Baliq oqsili gidrolizati oqsillarning kichikroq peptidlar va aminokislotalarga parchalanishi natijasida hosil bo‘ladigan oqsil kelib chiqishli aralashmadir. Ushbu tadqiqot Scomberomorus commersonni qayta ishlashning yon mahsuloti bo‘lgan mushak va teri to‘qimalarini Pediococcus pentosaceus IL13 bilan fermentatsiya qilish natijasida hosil bo‘lgan gidrolizatlarning α-glukozidaza ingibitor faolligi va to‘rtta patogen bakteriyaga qarshi antibakterial faolligini bevosita laboratoriya sharoitida o‘rgangan; ultrafiltratsiya orqali <30, <10 va <3 kDa peptid fraksiyalarini ajratgan; LC-HRMS asosidagi peptidomik tahlil va ko‘plab in silico prediction platformalari yordamida tanlangan peptidlarning potensial biologik xususiyatlarini baholagan. Eng past crude-hydrolysate IC₅₀ qiymati mushak+teri aralashmasidan iborat FXH guruhida 34,692±1,355 mg/mL deb topilgan. <3 kDa fraksiyalar α-glukozidaza ingibitsiyasida va ayniqsa Listeria monocytogenesga qarshi antibakterial faollikda ajralib turgan. Biroq peptidlarning antidiyabetik, antimikrob, toksik yoki allergen bo‘lishiga doir kompyuter prognozlari haqiqiy klinik samaradorlik yoki xavfsizlik dalili emas.

α-Glukozidaza ingibitsiyasi uchun <3 kDa fraksiyalar FMH, FSH va FXHda mos ravishda taxminan %79,45, %78,03 va %79,03 inhibition ko‘rsatgan. Freeze-dried crude hydrolysate dose-response tahlilida FXHning IC₅₀ qiymati 34,692±1,355 mg/mL, FSHniki 36,643±1,384 mg/mL va FMHniki 46,541±1,228 mg/mL. Pastroq IC₅₀ ayni tajriba tizimida pastroq konsentratsiyada %50 inhibitionga erishilganini va shu sababli kuchliroq ingibitor potensialini anglatadi.

Antibakterial tajribalarda <3 kDa fraksiyalar ayniqsa L. monocytogenesda katta inhibition zones hosil qilgan: FSH 23,17±1,89 mm, FMH 22,50±0,50 mm va FXH 21,83±1,76 mm. Salmonella typhi umuman olganda pastroq sezgirlik ko‘rsatgan. Bu qiymatlar agar-well diffusion testidagi zona diametrlaridir; minimum inhibitory concentration (MIC), minimum bactericidal concentration (MBC) yoki odamlardagi antibiotik samaradorligi emas.

LC-HRMS asosidagi tadqiqot 211 peptide sequence orasidan relative abundance asosida 35 vakillik ketma-ketligini keyingi in silico baholashga olib o‘tgan. PeptideRankerda SPAMPVPGPMGPMGPR 0,926 bilan eng yuqori umumiy bioactivity score olgan; AntiT2DMP-Predda ayni peptid 0,811 bilan eng yuqori type-2-antidiabetic prediction qiymatini ko‘rsatgan. AVFPSIVGRPR esa bir nechta antimicrobial prediction platformalarida ijobiy tasnif olgani sabab manba tomonidan kuchli antimicrobial candidate sifatida ustuvorlashtirilgan. Bu natijalar nomzodlarni tanlash uchundir; dori samaradorligining dalili emas.

Batafsil Tushuntirish

Tadqiqotning asosiy muammosi

Baliqni qayta ishlash sanoati mushak bo‘laklari, teri, suyak, bosh, ichki organlar va boshqa yon mahsulotlardan katta miqdorda biologik qoldiq hosil qilishi mumkin. Ushbu yon mahsulotlarning muhim qismi oqsilga boy. Tadqiqotning asosiy yondashuvi past qiymatli yoki chiqindi deb hisoblangan bu oqsil materialini mikrob fermentatsiyasi orqali kichikroq va biologik faollik ko‘rsatishi mumkin bo‘lgan peptidlarga aylantirish hamda shu tariqa bir vaqtning o‘zida chiqindilarni valorizatsiya qilish va potensial funksional komponentlarni kashf etishga hissa qo‘shishdir.

Ushbu tadqiqot ayniqsa ikki biologik faollikni nishonga oladi:

• α-glukozidaza fermentini ingibitsiya qilish orqali ehtimoliy antidiyabetik potensialning dastlabki skriningi,
• Gram-musbat va Gram-manfiy bakteriyalarga qarshi antibakterial faollik.

Bunga LC-HRMS peptidomik va in silico prediction qatlami qo‘shilib, qaysi peptide sequences keyingi eksperimental tasdiqlash uchun ustuvorlashtirilishi mumkinligi o‘rganilgan.

Uch gidrolizat guruhi nimani anglatadi?

Baliq materiali qayerdan olingan?

Scomberomorus commersonni qayta ishlash yon mahsulotlari 2025-yil yanvar oyida Muara Baru Fish Market, Penjaringan, Jakarta, Indonesiadan olingan. Manba koordinatalarni 6°06′36″S, 106°48′06″E deb ko‘rsatadi.

Material:

• skin,
• fragmented flesh,
• softened meat,
• ruptured abdominal portions kabi mechanically damaged muscle tissues

ni o‘z ichiga olgan.

Namunalar yuvilgan, blender va meat grinder bilan gomogenlashtirilgan; qadoqlanib yorliqlangan, dastlabki 24–48 soat −4°Cda saqlangan, chilled insulated ice boxes bilan tashilgan va tahlildan oldin −20°Cda saqlangan.

Pediococcus pentosaceus IL13 nima uchun ishlatilgan?

Pediococcus pentosaceus IL13 tadqiqotning fermentatsiya mikroorganizmi hisoblanadi. Manbada ushbu sut kislotasi bakteriyasi Microbial Bioprospecting Laboratory, Research Center for Biotechnology, IPB Universitydan olingani ko‘rsatilgan.

Fermentatsiyaning ilmiy mantiqi mikroorganizmlar va tegishli proteolitik jarayonlarning yirik oqsil tuzilmalarini kichikroq peptide fragmentsga parchalashi mumkinligidir. Oqsil tarkibida dastlab mavjud bo‘lgan, ammo erishib bo‘lmaydigan ayrim bioactive peptide sequences ushbu proteolysis/hydrolysis jarayoni bilan ajralib chiqishi mumkin.

Fermentatsiya qanday amalga oshirilgan?

P. pentosaceus IL13 glycerol stock avval MRS broth ichida 37°Cda 24 soat qayta faollashtirilgan.

Shundan so‘ng:

1. MRS agar plate ustiga streak qilingan.
2. 37°Cda 48 soat inkubatsiya qilingan.
3. Bitta colony 10 mL MRS brothga ko‘chirilgan va 37°Cda 24 soat o‘stirilgan.
4. Starter culture tayyorlash uchun ushbu pre-culturedan 1 mL olinib 100 mL fresh MRS brothga inoculate qilingan.
5. Muscle, skin va 1:1 muscle+skin ko‘rinishida uchta experimental group tayyorlangan.
6. Har bir guruhdan 10 g material alohida 50 mL Falcon tubega joylashtirilgan.
7. 40 mL %10 (w/v) glucose solution qo‘shilgan.
8. Namunalar 121°Cda 15 daqiqa sterilizatsiya qilingan.
9. Har bir namunaga 400 μL P. pentosaceus IL13 culture inoculate qilingan.

Submerged fermentation muddati muscle va mixed samples uchun to‘rt kun, skin uchun besh kun bo‘lgan.

Gidrolizatlar P. pentosaceus IL13ning optimal growth curve vaqt nuqtasida yig‘ib olingan. Supernatant 14.000×gda 30 daqiqa, 4°Cda sentrifugalash orqali ajratilgan; liquid hydrolysate −20°Cda saqlangan.

Ultrafiltratsiya Nima Uchun <3 kDa Fraksiyasini Ajratib Ko‘rsatdi?

Ultrafiltratsiya gidrolizatdagi molekulalarni taxminiy molekulyar kattaligiga ko‘ra membranalardan o‘tkazib ajratadigan fraksiyalash usulidir; ushbu tadqiqotda 30, 10 va 3 kDa molecular-weight-cutoff membranlari qo‘llangan va <3 kDa permeate kichikroq peptidlar boyigan fraksiya sifatida ham α-glukozidaza ingibitsiyasida, ham antibakterial tajribalarning muhim qismida eng kuchli natijalarni ko‘rsatgan.

kDa nimani anglatadi?

kDa kilodalton birligidir. Dalton molekulyar massa birligidir; 1 kDa taxminan 1.000 Da degani. “<3 kDa fraction” iborasi ushbu tadqiqotda ishlatilgan ultrafiltration membranedan o‘ta oladigan va taxminan 3 kilodaltondan past molekulyar og‘irlik hududini anglatadi.

Bu ibora barcha peptidlar bir xil kattalikda ekanini anglatmaydi; u molecular-weight range ni belgilaydi.

Ultrafiltratsiya sharoitlari

Amicon Ultra-15, Millipore ultrafiltration tizimi va mos ravishda 30, 10 va 3 kDa MWCO membranlari ishlatilgan.

Fractionation:

5.000×g, 30 daqiqa, 10°C

sharoitida bajarilgan.

Manba fraksiyalarni:

• F-I: <30 kDa,
• F-II: <10 kDa,
• F-III: <3 kDa

deb belgilaydi.

Yig‘ilgan fraksiyalar bioactivity evaluationdan oldin −20°Cda saqlangan.

α-Glukozidaza Ingibitsiyasi Nima Uchun “Antidiyabetik Salohiyat” Sifatida O‘rganiladi?

α-Glukozidaza uglevodlar hazmining yakuniy bosqichlarida kichikroq shakar tuzilmalarini glyukozaga aylantiradigan fermentlardan biridir; ferment faolligini sekinlashtira oladigan birikma laboratoriya sharoitida postprandial glyukoza hosil bo‘lishini kamaytirishga qaratilgan nomzod sifatida baholanishi mumkin, biroq ushbu tadqiqotdagi α-glukozidaza ingibitsiyasi faqat in vitro ferment assayidir va odamlarda qon shakarini pasaytirishini isbotlamaydi.

α-Glukozidaza tajribasining tarkibiy qismlari

Manba assayda Saccharomyces cerevisiaedan olingan α-glukozidazadan foydalangan.

Har bir reaction system uchun:

• 50 μL diluted hydrolysate sample,
• 30 μL phosphate buffer, pH 6,8,
• 60 μL p-nitrophenyl-α-D-glucopyranoside (pNPG),
• 60 μL α-glucosidase enzyme solution

ishlatilgan.

Reaksiya 37°Cda 30 daqiqa davom ettirilgan, so‘ng har bir wellga:

60 μL 200 mM Na₂CO₃

qo‘shilib to‘xtatilgan.

Absorbance 405 nmda microplate spectrophotometer bilan o‘lchangan.

pNPG va pNP nima vazifa bajaradi?

pNPG α-glukozidaza parchalashi mumkin bo‘lgan chromogenic substrate hisoblanadi. Ferment pNPGni gidroliz qilganda o‘lchash mumkin bo‘lgan rangli mahsulotlardan biri — p-nitrophenol (pNP) hosil bo‘ladi.

Shuning uchun asosiy mantiq quyidagicha:

Faol α-glukozidaza ko‘proq → pNP ko‘proq hosil bo‘ladi.

α-glukozidaza ingibitsiyasi kuchliroq → pNP kamroq hosil bo‘ladi.

Manba 0–500 ppm pNP standard curve tayyorlagan va 405 nm absorbance bilan linear regressiondan foydalangan:

\[ R^2>0.99 \]

Ushbu calibration curve o‘lchangan absorbanceni pNP concentrationga aylantirishda ishlatilgan.

Manbada pNP inhibition uchun aniq algebraik foiz formulasi yozilmagan. Shu sababli Verianla manbada bo‘lmagan assay equationni “maqola formulasi” sifatida qo‘shmaydi.

Nazoratlar

α-Glukozidaza assayida:

• Acarbose 100 ppm positive control,
• Sterile distilled water negative control

sifatida ishlatilgan.

Shuningdek, baseline absorbance correction uchun enzyme qo‘shilmagan control system tayyorlangan.

Table 1: pNP hosil bo‘lishi nima uchun muhim?

Uchala gidrolizat guruhida ham molecular-weight fraction kichraygani sari pNP production umuman kamaygan. Eng past pNP concentration FMH <3 kDa guruhida 37,323 ppm bo‘lgan. pNPning kamayishi assay mantiqida yuqoriroq α-glukozidaza inhibition bilan mos keladi.

Ushbu taqqoslashda manba turli superscript letters bilan p<0,05 darajasidagi statistical differencesni ko‘rsatgan.

IC50 Qiymatini Qanday Talqin Qilish Kerak?

IC₅₀ sinov qilinayotgan material o‘lchanayotgan biologik javobni %50 darajasiga keltirishi uchun zarur konsentratsiyani anglatadi; bir xil assay sharoitida pastroq IC₅₀ yuqoriroq ingibitor potencyga ishora qiladi, biroq turli assay usullari yoki turli moddalar orasida bevosita klinik doza ekvivalentligini yaratmaydi.

IC₅₀ tahlili uchun freeze-dried crude hydrolysates:

10–50 mg/mL

oralig‘ida sinovdan o‘tkazilgan.

Percentage inhibition va sample concentration orasida dose-response curves yaratilgan va IC₅₀:

GraphPad Prism version 10.0 bilan nonlinear regression

yordamida hisoblangan.

FXHning pastroq IC₅₀ ko‘rsatishi mixed hydrolysate ushbu assayda yuqoriroq inhibitory potencyga ega ekaniga mos keladi.

Discussion bo‘limi buni muscle va skin peptide pools orasidagi ehtimoliy “synergistic enhancement” sifatida talqin qiladi. Biroq tadqiqot klassik synergy design, combination index yoki isobologram tahlilini bajarmagan. Shuning uchun sinergiya bu yerda bevosita o‘lchangan alohida tajriba natijasi emas, mualliflarning mechanistic interpretationidir.

Antibakterial Faollik Qanday O‘lchangan?

Tadqiqot antibacterial activityni agar-well diffusion usuli bilan o‘lchagan; standartlashtirilgan bakteriyalar agarga tarqatilgan, 6 mm quduqlarga 100 μL filtrlangan hydrolysate qo‘shilgan va 24 soat inkubatsiya oxirida hosil bo‘lgan clear inhibition zone diametri millimetrda o‘lchangan.

Sinov qilingan bakteriyalar

To‘rtta bakteriya ishlatilgan:

• Listeria monocytogenes,
• Enterococcus faecalis,
• Escherichia coli,
• Salmonella typhi.

Bacterial cultures 37°Cda 24 soat LB brothda o‘stirilgan va 0,5 McFarland turbidity standardiga moslashtirilgan.

Manba bu zichlikni taxminan:

\[ 1\times10^8\ \text{CFU/mL} \]

deb beradi.

100 μL standardized bacterial culture taxminan 45°Cdagi molten LB agar bilan aralashtirilgan.

Agar solidificationdan keyin 6 mm diametrli wells ochilgan va har bir wellga 100 μL filter-sterilized hydrolysate sample qo‘shilgan.

Samples diffusion uchun room temperatureda bir soat qoldirilgan; so‘ng 37°Cda 24 soat inkubatsiya qilingan.

Tajribalar triplicate bajarilgan.

Negative control sterile distilled water, positive control esa chloramphenicol 100 ppm bo‘lgan.

Ingibitsiya zonasi tasnifi

Manba Davis va Stout tasnifidan foydalangan:

Table 2: Antibakterial natijalar

Manbada turli superscript letters p<0,05 darajasidagi statistical differencesni ko‘rsatadi.

L. monocytogenes ayniqsa past-molecular-weight fraksiyalarga sezgir ko‘rinadi. FMH, FSH va FXHning <3 kDa fraksiyalarining barchasi manba tasnifida ≥20 mm bo‘lgani sabab “very strong” toifasiga kiradi.

S. typhi esa eng past sezgirlik ko‘rsatgan organizmdir. Ayniqsa FSH crude, <30 kDa va <10 kDa fraksiyalarida 0 mm inhibition qayd etilgan.

Nima uchun zona diametrini antibiotik kuchi bilan bevosita tenglashtirmaslik kerak?

Agar-well diffusion natijasiga faqat biologik inhibition ta’sir qilmaydi; test moddasining agar ichidagi diffusion xatti-harakati ham zonaga hissa qo‘shadi. Shuning uchun FSH <3 kDa Listeria uchun 23,17 mm, chloramphenicol control esa 14,25 mm zona hosil qilgani “gidrolizat chloramphenicoldan kuchliroq antibiotik” deb bevosita talqin qilinmaydi.

Tadqiqot hydrolysates uchun:

• MIC,
• MBC,
• time-kill kinetics,
• in vivo infection outcome

ni qayd etmagan.

LC-HRMS peptidomik tayyorlash

Har bir tahlil uchun 100 mg freeze-dried hydrolysate, 1 mL 50 mM ammonium bicarbonate buffer pH 8,0 ichida suspenziya qilingan.

Asosiy tayyorlash bosqichlari:

1. 14.000×g, 20 daqiqa, 4°C centrifugation.
2. 500 μL supernatant + teng hajmda −20°C acetone.
3. −20°Cda 4 soat incubation.
4. 16.000×g, 20 daqiqa, 4°C centrifugation.
5. Pellet 45°Cda 30 daqiqa quritish.
6. 500 μL buffer ichida qayta eritish.
7. 10 μL 10 mM DTT bilan 56°Cda 60 daqiqa reduction.
8. 10 μL 20 mM IAA bilan qorong‘ida 60 daqiqa alkylation.
9. 0,1 mg/mL trypsin bilan 37°Cda 17 soat digestion.
10. 500 μL %1 TFA bilan reaction termination.
11. 8.100×g, 5 daqiqa centrifugation.
12. 0,2 μm PVDF membrane filtration.

LC-HRMS Peptidomik Tahlili Nima Qiladi?

LC-HRMS murakkab peptide mixturesni avval liquid chromatography orqali ajratadigan, so‘ng high-resolution mass spectrometry bilan massa/zaryad ma’lumotlarini o‘lchab peptide sequencesni aniqlashga yordam beradigan analitik yondashuvdir; ushbu tadqiqotda LC-HRMS/LFQ qatlami peptide identity va relative abundanceni ta’minlab, keyinchalik in silico baholashga olinadigan 35 vakillik ketma-ketligini tanlash uchun asos bo‘lgan.

LC tomoni

Peptide separation:

• Vanquish™ Horizon UHPLC,
• PepMap™ 100 C18 column, 150 mm × 1 mm, 3 μm,
• 75 μL/min flow rate,
• 30°C,
• 0,1% formic acid saqlovchi water va acetonitrile mobile phases

bilan amalga oshirilgan.

MS tomoni

Mass-spectrometry system:

• Orbitrap Exploris 240 HRMS,
• OptaMax™ NG H-ESI source,
• positive mode,
• Full MS/dd-MS2 acquisition,
• Full-MS resolution: 120.000,
• MS2 resolution: 15.000 FWHM

deb qayd etilgan.

Raw data Proteome Discoverer 2.5 ichida SequestHT yordamida UniProt va NCBI databasesga qarshi qayta ishlangan.

Label-free quantification (LFQ) peptide abundance taqqoslashini isotope-label qo‘shmasdan MS signal intensivliklari orqali nisbiy tarzda amalga oshirishga qaratilgan yondashuvdir.

211 peptiddan 35 peptidga qanday o‘tildi?

Manba 211 peptide sequence orasidan taxminan har bir hydrolysate type uchun highest-abundance qismini tanlab, jami 35 representative peptide sequenceni keyingi in silico tahlillarga olib o‘tgan.

Bu 35 sequence:

• 8–18 amino acid uzunlikda,
• aksariyati 10–14 residue oralig‘ida,
• FMH 20 unique sequence,
• FSH 10 unique sequence,
• beshta peptide bir nechta hydrolysate type ichida umumiy

deb qayd etilgan.

In Silico Prediction Natijasi Haqiqiy Biologik Faollikni Anglatadimi?

Yo‘q. In silico prediction platformalari peptide sequence xususiyatlaridan kelib chiqib ma’lum biologik sinflarga o‘xshashlik ehtimoli yoki taxminiy faollik skorini hisoblaydi; bu skorlar nomzodlarni saralash uchun qimmatli, ammo peptidning haqiqiy organizmda antidiyabetik, antibakterial, toksik, allergen yoki xavfsiz ekanini o‘z-o‘zidan isbotlamaydi.

PeptideRanker

PeptideRanker sequencening umumiy bioactive-peptide bo‘lish ehtimolini ustuvorlashtirish uchun ishlatilgan.

Manbada score oralig‘i:

\[ 0.000-0.926 \]

deb qayd etilgan.

To‘qqiz peptide 0,5dan yuqori score olgan.

Ajralib turganlar:

Novelty tahlili

BIOPEP-UWM database taqqoslashida:

33/35 peptide = %94,3

manba tomonidan novel deb tasniflangan.

Reported sifatida topilgan ikki sequence:

• IWHHTFYNELR,
• AGFAGDDAPR.

Bu yerdagi “novel” sequence tegishli database/literature cross-reference ichida ilgari bioactive peptide sifatida qayd etilmaganini anglatadi; “tabiatda birinchi marta paydo bo‘ldi” degani emas.

Toxicity prediction

Table 3ga ko‘ra:

32/35 = %91,43 non-toxic prediction

mavjud.

Toxin sifatida ko‘rsatilgan uch peptide:

• IEELEEEIEAER,
• TGPIGMPGAR,
• VEELEEEIEAER.

Manba prose bu yerda “two peptides” iborasini ishlatsa-da, uch sequence sanab o‘tilgan. Table 3 va 32/35 hisobi uchta toxic-predicted peptide bilan mos keladi.

Allergenicity nima uchun yagona natija bermaydi?

Manba uch xil prediction yondashuvidan foydalangan:

• pLM4Alg-640,
• AlgPred2,
• AllerCatPro 2.0.

Bir xil peptide turli modellar tomonidan turlicha tasniflanishi mumkin. Bu holat Table 3da yaqqol ko‘rinadi.

Manba faqat to‘rtta peptid kamida ikki modelda izchil non-allergen prognoz ko‘rsatganini bildiradi:

• IWHHTFYNELR,
• GYSFVTTAER,
• AGEPGAAGLR,
• SPAMPVPGPMGPMGPR.

Shuning uchun “non-allergen prediction” ham clinical food-allergy safety natijasi emas.

Manba ichidagi sequence yozilish farqlari

Antidiyabetik prediction vositalari

Ikki xil vosita ishlatilgan:

• AntiDMP-pred: general antidiabetic bioactive peptide prediction,
• AntiT2DMP-Pred: Type 2 diabetes-related peptide prediction.

Manbada prediction score 0–1 oralig‘ida va 0,5dan yuqori qiymatlar potential positive prediction sifatida baholangan.

AntiDMP-predda 27/35 peptide, ya’ni %77,1, 0,5dan yuqori score olgan.

AntiT2DMP-Pred esa ancha selektiv natija bergan. 35 peptide ichida faqat ikkita ketma-ketlik 0,5dan yuqori score olgan:

Ushbu vositalar farqi ilmiy jihatdan muhim. Masalan, VAEQELVDASER AntiDMP-predda 0,83 bo‘lsa, AntiT2DMP-Predda atigi 0,012. AVFPSIVGRPR esa AntiDMP-predda 0,31, AntiT2DMP-Predda 0,663.

Shuning uchun “antidiabetic peptide” yagona va modeldan mustaqil classification emas.

Antimicrobial prediction vositalari

Manba quyidagi tizimlardan foydalangan:

• CAMPR4 — Random Forest, Support Vector Machine va Artificial Neural Network algoritmlari,
• Antimicrobial Peptide Scanner v2,
• ADAM,
• AntiBP3 — Gram-positive va Gram-negative antibacterial prediction.

Table 5ning CAMPR4 headerida uchinchi model yorlig‘i yana “SVM” deb yozilgan; biroq metod bo‘limi, Results prose va table footnote uchinchi modelni Artificial Neural Network deb belgilaydi. Shu sababli Verianla manba headerini xatosizdek qayta yozmaydi.

Modellar nima uchun bir xil natija bermaydi?

Har bir model turli training dataset, features, architecture va classification threshold ishlatadi. Shu sabab bir xil peptide:

• bir modelda AMP,
• boshqa modelda Non-AMP,
• bir AntiBP3 tarmog‘ida ABP,
• boshqasida non-ABP

bo‘lishi mumkin.

Table 5ning o‘z izohi yulduzcha qo‘yilgan natijalarni internal prediction inconsistencies deb belgilaydi.

Bu prediction vositalari xatosiz emasligini va bitta algoritm natijasini qat’iy biologik haqiqat sifatida ishlatmaslik kerakligini ko‘rsatadi.

AVFPSIVGRPR nima uchun ajralib turadi?

AVFPSIVGRPR Table 5da:

Manba prose AVFPSIVGRPR uchun ayrim Scanner/ADAM raqamlarini Table 5dagidan boshqacha moslashtiradi. Yuqoridagi jadval e’lon qilingan Table 5 qiymatlarini saqlaydi.

“Most promising antimicrobial peptide” iborasi ko‘plab modellarning umumiy prediction yo‘nalishiga asoslangan nomzod ustuvorligidir; haqiqiy bakteriyalarga qarshi purified AVFPSIVGRPR peptide assay ushbu tadqiqotda bajarilmagan.

SPAMPVPGPMGPMGPR nima uchun ajralib turadi?

Ushbu collagen-derived sequence uch xil prediction qatlamida e’tibor tortadi:

Manba Results prosenining bir joyida SPAMPVPGPMGPMGPR uchun “peptide 23” deyiladi; Table 4 va boshqa Results bayoni ushbu ketma-ketlikni peptide 28 deb belgilaydi. GFPGSDGSAGPK esa peptide 23 sifatida berilgan. Ushbu peptide-number farqi yashirilmagan.

Statistik tahlil

Experimental data:

• Microsoft Excel,
• GraphPad Prism,
• IBM SPSS Statistics version 27

bilan tahlil qilingan.

Treatment groups orasidagi statistical differences:

One-way analysis of variance (ANOVA)

va undan keyin:

Duncan's multiple range test

bilan baholangan.

Ahamiyatlilik chegarasi:

\[ P<0.05 \]

deb belgilangan.

ANOVA bir nechta guruh o‘rtachalarining barchasi bir xil degan null hypothesisga qarshi umumiy farq mavjudligini baholaydi. Duncan multiple range test esa ahamiyatli umumiy farqdan keyin qaysi guruhlar bir-biridan ajralishini harf guruhlari orqali aniqlashga qaratilgan post-hoc yondashuvdir.

Tadqiqot Usuli va Natijalari

Tajriba dizaynining umumiy ko‘rinishi

Asosiy α-glukozidaza natijasi

Ultrafiltration umuman lower-molecular-weight fractions ichida yuqoriroq α-glukozidaza inhibition bilan birga kuzatilgan.

<3 kDa:

• FMH ≈ %79,45,
• FSH ≈ %78,03,
• FXH ≈ %79,03

inhibition ko‘rsatgan.

Manba ayni Results paragrafi boshida umumiy inhibition oralig‘ini taxminan %61,97–79,09 deb yozgan. FMH <3 kDa uchun ayni paragrafda %79,45 berilgani sabab bu ikki hisobot orasida kichik manba-ichki yuqori chegara farqi mavjud.

Crude hydrolysate dose-response natijasi

10–50 mg/mL oralig‘ida inhibition concentration-dependent oshgan.

IC₅₀ tartibi:

FXH 34,692±1,355 < FSH 36,643±1,384 < FMH 46,541±1,228 mg/mL.

Bu tartib sinov qilingan assay sharoitlarida FXH crude-hydrolysate darajasida yuqoriroq α-glukozidaza inhibitory potency ko‘rsatishiga mos keladi.

Asosiy antibakterial natija

Molecular weight kichraygan sari inhibition zone ayniqsa ko‘plab FMH, FSH va FXH taqqoslashlarida kattalashgan.

L. monocytogenes eng sezgir organizm sifatida ajralib turadi.

<3 kDa fraksiyalarda:

• FSH: 23,17±1,89 mm,
• FMH: 22,50±0,50 mm,
• FXH: 21,83±1,76 mm

o‘lchangan.

Manba classificationida uchalasi ham very strong inhibition zone toifasida.

211 peptide → 35 candidate

LC-HRMS/MS peptide pool jami 211 sequence saqlaydi.

Relative abundance va hydrolysate coverage yordamida 35 representative sequence tanlangan va computational profiling bajarilgan.

Ushbu nomzod tanlovining maqsadi barcha 211 peptid bir xil darajada kuchli ekanini ko‘rsatish emas; batafsilroq prediction tadqiqoti uchun peptide poolni toraytirishdir.

Ajralib turgan nomzodlar

Tadqiqot bevosita qo‘llab-quvvatlaydigan natijalar

• P. pentosaceus IL13 bilan fermentlangan skumbriya mushak, teri va aralash yon mahsulotlaridan protein hydrolysates olingan.
• <3 kDa fractions umuman kuchli α-glukozidaza inhibition ko‘rsatgan.
• FXH crude hydrolysate 34,692±1,355 mg/mL bilan uch crude group orasida eng past IC50 qiymatiga ega.
• Low-molecular-weight fractions ko‘plab antibacterial comparisonda kattaroq inhibition zones ko‘rsatgan.
• L. monocytogenes ayniqsa <3 kDa fractionsga sezgir.
• LC-HRMS peptidomic pool ichida 211 peptide sequence mavjud.
• 35 representative peptide keyingi computational evaluation uchun tanlangan.
• 33/35 sequence BIOPEP-UWM taqqoslashida novel deb tasniflangan.
• Table 3 ma’lumotiga ko‘ra 32/35 peptide non-toxic prediction olgan.
• SPAMPVPGPMGPMGPR va AVFPSIVGRPR keyingi eksperimental tasdiqlash uchun ajralib turgan computational candidates qatorida.

Tadqiqot bevosita qo‘llab-quvvatlamaydigan natijalar

• Gidrolizatlar odamlarda diabetni davolashi ko‘rsatilmagan.
• Odamlarda postprandial glucose pasayishi o‘lchanmagan.
• Peptidlarning oral bioavailabilitysi ko‘rsatilmagan.
• Gastrointestinal digestiondan keyin faol qolishi sinovdan o‘tkazilmagan.
• Purified SPAMPVPGPMGPMGPRning odamlardagi antidiyabetik ta’siri ko‘rsatilmagan.
• Purified AVFPSIVGRPRning bakteriyalarga qarshi haqiqiy MIC/MBC qiymati ushbu tadqiqotda o‘lchanmagan.
• In silico non-toxic prediction inson toksikologik xavfsizligi emas.
• In silico non-allergen prediction odamlarda food-allergy safety emas.
• Agar inhibition zone antibiotikning klinik potenciesiga teng emas.
• FXH uchun haqiqiy pharmacological synergy combination-index usuli bilan ko‘rsatilmagan.
• Functional-food yoki nutraceutical mahsulot ishlab chiqilmagan.
• In vivo efficacy yoki human clinical trial o‘tkazilmagan.

Manba ichidagi muhim hisobot farqlari

Tadqiqotning asosiy kuchli tomonlari

Tadqiqot faqat bitta bioactivity assaydan foydalanmaydi. Ayni materialni:

• fermentation,
• molecular-weight fractionation,
• α-glucosidase inhibition,
• antibacterial testing,
• LC-HRMS peptidomics,
• general bioactivity prediction,
• toxicity prediction,
• allergenicity prediction,
• general antidiabetic prediction,
• type-2-specific prediction,
• multi-model antimicrobial prediction

qatlamlarida baholaydi.

Ushbu tuzilma bitta prediction modeliga tayanish o‘rniga candidate prioritization uchun turli dalil qatlamlarini yonma-yon qo‘yadi.

Asosiy cheklovlar

In vitro α-glukozidaza assay: Inson metabolizmini ifodalamaydi.

Agar diffusion: Inhibition zone diffusion propertydan ta’sirlanadi va MIC/MBC o‘rnini bosmaydi.

In silico prediction: Sequence-based prognozlar experimental validation talab qiladi.

Peptide purification: Ajralib turgan individual peptides ushbu tadqiqotda tozalanib alohida α-glukozidaza yoki antibacterial assay bilan tasdiqlangani ko‘rsatilmagan.

Bioavailability: O‘lchanmagan.

Gastrointestinal stability: O‘lchanmagan.

In vivo validation: Yo‘q.

Human clinical validation: Yo‘q.

Prediction disagreement: Bir xil sequence uchun model natijalari tez-tez farqlanadi.

Sequence/reporting inconsistencies: Table 3–5 va prose orasida ayrim sequence va model-score farqlari bor.

Synergy: FXHning pastroq IC50 qiymati kuzatilgan, biroq formal synergy analysis qilinmagan.

Kelgusi tadqiqotlar

Manbaning xulosa bo‘limi ayniqsa quyidagi tasdiqlashlarni talab qiladi:

• molecular interaction analysis,
• gastrointestinal stability,
• bioavailability,
• keyingi in vitro experiments,
• in vivo experiments.

Ushbu talablar mavjud natijalar candidate-discovery va preliminary bioactivity darajasida ekanini aniq chegaralaydi.

Manba va Usul Haqida Izoh

Asl tadqiqot: α-Glucosidase Inhibitory and Antibacterial Activity of Fermented Mackerel By-Product Muscle and Skin Hydrolysates: In Vitro and In Silico Peptidomics Analysis.

Mualliflar: Ariandi Ariandi, Dimas Andrianto, Apon Zaenal Mustopa, Anja Meryandini.

Mualliflar tartibi: Manba PDF va amaldagi rasmiy jurnal metadata tartibi saqlangan.

Teng hissa: Manbada equal-contribution bayonoti yo‘q.

Mas’ul muallif: Anja Meryandini.

Affiliatsiya 1: Doctoral Program in Microbiology, Department of Biology, Faculty of Mathematics and Natural Sciences, Bogor Agricultural University (IPB University), IPB Dramaga Campus, Bogor City 16680, Indonesia.

Affiliatsiya 2: Department of Biotechnology, Faculty of Mathematics and Natural Sciences, Universitas Sulawesi Barat, Majene, West Sulawesi 91412, Indonesia.

Affiliatsiya 3: Department of Biochemistry, Faculty of Mathematics and Natural Sciences, Bogor Agricultural University (IPB University), IPB Dramaga Campus, Bogor City 16680, Indonesia.

Affiliatsiya 4: Research Center for Genetic Engineering, National Research and Innovation Agency (BRIN), Bogor City 16680, Indonesia.

Affiliatsiya 5: Department of Biology, Faculty of Mathematics and Natural Sciences, Bogor Agricultural University (IPB University), IPB Dramaga Campus, Bogor City 16680, Indonesia.

Affiliatsiya 6: Biotechnology Research Center, Bogor Agricultural University (IPB University), IPB Dramaga Campus, Bogor City 16680, Indonesia.

Jurnal: HAYATI Journal of Biosciences.

Nashriyot tuzilmasi: Department of Biology, Bogor Agricultural University/IPB University va Indonesian Society for Biology.

Jild / son: Vol. 33 No. 6.

Sahifalar: 1423–1440.

DOI: 10.4308/hjb.33.6.1423-1440.

ISSN: 1978-3019.

EISSN: 2086-4094.

Manba turi: Research Article.

Taqriz: HAYATI Journal of Biosciences double-blind peer review qo‘llaydi; section editor kamida ikki scientistdan review so‘raydi.

Received: July 1, 2026.

Received in revised form: September 3, 2026.

Accepted: September 9, 2026.

PDF Available Online: October 1, 2026.

Rasmiy issue metadata Published: November 1, 2026.

Litsenziya: Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).

Preprint: Manba PDF yoki tasdiqlangan rasmiy maqola sahifasida alohida preprint qaydi ko‘rsatilmagan.

Baliq materiali: Scomberomorus commerson processing by-products; skin va mechanically damaged muscle tissues.

Namuna sanasi va joyi: January 2025; Muara Baru Fish Market, Penjaringan, Jakarta, Indonesia; 6°06′36″S, 106°48′06″E.

Fermentatsiya organizmi: Pediococcus pentosaceus IL13.

Tajriba guruhlari: FMH, FSH va FXH; FXH muscle+skin 1:1 (w/w).

Fermentatsiya yuklamasi: 10 g sample + 40 mL %10 (w/v) glucose solution + 400 μL starter culture.

Sterilizatsiya: 121°C, 15 daqiqa.

Fermentatsiya: Muscle va mixed samples 4 kun; skin sample 5 kun.

Hydrolysate separation: 14.000×g, 30 daqiqa, 4°C.

Ultrafiltration: 30, 10 va 3 kDa MWCO; 5.000×g, 30 daqiqa, 10°C.

Fractions: <30 kDa, <10 kDa, <3 kDa.

α-Glukozidaza: Saccharomyces cerevisiae source; Sigma Type I, ≥10 units/mg protein.

α-Glukozidaza assay: 50 μL sample + 30 μL phosphate buffer pH 6,8 + 60 μL pNPG + 60 μL enzyme; 37°C, 30 daqiqa.

Reaction stop: 60 μL 200 mM Na2CO3.

Absorbance: 405 nm.

pNP standard curve: 0–500 ppm; linear regression R²>0,99.

Positive control: Acarbose 100 ppm.

Negative control: Sterile distilled water.

IC50 concentration series: 10–50 mg/mL freeze-dried crude hydrolysates.

IC50 analysis: Nonlinear regression, GraphPad Prism 10.0.

FMH IC50: 46,541±1,228 mg/mL.

FSH IC50: 36,643±1,384 mg/mL.

FXH IC50: 34,692±1,355 mg/mL.

Antibacterial test: Agar-well diffusion.

Sinov bakteriyalari: Listeria monocytogenes, Enterococcus faecalis, Escherichia coli, Salmonella typhi.

Bacterial density: 0,5 McFarland ≈1×10⁸ CFU/mL.

Well diameter: 6 mm.

Hydrolysate volume: 100 μL/well.

Diffusion: Room temperature, 1 soat.

Incubation: 37°C, 24 soat.

Antibacterial replicates: Triplicate.

Antibacterial positive control: Chloramphenicol 100 ppm.

Antibacterial negative control: Sterile distilled water / Table 2 notation medium.

LC-HRMS sample: 100 mg freeze-dried hydrolysate.

Reduction: 10 μL 10 mM DTT, 56°C, 60 daqiqa.

Alkylation: 10 μL 20 mM IAA, qorong‘ida 60 daqiqa.

Digestion: Trypsin 0,1 mg/mL, 17 soat, 37°C.

UHPLC: Vanquish™ Horizon UHPLC.

Column: PepMap™ 100 C18, 150 mm × 1 mm, 3 μm.

Flow: 75 μL/min.

Column temperature: 30°C.

HRMS: Orbitrap Exploris 240, OptaMax™ NG H-ESI.

Acquisition: Positive mode, Full MS/dd-MS2.

Resolution: 120.000 Full MS; 15.000 MS2 FWHM.

Processing: Proteome Discoverer 2.5, SequestHT, UniProt va NCBI.

Quantification: Label-free quantification (LFQ).

Peptide pool: 211 identified sequences.

In silico selected set: 35 representative sequences.

Peptide length: 8–18 amino acids; aksariyati 10–14 residues.

General bioactivity: PeptideRanker.

Novelty: BIOPEP-UWM.

Toxicity: Methodda ToxinPred havolasi; Results/Table 3da ToxinPred3 nomi.

Allergenicity: pLM4Alg-640, AlgPred2, AllerCatPro 2.0.

General antidiabetic: AntiDMP-pred.

Type 2 antidiabetic: AntiT2DMP-Pred.

Antimicrobial prediction: CAMPR4, Antimicrobial Peptide Scanner v2, ADAM, AntiBP3.

Statistics: One-way ANOVA + Duncan's multiple range test, P<0,05.

Software: Microsoft Excel, GraphPad Prism, IBM SPSS Statistics version 27.

Funding: Center for Higher Education Funding and Assessment (PPAPT), Ministry of Higher Education, Science, and Technology of the Republic of Indonesia; Indonesian Endowment Fund for Education (LPDP), Ministry of Finance of the Republic of Indonesia; Indonesian Education Scholarship/BPI, Grant No. 00769/BPPT/BPI.06/9/2023, BPI ID 202327091759.

Acknowledgement: Genomic Laboratories va Taksa Laboratories, KST Cibinong, National Research and Innovation Agency (BRIN).

Data Availability: Manba PDFda alohida data-availability statement yo‘q.

Conflict of Interest: Manba PDFda alohida conflict-of-interest statement yo‘q.

CRediT / Author Contributions: Manba PDFda alohida author-contribution yoki CRediT bo‘limi yo‘q.

Ethical approval: Manbada alohida etik qo‘mita bayonoti yo‘q. Tadqiqotda qayd etilgan material bozordan olingan qayta ishlash yon mahsulotlari va kultura kolleksiyalaridan olingan mikroorganizmlardir; inson ishtirokchilari yoki tirik hayvonlarga aralashuv tajribasi qayd etilmagan.

Asosiy talqin chegarasi: α-glukozidaza inhibition va bacterial inhibition zones in vitro natijalardir; individual peptide bioactivity, toxicity, allergenicity, antidiabetic va antimicrobial natijalarining muhim qismi in silico predictiondir. Bular clinical efficacy yoki human safety natijasi emas.

Manba-ichki hisobot izohi 1: Figure 1 Results oralig‘i taxminan %61,97–79,09 deb berilgan bo‘lsa, ayni paragraf FMH <3 kDa uchun taxminan %79,45ni bildiradi.

Manba-ichki hisobot izohi 2: Prose “two peptides” desa-da, Table 3 va ayni jumladagi ketma-ketliklar uch toxic-predicted peptidni ko‘rsatadi.

Manba-ichki hisobot izohi 3: Table 3–4 va prose orasida ayrim peptide sequence transcription farqlari bor.

Manba-ichki hisobot izohi 4: Table 5 CAMPR4 headerida uchinchi algorithm “SVM” deb bosilgan; metod, Results va footnote uchinchi model ANN ekanini ko‘rsatadi.

Manba-ichki hisobot izohi 5: SPAMPVPGPMGPMGPR peptide number bir Results jumlasida 23 sifatida ko‘rinadi, boshqa source context esa peptide 28ni qo‘llab-quvvatlaydi.

Manba-ichki hisobot izohi 6: AVFPSIVGRPR uchun Table 5 va prosedagi ayrim antimicrobial prediction score mosliklari bir-biriga to‘g‘ri kelmaydi.

Kelgusi tasdiqlashlar: Molecular interaction analysis, gastrointestinal stability, bioavailability, keyingi in vitro va in vivo experiments.