Toward enhancement of antibody thermostability and affinity by computational design in the absence of antigen.

Over the past two decades, therapeutic antibodies have emerged as a rapidly expanding domain within the field of biologics. In silico tools that can streamline the process of antibody discovery and optimization are critical to support a pipeline that is growing more numerous and complex every year. High-quality structural information remains critical for the antibody optimization process, but antibody-antigen complex structures are often unavailable and in silico antibody docking methods are still unreliable. In this study, DeepAb, a deep learning model for predicting antibody Fv structure directly from sequence, was used in conjunction with single-point experimental deep mutational scanning (DMS) enrichment data to design 200 potentially optimized variants of an anti-hen egg lysozyme (HEL) antibody. We sought to determine whether DeepAb-designed variants containing combinations of beneficial mutations from the DMS exhibit enhanced thermostability and whether this optimization affected their developability profile. The 200 variants were produced through a robust high-throughput method and tested for thermal and colloidal stability (Tonset, Tm, Tagg), affinity (KD) relative to the parental antibody, and for developability parameters (nonspecific binding, aggregation propensity, self-association). Of the designed clones, 91% and 94% exhibited increased thermal and colloidal stability and affinity, respectively. Of these, 10% showed a significantly increased affinity for HEL (5- to 21-fold increase) and thermostability (>2.5C increase in Tm1), with most clones retaining the favorable developability profile of the parental antibody. Additional in silico tests suggest that these methods would enrich for binding affinity even without first collecting experimental DMS measurements. These data open the possibility of in silico antibody optimization without the need to predict the antibody-antigen interface, which is notoriously difficult in the absence of crystal structures.

Nutraceutical formulation, characterisation, and in-vitro evaluation of methylselenocysteine and selenocystine using food derived chitosan:zein nanoparticles.

Selenoamino acids (SeAAs) have been shown to possess antioxidant and anticancer properties. However, their bioaccessibility is low and they may be toxic above the recommended nutritional intake level, thus improved targeted oral delivery methods are desirable. In this work, the SeAAs, Methylselenocysteine (MSC) and selenocystine (SeCys2) were encapsulated into nanoparticles (NPs) using the mucoadhesive polymer chitosan (Cs), via ionotropic gelation with tripolyphosphate (TPP) and the NPs produced were then coated with zein (a maize derived prolamine rich protein). NPs with optimized physicochemical properties for oral delivery were obtained at a 6: 1 ratio of Cs:TPP, with a 1:0.75 mass ratio of Cs:zein coating (diameter ~260 nm, polydispersivity index ~0.2, zeta potential >30 mV). Scanning Electron Microscopy (SEM) analysis showed that spheroidal, well distributed particles were obtained. Encapsulation Efficiencies of 80.7% and 78.9% were achieved, respectively, for MSC and SeCys2 loaded NPs. Cytotoxicity studies of MSC loaded NPs showed no decrease in cellular viability in either Caco-2 (intestine) or HepG2 (liver) cells after 4 and 72 h exposures. For SeCys2 loaded NPs, although no cytotoxicity was observed in Caco-2 cells after 4 h, a significant reduction in cytotoxicity was observed, compared to pure SeCys2, across all test concentrations in HepG2 after 72 h exposure. Accelerated thermal stability testing of both loaded NPs indicated good stability under normal storage conditions. Lastly, after 6 h exposure to simulated gastrointestinal tract environments, the sustained release profile of the formulation showed that 62 ±â€¯8% and 69 ±â€¯4% of MSC and SeCys2, had been released from the NPs respectively.

Application of Box-Behnken experimental design for the formulation and optimisation of selenomethionine-loaded chitosan nanoparticles coated with zein for oral delivery.

Selenomethionine is an essential amino acid with a narrow therapeutic index and susceptibility to oxidation. Here it was encapsulated into a nanoparticle composed of chitosan cross-linked with tripolyphosphate for oral delivery. The formulation was optimised using a three-factor Box-Behnken experimental design. The chitosan:tripolyphosphate ratio, chitosan solvent pH, and drug load concentration were independently varied. The dependent variables studied were encapsulation efficiency, particle size, polydispersity index and zeta potential. For optimisation, encapsulation efficiency and zeta potential were maximised, particle diameter was set to 300 nm and polydispersity index was minimised. A 0.15 mg/mL concentration of selenomethionine, chitosan solvent pH of 3, and chitosan:tripolyphosphate ratio of 6:1 yielded optimum nanoparticles of size 187 ±â€¯58 nm, polydispersity index 0.24 ±â€¯0.01, zeta potential 36 ±â€¯6 mV, and encapsulation efficiency of 39 ±â€¯3%. Encapsulation efficiency was doubled to 80 ±â€¯1.5% by varying pH of the ionotropic solution components and by subsequent coating of the NPs with zein, increasing NP diameter to 377 ±â€¯47 nm, whilst retaining polydispersity index and zeta potential values. Selenomethionine-entrapped nanoparticles were not cytotoxic to intestinal and liver cell lines. Accelerated thermal stability studies indicated good stability of the nanoparticles under normal storage conditions (23 °C). In simulated gastrointestinal and intestinal fluid conditions, 60% cumulative release was obtained over 6 h.

Formulation, Characterization and Stability Assessment of a Food-Derived Tripeptide, Leucine-Lysine-Proline Loaded Chitosan Nanoparticles.

The chicken- or fish-derived tripeptide, leucine-lysine-proline (LKP), inhibits the angiotensin converting enzyme and may be used as an alternative treatment for prehypertension. However, it has low permeation across the small intestine. The formulation of LKP into a nanoparticle (NP) has the potential to address this issue. LKP-loaded NPs were produced using an ionotropic gelation technique, using chitosan (CL113). Following optimization of unloaded NPs, a mixture amount design was constructed using variable concentration of CL113 and tripolyphosphate at a fixed LKP concentration. Resultant particle sizes ranged from 120 to 271 nm, zeta potential values from 29 to 37 mV, and polydispersity values from 0.3 to 0.6. A ratio of 6:1 (CL113:TPP) produced the best encapsulation of approximately 65%. Accelerated studies of the loaded NPs indicated stability under normal storage conditions (room temperature). Cytotoxicity assessment showed no significant loss of cell viability and in vitro release studies indicated an initial burst followed by a slower and sustained release.