Transition States: Substrate- Induced Conformational Transitions
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A Network of Molecular Switches Controls the Activation of the Two-Component Response Regulator Ntrc
ARTICLE Received 8 Aug 2014 | Accepted 26 Apr 2015 | Published 15 Jun 2015 DOI: 10.1038/ncomms8283 A network of molecular switches controls the activation of the two-component response regulator NtrC Dan K. Vanatta1, Diwakar Shukla1,2,3, Morgan Lawrenz1 & Vijay S. Pande1,2 Recent successes in simulating protein structure and folding dynamics have demonstrated the power of molecular dynamics to predict the long timescale behaviour of proteins. Here, we extend and improve these methods to predict molecular switches that characterize conformational change pathways between the active and inactive state of nitrogen regulatory protein C (NtrC). By employing unbiased Markov state model-based molecular dynamics simulations, we construct a dynamic picture of the activation pathways of this key bacterial signalling protein that is consistent with experimental observations and predicts new mutants that could be used for validation of the mechanism. Moreover, these results suggest a novel mechanistic paradigm for conformational switching. 1 Department of Chemistry, Stanford University, Stanford, California 94305, USA. 2 SIMBIOS NIH Center for Biomedical Computation, Stanford University, Stanford, California 94305,USA. 3 Department of Chemical and Bimolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illionios 61801, USA. Correspondence and requests for materials should be addressed to V.S.P. (email: [email protected]). NATURE COMMUNICATIONS | 6:7283 | DOI: 10.1038/ncomms8283 | www.nature.com/naturecommunications 1 & 2015 Macmillan Publishers Limited. All rights reserved. ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/ncomms8283 roteins involved in cellular signalling change their con- Results formation in response to changes in environment (input Simulations reveal molecular switches for NtrC activation. Psignal), such as ligand binding or chemical modification, MSMs for NtrC were built using snapshots along the simulated to control downstream cellular processes (output signal)1. -
Spring 2013 Lecture 23
CHM333 LECTURES 23: 3/25/13 SPRING 2013 Professor Christine Hrycyna LIPIDS III EFFECT OF CHOLESTEROL ON MEMBRANES: - Bulky rigid molecule - Moderates fluidity of membranes – both increases and decreases o Cholesterol in membranes DECREASES fluidity because it is rigid o Prevents crystallization (making solid) of fatty acyl side chains by fitting between them. Disrupts close packing of fatty acyl chains. Therefore, INCREASED fluidity BIOLOGICAL MEMBRANES CONTAIN PROTEINS AS WELL AS LIPIDS: - Proteins are 20-80% of cell membrane - Rest is lipid or carbohydrate; supramolecular assembly of lipid, protein and carbohydrate - Proteins are also distributed asymmetrically - TWO classes of Membrane Proteins: o Integral Membrane Proteins o Peripheral Membrane Proteins 178 CHM333 LECTURES 23: 3/25/13 SPRING 2013 Professor Christine Hrycyna - INTEGRAL MEMBRANE PROTEINS o Located WITHIN the lipid bilayer o Usually span the bilayer one or more times – called transmembrane (TM) proteins o Hydrophobic amino acids interact with fatty acid chains in the hydrophobic core of the membrane o Can be removed from the membrane with detergents like SDS – need to disrupt the hydrophobic interactions § Membrane Disruption Animation: o http://www.youtube.com/watch?v=AHT37pvcjc0 o Function: § Transporters – moving molecules into or out of cells or cell membranes § Receptors – transmitting signals from outside of the cell to the inside - β Barrel Integral Membrane Proteins § Barrel-shaped membrane protein that is made up of antiparallel β-strands with hydrophilic (interior) and hydrophobic (facing lipid tails). § So far found only in outer membranes of Gram-negative bacteria, cell wall of Gram-positive bacteria, and outer membranes of mitochondria and chloroplasts. 179 CHM333 LECTURES 23: 3/25/13 SPRING 2013 Professor Christine Hrycyna - α-Helical Membrane Proteins - Can cross the membrane once or many times and have multiple transmembrane segments. -
Site-Specific Tryptophan Labels Reveal Local Microsecond
molecules Article Site-Specific Tryptophan Labels Reveal Local Microsecond–Millisecond Motions of Dihydrofolate Reductase Morgan B. Vaughn 1,*, Chloe Biren 2, Qun Li 2, Ashwin Ragupathi 2 and R. Brian Dyer 2,* 1 Division of Natural Sciences, Oglethorpe University, Atlanta, GA 30319, USA 2 Department of Chemistry, Emory University, Atlanta, GA 30322, USA; [email protected] (C.B.); [email protected] (Q.L.); [email protected] (A.R.) * Correspondence: [email protected] (M.B.V.); [email protected] (R.B.D.); Tel.: +1-404-504-1214 (M.B.V.); +1-404-727-6637 (R.B.D.) Academic Editor: Rafik Karaman Received: 24 July 2020; Accepted: 21 August 2020; Published: 22 August 2020 Abstract: Many enzymes are known to change conformations during their catalytic cycle, but the role of these protein motions is not well understood. Escherichia coli dihydrofolate reductase (DHFR) is a small, flexible enzyme that is often used as a model system for understanding enzyme dynamics. Recently, native tryptophan fluorescence was used as a probe to study micro- to millisecond dynamics of DHFR. Yet, because DHFR has five native tryptophans, the origin of the observed conformational changes could not be assigned to a specific region within the enzyme. Here, we use DHFR mutants, each with a single tryptophan as a probe for temperature jump fluorescence spectroscopy, to further inform our understanding of DHFR dynamics. The equilibrium tryptophan fluorescence of the mutants shows that each tryptophan is in a different environment and that wild-type DHFR fluorescence is not a simple summation of all the individual tryptophan fluorescence signatures due to tryptophan–tryptophan interactions. -
Predicting Protein-Membrane Interfaces of Peripheral Membrane
bioRxiv preprint doi: https://doi.org/10.1101/2021.06.28.450157; this version posted June 29, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Predicting protein-membrane interfaces of pe- ripheral membrane proteins using ensemble machine learning Alexios Chatzigoulas1,2,* and Zoe Cournia1,* 1Biomedical Research Foundation, Academy of Athens, 4 Soranou Ephessiou, 11527 Athens, Greece, 2Depart- ment of Informatics and Telecommunications, National and Kapodistrian University of Athens, 15784 Athens, Greece *To whom correspondence should be addressed. Abstract Motivation: Abnormal protein-membrane attachment is involved in deregulated cellular pathways and in disease. Therefore, the possibility to modulate protein-membrane interactions represents a new promising therapeutic strategy for peripheral membrane proteins that have been considered so far undruggable. A major obstacle in this drug design strategy is that the membrane binding domains of peripheral membrane proteins are usually not known. The development of fast and efficient algorithms predicting the protein-membrane interface would shed light into the accessibility of membrane-protein interfaces by drug-like molecules. Results: Herein, we describe an ensemble machine learning methodology and algorithm for predicting membrane-penetrating residues. We utilize available experimental data in the literature for training 21 machine learning classifiers and a voting classifier. Evaluation of the ensemble classifier accuracy pro- duced a macro-averaged F1 score = 0.92 and an MCC = 0.84 for predicting correctly membrane-pen- etrating residues on unknown proteins of an independent test set. -
Effect of Enzyme/Substrate Ratio on the Antioxidant Properties of Hydrolysed African Yam Bean
African Journal of Biotechnology Vol. 11(50), pp. 11086-11091, 21 June, 2012 Available online at http://www.academicjournals.org/AJB DOI: 10.5897/AJB11.2271 ISSN 1684–5315 ©2012 Academic Journals Full Length Research Paper Effect of enzyme/substrate ratio on the antioxidant properties of hydrolysed African yam bean Fasasi Olufunmilayo*, Oyebode Esther and Fagbamila Oluwatoyin Department of Food Science and Technology, P. M. B. 704, Federal University of Technology, Akure, Nigeria. Accepted 8 June, 2012 The use of natural antioxidant as compared with synthetic antioxidant in food processing is a growing trend as consumers prefer natural to synthetic antioxidant mainly on emotional ground. This study investigates the antioxidant activity of hydrolysed African yam bean (Sphenostylis sternocarpa) which is regarded as one of the neglected underutilized species (NUS) of crop in Africa and Nigeria especially to improve food security and boost the economic importance of the crop. The antioxidant properties of African yam bean hydrolysates (AYH) produced at different enzyme to substrate (E/S) ratios of 1: 100 and 3: 100 (W/V) using pepsin (pH 2.0, 37°C) were studied. 2, 2-Diphenyl-1-picryl-hydrazyl (DPPH) radical scavenging activity of the hydrolysates was significantly influenced by the E\S ratio as DPPH radical scavenging activity ranged from 56.1 to 75.8% in AYH (1: 100) and 33.3 to 58.8% in AYH (3:100) with 1000 µg/ml having the highest DPPH radical scavenging activity. AYH (1:100) and AYH (3:100) had higher reducing activities of 0.42 and 0.23, respectively at a concentration of 1000 µg/ml. -
Regulation of Energy Substrate Metabolism in Endurance Exercise
International Journal of Environmental Research and Public Health Review Regulation of Energy Substrate Metabolism in Endurance Exercise Abdullah F. Alghannam 1,* , Mazen M. Ghaith 2 and Maha H. Alhussain 3 1 Lifestyle and Health Research Center, Health Sciences Research Center, Princess Nourah bInt. Abdulrahman University, Riyadh 84428, Saudi Arabia 2 Faculty of Applied Medical Sciences, Laboratory Medicine Department, Umm Al-Qura University, Al Abdeyah, Makkah 7607, Saudi Arabia; [email protected] 3 Department of Food Science and Nutrition, College of Food and Agriculture Sciences, King Saud University, Riyadh 11451, Saudi Arabia; [email protected] * Correspondence: [email protected] Abstract: The human body requires energy to function. Adenosine triphosphate (ATP) is the cellular currency for energy-requiring processes including mechanical work (i.e., exercise). ATP used by the cells is ultimately derived from the catabolism of energy substrate molecules—carbohydrates, fat, and protein. In prolonged moderate to high-intensity exercise, there is a delicate interplay between carbohydrate and fat metabolism, and this bioenergetic process is tightly regulated by numerous physiological, nutritional, and environmental factors such as exercise intensity and du- ration, body mass and feeding state. Carbohydrate metabolism is of critical importance during prolonged endurance-type exercise, reflecting the physiological need to regulate glucose homeostasis, assuring optimal glycogen storage, proper muscle fuelling, and delaying the onset of fatigue. Fat metabolism represents a sustainable source of energy to meet energy demands and preserve the ‘limited’ carbohydrate stores. Coordinated neural, hormonal and circulatory events occur during prolonged endurance-type exercise, facilitating the delivery of fatty acids from adipose tissue to the Citation: Alghannam, A.F.; Ghaith, working muscle for oxidation. -
Conformational Proofreading: the Impact of Conformational
Conformational Proofreading: The Impact of Conformational Changes on the Specificity of Molecular Recognition Yonatan Savir1 and Tsvi Tlusty1,* 1Department of Physics of Complex Systems, the Weizmann Institute of Science, Rehovot, Israel, 76100 *Corresponding author. E-mail: [email protected] Abstract To perform recognition, molecules must locate and specifically bind their targets within a noisy biochemical environment with many look-alikes. Molecular recognition processes, especially the induced-fit mechanism, are known to involve conformational changes. This arises a basic question: does molecular recognition gain any advantage by such conformational changes? By introducing a simple statistical-mechanics approach, we study the effect of conformation and flexibility on the quality of recognition processes. Our model relates specificity to the conformation of the participant molecules and thus suggests a possible answer: Optimal specificity is achieved when the ligand is slightly off target, that is a conformational mismatch between the ligand and its main target improves the selectivity of the process. This indicates that deformations upon binding serve as a conformational proofreading mechanism, which may be selected for via evolution. Introduction Practically all biological systems rely on the ability of bio-molecules to specifically recognize each other. Examples are antibodies targeting antigens, regulatory proteins binding DNA and enzymes catalyzing their substrates. These and other molecular recognizers must locate and preferentially interact with their specific targets among a vast variety of molecules that are often structurally similar. This task is further complicated by the inherent noise in the biochemical environment, whose magnitude is comparable with that of the non- covalent binding interactions [1-3]. -
Spring 2013 Lecture 13-14
CHM333 LECTURE 13 – 14: 2/13 – 15/13 SPRING 2013 Professor Christine Hrycyna INTRODUCTION TO ENZYMES • Enzymes are usually proteins (some RNA) • In general, names end with suffix “ase” • Enzymes are catalysts – increase the rate of a reaction – not consumed by the reaction – act repeatedly to increase the rate of reactions – Enzymes are often very “specific” – promote only 1 particular reaction – Reactants also called “substrates” of enzyme catalyst rate enhancement non-enzymatic (Pd) 102-104 fold enzymatic up to 1020 fold • How much is 1020 fold? catalyst time for reaction yes 1 second no 3 x 1012 years • 3 x 1012 years is 500 times the age of the earth! Carbonic Anhydrase Tissues ! + CO2 +H2O HCO3− +H "Lungs and Kidney 107 rate enhancement Facilitates the transfer of carbon dioxide from tissues to blood and from blood to alveolar air Many enzyme names end in –ase 89 CHM333 LECTURE 13 – 14: 2/13 – 15/13 SPRING 2013 Professor Christine Hrycyna Why Enzymes? • Accelerate and control the rates of vitally important biochemical reactions • Greater reaction specificity • Milder reaction conditions • Capacity for regulation • Enzymes are the agents of metabolic function. • Metabolites have many potential pathways • Enzymes make the desired one most favorable • Enzymes are necessary for life to exist – otherwise reactions would occur too slowly for a metabolizing organis • Enzymes DO NOT change the equilibrium constant of a reaction (accelerates the rates of the forward and reverse reactions equally) • Enzymes DO NOT alter the standard free energy change, (ΔG°) of a reaction 1. ΔG° = amount of energy consumed or liberated in the reaction 2. -
M.Sc. [Botany] 346 13
cover page as mentioned below: below: mentioned Youas arepage instructedcover the to updateupdate to the coverinstructed pageare asYou mentioned below: Increase the font size of the Course Name. Name. 1. IncreaseCourse the theof fontsize sizefont ofthe the CourseIncrease 1. Name. use the following as a header in the Cover Page. Page. Cover 2. the usein the followingheader a as as a headerfollowing the inuse the 2. Cover Page. ALAGAPPAUNIVERSITY UNIVERSITYALAGAPPA [Accredited with ’A+’ Grade by NAAC (CGPA:3.64) in the Third Cycle Cycle Third the in (CGPA:3.64) [AccreditedNAAC by withGrade ’A+’’A+’ Gradewith by NAAC[Accredited (CGPA:3.64) in the Third Cycle and Graded as Category–I University by MHRD-UGC] MHRD-UGC] by University and Category–I Graded as as Graded Category–I and University by MHRD-UGC] M.Sc. [Botany] 003 630 – KARAIKUDIKARAIKUDI – 630 003 346 13 EDUCATION DIRECTORATEDISTANCE OF OF DISTANCEDIRECTORATE EDUCATION BIOLOGICAL TECHNIQUES IN BOTANY I - Semester BOTANY IN TECHNIQUES BIOLOGICAL M.Sc. [Botany] 346 13 cover page as mentioned below: below: mentioned Youas arepage instructedcover the to updateupdate to the coverinstructed pageare asYou mentioned below: Increase the font size of the Course Name. Name. 1. IncreaseCourse the theof fontsize sizefont ofthe the CourseIncrease 1. Name. use the following as a header in the Cover Page. Page. Cover 2. the usein the followingheader a as as a headerfollowing the inuse the 2. Cover Page. ALAGAPPAUNIVERSITY UNIVERSITYALAGAPPA [Accredited with ’A+’ Grade by NAAC (CGPA:3.64) in the Third Cycle Cycle Third the in (CGPA:3.64) [AccreditedNAAC by withGrade ’A+’’A+’ Gradewith by NAAC[Accredited (CGPA:3.64) in the Third Cycle and Graded as Category–I University by MHRD-UGC] MHRD-UGC] by University and Category–I Graded as as Graded Category–I and University by MHRD-UGC] M.Sc. -
Swiveling Domain Mechanism in Pyruvate Phosphate Dikinase†,‡ Kap Lim,§ Randy J
Biochemistry 2007, 46, 14845-14853 14845 Swiveling Domain Mechanism in Pyruvate Phosphate Dikinase†,‡ Kap Lim,§ Randy J. Read,| Celia C. H. Chen,§ Aleksandra Tempczyk,§ Min Wei,⊥ Dongmei Ye,⊥ Chun Wu,⊥ Debra Dunaway-Mariano,⊥ and Osnat Herzberg*,§ Center for AdVanced Research in Biotechnology, UniVersity of Maryland Biotechnology Institute, RockVille, Maryland 20850, Department of Haematology, Cambridge Institute for Medical Research, UniVersity of Cambridge, Cambridge, United Kingdom, and Department of Chemistry, UniVersity of New Mexico, Albuquerque, New Mexico ReceiVed September 10, 2007; ReVised Manuscript ReceiVed October 17, 2007 ABSTRACT: Pyruvate phosphate dikinase (PPDK) catalyzes the reversible conversion of phosphoenolpyruvate (PEP), AMP, and Pi to pyruvate and ATP. The enzyme contains two remotely located reaction centers: the nucleotide partial reaction takes place at the N-terminal domain, and the PEP/pyruvate partial reaction takes place at the C-terminal domain. A central domain, tethered to the N- and C-terminal domains by two closely associated linkers, contains a phosphorylatable histidine residue (His455). The molecular architecture suggests a swiveling domain mechanism that shuttles a phosphoryl group between the two reaction centers. In an early structure of PPDK from Clostridium symbiosum, the His445-containing domain (His domain) was positioned close to the nucleotide binding domain and did not contact the PEP/pyruvate- binding domain. Here, we present the crystal structure of a second conformational state of C. symbiosum PPDK with the His domain adjacent to the PEP-binding domain. The structure was obtained by producing a three-residue mutant protein (R219E/E271R/S262D) that introduces repulsion between the His and nucleotide-binding domains but preserves viable interactions with the PEP/pyruvate-binding domain. -
Single-Substrate Enzyme Kinetics: the Quasi-Steady-State Approximation and Beyond
Single-substrate Enzyme Kinetics: The Quasi-steady-state Approximation and Beyond Sharmistha Dhatt# and Kamal Bhattacharyya* Department of Chemistry, University of Calcutta, Kolkata 700 009, India Abstract We analyze the standard model of enzyme-catalyzed reactions at various substrate-enzyme ratios by adopting a different scaling scheme. The regions of validity of the quasi-steady-state approximation are noted. Certain prevalent conditions are checked and compared against the actual findings. Efficacies of a few other measures are highlighted. Some recent observations are rationalized, particularly at moderate and high enzyme concentrations. Keywords: Michaelis-Menten kinetics, Quasi-steady state approximation, Padé approximants #[email protected] *[email protected] (Corresponding author) 0 1. Introduction The kinetics of enzyme-catalyzed reactions is usually modeled by a set of coupled differential equations, exact solutions of which are not obtainable in closed forms. However, in view of the importance of such reactions involving biochemical systems, simplifying assumptions are often made. One celebrated result of such endeavors is the standard Michaelis– Menten (MM) form, based on the quasi-steady-state approximation (QSSA). Crucial in this treatment is the assumption that, after a short transient, the concentration of the enzyme-substrate complex remains approximately constant. The impact of the MM form is still quite significant, even after about a century, as may be gazed from a very recent attention to the original work [1]. The two-step model is symbolized by the reaction scheme k1 k SE+⎯⎯←⎯⎯⎯⎯→ ES2 →+ PE. (1) k−1 On the basis of (1), various aspects of the QSSA have been studied from time to time. -
Enzyme Kinetics in This Exercise We Will Look at the Catalytic Behavior of Enzymes
1 Enzyme Kinetics In this exercise we will look at the catalytic behavior of enzymes. You will use Excel to answer the questions in the exercise section. At the end of this session, you must hand in answers to all the questions, along with print outs of any plots you created. Background Enzymes are the catalysts of biological systems and are extremely efficient and specific as catalysts. In fact, typically, an enzyme accelerates the rate of a reaction by factors of at least a million compared to the rate of the same reaction in the absence of the enzyme. Most biological reactions do not occur at perceptible rates in the absence of enzymes. One of the simplest biological reactions catalyzed by an enzyme is the hydration of CO2. The catalyst in this reaction is carbonic anhydrase. This reaction is part of the respiration cycle which expels CO2 from the body. Carbonic anhydrase is a highly efficient enzyme – each enzyme molecule 5 can catalyze the hydration of 10 CO2 molecules per second. Enzymes are highly specific. Typically a particular enzyme catalyzes only a single chemical reaction or a set of closely related chemical reactions. As is true of any catalyst, enzymes do not alter the equilibrium point of the reaction. This means that the enzyme accelerates the forward and reverse reaction by precisely the same factor. For example, consider the interconversion of A and B. A ↔ B (1) -4 -1 Suppose that in the absence of the enzyme the forward rate constant (kf) is 10 s and the -6 -1 reverse rate constant (kr) is 10 s .