Development of surface-engineered PLGA nanoparticulate-delivery system of Tet1-conjugated nattokinase enzyme for inhibition of Aβ₄₀ plaques in Alzheimer’s disease

Figures & data

Table 1 Summary of experimental design, with actual and predicted values of dependent factors for NK polymeric NPs

Drug loading (%)	PLGA(mg)	Span 60 (%)	Tween 80 (%)	Sonication (seconds)	Particle size nm		PDI		EE (%)
					Actual	Predicted	Actual	Predicted	Actual	Predicted
15	175	15	7.5	10	283	270.45	0.31	0.29	83	77.69
10	175	10	5	20	200	195.22	0.23	0.23	88.4	81.90
15	175	15	5	20	201	199.00	0.22	0.22	89.3	85.03
15	175	15	5	20	201	199.00	0.22	0.22	88.2	85.03
15	175	15	5	20	201	199.00	0.22	0.22	85.5	85.03
20	250	15	5	20	219.7	227.50	0.16	0.19	94.3	92.85
10	175	15	5	10	204	215.75	0.21	0.24	82.8	78.85
20	100	15	5	20	175	159.61	0.153	0.16	71.3	75.58
20	175	15	5	10	208	209.08	0.17	0.19	81.8	83.51
10	175	15	2.5	20	171	171.99	0.19	0.17	86.4	90.06
20	175	15	2.5	20	221.3	240.26	0.215	0.20	82.3	74.62
15	100	10	5	20	189.3	204.86	0.189	0.21	61.5	61.74
15	175	10	2.5	20	210	184.38	0.226	0.21	80.9	82.13
15	250	20	5	20	312	311.58	0.35	0.33	61	67.41
15	175	15	5	20	189	199.00	0.19	0.22	84.6	85.03
15	100	15	2.5	20	195.2	207.12	0.197	0.22	68.8	68.24
15	250	15	2.5	20	188	183.41	0.145	0.14	96.1	91.91
15	175	20	5	30	240.4	254.82	0.27	0.29	78.7	74.51
10	100	15	5	20	220.9	212.19	0.211	0.20	59.5	64.12
20	175	10	5	20	230.8	225.40	0.217	0.21	87.3	86.82
15	175	10	5	30	251	264.38	0.235	0.26	89.1	80.50
15	100	15	7.5	20	188	196.13	0.19	0.20	67.2	64.04
15	250	15	5	10	195	201.98	0.21	0.22	91.4	87.09
15	175	20	5	10	321	314.86	0.39	0.37	48.8	59.4
15	175	10	5	10	175	167.82	0.221	0.20	81.4	87.59
15	250	10	5	20	183.7	194.05	0.202	0.21	94.2	102.45
15	175	10	7.5	20	264	267.69	0.28	0.28	79.5	79.18
20	175	15	5	30	205	211.34	0.202	0.20	85.7	88.82
15	100	20	5	20	220	224.80	0.28	0.28	64.2	62.6
20	175	15	7.5	20	196.4	200.02	0.212	0.21	88.4	90.92
15	175	15	5	20	201	199.00	0.22	0.22	82.8	85.03
10	175	20	5	20	333.2	316.81	0.36	0.34	71.8	63.77
15	175	15	2.5	10	188.2	185.83	0.2	0.20	76.5	77.24
15	250	15	7.5	20	304.2	295.82	0.35	0.33	92.7	85.91
10	250	15	5	20	205.8	220.28	0.21	0.22	93.5	92.38
10	175	15	5	30	233	250.01	0.223	0.23	84.1	81.56
15	100	15	5	30	207	182.25	0.225	0.19	66.5	68.34
15	175	20	7.5	20	278.8	303.83	0.35	0.39	61.3	59.94
10	175	15	7.5	20	328	313.65	0.33	0.33	49.7	63.56
15	175	15	5	20	201	199.00	0.22	0.22	79.8	85.03
15	175	20	2.5	20	290	285.72	0.281	0.30	67	67.19
15	100	15	5	10	192.7	201.14	0.203	0.20	76.4	70.73
15	250	15	5	30	283.6	257.39	0.234	0.22	94.3	97.50
20	175	20	5	20	258.3	241.29	0.31	0.29	72.8	70.78
15	175	15	2.5	30	233	238.00	0.19	0.20	80.2	86.81
15	175	15	7.5	30	260	254.81	0.278	0.27	75.6	76.16

Note: Obtained from Box–Behnken design of response-surface methodology.

Abbreviations: NK, nattokinase; NPs, nanoparticles; PLGA, poly(lactic-co-glycolic acid); PDI, polydispersity index; EE, entrapment efficiency.

Figure 1 3-D surface and contour plots.

Note: Interaction effects of independent variables, such as drug loading, polymer concentration, sonication time, and concentration of surfactants, on particle size (PS).

Abbreviation: PLGA, poly(lactic-co-glycolic acid) nanoparticle.

Figure 2 3-D surface and contour plots.

Note: Interaction effects of independent variables, such as drug loading, polymer concentration, sonication time, and concentration of surfactants, on polydispersity index (PDI).

Abbreviation: PLGA, poly(lactic-co-glycolic acid) nanoparticle.

Figure 3 3-D surface and contour plots.

Note: Interaction effects of independent variables, such as drug loading, polymer concentration, sonication time and concentration of surfactants, on entrapment efficiency (EE).

Abbreviation: PLGA, poly(lactic-co-glycolic acid) nanoparticle.

Table 2 Analysis of variance of calculated model of NK polymeric NPs

Response	PS	PDI	EE (%)
Regression
Sum of squares	83,080.36	0.1416	5,297.01
df	20	20	20
Mean squares	4,154.01	0.007	264.89
F-value	16.07	13.44	6.07
P-value	0.009	0.0001	0.0008
Residual
Sum of squares	6,459.33	0.0131	1,089.17
df	25	25	25
Mean squares	258	0.0005	43.56
Lack-of-fit test
Sum of squares	6,339.33	0.0124	1,028
df	20	20	20
Mean squares	316.96	0.00062	51.40
F-value	13.20	4.13	4.21
P-value	0.004	0.0608	0.0586
Coefficient correlation (r^2)	0.927	0.914	0.829
Coefficient of variation (%)	7.07	9.68	8.3
Adequate precision value	14.47	16.01	9.65
Predicted R^2	0.71	0.67	0.34
Adjusted R^2	0.87	0.84	0.69
SD	16.07	0.022	6.60
Mean	227.33	0.23	78.83

Abbreviations: NK, nattokinase; NPs, nanoparticles; PS, particle size; PDI, poly-dispersity index; EE, entrapment efficiency.

Figure 4 SEM of the optimized NPNP formulation at 10.46 K× (A) and 10.69 K× (B) magnification.

Abbreviations: SEM, scanning electron microscopy; NPNP, nattokinase–poly(lactic-co-glycolic acid) nanoparticle.

Figure 5 TEM of (A) conjugated and (B) optimized NPNP formulation.

Abbreviations: TEM, transmission electron microscopy; NPNP, nattokinase–poly(lactic-co-glycolic acid) nanoparticle; PLGA, poly(lactic-co-glycolic acid) nanoparticle.

Figure 6 (A) Particle size and PDI of NKNPs; (B) particle-size distribution of NKNPs.

Abbreviations: PDI, polydispersity index; NKNPs, nattokinase–poly(lactic-co-glycolic acid) nanoparticles.

Figure 7 In vitro release of nattokinase from nattokinase polymeric nanoparticles at different time intervals (0–48 hours) using dialysis in PBS at pH 7.4.

Figure 8 Fluorescence emission spectra obtained by using ThT binding assay of Aβ-40 plaque before (green line) and after digestion (24 hours) by nattokinase (red line) and NKNPs (blue line) and ThT was used as a blank (purple line) at 40°C, pH 7.

Abbreviations: ThT, thioflavin T; NK, nattokinase; PLGA, poly(lactic-co-glycolic acid); NKNPs, nattokinase–poly(lactic-co-glycolic acid) nanoparticles.

Figure 9 Scanning electron microscopy of Aβ₄₀ plaques.

Notes: Untreated Aβ₄₀ plaque (A and B), Aβ₄₀ plaques digested with unformulated nattokinase for 1 h (C), Aβ₄₀ plaques digested with unformulated nattokinase for 24 h (D), Aβ₄₀ plaques digested with NKNPs for 1 h (E) and for 24 h (F), Aβ₄₀ plaques digested with conjugated NKNPs for 1 h (G) and for 24 h (H).

Abbreviations: h, hours; NKNPs, nattokinase–poly(lactic-co-glycolic acid) nanoparticles.

Figure 10 Invitro thrombin plaque inhibition of NK (A and D), NKNPs (B and E), and NKNPs-Tel-1 (C and F) before (A–C) and after (D–F) the preparation of NKNPs and surface modification.

Abbreviations: NK, nattokinase; NKNPs, nattokinase–poly(lactic-co-glycolic acid) nanoparticles.

Figure S1 3-D surface and contour plots.

Note: Interaction effects of independent variables, such as drug loading, polymer concentration, sonication time, and concentration of surfactants, on particle size (PS).

Abbreviation: PLGA, poly(lactic-co-glycolic acid) nanoparticle.

Figure S2 3-D surface and contour plots.

Note: Interaction effects of independent variables, such as drug loading, polymer concentration, sonication time, and concentration of surfactants, on polydispersity index (PDI).

Abbreviation: PLGA, poly(lactic-co-glycolic acid) nanoparticle.

Figure S3 3-D surface and contour plots.

Note: Interaction effects of independent variables, such as drug loading, polymer concentration, sonication time, and concentration of surfactants, on entrapment efficiency (EE).

Abbreviation: PLGA, poly(lactic-co-glycolic acid) nanoparticle.

Figure S4 FTIR spectra of (A) PLGA polymer, (B) NK, and (C) NKNPs.

Abbreviations: FTIR, Fourier-transform infrared; NK, nattokinase; PLGA, poly(lactic-co-glycolic acid); NKNPs, NK-PLGA nanoparticles.

Figure S5 DSC thermograms of (A) NK and (B) optimized-formulation NKNPs.

Abbreviations: DSC, differential scanning calorimetry; NK, nattokinase; NKNPs, NK–poly(lactic-co-glycolic acid) nanoparticles.