Response Monitoring of Acute Lymphoblastic Leukemia Patients Undergoing l‑Asparaginase Therapy: Successes and Challenges Associated with Clinical Sample Analysis in Plasmonic Sensing

Monitoring the response of patients undergoing chemotherapeutic treatments is of great importance to predict remission success, avoid adverse effects and thus, maximize the patients’ quality of life. In the case of leukemia patients treated with E. coli l-asparaginase, monitoring the immune response by the detection of specific antibodies to l-asparaginase in the serum of patients can prevent extended immune response to the drug. Here, we developed a surface plasmon resonance (SPR) biosensor to rapidly detect anti-asparaginase antibodies directly in patients’ sera, without requiring sample pretreatment or dilution. A direct assay with SPR sensing to detect anti-asparaginase antibodies exhibited a limit of detection of 500 pM and a high sensitivity range between 100 nM and 1 μM in pooled and undiluted human serum from a commercial source. While the SPR assay showed excellent reproducibility (12% RSD) in pooled serum, challenges were encountered upon analyzing clinical samples due to high sample-to-sample variability in color and turbidity and, in all likelihood, in composition. As a result, direct detection in clinical samples was unreliable due to factors that may generally affect assays based on plasmonic detection. Addition of a secondary detection step overcame sample variability due to bulk differences in patients’ sera. By those means, the SPR biosensor was successfully applied to the analysis of clinical samples from leukemia patients undergoing asparaginase treatments and the results agreed well with the standard ELISA assay. Monitoring antibodies against drugs is common such that this type of sensing scheme could serve to monitor a plethora of immune responses in sera of patients undergoing treatment

DNA sequencing electropherogram of the Tyr93 mutant library.

<p>The peak height is given in relative fluorescence units (RFU) and represents the signal intensity at each nucleotide, along the x axis. The identity of each nucleotide is automatically assigned (above each peak) when the signal is unequivocal, or is labelled ‘N’ when more than one nucleotide provides a statistically significant signal. The NDT degeneracy (25% each A/C/G/T; 33% A/G/T; T) is clearly visible.</p

Substrate-Specific Screening for Mutational Hotspots Using Biased Molecular Dynamics Simulations

Prediction of substrate-specific mutational hotspots for enzyme engineering is a complex and computationally intensive task. This becomes particularly challenging when the available crystal structures have no ligand, bind a distant homologue of the desired substrate, or hold the ligand in a nonproductive conformation. To address that shortcoming, we present a combined molecular dynamics simulation and molecular docking protocol to predict the conformation of catalytically relevant enzyme–ligand complexes even in the absence of a ligand-bound structure. We applied the adaptive biasing force method to predict the ligand-specific path of diffusion of a fatty acid substrate from the bulk media into the active site of cytochrome P450 CYP102A1 (BM3). Starting with a ligand-free crystal structure, we successfully identified all residues known to be involved in palmitic acid binding to BM3. The binding trajectory also revealed a yet unknown binding residue, Q73, which we confirmed experimentally. Building the free-energy landscape illustrates that, similar to human cytochrome P450s, binding is multistep and does not follow simple Michaelis–Menten kinetics. We confirmed the robustness of the method using a structurally distinct substrate, the small aromatic indole. We then applied the predicted BM3:palmitate complex to molecular docking of a library of 29 palmitate analogues. This produced catalytically relevant binding poses for the entire library, while docking directly into ligand-free and ligand-bound crystal structures gave poor results. This fast and simple computational method is broadly applicable for predicting binding hotspots in a substrate-specific manner and has the potential to drastically reduce the experimental screening effort to tailor an enzyme to substrates of interest

Facile reassembly of individually mutated gene parts.

<p>The Cal-A gene was obtained as three separate parts in DNA2.0 mother vectors. In this method, the parts can be mutated independently as appropriate for each part (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0171741#pone.0171741.t001" target="_blank">Table 1</a>, yellow stars represent illustrative mutations). As a proof of concept to demonstrate the versatility of the method, NDT libraries were generated for parts 1 and 3, and part 2 was randomly mutated. The parts (both mutated and wild-type) were then amplified by PCR reactions. They were then purified (steps 1, 2 and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0171741#pone.0171741.s009" target="_blank">S3 Fig</a>) for assembly into a number among the possible combinations of mutated parts (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0171741#pone.0171741.t001" target="_blank">Table 1</a> for chosen combinations), in a one-pot restriction-ligation reaction using <i>Bsa</i>I (3). The library of assembled genes was PCR amplified and gel purified (4, 5 and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0171741#pone.0171741.s010" target="_blank">S4 Fig</a>). Each amplified library was inserted into the daughter vector (6) using <i>Sap</i>I in a one-pot restriction-ligation reaction, for transformation into <i>E</i>. <i>coli</i> (7). Note that a simplified version of this strategy is also possible, but was found to work only when applied to the wild-type parts (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0171741#pone.0171741.s007" target="_blank">S1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0171741#pone.0171741.s011" target="_blank">S5</a> Figs).</p

Summary of sequencing results defining the quality of the random library (library 10, Table 1).

<p>Summary of sequencing results defining the quality of the random library (library 10, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0171741#pone.0171741.t001" target="_blank">Table 1</a>).</p

Qualitative results of the screening of Cal-A libraries.

<p>Qualitative results of the screening of Cal-A libraries.</p

Substrate-Specific Screening for Mutational Hotspots Using Biased Molecular Dynamics Simulations

Prediction of substrate-specific mutational hotspots for enzyme engineering is a complex and computationally intensive task. This becomes particularly challenging when the available crystal structures have no ligand, bind a distant homologue of the desired substrate, or hold the ligand in a nonproductive conformation. To address that shortcoming, we present a combined molecular dynamics simulation and molecular docking protocol to predict the conformation of catalytically relevant enzyme–ligand complexes even in the absence of a ligand-bound structure. We applied the adaptive biasing force method to predict the ligand-specific path of diffusion of a fatty acid substrate from the bulk media into the active site of cytochrome P450 CYP102A1 (BM3). Starting with a ligand-free crystal structure, we successfully identified all residues known to be involved in palmitic acid binding to BM3. The binding trajectory also revealed a yet unknown binding residue, Q73, which we confirmed experimentally. Building the free-energy landscape illustrates that, similar to human cytochrome P450s, binding is multistep and does not follow simple Michaelis–Menten kinetics. We confirmed the robustness of the method using a structurally distinct substrate, the small aromatic indole. We then applied the predicted BM3:palmitate complex to molecular docking of a library of 29 palmitate analogues. This produced catalytically relevant binding poses for the entire library, while docking directly into ligand-free and ligand-bound crystal structures gave poor results. This fast and simple computational method is broadly applicable for predicting binding hotspots in a substrate-specific manner and has the potential to drastically reduce the experimental screening effort to tailor an enzyme to substrates of interest

General C–H Arylation Strategy for the Synthesis of Tunable Visible Light-Emitting Benzo[<i>a</i>]imidazo[2,1,5‑<i>c</i>,<i>d</i>]indolizine Fluorophores

Herein we report the discovery of the benzo­[<i>a</i>]­imidazo­[2,1,5-<i>c</i>,<i>d</i>]­indolizine motif displaying tunable emission covering most of the visible spectrum. The polycyclic core is obtained from readily available amides via a chemoselective process involving Tf₂O-mediated amide cyclodehydration, followed by intramolecular C–H arylation. Additionally, these fluorescent heterocycles are easily functionalized using electrophilic reagents, enabling divergent access to varied substitution. The effects of said substitution on the compounds’ photophysical properties were rationalized by density functional theory calculations. For some compounds, emission wavelengths are directly correlated to the substituent’s Hammett constants. Easily introduced nonconjugated reactive functional groups allow the labeling of biomolecules without modification of emissive properties. This work provides a straightforward platform for the synthesis of new moderately bright fluorescent dyes remarkable for their chemical stability, predictability, and unusually high excitation–emission differential