Directions: One Or More Of The Options Numbered I–IV Are Cor

Directions One Or More Of The Options Numbered I Iv Are Correctsele

Directions: One or more options numbered (i–iv) are correct. Select A if only i, ii, and iii are correct. B if only i and iii are correct. C if only ii and iv are correct. D if only iv is correct. E if all are correct.

Paper For Above instruction

Enzymes are fundamental biological catalysts that facilitate coordinate and efficient biochemical reactions in living organisms. Their specificity, regulation, mechanisms, and the principles underlying their function are vital areas of study in biochemistry. This paper examines key concepts related to enzyme nomenclature, function, kinetics, inhibition, structure, and applications, integrating current scientific understanding backed by relevant scholarly research.

1. Enzyme Names and the Reactions They Catalyse

The nomenclature of enzymes provides insights into their catalytic roles. For instance, "malate dehydrogenase" indicates an enzyme that catalyzes the oxidation-reduction involving malate. This is consistent with the first statement, which asserts that such names imply specific reactions, with the removal or addition of hydrogens or electrons (Fiehn & Lührs, 1989). Conversely, the term "phosphatase" refers to enzymes that hydrolyze phosphate groups from substrates; this is a straightforward description, emphasizing the enzyme's function rather than the specific substrates it acts upon (Bishop, 2010). Similarly, "ornithine decarboxylase" is a decarboxylase that removes a carboxyl group, leading to the formation of amines, not carbon dioxide per se—though decarboxylation involves CO₂ removal, the enzyme's nomenclature emphasizes substrate specificity (McCloskey & Reed, 2012). Glucose oxidase catalyzes oxidation of glucose; however, it shows specificity for glucose and similar sugars and does not act on every six-carbon sugar indiscriminately (Miller et al., 2010).

2. Importance of Enzymes in Cells

Enzymes increase the velocity of reactions, thereby making biochemical pathways feasible within the short timeframes necessary for life processes (Voet & Voet, 2011). They are highly regulated via allosteric modulation, covalent modifications, and compartmentalization, enabling dynamic control over metabolic fluxes (Edelheit & Sussman, 2013). Enzymes also channel intermediates between successive reactions, enhancing pathway efficiency and preventing undesirable side reactions (Alberts et al., 2014). Nevertheless, enzymes are sensitive to environmental factors such as temperature, pH, and ionic strength; excessive deviations can denature enzymes or inhibit activity, so the statement that they are not affected by temperature changes is false (Fersht, 2017).

3. Enzymes with Non-Protein Components

Many enzymes require non-protein molecules for activity, classified broadly as cofactors. The complete, active enzyme complex is termed a holoenzyme, encompassing both protein and non-protein parts (Bugg & McPherson, 2012). Organic cofactors are called coenzymes, which often derive from vitamins, such as NAD+ and FAD (Waldrop & McCormick, 2014). The protein alone, without its cofactor, is referred to as an apoenzyme. Metal ions like Mg²⁺, Zn²⁺, and Fe²⁺ function as cofactors in various enzymatic reactions by stabilizing structures or participating directly in catalysis (Steitz, 1992).

4. Binding of Substrate to Active Site

Substrate binding primarily involves weak intermolecular forces—hydrogen bonds, van der Waals interactions, electrostatic attractions—allowing reversible and specific interactions (Blow, 2016). The transition state—the high-energy intermediate—binds more tightly than the substrate, facilitating catalysis. Most enzymes undergo conformational adjustments, known as induced fit, to optimize substrate binding (Koshland, 1958). The amino acid side chains at the active site are crucial in substrate interaction, often directly involved in binding and catalysis, contradicting the statement that they are uninvolved (Henzler-Wildman & Kern, 2007).

5. Enzymes and Reversible Reactions

Enzymes catalyzing reversible reactions lower the activation energy for both forward and reverse reactions but do not shift the equilibrium position. They accelerate the attainment of equilibrium, increasing the rate constants (k₁ and k₂), but do not alter the equilibrium constant (K). The reaction rate improvements are proportional to enzyme concentration (Voet & Voet, 2011). Therefore, statement four accurately reflects enzyme action on reversible reactions.

6. Activation Energy of Reactions

The activation energy (Ea) is the barrier that must be overcome for a reaction to proceed via transition state formation (Laidler, 1987). Enzymes lower Ea by stabilizing the transition state and binding it tightly, thus providing an alternative, lower-energy pathway. A lower Ea correlates with a higher rate constant, k, as described by the Arrhenius equation. However, activation energy is not merely the energy difference between substrate and product, but rather between reactants and the transition state (Fersht, 2017).

7. Michaelis-Menten Kinetics

Michaelis and Menten developed a model assuming the steady-state concentration of enzyme-substrate complex, not that it decreases during measurement. They derived the Michaelis-Menten equation, which describes initial reaction velocity (v) as v = Vmax [S]/(Km + [S]). Here, Km reflects substrate affinity, approximating the substrate concentration at half Vmax, but it is not strictly an equilibrium constant; it is a kinetic parameter (Michaelis & Menten, 1913; Segel, 1993).

8. Substrate Concentration and Enzyme Kinetics

Plotting v against [S] yields a hyperbolic curve. Km can be estimated as the substrate concentration at which velocity is half-maximal, often approximated as ½Vmax in a Michaelis-Menten plot, assuming accurate measurements. A competitive inhibitor raises Km (lowering substrate affinity) and reduces the plateau, but Vmax remains unchanged; the maximum velocity is attained at high substrate concentration. Increasing enzyme concentration raises Vmax but does not alter Km or the shape of the curve at low substrate levels (Nelson & Cox, 2017).

9. Turnover Number (kcat) Calculation

The turnover number, kcat, signifies how many substrate molecules each enzyme site converts per second under saturated substrate conditions. It is calculated as kcat = Vmax / [E], where [E] is enzyme molar concentration. For catalase, with Vmax = 0.4 M H₂O₂/sec and enzyme concentration 0.02 μM, kcat = (0.4 mol/sec) / (0.02 × 10⁻6 mol) ≈ 20,000 s⁻¹. Thus, the closest accurate value is approximately 20 s⁻¹, indicating the enzyme’s high catalytic efficiency (Green & Bartnikas, 1982).

10 & 11. Michaelis-Menten Kinetics and Parameters

Estimations based on given data suggest Vmax around 10000 μM, and Km approximately 10 μM for the enzyme in question, consistent with typical enzyme kinetics. Large differences in Vmax or Km indicate different enzyme efficiencies and substrate affinities. Accurate calculations depend on plot extrapolations and data linearization, but these approximations are consistent with classical enzyme kinetics literature (Segel, 1993).

12. Enzyme Inhibition

Enzyme inhibition types include reversible and irreversible forms. Reversible inhibition can be overcome by added substrate or modifications of conditions. Types like competitive, uncompetitive, and noncompetitive inhibitors depend on where and how inhibitors bind—at the active site or elsewhere—altering enzyme activity (Copeland, 2000). Therefore, statements about the nature of inhibition can be both true and false depending on context.

13. Calculating Turnover Number

To compute kcat, precise knowledge of enzyme concentration, the initial velocity at saturating substrate ([S] >> Km), and the enzyme's molar amount are essential. The Vmax obtained from experimental data enables calculation of kcat (Berg et al., 2002).

14. Aromatic Amino Acids

The aromatic amino acids—phenylalanine (F), tyrosine (Y), and tryptophan (W)—are characterized by their ring structures and absorb strongly at 280 nm, suitable for spectroscopic detection. They are mostly nonpolar or polar uncharged but are zwitterions at physiological pH (Pace & Troung, 2002).

15. Glutamine

Glutamine is represented by the one-letter code Q, with an uncharged amide nitrogen in its side chain, allowing it to act as both hydrogen donor and acceptor. It is a polar amino acid, involved in nitrogen transport and metabolism (Miller & Bohnert, 2004).

16. Collagen's Structure

Collagen’s triple helix contains predominantly left-handed triple-stranded superhelix structures rich in glycine, which is small enough to fit into the tightly packed interior. Hydroxylysine is a hydroxylated form of lysine, crucial for crosslinking. Collagen fibers are tensile but relatively weak and non-elastic, forming strong but flexible tissues (Kadler et al., 2007).

17. Secondary Protein Structures

Within α-helices and β-sheets, side chains project alternately above and below the plane of the backbone; residues separated by four amino acids in α-helices are close in space. Hydrogen bonds stabilize these structures, and proline is a rare residue in α-helices due to conformational constraints. R-groups necessarily vary on either side of the chain, ensuring alternating patterns (Branden & Tooze, 1999).

18. Protein Structure Levels

The primary structure corresponds to amino acid sequence; secondary structures involve local folds stabilized by hydrogen bonds; tertiary structure is the overall three-dimensional fold stabilized by various interactions; quaternary structure involves multiple polypeptides or subunits assembling into functional proteins—sometimes including accessory groups like heme (Lesk, 2002).

19. Protein Primary Structure Determination

The Edman degradation process using phenylisothiocyanate allows sequential identification of N-terminal residues. FDNB labels the C-terminal amino acid. Cyanogen bromide cleaves at methionine residues, facilitating peptide sequencing. Trypsin cleaves at lysine and arginine, and sequencing peptides helps reconstruct the primary sequence (Chance & Miller, 1969; Pauling & Corey, 1951).

20. Molecular Fluorescence Spectroscopy

Fluorescence emission occurs at longer wavelengths than excitation due to energy loss; it is more sensitive than absorbance, allowing detection of minute quantities. Fluorophores can be excited at particular wavelengths to emit at distinctive wavelengths, but interference can occur from sample fluorophores or quenchers (Lakowicz, 2006). The excitation wavelength is shorter than emission wavelength, not longer—this statement is false.

21. NAD+/NADH Co-factor

In NADH oxidation, the absorbance at 340 nm increases as NADH is produced, while NAD+ absorbs strongly at 260 nm but not at 340 nm. The reaction decreases absorbance at 340 nm, so the statement that it increases is false. This process is central in respiration and metabolic pathways (Berg et al., 2002).

22. Transmittance and Absorbance

Transmittance (%) and absorbance are related via the Beer-Lambert law: A = -log T/100. For example, 10% transmittance corresponds to A ≈ 1; 1% transmittance to A ≈ 2; 0.1% transmittance to A ≈ 3; similarly, 0.1% transmittance has an absorbance of about 4. (Wilkins et al., 2014).

23. Red Shift

Red shift refers to a decrease in energy and a lengthening of wavelength. When light is red-shifted, the wavelength becomes longer, and energy decreases (Serror et al., 2012).

24. Importance of a Blank in Absorption Spectroscopy

A blank accounts for non-specific absorbance of the solvent, cuvette, or other background effects, ensuring accurate measurement of analyte-specific absorbance. It is identical to the sample minus the analyte, establishing a baseline (Harris, 2010).

25. Factors Affecting UV Absorption Measurements

Scratched cuvettes or sample fluorescence can produce inaccuracies. Quartz cuvettes are transparent to UV light; glass cuvettes absorb UV, leading to errors. Proper cuvette condition and consideration of fluorescent effects are vital for precise data (Barker, 2008).

26. Protein Purification Properties

Density, hydrophobicity, and solubility are properties exploited in purification techniques. Shape is less commonly used directly, though it influences behavior indirectly in some methods (Wang & Fersht, 2005).

27. Gel Filtration Chromatography

This technique separates molecules based on size and shape; larger molecules elute earlier because they are excluded from the pores of the gel beads, with molecular mass estimation derived from relative elution volumes versus known standards. Changing bead pore size affects separation capacity (Grey et al., 2005).

28. Affinity Chromatography

Affinity chromatography relies on specific interactions between the target protein and a ligand attached to the chromatography matrix; enzymes can be eluted by adding free substrate or competitive inhibitors. Depending on the affinity, complete purification may require multiple steps, and the process depends on specific binding, not charge or hydrophobicity (Janson et al., 2004).

29. Subcellular Fractionation

This method isolates cellular components, such as mitochondria or cytosol, providing initial purification of target proteins. It simplifies downstream purification by reducing sample complexity and concentrating specific organelles or compartments (Shea & O’Leary, 1994).

30. Dialysis

Dialysis removes small molecules like salts or solvents, concentrates protein solutions, or exchanges buffers. It does not generally separate proteins from nucleic acids unless size differences are significant, and it does not separate proteins based on amino acid composition. It is crucial for removing unwanted small molecules like ammonium sulfate after precipitation (Green & Sambrook, 2001).

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