Enzyme active sites: Identification and prediction of function using computational chemistry

Cellular and Biophysical Applications of Genetic Code Expansion

Despite their diverse functions, proteins are inherently constructed from a limited set of building blocks. These compositional constraints pose significant challenges to protein research and its practical applications. Strategically manipulating the cellular protein synthesis system to incorporate novel building blocks has emerged as a critical approach for overcoming these constraints in protein research and application. In the past two decades, the field of genetic code expansion (GCE) has achieved significant advancements, enabling the integration of numerous novel functionalities into proteins across a variety of organisms. This technological evolution has paved the way for the extensive application of genetic code expansion across multiple domains, including protein imaging, the introduction of probes for protein research, analysis of protein-protein interactions, spatiotemporal control of protein function, exploration of proteome changes induced by external stimuli, and the synthesis of proteins endowed with novel functions. In this comprehensive Review, we aim to provide an overview of cellular and biophysical applications that have employed GCE technology over the past two decades.

Identification and validation of fusidic acid and flufenamic acid as inhibitors of SARS-CoV-2 replication using DrugSolver CavitomiX

In this work, we present DrugSolver CavitomiX, a novel computational pipeline for drug repurposing and identifying ligands and inhibitors of target enzymes. The pipeline is based on cavity point clouds representing physico-chemical properties of the cavity induced solely by the protein. To test the pipeline's ability to identify inhibitors, we chose enzymes essential for SARS-CoV-2 replication as a test system. The active-site cavities of the viral enzymes main protease (M^pro) and papain-like protease (Pl^pro), as well as of the human transmembrane serine protease 2 (TMPRSS2), were selected as target cavities. Using active-site point-cloud comparisons, it was possible to identify two compounds-flufenamic acid and fusidic acid-which show strong inhibition of viral replication. The complexes from which fusidic acid and flufenamic acid were derived would not have been identified using classical sequence- and structure-based methods as they show very little structural (TM-score: 0.1 and 0.09, respectively) and very low sequence (~ 5%) identity to M^pro and TMPRSS2, respectively. Furthermore, a cavity-based off-target screening was performed using acetylcholinesterase (AChE) as an example. Using cavity comparisons, the human carboxylesterase was successfully identified, which is a described off-target for AChE inhibitors.

Enhancing the Catalytic Activity of Type II L-Asparaginase from Bacillus licheniformis through Semi-Rational Design

Low catalytic activity is a key factor limiting the widespread application of type II L-asparaginase (ASNase) in the food and pharmaceutical industries. In this study, smart libraries were constructed by semi-rational design to improve the catalytic activity of type II ASNase from Bacillus licheniformis. Mutants with greatly enhanced catalytic efficiency were screened by saturation mutations and combinatorial mutations. A quintuple mutant ILRAC was ultimately obtained with specific activity of 841.62 IU/mg and kcat/Km of 537.15 min−1·mM−1, which were 4.24-fold and 6.32-fold more than those of wild-type ASNase. The highest specific activity and kcat/Km were firstly reported in type II ASNase from Bacillus licheniformis. Additionally, enhanced pH stability and superior thermostability were both achieved in mutant ILRAC. Meanwhile, structural alignment and molecular dynamic simulation demonstrated that high structure stability and strong substrate binding were beneficial for the improved thermal stability and enzymatic activity of mutant ILRAC. This is the first time that enzymatic activity of type II ASNase from Bacillus licheniformis has been enhanced by the semi-rational approach, and results provide new insights into enzymatic modification of L-asparaginase for industrial applications.