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1.
Predicting proteome allocation, overflow metabolism, and metal requirements in a model acetogen.
Liu, JK, Lloyd, C, Al-Bassam, MM, Ebrahim, A, Kim, JN, Olson, C, Aksenov, A, Dorrestein, P, Zengler, K
PLoS computational biology. 2019;(3):e1006848
Abstract
The unique capability of acetogens to ferment a broad range of substrates renders them ideal candidates for the biotechnological production of commodity chemicals. In particular the ability to grow with H2:CO2 or syngas (a mixture of H2/CO/CO2) makes these microorganisms ideal chassis for sustainable bioproduction. However, advanced design strategies for acetogens are currently hampered by incomplete knowledge about their physiology and our inability to accurately predict phenotypes. Here we describe the reconstruction of a novel genome-scale model of metabolism and macromolecular synthesis (ME-model) to gain new insights into the biology of the model acetogen Clostridium ljungdahlii. The model represents the first ME-model of a Gram-positive bacterium and captures all major central metabolic, amino acid, nucleotide, lipid, major cofactors, and vitamin synthesis pathways as well as pathways to synthesis RNA and protein molecules necessary to catalyze these reactions, thus significantly broadens the scope and predictability. Use of the model revealed how protein allocation and media composition influence metabolic pathways and energy conservation in acetogens and accurately predicted secretion of multiple fermentation products. Predicting overflow metabolism is of particular interest since it enables new design strategies, e.g. the formation of glycerol, a novel product for C. ljungdahlii, thus broadening the metabolic capability for this model microbe. Furthermore, prediction and experimental validation of changing secretion rates based on different metal availability opens the window into fermentation optimization and provides new knowledge about the proteome utilization and carbon flux in acetogens.
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2.
Protein Solvent Interaction: Transition of Protein-solvent Interaction Concept from Basic Research into Solvent Manipulation of Chromatography.
Arakawa, T, Kita, Y
Current protein & peptide science. 2019;(1):34-39
Abstract
Previously, we have reviewed in this journal (Arakawa, T., Kita, Y., Curr. Protein Pept. Sci., 15, 608-620, 2014) the interaction of arginine with proteins and various applications of this solvent additive in the area of protein formulations and downstream processes. In this special issue, we expand the concept of protein-solvent interaction into the analysis of the effects of solvent additives on various column chromatography, including mixed-mode chromatography. Earlier in our research, we have studied the interactions of such a variety of solvent additives as sugars, salts, amino acids, polymers and organic solvents with a variety of proteins, which resulted in mechanistic understanding on their protein stabilization and precipitation effects, the latter known as Hofmeister series. While such a study was then a pure academic research, rapid development of genetic engineering technologies and resultant biotechnologies made it a valuable knowledge in fully utilizing solvent additives in manipulation of protein solution, including column chromatography.
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3.
Sudden cardiac death in a patient with LGI1 antibody-associated encephalitis.
Rizzi, R, Fisicaro, F, Zangrandi, A, Ghidoni, E, Baiardi, S, Ragazzi, M, Parchi, P
Seizure. 2019;:148-150
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4.
Effect of selective BET protein inhibitor apabetalone on cardiovascular outcomes in patients with acute coronary syndrome and diabetes: Rationale, design, and baseline characteristics of the BETonMACE trial.
Ray, KK, Nicholls, SJ, Ginsberg, HD, Johansson, JO, Kalantar-Zadeh, K, Kulikowski, E, Toth, PP, Wong, N, Cummings, JL, Sweeney, M, et al
American heart journal. 2019;:72-83
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Abstract
After an acute coronary syndrome (ACS), patients with diabetes remain at high risk for additional cardiovascular events despite use of current therapies. Bromodomain and extra-terminal (BET) proteins are epigenetic modulators of inflammation, thrombogenesis, and lipoprotein metabolism implicated in atherothrombosis. The BETonMACE trial tests the hypothesis that treatment with apabetalone, a selective BET protein inhibitor, will improve cardiovascular outcomes in patients with diabetes after an ACS. DESIGN Patients (n = 2425) with ACS in the preceding 7 to 90 days, with type 2 diabetes and low HDL cholesterol (≤40 mg/dl for men, ≤45 mg/dl for women), receiving intensive or maximum-tolerated therapy with atorvastatin or rosuvastatin, were assigned in double-blind fashion to receive apabetalone 100 mg orally twice daily or matching placebo. Baseline characteristics include female sex (25%), myocardial infarction as index ACS event (74%), coronary revascularization for index ACS (80%), treatment with dual anti-platelet therapy (87%) and renin-angiotensin system inhibitors (91%), median LDL cholesterol 65 mg per deciliter, and median HbA1c 7.3%. The primary efficacy measure is time to first occurrence of cardiovascular death, non-fatal myocardial infarction, or stroke. Assumptions include a primary event rate of 7% per annum in the placebo group and median follow-up of 1.5 years. Patients will be followed until at least 250 primary endpoint events have occurred, providing 80% power to detect a 30% reduction in the primary endpoint with apabetalone. SUMMARY BETonMACE will determine whether the addition of the selective BET protein inhibitor apabetalone to contemporary standard of care for ACS reduces cardiovascular morbidity and mortality in patients with type 2 diabetes. Results are expected in 2019.
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Structural Insights into Hearing Loss Genetics from Polarizable Protein Repacking.
Tollefson, MR, Litman, JM, Qi, G, O'Connell, CE, Wipfler, MJ, Marini, RJ, Bernabe, HV, Tollefson, WTA, Braun, TA, Casavant, TL, et al
Biophysical journal. 2019;(3):602-612
Abstract
Hearing loss is associated with ∼8100 mutations in 152 genes, and within the coding regions of these genes are over 60,000 missense variants. The majority of these variants are classified as "variants of uncertain significance" to reflect our inability to ascribe a phenotypic effect to the observed amino acid change. A promising source of pathogenicity information is biophysical simulation, although input protein structures often contain defects because of limitations in experimental data and/or only distant homology to a template. Here, we combine the polarizable atomic multipole optimized energetics for biomolecular applications force field, many-body optimization theory, and graphical processing unit acceleration to repack all deafness-associated proteins and thereby improve average structure MolProbity score from 2.2 to 1.0. We then used these optimized wild-type models to create over 60,000 structures for missense variants in the Deafness Variation Database, which are being incorporated into the Deafness Variation Database to inform deafness pathogenicity prediction. Finally, this work demonstrates that advanced polarizable atomic multipole force fields are efficient enough to repack the entire human proteome.
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Current Trends in Protein Engineering: Updates and Progress.
Sinha, R, Shukla, P
Current protein & peptide science. 2019;(5):398-407
Abstract
Proteins are one of the most important and resourceful biomolecules that find applications in health, industry, medicine, research, and biotechnology. Given its tremendous relevance, protein engineering has emerged as significant biotechnological intervention in this area. Strategic utilization of protein engineering methods and approaches has enabled better enzymatic properties, better stability, increased catalytic activity and most importantly, interesting and wide range applicability of proteins. In fact, the commercialization of engineered proteins have manifested in economically beneficial and viable solutions for industry and healthcare sector. Protein engineering has also evolved to become a powerful tool contributing significantly to the developments in both synthetic biology and metabolic engineering. The present review revisits the current trends in protein engineering approaches such as rational design, directed evolution, de novo design, computational approaches etc. and encompasses the recent progresses made in this field over the last few years. The review also throws light on advanced or futuristic protein engineering aspects, which are being explored for design and development of novel proteins with improved properties or advanced applications.
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How superoxide reductases and flavodiiron proteins combat oxidative stress in anaerobes.
Martins, MC, Romão, CV, Folgosa, F, Borges, PT, Frazão, C, Teixeira, M
Free radical biology & medicine. 2019;:36-60
Abstract
Microbial anaerobes are exposed in the natural environment and in their hosts, even if transiently, to fluctuating concentrations of oxygen and its derived reactive species, which pose a considerable threat to their anoxygenic lifestyle. To counteract these stressful conditions, they contain a multifaceted array of detoxifying systems that, in conjugation with cellular repairing mechanisms and in close crosstalk with metal homeostasis, allow them to survive in the presence of O2 and reactive oxygen species. Some of these systems are shared with aerobes, but two families of enzymes emerged more recently that, although not restricted to anaerobes, are predominant in anaerobic microbes. These are the iron-containing superoxide reductases, and the flavodiiron proteins, endowed with O2 and/or NO reductase activities, which are the subject of this Review. A detailed account of their physicochemical, physiological and molecular mechanisms will be presented, highlighting their unique properties in allowing survival of anaerobes in oxidative stress conditions, and comparing their properties with the most well-known detoxifying systems.
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Chemical and physical instabilities in manufacturing and storage of therapeutic proteins.
Krause, ME, Sahin, E
Current opinion in biotechnology. 2019;:159-167
Abstract
Development of a robust biologic drug product is accomplished by extensive formulation and process development screening studies; however, even in the most optimal formulation, a protein can undergo spontaneous degradation during manufacture, storage, and clinical use. Chemical changes to amino acid residues, such as oxidation of methionine or tryptophan, or changes in charge such as deamidation or carbonylation, can induce conformational changes in the overall protein structure, potentially leading to changes in physical - in addition to chemical - stability. Oxidation is often caused by light exposure or the presence of metal ions or peroxides. Asparagine deamidation is more likely to occur at higher pH and/or elevated temperature. Mechanical and interfacial stresses during manufacturing can lead to physical instabilities (i.e. various forms of aggregation). A well-defined manufacturing process and effective in-process controls are essential in minimizing chemical and physical instabilities, enabling robust production and distribution of a safe and efficacious drug product. In this work, the authors provide a review of developments in these areas over the past two years, with emphasis on manufacturability of therapeutically relevant proteins and protein-based drug products.
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9.
Better together: building protein oligomers naturally and by design.
Gwyther, REA, Jones, DD, Worthy, HL
Biochemical Society transactions. 2019;(6):1773-1780
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Abstract
Protein oligomers are more common in nature than monomers, with dimers being the most prevalent final structural state observed in known structures. From a biological perspective, this makes sense as it conserves vital molecular resources that may be wasted simply by generating larger single polypeptide units, and allows new features such as cooperativity to emerge. Taking inspiration from nature, protein designers and engineers are now building artificial oligomeric complexes using a variety of approaches to generate new and useful supramolecular protein structures. Oligomerisation is thus offering a new approach to sample structure and function space not accessible through simply tinkering with monomeric proteins.
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The Good, the Bad, and the Ugly: "HiPen", a New Dataset for Validating (S)QM/MM Free Energy Simulations.
Kearns, FL, Warrensford, L, Boresch, S, Woodcock, HL
Molecules (Basel, Switzerland). 2019;(4)
Abstract
Indirect (S)QM/MM free energy simulations (FES) are vital to efficiently incorporating sufficient sampling and accurate (QM) energetic evaluations when estimating free energies of practical/experimental interest. Connecting between levels of theory, i.e., calculating Δ A l o w → h i g h , remains to be the most challenging step within an indirect FES protocol. To improve calculations of Δ A l o w → h i g h , we must: (1) compare the performance of all FES methods currently available; and (2) compile and maintain datasets of Δ A l o w → h i g h calculated for a wide-variety of molecules so that future practitioners may replicate or improve upon the current state-of-the-art. Towards these two aims, we introduce a new dataset, "HiPen", which tabulates Δ A g a s M M → 3 o b (the free energy associated with switching from an M M to an S C C - D F T B molecular description using the 3ob parameter set in gas phase), calculated for 22 drug-like small molecules. We compare the calculation of this value using free energy perturbation, Bennett's acceptance ratio, Jarzynski's equation, and Crooks' equation. We also predict the reliability of each calculated Δ A g a s M M → 3 o b by evaluating several convergence criteria including sample size hysteresis, overlap statistics, and bias metric ( Π ). Within the total dataset, three distinct categories of molecules emerge: the "good" molecules, for which we can obtain converged Δ A g a s M M → 3 o b using Jarzynski's equation; "bad" molecules which require Crooks' equation to obtain a converged Δ A g a s M M → 3 o b ; and "ugly" molecules for which we cannot obtain reliably converged Δ A g a s M M → 3 o b with either Jarzynski's or Crooks' equations. We discuss, in depth, results from several example molecules in each of these categories and describe how dihedral discrepancies between levels of theory cause convergence failures even for these gas phase free energy simulations.