A combination of mutational and computational scanning guides the design of an artificial ligand-binding controlled lipase

Abstract

Allostery, i.e. the control of enzyme activity by a small molecule at a location distant from the enzyme’s active site, represents a mechanism essential for sustaining life. The rational design of allostery is a non-trivial task but can be achieved by fusion of a sensory domain, which responds to environmental stimuli with a change in its structure. Hereby, the site of domain fusion is difficult to predict. We here explore the possibility to rationally engineer allostery into the naturally not allosterically regulated Bacillus subtilis lipase A, by fusion of the citrate-binding sensor-domain of the CitA sensory-kinase of Klebsiella pneumoniae. The site of domain fusion was rationally determined based on whole-protein site-saturation mutagenesis data, complemented by computational evolutionary-coupling analyses. Functional assays, combined with biochemical and biophysical studies suggest a mechanism for control, similar but distinct to the one of the parent CitA protein, with citrate acting as an indirect modulator of Triton-X100 inhibition of the fusion protein. Our study demonstrates that the introduction of ligand-dependent regulatory control by domain fusion is surprisingly facile, suggesting that the catalytic mechanism of some enzymes may be evolutionary optimized in a way that it can easily be perturbed by small conformational changes.

The grease trap: uncovering the mechanism of the hydrophobic lid in Cutibacterium acnes lipase

“…Moreover, when they form crystallographic dimers, these interfaces are highly different from the CA lipase dimer (Figs. 1B, 2) (30)(31)(32)(33). The dimeric state of CA lipase contributes solubility and stability.…”

Combinatorial engineering of N-TIMP2 variants that selectively inhibit MMP9 and MMP14 function in the cell

“…While specificity prediction requires both positive design (i.e., stabilization of the desired complex) and negative design (i.e., destabilization of unwanted complexes), affinity prediction considers only positive design [ 10 , 20 ]. For instance, computationally saturated mutagenesis and similar classical approaches focus chiefly on single targets (namely, stabilization of the desired complex) and only allow for testing the effects of single mutations [ 1 , 3 , 9 , 21 , 22 ]. Predicting specificity by these methods is, therefore, time-consuming and laborious, as separate computations are required for all possible targets.…”

Structural homogeneity in microbial lipases.

“…At 30% sequences identity, only 22 unique presentative structures (Bacteria: 12; Eukaryota: 9; and Archaea: 1) of lipase have been found. In recent years, structural information and computational molecular modeling studies demonstrated their mechanistic properties [5,6]. The 3D structure of lipases usually have a common α/β hydrolase fold topology with mostly parallel β-sheets, flanked on both sides by α-helices [7].…”