloxy-3,5dimethoxy-benzamide (EH58), a well-known potent inhibitor for this enzyme. Electrostatic binding free energy and energy terms decomposition have been computed for PM II complexed with the EH58 inhibitor. The results reveal that there is a strong interaction between Asp34, Val78, Ser79, Tyr192 and Asp214 residues and the EH58 inhibitor. In addition, we have computed the potential of the mean force (PMF) profile in order to assign the protonation state of the two catalytic aspartates in PM II-EH58 complex. The results indicate that the protonation of Asp214 favors a stable active site structure, which is consistent with our electrostatic binding free energy calculation and with previous published works.

A Design Principle for an Autonomous Post-translational Pattern Formation.

PubMed

Sugai, Shuhei S; Ode, Koji L; Ueda, Hiroki R

2017-04-25

Previous autonomous pattern-formation models often assumed complex molecular and cellular networks. This theoretical study, however, shows that a system composed of one substrate with multisite phosphorylation and a pair of kinase and phosphatase can generate autonomous spatial information, including complex stripe patterns. All (de-)phosphorylation reactions are described with a generic Michaelis-Menten scheme, and all species freely diffuse without pre-existing gradients. Computational simulation upon >23,000,000 randomly generated parameter sets revealed the design motifs of cyclic reaction and enzyme sequestration by slow-diffusing substrates. These motifs constitute short-range positive and long-range negative feedback loops to induce Turing instability. The width and height of spatial patterns can be controlled independently by distinct reaction-diffusion processes. Therefore, multisite reversible post-translational modification can be a ubiquitous source for various patterns without requiring other complex regulations such as autocatalytic regulation of enzymes and is applicable to molecular mechanisms for inducing subcellular localization of proteins driven by post-translational modifications. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

The kinetics-based enzyme-linked immunosorbent assay for coronavirus antibodies in cats: calibration to the indirect immunofluorescence assay and computerized standardization of results through normalization to control values.

PubMed Central

Barlough, J E; Jacobson, R H; Downing, D R; Lynch, T J; Scott, F W

1987-01-01

The computer-assisted, kinetics-based enzyme-linked immunosorbent assay for coronavirus antibodies in cats was calibrated to the conventional indirect immunofluorescence assay by linear regression analysis and computerized interpolation (generation of "immunofluorescence assay-equivalent" titers). Procedures were developed for normalization and standardization of kinetics-based enzyme-linked immunosorbent assay results through incorporation of five different control sera of predetermined ("expected") titer in daily runs. When used with such sera and with computer assistance, the kinetics-based enzyme-linked immunosorbent assay minimized both within-run and between-run variability while allowing also for efficient data reduction and statistical analysis and reporting of results. PMID:3032390

The kinetics-based enzyme-linked immunosorbent assay for coronavirus antibodies in cats: calibration to the indirect immunofluorescence assay and computerized standardization of results through normalization to control values.

PubMed

Barlough, J E; Jacobson, R H; Downing, D R; Lynch, T J; Scott, F W

1987-01-01

The computer-assisted, kinetics-based enzyme-linked immunosorbent assay for coronavirus antibodies in cats was calibrated to the conventional indirect immunofluorescence assay by linear regression analysis and computerized interpolation (generation of "immunofluorescence assay-equivalent" titers). Procedures were developed for normalization and standardization of kinetics-based enzyme-linked immunosorbent assay results through incorporation of five different control sera of predetermined ("expected") titer in daily runs. When used with such sera and with computer assistance, the kinetics-based enzyme-linked immunosorbent assay minimized both within-run and between-run variability while allowing also for efficient data reduction and statistical analysis and reporting of results.

An innovative strategy for dual inhibitor design and its application in dual inhibition of human thymidylate synthase and dihydrofolate reductase enzymes.

PubMed

Arooj, Mahreen; Sakkiah, Sugunadevi; Cao, Guang ping; Lee, Keun Woo

2013-01-01

Due to the diligence of inherent redundancy and robustness in many biological networks and pathways, multitarget inhibitors present a new prospect in the pharmaceutical industry for treatment of complex diseases. Nevertheless, to design multitarget inhibitors is concurrently a great challenge for medicinal chemists. We have developed a novel computational approach by integrating the affinity predictions from structure-based virtual screening with dual ligand-based pharmacophore to discover potential dual inhibitors of human Thymidylate synthase (hTS) and human dihydrofolate reductase (hDHFR). These are the key enzymes in folate metabolic pathway that is necessary for the biosynthesis of RNA, DNA, and protein. Their inhibition has found clinical utility as antitumor, antimicrobial, and antiprotozoal agents. A druglike database was utilized to perform dual-target docking studies. Hits identified through docking experiments were mapped over a dual pharmacophore which was developed from experimentally known dual inhibitors of hTS and hDHFR. Pharmacophore mapping procedure helped us in eliminating the compounds which do not possess basic chemical features necessary for dual inhibition. Finally, three structurally diverse hit compounds that showed key interactions at both active sites, mapped well upon the dual pharmacophore, and exhibited lowest binding energies were regarded as possible dual inhibitors of hTS and hDHFR. Furthermore, optimization studies were performed for final dual hit compound and eight optimized dual hits demonstrating excellent binding features at target systems were also regarded as possible dual inhibitors of hTS and hDHFR. In general, the strategy used in the current study could be a promising computational approach and may be generally applicable to other dual target drug designs.

An Innovative Strategy for Dual Inhibitor Design and Its Application in Dual Inhibition of Human Thymidylate Synthase and Dihydrofolate Reductase Enzymes

PubMed Central

Arooj, Mahreen; Sakkiah, Sugunadevi; Cao, Guang ping; Lee, Keun Woo

2013-01-01

Due to the diligence of inherent redundancy and robustness in many biological networks and pathways, multitarget inhibitors present a new prospect in the pharmaceutical industry for treatment of complex diseases. Nevertheless, to design multitarget inhibitors is concurrently a great challenge for medicinal chemists. We have developed a novel computational approach by integrating the affinity predictions from structure-based virtual screening with dual ligand-based pharmacophore to discover potential dual inhibitors of human Thymidylate synthase (hTS) and human dihydrofolate reductase (hDHFR). These are the key enzymes in folate metabolic pathway that is necessary for the biosynthesis of RNA, DNA, and protein. Their inhibition has found clinical utility as antitumor, antimicrobial, and antiprotozoal agents. A druglike database was utilized to perform dual-target docking studies. Hits identified through docking experiments were mapped over a dual pharmacophore which was developed from experimentally known dual inhibitors of hTS and hDHFR. Pharmacophore mapping procedure helped us in eliminating the compounds which do not possess basic chemical features necessary for dual inhibition. Finally, three structurally diverse hit compounds that showed key interactions at both active sites, mapped well upon the dual pharmacophore, and exhibited lowest binding energies were regarded as possible dual inhibitors of hTS and hDHFR. Furthermore, optimization studies were performed for final dual hit compound and eight optimized dual hits demonstrating excellent binding features at target systems were also regarded as possible dual inhibitors of hTS and hDHFR. In general, the strategy used in the current study could be a promising computational approach and may be generally applicable to other dual target drug designs. PMID:23577115

Designing safer chemicals: predicting the rates of metabolism of halogenated alkanes.

PubMed

Yin, H; Anders, M W; Korzekwa, K R; Higgins, L; Thummel, K E; Kharasch, E D; Jones, J P

1995-11-21

A computational model is presented that can be used as a tool in the design of safer chemicals. This model predicts the rate of hydrogen-atom abstraction by cytochrome P450 enzymes. Excellent correlations between biotransformation rates and the calculated activation energies (delta Hact) of the cytochrome P450-mediated hydrogen-atom abstractions were obtained for the in vitro biotransformation of six halogenated alkanes (1-fluoro-1,1,2,2-tetrachloroethane, 1,1-difluoro-1,2,2-trichloroethane, 1,1,1-trifluro-2,2-dichloroethane, 1,1,1,2-tetrafluoro-2-chloroethane, 1,1,1,2,2,-pentafluoroethane, and 2-bromo-2-chloro-1,1,1-trifluoroethane) with both rat and human enzyme preparations: In(rate, rat liver microsomes) = 44.99 - 1.79(delta Hact), r2 = 0.86; In(rate, human CYP2E1) = 46.99 - 1.77(delta Hact), r2 = 0.97 (rates are in nmol of product per min per nmol of cytochrome P450 and energies are in kcal/mol). Correlations were also obtained for five inhalation anesthetics (enflurane, sevoflurane, desflurane, methoxyflurane, and isoflurane) for both in vivo and in vitro metabolism by humans: In[F(-)]peak plasma = 42.87 - 1.57(delta Hact), r2 = 0.86. To our knowledge, these are the first in vivo human metabolic rates to be quantitatively predicted. Furthermore, this is one of the first examples where computational predictions and in vivo and in vitro data have been shown to agree in any species. The model presented herein provides an archetype for the methodology that may be used in the future design of safer chemicals, particularly hydrochlorofluorocarbons and inhalation anesthetics.

Designing safer chemicals: predicting the rates of metabolism of halogenated alkanes.

PubMed Central

Yin, H; Anders, M W; Korzekwa, K R; Higgins, L; Thummel, K E; Kharasch, E D; Jones, J P

1995-01-01

A computational model is presented that can be used as a tool in the design of safer chemicals. This model predicts the rate of hydrogen-atom abstraction by cytochrome P450 enzymes. Excellent correlations between biotransformation rates and the calculated activation energies (delta Hact) of the cytochrome P450-mediated hydrogen-atom abstractions were obtained for the in vitro biotransformation of six halogenated alkanes (1-fluoro-1,1,2,2-tetrachloroethane, 1,1-difluoro-1,2,2-trichloroethane, 1,1,1-trifluro-2,2-dichloroethane, 1,1,1,2-tetrafluoro-2-chloroethane, 1,1,1,2,2,-pentafluoroethane, and 2-bromo-2-chloro-1,1,1-trifluoroethane) with both rat and human enzyme preparations: In(rate, rat liver microsomes) = 44.99 - 1.79(delta Hact), r2 = 0.86; In(rate, human CYP2E1) = 46.99 - 1.77(delta Hact), r2 = 0.97 (rates are in nmol of product per min per nmol of cytochrome P450 and energies are in kcal/mol). Correlations were also obtained for five inhalation anesthetics (enflurane, sevoflurane, desflurane, methoxyflurane, and isoflurane) for both in vivo and in vitro metabolism by humans: In[F(-)]peak plasma = 42.87 - 1.57(delta Hact), r2 = 0.86. To our knowledge, these are the first in vivo human metabolic rates to be quantitatively predicted. Furthermore, this is one of the first examples where computational predictions and in vivo and in vitro data have been shown to agree in any species. The model presented herein provides an archetype for the methodology that may be used in the future design of safer chemicals, particularly hydrochlorofluorocarbons and inhalation anesthetics. PMID:7479940

Pushing the frontiers of first-principles based computer simulations of chemical and biological systems.

PubMed

Brunk, Elizabeth; Ashari, Negar; Athri, Prashanth; Campomanes, Pablo; de Carvalho, F Franco; Curchod, Basile F E; Diamantis, Polydefkis; Doemer, Manuel; Garrec, Julian; Laktionov, Andrey; Micciarelli, Marco; Neri, Marilisa; Palermo, Giulia; Penfold, Thomas J; Vanni, Stefano; Tavernelli, Ivano; Rothlisberger, Ursula

2011-01-01

The Laboratory of Computational Chemistry and Biochemistry is active in the development and application of first-principles based simulations of complex chemical and biochemical phenomena. Here, we review some of our recent efforts in extending these methods to larger systems, longer time scales and increased accuracies. Their versatility is illustrated with a diverse range of applications, ranging from the determination of the gas phase structure of the cyclic decapeptide gramicidin S, to the study of G protein coupled receptors, the interaction of transition metal based anti-cancer agents with protein targets, the mechanism of action of DNA repair enzymes, the role of metal ions in neurodegenerative diseases and the computational design of dye-sensitized solar cells. Many of these projects are done in collaboration with experimental groups from the Institute of Chemical Sciences and Engineering (ISIC) at the EPFL.

Identification of new allosteric sites and modulators of AChE through computational and experimental tools.

PubMed

Roca, Carlos; Requena, Carlos; Sebastián-Pérez, Víctor; Malhotra, Sony; Radoux, Chris; Pérez, Concepción; Martinez, Ana; Antonio Páez, Juan; Blundell, Tom L; Campillo, Nuria E

2018-12-01

Allosteric sites on proteins are targeted for designing more selective inhibitors of enzyme activity and to discover new functions. Acetylcholinesterase (AChE), which is most widely known for the hydrolysis of the neurotransmitter acetylcholine, has a peripheral allosteric subsite responsible for amyloidosis in Alzheimer's disease through interaction with amyloid β-peptide. However, AChE plays other non-hydrolytic functions. Here, we identify and characterise using computational tools two new allosteric sites in AChE, which have allowed us to identify allosteric inhibitors by virtual screening guided by structure-based and fragment hotspot strategies. The identified compounds were also screened for in vitro inhibition of AChE and three were observed to be active. Further experimental (kinetic) and computational (molecular dynamics) studies have been performed to verify the allosteric activity. These new compounds may be valuable pharmacological tools in the study of non-cholinergic functions of AChE.

Pathway Design, Engineering, and Optimization.

PubMed

Garcia-Ruiz, Eva; HamediRad, Mohammad; Zhao, Huimin

The microbial metabolic versatility found in nature has inspired scientists to create microorganisms capable of producing value-added compounds. Many endeavors have been made to transfer and/or combine pathways, existing or even engineered enzymes with new function to tractable microorganisms to generate new metabolic routes for drug, biofuel, and specialty chemical production. However, the success of these pathways can be impeded by different complications from an inherent failure of the pathway to cell perturbations. Pursuing ways to overcome these shortcomings, a wide variety of strategies have been developed. This chapter will review the computational algorithms and experimental tools used to design efficient metabolic routes, and construct and optimize biochemical pathways to produce chemicals of high interest.

A Promiscuous De Novo Retro-Aldolase Catalyzes Asymmetric Michael Additions via Schiff Base Intermediates.

PubMed

Garrabou, Xavier; Beck, Tobias; Hilvert, Donald

2015-05-04

Recent advances in computational design have enabled the development of primitive enzymes for a range of mechanistically distinct reactions. Here we show that the rudimentary active sites of these catalysts can give rise to useful chemical promiscuity. Specifically, RA95.5-8, designed and evolved as a retro-aldolase, also promotes asymmetric Michael additions of carbanions to unsaturated ketones with high rates and selectivities. The reactions proceed by amine catalysis, as indicated by mutagenesis and X-ray data. The inherent flexibility and tunability of this catalyst should make it a versatile platform for further optimization and/or mechanistic diversification by directed evolution. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Automated Docking with Protein Flexibility in the Design of Femtomolar “Click Chemistry” Inhibitors of Acetylcholinesterase

PubMed Central

Morris, Garrett M.; Green, Luke G.; Radić, Zoran; Taylor, Palmer; Sharpless, K. Barry; Olson, Arthur J.; Grynszpan, Flavio

2013-01-01

The use of computer-aided structure-based drug design prior to synthesis has proven to be generally valuable in suggesting improved binding analogues of existing ligands.1 Here we describe the application of the program AutoDock2 to the design of a focused library that was used in the “click chemistry in-situ” generation of the most potent non-covalent inhibitor of the enzyme acetylcholinesterase (AChE) yet developed (Kd = ~100 fM).3 AutoDock version 3.0.5 has been widely distributed and successfully used to predict bound conformations of flexible ligands. Here, we also used a version of AutoDock which permits additional conformational flexibility in selected amino acid sidechains of the target protein. PMID:23451944

Neuraminidase Ribbon Diagram

NASA Technical Reports Server (NTRS)

2004-01-01

Ribbons is a program developed at UAB used worldwide to graphically depict complicated protein structures in a simplified format. The program uses sophisticated computer systems to understand the implications of protein structures. The Influenza virus remains a major causative agent for a large number of deaths among the elderly and young children and huge economic losses due to illness. Finding a cure will have a general impact both on the basic research of viral pathologists of fast evolving infectious agents and clinical treatment of influenza virus infection. The reproduction process of all strains of influenza are dependent on the same enzyme neuraminidase. Shown here is a segmented representation of the neuraminidase inhibitor compound sitting inside a cave-like contour of the neuraminidase enzyme surface. This cave-like formation present in every neuraminidase enzyme is the active site crucial to the flu's ability to infect. The space-grown crystals of neuraminidase have provided significant new details about the three-dimensional characteristics of this active site thus allowing researchers to design drugs that fit tighter into the site. Principal Investigator: Dr. Larry DeLucas

Refractive microlensarray made of silver-halide sensitized gelatin (SHSG) etched by enzyme with SLM-based lithography

NASA Astrophysics Data System (ADS)

Guo, Xiaowei; Chen, Mingyong; Zhu, Jianhua; Ma, Yanqin; Du, Jinglei; Guo, Yongkang; Du, Chunlei

2006-01-01

A novel method for the fabrication of continuous micro-optical components is presented in this paper. It employs a computer controlled digital-micromirror-device(DMD TM) as a switchable projection mask and silver-halide sensitized gelatin (SHSG) as recording material. By etching SHSG with enzyme solution, the micro-optical components with relief modulation can be generated through special processing procedures. The principles of etching SHSG with enzyme and theoretical analysis for deep etching are also discussed in detail, and the detailed quantitative experiments on the processing procedures are conducted to determine optimum technique parameters. A good linear relationship within a depth range of 4μm was experimentally obtained between exposure dose and relief depth. At last, the microlensarray with 256.8μm radius and 2.572μm depth was achieved. This method is simple, cheap and the aberration in processing procedures can be corrected in the step of designing mask, so it is a practical method to fabricate good continuous profile for low-volume production.

A biomimetic colorimetric logic gate system based on multi-functional peptide-mediated gold nanoparticle assembly

NASA Astrophysics Data System (ADS)

Li, Yong; Li, Wang; He, Kai-Yu; Li, Pei; Huang, Yan; Nie, Zhou; Yao, Shou-Zhuo

2016-04-01

In natural biological systems, proteins exploit various functional peptide motifs to exert target response and activity switch, providing a functional and logic basis for complex cellular activities. Building biomimetic peptide-based bio-logic systems is highly intriguing but remains relatively unexplored due to limited logic recognition elements and complex signal outputs. In this proof-of-principle work, we attempted to address these problems by utilizing multi-functional peptide probes and the peptide-mediated nanoparticle assembly system. Here, the rationally designed peptide probes function as the dual-target responsive element specifically responsive to metal ions and enzymes as well as the mediator regulating the assembly of gold nanoparticles (AuNPs). Taking advantage of Zn2+ ions and chymotrypsin as the model inputs of metal ions and enzymes, respectively, we constructed the peptide logic system computed by the multi-functional peptide probes and outputted by the readable colour change of AuNPs. In this way, the representative binary basic logic gates (AND, OR, INHIBIT, NAND, IMPLICATION) have been achieved by delicately coding the peptide sequence, demonstrating the versatility of our logic system. Additionally, we demonstrated that the three-input combinational logic gate (INHIBIT-OR) could also be successfully integrated and applied as a multi-tasking biosensor for colorimetric detection of dual targets. This nanoparticle-based peptide logic system presents a valid strategy to illustrate peptide information processing and provides a practical platform for executing peptide computing or peptide-related multiplexing sensing, implying that the controllable nanomaterial assembly is a promising and potent methodology for the advancement of biomimetic bio-logic computation.In natural biological systems, proteins exploit various functional peptide motifs to exert target response and activity switch, providing a functional and logic basis for complex cellular activities. Building biomimetic peptide-based bio-logic systems is highly intriguing but remains relatively unexplored due to limited logic recognition elements and complex signal outputs. In this proof-of-principle work, we attempted to address these problems by utilizing multi-functional peptide probes and the peptide-mediated nanoparticle assembly system. Here, the rationally designed peptide probes function as the dual-target responsive element specifically responsive to metal ions and enzymes as well as the mediator regulating the assembly of gold nanoparticles (AuNPs). Taking advantage of Zn2+ ions and chymotrypsin as the model inputs of metal ions and enzymes, respectively, we constructed the peptide logic system computed by the multi-functional peptide probes and outputted by the readable colour change of AuNPs. In this way, the representative binary basic logic gates (AND, OR, INHIBIT, NAND, IMPLICATION) have been achieved by delicately coding the peptide sequence, demonstrating the versatility of our logic system. Additionally, we demonstrated that the three-input combinational logic gate (INHIBIT-OR) could also be successfully integrated and applied as a multi-tasking biosensor for colorimetric detection of dual targets. This nanoparticle-based peptide logic system presents a valid strategy to illustrate peptide information processing and provides a practical platform for executing peptide computing or peptide-related multiplexing sensing, implying that the controllable nanomaterial assembly is a promising and potent methodology for the advancement of biomimetic bio-logic computation. Electronic supplementary information (ESI) available: Additional figures (Tables S1-S3 and Fig. S1-S6). See DOI: 10.1039/c6nr01072e

Enhancement of cellulosome-mediated deconstruction of cellulose by improving enzyme thermostability.

PubMed

Moraïs, Sarah; Stern, Johanna; Kahn, Amaranta; Galanopoulou, Anastasia P; Yoav, Shahar; Shamshoum, Melina; Smith, Matthew A; Hatzinikolaou, Dimitris G; Arnold, Frances H; Bayer, Edward A

2016-01-01

The concerted action of three complementary cellulases from Clostridium thermocellum, engineered to be stable at elevated temperatures, was examined on a cellulosic substrate and compared to that of the wild-type enzymes. Exoglucanase Cel48S and endoglucanase Cel8A, both key elements of the natural cellulosome from this bacterium, were engineered previously for increased thermostability, either by SCHEMA, a structure-guided, site-directed protein recombination method, or by consensus-guided mutagenesis combined with random mutagenesis using error-prone PCR, respectively. A thermostable β-glucosidase BglA mutant was also selected from a library generated by error-prone PCR that will assist the two cellulases in their methodic deconstruction of crystalline cellulose. The effects of a thermostable scaffoldin versus those of a largely mesophilic scaffoldin were also examined. By improving the stability of the enzyme subunits and the structural component, we aimed to improve cellulosome-mediated deconstruction of cellulosic substrates. The results demonstrate that the combination of thermostable enzymes as free enzymes and a thermostable scaffoldin was more active on the cellulosic substrate than the wild-type enzymes. Significantly, "thermostable" designer cellulosomes exhibited a 1.7-fold enhancement in cellulose degradation compared to the action of conventional designer cellulosomes that contain the respective wild-type enzymes. For designer cellulosome formats, the use of the thermostabilized scaffoldin proved critical for enhanced enzymatic performance under conditions of high temperatures. Simple improvement in the activity of a given enzyme does not guarantee its suitability for use in an enzyme cocktail or as a designer cellulosome component. The true merit of improvement resides in its ultimate contribution to synergistic action, which can only be determined experimentally. The relevance of the mutated thermostable enzymes employed in this study as components in multienzyme systems has thus been confirmed using designer cellulosome technology. Enzyme integration via a thermostable scaffoldin is critical to the ultimate stability of the complex at higher temperatures. Engineering of thermostable cellulases and additional lignocellulosic enzymes may prove a determinant parameter for development of state-of-the-art designer cellulosomes for their employment in the conversion of cellulosic biomass to soluble sugars.Graphical abstractConversion of conventional designer cellulosomes into thermophilic designer cellulosomes.

Is your ribozyme design really correct?: A proposal of simple single turnover competition assay to evaluate ribozymes.

PubMed

Tanaka, T; Inui, O; Dohi, N; Okada, N; Okada, H; Kikuchi, Y

2001-07-01

Today, many nucleic acid enzymes are used in gene therapy and gene regulations. However, no simple assay methods to evaluate enzymatic activities, with which we judge the enzyme design, have been reported. Here, we propose a new simple competition assay for nucleic acid enzymes of different types to evaluate the cleaving efficiency of a target RNA molecule, of which the recognition sites are different but overlapped. Two nucleic acid enzymes were added to one tube to make a competition of these two enzymes for one substrate. The assay was used on two ribozymes, hammerhead ribozyme and hairpin ribozyme, and a DNA-enzyme. We found that this assay method is capable of application to those enzymes, as a powerful tool for the selection and designing of RNA-cleaving enzymes.

A computational analysis of SARS cysteine proteinase-octapeptide substrate interaction: implication for structure and active site binding mechanism

PubMed Central

Phakthanakanok, Krongsakda; Ratanakhanokchai, Khanok; Kyu, Khin Lay; Sompornpisut, Pornthep; Watts, Aaron; Pinitglang, Surapong

2009-01-01

Background SARS coronavirus main proteinase (SARS CoVMpro) is an important enzyme for the replication of Severe Acute Respiratory Syndrome virus. The active site region of SARS CoVMpro is divided into 8 subsites. Understanding the binding mode of SARS CoVMpro with a specific substrate is useful and contributes to structural-based drug design. The purpose of this research is to investigate the binding mode between the SARS CoVMpro and two octapeptides, especially in the region of the S3 subsite, through a molecular docking and molecular dynamics (MD) simulation approach. Results The one turn α-helix chain (residues 47–54) of the SARS CoVMpro was directly involved in the induced-fit model of the enzyme-substrate complex. The S3 subsite of the enzyme had a negatively charged region due to the presence of Glu47. During MD simulations, Glu47 of the enzyme was shown to play a key role in electrostatic bonding with the P3Lys of the octapeptide. Conclusion MD simulations were carried out on the SARS CoVMpro-octapeptide complex. The hypothesis proposed that Glu47 of SARS CoVMpro is an important residue in the S3 subsite and is involved in binding with P3Lys of the octapeptide. PMID:19208150

Computational characterization of DNA/peptide/nanotube self assembly for bioenergy applications

NASA Astrophysics Data System (ADS)

Ortiz, Vanessa; Araki, Ruriko; Collier, Galen

2012-02-01

Multi-enzyme pathways have become a subject of increasing interest for their role in the engineering of biomimetic systems for applications including biosensors, bioelectronics, and bioenergy. The efficiencies found in natural metabolic pathways partially arise from biomolecular self-assembly of the component enzymes in an effort to avoid transport limitations. The ultimate goal of this effort is to design and build biofuel cells with efficiencies similar to those of native systems by introducing biomimetic structures that immobilize multiple enzymes in specific orientations on a bioelectrode. To achieve site-specific immobilization, the specificity of DNA-binding domains is exploited with an approach that allows any redox enzyme to be modified to site-specifically bind to double stranded (ds) DNA while retaining activity. Because of its many desirable properties, the bioelectrode of choice is single-wall carbon nanotubes (SWNTs), but little is known about dsDNA/SWNT assembly and how this might affect the activity of the DNA-binding domains. Here we evaluate the feasibility of the proposed assembly by performing atomistic molecular dynamics simulations to look at the stability and conformations adopted by dsDNA when bound to a SWNT. We also evaluate the effects of the presence of a SWNT on the stability of the complex formed by a DNA-binding domain and DNA.

Insights into enzymatic halogenation from computational studies

PubMed Central

Senn, Hans M.

2014-01-01

The halogenases are a group of enzymes that have only come to the fore over the last 10 years thanks to the discovery and characterization of several novel representatives. They have revealed the fascinating variety of distinct chemical mechanisms that nature utilizes to activate halogens and introduce them into organic substrates. Computational studies using a range of approaches have already elucidated many details of the mechanisms of these enzymes, often in synergistic combination with experiment. This Review summarizes the main insights gained from these studies. It also seeks to identify open questions that are amenable to computational investigations. The studies discussed herein serve to illustrate some of the limitations of the current computational approaches and the challenges encountered in computational mechanistic enzymology. PMID:25426489

Large-Scale Analysis Exploring Evolution of Catalytic Machineries and Mechanisms in Enzyme Superfamilies.

PubMed

Furnham, Nicholas; Dawson, Natalie L; Rahman, Syed A; Thornton, Janet M; Orengo, Christine A

2016-01-29

Enzymes, as biological catalysts, form the basis of all forms of life. How these proteins have evolved their functions remains a fundamental question in biology. Over 100 years of detailed biochemistry studies, combined with the large volumes of sequence and protein structural data now available, means that we are able to perform large-scale analyses to address this question. Using a range of computational tools and resources, we have compiled information on all experimentally annotated changes in enzyme function within 379 structurally defined protein domain superfamilies, linking the changes observed in functions during evolution to changes in reaction chemistry. Many superfamilies show changes in function at some level, although one function often dominates one superfamily. We use quantitative measures of changes in reaction chemistry to reveal the various types of chemical changes occurring during evolution and to exemplify these by detailed examples. Additionally, we use structural information of the enzymes active site to examine how different superfamilies have changed their catalytic machinery during evolution. Some superfamilies have changed the reactions they perform without changing catalytic machinery. In others, large changes of enzyme function, in terms of both overall chemistry and substrate specificity, have been brought about by significant changes in catalytic machinery. Interestingly, in some superfamilies, relatives perform similar functions but with different catalytic machineries. This analysis highlights characteristics of functional evolution across a wide range of superfamilies, providing insights that will be useful in predicting the function of uncharacterised sequences and the design of new synthetic enzymes. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Enzyme Function Initiative-Enzyme Similarity Tool (EFI-EST): A web tool for generating protein sequence similarity networks.

PubMed

Gerlt, John A; Bouvier, Jason T; Davidson, Daniel B; Imker, Heidi J; Sadkhin, Boris; Slater, David R; Whalen, Katie L

2015-08-01

The Enzyme Function Initiative, an NIH/NIGMS-supported Large-Scale Collaborative Project (EFI; U54GM093342; http://enzymefunction.org/), is focused on devising and disseminating bioinformatics and computational tools as well as experimental strategies for the prediction and assignment of functions (in vitro activities and in vivo physiological/metabolic roles) to uncharacterized enzymes discovered in genome projects. Protein sequence similarity networks (SSNs) are visually powerful tools for analyzing sequence relationships in protein families (H.J. Atkinson, J.H. Morris, T.E. Ferrin, and P.C. Babbitt, PLoS One 2009, 4, e4345). However, the members of the biological/biomedical community have not had access to the capability to generate SSNs for their "favorite" protein families. In this article we announce the EFI-EST (Enzyme Function Initiative-Enzyme Similarity Tool) web tool (http://efi.igb.illinois.edu/efi-est/) that is available without cost for the automated generation of SSNs by the community. The tool can create SSNs for the "closest neighbors" of a user-supplied protein sequence from the UniProt database (Option A) or of members of any user-supplied Pfam and/or InterPro family (Option B). We provide an introduction to SSNs, a description of EFI-EST, and a demonstration of the use of EFI-EST to explore sequence-function space in the OMP decarboxylase superfamily (PF00215). This article is designed as a tutorial that will allow members of the community to use the EFI-EST web tool for exploring sequence/function space in protein families. Copyright © 2015 Elsevier B.V. All rights reserved.

From molecular engineering to process engineering: development of high-throughput screening methods in enzyme directed evolution.

PubMed

Ye, Lidan; Yang, Chengcheng; Yu, Hongwei

2018-01-01

With increasing concerns in sustainable development, biocatalysis has been recognized as a competitive alternative to traditional chemical routes in the past decades. As nature's biocatalysts, enzymes are able to catalyze a broad range of chemical transformations, not only with mild reaction conditions but also with high activity and selectivity. However, the insufficient activity or enantioselectivity of natural enzymes toward non-natural substrates limits their industrial application, while directed evolution provides a potent solution to this problem, thanks to its independence on detailed knowledge about the relationship between sequence, structure, and mechanism/function of the enzymes. A proper high-throughput screening (HTS) method is the key to successful and efficient directed evolution. In recent years, huge varieties of HTS methods have been developed for rapid evaluation of mutant libraries, ranging from in vitro screening to in vivo selection, from indicator addition to multi-enzyme system construction, and from plate screening to computation- or machine-assisted screening. Recently, there is a tendency to integrate directed evolution with metabolic engineering in biosynthesis, using metabolites as HTS indicators, which implies that directed evolution has transformed from molecular engineering to process engineering. This paper aims to provide an overview of HTS methods categorized based on the reaction principles or types by summarizing related studies published in recent years including the work from our group, to discuss assay design strategies and typical examples of HTS methods, and to share our understanding on HTS method development for directed evolution of enzymes involved in specific catalytic reactions or metabolic pathways.

Virtual screening of selective inhibitors of phosphopantetheine adenylyltransferase from Mycobacterium tuberculosis

NASA Astrophysics Data System (ADS)

Podshivalov, D. D.; Timofeev, V. I.; Sidorov-Biryukov, D. D.; Kuranova, I. P.

2017-05-01

Bacterial phosphopantetheine adenylyltransferase from Mycobacterium tuberculosis (PPAT Mt) is a convenient target protein for the directed search for selective inhibitors as potent antituberculosis drugs. Four compounds suitable for the detailed investigation of their interactions with PPAT Mt were found by virtual screening. The active-site region of the enzyme was chosen as the ligand-binding site. The positions of the ligands found by the docking were refined by molecular dynamics simulation. The nearest environment of the ligands, the positions of which in the active site of the enzyme were found in a computational experiment, was analyzed. The compounds under consideration were shown to directly interact with functionally important active-site amino-acid residues and block access of substrates to the active site. Therefore, these compounds can be used for the design of selective inhibitors of PPAT Mt as potent antituberculosis drugs.

Molecular basis of cyclooxygenase enzymes (COXs) selective inhibition

PubMed Central

Limongelli, Vittorio; Bonomi, Massimiliano; Marinelli, Luciana; Gervasio, Francesco Luigi; Cavalli, Andrea; Novellino, Ettore; Parrinello, Michele

2010-01-01

The widely used nonsteroidal anti-inflammatory drugs block the cyclooxygenase enzymes (COXs) and are clinically used for the treatment of inflammation, pain, and cancers. A selective inhibition of the different isoforms, particularly COX-2, is desirable, and consequently a deeper understanding of the molecular basis of selective inhibition is of great demand. Using an advanced computational technique we have simulated the full dissociation process of a highly potent and selective inhibitor, SC-558, in both COX-1 and COX-2. We have found a previously unreported alternative binding mode in COX-2 explaining the time-dependent inhibition exhibited by this class of inhibitors and consequently their long residence time inside this isoform. Our metadynamics-based approach allows us to illuminate the highly dynamical character of the ligand/protein recognition process, thus explaining a wealth of experimental data and paving the way to an innovative strategy for designing new COX inhibitors with tuned selectivity. PMID:20215464

Strategic enzyme patterning for microfluidic biofuel cells

NASA Astrophysics Data System (ADS)

Kjeang, E.; Sinton, D.; Harrington, D. A.

The specific character of biological enzyme catalysts enables combined fuel and oxidant channels and simplified non-compartmentalized fuel cell assemblies. In this work, a microstructured enzymatic biofuel cell architecture is proposed, and species transport phenomena combined with consecutive chemical reactions are studied computationally in order to provide guidelines for optimization. This is the first computational study of this technology, and a 2D CFD model for species transport coupled with laminar fluid flow and Michaelis-Menten enzyme kinetics is established. It is shown that the system is reaction rate limited, indicating that enzyme specific turnover numbers are key parameters for biofuel cell performance. Separated and mixed enzyme patterns in different proportions are analyzed for various Peclet numbers. High fuel utilization is achieved in the diffusion dominated and mixed species transport regimes with separated enzymes arranged in relation to individual turnover rates. However, the Peclet number has to be above a certain threshold value to obtain satisfying current densities. The mixed transport regime is particularly attractive while current densities are maintained close to maximum levels. Optimum performance is achieved by mixed enzyme patterning tailored with respect to individual turnover rates, enabling high current densities combined with nearly complete fuel utilization.

On the active site of mononuclear B1 metallo β-lactamases: a computational study

NASA Astrophysics Data System (ADS)

Sgrignani, Jacopo; Magistrato, Alessandra; Dal Peraro, Matteo; Vila, Alejandro J.; Carloni, Paolo; Pierattelli, Roberta

2012-04-01

Metallo-β-lactamases (MβLs) are Zn(II)-based bacterial enzymes that hydrolyze β-lactam antibiotics, hampering their beneficial effects. In the most relevant subclass (B1), X-ray crystallography studies on the enzyme from Bacillus Cereus point to either two zinc ions in two metal sites (the so-called `3H' and `DCH' sites) or a single Zn(II) ion in the 3H site, where the ion is coordinated by Asp120, Cys221 and His263 residues. However, spectroscopic studies on the B1 enzyme from B. Cereus in the mono-zinc form suggested the presence of the Zn(II) ion also in the DCH site, where it is bound to an aspartate, a cysteine, a histidine and a water molecule. A structural model of this enzyme in its DCH mononuclear form, so far lacking, is therefore required for inhibitor design and mechanistic studies. By using force field based and mixed quantum-classical (QM/MM) molecular dynamics (MD) simulations of the protein in aqueous solution we constructed such structural model. The geometry and the H-bond network at the catalytic site of this model, in the free form and in complex with two common β-lactam drugs, is compared with experimental and theoretical findings of CphA and the recently solved crystal structure of new B2 MβL from Serratia fonticola (Sfh-I). These are MβLs from the B2 subclass, which features an experimentally well established mono-zinc form, in which the Zn(II) is located in the DCH site. From our simulations the ɛɛδ and δɛδ protomers emerge as possible DCH mono-zinc reactive species, giving a novel contribution to the discussion on the MβL reactivity and to the drug design process.

Introducing Michaelis-Menten Kinetics through Simulation

ERIC Educational Resources Information Center

Halkides, Christopher J.; Herman, Russell

2007-01-01

We describe a computer tutorial that introduces the concept of the steady state in enzyme kinetics. The tutorial allows students to produce graphs of the concentrations of free enzyme, enzyme-substrate complex, and product versus time in order to learn about the approach to steady state. By using a range of substrate concentrations and rate…

Computer-aided prediction of xenobiotic metabolism in the human body

NASA Astrophysics Data System (ADS)

Bezhentsev, V. M.; Tarasova, O. A.; Dmitriev, A. V.; Rudik, A. V.; Lagunin, A. A.; Filimonov, D. A.; Poroikov, V. V.

2016-08-01

The review describes the major databases containing information about the metabolism of xenobiotics, including data on drug metabolism, metabolic enzymes, schemes of biotransformation and the structures of some substrates and metabolites. Computational approaches used to predict the interaction of xenobiotics with metabolic enzymes, prediction of metabolic sites in the molecule, generation of structures of potential metabolites for subsequent evaluation of their properties are considered. The advantages and limitations of various computational methods for metabolism prediction and the prospects for their applications to improve the safety and efficacy of new drugs are discussed. Bibliography — 165 references.

Nanoscale Engineering of Designer Cellulosomes.

PubMed

Gunnoo, Melissabye; Cazade, Pierre-André; Galera-Prat, Albert; Nash, Michael A; Czjzek, Mirjam; Cieplak, Marek; Alvarez, Beatriz; Aguilar, Marina; Karpol, Alon; Gaub, Hermann; Carrión-Vázquez, Mariano; Bayer, Edward A; Thompson, Damien

2016-07-01

Biocatalysts showcase the upper limit obtainable for high-speed molecular processing and transformation. Efforts to engineer functionality in synthetic nanostructured materials are guided by the increasing knowledge of evolving architectures, which enable controlled molecular motion and precise molecular recognition. The cellulosome is a biological nanomachine, which, as a fundamental component of the plant-digestion machinery from bacterial cells, has a key potential role in the successful development of environmentally-friendly processes to produce biofuels and fine chemicals from the breakdown of biomass waste. Here, the progress toward so-called "designer cellulosomes", which provide an elegant alternative to enzyme cocktails for lignocellulose breakdown, is reviewed. Particular attention is paid to rational design via computational modeling coupled with nanoscale characterization and engineering tools. Remaining challenges and potential routes to industrial application are put forward. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Computer program for the reservoir model of metabolic crossroads.

PubMed

Ribeiro, J M; Juzgado, D; Crespo, E; Sillero, A

1990-01-01

A program containing 344 sentences, written in BASIC and adapted to run in personal computers (PC) has been developed to simulate the reservoir model of metabolic crossroads. The program draws the holes of the reservoir with shapes reflecting the Vmax, Km (S0.5) and cooperativity coefficients (n) of the enzymes and calculates both the actual velocities and the percentage of contribution of every enzyme to the overall removal of their common substrate.

Analytical and computational approaches to define the Aspergillus niger secretome.

PubMed

Tsang, Adrian; Butler, Gregory; Powlowski, Justin; Panisko, Ellen A; Baker, Scott E

2009-03-01

We used computational and mass spectrometric approaches to characterize the Aspergillus niger secretome.The 11,200 gene models predicted in the genome of A. niger strain ATCC 1015 were the data source for the analysis. Depending on the computational methods used, 691 to 881 proteins were predicted to be secreted proteins. We cultured A. niger in six different media and analyzed the extracellular proteins produced using mass spectrometry. A total of 222 proteins were identified, with 39 proteins expressed under all six conditions and 74 proteins expressed under only one condition. The secreted proteins identified by mass spectrometry were used to guide the correction of about 20 gene models. Additional analysis focused on extracellular enzymes of interest for biomass processing. Of the 63 glycoside hydrolases predicted to be capable of hydrolyzing cellulose, hemicellulose or pectin, 94% of the exo-acting enzymes and only 18% of the endo-acting enzymes were experimentally detected.

Analytical and computational approaches to define the Aspergillus niger secretome

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

Tsang, Adrian; Butler, Gregory D.; Powlowski, Justin

2009-03-01

We used computational and mass spectrometric approaches to characterize the Aspergillus niger secretome. The 11,200 gene models predicted in the genome of A. niger strain ATCC 1015 were the data source for the analysis. Depending on the computational methods used, 691 to 881 proteins were predicted to be secreted proteins. We cultured A. niger in six different media and analyzed the extracellular proteins produced using mass spectrometry. A total of 222 proteins were identified, with 39 proteins expressed under all six conditions and 74 proteins expressed under only one condition. The secreted proteins identified by mass spectrometry were used tomore » guide the correction of about 20 gene models. Additional analysis focused on extracellular enzymes of interest for biomass processing. Of the 63 glycoside hydrolases predicted to be capable of hydrolyzing cellulose, hemicellulose or pectin, 94% of the exo-acting enzymes and only 18% of the endo-acting enzymes were experimentally detected.« less

Biomimetic/Bioinspired Design of Enzyme@capsule Nano/Microsystems.

PubMed

Shi, J; Jiang, Y; Zhang, S; Yang, D; Jiang, Z

2016-01-01

Enzyme@capsule nano/microsystems, which refer to the enzyme-immobilized capsules, have received tremendous interest owing to the combination of the high catalytic activities of encapsulated enzymes and the hierarchical structure of the capsule. The preparation of capsules and simultaneous encapsulation of enzymes is recognized as the core process for the rational design and construction of enzyme@capsule nano/microsystems. The strategy used has three major steps: (a) generation of the templates, (b) surface coating on the templates, and (c) removal of the templates, and it has been proven to be effective and versatile for the construction of enzyme@capsule nano/microsystems. Several conventional methods, including layer-by-layer assembly of polyelectrolytes, liquid crystalline templating method, etc., were used to design and construct enzyme@capsule nano/microsystems, but these have two major drawbacks. One is the low mechanical stability of the systems and the second is the harsh conditions used in the construction process. Learning from nature, several biomimetic/bioinspired methods such as biomineralization, biomimetic/bioinspired adhesion, and their combination have been exploited for the construction of enzyme@capsule nano/microsystems. In this chapter, we will present a general protocol for the construction of enzyme@capsule nano/microsystems using the latter approach. Some suggestions for improved design, construction, and characterization will also be presented with detailed procedures for specific examples. © 2016 Elsevier Inc. All rights reserved.

Protein consensus-based surface engineering (ProCoS): a computer-assisted method for directed protein evolution.

PubMed

Shivange, Amol V; Hoeffken, Hans Wolfgang; Haefner, Stefan; Schwaneberg, Ulrich

2016-12-01

Protein consensus-based surface engineering (ProCoS) is a simple and efficient method for directed protein evolution combining computational analysis and molecular biology tools to engineer protein surfaces. ProCoS is based on the hypothesis that conserved residues originated from a common ancestor and that these residues are crucial for the function of a protein, whereas highly variable regions (situated on the surface of a protein) can be targeted for surface engineering to maximize performance. ProCoS comprises four main steps: ( i ) identification of conserved and highly variable regions; ( ii ) protein sequence design by substituting residues in the highly variable regions, and gene synthesis; ( iii ) in vitro DNA recombination of synthetic genes; and ( iv ) screening for active variants. ProCoS is a simple method for surface mutagenesis in which multiple sequence alignment is used for selection of surface residues based on a structural model. To demonstrate the technique's utility for directed evolution, the surface of a phytase enzyme from Yersinia mollaretii (Ymphytase) was subjected to ProCoS. Screening just 1050 clones from ProCoS engineering-guided mutant libraries yielded an enzyme with 34 amino acid substitutions. The surface-engineered Ymphytase exhibited 3.8-fold higher pH stability (at pH 2.8 for 3 h) and retained 40% of the enzyme's specific activity (400 U/mg) compared with the wild-type Ymphytase. The pH stability might be attributed to a significantly increased (20 percentage points; from 9% to 29%) number of negatively charged amino acids on the surface of the engineered phytase.

Old drug new use - Amoxapine and its metabolites as potent bacterial β-glucuronidase inhibitors for alleviating cancer drug toxicity

PubMed Central

Kong, Ren; Liu, Timothy; Zhu, Xiaoping; Ahmad, Syed; Williams, Alfred L.; Phan, Alexandria T; Zhao, Hong; Scott, John E.; Yeh, Li-An; Wong, Stephen TC

2014-01-01

Purpose Irinotecan (CPT-11) induced diarrhea occurs frequently in cancer patients and limits its usage. Bacteria β-glucuronidase (GUS) enzymes in intestines convert the non-toxic metabolite of CPT-11, SN-38G, to toxic SN-38, and finally lead to damage of intestinal epithelial cells and diarrhea. We previously reported amoxapine as potent GUS inhibitor in vitro. To further understand the molecular mechanism of amoxapine and its potential for treatment of CPT-11 induced diarrhea, we studied the binding modes of amoxapine and its metabolites by docking and molecular dynamics simulation, and tested the in vivo efficacy on mice in combination with CPT-11. Experimental Design The binding of amoxapine, its metabolites, 7-hydroxyamoxapine and 8-hydroxyamoxapine, and a control drug loxapine with GUS was explored by computational protocols. The in vitro potencies of metabolites were measured by E. Coli GUS enzyme and cell-based assay. Low dosage daily oral administration was designed to use along with CPT-11 to treat tumor-bearing mice. Results Computational modeling results indicated that amoxapine and its metabolites bound in the active site of GUS and satisfied critical pharmacophore features: aromatic features near bacterial loop residue F365’ and hydrogen bond toward E413. Amoxapine and its metabolites were demonstrated as potent in vitro. Administration of low dosages of amoxapine with CPT-11 in mice achieved significant suppression of diarrhea and reduced tumor growth. Conclusions Amoxapine has great clinical potential to be rapidly translated to human subjects for irinotecan induced diarrhea. PMID:24780296

Optimization of time-course experiments for kinetic model discrimination.

PubMed

Lages, Nuno F; Cordeiro, Carlos; Sousa Silva, Marta; Ponces Freire, Ana; Ferreira, António E N

2012-01-01

Systems biology relies heavily on the construction of quantitative models of biochemical networks. These models must have predictive power to help unveiling the underlying molecular mechanisms of cellular physiology, but it is also paramount that they are consistent with the data resulting from key experiments. Often, it is possible to find several models that describe the data equally well, but provide significantly different quantitative predictions regarding particular variables of the network. In those cases, one is faced with a problem of model discrimination, the procedure of rejecting inappropriate models from a set of candidates in order to elect one as the best model to use for prediction.In this work, a method is proposed to optimize the design of enzyme kinetic assays with the goal of selecting a model among a set of candidates. We focus on models with systems of ordinary differential equations as the underlying mathematical description. The method provides a design where an extension of the Kullback-Leibler distance, computed over the time courses predicted by the models, is maximized. Given the asymmetric nature this measure, a generalized differential evolution algorithm for multi-objective optimization problems was used.The kinetics of yeast glyoxalase I (EC 4.4.1.5) was chosen as a difficult test case to evaluate the method. Although a single-substrate kinetic model is usually considered, a two-substrate mechanism has also been proposed for this enzyme. We designed an experiment capable of discriminating between the two models by optimizing the initial substrate concentrations of glyoxalase I, in the presence of the subsequent pathway enzyme, glyoxalase II (EC 3.1.2.6). This discriminatory experiment was conducted in the laboratory and the results indicate a two-substrate mechanism for the kinetics of yeast glyoxalase I.

Biocatalysts: application and engineering for industrial purposes.

PubMed

Jemli, Sonia; Ayadi-Zouari, Dorra; Hlima, Hajer Ben; Bejar, Samir

2016-01-01

Enzymes are widely applied in various industrial applications and processes, including the food and beverage, animal feed, textile, detergent and medical industries. Enzymes screened from natural origins are often engineered before entering the market place because their native forms do not meet the requirements for industrial application. Protein engineering is concerned with the design and construction of novel enzymes with tailored functional properties, including stability, catalytic activity, reaction product inhibition and substrate specificity. Two broad approaches have been used for enzyme engineering, namely, rational design and directed evolution. The powerful and revolutionary techniques so far developed for protein engineering provide excellent opportunities for the design of industrial enzymes with specific properties and production of high-value products at lower production costs. The present review seeks to highlight the major fields of enzyme application and to provide an updated overview on previous protein engineering studies wherein natural enzymes were modified to meet the operational conditions required for industrial application.

Enzyme-guided DNA Sewing Architecture

PubMed Central

Song, In Hyun; Shin, Seung Won; Park, Kyung Soo; Lansac, Yves; Jang, Yun Hee; Um, Soong Ho

2015-01-01

With the advent of nanotechnology, a variety of nanoarchitectures with varied physicochemical properties have been designed. Owing to the unique characteristics, DNAs have been used as a functional building block for novel nanoarchitecture. In particular, a self-assembly of long DNA molecules via a piece DNA staple has been utilized to attain such constructs. However, it needs many talented prerequisites (e.g., complicated computer program) with fewer yields of products. In addition, it has many limitations to overcome: for instance, (i) thermal instability under moderate environments and (ii) restraint in size caused by the restricted length of scaffold strands. Alternatively, the enzymatic sewing linkage of short DNA blocks is simply designed into long DNA assemblies but it is more error-prone due to the undeveloped sequence data. Here, we present, for the first time, a comprehensive study for directly combining DNA structures into higher DNA sewing constructs through the 5′-end cohesive ligation of T4 enzyme. Inspired by these achievements, the synthesized DNA nanomaterials were also utilized for effective detection and real-time diagnosis of cancer-specific and cytosolic RNA markers. This generalized protocol for generic DNA sewing is expected to be useful in several DNA nanotechnology as well as any nucleic acid-related fields. PMID:26634810

DESHARKY: automatic design of metabolic pathways for optimal cell growth.

PubMed

Rodrigo, Guillermo; Carrera, Javier; Prather, Kristala Jones; Jaramillo, Alfonso

2008-11-01

The biological solution for synthesis or remediation of organic compounds using living organisms, particularly bacteria and yeast, has been promoted because of the cost reduction with respect to the non-living chemical approach. In that way, computational frameworks can profit from the previous knowledge stored in large databases of compounds, enzymes and reactions. In addition, the cell behavior can be studied by modeling the cellular context. We have implemented a Monte Carlo algorithm (DESHARKY) that finds a metabolic pathway from a target compound by exploring a database of enzymatic reactions. DESHARKY outputs a biochemical route to the host metabolism together with its impact in the cellular context by using mathematical models of the cell resources and metabolism. Furthermore, we provide the sequence of amino acids for the enzymes involved in the route closest phylogenetically to the considered organism. We provide examples of designed metabolic pathways with their genetic load characterizations. Here, we have used Escherichia coli as host organism. In addition, our bioinformatic tool can be applied for biodegradation or biosynthesis and its performance scales with the database size. Software, a tutorial and examples are freely available and open source at http://soft.synth-bio.org/desharky.html

Enzyme-guided DNA Sewing Architecture

NASA Astrophysics Data System (ADS)

Song, In Hyun; Shin, Seung Won; Park, Kyung Soo; Lansac, Yves; Jang, Yun Hee; Um, Soong Ho

2015-12-01

With the advent of nanotechnology, a variety of nanoarchitectures with varied physicochemical properties have been designed. Owing to the unique characteristics, DNAs have been used as a functional building block for novel nanoarchitecture. In particular, a self-assembly of long DNA molecules via a piece DNA staple has been utilized to attain such constructs. However, it needs many talented prerequisites (e.g., complicated computer program) with fewer yields of products. In addition, it has many limitations to overcome: for instance, (i) thermal instability under moderate environments and (ii) restraint in size caused by the restricted length of scaffold strands. Alternatively, the enzymatic sewing linkage of short DNA blocks is simply designed into long DNA assemblies but it is more error-prone due to the undeveloped sequence data. Here, we present, for the first time, a comprehensive study for directly combining DNA structures into higher DNA sewing constructs through the 5‧-end cohesive ligation of T4 enzyme. Inspired by these achievements, the synthesized DNA nanomaterials were also utilized for effective detection and real-time diagnosis of cancer-specific and cytosolic RNA markers. This generalized protocol for generic DNA sewing is expected to be useful in several DNA nanotechnology as well as any nucleic acid-related fields.

Allosteric activation transitions in enzymes and biomolecular motors: insights from atomistic and coarse-grained simulations.

PubMed

Daily, Michael D; Yu, Haibo; Phillips, George N; Cui, Qiang

2013-01-01

The chemical step in enzymes is usually preceded by a kinetically distinct activation step that involves large-scale conformational transitions. In "simple" enzymes this step corresponds to the closure of the active site; in more complex enzymes, such as biomolecular motors, the activation step is more complex and may involve interactions with other biomolecules. These activation transitions are essential to the function of enzymes and perturbations in the scale and/or rate of these transitions are implicated in various serious human diseases; incorporating key flexibilities into engineered enzymes is also considered a major remaining challenge in rational enzyme design. Therefore it is important to understand the underlying mechanism of these transitions. This is a significant challenge to both experimental and computational studies because of the allosteric and multi-scale nature of such transitions. Using our recent studies of two enzyme systems, myosin and adenylate kinase (AK), we discuss how atomistic and coarse-grained simulations can be used to provide insights into the mechanism of activation transitions in realistic systems. Collectively, the results suggest that although many allosteric transitions can be viewed as domain displacements mediated by flexible hinges, there are additional complexities and various deviations. For example, although our studies do not find any evidence for "cracking" in AK, our results do underline the contribution of intra-domain properties (e.g., dihedral flexibility) to the rate of the transition. The study of mechanochemical coupling in myosin highlights that local changes important to chemistry require stabilization from more extensive structural changes; in this sense, more global structural transitions are needed to activate the chemistry in the active site. These discussions further emphasize the importance of better understanding factors that control the degree of co-operativity for allosteric transitions, again hinting at the intimate connection between protein stability and functional flexibility. Finally, a number of topics of considerable future interest are briefly discussed.

Design of Heteronuclear Metalloenzymes

PubMed Central

Bhagi-Damodaran, Ambika; Hosseinzadeh, Parisa; Mirts, Evan; Reed, Julian; Petrik, Igor D.; Lu, Yi

2016-01-01

Heteronuclear metalloenzymes catalyze some of the most fundamentally interesting and practically useful reactions in nature. However, the presence of two or more metal ions in close proximity in these enzymes makes them more difficult to prepare and study than homonuclear metalloenzymes. To meet these challenges, heteronuclear metal centers have been designed into small and stable proteins with rigid scaffolds to understand how these heteronuclear centers are constructed and the mechanism of their function. This chapter describes methods for designing heterobinuclear metal centers in a protein scaffold by giving specific examples of a few heme-nonheme bimetallic centers engineered in myoglobin and cytochrome c peroxidase. We provide step-by-step procedure on how to choose the protein scaffold, design a heterobinuclear metal center in the protein computationally, incorporate metal centers in the protein and characterize the resulting metalloprotein, both structurally and functionally. Finally, we discuss how an initial design can be further improved by rationally tuning its secondary coordination sphere, electron/proton transfer rates, and the substrate affinity. PMID:27586347

Characterization of a restriction modification system from the commensal Escherichia coli strain A0 34/86 (O83:K24:H31).

PubMed

Weiserová, Marie; Ryu, Junichi

2008-06-27

Type I restriction-modification (R-M) systems are the most complex restriction enzymes discovered to date. Recent years have witnessed a renaissance of interest in R-M enzymes Type I. The massive ongoing sequencing programmes leading to discovery of, so far, more than 1 000 putative enzymes in a broad range of microorganisms including pathogenic bacteria, revealed that these enzymes are widely represented in nature. The aim of this study was characterisation of a putative R-M system EcoA0ORF42P identified in the commensal Escherichia coli A0 34/86 (O83: K24: H31) strain, which is efficiently used at Czech paediatric clinics for prophylaxis and treatment of nosocomial infections and diarrhoea of preterm and newborn infants. We have characterised a restriction-modification system EcoA0ORF42P of the commensal Escherichia coli strain A0 34/86 (O83: K24: H31). This system, designated as EcoAO83I, is a new functional member of the Type IB family, whose specificity differs from those of known Type IB enzymes, as was demonstrated by an immunological cross-reactivity and a complementation assay. Using the plasmid transformation method and the RM search computer program, we identified the DNA recognition sequence of the EcoAO83I as GGA(8N)ATGC. In consistence with the amino acids alignment data, the 3' TRD component of the recognition sequence is identical to the sequence recognized by the EcoEI enzyme. The A-T (modified adenine) distance is identical to that in the EcoAI and EcoEI recognition sites, which also indicates that this system is a Type IB member. Interestingly, the recognition sequence we determined here is identical to the previously reported prototype sequence for Eco377I and its isoschizomers. Putative restriction-modification system EcoA0ORF42P in the commensal Escherichia coli strain A0 34/86 (O83: K24: H31) was found to be a member of the Type IB family and was designated as EcoAO83I. Combination of the classical biochemical and bacterial genetics approaches with comparative genomics might contribute effectively to further classification of many other putative Type-I enzymes, especially in clinical samples.

Methods for Efficiently and Accurately Computing Quantum Mechanical Free Energies for Enzyme Catalysis.

PubMed

Kearns, F L; Hudson, P S; Boresch, S; Woodcock, H L

2016-01-01

Enzyme activity is inherently linked to free energies of transition states, ligand binding, protonation/deprotonation, etc.; these free energies, and thus enzyme function, can be affected by residue mutations, allosterically induced conformational changes, and much more. Therefore, being able to predict free energies associated with enzymatic processes is critical to understanding and predicting their function. Free energy simulation (FES) has historically been a computational challenge as it requires both the accurate description of inter- and intramolecular interactions and adequate sampling of all relevant conformational degrees of freedom. The hybrid quantum mechanical molecular mechanical (QM/MM) framework is the current tool of choice when accurate computations of macromolecular systems are essential. Unfortunately, robust and efficient approaches that employ the high levels of computational theory needed to accurately describe many reactive processes (ie, ab initio, DFT), while also including explicit solvation effects and accounting for extensive conformational sampling are essentially nonexistent. In this chapter, we will give a brief overview of two recently developed methods that mitigate several major challenges associated with QM/MM FES: the QM non-Boltzmann Bennett's acceptance ratio method and the QM nonequilibrium work method. We will also describe usage of these methods to calculate free energies associated with (1) relative properties and (2) along reaction paths, using simple test cases with relevance to enzymes examples. © 2016 Elsevier Inc. All rights reserved.

Mathematical model for internal pH control in immobilized enzyme particles

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

Liou, J.K.; Rousseau, I.

A mathematical model has been developed for the internal pH control in immobilized enzyme particles. This model describes the kinetics of a coupled system of two enzymes, immobilized in particles of either planar, cylindrical, or spherical shape. The enzyme kinetics are assumed to be of a mixed type, including Michaelis-Menten kinetics, uncompetitive substrate inhibition, and competitive and noncompetitive product inhibition. In a case study we have considered the enzyme combination urease and penicillin acylase, whose kinetics are coupled through the pH dependence of the kinetic parameters. The hydrolysis of urea by urease yields ammonia and carbon dioxide, whereas benzylpenicillin (Pen-G)more » is converted to 6-animo penicillanic acid and phenyl acetic acid by penicillin acylase. The production of acids by the latter enzyme will cause a decrease in pH. Because of the presence of the ammonia-carbon dioxide system, however, the pH may be kept under control. In order to obtain information about the optimum performance of this enzymatic pH controller, we have computed the effectiveness factor and the conversion in a CSTR at different enzyme loadings. The results of the computer simulations indicate that a high conversion of Pen-G may be achieved (80-90%) at bulk pH values of about 7.5 - 8. 27 references.« less

Chemical and protein structural basis for biological crosstalk between PPAR α and COX enzymes

NASA Astrophysics Data System (ADS)

Cleves, Ann E.; Jain, Ajay N.

2015-02-01

We have previously validated a probabilistic framework that combined computational approaches for predicting the biological activities of small molecule drugs. Molecule comparison methods included molecular structural similarity metrics and similarity computed from lexical analysis of text in drug package inserts. Here we present an analysis of novel drug/target predictions, focusing on those that were not obvious based on known pharmacological crosstalk. Considering those cases where the predicted target was an enzyme with known 3D structure allowed incorporation of information from molecular docking and protein binding pocket similarity in addition to ligand-based comparisons. Taken together, the combination of orthogonal information sources led to investigation of a surprising predicted relationship between a transcription factor and an enzyme, specifically, PPAR α and the cyclooxygenase enzymes. These predictions were confirmed by direct biochemical experiments which validate the approach and show for the first time that PPAR α agonists are cyclooxygenase inhibitors.

Hydride Transfer in DHFR by Transition Path Sampling, Kinetic Isotope Effects, and Heavy Enzyme Studies

PubMed Central

Wang, Zhen; Antoniou, Dimitri; Schwartz, Steven D.; Schramm, Vern L.

2016-01-01

Escherichia coli dihydrofolate reductase (ecDHFR) is used to study fundamental principles of enzyme catalysis. It remains controversial whether fast protein motions are coupled to the hydride transfer catalyzed by ecDHFR. Previous studies with heavy ecDHFR proteins labeled with 13C, 15N, and nonexchangeable 2H reported enzyme mass-dependent hydride transfer kinetics for ecDHFR. Here, we report refined experimental and computational studies to establish that hydride transfer is independent of protein mass. Instead, we found the rate constant for substrate dissociation to be faster for heavy DHFR. Previously reported kinetic differences between light and heavy DHFRs likely arise from kinetic steps other than the chemical step. This study confirms that fast (femtosecond to picosecond) protein motions in ecDHFR are not coupled to hydride transfer and provides an integrative computational and experimental approach to resolve fast dynamics coupled to chemical steps in enzyme catalysis. PMID:26652185

Computational methods in sequence and structure prediction

NASA Astrophysics Data System (ADS)

Lang, Caiyi

This dissertation is organized into two parts. In the first part, we will discuss three computational methods for cis-regulatory element recognition in three different gene regulatory networks as the following: (a) Using a comprehensive "Phylogenetic Footprinting Comparison" method, we will investigate the promoter sequence structures of three enzymes (PAL, CHS and DFR) that catalyze sequential steps in the pathway from phenylalanine to anthocyanins in plants. Our result shows there exists a putative cis-regulatory element "AC(C/G)TAC(C)" in the upstream of these enzyme genes. We propose this cis-regulatory element to be responsible for the genetic regulation of these three enzymes and this element, might also be the binding site for MYB class transcription factor PAP1. (b) We will investigate the role of the Arabidopsis gene glutamate receptor 1.1 (AtGLR1.1) in C and N metabolism by utilizing the microarray data we obtained from AtGLR1.1 deficient lines (antiAtGLR1.1). We focus our investigation on the putatively co-regulated transcript profile of 876 genes we have collected in antiAtGLR1.1 lines. By (a) scanning the occurrence of several groups of known abscisic acid (ABA) related cisregulatory elements in the upstream regions of 876 Arabidopsis genes; and (b) exhaustive scanning of all possible 6-10 bps motif occurrence in the upstream regions of the same set of genes, we are able to make a quantative estimation on the enrichment level of each of the cis-regulatory element candidates. We finally conclude that one specific cis-regulatory element group, called "ABRE" elements, are statistically highly enriched within the 876-gene group as compared to their occurrence within the genome. (c) We will introduce a new general purpose algorithm, called "fuzzy REDUCE1", which we have developed recently for automated cis-regulatory element identification. In the second part, we will discuss our newly devised protein design framework. With this framework we have developed a software package which is capable of designing novel protein structures at the atomic resolution. This software package allows us to perform protein structure design with a flexible backbone. The backbone flexibility includes loop region relaxation as well as a secondary structure collective mode relaxation scheme. (Abstract shortened by UMI.)

Misunderstanding the preorganization concept can lead to confusions about the origin of enzyme catalysis.

PubMed

Jindal, Garima; Warshel, Arieh

2017-12-01

Understanding the origin of the catalytic power of enzymes has both conceptual and practical importance. One of the most important finding from computational studies of enzyme catalysis is that a major part of the catalytic power is due to the preorganization of the enzyme active site. Unfortunately, misunderstanding of the nontrivial preorganization idea lead some to assume that it does not consider the effect of the protein residues. This major confusion reflects a misunderstanding of the statement that the interaction energy of the enzyme group and the transition state (TS) is similar to the corresponding interaction between the water molecules (in the reference system) and the TS, and that the catalysis is due to the reorganization free energy of the water molecules. Obviously, this finding does not mean that we do not consider the enzyme groups. Another problem is the idea that catalysis is due to substrate preorganization. This more traditional idea is based in some cases on inconsistent interpretation of the action of model compounds, which unfortunately, do not reflect the actual situation in the enzyme active site. The present article addresses the above problems, clarifying first the enzyme polar preorganization idea and the current misunderstandings. Next we take a specific model compound that was used to promote the substrate preorganization proposal and establish its irrelevance to enzyme catalysis. Overall, we show that the origin of the catalytic power of enzymes cannot be assessed uniquely without computer simulations, since at present this is the only way of relating structure and energetics. © 2017 Wiley Periodicals, Inc.

The Enzyme Function Initiative†

PubMed Central

Gerlt, John A.; Allen, Karen N.; Almo, Steven C.; Armstrong, Richard N.; Babbitt, Patricia C.; Cronan, John E.; Dunaway-Mariano, Debra; Imker, Heidi J.; Jacobson, Matthew P.; Minor, Wladek; Poulter, C. Dale; Raushel, Frank M.; Sali, Andrej; Shoichet, Brian K.; Sweedler, Jonathan V.

2011-01-01

The Enzyme Function Initiative (EFI) was recently established to address the challenge of assigning reliable functions to enzymes discovered in bacterial genome projects; in this Current Topic we review the structure and operations of the EFI. The EFI includes the Superfamily/Genome, Protein, Structure, Computation, and Data/Dissemination Cores that provide the infrastructure for reliably predicting the in vitro functions of unknown enzymes. The initial targets for functional assignment are selected from five functionally diverse superfamilies (amidohydrolase, enolase, glutathione transferase, haloalkanoic acid dehalogenase, and isoprenoid synthase), with five superfamily-specific Bridging Projects experimentally testing the predicted in vitro enzymatic activities. The EFI also includes the Microbiology Core that evaluates the in vivo context of in vitro enzymatic functions and confirms the functional predictions of the EFI. The deliverables of the EFI to the scientific community include: 1) development of a large-scale, multidisciplinary sequence/structure-based strategy for functional assignment of unknown enzymes discovered in genome projects (target selection, protein production, structure determination, computation, experimental enzymology, microbiology, and structure-based annotation); 2) dissemination of the strategy to the community via publications, collaborations, workshops, and symposia; 3) computational and bioinformatic tools for using the strategy; 4) provision of experimental protocols and/or reagents for enzyme production and characterization; and 5) dissemination of data via the EFI’s website, enzymefunction.org. The realization of multidisciplinary strategies for functional assignment will begin to define the full metabolic diversity that exists in nature and will impact basic biochemical and evolutionary understanding, as well as a wide range of applications of central importance to industrial, medicinal and pharmaceutical efforts. PMID:21999478

The Enzyme Function Initiative.

PubMed

Gerlt, John A; Allen, Karen N; Almo, Steven C; Armstrong, Richard N; Babbitt, Patricia C; Cronan, John E; Dunaway-Mariano, Debra; Imker, Heidi J; Jacobson, Matthew P; Minor, Wladek; Poulter, C Dale; Raushel, Frank M; Sali, Andrej; Shoichet, Brian K; Sweedler, Jonathan V

2011-11-22

The Enzyme Function Initiative (EFI) was recently established to address the challenge of assigning reliable functions to enzymes discovered in bacterial genome projects; in this Current Topic, we review the structure and operations of the EFI. The EFI includes the Superfamily/Genome, Protein, Structure, Computation, and Data/Dissemination Cores that provide the infrastructure for reliably predicting the in vitro functions of unknown enzymes. The initial targets for functional assignment are selected from five functionally diverse superfamilies (amidohydrolase, enolase, glutathione transferase, haloalkanoic acid dehalogenase, and isoprenoid synthase), with five superfamily specific Bridging Projects experimentally testing the predicted in vitro enzymatic activities. The EFI also includes the Microbiology Core that evaluates the in vivo context of in vitro enzymatic functions and confirms the functional predictions of the EFI. The deliverables of the EFI to the scientific community include (1) development of a large-scale, multidisciplinary sequence/structure-based strategy for functional assignment of unknown enzymes discovered in genome projects (target selection, protein production, structure determination, computation, experimental enzymology, microbiology, and structure-based annotation), (2) dissemination of the strategy to the community via publications, collaborations, workshops, and symposia, (3) computational and bioinformatic tools for using the strategy, (4) provision of experimental protocols and/or reagents for enzyme production and characterization, and (5) dissemination of data via the EFI's Website, http://enzymefunction.org. The realization of multidisciplinary strategies for functional assignment will begin to define the full metabolic diversity that exists in nature and will impact basic biochemical and evolutionary understanding, as well as a wide range of applications of central importance to industrial, medicinal, and pharmaceutical efforts. © 2011 American Chemical Society

Tryptophan as a Molecular Shovel in the Glycosyl Transfer Activity of Trypanosoma cruzi Trans-sialidase

PubMed Central

Mitchell, Felicity L.; Miles, Steven M.; Neres, João; Bichenkova, Elena V.; Bryce, Richard A.

2010-01-01

Abstract Molecular dynamics investigations into active site plasticity of Trypanosoma cruzi trans-sialidase, a protein implicated in Chagas disease, suggest that movement of the Trp312 loop plays an important role in the enzyme's sialic acid transfer mechanism. The observed Trp312 flexibility equates to a molecular shovel action, which leads to the expulsion of the donor aglycone leaving group from the catalytic site. These computational simulations provide detailed structural insights into sialyl transfer by the trans-sialidase and may aid the design of inhibitors effective against this neglected tropical disease. PMID:20441732

Support vector machine prediction of enzyme function with conjoint triad feature and hierarchical context.

PubMed

Wang, Yong-Cui; Wang, Yong; Yang, Zhi-Xia; Deng, Nai-Yang

2011-06-20

Enzymes are known as the largest class of proteins and their functions are usually annotated by the Enzyme Commission (EC), which uses a hierarchy structure, i.e., four numbers separated by periods, to classify the function of enzymes. Automatically categorizing enzyme into the EC hierarchy is crucial to understand its specific molecular mechanism. In this paper, we introduce two key improvements in predicting enzyme function within the machine learning framework. One is to introduce the efficient sequence encoding methods for representing given proteins. The second one is to develop a structure-based prediction method with low computational complexity. In particular, we propose to use the conjoint triad feature (CTF) to represent the given protein sequences by considering not only the composition of amino acids but also the neighbor relationships in the sequence. Then we develop a support vector machine (SVM)-based method, named as SVMHL (SVM for hierarchy labels), to output enzyme function by fully considering the hierarchical structure of EC. The experimental results show that our SVMHL with the CTF outperforms SVMHL with the amino acid composition (AAC) feature both in predictive accuracy and Matthew's correlation coefficient (MCC). In addition, SVMHL with the CTF obtains the accuracy and MCC ranging from 81% to 98% and 0.82 to 0.98 when predicting the first three EC digits on a low-homologous enzyme dataset. We further demonstrate that our method outperforms the methods which do not take account of hierarchical relationship among enzyme categories and alternative methods which incorporate prior knowledge about inter-class relationships. Our structure-based prediction model, SVMHL with the CTF, reduces the computational complexity and outperforms the alternative approaches in enzyme function prediction. Therefore our new method will be a useful tool for enzyme function prediction community.

Designing safer chemicals: Predicting the rates of metabolism of halogenated alkanes

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

Yin, H.; Anders, M.W.; Higgins, L.

1995-11-21

A computational model is presented that can be used as a tool in the design of safer chemicals. This model predicts that rate of hydrogen-atom abstraction by cytochrome P450 enzymes. Excellent correlations between biotransformation rates and the calculated activation energies ({Delta}H{sub act}) of the cytochrome P450-mediated hydrogen-atom abstractions were obtained for the in vitro biotransformation of six halogenated alkanes (1-fluoro-1,1,1,2,2-tetrachloroethane, 1,1,1,2-tetrafluoro-2-chloroethane, 1,1,1,2,2-pentafluoroethane, and 2-bromo-2-chloro-1,1,1-trifluoroethane) with both rat and human enzyme preparations: (rate, human CYP2E1) = 44.99 - 1.79 ({Delta}H{sub act}), r{sup 2} = 0.86; In (rate, human Cyp2E1)= 46399 -1.77 ({Delta}H{sub act}), r{sup 2} = 0.97 (rates are in nmolmore » of product per min per nmol of cytochrome P450 and energies are in kcal/mol). Correlations were also obtained for five inhalation anesthetics (enflurane, sevoflurane, desflurane, methoxyflurane, and isoflurane) for both in vivo and in vitro data have been shown to agree in any species. The model presented herein provides an archetype for the methodology that may be used in the future design of safer chemicals, particularly hydrochlorofluorocarbons and inhalation anesthetics. 41 refs., 1 fig., 2 tabs.« less

Analog Computer Laboratory with Biological Examples.

ERIC Educational Resources Information Center

Strebel, Donald E.

1979-01-01

The use of biological examples in teaching applications of the analog computer is discussed and several examples from mathematical ecology, enzyme kinetics, and tracer dynamics are described. (Author/GA)

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.

'Enzyme Test Bench': A biochemical application of the multi-rate modeling

NASA Astrophysics Data System (ADS)

Rachinskiy, K.; Schultze, H.; Boy, M.; Büchs, J.

2008-11-01

In the expanding field of 'white biotechnology' enzymes are frequently applied to catalyze the biochemical reaction from a resource material to a valuable product. Evolutionary designed to catalyze the metabolism in any life form, they selectively accelerate complex reactions under physiological conditions. Modern techniques, such as directed evolution, have been developed to satisfy the increasing demand on enzymes. Applying these techniques together with rational protein design, we aim at improving of enzymes' activity, selectivity and stability. To tap the full potential of these techniques, it is essential to combine them with adequate screening methods. Nowadays a great number of high throughput colorimetric and fluorescent enzyme assays are applied to measure the initial enzyme activity with high throughput. However, the prediction of enzyme long term stability within short experiments is still a challenge. A new high throughput technique for enzyme characterization with specific attention to the long term stability, called 'Enzyme Test Bench', is presented. The concept of the Enzyme Test Bench consists of short term enzyme tests conducted under partly extreme conditions to predict the enzyme long term stability under moderate conditions. The technique is based on the mathematical modeling of temperature dependent enzyme activation and deactivation. Adapting the temperature profiles in sequential experiments by optimum non-linear experimental design, the long term deactivation effects can be purposefully accelerated and detected within hours. During the experiment the enzyme activity is measured online to estimate the model parameters from the obtained data. Thus, the enzyme activity and long term stability can be calculated as a function of temperature. The results of the characterization, based on micro liter format experiments of hours, are in good agreement with the results of long term experiments in 1L format. Thus, the new technique allows for both: the enzyme screening with regard to the long term stability and the choice of the optimal process temperature. The presented article gives a successful example for the application of multi-rate modeling, experimental design and parameter estimation within biochemical engineering. At the same time, it shows the limitations of the methods at the state of the art and addresses the current problems to the applied mathematics community.

Quantitative Enzymatic and Immunologic Histophotometry of Diseased Human Kid-Ney Tissues Using Tv-Camera and Computer Assisted Image Processing Systems.

NASA Astrophysics Data System (ADS)

Heinert, G.; Mondorf, W.

1982-11-01

High speed image processing was used to analyse morphologic and metabolic characteristics of clinically relevant kidney tissue alterations.Qualitative computer-assisted histophotometry was performed to measure alterations in levels of the enzymes alkaline phosphatase (Ap),alanine aminopeptidase (AAP),g-glutamyltranspepti-dase (GGTP) and A-glucuronidase (B-G1) and AAP and GGTP immunologically determined in prepared renal and cancer tissue sections. A "Mioro-Videomat 2" image analysis system with a "Tessovar" macroscope,a computer-assisted "Axiomat" photomicroscope and an "Interactive Image Analysis System (IBAS)" were employed for analysing changes in enzyme activities determined by changes in absorbance or transmission.Diseased kidney as well as renal neoplastic tissues could be distinguished by significantly (wilcoxon test,p<0,05) decreased enzyme concentrations as compared to those found in normal human kidney tissues.This image analysis techniques might be of potential use in diagnostic and prognostic evaluation of renal cancer and diseased kidney tissues.

Assay for Angiotensin-Converting Enzyme.

ERIC Educational Resources Information Center

Russo, Salvatore F.

1983-01-01

Describes a three-hour experiment designed to introduce students to chemistry of the angiotensis-converting enzyme, illustrate design of a quenched fluorescence substrate, and examine considerations necessary in designing a clinical assay. Includes background information on the biochemistry of hypertension, reagents/materials needed, procedures…

Proteins with Novel Structure, Function and Dynamics

NASA Technical Reports Server (NTRS)

Pohorille, Andrew

2014-01-01

Recently, a small enzyme that ligates two RNA fragments with the rate of 10(exp 6) above background was evolved in vitro (Seelig and Szostak, Nature 448:828-831, 2007). This enzyme does not resemble any contemporary protein (Chao et al., Nature Chem. Biol. 9:81-83, 2013). It consists of a dynamic, catalytic loop, a small, rigid core containing two zinc ions coordinated by neighboring amino acids, and two highly flexible tails that might be unimportant for protein function. In contrast to other proteins, this enzyme does not contain ordered secondary structure elements, such as alpha-helix or beta-sheet. The loop is kept together by just two interactions of a charged residue and a histidine with a zinc ion, which they coordinate on the opposite side of the loop. Such structure appears to be very fragile. Surprisingly, computer simulations indicate otherwise. As the coordinating, charged residue is mutated to alanine, another, nearby charged residue takes its place, thus keeping the structure nearly intact. If this residue is also substituted by alanine a salt bridge involving two other, charged residues on the opposite sides of the loop keeps the loop in place. These adjustments are facilitated by high flexibility of the protein. Computational predictions have been confirmed experimentally, as both mutants retain full activity and overall structure. These results challenge our notions about what is required for protein activity and about the relationship between protein dynamics, stability and robustness. We hypothesize that small, highly dynamic proteins could be both active and fault tolerant in ways that many other proteins are not, i.e. they can adjust to retain their structure and activity even if subjected to mutations in structurally critical regions. This opens the doors for designing proteins with novel functions, structures and dynamics that have not been yet considered.

A biomimetic colorimetric logic gate system based on multi-functional peptide-mediated gold nanoparticle assembly.

PubMed

Li, Yong; Li, Wang; He, Kai-Yu; Li, Pei; Huang, Yan; Nie, Zhou; Yao, Shou-Zhuo

2016-04-28

In natural biological systems, proteins exploit various functional peptide motifs to exert target response and activity switch, providing a functional and logic basis for complex cellular activities. Building biomimetic peptide-based bio-logic systems is highly intriguing but remains relatively unexplored due to limited logic recognition elements and complex signal outputs. In this proof-of-principle work, we attempted to address these problems by utilizing multi-functional peptide probes and the peptide-mediated nanoparticle assembly system. Here, the rationally designed peptide probes function as the dual-target responsive element specifically responsive to metal ions and enzymes as well as the mediator regulating the assembly of gold nanoparticles (AuNPs). Taking advantage of Zn2+ ions and chymotrypsin as the model inputs of metal ions and enzymes, respectively, we constructed the peptide logic system computed by the multi-functional peptide probes and outputted by the readable colour change of AuNPs. In this way, the representative binary basic logic gates (AND, OR, INHIBIT, NAND, IMPLICATION) have been achieved by delicately coding the peptide sequence, demonstrating the versatility of our logic system. Additionally, we demonstrated that the three-input combinational logic gate (INHIBIT-OR) could also be successfully integrated and applied as a multi-tasking biosensor for colorimetric detection of dual targets. This nanoparticle-based peptide logic system presents a valid strategy to illustrate peptide information processing and provides a practical platform for executing peptide computing or peptide-related multiplexing sensing, implying that the controllable nanomaterial assembly is a promising and potent methodology for the advancement of biomimetic bio-logic computation.

cuRRBS: simple and robust evaluation of enzyme combinations for reduced representation approaches.

PubMed

Martin-Herranz, Daniel E; Ribeiro, António J M; Krueger, Felix; Thornton, Janet M; Reik, Wolf; Stubbs, Thomas M

2017-11-16

DNA methylation is an important epigenetic modification in many species that is critical for development, and implicated in ageing and many complex diseases, such as cancer. Many cost-effective genome-wide analyses of DNA modifications rely on restriction enzymes capable of digesting genomic DNA at defined sequence motifs. There are hundreds of restriction enzyme families but few are used to date, because no tool is available for the systematic evaluation of restriction enzyme combinations that can enrich for certain sites of interest in a genome. Herein, we present customised Reduced Representation Bisulfite Sequencing (cuRRBS), a novel and easy-to-use computational method that solves this problem. By computing the optimal enzymatic digestions and size selection steps required, cuRRBS generalises the traditional MspI-based Reduced Representation Bisulfite Sequencing (RRBS) protocol to all restriction enzyme combinations. In addition, cuRRBS estimates the fold-reduction in sequencing costs and provides a robustness value for the personalised RRBS protocol, allowing users to tailor the protocol to their experimental needs. Moreover, we show in silico that cuRRBS-defined restriction enzymes consistently out-perform MspI digestion in many biological systems, considering both CpG and CHG contexts. Finally, we have validated the accuracy of cuRRBS predictions for single and double enzyme digestions using two independent experimental datasets. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Biologically inspired design of feedback control systems implemented using DNA strand displacement reactions.

PubMed

Foo, Mathias; Sawlekar, Rucha; Kulkarni, Vishwesh V; Bates, Declan G

2016-08-01

The use of abstract chemical reaction networks (CRNs) as a modelling and design framework for the implementation of computing and control circuits using enzyme-free, entropy driven DNA strand displacement (DSD) reactions is starting to garner widespread attention in the area of synthetic biology. Previous work in this area has demonstrated the theoretical plausibility of using this approach to design biomolecular feedback control systems based on classical proportional-integral (PI) controllers, which may be constructed from CRNs implementing gain, summation and integrator operators. Here, we propose an alternative design approach that utilises the abstract chemical reactions involved in cellular signalling cycles to implement a biomolecular controller - termed a signalling-cycle (SC) controller. We compare the performance of the PI and SC controllers in closed-loop with a nonlinear second-order chemical process. Our results show that the SC controller outperforms the PI controller in terms of both performance and robustness, and also requires fewer abstract chemical reactions to implement, highlighting its potential usefulness in the construction of biomolecular control circuits.

Computer-aided design of DNA origami structures.

PubMed

Selnihhin, Denis; Andersen, Ebbe Sloth

2015-01-01

The DNA origami method enables the creation of complex nanoscale objects that can be used to organize molecular components and to function as reconfigurable mechanical devices. Of relevance to synthetic biology, DNA origami structures can be delivered to cells where they can perform complicated sense-and-act tasks, and can be used as scaffolds to organize enzymes for enhanced synthesis. The design of DNA origami structures is a complicated matter and is most efficiently done using dedicated software packages. This chapter describes a procedure for designing DNA origami structures using a combination of state-of-the-art software tools. First, we introduce the basic method for calculating crossover positions between DNA helices and the standard crossover patterns for flat, square, and honeycomb DNA origami lattices. Second, we provide a step-by-step tutorial for the design of a simple DNA origami biosensor device, from schematic idea to blueprint creation and to 3D modeling and animation, and explain how careful modeling can facilitate later experimentation in the laboratory.

Computer Series, 15: Bits and Pieces, 4.

ERIC Educational Resources Information Center

Moore, John W., Ed.

1981-01-01

Supplies short descriptions of several computer applications in the college science classroom and laboratory, including: applications; interfacing and data collection with the TRS-80; programs for activity corrections in acid/base and precipitation titration curve calculations; computer-assisted data analysis of enzyme kinetics; and microcomputer…

Kinetic modeling of cellulosic biomass to ethanol via simultaneous saccharification and fermentation: Part I. Accommodation of intermittent feeding and analysis of staged reactors.

PubMed

Shao, Xiongjun; Lynd, Lee; Wyman, Charles; Bakker, André

2009-01-01

The model of South et al. [South et al. (1995) Enzyme Microb Technol 17(9): 797-803] for simultaneous saccharification of fermentation of cellulosic biomass is extended and modified to accommodate intermittent feeding of substrate and enzyme, cascade reactor configurations, and to be more computationally efficient. A dynamic enzyme adsorption model is found to be much more computationally efficient than the equilibrium model used previously, thus increasing the feasibility of incorporating the kinetic model in a computational fluid dynamic framework in the future. For continuous or discretely fed reactors, it is necessary to use particle conversion in conversion-dependent hydrolysis rate laws rather than reactor conversion. Whereas reactor conversion decreases due to both reaction and exit of particles from the reactor, particle conversion decreases due to reaction only. Using the modified models, it is predicted that cellulose conversion increases with decreasing feeding frequency (feedings per residence time, f). A computationally efficient strategy for modeling cascade reactors involving a modified rate constant is shown to give equivalent results relative to an exhaustive approach considering the distribution of particles in each successive fermenter.

Taking the Mystery Out of Enzymes.

ERIC Educational Resources Information Center

DeYoung, H. Garrett

1984-01-01

Discusses structure and function of enzymes, design of new enzymes and enzyme substitutes, and enzyme uses in industry, medicine, and wastewater treatment. The latter is a low-cost method which can remove as much as 99 percent of toxic substances found in many industrial wastewater streams. (JN)

CoMFA, LeapFrog and blind docking studies on sulfonanilide derivatives acting as selective aromatase expression regulators.

PubMed

Gueto, Carlos; Torres, Juan; Vivas-Reyes, Ricardo

2009-09-01

Aromatase, the enzyme responsible for estrogen biosynthesis, is an attractive target in the treatment of hormone-dependent breast cancer. In this manuscript, the structure-based drug design approach of sulfonanilide analogues as potential selective aromatase expression regulators (SAERs) is described. Receptor-independent CoMFA (Comparative Molecular Field Analysis) maps were employed for generating a pseudocavity for LeapFrog calculation. A robust model, using 45 and 10 molecules in the training and test sets, respectively, was developed producing statistically significant results with cross-validated and conventional correlation coefficients of 0.656 and 0.956, respectively. This model was used to predict the activity of newly proposed molecules as SAERs candidates being two magnitude orders more potent than the previously reported compounds. Also in the present study, the computational blind docking method using eHiTS is tested on molecules study group and COX-2 enzyme. Future perspectives of the method in the screening of SAERs candidates with no COX-2 inhibitory activity are discussed.

De Novo Enzyme Design Using Rosetta3

PubMed Central

Richter, Florian; Leaver-Fay, Andrew; Khare, Sagar D.; Bjelic, Sinisa; Baker, David

2011-01-01

The Rosetta de novo enzyme design protocol has been used to design enzyme catalysts for a variety of chemical reactions, and in principle can be applied to any arbitrary chemical reaction of interest, The process has four stages: 1) choice of a catalytic mechanism and corresponding minimal model active site, 2) identification of sites in a set of scaffold proteins where this minimal active site can be realized, 3) optimization of the identities of the surrounding residues for stabilizing interactions with the transition state and primary catalytic residues, and 4) evaluation and ranking the resulting designed sequences. Stages two through four of this process can be carried out with the Rosetta package, while stage one needs to be done externally. Here, we demonstrate how to carry out the Rosetta enzyme design protocol from start to end in detail using for illustration the triosephosphate isomerase reaction. PMID:21603656

Characterising Complex Enzyme Reaction Data

PubMed Central

Rahman, Syed Asad; Thornton, Janet M.

2016-01-01

The relationship between enzyme-catalysed reactions and the Enzyme Commission (EC) number, the widely accepted classification scheme used to characterise enzyme activity, is complex and with the rapid increase in our knowledge of the reactions catalysed by enzymes needs revisiting. We present a manual and computational analysis to investigate this complexity and found that almost one-third of all known EC numbers are linked to more than one reaction in the secondary reaction databases (e.g., KEGG). Although this complexity is often resolved by defining generic, alternative and partial reactions, we have also found individual EC numbers with more than one reaction catalysing different types of bond changes. This analysis adds a new dimension to our understanding of enzyme function and might be useful for the accurate annotation of the function of enzymes and to study the changes in enzyme function during evolution. PMID:26840640

Interconversion of the Specificities of Human Lysosomal Enzymes Associated with Fabry and Schindler Diseases

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

Tomasic, Ivan B.; Metcalf, Matthew C.; Guce, Abigail I.

2010-09-03

The human lysosomal enzymes {alpha}-galactosidase ({alpha}-GAL, EC 3.2.1.22) and {alpha}-N-acetylgalactosaminidase ({alpha}-NAGAL, EC 3.2.1.49) share 46% amino acid sequence identity and have similar folds. The active sites of the two enzymes share 11 of 13 amino acids, differing only where they interact with the 2-position of the substrates. Using a rational protein engineering approach, we interconverted the enzymatic specificity of {alpha}-GAL and {alpha}-NAGAL. The engineered {alpha}-GAL (which we call {alpha}-GALSA) retains the antigenicity of {alpha}-GAL but has acquired the enzymatic specificity of {alpha}-NAGAL. Conversely, the engineered {alpha}-NAGAL (which we call {alpha}-NAGAL{sup EL}) retains the antigenicity of {alpha}-NAGAL but has acquired themore » enzymatic specificity of the {alpha}-GAL enzyme. Comparison of the crystal structures of the designed enzyme {alpha}-GAL{sup SA} to the wild-type enzymes shows that active sites of {alpha}-GAL{sup SA} and {alpha}-NAGAL superimpose well, indicating success of the rational design. The designed enzymes might be useful as non-immunogenic alternatives in enzyme replacement therapy for treatment of lysosomal storage disorders such as Fabry disease.« less

Discovery of a regioselectivity switch in nitrating P450s guided by molecular dynamics simulations and Markov models

NASA Astrophysics Data System (ADS)

Dodani, Sheel C.; Kiss, Gert; Cahn, Jackson K. B.; Su, Ye; Pande, Vijay S.; Arnold, Frances H.

2016-05-01

The dynamic motions of protein structural elements, particularly flexible loops, are intimately linked with diverse aspects of enzyme catalysis. Engineering of these loop regions can alter protein stability, substrate binding and even dramatically impact enzyme function. When these flexible regions are unresolvable structurally, computational reconstruction in combination with large-scale molecular dynamics simulations can be used to guide the engineering strategy. Here we present a collaborative approach that consists of both experiment and computation and led to the discovery of a single mutation in the F/G loop of the nitrating cytochrome P450 TxtE that simultaneously controls loop dynamics and completely shifts the enzyme's regioselectivity from the C4 to the C5 position of L-tryptophan. Furthermore, we find that this loop mutation is naturally present in a subset of homologous nitrating P450s and confirm that these uncharacterized enzymes exclusively produce 5-nitro-L-tryptophan, a previously unknown biosynthetic intermediate.

Programming Enzyme-Initiated Autonomous DNAzyme Nanodevices in Living Cells.

PubMed

Chen, Feng; Bai, Min; Cao, Ke; Zhao, Yue; Cao, Xiaowen; Wei, Jing; Wu, Na; Li, Jiang; Wang, Lihua; Fan, Chunhai; Zhao, Yongxi

2017-12-26

Molecular nanodevices are computational assemblers that switch defined states upon external stimulation. However, interfacing artificial nanodevices with natural molecular machineries in living cells remains a great challenge. Here, we delineate a generic method for programming assembly of enzyme-initiated DNAzyme nanodevices (DzNanos). Two programs including split assembly of two partzymes and toehold exchange displacement assembly of one intact DNAzyme initiated by telomerase are computed. The intact one obtains higher assembly yield and catalytic performance ascribed to proper conformation folding and active misplaced assembly. By employing MnO 2 nanosheets as both DNA carriers and source of Mn 2+ as DNAzyme cofactor, we find that this DzNano is well assembled via a series of conformational states in living cells and operates autonomously with sustained cleavage activity. Other enzymes can also induce corresponding DzNano assembly with defined programming modules. These DzNanos not only can monitor enzyme catalysis in situ but also will enable the implementation of cellular stages, behaviors, and pathways for basic science, diagnostic, and therapeutic applications as genetic circuits.

Michael Levitt and Computational Biology

Science.gov Websites

molecular structures, compute structural changes, refine experimental structure, model enzyme catalysis and (May 2004) Top Some links on this page may take you to non-federal websites. Their policies may differ

Artificial enzymes based on supramolecular scaffolds.

PubMed

Dong, Zeyuan; Luo, Quan; Liu, Junqiu

2012-12-07

Enzymes are nanometer-sized molecules with three-dimensional structures created by the folding and self-assembly of polymeric chain-like components through supramolecular interactions. They are capable of performing catalytic functions usually accompanied by a variety of conformational states. The conformational diversities and complexities of natural enzymes exerted in catalysis seriously restrict the detailed understanding of enzymatic mechanisms in molecular terms. A supramolecular viewpoint is undoubtedly helpful in understanding the principle of enzyme catalysis. The emergence of supramolecular artificial enzymes therefore provides an alternative way to approach the structural complexity and thus to unravel the mystery of enzyme catalysis. This critical review covers the recent development of artificial enzymes designed based on supramolecular scaffolds ranging from the synthetic macrocycles to self-assembled nanometer-sized objects. Such findings are anticipated to facilitate the design of supramolecular artificial enzymes as well as their potential uses in important fields, such as manufacturing and food industries, environmental biosensors, pharmaceutics and so on.

Computational analysis of calculated physicochemical and ADMET properties of protein-protein interaction inhibitors

NASA Astrophysics Data System (ADS)

Lagorce, David; Douguet, Dominique; Miteva, Maria A.; Villoutreix, Bruno O.

2017-04-01

The modulation of PPIs by low molecular weight chemical compounds, particularly by orally bioavailable molecules, would be very valuable in numerous disease indications. However, it is known that PPI inhibitors (iPPIs) tend to have properties that are linked to poor Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) and in some cases to poor clinical outcomes. Previously reported in silico analyses of iPPIs have essentially focused on physicochemical properties but several other ADMET parameters would be important to assess. In order to gain new insights into the ADMET properties of iPPIs, computations were carried out on eight datasets collected from several databases. These datasets involve compounds targeting enzymes, GPCRs, ion channels, nuclear receptors, allosteric modulators, oral marketed drugs, oral natural product-derived marketed drugs and iPPIs. Several trends are reported that should assist the design and optimization of future PPI inhibitors, either for drug discovery endeavors or for chemical biology projects.

Load capacity improvements in nucleic acid based systems using partially open feedback control.

PubMed

Kulkarni, Vishwesh; Kharisov, Evgeny; Hovakimyan, Naira; Kim, Jongmin

2014-08-15

Synthetic biology is facilitating novel methods and components to build in vivo and in vitro circuits to better understand and re-engineer biological networks. Recently, Kim and Winfree have synthesized a remarkably elegant network of transcriptional oscillators in vitro using a modular architecture of synthetic gene analogues and a few enzymes that, in turn, could be used to drive a variety of downstream circuits and nanodevices. However, these oscillators are sensitive to initial conditions and downstream load processes. Furthermore, the oscillations are not sustained since the inherently closed design suffers from enzyme deactivation, NTP fuel exhaustion, and waste product build up. In this paper, we show that a partially open architecture in which an [Symbol: see text]1 adaptive controller, implemented inside an in silico computer that resides outside the wet-lab apparatus, can ensure sustained tunable oscillations in two specific designs of the Kim-Winfree oscillator networks. We consider two broad cases of operation: (1) the oscillator network operating in isolation and (2) the oscillator network driving a DNA tweezer subject to a variable load. In both scenarios, our simulation results show a significant improvement in the tunability and robustness of these oscillator networks. Our approach can be easily adopted to improve the loading capacity of a wide range of synthetic biological devices.

Modelling and Optimization Studies on a Novel Lipase Production by Staphylococcus arlettae through Submerged Fermentation

PubMed Central

Chauhan, Mamta; Chauhan, Rajinder Singh; Garlapati, Vijay Kumar

2013-01-01

Microbial enzymes from extremophilic regions such as hot spring serve as an important source of various stable and valuable industrial enzymes. The present paper encompasses the modeling and optimization approach for production of halophilic, solvent, tolerant, and alkaline lipase from Staphylococcus arlettae through response surface methodology integrated nature inspired genetic algorithm. Response surface model based on central composite design has been developed by considering the individual and interaction effects of fermentation conditions on lipase production through submerged fermentation. The validated input space of response surface model (with R 2 value of 96.6%) has been utilized for optimization through genetic algorithm. An optimum lipase yield of 6.5 U/mL has been obtained using binary coded genetic algorithm predicted conditions of 9.39% inoculum with the oil concentration of 10.285% in 2.99 hrs using pH of 7.32 at 38.8°C. This outcome could contribute to introducing this extremophilic lipase (halophilic, solvent, and tolerant) to industrial biotechnology sector and will be a probable choice for different food, detergent, chemical, and pharmaceutical industries. The present work also demonstrated the feasibility of statistical design tools integration with computational tools for optimization of fermentation conditions for maximum lipase production. PMID:24455210

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

Molecular Imaging of Hydrolytic Enzymes Using PET and SPECT

PubMed Central

Rempel, Brian P.; Price, Eric W.

2017-01-01

Hydrolytic enzymes are a large class of biological catalysts that play a vital role in a plethora of critical biochemical processes required to maintain human health. However, the expression and/or activity of these important enzymes can change in many different diseases and therefore represent exciting targets for the development of positron emission tomography (PET) and single-photon emission computed tomography (SPECT) radiotracers. This review focuses on recently reported radiolabeled substrates, reversible inhibitors, and irreversible inhibitors investigated as PET and SPECT tracers for imaging hydrolytic enzymes. By learning from the most successful examples of tracer development for hydrolytic enzymes, it appears that an early focus on careful enzyme kinetics and cell-based studies are key factors for identifying potentially useful new molecular imaging agents. PMID:28927325

Molecular Imaging of Hydrolytic Enzymes Using PET and SPECT.

PubMed

Rempel, Brian P; Price, Eric W; Phenix, Christopher P

2017-01-01

Hydrolytic enzymes are a large class of biological catalysts that play a vital role in a plethora of critical biochemical processes required to maintain human health. However, the expression and/or activity of these important enzymes can change in many different diseases and therefore represent exciting targets for the development of positron emission tomography (PET) and single-photon emission computed tomography (SPECT) radiotracers. This review focuses on recently reported radiolabeled substrates, reversible inhibitors, and irreversible inhibitors investigated as PET and SPECT tracers for imaging hydrolytic enzymes. By learning from the most successful examples of tracer development for hydrolytic enzymes, it appears that an early focus on careful enzyme kinetics and cell-based studies are key factors for identifying potentially useful new molecular imaging agents.

More Ideas for Monitoring Biological Experiments with the BBC Computer: Absorption Spectra, Yeast Growth, Enzyme Reactions and Animal Behaviour.

ERIC Educational Resources Information Center

Openshaw, Peter

1988-01-01

Presented are five ideas for A-level biology experiments using a laboratory computer interface. Topics investigated include photosynthesis, yeast growth, animal movements, pulse rates, and oxygen consumption and production by organisms. Includes instructions specific to the BBC computer system. (CW)

Novel 2-pheynlbenzofuran derivatives as selective butyrylcholinesterase inhibitors for Alzheimer's disease.

PubMed

Kumar, Amit; Pintus, Francesca; Di Petrillo, Amalia; Medda, Rosaria; Caria, Paola; Matos, Maria João; Viña, Dolores; Pieroni, Enrico; Delogu, Francesco; Era, Benedetta; Delogu, Giovanna L; Fais, Antonella

2018-03-13

Alzheimer's disease (AD) is a neurodegenerative disorder representing the leading cause of dementia and is affecting nearly 44 million people worldwide. AD is characterized by a progressive decline in acetylcholine levels in the cholinergic systems, which results in severe memory loss and cognitive impairments. Expression levels and activity of butyrylcholinesterase (BChE) enzyme has been noted to increase significantly in the late stages of AD, thus making it a viable drug target. A series of hydroxylated 2-phenylbenzofurans compounds were designed, synthesized and their inhibitory activities toward acetylcholinesterase (AChE) and BChE enzymes were evaluated. Two compounds (15 and 17) displayed higher inhibitory activity towards BChE with IC 50 values of 6.23 μM and 3.57 μM, and a good antioxidant activity with EC 50 values 14.9 μM and 16.7 μM, respectively. The same compounds further exhibited selective inhibitory activity against BChE over AChE. Computational studies were used to compare protein-binding pockets and evaluate the interaction fingerprints of the compound. Molecular simulations showed a conserved protein residue interaction network between the compounds, resulting in similar interaction energy values. Thus, combination of biochemical and computational approaches could represent rational guidelines for further structural modification of these hydroxy-benzofuran derivatives as future drugs for treatment of AD.

Computational Model of Adrenal Steroidogenesis to Predict Biochemical Response to Endocrine Disruptors

EPA Science Inventory

Steroids, which have an important role in a wide range of physiological processes, are synthesized primarily in the gonads and adrenal glands through a series of enzyme mediated reactions. The activity of steroidogenic enzymes can be altered by various endocrine disrupters (ED), ...

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.

Tryptophan as a molecular shovel in the glycosyl transfer activity of Trypanosoma cruzi trans-sialidase.

PubMed

Mitchell, Felicity L; Miles, Steven M; Neres, João; Bichenkova, Elena V; Bryce, Richard A

2010-05-19

Molecular dynamics investigations into active site plasticity of Trypanosoma cruzi trans-sialidase, a protein implicated in Chagas disease, suggest that movement of the Trp(312) loop plays an important role in the enzyme's sialic acid transfer mechanism. The observed Trp(312) flexibility equates to a molecular shovel action, which leads to the expulsion of the donor aglycone leaving group from the catalytic site. These computational simulations provide detailed structural insights into sialyl transfer by the trans-sialidase and may aid the design of inhibitors effective against this neglected tropical disease. Copyright (c) 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Accurate Evaluation Method of Molecular Binding Affinity from Fluctuation Frequency

NASA Astrophysics Data System (ADS)

Hoshino, Tyuji; Iwamoto, Koji; Ode, Hirotaka; Ohdomari, Iwao

2008-05-01

Exact estimation of the molecular binding affinity is significantly important for drug discovery. The energy calculation is a direct method to compute the strength of the interaction between two molecules. This energetic approach is, however, not accurate enough to evaluate a slight difference in binding affinity when distinguishing a prospective substance from dozens of candidates for medicine. Hence more accurate estimation of drug efficacy in a computer is currently demanded. Previously we proposed a concept of estimating molecular binding affinity, focusing on the fluctuation at an interface between two molecules. The aim of this paper is to demonstrate the compatibility between the proposed computational technique and experimental measurements, through several examples for computer simulations of an association of human immunodeficiency virus type-1 (HIV-1) protease and its inhibitor (an example for a drug-enzyme binding), a complexation of an antigen and its antibody (an example for a protein-protein binding), and a combination of estrogen receptor and its ligand chemicals (an example for a ligand-receptor binding). The proposed affinity estimation has proven to be a promising technique in the advanced stage of the discovery and the design of drugs.

Identification and modification of dynamical regions in proteins for alteration of enzyme catalytic effect

DOEpatents

Agarwal, Pratul K.

2015-11-24

A method for analysis, control, and manipulation for improvement of the chemical reaction rate of a protein-mediated reaction is provided. Enzymes, which typically comprise protein molecules, are very efficient catalysts that enhance chemical reaction rates by many orders of magnitude. Enzymes are widely used for a number of functions in chemical, biochemical, pharmaceutical, and other purposes. The method identifies key protein vibration modes that control the chemical reaction rate of the protein-mediated reaction, providing identification of the factors that enable the enzymes to achieve the high rate of reaction enhancement. By controlling these factors, the function of enzymes may be modulated, i.e., the activity can either be increased for faster enzyme reaction or it can be decreased when a slower enzyme is desired. This method provides an inexpensive and efficient solution by utilizing computer simulations, in combination with available experimental data, to build suitable models and investigate the enzyme activity.

Identification and modification of dynamical regions in proteins for alteration of enzyme catalytic effect

DOEpatents

Agarwal, Pratul K.

2013-04-09

A method for analysis, control, and manipulation for improvement of the chemical reaction rate of a protein-mediated reaction is provided. Enzymes, which typically comprise protein molecules, are very efficient catalysts that enhance chemical reaction rates by many orders of magnitude. Enzymes are widely used for a number of functions in chemical, biochemical, pharmaceutical, and other purposes. The method identifies key protein vibration modes that control the chemical reaction rate of the protein-mediated reaction, providing identification of the factors that enable the enzymes to achieve the high rate of reaction enhancement. By controlling these factors, the function of enzymes may be modulated, i.e., the activity can either be increased for faster enzyme reaction or it can be decreased when a slower enzyme is desired. This method provides an inexpensive and efficient solution by utilizing computer simulations, in combination with available experimental data, to build suitable models and investigate the enzyme activity.

Computational Functional Analysis of Lipid Metabolic Enzymes.

PubMed

Bagnato, Carolina; Have, Arjen Ten; Prados, María B; Beligni, María V

2017-01-01

The computational analysis of enzymes that participate in lipid metabolism has both common and unique challenges when compared to the whole protein universe. Some of the hurdles that interfere with the functional annotation of lipid metabolic enzymes that are common to other pathways include the definition of proper starting datasets, the construction of reliable multiple sequence alignments, the definition of appropriate evolutionary models, and the reconstruction of phylogenetic trees with high statistical support, particularly for large datasets. Most enzymes that take part in lipid metabolism belong to complex superfamilies with many members that are not involved in lipid metabolism. In addition, some enzymes that do not have sequence similarity catalyze similar or even identical reactions. Some of the challenges that, albeit not unique, are more specific to lipid metabolism refer to the high compartmentalization of the routes, the catalysis in hydrophobic environments and, related to this, the function near or in biological membranes.In this work, we provide guidelines intended to assist in the proper functional annotation of lipid metabolic enzymes, based on previous experiences related to the phospholipase D superfamily and the annotation of the triglyceride synthesis pathway in algae. We describe a pipeline that starts with the definition of an initial set of sequences to be used in similarity-based searches and ends in the reconstruction of phylogenies. We also mention the main issues that have to be taken into consideration when using tools to analyze subcellular localization, hydrophobicity patterns, or presence of transmembrane domains in lipid metabolic enzymes.

Optimization of Cholinesterase-Based Catalytic Bioscavengers Against Organophosphorus Agents.

PubMed

Lushchekina, Sofya V; Schopfer, Lawrence M; Grigorenko, Bella L; Nemukhin, Alexander V; Varfolomeev, Sergei D; Lockridge, Oksana; Masson, Patrick

2018-01-01

Organophosphorus agents (OPs) are irreversible inhibitors of acetylcholinesterase (AChE). OP poisoning causes major cholinergic syndrome. Current medical counter-measures mitigate the acute effects but have limited action against OP-induced brain damage. Bioscavengers are appealing alternative therapeutic approach because they neutralize OPs in bloodstream before they reach physiological targets. First generation bioscavengers are stoichiometric bioscavengers. However, stoichiometric neutralization requires administration of huge doses of enzyme. Second generation bioscavengers are catalytic bioscavengers capable of detoxifying OPs with a turnover. High bimolecular rate constants ( k cat / K m > 10 6 M -1 min -1 ) are required, so that low enzyme doses can be administered. Cholinesterases (ChE) are attractive candidates because OPs are hemi-substrates. Moderate OP hydrolase (OPase) activity has been observed for certain natural ChEs and for G117H-based human BChE mutants made by site-directed mutagenesis. However, before mutated ChEs can become operational catalytic bioscavengers their dephosphylation rate constant must be increased by several orders of magnitude. New strategies for converting ChEs into fast OPase are based either on combinational approaches or on computer redesign of enzyme. The keystone for rational conversion of ChEs into OPases is to understand the reaction mechanisms with OPs. In the present work we propose that efficient OP hydrolysis can be achieved by re-designing the configuration of enzyme active center residues and by creating specific routes for attack of water molecules and proton transfer. Four directions for nucleophilic attack of water on phosphorus atom were defined. Changes must lead to a novel enzyme, wherein OP hydrolysis wins over competing aging reactions. Kinetic, crystallographic, and computational data have been accumulated that describe mechanisms of reactions involving ChEs. From these studies, it appears that introducing new groups that create a stable H-bonded network susceptible to activate and orient water molecule, stabilize transition states (TS), and intermediates may determine whether dephosphylation is favored over aging. Mutations on key residues (L286, F329, F398) were considered. QM/MM calculations suggest that mutation L286H combined to other mutations favors water attack from apical position. However, the aging reaction is competing. Axial direction of water attack is not favorable to aging. QM/MM calculation shows that F329H+F398H-based multiple mutants display favorable energy barrier for fast reactivation without aging.

Rational Modulation of the Induced-Fit Conformational Change for Slow-Onset Inhibition in Mycobacterium tuberculosis InhA.

PubMed

Lai, Cheng-Tsung; Li, Huei-Jiun; Yu, Weixuan; Shah, Sonam; Bommineni, Gopal R; Perrone, Victoria; Garcia-Diaz, Miguel; Tonge, Peter J; Simmerling, Carlos

2015-08-04

Slow-onset enzyme inhibitors are the subject of considerable interest as an approach to increasing the potency of pharmaceutical compounds by extending the residence time of the inhibitor on the target (the lifetime of the drug-receptor complex). However, rational modulation of residence time presents significant challenges because it requires additional mechanistic insight, such as the nature of the transition state for postbinding isomerization. Our previous work, based on X-ray crystallography, enzyme kinetics, and molecular dynamics simulation, suggested that the slow step in inhibition of the Mycobacterium tuberculosis enoyl-ACP reductase InhA involves a change in the conformation of the substrate binding loop from an open state in the initial enzyme-inhibitor complex to a closed state in the final enzyme-inhibitor complex. Here, we use multidimensional free energy landscapes for loop isomerization to obtain a computational model for the transition state. The results suggest that slow-onset inhibitors crowd key side chains on helices that slide past each other during isomerization, resulting in a steric clash. The landscapes become significantly flatter when residues involved in the steric clash are replaced with alanine. Importantly, this lower barrier can be increased by rational inhibitor redesign to restore the steric clash. Crystallographic studies and enzyme kinetics confirm the predicted effects on loop structure and flexibility, as well as inhibitor residence time. These loss and regain of function studies validate our mechanistic hypothesis for interactions controlling substrate binding loop isomerization, providing a platform for the future design of inhibitors with longer residence times and better in vivo potency. Similar opportunities for slow-onset inhibition via the same mechanism are identified in other pathogens.

Structural modelling and comparative analysis of homologous, analogous and specific proteins from Trypanosoma cruzi versus Homo sapiens: putative drug targets for chagas' disease treatment

PubMed Central

2010-01-01

Background Trypanosoma cruzi is the etiological agent of Chagas' disease, an endemic infection that causes thousands of deaths every year in Latin America. Therapeutic options remain inefficient, demanding the search for new drugs and/or new molecular targets. Such efforts can focus on proteins that are specific to the parasite, but analogous enzymes and enzymes with a three-dimensional (3D) structure sufficiently different from the corresponding host proteins may represent equally interesting targets. In order to find these targets we used the workflows MHOLline and AnEnΠ obtaining 3D models from homologous, analogous and specific proteins of Trypanosoma cruzi versus Homo sapiens. Results We applied genome wide comparative modelling techniques to obtain 3D models for 3,286 predicted proteins of T. cruzi. In combination with comparative genome analysis to Homo sapiens, we were able to identify a subset of 397 enzyme sequences, of which 356 are homologous, 3 analogous and 38 specific to the parasite. Conclusions In this work, we present a set of 397 enzyme models of T. cruzi that can constitute potential structure-based drug targets to be investigated for the development of new strategies to fight Chagas' disease. The strategies presented here support the concept of structural analysis in conjunction with protein functional analysis as an interesting computational methodology to detect potential targets for structure-based rational drug design. For example, 2,4-dienoyl-CoA reductase (EC 1.3.1.34) and triacylglycerol lipase (EC 3.1.1.3), classified as analogous proteins in relation to H. sapiens enzymes, were identified as new potential molecular targets. PMID:21034488

Structural modelling and comparative analysis of homologous, analogous and specific proteins from Trypanosoma cruzi versus Homo sapiens: putative drug targets for chagas' disease treatment.

PubMed

Capriles, Priscila V S Z; Guimarães, Ana C R; Otto, Thomas D; Miranda, Antonio B; Dardenne, Laurent E; Degrave, Wim M

2010-10-29

Trypanosoma cruzi is the etiological agent of Chagas' disease, an endemic infection that causes thousands of deaths every year in Latin America. Therapeutic options remain inefficient, demanding the search for new drugs and/or new molecular targets. Such efforts can focus on proteins that are specific to the parasite, but analogous enzymes and enzymes with a three-dimensional (3D) structure sufficiently different from the corresponding host proteins may represent equally interesting targets. In order to find these targets we used the workflows MHOLline and AnEnΠ obtaining 3D models from homologous, analogous and specific proteins of Trypanosoma cruzi versus Homo sapiens. We applied genome wide comparative modelling techniques to obtain 3D models for 3,286 predicted proteins of T. cruzi. In combination with comparative genome analysis to Homo sapiens, we were able to identify a subset of 397 enzyme sequences, of which 356 are homologous, 3 analogous and 38 specific to the parasite. In this work, we present a set of 397 enzyme models of T. cruzi that can constitute potential structure-based drug targets to be investigated for the development of new strategies to fight Chagas' disease. The strategies presented here support the concept of structural analysis in conjunction with protein functional analysis as an interesting computational methodology to detect potential targets for structure-based rational drug design. For example, 2,4-dienoyl-CoA reductase (EC 1.3.1.34) and triacylglycerol lipase (EC 3.1.1.3), classified as analogous proteins in relation to H. sapiens enzymes, were identified as new potential molecular targets.

Alginate Immobilization of Metabolic Enzymes (AIME) for High-Throughput Screening Assays (SOT)

EPA Science Inventory

Alginate Immobilization of Metabolic Enzymes (AIME) for High-Throughput Screening Assays DE DeGroot, RS Thomas, and SO SimmonsNational Center for Computational Toxicology, US EPA, Research Triangle Park, NC USAThe EPA’s ToxCast program utilizes a wide variety of high-throughput s...

Computational design of a pH stable enzyme: understanding molecular mechanism of penicillin acylase's adaptation to alkaline conditions.

PubMed

Suplatov, Dmitry; Panin, Nikolay; Kirilin, Evgeny; Shcherbakova, Tatyana; Kudryavtsev, Pavel; Svedas, Vytas

2014-01-01

Protein stability provides advantageous development of novel properties and can be crucial in affording tolerance to mutations that introduce functionally preferential phenotypes. Consequently, understanding the determining factors for protein stability is important for the study of structure-function relationship and design of novel protein functions. Thermal stability has been extensively studied in connection with practical application of biocatalysts. However, little work has been done to explore the mechanism of pH-dependent inactivation. In this study, bioinformatic analysis of the Ntn-hydrolase superfamily was performed to identify functionally important subfamily-specific positions in protein structures. Furthermore, the involvement of these positions in pH-induced inactivation was studied. The conformational mobility of penicillin acylase in Escherichia coli was analyzed through molecular modeling in neutral and alkaline conditions. Two functionally important subfamily-specific residues, Gluβ482 and Aspβ484, were found. Ionization of these residues at alkaline pH promoted the collapse of a buried network of stabilizing interactions that consequently disrupted the functional protein conformation. The subfamily-specific position Aspβ484 was selected as a hotspot for mutation to engineer enzyme variant tolerant to alkaline medium. The corresponding Dβ484N mutant was produced and showed 9-fold increase in stability at alkaline conditions. Bioinformatic analysis of subfamily-specific positions can be further explored to study mechanisms of protein inactivation and to design more stable variants for the engineering of homologous Ntn-hydrolases with improved catalytic properties.

Computational Design of a pH Stable Enzyme: Understanding Molecular Mechanism of Penicillin Acylase's Adaptation to Alkaline Conditions

PubMed Central

Suplatov, Dmitry; Panin, Nikolay; Kirilin, Evgeny; Shcherbakova, Tatyana; Kudryavtsev, Pavel; Švedas, Vytas

2014-01-01

Protein stability provides advantageous development of novel properties and can be crucial in affording tolerance to mutations that introduce functionally preferential phenotypes. Consequently, understanding the determining factors for protein stability is important for the study of structure-function relationship and design of novel protein functions. Thermal stability has been extensively studied in connection with practical application of biocatalysts. However, little work has been done to explore the mechanism of pH-dependent inactivation. In this study, bioinformatic analysis of the Ntn-hydrolase superfamily was performed to identify functionally important subfamily-specific positions in protein structures. Furthermore, the involvement of these positions in pH-induced inactivation was studied. The conformational mobility of penicillin acylase in Escherichia coli was analyzed through molecular modeling in neutral and alkaline conditions. Two functionally important subfamily-specific residues, Gluβ482 and Aspβ484, were found. Ionization of these residues at alkaline pH promoted the collapse of a buried network of stabilizing interactions that consequently disrupted the functional protein conformation. The subfamily-specific position Aspβ484 was selected as a hotspot for mutation to engineer enzyme variant tolerant to alkaline medium. The corresponding Dβ484N mutant was produced and showed 9-fold increase in stability at alkaline conditions. Bioinformatic analysis of subfamily-specific positions can be further explored to study mechanisms of protein inactivation and to design more stable variants for the engineering of homologous Ntn-hydrolases with improved catalytic properties. PMID:24959852

PlantCAZyme: a database for plant carbohydrate-active enzymes

PubMed Central

Ekstrom, Alexander; Taujale, Rahil; McGinn, Nathan; Yin, Yanbin

2014-01-01

PlantCAZyme is a database built upon dbCAN (database for automated carbohydrate active enzyme annotation), aiming to provide pre-computed sequence and annotation data of carbohydrate active enzymes (CAZymes) to plant carbohydrate and bioenergy research communities. The current version contains data of 43 790 CAZymes of 159 protein families from 35 plants (including angiosperms, gymnosperms, lycophyte and bryophyte mosses) and chlorophyte algae with fully sequenced genomes. Useful features of the database include: (i) a BLAST server and a HMMER server that allow users to search against our pre-computed sequence data for annotation purpose, (ii) a download page to allow batch downloading data of a specific CAZyme family or species and (iii) protein browse pages to provide an easy access to the most comprehensive sequence and annotation data. Database URL: http://cys.bios.niu.edu/plantcazyme/ PMID:25125445

DomSign: a top-down annotation pipeline to enlarge enzyme space in the protein universe.

PubMed

Wang, Tianmin; Mori, Hiroshi; Zhang, Chong; Kurokawa, Ken; Xing, Xin-Hui; Yamada, Takuji

2015-03-21

Computational predictions of catalytic function are vital for in-depth understanding of enzymes. Because several novel approaches performing better than the common BLAST tool are rarely applied in research, we hypothesized that there is a large gap between the number of known annotated enzymes and the actual number in the protein universe, which significantly limits our ability to extract additional biologically relevant functional information from the available sequencing data. To reliably expand the enzyme space, we developed DomSign, a highly accurate domain signature-based enzyme functional prediction tool to assign Enzyme Commission (EC) digits. DomSign is a top-down prediction engine that yields results comparable, or superior, to those from many benchmark EC number prediction tools, including BLASTP, when a homolog with an identity >30% is not available in the database. Performance tests showed that DomSign is a highly reliable enzyme EC number annotation tool. After multiple tests, the accuracy is thought to be greater than 90%. Thus, DomSign can be applied to large-scale datasets, with the goal of expanding the enzyme space with high fidelity. Using DomSign, we successfully increased the percentage of EC-tagged enzymes from 12% to 30% in UniProt-TrEMBL. In the Kyoto Encyclopedia of Genes and Genomes bacterial database, the percentage of EC-tagged enzymes for each bacterial genome could be increased from 26.0% to 33.2% on average. Metagenomic mining was also efficient, as exemplified by the application of DomSign to the Human Microbiome Project dataset, recovering nearly one million new EC-labeled enzymes. Our results offer preliminarily confirmation of the existence of the hypothesized huge number of "hidden enzymes" in the protein universe, the identification of which could substantially further our understanding of the metabolisms of diverse organisms and also facilitate bioengineering by providing a richer enzyme resource. Furthermore, our results highlight the necessity of using more advanced computational tools than BLAST in protein database annotations to extract additional biologically relevant functional information from the available biological sequences.

Isotope Effects as Probes for Enzyme Catalyzed Hydrogen-Transfer Reactions

PubMed Central

Roston, Daniel; Islam, Zahidul; Kohen, Amnon

2015-01-01

Kinetic Isotope effects (KIEs) have long served as a probe for the mechanisms of both enzymatic and solution reactions. Here, we discuss various models for the physical sources of KIEs, how experimentalists can use those models to interpret their data, and how the focus of traditional models has grown to a model that includes motion of the enzyme and quantum mechanical nuclear tunneling. We then present two case studies of enzymes, thymidylate synthase and alcohol dehydrogenase, and discuss how KIEs have shed light on the C-H bond cleavages those enzymes catalyze. We will show how the combination of both experimental and computational studieshas changed our notion of how these enzymes exert their catalytic powers. PMID:23673528

Computational modeling and in-vitro/in-silico correlation of phospholipid-based prodrugs for targeted drug delivery in inflammatory bowel disease

NASA Astrophysics Data System (ADS)

Dahan, Arik; Markovic, Milica; Keinan, Shahar; Kurnikov, Igor; Aponick, Aaron; Zimmermann, Ellen M.; Ben-Shabat, Shimon

2017-11-01

Targeting drugs to the inflamed intestinal tissue(s) represents a major advancement in the treatment of inflammatory bowel disease (IBD). In this work we present a powerful in-silico modeling approach to guide the molecular design of novel prodrugs targeting the enzyme PLA2, which is overexpressed in the inflamed tissues of IBD patients. The prodrug consists of the drug moiety bound to the sn-2 position of phospholipid (PL) through a carbonic linker, aiming to allow PLA2 to release the free drug. The linker length dictates the affinity of the PL-drug conjugate to PLA2, and the optimal linker will enable maximal PLA2-mediated activation. Thermodynamic integration and Weighted Histogram Analysis Method (WHAM)/Umbrella Sampling method were used to compute the changes in PLA2 transition state binding free energy of the prodrug molecule (ΔΔGtr) associated with decreasing/increasing linker length. The simulations revealed that 6-carbons linker is the optimal one, whereas shorter or longer linkers resulted in decreased PLA2-mediated activation. These in-silico results were shown to be in excellent correlation with experimental in-vitro data. Overall, this modern computational approach enables optimization of the molecular design of novel prodrugs, which may allow targeting the free drug specifically to the diseased intestinal tissue of IBD patients.

Designing Allosteric Control into Enzymes by Chemical Rescue of Structure

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

Deckert, Katelyn; Budiardjo, S. Jimmy; Brunner, Luke C.

2012-08-07

Ligand-dependent activity has been engineered into enzymes for purposes ranging from controlling cell morphology to reprogramming cellular signaling pathways. Where these successes have typically fused a naturally allosteric domain to the enzyme of interest, here we instead demonstrate an approach for designing a de novo allosteric effector site directly into the catalytic domain of an enzyme. This approach is distinct from traditional chemical rescue of enzymes in that it relies on disruption and restoration of structure, rather than active site chemistry, as a means to achieve modulate function. We present two examples, W33G in a {beta}-glycosidase enzyme ({beta}-gly) and W492Gmore » in a {beta}-glucuronidase enzyme ({beta}-gluc), in which we engineer indole-dependent activity into enzymes by removing a buried tryptophan side chain that serves as a buttress for the active site architecture. In both cases, we observe a loss of function, and in both cases we find that the subsequent addition of indole can be used to restore activity. Through a detailed analysis of {beta}-gly W33G kinetics, we demonstrate that this rescued enzyme is fully functionally equivalent to the corresponding wild-type enzyme. We then present the apo and indole-bound crystal structures of {beta}-gly W33G, which together establish the structural basis for enzyme inactivation and rescue. Finally, we use this designed switch to modulate {beta}-glycosidase activity in living cells using indole. Disruption and recovery of protein structure may represent a general technique for introducing allosteric control into enzymes, and thus may serve as a starting point for building a variety of bioswitches and sensors.« less

Optimization of process variables by central composite design for the immobilization of urease enzyme on functionalized gold nanoparticles for various applications.

PubMed

Talat, Mahe; Singh, Ashwani Kumar; Srivastava, O N

2011-08-01

In the present study, enzyme urease has been immobilized on amine-functionalized gold nanoparticles (AuNPs). AuNPs were synthesized using natural precursor, i.e., clove extract and amine functionalized through 0.004 M L: -cysteine. Enzyme (urease) was extracted and purified from the vegetable waste, i.e., seeds of pumpkin to apparent homogeneity (sp. activity 353 U/mg protein). FTIR spectroscopy and transmission electron microscopy was used to characterize the immobilized enzyme. The immobilized enzyme exhibited enhanced activity as compared with the enzyme in the solution, especially, at lower enzyme concentration. Based on the evaluation of activity assay of the immobilized enzyme, it was found that the immobilized enzyme was quite stable for about a month and could successfully be used even after eight cycles having enzyme activity of about 47%. In addition to this central composite design (CCD) with the help of MINITAB version 15 Software was utilized to optimize the process variables viz., pH and temperature affecting the enzyme activity upon immobilization on AuNPs. The results predicted by the design were found in good agreement (R2 = 96.38%) with the experimental results indicating the applicability of proposed model. The multiple regression analysis and ANOVA showed the individual and cumulative effect of pH and temperature on enzyme activity indicating that the activity increased with the increase of pH up to 7.5 and temperature 75 °C. The effects of each variables represented by main effect plot, 3D surface plot, isoresponse contour plot and optimized plot were helpful in predicting results by performing a limited set of experiments.

Forward design of a complex enzyme cascade reaction

PubMed Central

Hold, Christoph; Billerbeck, Sonja; Panke, Sven

2016-01-01

Enzymatic reaction networks are unique in that one can operate a large number of reactions under the same set of conditions concomitantly in one pot, but the nonlinear kinetics of the enzymes and the resulting system complexity have so far defeated rational design processes for the construction of such complex cascade reactions. Here we demonstrate the forward design of an in vitro 10-membered system using enzymes from highly regulated biological processes such as glycolysis. For this, we adapt the characterization of the biochemical system to the needs of classical engineering systems theory: we combine online mass spectrometry and continuous system operation to apply standard system theory input functions and to use the detailed dynamic system responses to parameterize a model of sufficient quality for forward design. This allows the facile optimization of a 10-enzyme cascade reaction for fine chemical production purposes. PMID:27677244

The maximum entropy production and maximum Shannon information entropy in enzyme kinetics

NASA Astrophysics Data System (ADS)

Dobovišek, Andrej; Markovič, Rene; Brumen, Milan; Fajmut, Aleš

2018-04-01

We demonstrate that the maximum entropy production principle (MEPP) serves as a physical selection principle for the description of the most probable non-equilibrium steady states in simple enzymatic reactions. A theoretical approach is developed, which enables maximization of the density of entropy production with respect to the enzyme rate constants for the enzyme reaction in a steady state. Mass and Gibbs free energy conservations are considered as optimization constraints. In such a way computed optimal enzyme rate constants in a steady state yield also the most uniform probability distribution of the enzyme states. This accounts for the maximal Shannon information entropy. By means of the stability analysis it is also demonstrated that maximal density of entropy production in that enzyme reaction requires flexible enzyme structure, which enables rapid transitions between different enzyme states. These results are supported by an example, in which density of entropy production and Shannon information entropy are numerically maximized for the enzyme Glucose Isomerase.

Computational Studies of Candida Antarctica Lipase B to Test its Capability as a Starting Point to Redesign New Diels-Alderases

PubMed Central

Świderek, Katarzyna; Moliner, Vicent

2015-01-01

The design of new biocatalysts is a target that is receiving increasing attention. One of the most popular reactions in this regard is the Diels-Alder cycloaddition due to its applications in organic synthesis and the absence of efficient natural enzymes that catalyze it. In this paper, the possibilities of using the highly promiscuous Candida Antarctica lipase B (CALB) as a protein scaffold to re-design a Diels-Alderase has been explored by means of theoretical quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations. Free energy surfaces have been computed for two reactions in the wild-type and in several mutants with hybrid AM1/MM potentials with corrections at M06-2X/MM level. The study of the counterpart reactions in solution has allowed performing comparative analysis that render interesting conclusion. Since the dienophile anchors very well in the oxyanion hole of all tested protein variants, the slight electronic changes from reactant complex to the transition state suggest that mutations should be focused in favoring the formation of reactive conformations of reactant complex that, in turn, would reduce the energy barrier. PMID:26624234

Functionalization and Characterization of Nanomaterial Gated Field-Effect Transistor-Based Biosensors and the Design of a Multi-Analyte Implantable Biosensing Platform

NASA Astrophysics Data System (ADS)

Croce, Robert A., Jr.

Advances in semiconductor research and complementary-metal-oxide semiconductor fabrication allow for the design and implementation of miniaturized metabolic monitoring systems, as well as advanced biosensor design. The first part of this dissertation will focus on the design and fabrication of nanomaterial (single-walled carbon nanotube and quantum dot) gated field-effect transistors configured as protein sensors. These novel device structures have been functionalized with single-stranded DNA aptamers, and have shown sensor operation towards the protein Thrombin. Such advanced transistor-based sensing schemes present considerable advantages over traditional sensing methodologies in view of its miniaturization, low cost, and facile fabrication, paving the way for the ultimate realization of a multi-analyte lab-on-chip. The second part of this dissertation focuses on the design and fabrication of a needle-implantable glucose sensing platform which is based solely on photovoltaic powering and optical communication. By employing these powering and communication schemes, this design negates the need for bulky on-chip RF-based transmitters and batteries in an effort to attain extreme miniaturization required for needle-implantable/extractable applications. A complete single-sensor system coupled with a miniaturized amperometric glucose sensor has been demonstrated to exhibit reality of this technology. Furthermore, an optical selection scheme of multiple potentiostats for four different analytes (glucose, lactate, O 2 and CO2) as well as the optical transmission of sensor data has been designed for multi-analyte applications. The last part of this dissertation will focus on the development of a computational model for the amperometric glucose sensors employed in the aforementioned implantable platform. This model has been applied to single-layer single-enzyme systems, as well as multi-layer (single enzyme) systems utilizing glucose flux limiting layer-by-layer assembled outer membranes. The concentration of glucose and hydrogen peroxide within the sensor geometry, the transient response and the device response time has been simulated for both systems.

Function and biotechnology of extremophilic enzymes in low water activity

PubMed Central

2012-01-01

Enzymes from extremophilic microorganisms usually catalyze chemical reactions in non-standard conditions. Such conditions promote aggregation, precipitation, and denaturation, reducing the activity of most non-extremophilic enzymes, frequently due to the absence of sufficient hydration. Some extremophilic enzymes maintain a tight hydration shell and remain active in solution even when liquid water is limiting, e.g. in the presence of high ionic concentrations, or at cold temperature when water is close to the freezing point. Extremophilic enzymes are able to compete for hydration via alterations especially to their surface through greater surface charges and increased molecular motion. These properties have enabled some extremophilic enzymes to function in the presence of non-aqueous organic solvents, with potential for design of useful catalysts. In this review, we summarize the current state of knowledge of extremophilic enzymes functioning in high salinity and cold temperatures, focusing on their strategy for function at low water activity. We discuss how the understanding of extremophilic enzyme function is leading to the design of a new generation of enzyme catalysts and their applications to biotechnology. PMID:22480329

Active Site Flexibility as a Hallmark for Efficient PET Degradation by I. sakaiensis PETase.

PubMed

Fecker, Tobias; Galaz-Davison, Pablo; Engelberger, Felipe; Narui, Yoshie; Sotomayor, Marcos; Parra, Loreto P; Ramírez-Sarmiento, César A

2018-03-27

Polyethylene terephthalate (PET) is one of the most-consumed synthetic polymers, with an annual production of 50 million tons. Unfortunately, PET accumulates as waste and is highly resistant to biodegradation. Recently, fungal and bacterial thermophilic hydrolases were found to catalyze PET hydrolysis with optimal activities at high temperatures. Strikingly, an enzyme from Ideonella sakaiensis, termed PETase, was described to efficiently degrade PET at room temperature, but the molecular basis of its activity is not currently understood. Here, a crystal structure of PETase was determined at 2.02 Å resolution and employed in molecular dynamics simulations showing that the active site of PETase has higher flexibility at room temperature than its thermophilic counterparts. This flexibility is controlled by a novel disulfide bond in its active site, with its removal leading to destabilization of the catalytic triad and reduction of the hydrolase activity. Molecular docking of a model substrate predicts that PET binds to PETase in a unique and energetically favorable conformation facilitated by several residue substitutions within its active site when compared to other enzymes. These computational predictions are in excellent agreement with recent mutagenesis and PET film degradation analyses. Finally, we rationalize the increased catalytic activity of PETase at room temperature through molecular dynamics simulations of enzyme-ligand complexes for PETase and other thermophilic PET-degrading enzymes at 298, 323, and 353 K. Our results reveal that both the binding pose and residue substitutions within PETase favor proximity between the catalytic residues and the labile carbonyl of the substrate at room temperature, suggesting a more favorable hydrolytic reaction. These results are valuable for enabling detailed evolutionary analysis of PET-degrading enzymes and for rational design endeavors aiming at increasing the efficiency of PETase and similar enzymes toward plastic degradation. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Computationally optimized deimmunization libraries yield highly mutated enzymes with low immunogenicity and enhanced activity.

PubMed

Salvat, Regina S; Verma, Deeptak; Parker, Andrew S; Kirsch, Jack R; Brooks, Seth A; Bailey-Kellogg, Chris; Griswold, Karl E

2017-06-27

Therapeutic proteins of wide-ranging function hold great promise for treating disease, but immune surveillance of these macromolecules can drive an antidrug immune response that compromises efficacy and even undermines safety. To eliminate widespread T-cell epitopes in any biotherapeutic and thereby mitigate this key source of detrimental immune recognition, we developed a Pareto optimal deimmunization library design algorithm that optimizes protein libraries to account for the simultaneous effects of combinations of mutations on both molecular function and epitope content. Active variants identified by high-throughput screening are thus inherently likely to be deimmunized. Functional screening of an optimized 10-site library (1,536 variants) of P99 β-lactamase (P99βL), a component of ADEPT cancer therapies, revealed that the population possessed high overall fitness, and comprehensive analysis of peptide-MHC II immunoreactivity showed the population possessed lower average immunogenic potential than the wild-type enzyme. Although similar functional screening of an optimized 30-site library (2.15 × 10 9 variants) revealed reduced population-wide fitness, numerous individual variants were found to have activity and stability better than the wild type despite bearing 13 or more deimmunizing mutations per enzyme. The immunogenic potential of one highly active and stable 14-mutation variant was assessed further using ex vivo cellular immunoassays, and the variant was found to silence T-cell activation in seven of the eight blood donors who responded strongly to wild-type P99βL. In summary, our multiobjective library-design process readily identified large and mutually compatible sets of epitope-deleting mutations and produced highly active but aggressively deimmunized constructs in only one round of library screening.

An efficient route to selective bio-oxidation catalysts: an iterative approach comprising modeling, diversification, and screening, based on CYP102A1.

PubMed

Seifert, Alexander; Antonovici, Mihaela; Hauer, Bernhard; Pleiss, Jürgen

2011-06-14

Perillyl alcohol is the terminal hydroxylation product of the cheap and readily available terpene, limonene. It has high potential as an anti-tumor substance, but is of limited availability. In principle, cytochrome P450 monooxygenases, such as the self-sufficient CYP102A1, are promising catalysts for the oxidation of limonene or other inert hydrocarbons. The wild-type enzyme converts (4R)-limonene to four different oxidation products; however, terminal hydroxylation at the allylic C7 is not observed. Here we describe a generic strategy to engineer this widely used enzyme to hydroxylate exclusively the exposed, but chemically less reactive, primary C7 in the presence of other reactive positions. The approach presented here turns CYP102A1 into a highly selective catalyst with a shifted product spectra by successive rounds of modeling, the design of small focused libraries, and screening. In the first round a minimal CYP102A1 mutant library was rationally designed. It contained variants with improved or strongly shifted regio-, stereo- and chemoselectivity, compared to wild-type. From this library the variant with the highest perillyl alcohol ratio was fine-tuned by two additional rounds of molecular modeling, diversification, and screening. In total only 29 variants needed to be screened to identify the triple mutant A264V/A238V/L437F that converts (4R)-limonene to perillyl alcohol with a selectivity of 97 %. Focusing mutagenesis on a small number of relevant positions identified by computational approaches is the key for efficient screening for enzyme selectivity. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Toluene o-Xylene Monooxygenase Enzymatic Activity for the Biosynthesis of Aromatic Antioxidants

PubMed Central

Pizzo, Elio; Notomista, Eugenio; Pezzella, Alessandro; Di Cristo, Carlo; De Lise, Federica; Di Donato, Alberto; Izzo, Viviana

2015-01-01

Monocyclic phenols and catechols are important antioxidant compounds for the food and pharmaceutic industries; their production through biotransformation of low-added value starting compounds is of major biotechnological interest. The toluene o-xylene monooxygenase (ToMO) from Pseudomonas sp. OX1 is a bacterial multicomponent monooxygenase (BMM) that is able to hydroxylate a wide array of aromatic compounds and has already proven to be a versatile biochemical tool to produce mono- and dihydroxylated derivatives of aromatic compounds. The molecular determinants of its regioselectivity and substrate specificity have been thoroughly investigated, and a computational strategy has been developed which allows designing mutants able to hydroxylate non-natural substrates of this enzyme to obtain high-added value compounds of commercial interest. In this work, we have investigated the use of recombinant ToMO, expressed in cells of Escherichia coli strain JM109, for the biotransformation of non-natural substrates of this enzyme such as 2-phenoxyethanol, phthalan and 2-indanol to produce six hydroxylated derivatives. The hydroxylated products obtained were identified, isolated and their antioxidant potential was assessed both in vitro, using the DPPH assay, and on the rat cardiomyoblast cell line H9c2. Incubation of H9c2 cells with the hydroxylated compounds obtained from ToMO-catalyzed biotransformation induced a differential protective effect towards a mild oxidative stress induced by the presence of sodium arsenite. The results obtained confirm once again the versatility of the ToMO system for oxyfunctionalization reactions of biotechnological importance. Moreover, the hydroxylated derivatives obtained possess an interesting antioxidant potential that encourages the use of the enzyme for further functionalization reactions and their possible use as scaffolds to design novel bioactive molecules. PMID:25915063

GENPLAT: an Automated Platform for Biomass Enzyme Discovery and Cocktail Optimization

PubMed Central

Walton, Jonathan; Banerjee, Goutami; Car, Suzana

2011-01-01

The high cost of enzymes for biomass deconstruction is a major impediment to the economic conversion of lignocellulosic feedstocks to liquid transportation fuels such as ethanol. We have developed an integrated high throughput platform, called GENPLAT, for the discovery and development of novel enzymes and enzyme cocktails for the release of sugars from diverse pretreatment/biomass combinations. GENPLAT comprises four elements: individual pure enzymes, statistical design of experiments, robotic pipeting of biomass slurries and enzymes, and automated colorimeteric determination of released Glc and Xyl. Individual enzymes are produced by expression in Pichia pastoris or Trichoderma reesei, or by chromatographic purification from commercial cocktails or from extracts of novel microorganisms. Simplex lattice (fractional factorial) mixture models are designed using commercial Design of Experiment statistical software. Enzyme mixtures of high complexity are constructed using robotic pipeting into a 96-well format. The measurement of released Glc and Xyl is automated using enzyme-linked colorimetric assays. Optimized enzyme mixtures containing as many as 16 components have been tested on a variety of feedstock and pretreatment combinations. GENPLAT is adaptable to mixtures of pure enzymes, mixtures of commercial products (e.g., Accellerase 1000 and Novozyme 188), extracts of novel microbes, or combinations thereof. To make and test mixtures of ˜10 pure enzymes requires less than 100 μg of each protein and fewer than 100 total reactions, when operated at a final total loading of 15 mg protein/g glucan. We use enzymes from several sources. Enzymes can be purified from natural sources such as fungal cultures (e.g., Aspergillus niger, Cochliobolus carbonum, and Galerina marginata), or they can be made by expression of the encoding genes (obtained from the increasing number of microbial genome sequences) in hosts such as E. coli, Pichia pastoris, or a filamentous fungus such as T. reesei. Proteins can also be purified from commercial enzyme cocktails (e.g., Multifect Xylanase, Novozyme 188). An increasing number of pure enzymes, including glycosyl hydrolases, cell wall-active esterases, proteases, and lyases, are available from commercial sources, e.g., Megazyme, Inc. (www.megazyme.com), NZYTech (www.nzytech.com), and PROZOMIX (www.prozomix.com). Design-Expert software (Stat-Ease, Inc.) is used to create simplex-lattice designs and to analyze responses (in this case, Glc and Xyl release). Mixtures contain 4-20 components, which can vary in proportion between 0 and 100%. Assay points typically include the extreme vertices with a sufficient number of intervening points to generate a valid model. In the terminology of experimental design, most of our studies are "mixture" experiments, meaning that the sum of all components adds to a total fixed protein loading (expressed as mg/g glucan). The number of mixtures in the simplex-lattice depends on both the number of components in the mixture and the degree of polynomial (quadratic or cubic). For example, a 6-component experiment will entail 63 separate reactions with an augmented special cubic model, which can detect three-way interactions, whereas only 23 individual reactions are necessary with an augmented quadratic model. For mixtures containing more than eight components, a quadratic experimental design is more practical, and in our experience such models are usually statistically valid. All enzyme loadings are expressed as a percentage of the final total loading (which for our experiments is typically 15 mg protein/g glucan). For "core" enzymes, the lower percentage limit is set to 5%. This limit was derived from our experience in which yields of Glc and/or Xyl were very low if any core enzyme was present at 0%. Poor models result from too many samples showing very low Glc or Xyl yields. Setting a lower limit in turn determines an upper limit. That is, for a six-component experiment, if the lower limit for each single component is set to 5%, then the upper limit of each single component will be 75%. The lower limits of all other enzymes considered as "accessory" are set to 0%. "Core" and "accessory" are somewhat arbitrary designations and will differ depending on the substrate, but in our studies the core enzymes for release of Glc from corn stover comprise the following enzymes from T. reesei: CBH1 (also known as Cel7A), CBH2 (Cel6A), EG1(Cel7B), BG (β-glucosidase), EX3 (endo-β1,4-xylanase, GH10), and BX (β-xylosidase). PMID:22042431

GENPLAT: an automated platform for biomass enzyme discovery and cocktail optimization.

PubMed

Walton, Jonathan; Banerjee, Goutami; Car, Suzana

2011-10-24

The high cost of enzymes for biomass deconstruction is a major impediment to the economic conversion of lignocellulosic feedstocks to liquid transportation fuels such as ethanol. We have developed an integrated high throughput platform, called GENPLAT, for the discovery and development of novel enzymes and enzyme cocktails for the release of sugars from diverse pretreatment/biomass combinations. GENPLAT comprises four elements: individual pure enzymes, statistical design of experiments, robotic pipeting of biomass slurries and enzymes, and automated colorimeteric determination of released Glc and Xyl. Individual enzymes are produced by expression in Pichia pastoris or Trichoderma reesei, or by chromatographic purification from commercial cocktails or from extracts of novel microorganisms. Simplex lattice (fractional factorial) mixture models are designed using commercial Design of Experiment statistical software. Enzyme mixtures of high complexity are constructed using robotic pipeting into a 96-well format. The measurement of released Glc and Xyl is automated using enzyme-linked colorimetric assays. Optimized enzyme mixtures containing as many as 16 components have been tested on a variety of feedstock and pretreatment combinations. GENPLAT is adaptable to mixtures of pure enzymes, mixtures of commercial products (e.g., Accellerase 1000 and Novozyme 188), extracts of novel microbes, or combinations thereof. To make and test mixtures of ˜10 pure enzymes requires less than 100 μg of each protein and fewer than 100 total reactions, when operated at a final total loading of 15 mg protein/g glucan. We use enzymes from several sources. Enzymes can be purified from natural sources such as fungal cultures (e.g., Aspergillus niger, Cochliobolus carbonum, and Galerina marginata), or they can be made by expression of the encoding genes (obtained from the increasing number of microbial genome sequences) in hosts such as E. coli, Pichia pastoris, or a filamentous fungus such as T. reesei. Proteins can also be purified from commercial enzyme cocktails (e.g., Multifect Xylanase, Novozyme 188). An increasing number of pure enzymes, including glycosyl hydrolases, cell wall-active esterases, proteases, and lyases, are available from commercial sources, e.g., Megazyme, Inc. (www.megazyme.com), NZYTech (www.nzytech.com), and PROZOMIX (www.prozomix.com). Design-Expert software (Stat-Ease, Inc.) is used to create simplex-lattice designs and to analyze responses (in this case, Glc and Xyl release). Mixtures contain 4-20 components, which can vary in proportion between 0 and 100%. Assay points typically include the extreme vertices with a sufficient number of intervening points to generate a valid model. In the terminology of experimental design, most of our studies are "mixture" experiments, meaning that the sum of all components adds to a total fixed protein loading (expressed as mg/g glucan). The number of mixtures in the simplex-lattice depends on both the number of components in the mixture and the degree of polynomial (quadratic or cubic). For example, a 6-component experiment will entail 63 separate reactions with an augmented special cubic model, which can detect three-way interactions, whereas only 23 individual reactions are necessary with an augmented quadratic model. For mixtures containing more than eight components, a quadratic experimental design is more practical, and in our experience such models are usually statistically valid. All enzyme loadings are expressed as a percentage of the final total loading (which for our experiments is typically 15 mg protein/g glucan). For "core" enzymes, the lower percentage limit is set to 5%. This limit was derived from our experience in which yields of Glc and/or Xyl were very low if any core enzyme was present at 0%. Poor models result from too many samples showing very low Glc or Xyl yields. Setting a lower limit in turn determines an upper limit. That is, for a six-component experiment, if the lower limit for each single component is set to 5%, then the upper limit of each single component will be 75%. The lower limits of all other enzymes considered as "accessory" are set to 0%. "Core" and "accessory" are somewhat arbitrary designations and will differ depending on the substrate, but in our studies the core enzymes for release of Glc from corn stover comprise the following enzymes from T. reesei: CBH1 (also known as Cel7A), CBH2 (Cel6A), EG1(Cel7B), BG (β-glucosidase), EX3 (endo-β1,4-xylanase, GH10), and BX (β-xylosidase).

Computational Steroidogenesis Model To Predict Biochemical Responses to Endocrine Active Chemicals: Model Development and Cross Validation

EPA Science Inventory

Steroids, which have an important role in a wide range of physiological processes, are synthesized primarily in the gonads and adrenal glands through a series of enzyme-mediated reactions. The activity of steroidogenic enzymes can be altered by a variety of endocrine active chem...

EnzyNet: enzyme classification using 3D convolutional neural networks on spatial representation

PubMed Central

Amidi, Afshine; Megalooikonomou, Vasileios; Paragios, Nikos

2018-01-01

During the past decade, with the significant progress of computational power as well as ever-rising data availability, deep learning techniques became increasingly popular due to their excellent performance on computer vision problems. The size of the Protein Data Bank (PDB) has increased more than 15-fold since 1999, which enabled the expansion of models that aim at predicting enzymatic function via their amino acid composition. Amino acid sequence, however, is less conserved in nature than protein structure and therefore considered a less reliable predictor of protein function. This paper presents EnzyNet, a novel 3D convolutional neural networks classifier that predicts the Enzyme Commission number of enzymes based only on their voxel-based spatial structure. The spatial distribution of biochemical properties was also examined as complementary information. The two-layer architecture was investigated on a large dataset of 63,558 enzymes from the PDB and achieved an accuracy of 78.4% by exploiting only the binary representation of the protein shape. Code and datasets are available at https://github.com/shervinea/enzynet. PMID:29740518

EnzyNet: enzyme classification using 3D convolutional neural networks on spatial representation.

PubMed

Amidi, Afshine; Amidi, Shervine; Vlachakis, Dimitrios; Megalooikonomou, Vasileios; Paragios, Nikos; Zacharaki, Evangelia I

2018-01-01

During the past decade, with the significant progress of computational power as well as ever-rising data availability, deep learning techniques became increasingly popular due to their excellent performance on computer vision problems. The size of the Protein Data Bank (PDB) has increased more than 15-fold since 1999, which enabled the expansion of models that aim at predicting enzymatic function via their amino acid composition. Amino acid sequence, however, is less conserved in nature than protein structure and therefore considered a less reliable predictor of protein function. This paper presents EnzyNet, a novel 3D convolutional neural networks classifier that predicts the Enzyme Commission number of enzymes based only on their voxel-based spatial structure. The spatial distribution of biochemical properties was also examined as complementary information. The two-layer architecture was investigated on a large dataset of 63,558 enzymes from the PDB and achieved an accuracy of 78.4% by exploiting only the binary representation of the protein shape. Code and datasets are available at https://github.com/shervinea/enzynet.

Programmable and autonomous computing machine made of biomolecules

PubMed Central

Benenson, Yaakov; Paz-Elizur, Tamar; Adar, Rivka; Keinan, Ehud; Livneh, Zvi; Shapiro, Ehud

2013-01-01

Devices that convert information from one form into another according to a definite procedure are known as automata. One such hypothetical device is the universal Turing machine1, which stimulated work leading to the development of modern computers. The Turing machine and its special cases2, including finite automata3, operate by scanning a data tape, whose striking analogy to information-encoding biopolymers inspired several designs for molecular DNA computers4–8. Laboratory-scale computing using DNA and human-assisted protocols has been demonstrated9–15, but the realization of computing devices operating autonomously on the molecular scale remains rare16–20. Here we describe a programmable finite automaton comprising DNA and DNA-manipulating enzymes that solves computational problems autonomously. The automaton’s hardware consists of a restriction nuclease and ligase, the software and input are encoded by double-stranded DNA, and programming amounts to choosing appropriate software molecules. Upon mixing solutions containing these components, the automaton processes the input molecule via a cascade of restriction, hybridization and ligation cycles, producing a detectable output molecule that encodes the automaton’s final state, and thus the computational result. In our implementation 1012 automata sharing the same software run independently and in parallel on inputs (which could, in principle, be distinct) in 120 μl solution at room temperature at a combined rate of 109 transitions per second with a transition fidelity greater than 99.8%, consuming less than 10−10 W. PMID:11719800

Enzymes immobilized in mesoporous silica: a physical-chemical perspective.

PubMed

Carlsson, Nils; Gustafsson, Hanna; Thörn, Christian; Olsson, Lisbeth; Holmberg, Krister; Åkerman, Björn

2014-03-01

Mesoporous materials as support for immobilized enzymes have been explored extensively during the last two decades, primarily not only for biocatalysis applications, but also for biosensing, biofuels and enzyme-controlled drug delivery. The activity of the immobilized enzymes inside the pores is often different compared to that of the free enzymes, and an important challenge is to understand how the immobilization affects the enzymes in order to design immobilization conditions that lead to optimal enzyme activity. This review summarizes methods that can be used to understand how material properties can be linked to changes in enzyme activity. Real-time monitoring of the immobilization process and techniques that demonstrate that the enzymes are located inside the pores is discussed by contrasting them to the common practice of indirectly measuring the depletion of the protein concentration or enzyme activity in the surrounding bulk phase. We propose that pore filling (pore volume fraction occupied by proteins) is the best standard for comparing the amount of immobilized enzymes at the molecular level, and present equations to calculate pore filling from the more commonly reported immobilized mass. Methods to detect changes in enzyme structure upon immobilization and to study the microenvironment inside the pores are discussed in detail. Combining the knowledge generated from these methodologies should aid in rationally designing biocatalyst based on enzymes immobilized in mesoporous materials. © 2013 Elsevier B.V. All rights reserved.

Computational Prediction of Metabolism: Sites, Products, SAR, P450 Enzyme Dynamics, and Mechanisms

PubMed Central

2012-01-01

Metabolism of xenobiotics remains a central challenge for the discovery and development of drugs, cosmetics, nutritional supplements, and agrochemicals. Metabolic transformations are frequently related to the incidence of toxic effects that may result from the emergence of reactive species, the systemic accumulation of metabolites, or by induction of metabolic pathways. Experimental investigation of the metabolism of small organic molecules is particularly resource demanding; hence, computational methods are of considerable interest to complement experimental approaches. This review provides a broad overview of structure- and ligand-based computational methods for the prediction of xenobiotic metabolism. Current computational approaches to address xenobiotic metabolism are discussed from three major perspectives: (i) prediction of sites of metabolism (SOMs), (ii) elucidation of potential metabolites and their chemical structures, and (iii) prediction of direct and indirect effects of xenobiotics on metabolizing enzymes, where the focus is on the cytochrome P450 (CYP) superfamily of enzymes, the cardinal xenobiotics metabolizing enzymes. For each of these domains, a variety of approaches and their applications are systematically reviewed, including expert systems, data mining approaches, quantitative structure–activity relationships (QSARs), and machine learning-based methods, pharmacophore-based algorithms, shape-focused techniques, molecular interaction fields (MIFs), reactivity-focused techniques, protein–ligand docking, molecular dynamics (MD) simulations, and combinations of methods. Predictive metabolism is a developing area, and there is still enormous potential for improvement. However, it is clear that the combination of rapidly increasing amounts of available ligand- and structure-related experimental data (in particular, quantitative data) with novel and diverse simulation and modeling approaches is accelerating the development of effective tools for prediction of in vivo metabolism, which is reflected by the diverse and comprehensive data sources and methods for metabolism prediction reviewed here. This review attempts to survey the range and scope of computational methods applied to metabolism prediction and also to compare and contrast their applicability and performance. PMID:22339582

Targeting the cell wall of Mycobacterium tuberculosis: a molecular modeling investigation of the interaction of imipenem and meropenem with L,D-transpeptidase 2.

PubMed

Silva, José Rogério A; Bishai, William R; Govender, Thavendran; Lamichhane, Gyanu; Maguire, Glenn E M; Kruger, Hendrik G; Lameira, Jeronimo; Alves, Cláudio N

2016-01-01

The single crystal X-ray structure of the extracellular portion of the L,D-transpeptidase (ex-LdtMt2 - residues 120-408) enzyme was recently reported. It was observed that imipenem and meropenem inhibit activity of this enzyme, responsible for generating L,D-transpeptide linkages in the peptidoglycan layer of Mycobacterium tuberculosis. Imipenem is more active and isothermal titration calorimetry experiments revealed that meropenem is subjected to an entropy penalty upon binding to the enzyme. Herein, we report a molecular modeling approach to obtain a molecular view of the inhibitor/enzyme interactions. The average binding free energies for nine commercially available inhibitors were calculated using MM/GBSA and Solvation Interaction Energy (SIE) approaches and the calculated energies corresponded well with the available experimentally observed results. The method reproduces the same order of binding energies as experimentally observed for imipenem and meropenem. We have also demonstrated that SIE is a reasonably accurate and cost-effective free energy method, which can be used to predict carbapenem affinities for this enzyme. A theoretical explanation was offered for the experimental entropy penalty observed for meropenem, creating optimism that this computational model can serve as a potential computational model for other researchers in the field.

Coupled enzyme reactions performed in heterogeneous reaction media: experiments and modeling for glucose oxidase and horseradish peroxidase in a PEG/citrate aqueous two-phase system.

PubMed

Aumiller, William M; Davis, Bradley W; Hashemian, Negar; Maranas, Costas; Armaou, Antonios; Keating, Christine D

2014-03-06

The intracellular environment in which biological reactions occur is crowded with macromolecules and subdivided into microenvironments that differ in both physical properties and chemical composition. The work described here combines experimental and computational model systems to help understand the consequences of this heterogeneous reaction media on the outcome of coupled enzyme reactions. Our experimental model system for solution heterogeneity is a biphasic polyethylene glycol (PEG)/sodium citrate aqueous mixture that provides coexisting PEG-rich and citrate-rich phases. Reaction kinetics for the coupled enzyme reaction between glucose oxidase (GOX) and horseradish peroxidase (HRP) were measured in the PEG/citrate aqueous two-phase system (ATPS). Enzyme kinetics differed between the two phases, particularly for the HRP. Both enzymes, as well as the substrates glucose and H2O2, partitioned to the citrate-rich phase; however, the Amplex Red substrate necessary to complete the sequential reaction partitioned strongly to the PEG-rich phase. Reactions in ATPS were quantitatively described by a mathematical model that incorporated measured partitioning and kinetic parameters. The model was then extended to new reaction conditions, i.e., higher enzyme concentration. Both experimental and computational results suggest mass transfer across the interface is vital to maintain the observed rate of product formation, which may be a means of metabolic regulation in vivo. Although outcomes for a specific system will depend on the particulars of the enzyme reactions and the microenvironments, this work demonstrates how coupled enzymatic reactions in complex, heterogeneous media can be understood in terms of a mathematical model.

Heterosis Is a Systemic Property Emerging From Non-linear Genotype-Phenotype Relationships: Evidence From in Vitro Genetics and Computer Simulations.

PubMed

Fiévet, Julie B; Nidelet, Thibault; Dillmann, Christine; de Vienne, Dominique

2018-01-01

Heterosis, the superiority of hybrids over their parents for quantitative traits, represents a crucial issue in plant and animal breeding as well as evolutionary biology. Heterosis has given rise to countless genetic, genomic and molecular studies, but has rarely been investigated from the point of view of systems biology. We hypothesized that heterosis is an emergent property of living systems resulting from frequent concave relationships between genotypic variables and phenotypes, or between different phenotypic levels. We chose the enzyme-flux relationship as a model of the concave genotype-phenotype (GP) relationship, and showed that heterosis can be easily created in the laboratory. First, we reconstituted in vitro the upper part of glycolysis. We simulated genetic variability of enzyme activity by varying enzyme concentrations in test tubes. Mixing the content of "parental" tubes resulted in "hybrids," whose fluxes were compared to the parental fluxes. Frequent heterotic fluxes were observed, under conditions that were determined analytically and confirmed by computer simulation. Second, to test this model in a more realistic situation, we modeled the glycolysis/fermentation network in yeast by considering one input flux, glucose, and two output fluxes, glycerol and acetaldehyde. We simulated genetic variability by randomly drawing parental enzyme concentrations under various conditions, and computed the parental and hybrid fluxes using a system of differential equations. Again we found that a majority of hybrids exhibited positive heterosis for metabolic fluxes. Cases of negative heterosis were due to local convexity between certain enzyme concentrations and fluxes. In both approaches, heterosis was maximized when the parents were phenotypically close and when the distributions of parental enzyme concentrations were contrasted and constrained. These conclusions are not restricted to metabolic systems: they only depend on the concavity of the GP relationship, which is commonly observed at various levels of the phenotypic hierarchy, and could account for the pervasiveness of heterosis.

First-principles modeling of biological systems and structure-based drug-design.

PubMed

Sgrignani, Jacopo; Magistrato, Alessandra

2013-03-01

Molecular modeling techniques play a relevant role in drug design providing detailed information at atomistic level on the structural, dynamical, mechanistic and electronic properties of biological systems involved in diseases' onset, integrating and supporting commonly used experimental approaches. These information are often not accessible to the experimental techniques taken singularly, but are of crucial importance for drug design. Due to the enormous increase of the computer power in the last decades, quantum mechanical (QM) or first-principles-based methods have become often used to address biological issues of pharmaceutical relevance, providing relevant information for drug design. Due to their complexity and their size, biological systems are often investigated by means of a mixed quantum-classical (QM/MM) approach, which treats at an accurate QM level a limited chemically relevant portion of the system and at the molecular mechanics (MM) level the remaining of the biomolecule and its environment. This method provides a good compromise between computational cost and accuracy, allowing to characterize the properties of the biological system and the (free) energy landscape of the process in study with the accuracy of a QM description. In this review, after a brief introduction of QM and QM/MM methods, we will discuss few representative examples, taken from our work, of the application of these methods in the study of metallo-enzymes of pharmaceutical interest, of metal-containing anticancer drugs targeting the DNA as well as of neurodegenerative diseases. The information obtained from these studies may provide the basis for a rationale structure-based drug design of new and more efficient inhibitors or drugs.

A Computational Methodology to Overcome the Challenges Associated With the Search for Specific Enzyme Targets to Develop Drugs Against Leishmania major

PubMed Central

Catharina, Larissa; Lima, Carlyle Ribeiro; Franca, Alexander; Guimarães, Ana Carolina Ramos; Alves-Ferreira, Marcelo; Tuffery, Pierre; Derreumaux, Philippe; Carels, Nicolas

2017-01-01

We present an approach for detecting enzymes that are specific of Leishmania major compared with Homo sapiens and provide targets that may assist research in drug development. This approach is based on traditional techniques of sequence homology comparison by similarity search and Markov modeling; it integrates the characterization of enzymatic functionality, secondary and tertiary protein structures, protein domain architecture, and metabolic environment. From 67 enzymes represented by 42 enzymatic activities classified by AnEnPi (Analogous Enzymes Pipeline) as specific for L major compared with H sapiens, only 40 (23 Enzyme Commission [EC] numbers) could actually be considered as strictly specific of L major and 27 enzymes (19 EC numbers) were disregarded for having ambiguous homologies or analogies with H sapiens. Among the 40 strictly specific enzymes, we identified sterol 24-C-methyltransferase, pyruvate phosphate dikinase, trypanothione synthetase, and RNA-editing ligase as 4 essential enzymes for L major that may serve as targets for drug development. PMID:28638238

A Computational Methodology to Overcome the Challenges Associated With the Search for Specific Enzyme Targets to Develop Drugs Against Leishmania major.

PubMed

Catharina, Larissa; Lima, Carlyle Ribeiro; Franca, Alexander; Guimarães, Ana Carolina Ramos; Alves-Ferreira, Marcelo; Tuffery, Pierre; Derreumaux, Philippe; Carels, Nicolas

2017-01-01

We present an approach for detecting enzymes that are specific of Leishmania major compared with Homo sapiens and provide targets that may assist research in drug development. This approach is based on traditional techniques of sequence homology comparison by similarity search and Markov modeling; it integrates the characterization of enzymatic functionality, secondary and tertiary protein structures, protein domain architecture, and metabolic environment. From 67 enzymes represented by 42 enzymatic activities classified by AnEnPi (Analogous Enzymes Pipeline) as specific for L major compared with H sapiens , only 40 (23 Enzyme Commission [EC] numbers) could actually be considered as strictly specific of L major and 27 enzymes (19 EC numbers) were disregarded for having ambiguous homologies or analogies with H sapiens . Among the 40 strictly specific enzymes, we identified sterol 24-C-methyltransferase, pyruvate phosphate dikinase, trypanothione synthetase, and RNA-editing ligase as 4 essential enzymes for L major that may serve as targets for drug development.

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.

Design, Synthesis, and Biological and Structural Evaluations of Novel HIV-1 Protease Inhibitors To Combat Drug Resistance

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

Parai, Maloy Kumar; Huggins, David J.; Cao, Hong

2012-09-11

A series of new HIV-1 protease inhibitors (PIs) were designed using a general strategy that combines computational structure-based design with substrate-envelope constraints. The PIs incorporate various alcohol-derived P2 carbamates with acyclic and cyclic heteroatomic functionalities into the (R)-hydroxyethylamine isostere. Most of the new PIs show potent binding affinities against wild-type HIV-1 protease and three multidrug resistant (MDR) variants. In particular, inhibitors containing the 2,2-dichloroacetamide, pyrrolidinone, imidazolidinone, and oxazolidinone moieties at P2 are the most potent with Ki values in the picomolar range. Several new PIs exhibit nanomolar antiviral potencies against patient-derived wild-type viruses from HIV-1 clades A, B, and Cmore » and two MDR variants. Crystal structure analyses of four potent inhibitors revealed that carbonyl groups of the new P2 moieties promote extensive hydrogen bond interactions with the invariant Asp29 residue of the protease. These structure-activity relationship findings can be utilized to design new PIs with enhanced enzyme inhibitory and antiviral potencies.« less

Interwell Connectivity Evaluation Using Injection and Production Fluctuation Data

NASA Astrophysics Data System (ADS)

Shang, Barry Zhongqi

The development of multiscale methods for computational simulation of biophysical systems represents a significant challenge. Effective computational models that bridge physical insights obtained from atomistic simulations and experimental findings are lacking. An accurate passing of information between these scales would enable: (1) an improved physical understanding of structure-function relationships, and (2) enhanced rational strategies for molecular engineering and materials design. Two approaches are described in this dissertation to facilitate these multiscale goals. In Part I, we develop a lattice kinetic Monte Carlo model to simulate cellulose decomposition by cellulase enzymes and to understand the effects of spatial confinement on enzyme kinetics. An enhanced mechanistic understanding of this reaction system could enhance the design of cellulose bioconversion technologies for renewable and sustainable energy. Using our model, we simulate the reaction up to experimental conversion times of days, while simultaneously capturing the microscopic kinetic behaviors. Therefore, the influence of molecular-scale kinetics on the macroscopic conversion rate is made transparent. The inclusion of spatial constraints in the kinetic model represents a significant advance over classical mass-action models commonly used to describe this reaction system. We find that restrictions due to enzyme jamming and substrate heterogeneity at the molecular level play a dominate role in limiting cellulose conversion. We identify that the key rate limitations are the slow rates of enzyme complexation with glucan chains and the competition between enzyme processivity and jamming. We show that the kinetics of complexation, which involves extraction of a glucan chain end from the cellulose surface and threading through the enzyme active site, occurs slowly on the order of hours, while intrinsic hydrolytic bond cleavage occurs on the order of seconds. We also elucidate the subtle trade-off between processivity and jamming. Highly processive enzymes cleave a large fraction of a glucan chain during each processive run but are prone to jamming at obstacles. Less processive enzymes avoid jamming but cleave only a small fraction of a chain. Optimizing this trade-off maximizes the cellulose conversion rate. We also elucidate the molecular-scale kinetic origins for synergy among cellulases in enzyme mixtures. In contrast to the currently accepted theory, we show that the ability of an endoglucanase to increase the concentration of chain ends for exoglucanases is insufficient for synergy to occur. Rather, endoglucanases must enhance the rate of complexation between exoglucanases and the newly created chain ends. This enhancement occurs when the endoglucanase is able to partially decrystallize the cellulose surface. We show generally that the driving forces for complexation and jamming, which govern the kinetics of pure exoglucanases, also control the degree of synergy in endo-exo mixtures. In Part II, we focus our attention on a different multiscale problem. This challenge is the development of coarse-grained models from atomistic models to access larger length- and time-scales in a simulation. This problem is difficult because it requires a delicate balance between maintaining (1) physical simplicity in the coarse-grained model and (2) physical consistency with the atomistic model. To achieve these goals, we develop a scheme to coarse-grain an atomistic fluid model into a fluctuating hydrodynamics (FHD) model. The FHD model describes the solvent as a field of fluctuating mass, momentum, and energy densities. The dynamics of the fluid are governed by continuum balance equations and fluctuation-dissipation relations based on the constitutive transport laws. The incorporation of both macroscopic transport and microscopic fluctuation phenomena could provide richer physical insight into the behaviors of biophysical systems driven by hydrodynamic fluctuations, such as hydrophobic assembly and crystal nucleation. We further extend our coarse-graining method by developing an interfacial FHD model using information obtained from simulations of an atomistic liquid-vapor interface. We illustrate that a phenomenological Ginzburg-Landau free energy employed in the FHD model can effectively represent the attractive molecular interactions of the atomistic model, which give rise to phase separation. For argon and water, we show that the interfacial FHD model can reproduce the compressibility, surface tension, and capillary wave spectrum of the atomistic model. Via this approach, simulations that explore the coupling between hydrodynamic fluctuations and phase equilibria with molecular-scale consistency are now possible. In both Parts I and II, the emerging theme is that the combination of bottom-up coarse graining and top-down phenomenology is essential for enabling a multiscale approach to remain physically consistent with molecular-scale interactions while simultaneously capturing the collective macroscopic behaviors. This hybrid strategy enables the resulting computational models to be both physically insightful and practically meaningful. (Abstract shortened by UMI.).

Structural determinants for the inhibitory ligands of orotidine-5′-monophosphate decarboxylase

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

Meza-Avina, Maria Elena; Wei, Lianhu; Liu, Yan

2010-06-14

In recent years, orotidine-5{prime}-monophosphate decarboxylase (ODCase) has gained renewed attention as a drug target. As a part of continuing efforts to design novel inhibitors of ODCase, we undertook a comprehensive study of potent, structurally diverse ligands of ODCase and analyzed their structural interactions in the active site of ODCase. These ligands comprise of pyrazole or pyrimidine nucleotides including the mononucleotide derivatives of pyrazofurin, barbiturate ribonucleoside, and 5-cyanouridine, as well as, in a computational approach, 1,4-dihydropyridine-based non-nucleoside inhibitors such as nifedipine and nimodipine. All these ligands bind in the active site of ODCase exhibiting distinct interactions paving the way to designmore » novel inhibitors against this interesting enzyme. We propose an empirical model for the ligand structure for rational modifications in new drug design and potentially new lead structures.« less

Dimeric [Mo₂S₁₂]²⁻ Cluster: A Molecular Analogue of MoS₂ Edges for Superior Hydrogen-Evolution Electrocatalysis

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

Huang, Zhongjie; Luo, Wenjia; Ma, Lu

2015-12-07

Proton reduction is one of the most fundamental and important reactions in nature. MoS2 edges have been identified as the active sites for hydrogen evolution reaction (HER) electrocatalysis. Designing molecular mimics of MoS2 edge sites is an attractive strategy to understand the underlying catalytic mechanism of different edge sites and improve their activities. Herein we report a dimeric molecular analogue [Mo₂S₁₂]²⁻, as the smallest unit possessing both the terminal and bridging disulfide ligands. Our electrochemical tests show that [Mo₂S₁₂]²⁻ is a superior heterogeneous HER catalyst under acidic conditions. Computations suggest that the bridging disulfide ligand of [Mo₂S₁₂]²⁻ exhibits a hydrogenmore » adsorption free energy near zero (-0.05eV). This work helps shed light on the rational design of HER catalysts and biomimetics of hydrogen-evolving enzymes.« less

Enzyme Sequestration as a Tuning Point in Controlling Response Dynamics of Signalling Networks

PubMed Central

Ollivier, Julien F.; Soyer, Orkun S.

2016-01-01

Signalling networks result from combinatorial interactions among many enzymes and scaffolding proteins. These complex systems generate response dynamics that are often essential for correct decision-making in cells. Uncovering biochemical design principles that underpin such response dynamics is a prerequisite to understand evolved signalling networks and to design synthetic ones. Here, we use in silico evolution to explore the possible biochemical design space for signalling networks displaying ultrasensitive and adaptive response dynamics. By running evolutionary simulations mimicking different biochemical scenarios, we find that enzyme sequestration emerges as a key mechanism for enabling such dynamics. Inspired by these findings, and to test the role of sequestration, we design a generic, minimalist model of a signalling cycle, featuring two enzymes and a single scaffolding protein. We show that this simple system is capable of displaying both ultrasensitive and adaptive response dynamics. Furthermore, we find that tuning the concentration or kinetics of the sequestering protein can shift system dynamics between these two response types. These empirical results suggest that enzyme sequestration through scaffolding proteins is exploited by evolution to generate diverse response dynamics in signalling networks and could provide an engineering point in synthetic biology applications. PMID:27163612

Structural analysis of peptides that fill sites near the active center of the two different enzyme molecules by artificial intelligence and computer simulations

NASA Astrophysics Data System (ADS)

Nishiyama, Katsuhiko

2018-05-01

Using artificial intelligence, the binding styles of 167 tetrapeptides were predicted in the active site of papain and cathepsin K. Five tetrapeptides (Asn-Leu-Lys-Trp, Asp-Gln-Trp-Gly, Cys-Gln-Leu-Arg, Gln-Leu-Trp-Thr and Arg-Ser-Glu-Arg) were found to bind sites near the active center of both papain and cathepsin K. These five tetrapeptides have the potential to also bind sites of other cysteine proteases, and structural characteristics of these tetrapeptides should aid the design of a common inhibitor of cysteine proteases. Smart application of artificial intelligence should accelerate data mining of important complex systems.

Evolutionary and molecular foundations of multiple contemporary functions of the nitroreductase superfamily

PubMed Central

Akiva, Eyal; Copp, Janine N.; Tokuriki, Nobuhiko; Babbitt, Patricia C.

2017-01-01

Insight regarding how diverse enzymatic functions and reactions have evolved from ancestral scaffolds is fundamental to understanding chemical and evolutionary biology, and for the exploitation of enzymes for biotechnology. We undertook an extensive computational analysis using a unique and comprehensive combination of tools that include large-scale phylogenetic reconstruction to determine the sequence, structural, and functional relationships of the functionally diverse flavin mononucleotide-dependent nitroreductase (NTR) superfamily (>24,000 sequences from all domains of life, 54 structures, and >10 enzymatic functions). Our results suggest an evolutionary model in which contemporary subgroups of the superfamily have diverged in a radial manner from a minimal flavin-binding scaffold. We identified the structural design principle for this divergence: Insertions at key positions in the minimal scaffold that, combined with the fixation of key residues, have led to functional specialization. These results will aid future efforts to delineate the emergence of functional diversity in enzyme superfamilies, provide clues for functional inference for superfamily members of unknown function, and facilitate rational redesign of the NTR scaffold. PMID:29078300

Synthetic Gene Network with Positive Feedback Loop Amplifies Cellulase Gene Expression in Neurospora crassa.

PubMed

Matsu-Ura, Toru; Dovzhenok, Andrey A; Coradetti, Samuel T; Subramanian, Krithika R; Meyer, Daniel R; Kwon, Jaesang J; Kim, Caleb; Salomonis, Nathan; Glass, N Louise; Lim, Sookkyung; Hong, Christian I

2018-05-18

Second-generation or lignocellulosic biofuels are a tangible source of renewable energy, which is critical to combat climate change by reducing the carbon footprint. Filamentous fungi secrete cellulose-degrading enzymes called cellulases, which are used for production of lignocellulosic biofuels. However, inefficient production of cellulases is a major obstacle for industrial-scale production of second-generation biofuels. We used computational simulations to design and implement synthetic positive feedback loops to increase gene expression of a key transcription factor, CLR-2, that activates a large number of cellulases in a filamentous fungus, Neurospora crassa. Overexpression of CLR-2 reveals previously unappreciated roles of CLR-2 in lignocellulosic gene network, which enabled simultaneous induction of approximately 50% of 78 lignocellulosic degradation-related genes in our engineered Neurospora strains. This engineering results in dramatically increased cellulase activity due to cooperative orchestration of multiple enzymes involved in the cellulose degradation pathway. Our work provides a proof of principle in utilizing mathematical modeling and synthetic biology to improve the efficiency of cellulase synthesis for second-generation biofuel production.

Inhibition of ligand exchange kinetics via active-site trapping with an antibody fragment.

PubMed

Oyen, David; Steyaert, Jan; Barlow, John N

2014-04-01

We describe the first example of an inhibitory antibody fragment (nanobody ca1697) that binds simultaneously to an enzyme (the enzyme dihydrofolate reductase from Escherichia coli) and its bound substrate (folate). Binding of the antibody to the substrate causes a 20-fold reduction in the rate of folate exchange kinetics. This work opens up the prospect of designing new types of antibody-based inhibitors of enzymes and receptors through suitable design of immunogens.

Stabilization of different types of transition states in a single enzyme active site: QM/MM analysis of enzymes in the alkaline phosphatase superfamily.

PubMed

Hou, Guanhua; Cui, Qiang

2013-07-17

The first step for the hydrolysis of a phosphate monoester (pNPP(2-)) in enzymes of the alkaline phosphatase (AP) superfamily, R166S AP and wild-type NPP, is studied using QM/MM simulations based on an approximate density functional theory (SCC-DFTBPR) and a recently introduced QM/MM interaction Hamiltonian. The calculations suggest that similar loose transition states are involved in both enzymes, despite the fact that phosphate monoesters are the cognate substrates for AP but promiscuous substrates for NPP. The computed loose transition states are clearly different from the more synchronous ones previously calculated for diester reactions in the same AP enzymes. Therefore, our results explicitly support the proposal that AP enzymes are able to recognize and stabilize different types of transition states in a single active site. Analysis of the structural features of computed transition states indicates that the plastic nature of the bimetallic site plays a minor role in accommodating multiple types of transition states and that the high degree of solvent accessibility of the AP active site also contributes to its ability to stabilize diverse transition-state structures without the need of causing large structural distortions of the bimetallic motif. The binding mode of the leaving group in the transition state highlights that vanadate may not always be an ideal transition state analog for loose phosphoryl transfer transition states.

The Role of Cholesterol Utilization in a Computational Adrenal Steroidogenesis Model to Improve Predictability of Biochemical Responses to Endocrine Active Chemicals

EPA Science Inventory

Steroids, which have an important role in a wide range of physiological processes, are synthesized primarily in the gonads and adrenal glands through a series of enzyme-mediated reactions. The activity of steroidogenic enzymes can be altered by a variety of endocrine active chem...

The Role of Oxysterols in a Computational Steroidogenesis Model of Human H295R Cells to Improve Predictability of Biochemical Responses to Endocrine Disruptors

EPA Science Inventory

Steroids, which have an important role in a wide range of physiological processes, are synthesized primarily in the gonads and adrenal glands through a series of enzyme mediated reactions. The activity of steroidogenic enzymes can be altered by a variety of endocrine disruptors (...

NMR Crystallography of Enzyme Active Sites: Probing Chemically-Detailed, Three-Dimensional Structure in Tryptophan Synthase

PubMed Central

Dunn, Michael F.

2013-01-01

Conspectus NMR crystallography – the synergistic combination of X-ray diffraction, solid-state NMR spectroscopy, and computational chemistry – offers unprecedented insight into three-dimensional, chemically-detailed structure. From its initial role in refining diffraction data of organic and inorganic solids, NMR crystallography is now being developed for application to active sites in biomolecules, where it reveals chemically-rich detail concerning the interactions between enzyme site residues and the reacting substrate that is not achievable when X-ray, NMR, or computational methodologies are applied in isolation. For example, typical X-ray crystal structures (1.5 to 2.5 Å resolution) of enzyme-bound intermediates identify possible hydrogen-bonding interactions between site residues and substrate, but do not directly identify the protonation state of either. Solid-state NMR can provide chemical shifts for selected atoms of enzyme-substrate complexes, but without a larger structural framework in which to interpret them, only empirical correlations with local chemical structure are possible. Ab initio calculations and molecular mechanics can build models for enzymatic processes, but rely on chemical details that must be specified. Together, however, X-ray diffraction, solid-state NMR spectroscopy, and computational chemistry can provide consistent and testable models for structure and function of enzyme active sites: X-ray crystallography provides a coarse framework upon which models of the active site can be developed using computational chemistry; these models can be distinguished by comparison of their calculated NMR chemical shifts with the results of solid-state NMR spectroscopy experiments. Conceptually, each technique is a puzzle piece offering a generous view of the big picture. Only when correctly pieced together, however, can they reveal the big picture at highest resolution. In this Account, we detail our first steps in the development of NMR crystallography for application to enzyme catalysis. We begin with a brief introduction to NMR crystallography and then define the process that we have employed to probe the active site in the β-subunit of tryptophan synthase with unprecedented atomic-level resolution. This approach has resulted in a novel structural hypothesis for the protonation state of the quinonoid intermediate in tryptophan synthase and its surprising role in directing the next step in the catalysis of L-Trp formation. PMID:23537227

Quantitative comparison of catalytic mechanisms and overall reactions in convergently evolved enzymes: implications for classification of enzyme function.

PubMed

Almonacid, Daniel E; Yera, Emmanuel R; Mitchell, John B O; Babbitt, Patricia C

2010-03-12

Functionally analogous enzymes are those that catalyze similar reactions on similar substrates but do not share common ancestry, providing a window on the different structural strategies nature has used to evolve required catalysts. Identification and use of this information to improve reaction classification and computational annotation of enzymes newly discovered in the genome projects would benefit from systematic determination of reaction similarities. Here, we quantified similarity in bond changes for overall reactions and catalytic mechanisms for 95 pairs of functionally analogous enzymes (non-homologous enzymes with identical first three numbers of their EC codes) from the MACiE database. Similarity of overall reactions was computed by comparing the sets of bond changes in the transformations from substrates to products. For similarity of mechanisms, sets of bond changes occurring in each mechanistic step were compared; these similarities were then used to guide global and local alignments of mechanistic steps. Using this metric, only 44% of pairs of functionally analogous enzymes in the dataset had significantly similar overall reactions. For these enzymes, convergence to the same mechanism occurred in 33% of cases, with most pairs having at least one identical mechanistic step. Using our metric, overall reaction similarity serves as an upper bound for mechanistic similarity in functional analogs. For example, the four carbon-oxygen lyases acting on phosphates (EC 4.2.3) show neither significant overall reaction similarity nor significant mechanistic similarity. By contrast, the three carboxylic-ester hydrolases (EC 3.1.1) catalyze overall reactions with identical bond changes and have converged to almost identical mechanisms. The large proportion of enzyme pairs that do not show significant overall reaction similarity (56%) suggests that at least for the functionally analogous enzymes studied here, more stringent criteria could be used to refine definitions of EC sub-subclasses for improved discrimination in their classification of enzyme reactions. The results also indicate that mechanistic convergence of reaction steps is widespread, suggesting that quantitative measurement of mechanistic similarity can inform approaches for functional annotation.

Quantitative Comparison of Catalytic Mechanisms and Overall Reactions in Convergently Evolved Enzymes: Implications for Classification of Enzyme Function

PubMed Central

Almonacid, Daniel E.; Yera, Emmanuel R.; Mitchell, John B. O.; Babbitt, Patricia C.

2010-01-01

Functionally analogous enzymes are those that catalyze similar reactions on similar substrates but do not share common ancestry, providing a window on the different structural strategies nature has used to evolve required catalysts. Identification and use of this information to improve reaction classification and computational annotation of enzymes newly discovered in the genome projects would benefit from systematic determination of reaction similarities. Here, we quantified similarity in bond changes for overall reactions and catalytic mechanisms for 95 pairs of functionally analogous enzymes (non-homologous enzymes with identical first three numbers of their EC codes) from the MACiE database. Similarity of overall reactions was computed by comparing the sets of bond changes in the transformations from substrates to products. For similarity of mechanisms, sets of bond changes occurring in each mechanistic step were compared; these similarities were then used to guide global and local alignments of mechanistic steps. Using this metric, only 44% of pairs of functionally analogous enzymes in the dataset had significantly similar overall reactions. For these enzymes, convergence to the same mechanism occurred in 33% of cases, with most pairs having at least one identical mechanistic step. Using our metric, overall reaction similarity serves as an upper bound for mechanistic similarity in functional analogs. For example, the four carbon-oxygen lyases acting on phosphates (EC 4.2.3) show neither significant overall reaction similarity nor significant mechanistic similarity. By contrast, the three carboxylic-ester hydrolases (EC 3.1.1) catalyze overall reactions with identical bond changes and have converged to almost identical mechanisms. The large proportion of enzyme pairs that do not show significant overall reaction similarity (56%) suggests that at least for the functionally analogous enzymes studied here, more stringent criteria could be used to refine definitions of EC sub-subclasses for improved discrimination in their classification of enzyme reactions. The results also indicate that mechanistic convergence of reaction steps is widespread, suggesting that quantitative measurement of mechanistic similarity can inform approaches for functional annotation. PMID:20300652

Cofactor specificity switch in Shikimate dehydrogenase by rational design and consensus engineering.

PubMed

García-Guevara, Fernando; Bravo, Iris; Martínez-Anaya, Claudia; Segovia, Lorenzo

2017-08-01

Consensus engineering has been used to design more stable variants using the most frequent amino acid at each site of a multiple sequence alignment; sometimes consensus engineering modifies function, but efforts have mainly been focused on studying stability. Here we constructed a consensus Rossmann domain for the Shikimate dehydrogenase enzyme; separately we decided to switch the cofactor specificity through rational design in the Escherichia coli Shikimate dehydrogenase enzyme and then analyzed the effect of consensus mutations on top of our design. We found that consensus mutations closest to the 2' adenine moiety increased the activity in our design. Consensus engineering has been shown to result in more stable proteins and our findings suggest it could also be used as a complementary tool for increasing or modifying enzyme activity during design. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

VX hydrolysis by human serum paraoxonase 1: a comparison of experimental and computational results.

PubMed

Peterson, Matthew W; Fairchild, Steven Z; Otto, Tamara C; Mohtashemi, Mojdeh; Cerasoli, Douglas M; Chang, Wenling E

2011-01-01

Human Serum paraoxonase 1 (HuPON1) is an enzyme that has been shown to hydrolyze a variety of chemicals including the nerve agent VX. While wildtype HuPON1 does not exhibit sufficient activity against VX to be used as an in vivo countermeasure, it has been suggested that increasing HuPON1's organophosphorous hydrolase activity by one or two orders of magnitude would make the enzyme suitable for this purpose. The binding interaction between HuPON1 and VX has recently been modeled, but the mechanism for VX hydrolysis is still unknown. In this study, we created a transition state model for VX hydrolysis (VX(ts)) in water using quantum mechanical/molecular mechanical simulations, and docked the transition state model to 22 experimentally characterized HuPON1 variants using AutoDock Vina. The HuPON1-VX(ts) complexes were grouped by reaction mechanism using a novel clustering procedure. The average Vina interaction energies for different clusters were compared to the experimentally determined activities of HuPON1 variants to determine which computational procedures best predict how well HuPON1 variants will hydrolyze VX. The analysis showed that only conformations which have the attacking hydroxyl group of VX(ts) coordinated by the sidechain oxygen of D269 have a significant correlation with experimental results. The results from this study can be used for further characterization of how HuPON1 hydrolyzes VX and design of HuPON1 variants with increased activity against VX.

VX Hydrolysis by Human Serum Paraoxonase 1: A Comparison of Experimental and Computational Results

PubMed Central

Peterson, Matthew W.; Fairchild, Steven Z.; Otto, Tamara C.; Mohtashemi, Mojdeh; Cerasoli, Douglas M.; Chang, Wenling E.

2011-01-01

Human Serum paraoxonase 1 (HuPON1) is an enzyme that has been shown to hydrolyze a variety of chemicals including the nerve agent VX. While wildtype HuPON1 does not exhibit sufficient activity against VX to be used as an in vivo countermeasure, it has been suggested that increasing HuPON1's organophosphorous hydrolase activity by one or two orders of magnitude would make the enzyme suitable for this purpose. The binding interaction between HuPON1 and VX has recently been modeled, but the mechanism for VX hydrolysis is still unknown. In this study, we created a transition state model for VX hydrolysis (VXts) in water using quantum mechanical/molecular mechanical simulations, and docked the transition state model to 22 experimentally characterized HuPON1 variants using AutoDock Vina. The HuPON1-VXts complexes were grouped by reaction mechanism using a novel clustering procedure. The average Vina interaction energies for different clusters were compared to the experimentally determined activities of HuPON1 variants to determine which computational procedures best predict how well HuPON1 variants will hydrolyze VX. The analysis showed that only conformations which have the attacking hydroxyl group of VXts coordinated by the sidechain oxygen of D269 have a significant correlation with experimental results. The results from this study can be used for further characterization of how HuPON1 hydrolyzes VX and design of HuPON1 variants with increased activity against VX. PMID:21655255

Influence of the membrane lipophilic environment on the structure and on the substrate access/egress routes of the human aromatase enzyme. A computational study.

PubMed

Sgrignani, Jacopo; Magistrato, Alessandra

2012-06-25

Human aromatase (HA), an enzyme located on the membrane of the endoplasmatic reticulum, is of crucial biological importance in the biosynthesis of estrogens. High levels of estrogens are related with important pathologies, conferring to HA a key role as a pharmacological target. In this study we provide, for the first time, an atomistic model of HA embedded on a membrane model to understand the influence of the membrane lipophilic environment on the structural and dynamical properties of HA and on the access/egress pathways of the substrate (androstenedione, ASD) and of the oxygen molecule (involved in the enzymatic process) into/from the HA active site. To this end we used several computational techniques such as force field-based molecular dynamics (MD) simulations, Random Expulsion MD, Steered MD, and Implicit Ligand Sampling. Our results show that the membrane anchoring does not markedly affect the structural properties and the flexibility of the protein, but they clearly point out that the membrane has a marked effect on the access/egress routes of the reactants, stabilizing the formation of different channels for both ASD and O(2) with respect to those observed in pure water solution. Due to the importance of HA in medicine and since access/egress channels may influence its substrate selectivity, a detailed understanding of the role of the membrane in shaping these channels may be of valuable help in drug design.

Discovery of Boolean metabolic networks: integer linear programming based approach.

PubMed

Qiu, Yushan; Jiang, Hao; Ching, Wai-Ki; Cheng, Xiaoqing

2018-04-11

Traditional drug discovery methods focused on the efficacy of drugs rather than their toxicity. However, toxicity and/or lack of efficacy are produced when unintended targets are affected in metabolic networks. Thus, identification of biological targets which can be manipulated to produce the desired effect with minimum side-effects has become an important and challenging topic. Efficient computational methods are required to identify the drug targets while incurring minimal side-effects. In this paper, we propose a graph-based computational damage model that summarizes the impact of enzymes on compounds in metabolic networks. An efficient method based on Integer Linear Programming formalism is then developed to identify the optimal enzyme-combination so as to minimize the side-effects. The identified target enzymes for known successful drugs are then verified by comparing the results with those in the existing literature. Side-effects reduction plays a crucial role in the study of drug development. A graph-based computational damage model is proposed and the theoretical analysis states the captured problem is NP-completeness. The proposed approaches can therefore contribute to the discovery of drug targets. Our developed software is available at " http://hkumath.hku.hk/~wkc/APBC2018-metabolic-network.zip ".

Structure-based design, synthesis, and biological evaluation of novel pyrrolyl aryl sulfones: HIV-1 non-nucleoside reverse transcriptase inhibitors active at nanomolar concentrations.

PubMed

Artico, M; Silvestri, R; Pagnozzi, E; Bruno, B; Novellino, E; Greco, G; Massa, S; Ettorre, A; Loi, A G; Scintu, F; La Colla, P

2000-05-04

Pyrrolyl aryl sulfones (PASs) have been recently reported as a new class of human immunodeficiency virus type 1 (HIV-1) reverse transcriptase (RT) inhibitors acting at the non-nucleoside binding site of this enzyme (Artico, M.; et al. J. Med. Chem. 1996, 39, 522-530). Compound 3, the most potent inhibitor within the series (EC(50) = 0.14 microM, IC(50) = 0.4 microM, and SI > 1429), was then selected as a lead compound for a synthetic project based on molecular modeling studies. Using the three-dimensional structure of RT cocrystallized with the alpha-APA derivative R95845, we derived a model of the RT/3 complex by taking into account previously developed structure-activity relationships. Inspection of this model and docking calculations on virtual compounds prompted the design of novel PAS derivatives and related analogues. Our computational approach proved to be effective in making qualitative predictions, that is in discriminating active versus inactive compounds. Among the compounds synthesized and tested, 20 was the most active one, with EC(50) = 0.045 microM, IC(50) = 0.05 microM, and SI = 5333. Compared with the lead 3, these values represent a 3- and 8-fold improvement in the cell-based and enzyme assays, respectively, together with the highest selectivity achieved so far in the PAS series.

Semisupervised Gaussian Process for Automated Enzyme Search.

PubMed

Mellor, Joseph; Grigoras, Ioana; Carbonell, Pablo; Faulon, Jean-Loup

2016-06-17

Synthetic biology is today harnessing the design of novel and greener biosynthesis routes for the production of added-value chemicals and natural products. The design of novel pathways often requires a detailed selection of enzyme sequences to import into the chassis at each of the reaction steps. To address such design requirements in an automated way, we present here a tool for exploring the space of enzymatic reactions. Given a reaction and an enzyme the tool provides a probability estimate that the enzyme catalyzes the reaction. Our tool first considers the similarity of a reaction to known biochemical reactions with respect to signatures around their reaction centers. Signatures are defined based on chemical transformation rules by using extended connectivity fingerprint descriptors. A semisupervised Gaussian process model associated with the similar known reactions then provides the probability estimate. The Gaussian process model uses information about both the reaction and the enzyme in providing the estimate. These estimates were validated experimentally by the application of the Gaussian process model to a newly identified metabolite in Escherichia coli in order to search for the enzymes catalyzing its associated reactions. Furthermore, we show with several pathway design examples how such ability to assign probability estimates to enzymatic reactions provides the potential to assist in bioengineering applications, providing experimental validation to our proposed approach. To the best of our knowledge, the proposed approach is the first application of Gaussian processes dealing with biological sequences and chemicals, the use of a semisupervised Gaussian process framework is also novel in the context of machine learning applied to bioinformatics. However, the ability of an enzyme to catalyze a reaction depends on the affinity between the substrates of the reaction and the enzyme. This affinity is generally quantified by the Michaelis constant KM. Therefore, we also demonstrate using Gaussian process regression to predict KM given a substrate-enzyme pair.

A QM/MM Metadynamics Study of the Direct Decarboxylation Mechanism for Orotidine-5'-monophosphate Decarboxylase using Two Different QM Regions: Acceleration too Small to Explain Rate of Enzyme Catalysis

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

Stanton, Courtney; Kuo, I-F W.; Mundy, Christopher J.

2007-11-01

Despite decades of study, the mechanism of orotidine-5'-monophosphate decarboxylase (ODCase) remains unresolved. A computational investigation of the direct decarboxylation mechanism has been performed using mixed quantum mechanical/molecular mechanical (QM/MM) dynamics simulations. The study was performed with the program CP2K that integrates classical dynamics and ab initio dynamics based on the Born-Oppenheimer approach. Two different QM regions were explored. It was found that the size of the QM region has a dramatic effect on the calculated reaction barrier. The free energy barriers for decarboxylation of orotidine-5'-monophosphate (OMP) in solution and in the enzyme were determined with the metadynamics method to bemore » 40 kcal/mol and 33 kcal/mol, respectively. The calculated change in activation free energy (ΔΔG±) on going from solution to the enzyme is therefore -7 kcal/mol, far less than the experimental change of -23 kcal/mol (for kcat/kuncat Radzicka, A.; Wolfenden, R., Science. 1995, 267, 90-92). These results do not support the direct decarboxylation mechanism in the enzyme. Funding was provided by the University of California Lawrence Livermore National Laboratory (LLNL) and the National Institutes of Health (NIH). Part of this work was performed under the auspices of the U.S. Department of Energy by LLNL under contract No. W-7405-Eng-48. Computer resources were provided by Livermore Computing.« less

Two strategies to engineer flexible loops for improved enzyme thermostability

PubMed Central

Yu, Haoran; Yan, Yihan; Zhang, Cheng; Dalby, Paul A.

2017-01-01

Flexible sites are potential targets for engineering the stability of enzymes. Nevertheless, the success rate of the rigidifying flexible sites (RFS) strategy is still low due to a limited understanding of how to determine the best mutation candidates. In this study, two parallel strategies were applied to identify mutation candidates within the flexible loops of Escherichia coli transketolase (TK). The first was a “back to consensus mutations” approach, and the second was computational design based on ΔΔG calculations in Rosetta. Forty-nine single variants were generated and characterised experimentally. From these, three single-variants I189H, A282P, D143K were found to be more thermostable than wild-type TK. The combination of A282P with H192P, a variant constructed previously, resulted in the best all-round variant with a 3-fold improved half-life at 60 °C, 5-fold increased specific activity at 65 °C, 1.3-fold improved kcat and a Tm increased by 5 °C above that of wild type. Based on a statistical analysis of the stability changes for all variants, the qualitative prediction accuracy of the Rosetta program reached 65.3%. Both of the two strategies investigated were useful in guiding mutation candidates to flexible loops, and had the potential to be used for other enzymes. PMID:28145457

Improvement in Saccharification Yield of Mixed Rumen Enzymes by Identification of Recalcitrant Cell Wall Constituents Using Enzyme Fingerprinting.

PubMed

Badhan, Ajay; Wang, Yu-Xi; Gruninger, Robert; Patton, Donald; Powlowski, Justin; Tsang, Adrian; McAllister, Tim A

2015-01-01

Identification of recalcitrant factors that limit digestion of forages and the development of enzymatic approaches that improve hydrolysis could play a key role in improving the efficiency of meat and milk production in ruminants. Enzyme fingerprinting of barley silage fed to heifers and total tract indigestible fibre residue (TIFR) collected from feces was used to identify cell wall components resistant to total tract digestion. Enzyme fingerprinting results identified acetyl xylan esterases as key to the enhanced ruminal digestion. FTIR analysis also suggested cross-link cell wall polymers as principal components of indigested fiber residues in feces. Based on structural information from enzymatic fingerprinting and FTIR, enzyme pretreatment to enhance glucose yield from barley straw and alfalfa hay upon exposure to mixed rumen-enzymes was developed. Prehydrolysis effects of recombinant fungal fibrolytic hydrolases were analyzed using microassay in combination with statistical experimental design. Recombinant hemicellulases and auxiliary enzymes initiated degradation of plant structural polysaccharides upon application and improved the in vitro saccharification of alfalfa and barley straw by mixed rumen enzymes. The validation results showed that microassay in combination with statistical experimental design can be successfully used to predict effective enzyme pretreatments that can enhance plant cell wall digestion by mixed rumen enzymes.

A combined computational-experimental analyses of selected metabolic enzymes in Pseudomonas species.

PubMed

Perumal, Deepak; Lim, Chu Sing; Chow, Vincent T K; Sakharkar, Kishore R; Sakharkar, Meena K

2008-09-10

Comparative genomic analysis has revolutionized our ability to predict the metabolic subsystems that occur in newly sequenced genomes, and to explore the functional roles of the set of genes within each subsystem. These computational predictions can considerably reduce the volume of experimental studies required to assess basic metabolic properties of multiple bacterial species. However, experimental validations are still required to resolve the apparent inconsistencies in the predictions by multiple resources. Here, we present combined computational-experimental analyses on eight completely sequenced Pseudomonas species. Comparative pathway analyses reveal that several pathways within the Pseudomonas species show high plasticity and versatility. Potential bypasses in 11 metabolic pathways were identified. We further confirmed the presence of the enzyme O-acetyl homoserine (thiol) lyase (EC: 2.5.1.49) in P. syringae pv. tomato that revealed inconsistent annotations in KEGG and in the recently published SYSTOMONAS database. These analyses connect and integrate systematic data generation, computational data interpretation, and experimental validation and represent a synergistic and powerful means for conducting biological research.

BIOINSPIRED DESIGN AND DIRECTED EVOLUTION OF IRON CONTAINING ENZYMES FOR GREENSYNTHETIC PROCESSES AND BIOREMEDIATION

EPA Science Inventory

SU833912
Title: Bioinspired Design and Directed Evolution of Iron Containing Enzymes for Green Synthetic Processes and BioremediationEdward I. Solomon, Shaun D. Wong, Lei Liu, Caleb B. Bell, IIICynthia Nolt-Helms
Project Period: August 15, 2008 - August 14,...

Molecular Dynamics Investigation of the Substrate Binding Mechanism in Carboxylesterase

DOE PAGES

Chen, Qi; Luan, Zheng-Jiao; Cheng, Xiaolin; ...

2015-02-25

A recombinant carboxylesterase, cloned from Pseudomonas putida and designated as rPPE, is capable of catalyzing the bioresolution of racemic 2-acetoxy-2-(2 -chlorophenyl)acetate (rac-AcO-CPA) with excellent (S)-enantioselectivity. Semi-rational design of the enzyme showed that the W187H variant could increase the activity by ~100-fold compared to the wild type (WT) enzyme. In this study, we performed all-atom molecular dynamics (MD) simulations of both apo-rPPE and rPPE in complex with (S)-AcO-CPA to gain insights into the origin of the increased catalysis in the W187H mutant. Moreover, our results show differential binding of (S)-AcO-CPA in the WT and W187H enzymes, especially the interactions of themore » substrate with the two active site residues Ser159 and His286. The replacement of Trp187 by His leads to considerable structural rearrangement in the active site of W187H. Unlike in the WT rPPE, the cap domain in the W187 mutant shows an open conformation in the simulations of both apo and substrate-bound enzymes. This open conformation exposes the catalytic triad to the solvent through a water accessible channel, which may facilitate the entry of the substrate and/or the exit of the product. Binding free energy calculations confirmed that the substrate binds more strongly in W187H than in WT. Based on these computational results, furthermore, we predicted that the mutations W187Y and D287G might also be able to increase the substrate binding, thus improve the enzyme s catalytic efficiency. Experimental binding and kinetic assays on W187Y and D287G show improved catalytic efficiency over WT, but not W187H. Contrary to our prediction, W187Y shows slightly decreased substrate binding coupled with a 100 fold increase in turn-over rate, while in D287G the substrate binding is 8 times stronger but with a slightly reduced turn-over rate. Finally, our work provides important molecular-level insights into the binding of the (S)-AcO-CPA substrate to carboxylesterase rPPEs, which will help guide future development of more efficient rPPE variants.« less

Molecular Dynamics Investigation of the Substrate Binding Mechanism in Carboxylesterase

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

Chen, Qi; Luan, Zheng-Jiao; Cheng, Xiaolin

A recombinant carboxylesterase, cloned from Pseudomonas putida and designated as rPPE, is capable of catalyzing the bioresolution of racemic 2-acetoxy-2-(2 -chlorophenyl)acetate (rac-AcO-CPA) with excellent (S)-enantioselectivity. Semi-rational design of the enzyme showed that the W187H variant could increase the activity by ~100-fold compared to the wild type (WT) enzyme. In this study, we performed all-atom molecular dynamics (MD) simulations of both apo-rPPE and rPPE in complex with (S)-AcO-CPA to gain insights into the origin of the increased catalysis in the W187H mutant. Moreover, our results show differential binding of (S)-AcO-CPA in the WT and W187H enzymes, especially the interactions of themore » substrate with the two active site residues Ser159 and His286. The replacement of Trp187 by His leads to considerable structural rearrangement in the active site of W187H. Unlike in the WT rPPE, the cap domain in the W187 mutant shows an open conformation in the simulations of both apo and substrate-bound enzymes. This open conformation exposes the catalytic triad to the solvent through a water accessible channel, which may facilitate the entry of the substrate and/or the exit of the product. Binding free energy calculations confirmed that the substrate binds more strongly in W187H than in WT. Based on these computational results, furthermore, we predicted that the mutations W187Y and D287G might also be able to increase the substrate binding, thus improve the enzyme s catalytic efficiency. Experimental binding and kinetic assays on W187Y and D287G show improved catalytic efficiency over WT, but not W187H. Contrary to our prediction, W187Y shows slightly decreased substrate binding coupled with a 100 fold increase in turn-over rate, while in D287G the substrate binding is 8 times stronger but with a slightly reduced turn-over rate. Finally, our work provides important molecular-level insights into the binding of the (S)-AcO-CPA substrate to carboxylesterase rPPEs, which will help guide future development of more efficient rPPE variants.« less

Biocatalysis and biomimetics

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

Burrington, J.D.; Clark, D.S.

1989-01-01

This book presents recent advances in catalytic science and biotechnology. The chapters illustrate how many of the key challenges in biotechnology can be addressed by bringing together traditionally separate disciplines within chemistry and biology. The authors focus on emerging enabling technologies at the interfaces of catalysis and biology that will provide new opportunities for the chemicals industries. Key aspects to be presented within this major theme of catalysis and biotechnology are biomimetics and hybrid catalysts, biocatalytic applications of computers and expert systems, enzyme solid-state structure and immobilization, enzyme structure-activity relationships, and the use of enzymes under novel conditions.

Computational and experimental analysis of short peptide motifs for enzyme inhibition.

PubMed

Fu, Jinglin; Larini, Luca; Cooper, Anthony J; Whittaker, John W; Ahmed, Azka; Dong, Junhao; Lee, Minyoung; Zhang, Ting

2017-01-01

The metabolism of living systems involves many enzymes that play key roles as catalysts and are essential to biological function. Searching ligands with the ability to modulate enzyme activities is central to diagnosis and therapeutics. Peptides represent a promising class of potential enzyme modulators due to the large chemical diversity, and well-established methods for library synthesis. Peptides and their derivatives are found to play critical roles in modulating enzymes and mediating cellular uptakes, which are increasingly valuable in therapeutics. We present a methodology that uses molecular dynamics (MD) and point-variant screening to identify short peptide motifs that are critical for inhibiting β-galactosidase (β-Gal). MD was used to simulate the conformations of peptides and to suggest short motifs that were most populated in simulated conformations. The function of the simulated motifs was further validated by the experimental point-variant screening as critical segments for inhibiting the enzyme. Based on the validated motifs, we eventually identified a 7-mer short peptide for inhibiting an enzyme with low μM IC50. The advantage of our methodology is the relatively simplified simulation that is informative enough to identify the critical sequence of a peptide inhibitor, with a precision comparable to truncation and alanine scanning experiments. Our combined experimental and computational approach does not rely on a detailed understanding of mechanistic and structural details. The MD simulation suggests the populated motifs that are consistent with the results of the experimental alanine and truncation scanning. This approach appears to be applicable to both natural and artificial peptides. With more discovered short motifs in the future, they could be exploited for modulating biocatalysis, and developing new medicine.

Discrimination of acidic and alkaline enzyme using Chou's pseudo amino acid composition in conjunction with probabilistic neural network model.

PubMed

Khan, Zaheer Ullah; Hayat, Maqsood; Khan, Muazzam Ali

2015-01-21

Enzyme catalysis is one of the most essential and striking processes among of all the complex processes that have evolved in living organisms. Enzymes are biological catalysts, which play a significant role in industrial applications as well as in medical areas, due to profound specificity, selectivity and catalytic efficiency. Refining catalytic efficiency of enzymes has become the most challenging job of enzyme engineering, into acidic and alkaline. Discrimination of acidic and alkaline enzymes through experimental approaches is difficult, sometimes impossible due to lack of established structures. Therefore, it is highly desirable to develop a computational model for discriminating acidic and alkaline enzymes from primary sequences. In this study, we have developed a robust, accurate and high throughput computational model using two discrete sample representation methods Pseudo amino acid composition (PseAAC) and split amino acid composition. Various classification algorithms including probabilistic neural network (PNN), K-nearest neighbor, decision tree, multi-layer perceptron and support vector machine are applied to predict acidic and alkaline with high accuracy. 10-fold cross validation test and several statistical measures namely, accuracy, F-measure, and area under ROC are used to evaluate the performance of the proposed model. The performance of the model is examined using two benchmark datasets to demonstrate the effectiveness of the model. The empirical results show that the performance of PNN in conjunction with PseAAC is quite promising compared to existing approaches in the literature so for. It has achieved 96.3% accuracy on dataset1 and 99.2% on dataset2. It is ascertained that the proposed model might be useful for basic research and drug related application areas. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Novel Terpenoid from Elephantopus Scaber – Antibacterial Activity on Staphylococcus Aureus: A Substantiate Computational Approach

PubMed Central

Daisy, P.; Mathew, Salu; Suveena, S.; Rayan, Nirmala A.

2008-01-01

Staphylococcus aureus has gained much attention in the last decade as it is a major cause of the Urinary Tract Infection in Diabetic patients. The Extended Spectrum β-Lactamases (ESβL) producers are highly resistant to several conventional antibiotics. This limits the therapeutic options.Hence efforts are now taken to screen few medicinal plants, which are both economic and less toxic. Among the several plants screened, we have chosen the acetone extract of Elephantopus scaber from which we purified a new terpenoid for our study. Its structure was generated using CHEMSKETCH software and the activity prediction was done using PASS PREDICTION software. We have confirmed the mechanism of anti-bacterial effect of terpenoid using Computer – Aided Drug Design (CADD) with computational methods to simulate drug – receptor interactions. The Protein-Ligand interaction plays a significant role in the structural based drug designing. In this present study we have taken the Autolysin, the bacteriolytic enzyme, that digest the cell wall peptidoglycon. The autolysin and terpenoid were docked using HEX docking software and the docking score with minimum energy value of -209.54 was calculated. It infers that the terpenoid can inhibit the activity of autolysin by forming a strong atomic interaction with the active site residues. Hence the terpenoid can act as a drug for bacterial infections. Further investigations can be carried out to predict the activity of terpeniod on other targets. PMID:23675090

Designing universal primers for the isolation of DNA sequences encoding Proanthocyanidins biosynthetic enzymes in Crataegus aronia

PubMed Central

2012-01-01

Background Hawthorn is the common name of all plant species in the genus Crataegus, which belongs to the Rosaceae family. Crataegus are considered useful medicinal plants because of their high content of proanthocyanidins (PAs) and other related compounds. To improve PAs production in Crataegus tissues, the sequences of genes encoding PAs biosynthetic enzymes are required. Findings Different bioinformatics tools, including BLAST, multiple sequence alignment and alignment PCR analysis were used to design primers suitable for the amplification of DNA fragments from 10 candidate genes encoding enzymes involved in PAs biosynthesis in C. aronia. DNA sequencing results proved the utility of the designed primers. The primers were used successfully to amplify DNA fragments of different PAs biosynthesis genes in different Rosaceae plants. Conclusion To the best of our knowledge, this is the first use of the alignment PCR approach to isolate DNA sequences encoding PAs biosynthetic enzymes in Rosaceae plants. PMID:22883984

Designing universal primers for the isolation of DNA sequences encoding Proanthocyanidins biosynthetic enzymes in Crataegus aronia.

PubMed

Zuiter, Afnan Saeid; Sawwan, Jammal; Al Abdallat, Ayed

2012-08-10

Hawthorn is the common name of all plant species in the genus Crataegus, which belongs to the Rosaceae family. Crataegus are considered useful medicinal plants because of their high content of proanthocyanidins (PAs) and other related compounds. To improve PAs production in Crataegus tissues, the sequences of genes encoding PAs biosynthetic enzymes are required. Different bioinformatics tools, including BLAST, multiple sequence alignment and alignment PCR analysis were used to design primers suitable for the amplification of DNA fragments from 10 candidate genes encoding enzymes involved in PAs biosynthesis in C. aronia. DNA sequencing results proved the utility of the designed primers. The primers were used successfully to amplify DNA fragments of different PAs biosynthesis genes in different Rosaceae plants. To the best of our knowledge, this is the first use of the alignment PCR approach to isolate DNA sequences encoding PAs biosynthetic enzymes in Rosaceae plants.

Design, synthesis, and evaluation of inhibitors of trypanosomal and leishmanial dihydrofolate reductase.

PubMed

Chowdhury, S F; Villamor, V B; Guerrero, R H; Leal, I; Brun, R; Croft, S L; Goodman, J M; Maes, L; Ruiz-Perez, L M; Pacanowska, D G; Gilbert, I H

1999-10-21

This paper concerns the design, synthesis, and evaluation of inhibitors of leishmanial and trypanosomal dihydrofolate reductase. Initially study was made of the structures of the leishmanial and human enzyme active sites to see if there were significant differences which could be exploited for selective drug design. Then a series of compounds were synthesized based on 5-benzyl-2, 4-diaminopyrimidines. These compounds were assayed against the protozoan and human enzymes and showed selectivity for the protozoan enzymes. The structural data was then used to rationalize the enzyme assay data. Compounds were also tested against the clinically relevant forms of the intact parasite. Activity was seen against the trypanosomes for a number of compounds. The compounds were in general less active against Leishmania. This latter result may be due to uptake problems. Two of the compounds also showed some in vivo activity in a model of African trypanosomiasis.

Heavy enzymes--experimental and computational insights in enzyme dynamics.

PubMed

Swiderek, Katarzyna; Ruiz-Pernía, J Javier; Moliner, Vicent; Tuñón, Iñaki

2014-08-01

The role of protein motions in the chemical step of enzyme-catalyzed reactions is the subject of an open debate in the scientific literature. The systematic use of isotopically substituted enzymes has been revealed as a useful tool to quantify the role of these motions. According to the Born-Oppenheimer approximation, changing the mass of the protein does not change the forces acting on the system but alters the frequencies of the protein motions, which in turn can affect the rate constant. Experimental and theoretical studies carried out in this field are presented in this article and discussed in the framework of Transition State Theory. Copyright © 2014 Elsevier Ltd. All rights reserved.

Structural insight of dopamine β-hydroxylase, a drug target for complex traits, and functional significance of exonic single nucleotide polymorphisms.

PubMed

Kapoor, Abhijeet; Shandilya, Manish; Kundu, Suman

2011-01-01

Human dopamine β-hydroxylase (DBH) is an important therapeutic target for complex traits. Several single nucleotide polymorphisms (SNPs) have also been identified in DBH with potential adverse physiological effect. However, difficulty in obtaining diffractable crystals and lack of a suitable template for modeling the protein has ensured that neither crystallographic three-dimensional structure nor computational model for the enzyme is available to aid rational drug design, prediction of functional significance of SNPs or analytical protein engineering. Adequate biochemical information regarding human DBH, structural coordinates for peptidylglycine alpha-hydroxylating monooxygenase and computational data from a partial model of rat DBH were used along with logical manual intervention in a novel way to build an in silico model of human DBH. The model provides structural insight into the active site, metal coordination, subunit interface, substrate recognition and inhibitor binding. It reveals that DOMON domain potentially promotes tetramerization, while substrate dopamine and a potential therapeutic inhibitor nepicastat are stabilized in the active site through multiple hydrogen bonding. Functional significance of several exonic SNPs could be described from a structural analysis of the model. The model confirms that SNP resulting in Ala318Ser or Leu317Pro mutation may not influence enzyme activity, while Gly482Arg might actually do so being in the proximity of the active site. Arg549Cys may cause abnormal oligomerization through non-native disulfide bond formation. Other SNPs like Glu181, Glu250, Lys239 and Asp290 could potentially inhibit tetramerization thus affecting function. The first three-dimensional model of full-length human DBH protein was obtained in a novel manner with a set of experimental data as guideline for consistency of in silico prediction. Preliminary physicochemical tests validated the model. The model confirms, rationalizes and provides structural basis for several biochemical data and claims testable hypotheses regarding function. It provides a reasonable template for drug design as well.

Computational Investigations of Trichoderma Reesei Cel7A Suggest New Routes for Enzyme Activity Improvements

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

Beckham, G. T.; Payne, C. M.; Bu, L.

2012-01-01

The Trichoderma reesei Family 7 cellulase (Cel7A) is a key industrial enzyme in the production of biofuels from lignocellulosic biomass. It is a multi-modular enzyme with a Family 1 carbohydrate-binding module, a flexible O-glycosylated linker, and a large catalytic domain. We have used simulation to elucidate new functions for the 3 sub-domains, which suggests new routes to increase the activity of this central enzyme. These findings include new roles for glycosylation, which we have shown can be used to tune the binding affinity. We have also examined the structures of the catalytically-active complex of Cel7A and its non-processive counterpart, Cel7B,more » engaged on cellulose, which suggests allosteric mechanisms involved in chain binding when these cellulases are complexed on cellulose. Our computational results also suggest that product inhibition varies significantly between Cel7A and Cel7B, and we offer a molecular-level explanation for this observation. Finally, we discuss simulations of the absolute and relative binding free energy of cellulose ligands and various mutations along the CD tunnel, which will affect processivity and the ability of Cel7A (and related enzymes) to digest cellulose. These results highlight new considerations in protein engineering for processive and non-processive cellulases for production of lignocellulosic biofuels.« less

Rational design for the stability improvement of Armillariella tabescens β-mannanase MAN47 based on N-glycosylation modification.

PubMed

Hu, Weixiong; Liu, Xiaoyun; Li, Yufeng; Liu, Daling; Kuang, Zhihe; Qian, Chuiwen; Yao, Dongsheng

2017-02-01

β-Mannanase has been widely used in industries such as food and feed processing and thus has been a target enzyme for biotechnological development. In this study, we sought to improve the stability and protease resistance of a recombinant β-mannanase, MAN47 from Armillariella tabescens, through rationally designed N-glycosylation. Based on homology modeling, molecular docking, secondary structure analysis and glycosylation feasibility analysis, an enhanced aromatic sequon sequence was introduced into specific MAN47 loop regions to facilitate N-glycosylation. The mutant enzymes were expressed in Pichia pastoris SMD1168, and their thermal stability, pH stability, trypsin resistance and pepsin resistance were determined. Two mutant MAN47 enzymes, g-123 and g-347, were glycosylated as expected when expressed in yeast, and their thermal stability, pH stability, and protease resistance were significantly improved compared to the wild-type enzyme. An enzyme with multiple stability characterizations has broad prospects in practical applications, and the rational design N-glycosylation strategy may have applications in simultaneously improving several properties of other biotechnological targets. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

β-galactosidase Production by Aspergillus niger ATCC 9142 Using Inexpensive Substrates in Solid-State Fermentation: Optimization by Orthogonal Arrays Design.

PubMed

Kazemi, Samaneh; Khayati, Gholam; Faezi-Ghasemi, Mohammad

2016-01-01

Enzymatic hydrolysis of lactose is one of the most important biotechnological processes in the food industry, which is accomplished by enzyme β-galactosidase (β-gal, β-D-galactoside galactohydrolase, EC 3.2.1.23), trivial called lactase. Orthogonal arrays design is an appropriate option for the optimization of biotechnological processes for the production of microbial enzymes. Design of experimental (DOE) methodology using Taguchi orthogonal array (OA) was employed to screen the most significant levels of parameters, including the solid substrates (wheat straw, rice straw, and peanut pod), the carbon/nitrogen (C/N) ratios, the incubation time, and the inducer. The level of β-gal production was measured by a photometric enzyme activity assay using the artificial substrate ortho-Nitrophenyl-β-D-galactopyranoside. The results showed that C/N ratio (0.2% [w/v], incubation time (144 hour), and solid substrate (wheat straw) were the best conditions determined by the design of experiments using the Taguchi approach. Our finding showed that the use of rice straw and peanut pod, as solid-state substrates, led to 2.041-folds increase in the production of the enzyme, as compared to rice straw. In addition, the presence of an inducer did not have any significant impact on the enzyme production levels.

Oriented and selective enzyme immobilization on functionalized silica carrier using the cationic binding module Z basic2: design of a heterogeneous D-amino acid oxidase catalyst on porous glass.

PubMed

Bolivar, Juan M; Nidetzky, Bernd

2012-06-01

D-amino acid oxidase from Trigonopsis variabilis (TvDAO) is applied in industry for the synthesis of pharmaceutical intermediates. Because free TvDAO is extremely sensitive to exposure to gas-liquid interfaces, biocatalytic processing is usually performed with enzyme immobilizates that offer enhanced stability under bubble aeration. We herein present an "Immobilization by Design" approach that exploits engineered charge complementarity between enzyme and carrier to optimize key features of the immobilization of TvDAO. A fusion protein between TvDAO and the positively charged module Z(basic2) was generated, and a corresponding oppositely charged carrier was obtained by derivatization of mesoporous glass with 3-(trihydroxysilyl)-1-propane-sulfonic acid. Using 250 mM NaCl for charge screening at pH 7.0, the Z(basic2) fusion of TvDAO was immobilized directly from E. coli cell extract with almost absolute selectivity and full retention of catalytic effectiveness of the isolated enzyme in solution. Attachment of the homodimeric enzyme to the carrier was quasi-permanent in low-salt buffer but fully reversible upon elution with 5 M NaCl. Immobilized TvDAO was not sensitive to bubble aeration and received substantial (≥ tenfold) stabilization of the activity at 45°C as compared to free enzyme, suggesting immobilization via multisubunit oriented interaction of enzyme with the insoluble carrier. The Z(basic2) enzyme immobilizate was demonstrated to serve as re-usable heterogeneous catalyst for D-amino acid oxidation. Z(basic2) -mediated binding on a sulfonic acid group-containing glass carrier constitutes a generally useful strategy of enzyme immobilization that supports transition from case-specific empirical development to rational design. Copyright © 2012 Wiley Periodicals, Inc.

FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants.

PubMed

Bednar, David; Beerens, Koen; Sebestova, Eva; Bendl, Jaroslav; Khare, Sagar; Chaloupkova, Radka; Prokop, Zbynek; Brezovsky, Jan; Baker, David; Damborsky, Jiri

2015-11-01

There is great interest in increasing proteins' stability to enhance their utility as biocatalysts, therapeutics, diagnostics and nanomaterials. Directed evolution is a powerful, but experimentally strenuous approach. Computational methods offer attractive alternatives. However, due to the limited reliability of predictions and potentially antagonistic effects of substitutions, only single-point mutations are usually predicted in silico, experimentally verified and then recombined in multiple-point mutants. Thus, substantial screening is still required. Here we present FireProt, a robust computational strategy for predicting highly stable multiple-point mutants that combines energy- and evolution-based approaches with smart filtering to identify additive stabilizing mutations. FireProt's reliability and applicability was demonstrated by validating its predictions against 656 mutations from the ProTherm database. We demonstrate that thermostability of the model enzymes haloalkane dehalogenase DhaA and γ-hexachlorocyclohexane dehydrochlorinase LinA can be substantially increased (ΔTm = 24°C and 21°C) by constructing and characterizing only a handful of multiple-point mutants. FireProt can be applied to any protein for which a tertiary structure and homologous sequences are available, and will facilitate the rapid development of robust proteins for biomedical and biotechnological applications.

Statistical Optimization of Fibrinolytic Enzyme Production Using Agroresidues by Bacillus cereus IND1 and Its Thrombolytic Activity In Vitro

PubMed Central

Prakash Vincent, Samuel Gnana

2014-01-01

A potent fibrinolytic enzyme-producing Bacillus cereus IND1 was isolated from the Indian food, rice. Solid-state fermentation was carried out using agroresidues for the production of fibrinolytic enzyme. Among the substrates, wheat bran supported more enzyme production and has been used for the optimized enzyme production by statistical approach. Two-level full-factorial design demonstrated that moisture, supplementation of beef extract, and sodium dihydrogen phosphate have significantly influenced enzyme production (P < 0.05). A central composite design resulted in the production of 3699 U/mL of enzyme in the presence of 0.3% (w/w) beef extract and 0.05% (w/w) sodium dihydrogen phosphate, at 100% (v/w) moisture after 72 h of fermentation. The enzyme production increased fourfold compared to the original medium. This enzyme was purified to homogeneity by ammonium sulfate precipitation, diethylaminoethyl-cellulose ion-exchange chromatography, Sephadex G-75 gel filtration chromatography, and casein-agarose affinity chromatography and had an apparent molecular mass of 29.5 kDa. The optimum pH and temperature for the activity of fibrinolytic enzyme were found to be 8.0 and 60°C, respectively. This enzyme was highly stable at wide pH range (7.0–9.0) and showed 27% ± 6% enzyme activity after initial denaturation at 60°C for 1 h. In vitro assays revealed that the enzyme could activate plasminogen and significantly degraded the fibrin net of blood clot, which suggests its potential as an effective thrombolytic agent. PMID:25003130

Structure Based Library Design (SBLD) for new 1,4-dihydropyrimidine scaffold as simultaneous COX-1/COX-2 and 5-LOX inhibitors.

PubMed

Lokwani, Deepak; Azad, Rajaram; Sarkate, Aniket; Reddanna, Pallu; Shinde, Devanand

2015-08-01

The various scaffolds containing 1,4-dihydropyrimidine ring were designed by considering the environment of the active site of COX-1/COX-2 and 5-LOX enzymes. The structure-based library design approach, including the focused library design (Virtual Combinatorial Library Design) and virtual screening was used to select the 1,4-dihydropyrimidine scaffold for simultaneous inhibition of both enzyme pathways (COX-1/COX-2 and 5-LOX). The virtual library on each 1,4-dihydropyrimidine scaffold was enumerated in two alternative ways. In first way, the chemical reagents at R groups were filtered by docking of scaffold with single position substitution, that is, only at R1, or R2, or R3, … Rn on COX-2 enzyme using Glide XP docking mode. The structures that do not dock well were removed and the library was enumerated with filtered chemical reagents. In second alternative way, the single position docking stage was bypassed, and the entire library was enumerated using all chemical reagents by docking on the COX-2 enzyme. The entire library of approximately 15,629 compounds obtained from both ways after screening for drug like properties, were further screened for their binding affinity against COX-1 and 5-LOX enzymes using Virtual Screening Workflow. Finally, 142 hits were obtained and divided into two groups based on their binding affinity for COX-1/COX-2 and for both enzyme pathways (COX-1/COX-2 and 5-LOX). The ten molecules were selected, synthesized and evaluated for their COX-1, COX-2 and 5-LOX inhibiting activity. Copyright © 2015 Elsevier Ltd. All rights reserved.

Computer-Aided Drug Design (CADD): Methodological Aspects and Practical Applications in Cancer Research

NASA Astrophysics Data System (ADS)

Gianti, Eleonora

Computer-Aided Drug Design (CADD) has deservedly gained increasing popularity in modern drug discovery (Schneider, G.; Fechner, U. 2005), whether applied to academic basic research or the pharmaceutical industry pipeline. In this work, after reviewing theoretical advancements in CADD, we integrated novel and stateof- the-art methods to assist in the design of small-molecule inhibitors of current cancer drug targets, specifically: Androgen Receptor (AR), a nuclear hormone receptor required for carcinogenesis of Prostate Cancer (PCa); Signal Transducer and Activator of Transcription 5 (STAT5), implicated in PCa progression; and Epstein-Barr Nuclear Antigen-1 (EBNA1), essential to the Epstein Barr Virus (EBV) during latent infections. Androgen Receptor. With the aim of generating binding mode hypotheses for a class (Handratta, V.D. et al. 2005) of dual AR/CYP17 inhibitors (CYP17 is a key enzyme for androgens biosynthesis and therefore implicated in PCa development), we successfully implemented a receptor-based computational strategy based on flexible receptor docking (Gianti, E.; Zauhar, R.J. 2012). Then, with the ultimate goal of identifying novel AR binders, we performed Virtual Screening (VS) by Fragment-Based Shape Signatures, an improved version of the original method developed in our Laboratory (Zauhar, R.J. et al. 2003), and we used the results to fully assess the high-level performance of this innovative tool in computational chemistry. STAT5. The SRC Homology 2 (SH2) domain of STAT5 is responsible for phospho-peptide recognition and activation. As a keystone of Structure-Based Drug Design (SBDD), we characterized key residues responsible for binding. We also generated a model of STAT5 receptor bound to a phospho-peptide ligand, which was validated by docking publicly known STAT5 inhibitors. Then, we performed Shape Signatures- and docking-based VS of the ZINC database (zinc.docking.org), followed by Molecular Mechanics Generalized Born Surface Area (MMGBSA) simulations, paired with Principal Component Analysis (PCA) of top-scoring hits to identify novel lead molecules likely to be active against STAT5. EBNA1 is the only viral protein consistently expressed in the many EBV-associated tumors, and is required for viral genome maintenance during latent infection. To immediately assist SBDD, we computationally identified "druggable" binding sites of EBNA1, and our predictions were later confirmed by experimental evidence (The Wistar Institute proprietary data).

Design of a single-step immunoassay principle based on the combination of an enzyme-labeled antibody release coating and a hydrogel copolymerized with a fluorescent enzyme substrate in a microfluidic capillary device.

PubMed

Wakayama, Hideki; Henares, Terence G; Jigawa, Kaede; Funano, Shun-ichi; Sueyoshi, Kenji; Endo, Tatsuro; Hisamoto, Hideaki

2013-11-21

A combination of an enzyme-labeled antibody release coating and a novel fluorescent enzyme substrate-copolymerized hydrogel in a microchannel for a single-step, no-wash microfluidic immunoassay is demonstrated. This hydrogel discriminates the free enzyme-conjugated antibody from an antigen-enzyme-conjugated antibody immunocomplex based on the difference in molecular size. A selective and sensitive immunoassay, with 10-1000 ng mL(-1) linear range, is reported.

Rational engineering of a mesohalophilic carbonic anhydrase to an extreme halotolerant biocatalyst

PubMed Central

Warden, Andrew C.; Williams, Michelle; Peat, Thomas S.; Seabrook, Shane A.; Newman, Janet; Dojchinov, Greg; Haritos, Victoria S.

2015-01-01

Enzymes expressed by highly salt-tolerant organisms show many modifications compared with salt-affected counterparts including biased amino acid and lower α-helix content, lower solvent accessibility and negative surface charge. Here, we show that halotolerance can be generated in an enzyme solely by modifying surface residues. Rational design of carbonic anhydrase II is undertaken in three stages replacing 18 residues in total, crystal structures confirm changes are confined to surface residues. Catalytic activities and thermal unfolding temperatures of the designed enzymes increase at high salt concentrations demonstrating their shift to halotolerance, whereas the opposite response is found in the wild-type enzyme. Molecular dynamics calculations reveal a key role for sodium ions in increasing halotolerant enzyme stability largely through interactions with the highly ordered first Na+ hydration shell. For the first time, an approach to generate extreme halotolerance, a trait with broad application in industrial biocatalysis, in a wild-type enzyme is demonstrated. PMID:26687908

Biomimicry enhances sequential reactions of tethered glycolytic enzymes, TPI and GAPDHS.

PubMed

Mukai, Chinatsu; Gao, Lizeng; Bergkvist, Magnus; Nelson, Jacquelyn L; Hinchman, Meleana M; Travis, Alexander J

2013-01-01

Maintaining activity of enzymes tethered to solid interfaces remains a major challenge in developing hybrid organic-inorganic devices. In nature, mammalian spermatozoa have overcome this design challenge by having glycolytic enzymes with specialized targeting domains that enable them to function while tethered to a cytoskeletal element. As a step toward designing a hybrid organic-inorganic ATP-generating system, we implemented a biomimetic site-specific immobilization strategy to tether two glycolytic enzymes representing different functional enzyme families: triose phosphoisomerase (TPI; an isomerase) and glyceraldehyde 3-phosphate dehydrogenase (GAPDHS; an oxidoreductase). We then evaluated the activities of these enzymes in comparison to when they were tethered via classical carboxyl-amine crosslinking. Both enzymes show similar surface binding regardless of immobilization method. Remarkably, specific activities for both enzymes were significantly higher when tethered using the biomimetic, site-specific immobilization approach. Using this biomimetic approach, we tethered both enzymes to a single surface and demonstrated their function in series in both forward and reverse directions. Again, the activities in series were significantly higher in both directions when the enzymes were coupled using this biomimetic approach versus carboxyl-amine binding. Our results suggest that biomimetic, site-specific immobilization can provide important functional advantages over chemically specific, but non-oriented attachment, an important strategic insight given the growing interest in recapitulating entire biological pathways on hybrid organic-inorganic devices.

Biomimicry Enhances Sequential Reactions of Tethered Glycolytic Enzymes, TPI and GAPDHS

PubMed Central

Mukai, Chinatsu; Gao, Lizeng; Bergkvist, Magnus; Nelson, Jacquelyn L.; Hinchman, Meleana M.; Travis, Alexander J.

2013-01-01

Maintaining activity of enzymes tethered to solid interfaces remains a major challenge in developing hybrid organic-inorganic devices. In nature, mammalian spermatozoa have overcome this design challenge by having glycolytic enzymes with specialized targeting domains that enable them to function while tethered to a cytoskeletal element. As a step toward designing a hybrid organic-inorganic ATP-generating system, we implemented a biomimetic site-specific immobilization strategy to tether two glycolytic enzymes representing different functional enzyme families: triose phosphoisomerase (TPI; an isomerase) and glyceraldehyde 3-phosphate dehydrogenase (GAPDHS; an oxidoreductase). We then evaluated the activities of these enzymes in comparison to when they were tethered via classical carboxyl-amine crosslinking. Both enzymes show similar surface binding regardless of immobilization method. Remarkably, specific activities for both enzymes were significantly higher when tethered using the biomimetic, site-specific immobilization approach. Using this biomimetic approach, we tethered both enzymes to a single surface and demonstrated their function in series in both forward and reverse directions. Again, the activities in series were significantly higher in both directions when the enzymes were coupled using this biomimetic approach versus carboxyl-amine binding. Our results suggest that biomimetic, site-specific immobilization can provide important functional advantages over chemically specific, but non-oriented attachment, an important strategic insight given the growing interest in recapitulating entire biological pathways on hybrid organic-inorganic devices. PMID:23626684

Computational design of bio-inspired carnosine-based HOBr antioxidants

NASA Astrophysics Data System (ADS)

Sarrami, Farzaneh; Yu, Li-Juan; Karton, Amir

2017-10-01

During a respiratory burst the enzyme myeloperoxidase generates significant amounts of hypohalous acids (HOX, X = Cl and Br) in order to inflict oxidative damage upon invading pathogens. However, excessive production of these potent oxidants is associated with numerous inflammatory diseases. It has been suggested that the endogenous antioxidant carnosine is an effective HOCl scavenger. Recent computational and experimental studies suggested that an intramolecular Cl+ transfer from the imidazole ring to the terminal amine might play an important role in the antioxidant activity of carnosine. Based on high-level ab initio calculations, we propose a similar reaction mechanism for the intramolecular Br+ transfer in carnosine. These results suggest that carnosine may be an effective HOBr scavenger. On the basis of the proposed reaction mechanism, we proceed to design systems that share similar structural features to carnosine but with enhanced HOX scavenging capabilities for X = Cl and Br. We find that (i) elongating the β-alanyl-glycyl side chain by one carbon reduces the reaction barriers by up to 44%, and (ii) substituting the imidazole ring with strong electron-donating groups reduces the reaction barriers by similar amounts. We also show that the above structural and electronic effects are largely additive. In an antioxidant candidate that involves both of these effects the reaction barriers are reduced by 71%.

Enormous Hydrogen Bond Strength Enhancement through π-Conjugation Gain: Implications for Enzyme Catalysis.

PubMed

Wu, Chia-Hua; Ito, Keigo; Buytendyk, Allyson M; Bowen, K H; Wu, Judy I

2017-08-22

Surprisingly large resonance-assistance effects may explain how some enzymes form extremely short, strong hydrogen bonds to stabilize reactive oxyanion intermediates and facilitate catalysis. Computational models for several enzymic residue-substrate interactions reveal that when a π-conjugated, hydrogen bond donor (XH) forms a hydrogen bond to a charged substrate (Y - ), XH can become significantly more π-electron delocalized, and this "extra" stabilization may boost the [XH···Y - ] hydrogen bond strength by ≥15 kcal/mol. This reciprocal relationship departs from the widespread pK a concept (i.e., the idea that short, strong hydrogen bonds form when the interacting moieties have matching pK a values), which has been the rationale for enzymic acid-base reactions. The findings presented here provide new insight into how short, strong hydrogen bonds could form in enzymes.

Peroxide Activation for Electrophilic Reactivity by the Binuclear Non-heme Iron Enzyme AurF

DOE PAGES

Park, Kiyoung; Li, Ning; Kwak, Yeonju; ...

2017-05-01

Binuclear non-heme iron enzymes activate O 2 for diverse chemistries that include oxygenation of organic substrates and hydrogen atom abstraction. This process often involves the formation of peroxo-bridged biferric intermediates, only some of which can perform electrophilic reactions. To elucidate the geometric and electronic structural requirements to activate peroxo reactivity, the active peroxo intermediate in 4-aminobenzoate N-oxygenase (AurF) has been characterized spectroscopically and computationally. A magnetic circular dichroism study of reduced AurF shows that its electronic and geometric structures are poised to react rapidly with O 2. Nuclear resonance vibrational spectroscopic definition of the peroxo intermediate formed in this reactionmore » shows that the active intermediate has a protonated peroxo bridge. Density functional theory computations on the structure established here show that the protonation activates peroxide for electrophilic/single-electron-transfer reactivity. As a result, this activation of peroxide by protonation is likely also relevant to the reactive peroxo intermediates in other binuclear non-heme iron enzymes.« less

Peroxide Activation for Electrophilic Reactivity by the Binuclear Non-heme Iron Enzyme AurF

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

Park, Kiyoung; Li, Ning; Kwak, Yeonju

Binuclear non-heme iron enzymes activate O 2 for diverse chemistries that include oxygenation of organic substrates and hydrogen atom abstraction. This process often involves the formation of peroxo-bridged biferric intermediates, only some of which can perform electrophilic reactions. To elucidate the geometric and electronic structural requirements to activate peroxo reactivity, the active peroxo intermediate in 4-aminobenzoate N-oxygenase (AurF) has been characterized spectroscopically and computationally. A magnetic circular dichroism study of reduced AurF shows that its electronic and geometric structures are poised to react rapidly with O 2. Nuclear resonance vibrational spectroscopic definition of the peroxo intermediate formed in this reactionmore » shows that the active intermediate has a protonated peroxo bridge. Density functional theory computations on the structure established here show that the protonation activates peroxide for electrophilic/single-electron-transfer reactivity. As a result, this activation of peroxide by protonation is likely also relevant to the reactive peroxo intermediates in other binuclear non-heme iron enzymes.« less

Enzyme-MOF (metal-organic framework) composites.

PubMed

Lian, Xizhen; Fang, Yu; Joseph, Elizabeth; Wang, Qi; Li, Jialuo; Banerjee, Sayan; Lollar, Christina; Wang, Xuan; Zhou, Hong-Cai

2017-06-06

The ex vivo application of enzymes in various processes, especially via enzyme immobilization techniques, has been extensively studied in recent years in order to enhance the recyclability of enzymes, to minimize enzyme contamination in the product, and to explore novel horizons for enzymes in biomedical applications. Possessing remarkable amenability in structural design of the frameworks as well as almost unparalelled surface tunability, Metal-Organic Frameworks (MOFs) have been gaining popularity as candidates for enzyme immobilization platforms. Many MOF-enzyme composites have achieved unprecedented results, far outperforming free enzymes in many aspects. This review summarizes recent developments of MOF-enzyme composites with special emphasis on preparative techniques and the synergistic effects of enzymes and MOFs. The applications of MOF-enzyme composites, primarily in transferation, catalysis and sensing, are presented as well. The enhancement of enzymatic activity of the composites over free enzymes in biologically incompatible conditions is emphasized in many cases.

Engineering a thermostable fungal GH10 xylanase, importance of N-terminal amino acids.

PubMed

Song, Letian; Tsang, Adrian; Sylvestre, Michel

2015-06-01

Xylanases are used in many industrial processes including pulp bleaching, baking, detergent, and the hydrolysis of plant cell wall in biofuels production. In this work we have evolved a single domain GH10 xylanase, Xyn10A_ASPNG, from Aspergillus niger to improve its thermostability. We introduced a rational approach involving as the first step a computational analysis to guide the design of a mutagenesis library in targeted regions which identified thermal important residues that were subsequently randomly mutagenized through rounds of iterative saturation mutagenesis (ISM). Focusing on five residues, four rounds of ISM had generated a quintuple mutant 4S1 (R25W/V29A/I31L/L43F/T58I) which exhibited thermal inactivation half-life (t1/2 ) at 60°C that was prolonged by 30 folds in comparison with wild-type enzyme. Whereas the wild-type enzyme retained 0.2% of its initial activity after a heat treatment of 10 min at 60°C and was completely inactivated after 2 min at 65°C, 4S1 mutant retained 30% of its initial activity after 15 min heating at 65°C. Furthermore, the mutant melting temperature (Tm ) increased by 17.4°C compared to the wild type. Each of the five mutations in 4S1 was found to contribute to thermoresistance, but the dramatic improvement of enzyme thermoresistance of 4S1 was attributed to the synergistic effects of the five mutations. Comparison of biochemical data and model structure between 4S1 and the wild-type enzyme suggested that the N-terminal coil of the enzyme is important in stabilizing GH10 xylanase structure. Based on model structure analyses, we propose that enforced hydrophobic interactions within N-terminal elements and between N- and C-terminal ends are responsible for the improved thermostability of Xyn10A_ASPNG. © 2015 Wiley Periodicals, Inc.

Preliminary Identification and Typing of Pathogenic and Toxigenic Fusarium Species Using Restriction Digestion of ITS1-5.8S rDNA-ITS2 Region.

PubMed

Mirhendi, H; Ghiasian, A; Vismer, Hf; Asgary, Mr; Jalalizand, N; Arendrup, Mc; Makimura, K

2010-01-01

Fusarium species are capable of causing a wide range of crop plants infections as well as uncommon human infections. Many species of the genus produce mycotoxins, which are responsible for acute or chronic diseases in animals and humans. Identification of Fusaria to the species level is necessary for biological, epidemiological, pathological, and toxicological purposes. In this study, we undertook a computer-based analysis of ITS1-5.8SrDNA-ITS2 in 192 GenBank sequences from 36 Fusarium species to achieve data for establishing a molecular method for specie-specific identification. Sequence data and 610 restriction enzymes were analyzed for choosing RFLP profiles, and subsequently designed and validated a PCR-restriction enzyme system for identification and typing of species. DNA extracted from 32 reference strains of 16 species were amplified using ITS1 and ITS4 universal primers followed by sequencing and restriction enzyme digestion of PCR products. The following 3 restriction enzymes TasI, ItaI and CfoI provide the best discriminatory power. Using ITS1 and ITS4 primers a product of approximately 550bp was observed for all Fusarium strains, as expected regarding the sequence analyses. After RFLP of the PCR products, some species were definitely identified by the method and some strains had different patterns in same species. Our profile has potential not only for identification of species, but also for genotyping of strains. On the other hand, some Fusarium species were 100% identical in their ITS-5.8SrDNA-ITS2 sequences, therefore differentiation of these species is impossible regarding this target alone. ITS-PCR-RFLP method might be useful for preliminary differentiation and typing of most common Fusarium species.

Comparison of dynamics of wildtype and V94M human UDP-galactose 4-epimerase-A computational perspective on severe epimerase-deficiency galactosemia.

PubMed

Timson, David J; Lindert, Steffen

2013-09-10

UDP-galactose 4'-epimerase (GALE) catalyzes the interconversion of UDP-galactose and UDP-glucose, an important step in galactose catabolism. Type III galactosemia, an inherited metabolic disease, is associated with mutations in human GALE. The V94M mutation has been associated with a very severe form of type III galactosemia. While a variety of structural and biochemical studies have been reported that elucidate differences between the wildtype and this mutant form of human GALE, little is known about the dynamics of the protein and how mutations influence structure and function. We performed molecular dynamics simulations on the wildtype and V94M enzyme in different states of substrate and cofactor binding. In the mutant, the average distance between the substrate and both a key catalytic residue (Tyr157) and the enzyme-bound NAD+ cofactor and the active site dynamics are altered making substrate binding slightly less stable. However, overall stability or dynamics of the protein is not altered. This is consistent with experimental findings that the impact is largely on the turnover number (kcat), with less substantial effects on Km. Active site fluctuations were found to be correlated in enzyme with substrate bound to just one of the subunits in the homodimer suggesting inter-subunit communication. Greater active site loop mobility in human GALE compared to the equivalent loop in Escherichia coli GALE explains why the former can catalyze the interconversion of UDP-N-acetylgalactosamine and UDP-N-acetylglucosamine while the bacterial enzyme cannot. This work illuminates molecular mechanisms of disease and may inform the design of small molecule therapies for type III galactosemia. Copyright © 2013 Elsevier B.V. All rights reserved.

An investigation into the applicability of the semiempirical method PM7 for modeling the catalytic mechanism in the enzyme chymotrypsin.

PubMed

Stewart, James J P

2017-05-01

The catalytic cycle for the serine protease α-chymotrypsin was investigated in an attempt to determine the suitability of using the semiempirical method PM7 in the program MOPAC for investigating enzyme-catalyzed reactions. All six classical intermediates were modeled using standard methods, and were characterized as stable minima on the potential energy surface. Using a modified saddle point optimization method, five transition states were located and verified both by vibrational and by intrinsic reaction coordinate analysis. Some individual features, such as the hydrogen bonds in the oxyanion hole, the nature of various electrostatic interactions, and the role of Met192, were examined. This involved designing and running computational experiments to model mutations that would allow features of interest, in particular the energies involved, to be isolated. Three features within the enzyme were examined in detail: the reaction site itself, where covalent bonds were made and broken, the electrostatic effects of the buried aspartate anion, a passive but essential component of the catalytic triad, and the oxyanion hole, where hydrogen bonds help stabilize charged intermediates. With one minor exception, all phenomena investigated agreed with previously-reported descriptions. This result, along with the fact that all the techniques used were relatively straightforward, leads to the recommendation that PM7 and related methods, such as PM6-D3H4, are appropriate for modeling similar enzyme-catalyzed reactions. Graphical abstract Fifth of six transition states, showing water splitting into hydroxyl anion and a proton, to form the second tetrahedral intermediate and histidinium ion. Atoms of the water molecule involved in the hydrolysis are indicated by halos.

Enzyme Activity Experiments Using a Simple Spectrophotometer

ERIC Educational Resources Information Center

Hurlbut, Jeffrey A.; And Others

1977-01-01

Experimental procedures for studying enzyme activity using a Spectronic 20 spectrophotometer are described. The experiments demonstrate the effect of pH, temperature, and inhibitors on enzyme activity and allow the determination of Km, Vmax, and Kcat. These procedures are designed for teaching large lower-level biochemistry classes. (MR)

The ascent of man(made oxidoreductases).

PubMed

Grayson, Katie J; Anderson, Jl Ross

2018-05-10

Though established 40 years ago, the field of de novo protein design has recently come of age, with new designs exhibiting an unprecedented level of sophistication in structure and function. With respect to catalysis, de novo enzymes promise to revolutionise the industrial production of useful chemicals and materials, while providing new biomolecules as plug-and-play components in the metabolic pathways of living cells. To this end, there are now de novo metalloenzymes that are assembled in vivo, including the recently reported C45 maquette, which can catalyse a variety of substrate oxidations with efficiencies rivalling those of closely related natural enzymes. Here we explore the successful design of this de novo enzyme, which was designed to minimise the undesirable complexity of natural proteins using a minimalistic bottom-up approach. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Protonation States of Homocitrate and Nearby Residues in Nitrogenase Studied by Computational Methods and Quantum Refinement.

PubMed

Cao, Lili; Caldararu, Octav; Ryde, Ulf

2017-09-07

Nitrogenase is the only enzyme that can break the triple bond in N 2 to form two molecules of ammonia. The enzyme has been thoroughly studied with both experimental and computational methods, but there is still no consensus regarding the atomic details of the reaction mechanism. In the most common form, the active site is a MoFe 7 S 9 C(homocitrate) cluster. The homocitrate ligand contains one alcohol and three carboxylate groups. In water solution, the triply deprotonated form dominates, but because the alcohol (and one of the carboxylate groups) coordinate to the Mo ion, this may change in the enzyme. We have performed a series of computational calculations with molecular dynamics (MD), quantum mechanical (QM) cluster, combined QM and molecular mechanics (QM/MM), QM/MM with Poisson-Boltzmann and surface area solvation, QM/MM thermodynamic cycle perturbations, and quantum refinement methods to settle the most probable protonation state of the homocitrate ligand in nitrogenase. The results quite conclusively point out a triply deprotonated form (net charge -3) with a proton shared between the alcohol and one of the carboxylate groups as the most stable at pH 7. Moreover, we have studied eight ionizable protein residues close to the active site with MD simulations and determined the most likely protonation states.

Computational and experimental analysis identified 6-diazo-5-oxonorleucine as a potential agent for treating infection by Plasmodium falciparum.

PubMed

Plaimas, Kitiporn; Wang, Yulin; Rotimi, Solomon O; Olasehinde, Grace; Fatumo, Segun; Lanzer, Michael; Adebiyi, Ezekiel; König, Rainer

2013-12-01

Plasmodium falciparum (PF) is the most severe malaria parasite. It is developing resistance quickly to existing drugs making it indispensable to discover new drugs. Effective drugs have been discovered targeting metabolic enzymes of the parasite. In order to predict new drug targets, computational methods can be used employing database information of metabolism. Using this data, we performed recently a computational network analysis of metabolism of PF. We analyzed the topology of the network to find reactions which are sensitive against perturbations, i.e., when a single enzyme is blocked by drugs. We now used a refined network comprising also the host enzymes which led to a refined set of the five targets glutamyl-tRNA (gln) amidotransferase, hydroxyethylthiazole kinase, deoxyribose-phophate aldolase, pseudouridylate synthase, and deoxyhypusine synthase. It was shown elsewhere that glutamyl-tRNA (gln) amidotransferase of other microorganisms can be inhibited by 6-diazo-5-oxonorleucine. Performing a half maximal inhibitory concentration (IC50) assay, we showed, that 6-diazo-5-oxonorleucine is also severely affecting viability of PF in blood plasma of the human host. We confirmed this by an in vivo study observing Plasmodium berghei infected mice. Copyright © 2013 Elsevier B.V. All rights reserved.

Recent advances in rational approaches for enzyme engineering

PubMed Central

Steiner, Kerstin; Schwab, Helmut

2012-01-01

Enzymes are an attractive alternative in the asymmetric syntheses of chiral building blocks. To meet the requirements of industrial biotechnology and to introduce new functionalities, the enzymes need to be optimized by protein engineering. This article specifically reviews rational approaches for enzyme engineering and de novo enzyme design involving structure-based approaches developed in recent years for improvement of the enzymes’ performance, broadened substrate range, and creation of novel functionalities to obtain products with high added value for industrial applications. PMID:24688651

Oxygen tolerance of an in silico-designed bioinspired hydrogen-evolving catalyst in water.

PubMed

Sit, Patrick H-L; Car, Roberto; Cohen, Morrel H; Selloni, Annabella

2013-02-05

Certain bacterial enzymes, the diiron hydrogenases, have turnover numbers for hydrogen production from water as large as 10(4)/s. Their much smaller common active site, composed of earth-abundant materials, has a structure that is an attractive starting point for the design of a practical catalyst for electrocatalytic or solar photocatalytic hydrogen production from water. In earlier work, our group has reported the computational design of [FeFe](P)/FeS(2), a hydrogenase-inspired catalyst/electrode complex, which is efficient and stable throughout the production cycle. However, the diiron hydrogenases are highly sensitive to ambient oxygen by a mechanism not yet understood in detail. An issue critical for practical use of [FeFe](P)/FeS(2) is whether this catalyst/electrode complex is tolerant to the ambient oxygen. We report demonstration by ab initio simulations that the complex is indeed tolerant to dissolved oxygen over timescales long enough for practical application, reducing it efficiently. This promising hydrogen-producing catalyst, composed of earth-abundant materials and with a diffusion-limited rate in acidified water, is efficient as well as oxygen tolerant.

Oxygen tolerance of an in silico-designed bioinspired hydrogen-evolving catalyst in water

PubMed Central

Sit, Patrick H.-L.; Car, Roberto; Cohen, Morrel H.; Selloni, Annabella

2013-01-01

Certain bacterial enzymes, the diiron hydrogenases, have turnover numbers for hydrogen production from water as large as 104/s. Their much smaller common active site, composed of earth-abundant materials, has a structure that is an attractive starting point for the design of a practical catalyst for electrocatalytic or solar photocatalytic hydrogen production from water. In earlier work, our group has reported the computational design of [FeFe]P/FeS2, a hydrogenase-inspired catalyst/electrode complex, which is efficient and stable throughout the production cycle. However, the diiron hydrogenases are highly sensitive to ambient oxygen by a mechanism not yet understood in detail. An issue critical for practical use of [FeFe]P/FeS2 is whether this catalyst/electrode complex is tolerant to the ambient oxygen. We report demonstration by ab initio simulations that the complex is indeed tolerant to dissolved oxygen over timescales long enough for practical application, reducing it efficiently. This promising hydrogen-producing catalyst, composed of earth-abundant materials and with a diffusion-limited rate in acidified water, is efficient as well as oxygen tolerant. PMID:23341607

Design and Testing of an Assessment Instrument to Measure Understanding of Protein Structure and Enzyme Inhibition in a New Context

ERIC Educational Resources Information Center

Villafañe, Sachel M.; Heyen, Bruce J.; Lewis, Jennifer E.; Loertscher, Jennifer; Minderhout, Vicky; Murray, Tracey Arnold

2016-01-01

Assessment instruments designed to measure student conceptual understanding and skills proficiency related to biochemistry are important to transform undergraduate biochemistry education. The purpose of this study was to develop an assessment instrument to measure student understanding of protein structure and enzyme inhibition in a new context,…

Folate biosynthesis pathway: mechanisms and insights into drug design for infectious diseases.

PubMed

Bertacine Dias, Marcio V; Santos, Jademilson C; Libreros-Zúñiga, Gerardo A; Ribeiro, João A; Chavez-Pacheco, Sair M

2018-04-01

Folate pathway is a key target for the development of new drugs against infectious diseases since the discovery of sulfa drugs and trimethoprim. The knowledge about this pathway has increased in the last years and the catalytic mechanism and structures of all enzymes of the pathway are fairly understood. In addition, differences among enzymes from prokaryotes and eukaryotes could be used for the design of specific inhibitors. In this review, we show a panorama of progress that has been achieved within the folate pathway obtained in the last years. We explored the structure and mechanism of enzymes, several genetic features, strategies, and approaches used in the design of new inhibitors that have been used as targets in pathogen chemotherapy.

Improvement on sugar cane bagasse hydrolysis using enzymatic mixture designed cocktail.

PubMed

Bussamra, Bianca Consorti; Freitas, Sindelia; Costa, Aline Carvalho da

2015-01-01

The aim of this work was to study cocktail supplementation for sugar cane bagasse hydrolysis, where the enzymes were provided from both commercial source and microorganism cultivation (Trichoderma reesei and genetically modified Escherichia coli), followed by purification. Experimental simplex lattice mixture design was performed to optimize the enzymatic proportion. The response was evaluated through hydrolysis microassays validated here. The optimized enzyme mixture, comprised of T. reesei fraction (80%), endoglucanase (10%) and β-glucosidase (10%), converted, theoretically, 72% of cellulose present in hydrothermally pretreated bagasse, whereas commercial Celluclast 1.5L converts 49.11%±0.49. Thus, a rational enzyme mixture designed by using synergism concept and statistical analysis was capable of improving biomass saccharification. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Self-Instructional Approach To the Teaching of Enzymology Involving Computer-Based Sequence Analysis and Molecular Modelling.

ERIC Educational Resources Information Center

Attwood, Paul V.

1997-01-01

Describes a self-instructional assignment approach to the teaching of advanced enzymology. Presents an assignment that offers a means of teaching enzymology to students that exposes them to modern computer-based techniques of analyzing protein structure and relates structure to enzyme function. (JRH)

Exercises in molecular computing.

PubMed

Stojanovic, Milan N; Stefanovic, Darko; Rudchenko, Sergei

2014-06-17

CONSPECTUS: The successes of electronic digital logic have transformed every aspect of human life over the last half-century. The word "computer" now signifies a ubiquitous electronic device, rather than a human occupation. Yet evidently humans, large assemblies of molecules, can compute, and it has been a thrilling challenge to develop smaller, simpler, synthetic assemblies of molecules that can do useful computation. When we say that molecules compute, what we usually mean is that such molecules respond to certain inputs, for example, the presence or absence of other molecules, in a precisely defined but potentially complex fashion. The simplest way for a chemist to think about computing molecules is as sensors that can integrate the presence or absence of multiple analytes into a change in a single reporting property. Here we review several forms of molecular computing developed in our laboratories. When we began our work, combinatorial approaches to using DNA for computing were used to search for solutions to constraint satisfaction problems. We chose to work instead on logic circuits, building bottom-up from units based on catalytic nucleic acids, focusing on DNA secondary structures in the design of individual circuit elements, and reserving the combinatorial opportunities of DNA for the representation of multiple signals propagating in a large circuit. Such circuit design directly corresponds to the intuition about sensors transforming the detection of analytes into reporting properties. While this approach was unusual at the time, it has been adopted since by other groups working on biomolecular computing with different nucleic acid chemistries. We created logic gates by modularly combining deoxyribozymes (DNA-based enzymes cleaving or combining other oligonucleotides), in the role of reporting elements, with stem-loops as input detection elements. For instance, a deoxyribozyme that normally exhibits an oligonucleotide substrate recognition region is modified such that a stem-loop closes onto the substrate recognition region, making it unavailable for the substrate and thus rendering the deoxyribozyme inactive. But a conformational change can then be induced by an input oligonucleotide, complementary to the loop, to open the stem, allow the substrate to bind, and allow its cleavage to proceed, which is eventually reported via fluorescence. In this Account, several designs of this form are reviewed, along with their application in the construction of large circuits that exhibited complex logical and temporal relationships between the inputs and the outputs. Intelligent (in the sense of being capable of nontrivial information processing) theranostic (therapy + diagnostic) applications have always been the ultimate motivation for developing computing (i.e., decision-making) circuits, and we review our experiments with logic-gate elements bound to cell surfaces that evaluate the proximal presence of multiple markers on lymphocytes.

Heterogeneous catalysis: Enigmas, illusions, challenges, realities, and emergent strategies of design

NASA Astrophysics Data System (ADS)

Thomas, John Meurig

2008-05-01

Predominantly this article deals with the question of how to design new solid catalysts for a variety of industrial and laboratory-orientated purposes. A generally applicable strategy, illustrated by numerous examples, is made possible based on the use of nanoporous materials on to the (high-area) inner surfaces of which well-defined (experimentally and computationally) active centers are placed in a spatially separated fashion. Such single-site catalysts, which have much in common with metal-centered homogenous catalysts and enzymes, enable a wide range of new catalysts to be designed for a variety of selective oxidations, hydrogenations, hydrations and hydrodewaxing, and other reactions that the "greening" of industrial processes demand. Examples are given of new shape-selective, regio-selective, and enantioselective catalysts, many of which operate under mild, environmentally benign conditions. Also considered are some of the reasons why detailed studies of adsorption and stoichiometric reactions at single-crystal surfaces have, disappointingly, not hitherto paved the way to the design and production of many new heterogenous catalysts. Recent work of a theoretical and high-throughout nature, allied to some experimental studies of well-chosen model systems, holds promise for the identification of new catalysts for simple, but industrially important reactions.

Novel concept of enzyme selective nicotinamide adenine dinucleotide (NAD)-modified inhibitors based on enzyme taxonomy from the diphosphate conformation of NAD.

PubMed

Fujii, Mikio; Kitagawa, Yasuyuki; Iida, Shui; Kato, Keisuke; Ono, Machiko

2015-11-15

The dihedral angle θ of the diphosphate part of NAD(P) were investigated to distinguish the differences in the binding-conformation of NAD(P) to enzymes and to create an enzyme taxonomy. Furthermore, new inhibitors with fixed dihedral angles showed that enzymes could recognize the differences in the dihedral angle θ. We suggest the taxonomy and the dihedral angle θ are important values for chemists to consider when designing inhibitors and drugs that target enzymes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Design Principles of DNA Enzyme-Based Walkers: Translocation Kinetics and Photoregulation.

PubMed

Cha, Tae-Gon; Pan, Jing; Chen, Haorong; Robinson, Heather N; Li, Xiang; Mao, Chengde; Choi, Jong Hyun

2015-07-29

Dynamic DNA enzyme-based walkers complete their stepwise movements along the prescribed track through a series of reactions, including hybridization, enzymatic cleavage, and strand displacement; however, their overall translocation kinetics is not well understood. Here, we perform mechanistic studies to elucidate several key parameters that govern the kinetics and processivity of DNA enzyme-based walkers. These parameters include DNA enzyme core type and structure, upper and lower recognition arm lengths, and divalent metal cation species and concentration. A theoretical model is developed within the framework of single-molecule kinetics to describe overall translocation kinetics as well as each reaction step. A better understanding of kinetics and design parameters enables us to demonstrate a walker movement near 5 μm at an average speed of ∼1 nm s(-1). We also show that the translocation kinetics of DNA walkers can be effectively controlled by external light stimuli using photoisomerizable azobenzene moieties. A 2-fold increase in the cleavage reaction is observed when the hairpin stems of enzyme catalytic cores are open under UV irradiation. This study provides general design guidelines to construct highly processive, autonomous DNA walker systems and to regulate their translocation kinetics, which would facilitate the development of functional DNA walkers.

Computational studies of novel chymase inhibitors against cardiovascular and allergic diseases: mechanism and inhibition.

PubMed

Arooj, Mahreen; Thangapandian, Sundarapandian; John, Shalini; Hwang, Swan; Park, Jong K; Lee, Keun W

2012-12-01

To provide a new idea for drug design, a computational investigation is performed on chymase and its novel 1,4-diazepane-2,5-diones inhibitors that explores the crucial molecular features contributing to binding specificity. Molecular docking studies of inhibitors within the active site of chymase were carried out to rationalize the inhibitory properties of these compounds and understand their inhibition mechanism. The density functional theory method was used to optimize molecular structures with the subsequent analysis of highest occupied molecular orbital, lowest unoccupied molecular orbital, and molecular electrostatic potential maps, which revealed that negative potentials near 1,4-diazepane-2,5-diones ring are essential for effective binding of inhibitors at active site of enzyme. The Bayesian model with receiver operating curve statistic of 0.82 also identified arylsulfonyl and aminocarbonyl as the molecular features favoring and not favoring inhibition of chymase, respectively. Moreover, genetic function approximation was applied to construct 3D quantitative structure-activity relationships models. Two models (genetic function approximation model 1 r(2) = 0.812 and genetic function approximation model 2 r(2) = 0.783) performed better in terms of correlation coefficients and cross-validation analysis. In general, this study is used as example to illustrate how combinational use of 2D/3D quantitative structure-activity relationships modeling techniques, molecular docking, frontier molecular orbital density fields (highest occupied molecular orbital and lowest unoccupied molecular orbital), and molecular electrostatic potential analysis may be useful to gain an insight into the binding mechanism between enzyme and its inhibitors. © 2012 John Wiley & Sons A/S.

Old drug new use--amoxapine and its metabolites as potent bacterial β-glucuronidase inhibitors for alleviating cancer drug toxicity.

PubMed

Kong, Ren; Liu, Timothy; Zhu, Xiaoping; Ahmad, Syed; Williams, Alfred L; Phan, Alexandria T; Zhao, Hong; Scott, John E; Yeh, Li-An; Wong, Stephen T C

2014-07-01

Irinotecan (CPT-11) induced diarrhea occurs frequently in patients with cancer and limits its usage. Bacteria β-glucuronidase (GUS) enzymes in intestines convert the nontoxic metabolite of CPT-11, SN-38G, to toxic SN-38, and finally lead to damage of intestinal epithelial cells and diarrhea. We previously reported amoxapine as a potent GUS inhibitor in vitro. To further understand the molecular mechanism of amoxapine and its potential for treatment of CPT-11-induced diarrhea, we studied the binding modes of amoxapine and its metabolites by docking and molecular dynamics simulation, and tested the in vivo efficacy on mice in combination with CPT-11. The binding of amoxapine, its metabolites, 7-hydroxyamoxapine and 8-hydroxyamoxapine, and a control drug loxapine with GUS was explored by computational protocols. The in vitro potencies of metabolites were measured by Escherichia coli GUS enzyme and cell-based assay. Low-dosage daily oral administration was designed to use along with CPT-11 to treat tumor-bearing mice. Computational modeling results indicated that amoxapine and its metabolites bound in the active site of GUS and satisfied critical pharmacophore features: aromatic features near bacterial loop residue F365' and hydrogen bond toward E413. Amoxapine and its metabolites were demonstrated as potent in vitro. Administration of low dosages of amoxapine with CPT-11 in mice achieved significant suppression of diarrhea and reduced tumor growth. Amoxapine has great clinical potential to be rapidly translated to human subjects for irinotecan-induced diarrhea. ©2014 American Association for Cancer Research.

Production optimization of invertase by Lactobacillus brevis Mm-6 and its immobilization on alginate beads.

PubMed

Awad, Ghada E A; Amer, Hassan; El-Gammal, Eman W; Helmy, Wafaa A; Esawy, Mona A; Elnashar, Magdy M M

2013-04-02

A sequential optimization strategy, based on statistical experimental designs, was employed to enhance the production of invertase by Lactobacillus brevis Mm-6 isolated from breast milk. First, a 2-level Plackett-Burman design was applied to screen the bioprocess parameters that significantly influence the invertase production. The second optimization step was performed using fractional factorial design in order to optimize the amounts of variables have the highest positive significant effect on the invertase production. A maximal enzyme activity of 1399U/ml was more than five folds the activity obtained using the basal medium. Invertase was immobilized onto grafted alginate beads to improve the enzyme's stability. Immobilization process increased the operational temperature from 30 to 60°C compared to the free enzyme. The reusability test proved the durability of the grafted alginate beads for 15 cycles with retention of 100% of the immobilized enzyme activity to be more convenient for industrial uses. Copyright © 2013 Elsevier Ltd. All rights reserved.

Molecular modelling and quantum biochemistry computations of a naturally occurring bioremediation enzyme: Alkane hydroxylase from Pseudomonas putida P1.

PubMed

de Sousa, B G; Oliveira, J I N; Albuquerque, E L; Fulco, U L; Amaro, V E; Blaha, C A G

2017-10-01

Many species of bacteria involved in degradation of n-alkanes have an important constitutional metabolic enzyme, the alkane hydroxylase called AlkB, specialized in the conversion of hydrocarbons molecules that can be used as carbon and/or energy source. This enzyme plays an important role in the microbial degradation of oil, chlorinated hydrocarbons, fuel additives, and many other compounds. A number of these enzymes has been biochemically characterized in detail because the potential of alkane hydroxylases to catalyse high added-value reactions is widely recognized. Nevertheless, the industrial and process bioremediation application of them is restricted, owing to their complex biochemistry, challenging process requirements, and the limited number of their three-dimensional structures. Furthermore, AlkB has great potential as biocatalysts for selective transformation of a wide range of chemically inert unreactive alkanes into reactive chemical precursors that can be used as tools for bioremediation and bioprocesses. Aiming to understand the possible ways the AlkB enzyme Pseudomonas putida P1 interacts with octane, octanol and 1-octyne, we consider its suitable biochemical structure taking into account a 3-D homology modelling. Besides, by using a quantum chemistry computational model based on the density functional theory (DFT), we determine possible protein-substrate interaction regions measured by means of its binding energy simulated throughout the Molecular Fractionation with Conjugated Caps (MFCC) approach. Copyright © 2017 Elsevier Inc. All rights reserved.

Enzyme catalysis by entropy without Circe effect.

PubMed

Kazemi, Masoud; Himo, Fahmi; Åqvist, Johan

2016-03-01

Entropic effects have often been invoked to explain the extraordinary catalytic power of enzymes. In particular, the hypothesis that enzymes can use part of the substrate-binding free energy to reduce the entropic penalty associated with the subsequent chemical transformation has been very influential. The enzymatic reaction of cytidine deaminase appears to be a distinct example. Here, substrate binding is associated with a significant entropy loss that closely matches the activation entropy penalty for the uncatalyzed reaction in water, whereas the activation entropy for the rate-limiting catalytic step in the enzyme is close to zero. Herein, we report extensive computer simulations of the cytidine deaminase reaction and its temperature dependence. The energetics of the catalytic reaction is first evaluated by density functional theory calculations. These results are then used to parametrize an empirical valence bond description of the reaction, which allows efficient sampling by molecular dynamics simulations and computation of Arrhenius plots. The thermodynamic activation parameters calculated by this approach are in excellent agreement with experimental data and indeed show an activation entropy close to zero for the rate-limiting transition state. However, the origin of this effect is a change of reaction mechanism compared the uncatalyzed reaction. The enzyme operates by hydroxide ion attack, which is intrinsically associated with a favorable activation entropy. Hence, this has little to do with utilization of binding free energy to pay the entropic penalty but rather reflects how a preorganized active site can stabilize a reaction path that is not operational in solution.

Enzyme catalysis by entropy without Circe effect

PubMed Central

Kazemi, Masoud; Himo, Fahmi; Åqvist, Johan

2016-01-01

Entropic effects have often been invoked to explain the extraordinary catalytic power of enzymes. In particular, the hypothesis that enzymes can use part of the substrate-binding free energy to reduce the entropic penalty associated with the subsequent chemical transformation has been very influential. The enzymatic reaction of cytidine deaminase appears to be a distinct example. Here, substrate binding is associated with a significant entropy loss that closely matches the activation entropy penalty for the uncatalyzed reaction in water, whereas the activation entropy for the rate-limiting catalytic step in the enzyme is close to zero. Herein, we report extensive computer simulations of the cytidine deaminase reaction and its temperature dependence. The energetics of the catalytic reaction is first evaluated by density functional theory calculations. These results are then used to parametrize an empirical valence bond description of the reaction, which allows efficient sampling by molecular dynamics simulations and computation of Arrhenius plots. The thermodynamic activation parameters calculated by this approach are in excellent agreement with experimental data and indeed show an activation entropy close to zero for the rate-limiting transition state. However, the origin of this effect is a change of reaction mechanism compared the uncatalyzed reaction. The enzyme operates by hydroxide ion attack, which is intrinsically associated with a favorable activation entropy. Hence, this has little to do with utilization of binding free energy to pay the entropic penalty but rather reflects how a preorganized active site can stabilize a reaction path that is not operational in solution. PMID:26755610

Sortase Transpeptidases: Structural Biology and Catalytic Mechanism

PubMed Central

Jacobitz, Alex W.; Kattke, Michele D.; Wereszczynski, Jeff; Clubb, Robert T.

2017-01-01

Gram-positive bacteria use sortase cysteine transpeptidase enzymes to covalently attach proteins to their cell wall and to assemble pili. In pathogenic bacteria sortases are potential drug targets, as many of the proteins that they display on the microbial surface play key roles in the infection process. Moreover, the Staphylococcus aureus Sortase A (SaSrtA) enzyme has been developed into a valuable biochemical reagent because of its ability to ligate biomolecules together in vitro via a covalent peptide bond. Here we review what is known about the structures and catalytic mechanism of sortase enzymes. Based on their primary sequences, most sortase homologs can be classified into six distinct subfamilies, called class A–F enzymes. Atomic structures reveal unique, class-specific variations that support alternate substrate specificities, while structures of sortase enzymes bound to sorting signal mimics shed light onto the molecular basis of substrate recognition. The results of computational studies are reviewed that provide insight into how key reaction intermediates are stabilized during catalysis, as well as the mechanism and dynamics of substrate recognition. Lastly, the reported in vitro activities of sortases are compared, revealing that the transpeptidation activity of SaSrtA is at least 20-fold faster than other sortases that have thus far been characterized. Together, the results of the structural, computational, and biochemical studies discussed in this review begin to reveal how sortases decorate the microbial surface with proteins and pili, and may facilitate ongoing efforts to discover therapeutically useful small molecule inhibitors. PMID:28683919

Fluorescence and computational studies of thymidine phosphorylase affinity toward lipidated 5-FU derivatives

NASA Astrophysics Data System (ADS)

Lettieri, R.; D'Abramo, M.; Stella, L.; La Bella, A.; Leonelli, F.; Giansanti, L.; Venanzi, M.; Gatto, E.

2018-04-01

Thymidine phosphorylase (TP) is an enzyme that is up-regulated in a wide variety of solid tumors, including breast and colorectal cancers. It is involved in tumor growth and metastasis, for this reason it is one of the key enzyme to be inhibited, in an attempt to prevent tumor proliferation. However, it also plays an active role in cancer treatment, through its contribution in the conversion of the anti-cancer drug 5-fluorouracil (5-FU) to an irreversible inhibitor of thymidylate synthase (TS), responsible of the inhibition of the DNA synthesis. In this work, the intrinsic TP fluorescence has been investigated for the first time and exploited to study TP binding affinity for the unsubstituted 5-FU and for two 5-FU derivatives, designed to expose this molecule on liposomal membranes. These molecules were obtained by functionalizing the nitrogen atom with a chain consisting of six (1) or seven (2) units of glycol, linked to an alkyl moiety of 12 carbon atoms. Derivatives (1) and (2) exhibited an affinity for TP in the micromolar range, 10 times higher than the parent compound, irrespective of the length of the polyoxyethylenic spacer. This high affinity was maintained also when the compounds were anchored in liposomal membranes. Experimental results were supported by molecular dynamics simulations and docking calculations, supporting a feasible application of the designed supramolecular lipid structure in selective targeting of TP, to be potentially used as a drug delivery system or sensor device.

Construction and in vivo assembly of a catalytically proficient and hyperthermostable de novo enzyme.

PubMed

Watkins, Daniel W; Jenkins, Jonathan M X; Grayson, Katie J; Wood, Nicola; Steventon, Jack W; Le Vay, Kristian K; Goodwin, Matthew I; Mullen, Anna S; Bailey, Henry J; Crump, Matthew P; MacMillan, Fraser; Mulholland, Adrian J; Cameron, Gus; Sessions, Richard B; Mann, Stephen; Anderson, J L Ross

2017-08-25

Although catalytic mechanisms in natural enzymes are well understood, achieving the diverse palette of reaction chemistries in re-engineered native proteins has proved challenging. Wholesale modification of natural enzymes is potentially compromised by their intrinsic complexity, which often obscures the underlying principles governing biocatalytic efficiency. The maquette approach can circumvent this complexity by combining a robust de novo designed chassis with a design process that avoids atomistic mimicry of natural proteins. Here, we apply this method to the construction of a highly efficient, promiscuous, and thermostable artificial enzyme that catalyzes a diverse array of substrate oxidations coupled to the reduction of H 2 O 2 . The maquette exhibits kinetics that match and even surpass those of certain natural peroxidases, retains its activity at elevated temperature and in the presence of organic solvents, and provides a simple platform for interrogating catalytic intermediates common to natural heme-containing enzymes.Catalytic mechanisms of enzymes are well understood, but achieving diverse reaction chemistries in re-engineered proteins can be difficult. Here the authors show a highly efficient and thermostable artificial enzyme that catalyzes a diverse array of substrate oxidations coupled to the reduction of H 2 O 2 .

Synthetic metabolism: metabolic engineering meets enzyme design.

PubMed

Erb, Tobias J; Jones, Patrik R; Bar-Even, Arren

2017-04-01

Metabolic engineering aims at modifying the endogenous metabolic network of an organism to harness it for a useful biotechnological task, for example, production of a value-added compound. Several levels of metabolic engineering can be defined and are the topic of this review. Basic 'copy, paste and fine-tuning' approaches are limited to the structure of naturally existing pathways. 'Mix and match' approaches freely recombine the repertoire of existing enzymes to create synthetic metabolic networks that are able to outcompete naturally evolved pathways or redirect flux toward non-natural products. The space of possible metabolic solution can be further increased through approaches including 'new enzyme reactions', which are engineered on the basis of known enzyme mechanisms. Finally, by considering completely 'novel enzyme chemistries' with de novo enzyme design, the limits of nature can be breached to derive the most advanced form of synthetic pathways. We discuss the challenges and promises associated with these different metabolic engineering approaches and illuminate how enzyme engineering is expected to take a prime role in synthetic metabolic engineering for biotechnology, chemical industry and agriculture of the future. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Adapting capillary gel electrophoresis as a sensitive, high-throughput method to accelerate characterization of nucleic acid metabolic enzymes

PubMed Central

Greenough, Lucia; Schermerhorn, Kelly M.; Mazzola, Laurie; Bybee, Joanna; Rivizzigno, Danielle; Cantin, Elizabeth; Slatko, Barton E.; Gardner, Andrew F.

2016-01-01

Detailed biochemical characterization of nucleic acid enzymes is fundamental to understanding nucleic acid metabolism, genome replication and repair. We report the development of a rapid, high-throughput fluorescence capillary gel electrophoresis method as an alternative to traditional polyacrylamide gel electrophoresis to characterize nucleic acid metabolic enzymes. The principles of assay design described here can be applied to nearly any enzyme system that acts on a fluorescently labeled oligonucleotide substrate. Herein, we describe several assays using this core capillary gel electrophoresis methodology to accelerate study of nucleic acid enzymes. First, assays were designed to examine DNA polymerase activities including nucleotide incorporation kinetics, strand displacement synthesis and 3′-5′ exonuclease activity. Next, DNA repair activities of DNA ligase, flap endonuclease and RNase H2 were monitored. In addition, a multicolor assay that uses four different fluorescently labeled substrates in a single reaction was implemented to characterize GAN nuclease specificity. Finally, a dual-color fluorescence assay to monitor coupled enzyme reactions during Okazaki fragment maturation is described. These assays serve as a template to guide further technical development for enzyme characterization or nucleoside and non-nucleoside inhibitor screening in a high-throughput manner. PMID:26365239

KAS IV: a 3-ketoacyl-ACP synthase from Cuphea sp. is a medium chain specific condensing enzyme.

PubMed

Dehesh, K; Edwards, P; Fillatti, J; Slabaugh, M; Byrne, J

1998-08-01

cDNA clones encoding a novel 3-ketoacyl-ACP synthase (KAS) have been isolated from Cuphea. The amino acid sequence of this enzyme is different from the previously characterized classes of KASs, designated KAS I and III, and similar to those designated as KAS II. To define the acyl chain specificity of this enzyme, we generated transgenic Brassica plants over-expressing the cDNA encoded protein in a seed specific manner. Expression of this enzyme in transgenic Brassica seeds which normally do not produce medium chain fatty acids does not result in any detectable modification of the fatty acid profile. However, co-expression of the Cuphea KAS with medium chain specific thioesterases, capable of production of either 12:0 or 8:0/10:0 fatty acids in seed oil, strongly enhances the levels of these medium chain fatty acids as compared with seed oil of plants expressing the thioesterases alone. By contrast, co-expression of the Cuphea KAS along with an 18:0/18.1-ACP thioesterase does not result in any detectable modification of the fatty acids. These data indicate that the Cuphea KAS reported here has a different acyl-chain specificity to the previously characterized KAS I, II and III. Therefore, we designate this enzyme KAS IV, a medium chain specific condensing enzyme.

Stable metal-organic frameworks containing single-molecule traps for enzyme encapsulation.

PubMed

Feng, Dawei; Liu, Tian-Fu; Su, Jie; Bosch, Mathieu; Wei, Zhangwen; Wan, Wei; Yuan, Daqiang; Chen, Ying-Pin; Wang, Xuan; Wang, Kecheng; Lian, Xizhen; Gu, Zhi-Yuan; Park, Jihye; Zou, Xiaodong; Zhou, Hong-Cai

2015-01-19

Enzymatic catalytic processes possess great potential in chemical manufacturing, including pharmaceuticals, fuel production and food processing. However, the engineering of enzymes is severely hampered due to their low operational stability and difficulty of reuse. Here, we develop a series of stable metal-organic frameworks with rationally designed ultra-large mesoporous cages as single-molecule traps (SMTs) for enzyme encapsulation. With a high concentration of mesoporous cages as SMTs, PCN-333(Al) encapsulates three enzymes with record-high loadings and recyclability. Immobilized enzymes that most likely undergo single-enzyme encapsulation (SEE) show smaller Km than free enzymes while maintaining comparable catalytic efficiency. Under harsh conditions, the enzyme in SEE exhibits better performance than free enzyme, showing the effectiveness of SEE in preventing enzyme aggregation or denaturation. With extraordinarily large pore size and excellent chemical stability, PCN-333 may be of interest not only for enzyme encapsulation, but also for entrapment of other nanoscaled functional moieties.

Stable metal-organic frameworks containing single-molecule traps for enzyme encapsulation

NASA Astrophysics Data System (ADS)

Feng, Dawei; Liu, Tian-Fu; Su, Jie; Bosch, Mathieu; Wei, Zhangwen; Wan, Wei; Yuan, Daqiang; Chen, Ying-Pin; Wang, Xuan; Wang, Kecheng; Lian, Xizhen; Gu, Zhi-Yuan; Park, Jihye; Zou, Xiaodong; Zhou, Hong-Cai

2015-01-01

Enzymatic catalytic processes possess great potential in chemical manufacturing, including pharmaceuticals, fuel production and food processing. However, the engineering of enzymes is severely hampered due to their low operational stability and difficulty of reuse. Here, we develop a series of stable metal-organic frameworks with rationally designed ultra-large mesoporous cages as single-molecule traps (SMTs) for enzyme encapsulation. With a high concentration of mesoporous cages as SMTs, PCN-333(Al) encapsulates three enzymes with record-high loadings and recyclability. Immobilized enzymes that most likely undergo single-enzyme encapsulation (SEE) show smaller Km than free enzymes while maintaining comparable catalytic efficiency. Under harsh conditions, the enzyme in SEE exhibits better performance than free enzyme, showing the effectiveness of SEE in preventing enzyme aggregation or denaturation. With extraordinarily large pore size and excellent chemical stability, PCN-333 may be of interest not only for enzyme encapsulation, but also for entrapment of other nanoscaled functional moieties.

On the Convenience of Using a Computer Simulation to Teach Enzyme Kinetics to Undergraduate Students with Biological Chemistry-Related Curricula

ERIC Educational Resources Information Center

Gonzalez-Cruz, Javier; Rodriguez-Sotres, Rogelio; Rodriguez-Penagos, Mireya

2003-01-01

Enzyme kinetics is a difficult subject for students to learn and for tutors to teach. During the practicals included in the biochemical courses at the Faculty of Chemistry of Universidad Nacional Autonoma de Mexico, we found that the students acquire good training in the calculations to obtain kinetic parameters such as K[subscript m], V[subscript…

Three-dimensional quantitative structure-activity relationship analysis for human pregnane X receptor for the prediction of CYP3A4 induction in human hepatocytes: structure-based comparative molecular field analysis.

PubMed

Handa, Koichi; Nakagome, Izumi; Yamaotsu, Noriyuki; Gouda, Hiroaki; Hirono, Shuichi

2015-01-01

The pregnane X receptor [PXR (NR1I2)] induces the expression of xenobiotic metabolic genes and transporter genes. In this study, we aimed to establish a computational method for quantifying the enzyme-inducing potencies of different compounds via their ability to activate PXR, for the application in drug discovery and development. To achieve this purpose, we developed a three-dimensional quantitative structure-activity relationship (3D-QSAR) model using comparative molecular field analysis (CoMFA) for predicting enzyme-inducing potencies, based on computer-ligand docking to multiple PXR protein structures sampled from the trajectory of a molecular dynamics simulation. Molecular mechanics-generalized born/surface area scores representing the ligand-protein-binding free energies were calculated for each ligand. As a result, the predicted enzyme-inducing potencies for compounds generated by the CoMFA model were in good agreement with the experimental values. Finally, we concluded that this 3D-QSAR model has the potential to predict the enzyme-inducing potencies of novel compounds with high precision and therefore has valuable applications in the early stages of the drug discovery process. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

Potent Inhibitors of the Hepatitis C Virus NS3 Protease: Design and Synthesis of Macrocyclic Substrate-Based [beta]-Strand Mimics

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

Goudreau, Nathalie; Brochu, Christian; Cameron, Dale R.

2008-06-30

The virally encoded NS3 protease is essential to the life cycle of the hepatitis C virus (HCV), an important human pathogen causing chronic hepatitis, cirrhosis of the liver, and hepatocellular carcinoma. The design and synthesis of 15-membered ring {beta}-strand mimics which are capable of inhibiting the interactions between the HCV NS3 protease enzyme and its polyprotein substrate will be described. The binding interactions between a macrocyclic ligand and the enzyme were explored by NMR and molecular dynamics, and a model of the ligand/enzyme complex was developed.

Glutamyl-gamma-boronate inhibitors of bacterial Glu-tRNA(Gln) amidotransferase.

PubMed

Decicco, C P; Nelson, D J; Luo, Y; Shen, L; Horiuchi, K Y; Amsler, K M; Foster, L A; Spitz, S M; Merrill, J J; Sizemore, C F; Rogers, K C; Copeland, R A; Harpel, M R

2001-09-17

Analogues of glutamyl-gamma-boronate (1) were synthesized as mechanism-based inhibitors of bacterial Glu-tRNA(Gln) amidotransferase (Glu-AdT) and were designed to engage a putative catalytic serine nucleophile required for the glutaminase activity of the enzyme. Although 1 provides potent enzyme inhibition, structure-activity studies revealed a narrow range of tolerated chemical changes that maintained activity. Nonetheless, growth inhibition of organisms that require Glu-AdT by the most potent enzyme inhibitors appears to validate mechanism-based inhibitor design of Glu-AdT as an approach to antimicrobial development.

Computational screening of disease-associated mutations in OCA2 gene.

PubMed

Kamaraj, Balu; Purohit, Rituraj

2014-01-01

Oculocutaneous albinism type 2 (OCA2), caused by mutations of OCA2 gene, is an autosomal recessive disorder characterized by reduced biosynthesis of melanin pigment in the skin, hair, and eyes. The OCA2 gene encodes instructions for making a protein called the P protein. This protein plays a crucial role in melanosome biogenesis, and controls the eumelanin content in melanocytes in part via the processing and trafficking of tyrosinase which is the rate-limiting enzyme in melanin synthesis. In this study we analyzed the pathogenic effect of 95 non-synonymous single nucleotide polymorphisms reported in OCA2 gene using computational methods. We found R305W mutation as most deleterious and disease associated using SIFT, PolyPhen, PANTHER, PhD-SNP, Pmut, and MutPred tools. To understand the atomic arrangement in 3D space, the native and mutant (R305W) structures were modeled. Molecular dynamics simulation was conducted to observe the structural significance of computationally prioritized disease-associated mutation (R305W). Root-mean-square deviation, root-mean-square fluctuation, radius of gyration, solvent accessibility surface area, hydrogen bond (NH bond), trace of covariance matrix, eigenvector projection analysis, and density analysis results showed prominent loss of stability and rise in mutant flexibility values in 3D space. This study presents a well designed computational methodology to examine the albinism-associated SNPs.

Virtual Screening on MMP-13 Led to Discovering New Inhibitors Including a Non-Zinc Binding and a Micro Molar One: A Successful Example of Receptor Selection According to Cross-Docking Results for a Flexible Enzyme.

PubMed

Ramezani, Mohammad; Shamsara, Jamal

2017-01-01

MMP-13 belongs to a large family of proteases called matrix metalloproteinases (MMPs) that degrades type II collagen, the main structural protein of articular cartilage. The main pathologic role of MMP-13 over expression is to contribute to the development of osteoarthritis. To find new inhibitors with possible selectivity for MMP-13 a structure based virtual screening was employed. The inhibitory activities of 11 inhibitors among 19 purchased compounds were approved by enzyme inhibition assay. Our results demonstrated that the CADD (computer aided drug design) could be successfully applied to find new MMP-13 inhibitors using a receptor structure (PDB code: 3O2X) which had been demonstrated a good performance in a cross-docking study. We discovered inhibitors with new scaffolds for inhibition of MMP-13 and some selectivity features such as proper S1' occupancy and interactions with S1' pocket that could be subjected to a future lead optimization study. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Virtual Screening for the Development of Dual-Inhibitors Targeting Topoisomerase IB and Tyrosyl-DNA Phosphodiesterase 1.

PubMed

Cardamone, Francesca; Pizzi, Simone; Iacovelli, Federico; Falconi, Mattia; Desideri, Alessandro

2017-01-01

Human topoisomerase IB is an important target in cancer therapy and drugs selectively stabilizing the topoisomerase IB-DNA covalent complex are in clinical use for several cancer types. Tyrosyl- DNA phosphodiesterase 1 is involved in the DNA repair resolving the topoisomerase IB-DNA covalent complex that is extremely dangerous for the survival of the cells since it produces an irreversible DNA damage. Given the close biological relationship between these two enzymes, the development of synergistic inhibitors, called dual-inhibitors, is an important challenge in cancer therapy and computer-aided drug design may help in the identification of the best compounds. In this review, an overview of the compounds inhibiting one of the two enzymes or acting as dual inhibitors is provided. Moreover, the general procedures of the virtual screening approach, providing a description of two widely used opensource programs, namely AutoDock4 and AutoDock Vina, are described. Finally, an application of the two programs on a selected number of dual inhibitors for tyrosyl-DNA phosphodiesterase 1 and topoisomerase IB and their performance is briefly discussed. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Papain hydrolysis of X-phenyl-N-methanesulfonyl glycinates: a quantitative structure-activity relationship and molecular graphics analysis.

PubMed

Carotti, A; Smith, R N; Wong, S; Hansch, C; Blaney, J M; Langridge, R

1984-02-15

The hydrolysis of 32 X-phenyl-N-methanesulfonyl glycinates by papain was investigated. It was found that the variation in the Michaelis constants could be rationalized by the following correlation equation: log 1/Km = 0.61 pi '3 + 0.46 MR4 + 0.55 sigma + 2.00 with a correlation coefficient of 0.945. In this expression, pi '3 is the hydrophobic constant for the more lipophilic of the two possible meta substituents, MR4 is the molar refractivity of 4-substituents, and sigma is the Hammett constant summed for all substituents. Using this equation, we designed, synthesized, and successfully predicted Km for a new congener intended to maximize binding (1/Km). The interactions involved in enzyme-substrate binding, as characterized by the correlation equation, are interpreted using a computer-constructed color three-dimensional-graphics molecular model of the enzyme active site. The nonenzymatic hydrolysis (both acid and basic) of phenyl hippurates yield rate constants which are well correlated by Hammett equations; however, log k for both acid and alkaline hydrolysis are not linearly related to log 1/Km or log kcat/Km.

Mathematical modeling of physiological systems: an essential tool for discovery.

PubMed

Glynn, Patric; Unudurthi, Sathya D; Hund, Thomas J

2014-08-28

Mathematical models are invaluable tools for understanding the relationships between components of a complex system. In the biological context, mathematical models help us understand the complex web of interrelations between various components (DNA, proteins, enzymes, signaling molecules etc.) in a biological system, gain better understanding of the system as a whole, and in turn predict its behavior in an altered state (e.g. disease). Mathematical modeling has enhanced our understanding of multiple complex biological processes like enzyme kinetics, metabolic networks, signal transduction pathways, gene regulatory networks, and electrophysiology. With recent advances in high throughput data generation methods, computational techniques and mathematical modeling have become even more central to the study of biological systems. In this review, we provide a brief history and highlight some of the important applications of modeling in biological systems with an emphasis on the study of excitable cells. We conclude with a discussion about opportunities and challenges for mathematical modeling going forward. In a larger sense, the review is designed to help answer a simple but important question that theoreticians frequently face from interested but skeptical colleagues on the experimental side: "What is the value of a model?" Copyright © 2014 Elsevier Inc. All rights reserved.

The effectiveness of dietary sunflower meal and exogenous enzyme on growth, digestive enzymes, carcass traits, and blood chemistry of broilers.

PubMed

Alagawany, Mahmoud; Attia, Adel I; Ibrahim, Zenat A; Mahmoud, Reda A; El-Sayed, Sabry A

2017-05-01

High costs of conventional protein feed sources including soybean meal (SBM) generated the need for finding other alternatives. Thus, the present study was designed to evaluate the impact of graded replacements of SBM by sunflower seed meal (SFM) with or without enzyme supplementation on growth performance, digestive enzymes, carcass traits, and blood profile of broiler chickens. A total of 240 unsexed 1-week-old broiler chicks (Hubbard) were randomly divided into eight treatment groups of 30 chicks each in five replicates each of six chicks in a factorial design (4 × 2) arrangement, including four levels of SFM (0, 25, 50, and 75% replacing SBM) and two levels of enzyme (0- or 0.1-g/kg diet) supplementation. Performance traits including feed conversion ratio, body weight, and weight gain were significantly (P < 0.01) improved with increasing SFM up to 50% substitution for SBM or with enzyme supplementation in broiler diet during the experiment. However, feed intake of broiler chicks was decreased with enzyme supplementation (P < 0.05). The activities of digestive enzymes (protease and amylase) were significantly (P < 0.05) influenced and enhanced by SFM and enzyme inclusion in diets, respectively. The activities of protease and amylase were improved with SFM diet supplemented with 0.1 g/kg enzyme in comparison with those with the un-supplemented diet. The evaluated carcass traits were not statistically (P > 0.05) influenced by feeding SFM meal or enzyme addition. Biochemical blood parameters were significantly (P < 0.01) affected by SFM, enzyme, or their interaction in broiler diets, except for globulin that was not affected by dietary enzyme. It is concluded that increasing SFM level in the diet up to 50% replacing SBM with the supplementation of enzyme improved the growth performance and enhanced positively carcass traits as well as the activity of digestive enzymes in broiler chickens.

Affinity comparison of different THCA synthase to CBGA using modeling computational approaches.

PubMed

Alaoui, Moulay Abdelaziz El; Ibrahimi, Azeddine; Semlali, Oussama; Tarhda, Zineb; Marouane, Melloul; Najwa, Alaoui; Soulaymani, Abdelmajid; Fahime, Elmostafa El

2014-01-01

The Δ(9-)Tetrahydrocannabinol (THCA) is the primary psychoactive compound of Cannabis Sativa. It is produced by Δ(1-) Tetrahydrocannabinolic acid synthase (THCA) which catalyzes the oxidative cyclization of cannabigerolic acid (CBGA) the precursor of the THCA. In this study, we were interested by the three dimensional structure of THCA synthase protein. Generation of models were done by MODELLER v9.11 and homology modeling with Δ1-tetrahydrocannabinolic acid (THCA) synthase X ray structure (PDB code 3VTE) on the basis of sequences retrieved from GenBank. Procheck, Errat, and Verify 3D tools were used to verify the reliability of the six 3D models obtained, the overall quality factor and the Prosa Z-score were also used to check the quality of the six modeled proteins. The RMSDs for C-alpha atoms, main-chain atoms, side-chain atoms and all atoms between the modeled structures and the corresponding template ranged between 0.290 Å-1.252 Å, reflecting the good quality of the obtained models. Our study of the CBGA-THCA synthase docking demonstrated that the active site pocket was successfully recognized using computational approach. The interaction energy of CBGA computed in 'fiber types' proteins ranged between -4.1 95 kcal/mol and -5.95 kcal/mol whereas in the 'drug type' was about -7.02 kcal/mol to -7.16 kcal/mol, which maybe indicate the important role played by the interaction energy of CBGA in the determination of the THCA level in Cannabis Sativa L. varieties. Finally, we have proposed an experimental design in order to explore the binding energy source of ligand-enzyme in Cannabis Sativa and the production level of the THCA in the absence of any information regarding the correlation between the enzyme affinity and THCA level production. This report opens the doors to more studies predicting the binding site pocket with accuracy from the perspective of the protein affinity and THCA level produced in Cannabis Sativa.

Therapeutic Enzymes: Applications and Approaches to Pharmacological Improvement.

PubMed

Yari, Maryam; Ghoshoon, Mohammad B; Vakili, Bahareh; Ghasemi, Younes

2017-01-01

Among therapeutic proteins, enzymes represent small and of course profitable market. They can be used to treat important, rare, and deadly diseases. Enzyme therapy is the only available treatment for certain disorders. Here, pharmaceutical enzymes are reviewed. They are categorized in four main groups, enzymes in replacement therapy, enzymes in cancer treatment, enzymes for fibrinolysis, and finally enzymes that are used topically for various treatments. Furthermore, enzyme gene therapy and future perspective of therapeutic enzymes are mentioned in brief. There are many important approved enzymes in pharmaceutical market. Several approaches such as point mutation, fusion protein designing, glycoengineering, and PEGylation were used to achieve improved enzymes. Although sometimes enzymes were engineered to facilitate production and purification process, appropriate delivery to target sites, extending half-life, and reducing immunogenicity are among the main goals of engineering approaches. Overall, enzymes play a critical role in treatment of common and rare diseases. Evaluation of new enzymes as well as improvement of approved enzymes are of the most important challenges in biotechnology. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Making the Rate: Enzyme Dynamics

ERIC Educational Resources Information Center

Ragsdale, Frances R.

2004-01-01

An enzyme exercise to address the problem of students inability to visualize chemical reaction at the molecular level is described. This exercise is designed as a dry lab exercise but can be modified into a classroom activity then can be augmented by a wet lab procedure, thereby providing students with a practical exposure to enzyme function.

Microgravity

NASA Image and Video Library

2004-04-15

The reproduction process of all strains of influenza are dependent on the same enzyme neuraminidase. Pharmaceutical companies have been developing drugs that can inhibit the function of neuraminidase hoping to create an effective weapon against the flu. Researchers from the pharmaceutical industry and from the Center for Macromolecular Crystallography have grown crystals of neuraminidase in space. These improved, space-grown crystals have provided information that have helped design drugs which form a stronger interaction with the enzyme. These drugs inhibit neuraminidase by attaching themselves to the enzyme. Since the drugs are less likely to detach from the enzyme, they are more effective, require smaller dosages, and have fewer side effects. Shown here is a segmented representation of the neuraminidase inhibitor compound sitting inside a cave-like contour of the neuraminidase enzyme surface. This cave-like formation present in every neuraminidase enzyme is the active site crucial to the flu's ability to infect. The space-grown crystals of neuraminidase have provided significant new details about the three-dimensional characteristics of this active site thus allowing researchers to design drugs that fit tighter into the site. Principal Investigator: Dr. Larry DeLucas

Neuraminidase

NASA Technical Reports Server (NTRS)

2004-01-01

The reproduction process of all strains of influenza are dependent on the same enzyme neuraminidase. Pharmaceutical companies have been developing drugs that can inhibit the function of neuraminidase hoping to create an effective weapon against the flu. Researchers from the pharmaceutical industry and from the Center for Macromolecular Crystallography have grown crystals of neuraminidase in space. These improved, space-grown crystals have provided information that have helped design drugs which form a stronger interaction with the enzyme. These drugs inhibit neuraminidase by attaching themselves to the enzyme. Since the drugs are less likely to detach from the enzyme, they are more effective, require smaller dosages, and have fewer side effects. Shown here is a segmented representation of the neuraminidase inhibitor compound sitting inside a cave-like contour of the neuraminidase enzyme surface. This cave-like formation present in every neuraminidase enzyme is the active site crucial to the flu's ability to infect. The space-grown crystals of neuraminidase have provided significant new details about the three-dimensional characteristics of this active site thus allowing researchers to design drugs that fit tighter into the site. Principal Investigator: Dr. Larry DeLucas

Strategies for design of improved biocatalysts for industrial applications.

PubMed

Madhavan, Aravind; Sindhu, Raveendran; Binod, Parameswaran; Sukumaran, Rajeev K; Pandey, Ashok

2017-12-01

Biocatalysts are creating increased interest among researchers due to their unique properties. Several enzymes are efficiently produced by microorganisms. However, the use of natural enzymes as biocatalysts is hindered by low catalytic efficiency and stability during various industrial processes. Many advanced enzyme technologies have been developed to reshape the existing natural enzymes to reduce these limitations and prospecting of novel enzymes. Frequently used enzyme technologies include protein engineering by directed evolution, immobilisation techniques, metagenomics etc. This review summarizes recent and emerging advancements in the area of enzyme technologies for the development of novel biocatalysts and further discusses the future directions in this field. Copyright © 2017 Elsevier Ltd. All rights reserved.

How Do Enzymes 'Meet' Nanoparticles and Nanomaterials?

PubMed

Chen, Ming; Zeng, Guangming; Xu, Piao; Lai, Cui; Tang, Lin

2017-11-01

Enzymes are fundamental biological catalysts responsible for biological regulation and metabolism. The opportunity for enzymes to 'meet' nanoparticles and nanomaterials is rapidly increasing due to growing demands for applications in nanomaterial design, environmental monitoring, biochemical engineering, and biomedicine. Therefore, understanding the nature of nanomaterial-enzyme interactions is becoming important. Since 2014, enzymes have been used to modify, degrade, or make nanoparticles/nanomaterials, while numerous nanoparticles/nanomaterials have been used as materials for enzymatic immobilization and biosensors and as enzyme mimicry. Among the various nanoparticles and nanomaterials, metal nanoparticles and carbon nanomaterials have received extensive attention due to their fascinating properties. This review provides an overview about how enzymes meet nanoparticles and nanomaterials. Copyright © 2017 Elsevier Ltd. All rights reserved.

The disruptive effect of lysozyme on the bacterial cell wall explored by an in-silico structural outlook.

PubMed

Primo, Emiliano D; Otero, Lisandro H; Ruiz, Francisco; Klinke, Sebastián; Giordano, Walter

2018-01-01

The bacterial cell wall, a structural unit of peptidoglycan polymer comprised of glycan strands consisting of a repeating disaccharide motif [N-acetylglucosamine (NAG) and N-acetylmuramylpentapeptide (NAM pentapeptide)], encases bacteria and provides structural integrity and protection. Lysozymes are enzymes that break down the bacterial cell wall and disrupt the bacterial life cycle by cleaving the linkage between the NAG and NAM carbohydrates. Lab exercises focused on the effects of lysozyme on the bacterial cell wall are frequently incorporated in biochemistry classes designed for undergraduate students in diverse fields as biology, microbiology, chemistry, agronomy, medicine, and veterinary medicine. Such exercises typically do not include structural data. We describe here a sequence of computer tasks designed to illustrate and reinforce both physiological and structural concepts involved in lysozyme effects on the bacterial cell-wall structure. This lab class usually lasts 3.5 hours. First, the instructor presents introductory concepts of the bacterial cell wall and the effect of lysozyme on its structure. Then, students are taught to use computer modeling to visualize the three-dimensional structure of a lysozyme in complex with bacterial cell-wall fragments. Finally, the lysozyme inhibitory effect on a bacterial culture is optionally proposed as a simple microbiological assay. The computer lab exercises described here give students a realistic understanding of the disruptive effect of lysozymes on the bacterial cell wall, a crucial component in bacterial survival. © 2017 by The International Union of Biochemistry and Molecular Biology, 46(1):83-90, 2018. © 2017 The International Union of Biochemistry and Molecular Biology.

Mitoketoscins: Novel mitochondrial inhibitors for targeting ketone metabolism in cancer stem cells (CSCs)

PubMed Central

Ozsvari, Bela; Sotgia, Federica; Simmons, Katie; Trowbridge, Rachel; Foster, Richard; Lisanti, Michael P.

2017-01-01

Previous studies have now well-established that epithelial cancer cells can utilize ketone bodies (3-hydroxybutyrate and aceto-acetate) as mitochondrial fuels, to actively promote tumor growth and metastatic dissemination. The two critical metabolic enzymes implicated in this process are OXCT1 and ACAT1, which are both mitochondrial proteins. Importantly, over-expression of OXCT1 or ACAT1 in human breast cancer cells is sufficient to genetically drive tumorigenesis and/or lung metastasis, validating that they indeed behave as metabolic “tumor promoters”. Here, we decided to target these two enzymes, which give cancer cells the ability to recycle ketone bodies into Acetyl-CoA and, therefore, to produce increased ATP. Briefly, we used computational chemistry (in silico drug design) to select a sub-set of potentially promising compounds that spatially fit within the active site of these enzymes, based on their known 3D crystal structures. These libraries of compounds were then phenotypically screened for their effects on total cellular ATP levels. Positive hits were further validated by metabolic flux analysis. Our results indicated that four of these compounds effectively inhibited mitochondrial oxygen consumption. Two of these compounds also induced a reactive glycolytic phenotype in cancer cells. Most importantly, using the mammosphere assay, we showed that these compounds can be used to functionally inhibit cancer stem cell (CSC) activity and propagation. Finally, our molecular modeling studies directly show how these novel compounds are predicted to bind to the active catalytic sites of OXCT1 and ACAT1, within their Coenzyme A binding site. As such, we speculate that these mitochondrial inhibitors are partially mimicking the structure of Coenzyme A. Thus, we conclude that OXCT1 and ACAT1 are important new therapeutic targets for further drug development and optimization. We propose that this new class of drugs should be termed “mitoketoscins”, to reflect that they were designed to target ketone re-utilization and mitochondrial function. PMID:29108233

Rational approaches for engineering novel functionalities in carbon-carbon bond forming enzymes

PubMed Central

Baker, Perrin; Seah, Stephen Y. K.

2012-01-01

Enzymes that catalyze carbon-carbon bond formation can be exploited as biocatalyst for synthetic organic chemistry. However, natural enzymes frequently do not possess the required properties or specificities to catalyze industrially useful transformations. This mini-review describes recent work using knowledge-guided site-specific mutagenesis of key active site residues to alter substrate specificity, stereospecificity and reaction specificity of these enzymes. In addition, examples of de novo designed enzymes that catalyze C-C bond reactions not found in nature will be discussed. PMID:24688644

In silico prediction of potential chemical reactions mediated by human enzymes.

PubMed

Yu, Myeong-Sang; Lee, Hyang-Mi; Park, Aaron; Park, Chungoo; Ceong, Hyithaek; Rhee, Ki-Hyeong; Na, Dokyun

2018-06-13

Administered drugs are often converted into an ineffective or activated form by enzymes in our body. Conventional in silico prediction approaches focused on therapeutically important enzymes such as CYP450. However, there are more than thousands of different cellular enzymes that potentially convert administered drug into other forms. We developed an in silico model to predict which of human enzymes including metabolic enzymes as well as CYP450 family can catalyze a given chemical compound. The prediction is based on the chemical and physical similarity between known enzyme substrates and a query chemical compound. Our in silico model was developed using multiple linear regression and the model showed high performance (AUC = 0.896) despite of the large number of enzymes. When evaluated on a test dataset, it also showed significantly high performance (AUC = 0.746). Interestingly, evaluation with literature data showed that our model can be used to predict not only enzymatic reactions but also drug conversion and enzyme inhibition. Our model was able to predict enzymatic reactions of a query molecule with a high accuracy. This may foster to discover new metabolic routes and to accelerate the computational development of drug candidates by enabling the prediction of the potential conversion of administered drugs into active or inactive forms.

In silico strategies toward enzyme function and dynamics.

PubMed

Estácio, Sílvia G

2012-01-01

Enzymes are outstanding biocatalysts involved in a plethora of chemical reactions occurring in the cell. Despite their incommensurable importance, a comprehensive understanding of enzyme catalysis is still missing. This task becomes more laborious given the unavoidability of including the inherent dynamic nature of enzymes into that description. As such, it is essential to ascertain the nature and contribution of enzyme conformational changes to catalysis and to evaluate the adequacy of the proposal associating protein internal motions to the rate enhancement achieved. Dynamic events in enzymes span a wide range of time- and length-scales which have led to a surge in multiscale methodologies targeting enzyme function and dynamics. Computational strategies assume a preponderant role in such studies by allowing the atomic detail investigation of the fundamental mechanisms of enzyme catalysis thus surpassing what is achievable through experiments. While high-accuracy quantum mechanical methods are indicated to uncover the details of the chemical reaction occurring at the active site, molecular mechanical force fields and molecular dynamics approaches provide powerful means to access the conformational energy landscape accessible to enzymes. This review outlines some of the most important in silico methodologies in this area, highlighting examples of problems tackled and the insights obtained. Copyright © 2012 Elsevier Inc. All rights reserved.

Structure-based design, synthesis, molecular docking study and biological evaluation of 1,2,4-triazine derivatives acting as COX/15-LOX inhibitors with anti-oxidant activities.

PubMed

Khoshneviszadeh, Mehdi; Shahraki, Omolbanin; Khoshneviszadeh, Mahsima; Foroumadi, Alireza; Firuzi, Omidreza; Edraki, Najmeh; Nadri, Hamid; Moradi, Alireza; Shafiee, Abbas; Miri, Ramin

2016-12-01

A set of 1,2,4-triazine derivatives were designed as cyclooxygenase-2 (COX-2) inhibitors. These compounds were synthesized and screened for inhibition of cyclooxygenases (COX-1 and COX-2) based on a cellular assay using human whole blood (HWB) and lipoxygenase (LOX-15) that are key enzymes in inflammation. The results showed that 3-(2-(benzo[d][1,3]dioxol-5-ylmethylene)hydrazinyl)-5,6-bis(4-methoxyphenyl)-1,2,4-triazine (G11) was identified as the most potent COX-2 inhibitor (78%) relative to COX-1 (50%). Ferric reducing anti-oxidant power (FRAP) assay revealed that compound G10 possesses the highest anti-oxidant activity. The compound G3 with IC50 value of 124 μM was the most potent compound in LOX inhibitory assay. Molecular docking was performed and a good agreement was observed between computational and experimental results.

Preprogramming Complex Hydrogel Responses using Enzymatic Reaction Networks.

PubMed

Postma, Sjoerd G J; Vialshin, Ilia N; Gerritsen, Casper Y; Bao, Min; Huck, Wilhelm T S

2017-02-06

The creation of adaptive matter is heavily inspired by biological systems. However, it remains challenging to design complex material responses that are governed by reaction networks, which lie at the heart of cellular complexity. The main reason for this slow progress is the lack of a general strategy to integrate reaction networks with materials. Herein we use a systematic approach to preprogram the response of a hydrogel to a trigger, in this case the enzyme trypsin, which activates a reaction network embedded within the hydrogel. A full characterization of all the kinetic rate constants in the system enabled the construction of a computational model, which predicted different hydrogel responses depending on the input concentration of the trigger. The results of the simulation are in good agreement with experimental findings. Our methodology can be used to design new, adaptive materials of which the properties are governed by reaction networks of arbitrary complexity. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Predicting the Metabolic Sites by Flavin-Containing Monooxygenase on Drug Molecules Using SVM Classification on Computed Quantum Mechanics and Circular Fingerprints Molecular Descriptors

PubMed Central

Fu, Chien-wei; Lin, Thy-Hou

2017-01-01

As an important enzyme in Phase I drug metabolism, the flavin-containing monooxygenase (FMO) also metabolizes some xenobiotics with soft nucleophiles. The site of metabolism (SOM) on a molecule is the site where the metabolic reaction is exerted by an enzyme. Accurate prediction of SOMs on drug molecules will assist the search for drug leads during the optimization process. Here, some quantum mechanics features such as the condensed Fukui function and attributes from circular fingerprints (called Molprint2D) are computed and classified using the support vector machine (SVM) for predicting some potential SOMs on a series of drugs that can be metabolized by FMO enzymes. The condensed Fukui function fA− representing the nucleophilicity of central atom A and the attributes from circular fingerprints accounting the influence of neighbors on the central atom. The total number of FMO substrates and non-substrates collected in the study is 85 and they are equally divided into the training and test sets with each carrying roughly the same number of potential SOMs. However, only N-oxidation and S-oxidation features were considered in the prediction since the available C-oxidation data was scarce. In the training process, the LibSVM package of WEKA package and the option of 10-fold cross validation are employed. The prediction performance on the test set evaluated by accuracy, Matthews correlation coefficient and area under ROC curve computed are 0.829, 0.659, and 0.877 respectively. This work reveals that the SVM model built can accurately predict the potential SOMs for drug molecules that are metabolizable by the FMO enzymes. PMID:28072829

Exercises in Molecular Computing

PubMed Central

2014-01-01

Conspectus The successes of electronic digital logic have transformed every aspect of human life over the last half-century. The word “computer” now signifies a ubiquitous electronic device, rather than a human occupation. Yet evidently humans, large assemblies of molecules, can compute, and it has been a thrilling challenge to develop smaller, simpler, synthetic assemblies of molecules that can do useful computation. When we say that molecules compute, what we usually mean is that such molecules respond to certain inputs, for example, the presence or absence of other molecules, in a precisely defined but potentially complex fashion. The simplest way for a chemist to think about computing molecules is as sensors that can integrate the presence or absence of multiple analytes into a change in a single reporting property. Here we review several forms of molecular computing developed in our laboratories. When we began our work, combinatorial approaches to using DNA for computing were used to search for solutions to constraint satisfaction problems. We chose to work instead on logic circuits, building bottom-up from units based on catalytic nucleic acids, focusing on DNA secondary structures in the design of individual circuit elements, and reserving the combinatorial opportunities of DNA for the representation of multiple signals propagating in a large circuit. Such circuit design directly corresponds to the intuition about sensors transforming the detection of analytes into reporting properties. While this approach was unusual at the time, it has been adopted since by other groups working on biomolecular computing with different nucleic acid chemistries. We created logic gates by modularly combining deoxyribozymes (DNA-based enzymes cleaving or combining other oligonucleotides), in the role of reporting elements, with stem–loops as input detection elements. For instance, a deoxyribozyme that normally exhibits an oligonucleotide substrate recognition region is modified such that a stem–loop closes onto the substrate recognition region, making it unavailable for the substrate and thus rendering the deoxyribozyme inactive. But a conformational change can then be induced by an input oligonucleotide, complementary to the loop, to open the stem, allow the substrate to bind, and allow its cleavage to proceed, which is eventually reported via fluorescence. In this Account, several designs of this form are reviewed, along with their application in the construction of large circuits that exhibited complex logical and temporal relationships between the inputs and the outputs. Intelligent (in the sense of being capable of nontrivial information processing) theranostic (therapy + diagnostic) applications have always been the ultimate motivation for developing computing (i.e., decision-making) circuits, and we review our experiments with logic-gate elements bound to cell surfaces that evaluate the proximal presence of multiple markers on lymphocytes. PMID:24873234

Computational study concerning the effect of some pesticides on the Proteus Mirabilis catalase activity

NASA Astrophysics Data System (ADS)

Isvoran, Adriana

2016-03-01

Assessment of the effects of the herbicides nicosulfuron and chlorsulfuron and the fungicides difenoconazole and drazoxlone upon catalase produced by soil microorganism Proteus mirabilis is performed using the molecular docking technique. The interactions of pesticides with the enzymes are predicted using SwissDock and PatchDock docking tools. There are correlations for predicted binding energy values for enzyme-pesticide complexes obtained using the two docking tools, all the considered pesticides revealing favorable binding to the enzyme, but only the herbicides bind to the catalytic site. These results suggest the inhibitory potential of chlorsulfuron and nicosulfuron on the catalase activity in soil.

Molecular Bases of Enantioselectivity of Haloalkane Dehalogenase DbjA

NASA Astrophysics Data System (ADS)

Sato, Yukari; Natsume, Ryo; Prokop, Zbynek; Brezovsky, Jan; Chaloupkova, Radka; Damborsky, Jiri; Nagata, Yuji; Senda, Toshiya

Enzymes are widely used for the synthesis of pharmaceuticals, agrochemicals, and food additives because they can catalyze high enantioselective transformations. In order to construct selective enzymes by protein engineering, it is important to understand the molecular basis of enzyme-substrate interactions that contribute to enantioselectivity. The haloalkane dehalogenase DbjA showed high enantioselectivity for two racemic mixtures: α-bromoesters and β-bromoalkanes. Thermodynamic analysis, protein crystallography, and computer simulations indicated that DbjA carries two bases for the enantiodiscrimination of each racemic mixture. This study helps us understand the molecular basis of the enantioselectivity and opens up new possibilities for constructing enantiospecific biocatalysts through protein engineering.

A Century of Enzyme Kinetic Analysis, 1913 to 2013

PubMed Central

Johnson, Kenneth A.

2013-01-01

This review traces the history and logical progression of methods for quantitative analysis of enzyme kinetics from the 1913 Michaelis and Menten paper to the application of modern computational methods today. Following a brief review of methods for fitting steady state kinetic data, modern methods are highlighted for fitting full progress curve kinetics based upon numerical integration of rate equations, including a re-analysis of the original Michaelis-Menten full time course kinetic data. Finally, several illustrations of modern transient state kinetic methods of analysis are shown which enable the elucidation of reactions occurring at the active sites of enzymes in order to relate structure and function. PMID:23850893

DNA-Based Enzyme Reactors and Systems

PubMed Central

Linko, Veikko; Nummelin, Sami; Aarnos, Laura; Tapio, Kosti; Toppari, J. Jussi; Kostiainen, Mauri A.

2016-01-01

During recent years, the possibility to create custom biocompatible nanoshapes using DNA as a building material has rapidly emerged. Further, these rationally designed DNA structures could be exploited in positioning pivotal molecules, such as enzymes, with nanometer-level precision. This feature could be used in the fabrication of artificial biochemical machinery that is able to mimic the complex reactions found in living cells. Currently, DNA-enzyme hybrids can be used to control (multi-enzyme) cascade reactions and to regulate the enzyme functions and the reaction pathways. Moreover, sophisticated DNA structures can be utilized in encapsulating active enzymes and delivering the molecular cargo into cells. In this review, we focus on the latest enzyme systems based on novel DNA nanostructures: enzyme reactors, regulatory devices and carriers that can find uses in various biotechnological and nanomedical applications. PMID:28335267

Marked and variable inhibition by chemical fixation of cytochrome oxidase and succinate dehydrogenase in single motoneurons

NASA Technical Reports Server (NTRS)

Chalmers, G. R.; Edgerton, V. R.

1989-01-01

The effect of tissue fixation on succinate dehydrogenase and cytochrome oxidase activity in single motoneurons of the rat was demonstrated using a computer image processing system. Inhibition of enzyme activity by chemical fixation was variable, with some motoneurons being affected more than others. It was concluded that quantification of enzymatic activity in chemically fixed tissue provides an imprecise estimate of enzyme activities found in fresh-frozen tissues.

Design principles of autocatalytic cycles constrain enzyme kinetics and force low substrate saturation at flux branch points

PubMed Central

Barenholz, Uri; Davidi, Dan; Reznik, Ed; Bar-On, Yinon; Antonovsky, Niv; Noor, Elad; Milo, Ron

2017-01-01

A set of chemical reactions that require a metabolite to synthesize more of that metabolite is an autocatalytic cycle. Here, we show that most of the reactions in the core of central carbon metabolism are part of compact autocatalytic cycles. Such metabolic designs must meet specific conditions to support stable fluxes, hence avoiding depletion of intermediate metabolites. As such, they are subjected to constraints that may seem counter-intuitive: the enzymes of branch reactions out of the cycle must be overexpressed and the affinity of these enzymes to their substrates must be relatively weak. We use recent quantitative proteomics and fluxomics measurements to show that the above conditions hold for functioning cycles in central carbon metabolism of E. coli. This work demonstrates that the topology of a metabolic network can shape kinetic parameters of enzymes and lead to seemingly wasteful enzyme usage. DOI: http://dx.doi.org/10.7554/eLife.20667.001 PMID:28169831

Coupling Binding to Catalysis: Using Yeast Cell Surface Display to Select Enzymatic Activities.

PubMed

Zhang, Keya; Bhuripanyo, Karan; Wang, Yiyang; Yin, Jun

2015-01-01

We find yeast cell surface display can be used to engineer enzymes by selecting the enzyme library for high affinity binding to reaction intermediates. Here we cover key steps of enzyme engineering on the yeast cell surface including library design, construction, and selection based on magnetic and fluorescence-activated cell sorting.

Analysis of galactosemia-linked mutations of GALT enzyme using a computational biology approach.

PubMed

Facchiano, A; Marabotti, A

2010-02-01

We describe the prediction of the structural and functional effects of mutations on the enzyme galactose-1-phosphate uridyltransferase related to the genetic disease galactosemia, using a fully computational approach. One hundred and seven single-point mutants were simulated starting from the structural model of the enzyme obtained by homology modeling methods. Several bioinformatics programs were then applied to each resulting mutant protein to analyze the effect of the mutations. The mutations have a direct effect on the active site, or on the dimer assembly and stability, or on the monomer stability. We describe how mutations may exert their effect at a molecular level by altering H-bonds, salt bridges, secondary structure or surface features. The alteration of protein stability, at level of monomer and/or dimer, is the main effect observed. We found an agreement between our results and the functional experimental data available in literature for some mutants. The data and analyses for all the mutants are fully available in the web-accessible database hosted at http://bioinformatica.isa.cnr.it/GALT.

Optimization of parameters for enhanced oil recovery from enzyme treated wild apricot kernels.

PubMed

Rajaram, Mahatre R; Kumbhar, Baburao K; Singh, Anupama; Lohani, Umesh Chandra; Shahi, Navin C

2012-08-01

Present investigation was undertaken with the overall objective of optimizing the enzymatic parameters i.e. moisture content during hydrolysis, enzyme concentration, enzyme ratio and incubation period on wild apricot kernel processing for better oil extractability and increased oil recovery. Response surface methodology was adopted in the experimental design. A central composite rotatable design of four variables at five levels was chosen. The parameters and their range for the experiments were moisture content during hydrolysis (20-32%, w.b.), enzyme concentration (12-16% v/w of sample), combination of pectolytic and cellulolytic enzyme i.e. enzyme ratio (30:70-70:30) and incubation period (12-16 h). Aspergillus foetidus and Trichoderma viride was used for production of crude enzyme i.e. pectolytic and cellulolytic enzyme respectively. A complete second order model for increased oil recovery as the function of enzymatic parameters fitted the data well. The best fit model for oil recovery was also developed. The effect of various parameters on increased oil recovery was determined at linear, quadric and interaction level. The increased oil recovery ranged from 0.14 to 2.53%. The corresponding conditions for maximum oil recovery were 23% (w.b.), 15 v/w of the sample, 60:40 (pectolytic:cellulolytic), 13 h. Results of the study indicated that incubation period during enzymatic hydrolysis is the most important factor affecting oil yield followed by enzyme ratio, moisture content and enzyme concentration in the decreasing order. Enzyme ratio, incubation period and moisture content had insignificant effect on oil recovery. Second order model for increased oil recovery as a function of enzymatic hydrolysis parameters predicted the data adequately.

A 13-week research-based biochemistry laboratory curriculum.

PubMed

Lefurgy, Scott T; Mundorff, Emily C

2017-09-01

Here, we present a 13-week research-based biochemistry laboratory curriculum designed to provide the students with the experience of engaging in original research while introducing foundational biochemistry laboratory techniques. The laboratory experience has been developed around the directed evolution of an enzyme chosen by the instructor, with mutations designed by the students. Ideal enzymes for this curriculum are able to be structurally modeled, solubly expressed, and monitored for activity by UV/Vis spectroscopy, and an example curriculum for haloalkane dehalogenase is given. Unique to this curriculum is a successful implementation of saturation mutagenesis and high-throughput screening of enzyme function, along with bioinformatics analysis, homology modeling, structural analysis, protein expression and purification, polyacrylamide gel electrophoresis, UV/Vis spectroscopy, and enzyme kinetics. Each of these techniques is carried out using a novel student-designed mutant library or enzyme variant unique to the lab team and, importantly, not described previously in the literature. Use of a well-established set of protocols promotes student data quality. Publication may result from the original student-generated hypotheses and data, either from the class as a whole or individual students that continue their independent projects upon course completion. © 2017 by The International Union of Biochemistry and Molecular Biology, 45(5):437-448, 2017. © 2017 The International Union of Biochemistry and Molecular Biology.

A substrate selectivity and inhibitor design lesson from the PDE10-cAMP crystal structure: a computational study.

PubMed

Lau, Justin Kai-Chi; Li, Xiao-Bo; Cheng, Yuen-Kit

2010-04-22

Phosphodiesterases (PDEs) catalyze the hydrolysis of second messengers cAMP and cGMP in regulating many important cellular signals and have been recognized as important drug targets. Experimentally, a range of specificity/selectivity toward cAMP and cGMP is well-known for the individual PDE families. The study reported here reveals that PDEs might also exhibit selectivity toward conformations of the endogenous substrates cAMP and cGMP. Molecular dynamics simulations and free energy study have been applied to study the binding of the cAMP torsional conformers about the glycosyl bond in PDE10A2. The computational results elucidated that PDE10A2 is energetically more favorable in complex with the syn cAMP conformer (as reported in the crystal structure) and the binding of anti cAMP to PDE10A2 would lead to either a nonreactive configuration or significant perturbation on the catalytic pocket of the enzyme. This experimentally inaccessible information provides important molecular insights for the development of effective PDE10 ligands.

Adapting capillary gel electrophoresis as a sensitive, high-throughput method to accelerate characterization of nucleic acid metabolic enzymes.

PubMed

Greenough, Lucia; Schermerhorn, Kelly M; Mazzola, Laurie; Bybee, Joanna; Rivizzigno, Danielle; Cantin, Elizabeth; Slatko, Barton E; Gardner, Andrew F

2016-01-29

Detailed biochemical characterization of nucleic acid enzymes is fundamental to understanding nucleic acid metabolism, genome replication and repair. We report the development of a rapid, high-throughput fluorescence capillary gel electrophoresis method as an alternative to traditional polyacrylamide gel electrophoresis to characterize nucleic acid metabolic enzymes. The principles of assay design described here can be applied to nearly any enzyme system that acts on a fluorescently labeled oligonucleotide substrate. Herein, we describe several assays using this core capillary gel electrophoresis methodology to accelerate study of nucleic acid enzymes. First, assays were designed to examine DNA polymerase activities including nucleotide incorporation kinetics, strand displacement synthesis and 3'-5' exonuclease activity. Next, DNA repair activities of DNA ligase, flap endonuclease and RNase H2 were monitored. In addition, a multicolor assay that uses four different fluorescently labeled substrates in a single reaction was implemented to characterize GAN nuclease specificity. Finally, a dual-color fluorescence assay to monitor coupled enzyme reactions during Okazaki fragment maturation is described. These assays serve as a template to guide further technical development for enzyme characterization or nucleoside and non-nucleoside inhibitor screening in a high-throughput manner. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Biochemical characterization of a phosphinate inhibitor of Escherichia coli MurC.

PubMed

Marmor, S; Petersen, C P; Reck, F; Yang, W; Gao, N; Fisher, S L

2001-10-09

The bacterial UDP-N-acetylmuramyl-L-alanine ligase (MurC) from Escherichia coli, an essential, cytoplasmic peptidoglycan biosynthetic enzyme, catalyzes the ATP-dependent ligation of L-alanine (Ala) and UDP-N-acetylmuramic acid (UNAM) to form UDP-N-acetylmuramyl-L-alanine (UNAM-Ala). The phosphinate inhibitor 1 was designed and prepared as a multisubstrate/transition state analogue. The compound exhibits mixed-type inhibition with respect to all three enzyme substrates (ATP, UNAM, Ala), suggesting that this compound forms dead-end complexes with multiple enzyme states. Results from isothermal titration calorimetry (ITC) studies supported these findings as exothermic binding was observed under conditions with free enzyme (K(d) = 1.80-2.79 microM, 95% CI), enzyme saturated with ATP (K(d) = 0.097-0.108 microM, 95% CI), and enzyme saturated with the reaction product ADP (K(d) = 0.371-0.751 microM, 95% CI). Titrations run under conditions of saturating UNAM or the product UNAM-Ala did not show heat effects consistent with competitive compound binding to the active site. The potent binding affinity observed in the presence of ATP is consistent with the inhibitor design and the proposed Ordered Ter-Ter mechanism for this enzyme; however, the additional binding pathways suggest that the inhibitor can also serve as a product analogue.

Unlocking the potential of metagenomics through replicated experimental design.

PubMed

Knight, Rob; Jansson, Janet; Field, Dawn; Fierer, Noah; Desai, Narayan; Fuhrman, Jed A; Hugenholtz, Phil; van der Lelie, Daniel; Meyer, Folker; Stevens, Rick; Bailey, Mark J; Gordon, Jeffrey I; Kowalchuk, George A; Gilbert, Jack A

2012-06-07

Metagenomics holds enormous promise for discovering novel enzymes and organisms that are biomarkers or drivers of processes relevant to disease, industry and the environment. In the past two years, we have seen a paradigm shift in metagenomics to the application of cross-sectional and longitudinal studies enabled by advances in DNA sequencing and high-performance computing. These technologies now make it possible to broadly assess microbial diversity and function, allowing systematic investigation of the largely unexplored frontier of microbial life. To achieve this aim, the global scientific community must collaborate and agree upon common objectives and data standards to enable comparative research across the Earth's microbiome. Improvements in comparability of data will facilitate the study of biotechnologically relevant processes, such as bioprospecting for new glycoside hydrolases or identifying novel energy sources.

Regioselective Acetylation of C21 Hydroxysteroids by the Bacterial Chloramphenicol Acetyltransferase I.

PubMed

Mosa, Azzam; Hutter, Michael C; Zapp, Josef; Bernhardt, Rita; Hannemann, Frank

2015-07-27

Chloramphenicol acetyltransferase I (CATI) detoxifies the antibiotic chloramphenicol and confers a corresponding resistance to bacteria. In this study we identified this enzyme as a steroid acetyltransferase and designed a new and efficient Escherichia-coli-based biocatalyst for the regioselective acetylation of C21 hydroxy groups in steroids of pharmaceutical interest. The cells carried a recombinant catI gene controlled by a constitutive promoter. The capacity of the whole-cell system to modify different hydroxysteroids was investigated, and NMR spectroscopy revealed that all substrates were selectively transformed into the corresponding 21-acetoxy derivatives. The biotransformation was optimized, and the reaction mechanism is discussed on the basis of a computationally modeled substrate docking into the crystal structure of CATI. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Spreadsheet-based program for alignment of overlapping DNA sequences.

PubMed

Anbazhagan, R; Gabrielson, E

1999-06-01

Molecular biology laboratories frequently face the challenge of aligning small overlapping DNA sequences derived from a long DNA segment. Here, we present a short program that can be used to adapt Excel spreadsheets as a tool for aligning DNA sequences, regardless of their orientation. The program runs on any Windows or Macintosh operating system computer with Excel 97 or Excel 98. The program is available for use as an Excel file, which can be downloaded from the BioTechniques Web site. Upon execution, the program opens a specially designed customized workbook and is capable of identifying overlapping regions between two sequence fragments and displaying the sequence alignment. It also performs a number of specialized functions such as recognition of restriction enzyme cutting sites and CpG island mapping without costly specialized software.

Medium Optimization for the Production of Fibrinolytic Enzyme by Paenibacillus sp. IND8 Using Response Surface Methodology

PubMed Central

Prakash Vincent, Samuel Gnana

2014-01-01

Production of fibrinolytic enzyme by a newly isolated Paenibacillus sp. IND8 was optimized using wheat bran in solid state fermentation. A 25 full factorial design (first-order model) was applied to elucidate the key factors as moisture, pH, sucrose, yeast extract, and sodium dihydrogen phosphate. Statistical analysis of the results has shown that moisture, sucrose, and sodium dihydrogen phosphate have the most significant effects on fibrinolytic enzymes production (P < 0.05). Central composite design (CCD) was used to determine the optimal concentrations of these three components and the experimental results were fitted with a second-order polynomial model at 95% level (P < 0.05). Overall, 4.5-fold increase in fibrinolytic enzyme production was achieved in the optimized medium as compared with the unoptimized medium. PMID:24523635

In Vitro Fluorogenic Real-time Assay of the Repair of Oxidative DNA Damage

PubMed Central

Edwards, Sarah K.; Ono, Toshikazu; Wang, Shenliang; Jiang, Wei; Franzini, Raphael M.; Jung, Jong Wha; Chan, Ke Min; Kool, Eric T.

2015-01-01

The repair of oxidative damage to DNA is essential to avoidance of mutations that lead to cancer. Oxidized DNA bases, such as 8-oxoguanine, are a chief source of these mutations, and the enzyme 8-oxoguanine glycosylase 1 (OGG1) is the chief human enzyme that excises 8-oxoguanine from DNA. The activity of OGG1 has been linked to human inflammation responses and to cancer, and researchers are beginning to search for inhibitors of the enzyme. However, measuring the activity of the enzyme typically requires laborious gel-based measurements of radiolabeled DNAs. Here we report on the design and properties of fluorogenic probes that directly report on OGG1 (and bacterial homologue Fpg) activity in real time as the oxidized base is excised. The probes are short modified DNA oligomers containing fluorescent DNA bases and are designed to utilize the damaged DNA base itself as a fluorescence quencher. Screening of combinations of fluorophores and 8-oxoguanine revealed two fluorophores, pyrene and tCo, that are strongly quenched by the damaged base. We tested 42 potential probe designs containing these fluorophores, and we found an optimized probe OGR1 that yields a 60-fold light-up signal in vitro with OGG1 and Fpg, and can report on oxidative repair activity in mammalian cell lysate and with bacterial cells overexpressing a repair enzyme. Such probes may be useful in quantifying enzyme activity and performing competitive inhibition assays. PMID:26073452

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.

Thermodynamically based solvent design for enzymatic saccharide acylation with hydroxycinnamic acids in non-conventional media.

PubMed

Zeuner, Birgitte; Kontogeorgis, Georgios M; Riisager, Anders; Meyer, Anne S

2012-02-15

Enzyme-catalyzed synthesis has been widely studied with lipases (EC 3.1.1.3), but feruloyl esterases (FAEs; EC 3.1.1.73) may provide advantages such as higher substrate affinity and regioselectivity in the synthesis of hydroxycinnamate saccharide esters. These compounds are interesting because of their amphiphilicity and antioxidative potential. Synthetic reactions using mono- or disaccharides as one of the substrates may moreover direct new routes for biomass upgrading in the biorefinery. The paper reviews the available data for enzymatic hydroxycinnamate saccharide ester synthesis in organic solvent systems as well as other enzymatic hydroxycinnamate acylations in ionic liquid systems. The choice of solvent system is highly decisive for enzyme stability, selectivity, and reaction yields in these synthesis reactions. To increase the understanding of the reaction environment and to facilitate solvent screening as a crucial part of the reaction design, the review explores the use of activity coefficient models for describing these systems and - more importantly - the use of group contribution model UNIFAC and quantum chemistry based COSMO-RS for thermodynamic predictions and preliminary solvent screening. Surfactant-free microemulsions of a hydrocarbon, a polar alcohol, and water are interesting solvent systems because they accommodate different substrate and product solubilities and maintain enzyme stability. Ionic liquids may provide advantages as solvents in terms of increased substrate and product solubility, higher reactivity and selectivity, as well as tunable physicochemical properties, but their design should be carefully considered in relation to enzyme stability. The treatise shows that thermodynamic modeling tools for solvent design provide a new toolbox to design enzyme-catalyzed synthetic reactions from biomass sources. Copyright © 2011 Elsevier B.V. All rights reserved.

ORENZA: a web resource for studying ORphan ENZyme activities

PubMed Central

Lespinet, Olivier; Labedan, Bernard

2006-01-01

Background Despite the current availability of several hundreds of thousands of amino acid sequences, more than 36% of the enzyme activities (EC numbers) defined by the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology (NC-IUBMB) are not associated with any amino acid sequence in major public databases. This wide gap separating knowledge of biochemical function and sequence information is found for nearly all classes of enzymes. Thus, there is an urgent need to explore these sequence-less EC numbers, in order to progressively close this gap. Description We designed ORENZA, a PostgreSQL database of ORphan ENZyme Activities, to collate information about the EC numbers defined by the NC-IUBMB with specific emphasis on orphan enzyme activities. Complete lists of all EC numbers and of orphan EC numbers are available and will be periodically updated. ORENZA allows one to browse the complete list of EC numbers or the subset associated with orphan enzymes or to query a specific EC number, an enzyme name or a species name for those interested in particular organisms. It is possible to search ORENZA for the different biochemical properties of the defined enzymes, the metabolic pathways in which they participate, the taxonomic data of the organisms whose genomes encode them, and many other features. The association of an enzyme activity with an amino acid sequence is clearly underlined, making it easy to identify at once the orphan enzyme activities. Interactive publishing of suggestions by the community would provide expert evidence for re-annotation of orphan EC numbers in public databases. Conclusion ORENZA is a Web resource designed to progressively bridge the unwanted gap between function (enzyme activities) and sequence (dataset present in public databases). ORENZA should increase interactions between communities of biochemists and of genomicists. This is expected to reduce the number of orphan enzyme activities by allocating gene sequences to the relevant enzymes. PMID:17026747

iSCHRUNK--In Silico Approach to Characterization and Reduction of Uncertainty in the Kinetic Models of Genome-scale Metabolic Networks.

PubMed

Andreozzi, Stefano; Miskovic, Ljubisa; Hatzimanikatis, Vassily

2016-01-01

Accurate determination of physiological states of cellular metabolism requires detailed information about metabolic fluxes, metabolite concentrations and distribution of enzyme states. Integration of fluxomics and metabolomics data, and thermodynamics-based metabolic flux analysis contribute to improved understanding of steady-state properties of metabolism. However, knowledge about kinetics and enzyme activities though essential for quantitative understanding of metabolic dynamics remains scarce and involves uncertainty. Here, we present a computational methodology that allow us to determine and quantify the kinetic parameters that correspond to a certain physiology as it is described by a given metabolic flux profile and a given metabolite concentration vector. Though we initially determine kinetic parameters that involve a high degree of uncertainty, through the use of kinetic modeling and machine learning principles we are able to obtain more accurate ranges of kinetic parameters, and hence we are able to reduce the uncertainty in the model analysis. We computed the distribution of kinetic parameters for glucose-fed E. coli producing 1,4-butanediol and we discovered that the observed physiological state corresponds to a narrow range of kinetic parameters of only a few enzymes, whereas the kinetic parameters of other enzymes can vary widely. Furthermore, this analysis suggests which are the enzymes that should be manipulated in order to engineer the reference state of the cell in a desired way. The proposed approach also sets up the foundations of a novel type of approaches for efficient, non-asymptotic, uniform sampling of solution spaces. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Design Strategy of Multi-electron Transfer Catalysts Based on a Bioinformatic Analysis of Oxygen Evolution and Reduction Enzymes.

PubMed

Ooka, Hideshi; Hashimoto, Kazuhito; Nakamura, Ryuhei

2018-05-14

Understanding the design strategy of photosynthetic and respiratory enzymes is important to develop efficient artificial catalysts for oxygen evolution and reduction reactions. Here, based on a bioinformatic analysis of cyanobacterial oxygen evolution and reduction enzymes (photosystem II: PS II and cytochrome c oxidase: COX, respectively), the gene encoding the catalytic D1 subunit of PS II was found to be expressed individually across 38 phylogenetically diverse strains, which is in contrast to the operon structure of the genes encoding major COX subunits. Selective synthesis of the D1 subunit minimizes the repair cost of PS II, which allows compensation for its instability by lowering the turnover number required to generate a net positive energy yield. The different bioenergetics observed between PS II and COX suggest that in addition to the catalytic activity rationalized by the Sabatier principle, stability factors have also provided a major influence on the design strategy of biological multi-electron transfer enzymes. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Structural models for the design of novel antiviral agents against Greek Goat Encephalitis

PubMed Central

Papageorgiou, Louis; Loukatou, Styliani; Koumandou, Vassiliki Lila; Makałowski, Wojciech; Megalooikonomou, Vasileios

2014-01-01

The Greek Goat Encephalitis virus (GGE) belongs to the Flaviviridae family of the genus Flavivirus. The GGE virus constitutes an important pathogen of livestock that infects the goat’s central nervous system. The viral enzymes of GGE, helicase and RNA-dependent RNA polymerase (RdRP), are ideal targets for inhibitor design, since those enzymes are crucial for the virus’ survival, proliferation and transmission. In an effort to understand the molecular structure underlying the functions of those viral enzymes, the three dimensional structures of GGE NS3 helicase and NS5 RdRP have been modelled. The models were constructed in silico using conventional homology modelling techniques and the known 3D crystal structures of solved proteins from closely related species as templates. The established structural models of the GGE NS3 helicase and NS5 RdRP have been evaluated for their viability using a repertoire of in silico tools. The goal of this study is to present the 3D conformations of the GGE viral enzymes as reliable structural models that could provide the platform for the design of novel anti-GGE agents. PMID:25392762

Chemical Modification in the Design of Immobilized Enzyme Biocatalysts: Drawbacks and Opportunities.

PubMed

Rueda, Nazzoly; Dos Santos, Jose C S; Ortiz, Claudia; Torres, Rodrigo; Barbosa, Oveimar; Rodrigues, Rafael C; Berenguer-Murcia, Ángel; Fernandez-Lafuente, Roberto

2016-06-01

Chemical modification of enzymes and immobilization used to be considered as separate ways to improve enzyme properties. This review shows how the coupled use of both tools may greatly improve the final biocatalyst performance. Chemical modification of a previously immobilized enzyme is far simpler and easier to control than the modification of the free enzyme. Moreover, if protein modification is performed to improve its immobilization (enriching the enzyme in reactive groups), the final features of the immobilized enzyme may be greatly improved. Chemical modification may be directed to improve enzyme stability, but also to improve selectivity, specificity, activity, and even cell penetrability. Coupling of immobilization and chemical modification with site-directed mutagenesis is a powerful instrument to obtain fully controlled modification. Some new ideas such as photoreceptive enzyme modifiers that change their physical properties under UV exposition are discussed. © 2016 The Chemical Society of Japan & Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimal experimental design for assessment of enzyme kinetics in a drug discovery screening environment.

PubMed

Sjögren, Erik; Nyberg, Joakim; Magnusson, Mats O; Lennernäs, Hans; Hooker, Andrew; Bredberg, Ulf

2011-05-01

A penalized expectation of determinant (ED)-optimal design with a discrete parameter distribution was used to find an optimal experimental design for assessment of enzyme kinetics in a screening environment. A data set for enzyme kinetic data (V(max) and K(m)) was collected from previously reported studies, and every V(max)/K(m) pair (n = 76) was taken to represent a unique drug compound. The design was restricted to 15 samples, an incubation time of up to 40 min, and starting concentrations (C(0)) for the incubation between 0.01 and 100 μM. The optimization was performed by finding the sample times and C(0) returning the lowest uncertainty (S.E.) of the model parameter estimates. Individual optimal designs, one general optimal design and one, for laboratory practice suitable, pragmatic optimal design (OD) were obtained. In addition, a standard design (STD-D), representing a commonly applied approach for metabolic stability investigations, was constructed. Simulations were performed for OD and STD-D by using the Michaelis-Menten (MM) equation, and enzyme kinetic parameters were estimated with both MM and a monoexponential decay. OD generated a better result (relative standard error) for 99% of the compounds and an equal or better result [(root mean square error (RMSE)] for 78% of the compounds in estimation of metabolic intrinsic clearance. Furthermore, high-quality estimates (RMSE < 30%) of both V(max) and K(m) could be obtained for a considerable number (26%) of the investigated compounds by using the suggested OD. The results presented in this study demonstrate that the output could generally be improved compared with that obtained from the standard approaches used today.

Promiscuity in the Enzymatic Catalysis of Phosphate and Sulfate Transfer

PubMed Central

2016-01-01

The enzymes that facilitate phosphate and sulfate hydrolysis are among the most proficient natural catalysts known to date. Interestingly, a large number of these enzymes are promiscuous catalysts that exhibit both phosphatase and sulfatase activities in the same active site and, on top of that, have also been demonstrated to efficiently catalyze the hydrolysis of other additional substrates with varying degrees of efficiency. Understanding the factors that underlie such multifunctionality is crucial both for understanding functional evolution in enzyme superfamilies and for the development of artificial enzymes. In this Current Topic, we have primarily focused on the structural and mechanistic basis for catalytic promiscuity among enzymes that facilitate both phosphoryl and sulfuryl transfer in the same active site, while comparing this to how catalytic promiscuity manifests in other promiscuous phosphatases. We have also drawn on the large number of experimental and computational studies of selected model systems in the literature to explore the different features driving the catalytic promiscuity of such enzymes. Finally, on the basis of this comparative analysis, we probe the plausible origins and determinants of catalytic promiscuity in enzymes that catalyze phosphoryl and sulfuryl transfer. PMID:27187273

Enzyme-Powered Pumps: From Fundamentals to Applications

NASA Astrophysics Data System (ADS)

Ortiz-Rivera, Isamar

Non-mechanical nano and microfluidic devices that function without the aid of an external power source, and can be tailored to meet specific needs, represent the next generation of smart devices. Recently, we have shown that surface-bound enzymes can act as pumps driving large-scale fluid flows in the presence of any substance that triggers the enzymatic reaction (e.g. substrate, co-factor, or biomarker). The fluid velocities attained in such systems depend directly on the enzymatic reaction rate and the concentration of the substance that initiates enzymatic catalysis. The use of biochemical reactions to power a micropump offers the advantages of specificity, sensitivity, and selectively, eliminating at the same time the need of an external power source, while providing biocompatibility. More importantly, these self-powered pumps overcome a significant obstacle in nano- and micro-fluidics: the need to use external pressure-driven pumps to push fluids through devices. Certainly, the development of enzyme-powered devices opens up new venues in biochemical engineering, particularly in the biomedical field. The work highlighted in this dissertation covers all the studies performed with enzyme-powered pumps, from the development of the micropump design, to the efforts invested in understanding the enzyme pump concept as a whole. The data collected to date, aims to expand our knowledge about enzyme-powered micropumps from the inside out: not only by exploring the different applications of these devices at the macroscale, but also by investigating in depth the mechanism of pump activation behind these systems. Specifically, we have focused on: (1) The general features that characterize the pumping behavior observed in enzyme-powered pumps, as well as the optimization of the device, (2) the possible mechanisms behind fluid motion, including the role of enzyme coverage and/or activity on the transduction of chemical energy into mechanical fluid flow in these devices, covering also the effect of the thermodynamics of the enzymatic reaction in the pumping behavior, and (3) the applicability of enzyme pumps as fluid flow-based inhibitor assays and as drug delivery devices. Our findings in each of these areas, gets us closer to our ultimate goal, where we aim to identify the optimal conditions needed for enzyme micropump operation, and construct a general model that could accurately predict enzyme micropump behavior for any enzyme-substrate combination. The information aforementioned has been divided in four chapters. Chapter 1 gives a quick glance into the development of enzyme-powered micropumps: from the systems and observed behaviors inspiring this work, to the first systems that were developed. The stability, duration, and extent of fluid pumping of enzyme pumps in general, are also discussed, along with the optimization of the enzyme-pump design. This chapter aims to provide a general idea of the motivation behind the concept of "enzyme-powered pumps", what are "enzyme-powered pumps", and which are the key features that characterize these systems. Chapter 2 is an extensive analysis of the mechanisms of actuation proposed for enzyme-powered micropumps. This chapter not only covers the first attempts to understand how enzyme pumps work, but also explores further the behavior of urease-powered pumps, which fluid flow patterns cannot be completely predicted only by considering thermal or solutal gradients. The findings of these studies could allow us to rationally control fluid flow for the directed delivery of payloads at designated locations. In Chapters 3 and 4, our focus was to highlight the potential application of enzyme-powered pumps for sensing and delivery. Chapter 3 explores the use of enzyme pumps as fluid flow-based inhibitor assays. At fixed concentrations of an enzyme and its substrate, the presence of an inhibitor can be detected by monitoring the decrease in fluid flow speed. Using this principle, sensors for toxic substances, like mercury, cyanide and azide, were designed using urease and catalase-powered pumps, respectively, with limits of detection well below the concentrations permitted by the Environmental Protection Agency (EPA). Chapter 4 demonstrates that, apart from their applicability as sensors, enzyme pumps can also be used for stimuli-responsive release, if the architecture applied for the design of the enzyme pump consists of a porous scaffold (e.g. hydrogel), that serves both as the platform for enzyme immobilization and as the host for guest molecules to be released. These proof-of-concept devices were developed with the idea of using the flows generated by enzymatic catalysis to power cargo release, only in the presence of the correct stimuli (e.g. release of insulin in the presence of glucose; release of antidotes in the presence of a toxic agent). In the cases studied, cargo release was directly proportional to the concentration of enzyme substrate in solution, highlighting the sensitivity of the device and its potential for drug delivery purposes. (Abstract shortened by Proquest.).

Computer-aided design and computer science technology

NASA Technical Reports Server (NTRS)

Fulton, R. E.; Voigt, S. J.

1976-01-01

A description is presented of computer-aided design requirements and the resulting computer science advances needed to support aerospace design. The aerospace design environment is examined, taking into account problems of data handling and aspects of computer hardware and software. The interactive terminal is normally the primary interface between the computer system and the engineering designer. Attention is given to user aids, interactive design, interactive computations, the characteristics of design information, data management requirements, hardware advancements, and computer science developments.

Enzyme Active Site Interactions by Raman/FTIR, NMR, and Ab Initio Calculations

PubMed Central

Deng, Hua

2017-01-01

Characterization of enzyme active site structure and interactions at high resolution is important for the understanding of the enzyme catalysis. Vibrational frequency and NMR chemical shift measurements of enzyme-bound ligands are often used for such purpose when X-ray structures are not available or when higher resolution active site structures are desired. This review is focused on how ab initio calculations may be integrated with vibrational and NMR chemical shift measurements to quantitatively determine high-resolution ligand structures (up to 0.001 Å for bond length and 0.01 Å for hydrogen bonding distance) and how interaction energies between bound ligand and its surroundings at the active site may be determined. Quantitative characterization of substrate ionic states, bond polarizations, tautomeric forms, conformational changes and its interactions with surroundings in enzyme complexes that mimic ground state or transition state can provide snapshots for visualizing the substrate structural evolution along enzyme-catalyzed reaction pathway. Our results have shown that the integration of spectroscopic studies with theoretical computation greatly enhances our ability to interpret experimental data and significantly increases the reliability of the theoretical analysis. PMID:24018325

Discovery, Molecular Mechanisms, and Industrial Applications of Cold-Active Enzymes

PubMed Central

Santiago, Margarita; Ramírez-Sarmiento, César A.; Zamora, Ricardo A.; Parra, Loreto P.

2016-01-01

Cold-active enzymes constitute an attractive resource for biotechnological applications. Their high catalytic activity at temperatures below 25°C makes them excellent biocatalysts that eliminate the need of heating processes hampering the quality, sustainability, and cost-effectiveness of industrial production. Here we provide a review of the isolation and characterization of novel cold-active enzymes from microorganisms inhabiting different environments, including a revision of the latest techniques that have been used for accomplishing these paramount tasks. We address the progress made in the overexpression and purification of cold-adapted enzymes, the evolutionary and molecular basis of their high activity at low temperatures and the experimental and computational techniques used for their identification, along with protein engineering endeavors based on these observations to improve some of the properties of cold-adapted enzymes to better suit specific applications. We finally focus on examples of the evaluation of their potential use as biocatalysts under conditions that reproduce the challenges imposed by the use of solvents and additives in industrial processes and of the successful use of cold-adapted enzymes in biotechnological and industrial applications. PMID:27667987

Discovery, Molecular Mechanisms, and Industrial Applications of Cold-Active Enzymes.

PubMed

Santiago, Margarita; Ramírez-Sarmiento, César A; Zamora, Ricardo A; Parra, Loreto P

2016-01-01

Cold-active enzymes constitute an attractive resource for biotechnological applications. Their high catalytic activity at temperatures below 25°C makes them excellent biocatalysts that eliminate the need of heating processes hampering the quality, sustainability, and cost-effectiveness of industrial production. Here we provide a review of the isolation and characterization of novel cold-active enzymes from microorganisms inhabiting different environments, including a revision of the latest techniques that have been used for accomplishing these paramount tasks. We address the progress made in the overexpression and purification of cold-adapted enzymes, the evolutionary and molecular basis of their high activity at low temperatures and the experimental and computational techniques used for their identification, along with protein engineering endeavors based on these observations to improve some of the properties of cold-adapted enzymes to better suit specific applications. We finally focus on examples of the evaluation of their potential use as biocatalysts under conditions that reproduce the challenges imposed by the use of solvents and additives in industrial processes and of the successful use of cold-adapted enzymes in biotechnological and industrial applications.

dEMBF: A Comprehensive Database of Enzymes of Microalgal Biofuel Feedstock.

PubMed

Misra, Namrata; Panda, Prasanna Kumar; Parida, Bikram Kumar; Mishra, Barada Kanta

2016-01-01

Microalgae have attracted wide attention as one of the most versatile renewable feedstocks for production of biofuel. To develop genetically engineered high lipid yielding algal strains, a thorough understanding of the lipid biosynthetic pathway and the underpinning enzymes is essential. In this work, we have systematically mined the genomes of fifteen diverse algal species belonging to Chlorophyta, Heterokontophyta, Rhodophyta, and Haptophyta, to identify and annotate the putative enzymes of lipid metabolic pathway. Consequently, we have also developed a database, dEMBF (Database of Enzymes of Microalgal Biofuel Feedstock), which catalogues the complete list of identified enzymes along with their computed annotation details including length, hydrophobicity, amino acid composition, subcellular location, gene ontology, KEGG pathway, orthologous group, Pfam domain, intron-exon organization, transmembrane topology, and secondary/tertiary structural data. Furthermore, to facilitate functional and evolutionary study of these enzymes, a collection of built-in applications for BLAST search, motif identification, sequence and phylogenetic analysis have been seamlessly integrated into the database. dEMBF is the first database that brings together all enzymes responsible for lipid synthesis from available algal genomes, and provides an integrative platform for enzyme inquiry and analysis. This database will be extremely useful for algal biofuel research. It can be accessed at http://bbprof.immt.res.in/embf.

Conformational Sub-states and Populations in Enzyme Catalysis

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

Agarwal, Pratul K; Doucet, Nicholas; Chennubholta, C

reactants in the active site, chemical turnover, and release of products. In addition to formation of crucial structural interactions between enzyme and substrate(s), coordinated motions within the enzyme substrate complex allow reaction to proceed at a much faster rate, compared to the reaction in solution and in the absence of enzyme. An increasing number of enzyme systems show the presence of conserved protein motions that are important for function. A wide variety of motions are naturally sampled (over femtosecond to millisecond time-scales) as the enzyme complex moves along the energetic landscape, driven by temperature and dynamical events from the surroundingmore » environment. Areas of low energy along the landscape form conformational sub-states, which show higher conformational populations than surrounding areas. A small number of these protein conformational sub-states contain functionally important structural and dynamical features, which assist the enzyme mechanism along the catalytic cycle. Identification and characterization of these higher-energy (also called excited) sub-states and the associated populations are challenging, as these sub-states are very short-lived and therefore rarely populated. Specialized techniques based on computer simulations, theoretical modeling, and nuclear magnetic resonance have been developed for quantitative characterization of these sub-states and populations. This chapter discusses these techniques and provides examples of their applications to enzyme systems.« less

dEMBF: A Comprehensive Database of Enzymes of Microalgal Biofuel Feedstock

PubMed Central

Misra, Namrata; Panda, Prasanna Kumar; Parida, Bikram Kumar; Mishra, Barada Kanta

2016-01-01

Microalgae have attracted wide attention as one of the most versatile renewable feedstocks for production of biofuel. To develop genetically engineered high lipid yielding algal strains, a thorough understanding of the lipid biosynthetic pathway and the underpinning enzymes is essential. In this work, we have systematically mined the genomes of fifteen diverse algal species belonging to Chlorophyta, Heterokontophyta, Rhodophyta, and Haptophyta, to identify and annotate the putative enzymes of lipid metabolic pathway. Consequently, we have also developed a database, dEMBF (Database of Enzymes of Microalgal Biofuel Feedstock), which catalogues the complete list of identified enzymes along with their computed annotation details including length, hydrophobicity, amino acid composition, subcellular location, gene ontology, KEGG pathway, orthologous group, Pfam domain, intron-exon organization, transmembrane topology, and secondary/tertiary structural data. Furthermore, to facilitate functional and evolutionary study of these enzymes, a collection of built-in applications for BLAST search, motif identification, sequence and phylogenetic analysis have been seamlessly integrated into the database. dEMBF is the first database that brings together all enzymes responsible for lipid synthesis from available algal genomes, and provides an integrative platform for enzyme inquiry and analysis. This database will be extremely useful for algal biofuel research. It can be accessed at http://bbprof.immt.res.in/embf. PMID:26727469

The Use and Benefits of Computer Aided Learning in the Assessment of the Laboratory Exercise "Enzyme Induction in Escherichia coli".

ERIC Educational Resources Information Center

Pamula, F.; And Others

1995-01-01

Describes an interactive computer program written to provide accurate and immediate feedback to students while they are processing experimental data. Discusses the problems inherent in laboratory courses that led to the development of this program. Advantages of the software include allowing students to work at their own pace in a nonthreatening…

Development of Quantum Chemical Method to Calculate Half Maximal Inhibitory Concentration (IC50 ).

PubMed

Bag, Arijit; Ghorai, Pradip Kr

2016-05-01

Till date theoretical calculation of the half maximal inhibitory concentration (IC50 ) of a compound is based on different Quantitative Structure Activity Relationship (QSAR) models which are empirical methods. By using the Cheng-Prusoff equation it may be possible to compute IC50 , but this will be computationally very expensive as it requires explicit calculation of binding free energy of an inhibitor with respective protein or enzyme. In this article, for the first time we report an ab initio method to compute IC50 of a compound based only on the inhibitor itself where the effect of the protein is reflected through a proportionality constant. By using basic enzyme inhibition kinetics and thermodynamic relations, we derive an expression of IC50 in terms of hydrophobicity, electric dipole moment (μ) and reactivity descriptor (ω) of an inhibitor. We implement this theory to compute IC50 of 15 HIV-1 capsid inhibitors and compared them with experimental results and available other QASR based empirical results. Calculated values using our method are in very good agreement with the experimental values compared to the values calculated using other methods. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Approaching a Conceptual Understanding of Enzyme Kinetics and Inhibition: Development of an Active Learning Inquiry Activity for Prehealth and Nonscience Majors

ERIC Educational Resources Information Center

House, Chloe; Meades, Glen; Linenberger, Kimberly J.

2016-01-01

Presented is a guided inquiry activity designed to be conducted with prenursing students using an analogous system to help develop a conceptual understanding of factors impacting enzyme kinetics and the various types of enzyme inhibition. Pre- and postconceptual understanding evaluations and effectiveness of implementation surveys were given to…

Interaction of Carthamus tinctorius lignan arctigenin with the binding site of tryptophan-degrading enzyme indoleamine 2,3-dioxygenase☆

PubMed Central

Temml, Veronika; Kuehnl, Susanne; Schuster, Daniela; Schwaiger, Stefan; Stuppner, Hermann; Fuchs, Dietmar

2013-01-01

Mediterranean Carthamus tinctorius (Safflower) is used for treatment of inflammatory conditions and neuropsychiatric disorders. Recently C. tinctorius lignans arctigenin and trachelogenin but not matairesinol were described to interfere with the activity of tryptophan-degrading enzyme indoleamine 2,3-dioxygenase (IDO) in peripheral blood mononuclear cells in vitro. We examined a potential direct influence of compounds on IDO enzyme activity applying computational calculations based on 3D geometry of the compounds. The interaction pattern analysis and force field-based minimization was performed within LigandScout 3.03, the docking simulation with MOE 2011.10 using the X-ray crystal structure of IDO. Results confirm the possibility of an intense interaction of arctigenin and trachelogenin with the binding site of the enzyme, while matairesinol had no such effect. PMID:24251110

In Silico Identification of Bioremediation Potential: Carbamazepine and Other Recalcitrant Personal Care Products.

PubMed

Aukema, Kelly G; Escalante, Diego E; Maltby, Meghan M; Bera, Asim K; Aksan, Alptekin; Wackett, Lawrence P

2017-01-17

Emerging contaminants are principally personal care products not readily removed by conventional wastewater treatment and, with an increasing reliance on water recycling, become disseminated in drinking water supplies. Carbamazepine, a widely used neuroactive pharmaceutical, increasingly escapes wastewater treatment and is found in potable water. In this study, a mechanism is proposed by which carbamazepine resists biodegradation, and a previously unknown microbial biodegradation was predicted computationally. The prediction identified biphenyl dioxygenase from Paraburkholderia xenovorans LB400 as the best candidate enzyme for metabolizing carbamazepine. The rate of degradation described here is 40 times greater than the best reported rates. The metabolites cis-10,11-dihydroxy-10,11-dihydrocarbamazepine and cis-2,3-dihydroxy-2,3-dihydrocarbamazepine were demonstrated with the native organism and a recombinant host. The metabolites are considered nonharmful and mitigate the generation of carcinogenic acridine products known to form when advanced oxidation methods are used in water treatment. Other recalcitrant personal care products were subjected to prediction by the Pathway Prediction System and tested experimentally with P. xenovorans LB400. It was shown to biodegrade structurally diverse compounds. Predictions indicated hydrolase or oxygenase enzymes catalyzed the initial reactions. This study highlights the potential for using the growing body of enzyme-structural and genomic information with computational methods to rapidly identify enzymes and microorganisms that biodegrade emerging contaminants.

Protein Design for Pathway Engineering

PubMed Central

Eriksen, Dawn T.; Lian, Jiazhang; Zhao, Huimin

2013-01-01

Design and construction of biochemical pathways has increased the complexity of biosynthetically-produced compounds when compared to single enzyme biocatalysis. However, the coordination of multiple enzymes can introduce a complicated set of obstacles to overcome in order to achieve a high titer and yield of the desired compound. Metabolic engineering has made great strides in developing tools to optimize the flux through a target pathway, but the inherent characteristics of a particular enzyme within the pathway can still limit the productivity. Thus, judicious protein design is critical for metabolic and pathway engineering. This review will describe various strategies and examples of applying protein design to pathway engineering to optimize the flux through the pathway. The proteins can be engineered for altered substrate specificity/selectivity, increased catalytic activity, reduced mass transfer limitations through specific protein localization, and reduced substrate/product inhibition. Protein engineering can also be expanded to design biosensors to enable high through-put screening and to customize cell signaling networks. These strategies have successfully engineered pathways for significantly increased productivity of the desired product or in the production of novel compounds. PMID:23558037

Protein design for pathway engineering.

PubMed

Eriksen, Dawn T; Lian, Jiazhang; Zhao, Huimin

2014-02-01

Design and construction of biochemical pathways has increased the complexity of biosynthetically-produced compounds when compared to single enzyme biocatalysis. However, the coordination of multiple enzymes can introduce a complicated set of obstacles to overcome in order to achieve a high titer and yield of the desired compound. Metabolic engineering has made great strides in developing tools to optimize the flux through a target pathway, but the inherent characteristics of a particular enzyme within the pathway can still limit the productivity. Thus, judicious protein design is critical for metabolic and pathway engineering. This review will describe various strategies and examples of applying protein design to pathway engineering to optimize the flux through the pathway. The proteins can be engineered for altered substrate specificity/selectivity, increased catalytic activity, reduced mass transfer limitations through specific protein localization, and reduced substrate/product inhibition. Protein engineering can also be expanded to design biosensors to enable high through-put screening and to customize cell signaling networks. These strategies have successfully engineered pathways for significantly increased productivity of the desired product or in the production of novel compounds. Copyright © 2013 Elsevier Inc. All rights reserved.

Conservation of Dynamics Associated with Biological Function in an Enzyme Superfamily.

PubMed

Narayanan, Chitra; Bernard, David N; Bafna, Khushboo; Gagné, Donald; Chennubhotla, Chakra S; Doucet, Nicolas; Agarwal, Pratul K

2018-03-06

Enzyme superfamily members that share common chemical and/or biological functions also share common features. While the role of structure is well characterized, the link between enzyme function and dynamics is not well understood. We present a systematic characterization of intrinsic dynamics of over 20 members of the pancreatic-type RNase superfamily, which share a common structural fold. This study is motivated by the fact that the range of chemical activity as well as molecular motions of RNase homologs spans over 10 5 folds. Dynamics was characterized using a combination of nuclear magnetic resonance experiments and computer simulations. Phylogenetic clustering led to the grouping of sequences into functionally distinct subfamilies. Detailed characterization of the diverse RNases showed conserved dynamical traits for enzymes within subfamilies. These results suggest that selective pressure for the conservation of dynamical behavior, among other factors, may be linked to the distinct chemical and biological functions in an enzyme superfamily. Copyright © 2018 Elsevier Ltd. All rights reserved.

Protein dynamics and enzyme catalysis: insights from simulations.

PubMed

McGeagh, John D; Ranaghan, Kara E; Mulholland, Adrian J

2011-08-01

The role of protein dynamics in enzyme catalysis is one of the most active and controversial areas in enzymology today. Some researchers claim that protein dynamics are at the heart of enzyme catalytic efficiency, while others state that dynamics make no significant contribution to catalysis. What is the biochemist - or student - to make of the ferocious arguments in this area? Protein dynamics are complex and fascinating, as molecular dynamics simulations and experiments have shown. The essential question is: do these complex motions have functional significance? In particular, how do they affect or relate to chemical reactions within enzymes, and how are chemical and conformational changes coupled together? Biomolecular simulations can analyse enzyme reactions and dynamics in atomic detail, beyond that achievable in experiments: accurate atomistic modelling has an essential part to play in clarifying these issues. This article is part of a Special Issue entitled: Protein Dynamics: Experimental and Computational Approaches. Copyright © 2010 Elsevier B.V. All rights reserved.

Computer-assisted engineering of the synthetic pathway for biodegradation of a toxic persistent pollutant.

PubMed

Kurumbang, Nagendra Prasad; Dvorak, Pavel; Bendl, Jaroslav; Brezovsky, Jan; Prokop, Zbynek; Damborsky, Jiri

2014-03-21

Anthropogenic halogenated compounds were unknown to nature until the industrial revolution, and microorganisms have not had sufficient time to evolve enzymes for their degradation. The lack of efficient enzymes and natural pathways can be addressed through a combination of protein and metabolic engineering. We have assembled a synthetic route for conversion of the highly toxic and recalcitrant 1,2,3-trichloropropane to glycerol in Escherichia coli, and used it for a systematic study of pathway bottlenecks. Optimal ratios of enzymes for the maximal production of glycerol, and minimal toxicity of metabolites were predicted using a mathematical model. The strains containing the expected optimal ratios of enzymes were constructed and characterized for their viability and degradation efficiency. Excellent agreement between predicted and experimental data was observed. The validated model was used to quantitatively describe the kinetic limitations of currently available enzyme variants and predict improvements required for further pathway optimization. This highlights the potential of forward engineering of microorganisms for the degradation of toxic anthropogenic compounds.

Integrating enzyme fermentation in lignocellulosic ethanol production: life-cycle assessment and techno-economic analysis.

PubMed

Olofsson, Johanna; Barta, Zsolt; Börjesson, Pål; Wallberg, Ola

2017-01-01

Cellulase enzymes have been reported to contribute with a significant share of the total costs and greenhouse gas emissions of lignocellulosic ethanol production today. A potential future alternative to purchasing enzymes from an off-site manufacturer is to integrate enzyme and ethanol production, using microorganisms and part of the lignocellulosic material as feedstock for enzymes. This study modelled two such integrated process designs for ethanol from logging residues from spruce production, and compared it to an off-site case based on existing data regarding purchased enzymes. Greenhouse gas emissions and primary energy balances were studied in a life-cycle assessment, and cost performance in a techno-economic analysis. The base case scenario suggests that greenhouse gas emissions per MJ of ethanol could be significantly lower in the integrated cases than in the off-site case. However, the difference between the integrated and off-site cases is reduced with alternative assumptions regarding enzyme dosage and the environmental impact of the purchased enzymes. The comparison of primary energy balances did not show any significant difference between the cases. The minimum ethanol selling price, to reach break-even costs, was from 0.568 to 0.622 EUR L -1 for the integrated cases, as compared to 0.581 EUR L -1 for the off-site case. An integrated process design could reduce greenhouse gas emissions from lignocellulose-based ethanol production, and the cost of an integrated process could be comparable to purchasing enzymes produced off-site. This study focused on the environmental and economic assessment of an integrated process, and in order to strengthen the comparison to the off-site case, more detailed and updated data regarding industrial off-site enzyme production are especially important.

Science Notes.

ERIC Educational Resources Information Center

School Science Review, 1990

1990-01-01

Included are 30 science activities that include computer monitoring, fieldwork, enzyme activity, pH, drugs, calorimeters, Raoult's Law, food content, solubility, electrochemistry, titration, physical properties of materials, gel filtration, energy, concepts in physics, and electricity. (KR)

Model based on GRID-derived descriptors for estimating CYP3A4 enzyme stability of potential drug candidates

NASA Astrophysics Data System (ADS)

Crivori, Patrizia; Zamora, Ismael; Speed, Bill; Orrenius, Christian; Poggesi, Italo

2004-03-01

A number of computational approaches are being proposed for an early optimization of ADME (absorption, distribution, metabolism and excretion) properties to increase the success rate in drug discovery. The present study describes the development of an in silico model able to estimate, from the three-dimensional structure of a molecule, the stability of a compound with respect to the human cytochrome P450 (CYP) 3A4 enzyme activity. Stability data were obtained by measuring the amount of unchanged compound remaining after a standardized incubation with human cDNA-expressed CYP3A4. The computational method transforms the three-dimensional molecular interaction fields (MIFs) generated from the molecular structure into descriptors (VolSurf and Almond procedures). The descriptors were correlated to the experimental metabolic stability classes by a partial least squares discriminant procedure. The model was trained using a set of 1800 compounds from the Pharmacia collection and was validated using two test sets: the first one including 825 compounds from the Pharmacia collection and the second one consisting of 20 known drugs. This model correctly predicted 75% of the first and 85% of the second test set and showed a precision above 86% to correctly select metabolically stable compounds. The model appears a valuable tool in the design of virtual libraries to bias the selection toward more stable compounds. Abbreviations: ADME - absorption, distribution, metabolism and excretion; CYP - cytochrome P450; MIFs - molecular interaction fields; HTS - high throughput screening; DDI - drug-drug interactions; 3D - three-dimensional; PCA - principal components analysis; CPCA - consensus principal components analysis; PLS - partial least squares; PLSD - partial least squares discriminant; GRIND - grid independent descriptors; GRID - software originally created and developed by Professor Peter Goodford.

Fundamental Reaction Pathway and Free Energy Profile for Butyrylcholinesterase-Catalyzed Hydrolysis of Heroin

PubMed Central

Qiao, Yan; Han, Keli; Zhan, Chang-Guo

2013-01-01

The pharmacological function of heroin requires an activation process which transforms heroin into 6-monoacetylmorphine (6-MAM) which is the most active form. The primary enzyme responsible for this activation process in human plasma is butyrylcholinesterase (BChE). The detailed reaction pathway of the activation process via BChE-catalyzed hydrolysis has been explored computationally, for the first time, in the present study by performing molecular dynamics simulation and first-principles quantum mechanical/molecular mechanical free energy calculations. It has been demonstrated that the whole reaction process includes acylation and deacylation stages. The acylation consists of two reaction steps, i.e. the nucleophilic attack on the carbonyl carbon of 3-acetyl group of heroin by the hydroxyl oxygen of Ser198 side chain and the dissociation of 6-MAM. The deacylation also consists of two reaction steps, i.e. the nucleophilic attack on the carbonyl carbon of the acyl-enzyme intermediate by a water molecule and the dissociation of the acetic acid from Ser198. The calculated free energy profile reveals that the second transition state (TS2) should be rate-determining. The structural analysis reveals that the oxyanion hole of BChE plays an important role in the stabilization of the rate-determining transition state TS2. The free energy barrier (15.9±0.2 or 16.1±0.2 kcal/mol) calculated for the rate-determining step is in good agreement with the experimentally-derived activation free energy (~16.2 kcal/mol), suggesting that the mechanistic insights obtained from the present computational study are reliable. The obtained structural and mechanistic insights could be valuable for use in future rational design of a novel therapeutic treatment of heroin abuse. PMID:23992153

Comparing sixteen scoring functions for predicting biological activities of ligands for protein targets.

PubMed

Xu, Weijun; Lucke, Andrew J; Fairlie, David P

2015-04-01

Accurately predicting relative binding affinities and biological potencies for ligands that interact with proteins remains a significant challenge for computational chemists. Most evaluations of docking and scoring algorithms have focused on enhancing ligand affinity for a protein by optimizing docking poses and enrichment factors during virtual screening. However, there is still relatively limited information on the accuracy of commercially available docking and scoring software programs for correctly predicting binding affinities and biological activities of structurally related inhibitors of different enzyme classes. Presented here is a comparative evaluation of eight molecular docking programs (Autodock Vina, Fitted, FlexX, Fred, Glide, GOLD, LibDock, MolDock) using sixteen docking and scoring functions to predict the rank-order activity of different ligand series for six pharmacologically important protein and enzyme targets (Factor Xa, Cdk2 kinase, Aurora A kinase, COX-2, pla2g2a, β Estrogen receptor). Use of Fitted gave an excellent correlation (Pearson 0.86, Spearman 0.91) between predicted and experimental binding only for Cdk2 kinase inhibitors. FlexX and GOLDScore produced good correlations (Pearson>0.6) for hydrophilic targets such as Factor Xa, Cdk2 kinase and Aurora A kinase. By contrast, pla2g2a and COX-2 emerged as difficult targets for scoring functions to predict ligand activities. Although possessing a high hydrophobicity in its binding site, β Estrogen receptor produced reasonable correlations using LibDock (Pearson 0.75, Spearman 0.68). These findings can assist medicinal chemists to better match scoring functions with ligand-target systems for hit-to-lead optimization using computer-aided drug design approaches. Copyright © 2015 Elsevier Inc. All rights reserved.

The complete conformational free energy landscape of β-xylose reveals a two-fold catalytic itinerary for β-xylanases.

PubMed

Iglesias-Fernández, Javier; Raich, Lluís; Ardèvol, Albert; Rovira, Carme

2015-02-01

Unraveling the conformational catalytic itinerary of glycoside hydrolases (GHs) is a growing topic of interest in glycobiology, with major impact in the design of GH inhibitors. β-xylanases are responsible for the hydrolysis of glycosidic bonds in β-xylans, a group of hemicelluloses of high biotechnological interest that are found in plant cell walls. The precise conformations followed by the substrate during catalysis in β-xylanases have not been unambiguously resolved, with three different pathways being proposed from structural analyses. In this work, we compute the conformational free energy landscape (FEL) of β-xylose to predict the most likely catalytic itineraries followed by β-xylanases. The calculations are performed by means of ab initio metadynamics, using the Cremer-Pople puckering coordinates as collective variables. The computed FEL supports only two of the previously proposed itineraries, 2 S O → [ 2,5 B] ǂ → 5 S 1 and 1 S 3 → [ 4 H 3 ] ǂ → 4 C 1 , which clearly appear in low energy regions of the FEL. Consistently, 2 S O and 1 S 3 are conformations preactivated for catalysis in terms of free energy/anomeric charge and bond distances. The results however exclude the O E → [ O S 2 ] ǂ → B 2,5 itinerary that has been recently proposed for a family 11 xylanase. Classical and ab initio QM/MM molecular dynamics simulations reveal that, in this case, the observed O E conformation has been enforced by enzyme mutation. These results add a word of caution on using modified enzymes to inform on catalytic conformational itineraries of glycoside hydrolases.

The complete conformational free energy landscape of β-xylose reveals a two-fold catalytic itinerary for β-xylanases† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c4sc02240h Click here for additional data file.

PubMed Central

Iglesias-Fernández, Javier; Raich, Lluís; Ardèvol, Albert

2015-01-01

Unraveling the conformational catalytic itinerary of glycoside hydrolases (GHs) is a growing topic of interest in glycobiology, with major impact in the design of GH inhibitors. β-xylanases are responsible for the hydrolysis of glycosidic bonds in β-xylans, a group of hemicelluloses of high biotechnological interest that are found in plant cell walls. The precise conformations followed by the substrate during catalysis in β-xylanases have not been unambiguously resolved, with three different pathways being proposed from structural analyses. In this work, we compute the conformational free energy landscape (FEL) of β-xylose to predict the most likely catalytic itineraries followed by β-xylanases. The calculations are performed by means of ab initio metadynamics, using the Cremer–Pople puckering coordinates as collective variables. The computed FEL supports only two of the previously proposed itineraries, 2SO → [2,5B]ǂ → 5S1 and 1S3 → [4H3]ǂ → 4C1, which clearly appear in low energy regions of the FEL. Consistently, 2SO and 1S3 are conformations preactivated for catalysis in terms of free energy/anomeric charge and bond distances. The results however exclude the OE → [OS2]ǂ → B2,5 itinerary that has been recently proposed for a family 11 xylanase. Classical and ab initio QM/MM molecular dynamics simulations reveal that, in this case, the observed OE conformation has been enforced by enzyme mutation. These results add a word of caution on using modified enzymes to inform on catalytic conformational itineraries of glycoside hydrolases. PMID:29560204

Flexible ligand docking using a genetic algorithm

NASA Astrophysics Data System (ADS)

Oshiro, C. M.; Kuntz, I. D.; Dixon, J. Scott

1995-04-01

Two computational techniques have been developed to explore the orientational and conformational space of a flexible ligand within an enzyme. Both methods use the Genetic Algorithm (GA) to generate conformationally flexible ligands in conjunction with algorithms from the DOCK suite of programs to characterize the receptor site. The methods are applied to three enzyme-ligand complexes: dihydrofolate reductase-methotrexate, thymidylate synthase-phenolpthalein and HIV protease-thioketal haloperidol. Conformations and orientations close to the crystallographically determined structures are obtained, as well as alternative structures with low energy. The potential for the GA method to screen a database of compounds is also examined. A collection of ligands is evaluated simultaneously, rather than docking the ligands individually into the enzyme.

Techno-economic analysis of lipase enzyme production from agro-industry waste with solid state fermentation method

NASA Astrophysics Data System (ADS)

Hidayatullah, I. M.; Arbianti, R.; Utami, T. S.; Suci, M.; Sahlan, M.; Wijanarko, A.; Gozan, M.; Hermansyah, H.

2018-03-01

Needs for this kind of catalyst derived from biological raw materials (biocatalysts) has increased along with development of products based on eco-friendly. To achieve the needs of biocatalyst (enzyme), large production is necessary. This study aimed to get the best conditions and design equipment to produce lipase enzyme based on solid state fermentation using SuperPro Designer v9.0. Several equipment such as Tray Bioreactor, Mixing Tank 1, Filter Press, centrifuge, Mixing Tank 2, and a dryer have been improved during the simulation. Economic analysis in the form of NPV, IRR, Payback Period, and the Benefit Cost Ratio was evaluated respectively. The result showed that production of 10 kg enzyme with NPV Rp112.796.147.423,00; IRR 54.20%; Payback Period 1.95 years; and Benefit Cost Ratio of 3.36 was more advantageous.

Design and analysis of synthetic carbon fixation pathways

PubMed Central

Bar-Even, Arren; Noor, Elad; Lewis, Nathan E.; Milo, Ron

2010-01-01

Carbon fixation is the process by which CO2 is incorporated into organic compounds. In modern agriculture in which water, light, and nutrients can be abundant, carbon fixation could become a significant growth-limiting factor. Hence, increasing the fixation rate is of major importance in the road toward sustainability in food and energy production. There have been recent attempts to improve the rate and specificity of Rubisco, the carboxylating enzyme operating in the Calvin–Benson cycle; however, they have achieved only limited success. Nature employs several alternative carbon fixation pathways, which prompted us to ask whether more efficient novel synthetic cycles could be devised. Using the entire repertoire of approximately 5,000 metabolic enzymes known to occur in nature, we computationally identified alternative carbon fixation pathways that combine existing metabolic building blocks from various organisms. We compared the natural and synthetic pathways based on physicochemical criteria that include kinetics, energetics, and topology. Our study suggests that some of the proposed synthetic pathways could have significant quantitative advantages over their natural counterparts, such as the overall kinetic rate. One such cycle, which is predicted to be two to three times faster than the Calvin–Benson cycle, employs the most effective carboxylating enzyme, phosphoenolpyruvate carboxylase, using the core of the naturally evolved C4 cycle. Although implementing such alternative cycles presents daunting challenges related to expression levels, activity, stability, localization, and regulation, we believe our findings suggest exciting avenues of exploration in the grand challenge of enhancing food and renewable fuel production via metabolic engineering and synthetic biology. PMID:20410460

Molecularly imprinted polymer nanoparticle-based assay (MINA): application for fumonisin B1 determination.

PubMed

Munawar, Hasim; Smolinska-Kempisty, Katarzyna; Cruz, Alvaro Garcia; Canfarotta, Francesco; Piletska, Elena; Karim, Khalku; Piletsky, Sergey A

2018-06-20

The enzyme-linked immunosorbent assay (ELISA) has been used as a standard tool for monitoring food and animal feed contamination from the carcinogenic fumonisin B1 (FB1). Unfortunately, ELISA is not always efficient due to the instability of the antibody and enzyme components in the immunoassay, the presence of natural enzyme inhibitors in the samples and the high levels of non-specific protein binding. Additionally, the production of antibodies for ELISA can be time-consuming and costly, due to the involvement of animals in the manufacturing process. To overcome these limiting factors, a molecularly imprinted nanoparticle based assay (MINA) has been developed, where the molecularly imprinted nanoparticles (nanoMIPs) replace the primary antibody used in a competitive ELISA. Herein, computational modelling was used to design the nanoMIPs by selecting monomers that specifically interact with FB1. The affinity of the monomers to FB1 was verified by measuring their binding in affinity chromatography experiments. The nanoMIPs were produced by solid phase synthesis and the results showed that nanoMIPs had a hydrodynamic diameter of around 249 ± 29 nm. The assay tested in model samples is highly selective and does not show cross-reactivity with other mycotoxins such as fumonisin B2 (FB2), aflatoxin B1 (AFB1), citrinin (CTT), zearalenone (ZEA), and deoxynivalenol (DON). The MINA allows the detection of FB1 in the concentration range of 10 pM-10 nM with a detection limit of 1.9 pM and a recovery of 108.13-113.76%.

Design and characterization of a prototype enzyme microreactor: quantification of immobilized transketolase kinetics.

PubMed

Matosevic, S; Lye, G J; Baganz, F

2010-01-01

In this work, we describe the design of an immobilized enzyme microreactor (IEMR) for use in transketolase (TK) bioconversion process characterization. The prototype microreactor is based on a 200-microm ID fused silica capillary for quantitative kinetic analysis. The concept is based on the reversible immobilization of His(6)-tagged enzymes via Ni-NTA linkage to surface derivatized silica. For the initial microreactor design, the mode of operation is a stop-flow analysis which promotes higher degrees of conversion. Kinetics for the immobilized TK-catalysed synthesis of L-erythrulose from substrates glycolaldehyde (GA) and hydroxypyruvate (HPA) were evaluated based on a Michaelis-Menten model. Results show that the TK kinetic parameters in the IEMR (V(max(app)) = 0.1 +/- 0.02 mmol min(-1), K(m(app)) = 26 +/- 4 mM) are comparable with those measured in free solution. Furthermore, the k(cat) for the microreactor of 4.1 x 10(5) s(-1) was close to the value for the bioconversion in free solution. This is attributed to the controlled orientation and monolayer surface coverage of the His(6)-immobilized TK. Furthermore, we show quantitative elution of the immobilized TK and the regeneration and reuse of the derivatized capillary over five cycles. The ability to quantify kinetic parameters of engineered enzymes at this scale has benefits for the rapid and parallel evaluation of evolved enzyme libraries for synthetic biology applications and for the generation of kinetic models to aid bioconversion process design and bioreactor selection as a more efficient alternative to previously established microwell-based systems for TK bioprocess characterization.

Empirical evaluation of a virtual laboratory approach to teach lactate dehydrogenase enzyme kinetics.

PubMed

Booth, Christine; Cheluvappa, Rajkumar; Bellinson, Zack; Maguire, Danni; Zimitat, Craig; Abraham, Joyce; Eri, Rajaraman

2016-06-01

Personalised instruction is increasingly recognised as crucial for efficacious learning today. Our seminal work delineates and elaborates on the principles, development and implementation of a specially-designed adaptive, virtual laboratory. We strived to teach laboratory skills associated with lactate dehydrogenase (LDH) enzyme kinetics to 2nd-year biochemistry students using our adaptive learning platform. Pertinent specific aims were to:(1)design/implement a web-based lesson to teach lactate dehydrogenase(LDH) enzyme kinetics to 2nd-year biochemistry students(2)determine its efficacious in improving students' comprehension of enzyme kinetics(3)assess their perception of its usefulness/manageability(vLab versus Conventional Tutorial). Our tools were designed using HTML5 technology. We hosted the program on an adaptive e-learning platform (AeLP). Provisions were made to interactively impart informed laboratory skills associated with measuring LDH enzyme kinetics. A series of e-learning methods were created. Tutorials were generated for interactive teaching and assessment. The learning outcomes herein were on par with that from a conventional classroom tutorial. Student feedback showed that the majority of students found the vLab learning experience "valuable"; and the vLab format/interface "well-designed". However, there were a few technical issues with the 1st roll-out of the platform. Our pioneering effort resulted in productive learning with the vLab, with parity with that from a conventional tutorial. Our contingent discussion emphasises not only the cornerstone advantages, but also the shortcomings of the AeLP method utilised. We conclude with an astute analysis of possible extensions and applications of our methodology.

Predicting Monoamine Oxidase Inhibitory Activity through Ligand-Based Models

PubMed Central

Vilar, Santiago; Ferino, Giulio; Quezada, Elias; Santana, Lourdes; Friedman, Carol

2013-01-01

The evolution of bio- and cheminformatics associated with the development of specialized software and increasing computer power has produced a great interest in theoretical in silico methods applied in drug rational design. These techniques apply the concept that “similar molecules have similar biological properties” that has been exploited in Medicinal Chemistry for years to design new molecules with desirable pharmacological profiles. Ligand-based methods are not dependent on receptor structural data and take into account two and three-dimensional molecular properties to assess similarity of new compounds in regards to the set of molecules with the biological property under study. Depending on the complexity of the calculation, there are different types of ligand-based methods, such as QSAR (Quantitative Structure-Activity Relationship) with 2D and 3D descriptors, CoMFA (Comparative Molecular Field Analysis) or pharmacophoric approaches. This work provides a description of a series of ligand-based models applied in the prediction of the inhibitory activity of monoamine oxidase (MAO) enzymes. The controlled regulation of the enzymes’ function through the use of MAO inhibitors is used as a treatment in many psychiatric and neurological disorders, such as depression, anxiety, Alzheimer’s and Parkinson’s disease. For this reason, multiple scaffolds, such as substituted coumarins, indolylmethylamine or pyridazine derivatives were synthesized and assayed toward MAO-A and MAO-B inhibition. Our intention is to focus on the description of ligand-based models to provide new insights in the relationship between the MAO inhibitory activity and the molecular structure of the different inhibitors, and further study enzyme selectivity and possible mechanisms of action. PMID:23231398

Flavourzyme, an Enzyme Preparation with Industrial Relevance: Automated Nine-Step Purification and Partial Characterization of Eight Enzymes.

PubMed

Merz, Michael; Eisele, Thomas; Berends, Pieter; Appel, Daniel; Rabe, Swen; Blank, Imre; Stressler, Timo; Fischer, Lutz

2015-06-17

Flavourzyme is sold as a peptidase preparation from Aspergillus oryzae. The enzyme preparation is widely and diversely used for protein hydrolysis in industrial and research applications. However, detailed information about the composition of this mixture is still missing due to the complexity. The present study identified eight key enzymes by mass spectrometry and partially by activity staining on native polyacrylamide gels or gel zymography. The eight enzymes identified were two aminopeptidases, two dipeptidyl peptidases, three endopeptidases, and one α-amylase from the A. oryzae strain ATCC 42149/RIB 40 (yellow koji mold). Various specific marker substrates for these Flavourzyme enzymes were ascertained. An automated, time-saving nine-step protocol for the purification of all eight enzymes within 7 h was designed. Finally, the purified Flavourzyme enzymes were biochemically characterized with regard to pH and temperature profiles and molecular sizes.

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.

Substrate specificity of bacterial DD-peptidases (penicillin-binding proteins).

PubMed

Pratt, R F

2008-07-01

The DD-peptidase enzymes (penicillin-binding proteins) catalyze the final transpeptidation reaction of bacterial cell wall (peptidoglycan) biosynthesis. Although there is now much structural information available about these enzymes, studies of their activity as enzymes lag. It is now established that representatives of two low-molecular-mass classes of DD-peptidases recognize elements of peptidoglycan structure and rapidly react with substrates and inhibitors incorporating these elements. No members of other DD-peptidase classes, including the high-molecular-mass enzymes, essential for bacterial growth, appear to interact strongly with any particular elements of peptidoglycan structure. Rational design of inhibitors for these enzymes is therefore challenging.

Mutagenesis of threonine to serine in the active site of Mycobacterium tuberculosis fructose-1,6-bisphosphatase (Class II) retains partial enzyme activity.

PubMed

Bondoc, Jasper Marc G; Wolf, Nina M; Ndichuck, Michael; Abad-Zapatero, Celerino; Movahedzadeh, Farahnaz

2017-09-01

The glpX gene encodes for the Class II fructose-1,6-bisphosphatase enzyme in Mycobacterium tuberculosis ( Mt ), an essential enzyme for pathogenesis. We have performed site directed mutagenesis to introduce two mutations at residue Thr84, T84A and T84S, to explore the binding affinity of the substrate and the catalytic mechanism. The T84A mutant fully abolishes enzyme activity while retaining substrate binding affinity. In contrast, the T84S mutant retains some activity having a 10 times reduction in V max and exhibited similar sensitivity to lithium when compared to the wildtype. Homology modeling using the Escherichia coli enzyme structure suggests that the replacement of the critical nucleophile OH - in the Thr84 residue of the wildtype of Mt FBPase by Ser84 results in subtle alterations of the position and orientation that reduce the catalytic efficiency. This mutant could be used to trap reaction intermediates, through crystallographic methods, facilitating the design of potent inhibitors via structure-based drug design.

Construction of a thermoresponsive magnetic porous polymer membrane enzyme reactor for glutaminase kinetics study.

PubMed

Zhao, Liping; Qiao, Juan; Moon, Meyong Hee; Qi, Li

2018-06-16

Fabrication of polymer membranes with nanopores and a confinement effect toward enzyme immobilization has been an enabling endeavor. In the work reported here, an enzyme reactor based on a thermoresponsive magnetic porous block copolymer membrane was designed and constructed. Reversible addition-fragmentation chain transfer polymerization was used to synthesize the block copolymer, poly(maleic anhydride-styrene-N-isopropylacrylamide), with poly(N-isopropylacrylamide) as the thermoresponsive moiety. The self-assembly property of the block copolymer was used for preparation of magnetic porous thin film matrices with iron oxide nanoparticles. By covalent bonding of glutaminase onto the surface of the membrane matrices and changing the temperature to tune the nanopore size, we observed enhanced enzymolysis efficiency due to the confinement effect. The apparent Michaelis-Menten constant and the maximum rate of the enzyme reactor were determined (K m = 32.3 mM, V max = 33.3 mM min -1 ) by a chiral ligand exchange capillary electrochromatography protocol with L-glutamine as the substrate. Compared with free glutaminase in solution, the proposed enzyme reactor exhibits higher enzymolysis efficiency, greater stability, and greater reusability. Furthermore, the enzyme reactor was applied for a glutaminase kinetics study. The tailored pore sizes and the thermoresponsive property of the block copolymer result in the designed porous membrane based enzyme reactor having great potential for high enzymolysis performance. Graphical abstract ᅟ.

Structure-based design and profiling of novel 17β-HSD14 inhibitors.

PubMed

Braun, Florian; Bertoletti, Nicole; Möller, Gabriele; Adamski, Jerzy; Frotscher, Martin; Guragossian, Nathalie; Madeira Gírio, Patrícia Alexandra; Le Borgne, Marc; Ettouati, Laurent; Falson, Pierre; Müller, Sebastian; Vollmer, Günther; Heine, Andreas; Klebe, Gerhard; Marchais-Oberwinkler, Sandrine

2018-05-22

The human enzyme 17β-hydroxysteroid dehydrogenase 14 (17β-HSD14) oxidizes the hydroxyl group at position 17 of estradiol and 5-androstenediol using NAD + as cofactor. However, the physiological role of the enzyme remains unclear. We recently described the first class of nonsteroidal inhibitors for this enzyme with compound 1 showing a high 17β-HSD14 inhibitory activity. Its crystal structure was used as starting point for a structure-based optimization in this study. The goal was to develop a promising chemical probe to further investigate the enzyme. The newly designed compounds revealed mostly very high inhibition of the enzyme and for seven of them the crystal structures of the corresponding inhibitor-enzyme complexes were resolved. The crystal structures disclosed that a small change in the substitution pattern of the compounds resulted in an alternative binding mode for one inhibitor. The profiling of a set of the most potent inhibitors identified 13 (K i  = 9 nM) with a good selectivity profile toward three 17β-HSDs and the estrogen receptor alpha. This inhibitor displayed no cytotoxicity, good solubility, and auspicious predicted bioavailability. Overall, 13 is a highly interesting 17β-HSD14 inhibitor, which might be used as chemical probe for further investigation of the target enzyme. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

SEE: structured representation of scientific evidence in the biomedical domain using Semantic Web techniques

PubMed Central

2014-01-01

Background Accounts of evidence are vital to evaluate and reproduce scientific findings and integrate data on an informed basis. Currently, such accounts are often inadequate, unstandardized and inaccessible for computational knowledge engineering even though computational technologies, among them those of the semantic web, are ever more employed to represent, disseminate and integrate biomedical data and knowledge. Results We present SEE (Semantic EvidencE), an RDF/OWL based approach for detailed representation of evidence in terms of the argumentative structure of the supporting background for claims even in complex settings. We derive design principles and identify minimal components for the representation of evidence. We specify the Reasoning and Discourse Ontology (RDO), an OWL representation of the model of scientific claims, their subjects, their provenance and their argumentative relations underlying the SEE approach. We demonstrate the application of SEE and illustrate its design patterns in a case study by providing an expressive account of the evidence for certain claims regarding the isolation of the enzyme glutamine synthetase. Conclusions SEE is suited to provide coherent and computationally accessible representations of evidence-related information such as the materials, methods, assumptions, reasoning and information sources used to establish a scientific finding by adopting a consistently claim-based perspective on scientific results and their evidence. SEE allows for extensible evidence representations, in which the level of detail can be adjusted and which can be extended as needed. It supports representation of arbitrary many consecutive layers of interpretation and attribution and different evaluations of the same data. SEE and its underlying model could be a valuable component in a variety of use cases that require careful representation or examination of evidence for data presented on the semantic web or in other formats. PMID:25093070

Automated Transition State Search and Its Application to Diverse Types of Organic Reactions.

PubMed

Jacobson, Leif D; Bochevarov, Art D; Watson, Mark A; Hughes, Thomas F; Rinaldo, David; Ehrlich, Stephan; Steinbrecher, Thomas B; Vaitheeswaran, S; Philipp, Dean M; Halls, Mathew D; Friesner, Richard A

2017-11-14

Transition state search is at the center of multiple types of computational chemical predictions related to mechanistic investigations, reactivity and regioselectivity predictions, and catalyst design. The process of finding transition states in practice is, however, a laborious multistep operation that requires significant user involvement. Here, we report a highly automated workflow designed to locate transition states for a given elementary reaction with minimal setup overhead. The only essential inputs required from the user are the structures of the separated reactants and products. The seamless workflow combining computational technologies from the fields of cheminformatics, molecular mechanics, and quantum chemistry automatically finds the most probable correspondence between the atoms in the reactants and the products, generates a transition state guess, launches a transition state search through a combined approach involving the relaxing string method and the quadratic synchronous transit, and finally validates the transition state via the analysis of the reactive chemical bonds and imaginary vibrational frequencies as well as by the intrinsic reaction coordinate method. Our approach does not target any specific reaction type, nor does it depend on training data; instead, it is meant to be of general applicability for a wide variety of reaction types. The workflow is highly flexible, permitting modifications such as a choice of accuracy, level of theory, basis set, or solvation treatment. Successfully located transition states can be used for setting up transition state guesses in related reactions, saving computational time and increasing the probability of success. The utility and performance of the method are demonstrated in applications to transition state searches in reactions typical for organic chemistry, medicinal chemistry, and homogeneous catalysis research. In particular, applications of our code to Michael additions, hydrogen abstractions, Diels-Alder cycloadditions, carbene insertions, and an enzyme reaction model involving a molybdenum complex are shown and discussed.