Selection of the Optimal L-asparaginase II Against Acute Lymphoblastic Leukemia: An In Silico Approach

Abstract

Background L-asparaginase II (asnB), a periplasmic protein commercially extracted from E coli and Erwinia, is often used to treat acute lymphoblastic leukemia. L-asparaginase is an enzyme that converts L-asparagine to aspartic acid and ammonia. Cancer cells are dependent on asparagine from other sources for growth, and when these cells are deprived of asparagine by the action of the enzyme, the cancer cells selectively die. Objective Questions remain as to whether asnB from E coli and Erwinia is the best asparaginase as they have many side effects. asnBs with the lowest Michaelis constant (Km; most potent) and lowest immunogenicity are considered the most optimal enzymes. In this paper, we have attempted the development of a method to screen for optimal enzymes that are better than commercially available enzymes. Methods In this paper, the asnB sequence of E coli was used to search for homologous proteins in different bacterial and archaeal phyla, and a maximum likelihood phylogenetic tree was constructed. The sequences that are most distant from E coli and Erwinia were considered the best candidates in terms of immunogenicity and were chosen for further processing. The structures of these proteins were built by homology modeling, and asparagine was docked with these proteins to calculate the binding energy. Results asnBs from Streptomyces griseus, Streptomyces venezuelae, and Streptomyces collinus were found to have the highest binding energy (–5.3 kcal/mol, –5.2 kcal/mol, and –5.3 kcal/mol, respectively; higher than the E coli and Erwinia asnBs) and were predicted to have the lowest Kms, as we found that there is an inverse relationship between binding energy and Km. Besides predicting the most optimal asparaginase, this technique can also be used to predict the most optimal enzymes where the substrate is known and the structure of one of the homologs is solved. Conclusions We have devised an in silico method to predict the enzyme kinetics from a sequence of an enzyme along with being able to screen for optimal alternative asnBs against acute lymphoblastic leukemia.

Massive annotation of bacterial l-asparaginases reveals their puzzling distribution and frequent gene transfer events

“…Although the experimental screening techniques for a lead compound for AII-based drug candidates are still expensive and time-consuming, subsequent in silico studies may further narrow down the candidate proteins to a smaller set of best candidates for experimental verification. For example, molecular modeling and docking have proven suitable for studies involving screening for alternative l-asparaginase candidates and enzyme optimization 30 . Docking asparagine to the AII structures www.nature.com/scientificreports/ predicted by homology modeling was used in screening for l-asparaginase enzymes with reduced glutaminase activity 31 .…”

Efficacy and Toxicity of Different Forms of Asparaginases Against Acute Lymphoblastic Leukemia: A Review

“…We can expect an organism that is evolutionarily distant from Escherichia coli or Erwinia chrysanthemi to have different enzyme activity. Thus, we can expect to find better alternatives to commercially available asparaginases with higher activity than Escherichia coli and Erwinia chrysanthemi [31,32].…”

Peer Review of “Selection of the Optimal L-asparaginase II Against Acute Lymphoblastic Leukemia: An In Silico Approach”

“…General Comments Baral and coworkers [1] conducted a screening of L-Asparaginase II (asnB) for selection of asnB with increased asparagine depletion efficiency and decreased unwanted immune response for potentially improved efficacy of acute lymphocytic leukemia treatment in comparison to the commercially available asnBs. In their work, the asparagine hydrolyzation efficiency was assessed by the simulated asparagine binding energy, and the immunogenicity was assessed by the phylogenetic tree distance to the commercial asnB strains via molecular evolutionary genetics analysis.…”