Remarkable activity enhancement of thermolysin mutants

Kidokoro, Shun‐ichi; Miki, Yōichiro; Endo, Kimiko; Wada, Akira; Nagao, Hiromasa; Miyake, T.; Aoyama, Atsushi; Yoneya, Takashi; Kai, Kenji; Ooe, Seigo

doi:10.1016/0014-5793(95)00537-j

Cited by 45 publications

(24 citation statements)

References 18 publications

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“…The active-site residues of enzymes are generally polar or charged, and are usually located in hydrophobic clefts [Fersht, 1999]. Stabilizing mutations in active site residues can reduce enzymatic activities [Beadle and Shoichet, 2002;Counago et al, 2008;Garcia et al, 2000;Kidokoro et al, 1995;Meiering et al, 1992;Mukaiyama et al, 2006;Nagatani et al, 2007;Schreiber et al, 1994, Shoichet et al, 1995Zhi et al, 1991]. Additionally, a stabilizing mutation increased the resistance of ribonuclease A to proteolysis [Markert et al, 2001], which, for example, would be an undesirable effect if it occurred in enzymes involved in cell signaling [Fink, 2005].…”

Section: Discussionmentioning

confidence: 99%

Performance of protein stability predictors

2010

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Stability is a fundamental property affecting function, activity, and regulation of biomolecules. Stability changes are often found for mutated proteins involved in diseases. Stability predictors computationally predict protein-stability changes caused by mutations. We performed a systematic analysis of 11 online stability predictors' performances. These predictors are CUPSAT, Dmutant, FoldX, I-Mutant2.0, two versions of IMutant3.0 (sequence and structure versions), MultiMutate, MUpro, SCide, Scpred, and SRide. As input, 1,784 single mutations found in 80 proteins were used, and these mutations did not include those used for training. The programs' performances were also assessed according to where the mutations were found in the proteins, that is, in secondary structures and on the surface or in the core of a protein, and according to protein structure type. The extents to which the mutations altered the occupied volumes at the residue sites and the charge interactions were also characterized. The predictions of all programs were in line with the experimental data. I-Mutant3.0 (utilizing structural information), Dmutant, and FoldX were the most reliable predictors. The stability-center predictors performed with similar accuracy. However, at best, the predictions were only moderately accurate ($60%) and significantly better tools would be needed for routine analysis of mutation effects. Hum Mutat 31:675-684,

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Section: Discussionmentioning

confidence: 99%

Performance of protein stability predictors

2010

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“…The lack of effects on thermal stability is not surprising, because it is known that the thermal stability of thermolysin-like proteases is mainly determined by local unfolding in a surface-located region in the N-terminal domain (Refs. 36, 43, 44; see also 45,46). None of the mutations described here are located in this surface region.…”

Section: Discussionmentioning

confidence: 99%

The Effects of Modifying the Surface Charge on the Catalytic Activity of a Thermolysin-like Protease

Kreij

Burg

Venema

et al. 2002

Journal of Biological Chemistry

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The impact of long range electrostatic interactions on catalysis in the thermolysin-like protease from Bacillus stearothermophilus was studied by analyzing the effects of inserting or removing charges on the protein surface. Various mutations were introduced at six different positions, and double-mutant cycle analysis was used to study the extent to which mutational effects were interdependent. The effects of single point mutations on the k cat /K m were non-additive, even in cases where the point mutations were located 10 Å or more from the active site Zn 2؉ and separated from each other by up to 25 Å. This shows that catalysis is affected by large electrostatic networks that involve major parts of the enzyme. The interdependence of mutations at positions as much as 25 Å apart in space also indicates that other effects, such as active site dynamics, play an important role in determining active site electrostatics. Several mutations yielded a significant increase in the activity, the most active (quadruple) mutant being almost four times as active as the wild type. In some cases the shape of the pH-activity profile was changed significantly. Remarkably, large changes in the pH-optimum were not observed.The acceleration of reaction rates by enzymes is one of the essential prerequisites for life as we know it, and the multitude and diversity of enzymes shows that it should be possible to design an enzyme that will catalyze almost any reaction under almost any set of conditions. To achieve a high rate of acceleration, enzymes rely on charged groups in their active site that stabilize the transition state or function as acid or base catalysts in the reaction. The kinetic parameters of enzymes therefore display a significant pH dependence, which is determined by the pK a values of the active site groups.Catalysis depends on intricate electrostatic interactions, which may be noticeable over distances that are large compared with short range of interactions such as hydrogen bonds and hydrophobic contacts. Thus, larger parts of an enzyme may be involved in optimizing its catalytic center than previously thought. The long range character of electrostatic effects is illustrated by a, very limited, number of examples in the literature, showing that changes in surface charge at locations as far as 15 Å from a catalytic center may affect enzyme activity (1, 2). Unfortunately, electrostatic interactions are hard to handle theoretically not only because of their long range character but also because of intrinsic theoretical difficulties. For example, most electrostatic models still use a single rigid protein structure and, at most, two dielectric constants to account for all the dynamics of the protein. This clearly is an oversimplification of reality (3).We have studied the contribution of long range electrostatic interactions to catalysis by analyzing the effects of a series of charge mutations scattered over a larger part of the surface of a thermolysin-like protease from Bacillus stearothermophilus (TLP-ste).

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“…It has been shown that local unfolding processes that render the protein susceptible towards autolysis are the rate-limiting steps in thermal inactivation [6,[15][16]. It has been proposed that these thermally induced local unfolding processes mainly involve surface located regions of the protein 16, 9, 141.…”

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Mutational Analysis of a Surface Area that is Critical for the Thermal Stability of Thermolysin‐Like Proteases

Veltman

Vriend²,

Hardy

et al. 1997

European Journal of Biochemistry

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Site-directed mutagenesis was used to assess the contribution of individual residues and a bound calcium in the 55 -69 region of the thermolysin-like protease of Bacillus stearothermophilus (TLP-ste) to thermal stability. The importance of the 55-69 region was reflected by finding that almost all mutations had drastic effects on stability. These effects (both stabilizing and destabilizing) were obtained by mutations affecting main chain flexibility, as well as by mutations affecting the interaction between the 55-69 region and the rest of the protease molecule. The calcium-dependency of stability could be largely abolished by mutating one of its ligands (Asp57 or Asp.59). In the case of the AspS7+Ser mutation, the accompanying loss in stability was modest compared with the effects of other destabilizing mutations or the effects of (combinations of) stabilizing mutations. The detailed knowledge of the stability-determining region of TLP-ste permits effective rational design of stabilizing mutations, which, presumably, are also useful for related TLP such as thermolysin. This is demonstrated by the successful design of a stabilizing salt bridge involving residues 65 and 11.Keywords: thermal stability; thermolysin; autolysis ; calcium binding; unfolding pathway.Bacillus thermolysin-li ke proteases (TLP) are metallo-endopeptidases consisting of 300-3 19 residues. These enzymes contain one zinc ion that is essential for catalysis and they bind a varying number of calcium ions for which it is known that they contribute to stability [I -21. The amino acid sequences of many TLP are known and the crystal structures of thermolysin (the TLP of Bacillus thermoproteolyticus; [3,41) and TLP-cer (the TLP of Bacillus cereus; [S]) have been determined. TLP consist of an N-terminal domain (residues 1 -154; thermolysin numbering) characterized by a predominance of P-pleated sheet and a C-terminal domain (residues 155-31 6) that is mainly a-helical [4, 51. TLP differ in thermal stability [6] and the structural determinants of these differences have been analyzed by several sitedirected mutagenesis studies [7-111. At elevated temperatures TLP are irreversibly inactivated as a result of autolysis. Considering the broad specificity of TLP [ 12, 131, conformational Enzyme. Thermolysin (EC 3.4.24.27).proteolytic attack [14]. It has been shown that local unfolding processes that render the protein susceptible towards autolysis are the rate-limiting steps in thermal inactivation [6,[15][16]. It has been proposed that these thermally induced local unfolding processes mainly involve surface located regions of the protein 16, 9, 141. Accordingly, it has been shown that the changes in the stability of TLP-ste is most easily effected by mutation of surface-located residues that are clustered in one particular region (residues 55-69) of the protein [9, 111 (and see Figs 1 and 2). The difference in stability between thermolysin (tso = 86.5 "C ; see below for definition of tS0) and the TLP of B. stemothermophilus CU21 (TLP-ste; t50 = 73.4"C) ...

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Remarkable activity enhancement of thermolysin mutants

Cited by 45 publications

References 18 publications

Performance of protein stability predictors

Performance of protein stability predictors

The Effects of Modifying the Surface Charge on the Catalytic Activity of a Thermolysin-like Protease

Mutational Analysis of a Surface Area that is Critical for the Thermal Stability of Thermolysin‐Like Proteases

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