Analiza peptida iz hrane

The aim of this review is to discuss the definition of food peptidomics and highlight the role of this approach in food and nutrition sciences. Similar to living organisms, food peptidome may be defined as the whole peptide pool present in a food product or raw material. This definition also covers peptides obtained during technological processes and/or storage. The area of interest of food peptidomics covers research concerning the origin of peptidome, its dynamic changes during processing and/or storage, the influence of its presence, the composition and changes in the pool of peptides on the properties of food products or raw materials as well as the methods applied in research into this group of compounds. The area of interests of food peptidomics would include biological activity, functional properties, allergenicity, sensory properties and information on the product or resource authenticity and origin as well as its history and relationships. Research methods applied in food peptidomics, with special emphasis on computational methods, are also summarized.Ovaj revijalni prikaz razmatra definiciju pojma „food peptidomics“, tj. istraživanje peptida iz hrane i njihovu ulogu u prehrambenoj tehnologiji i nutricionizmu. Slično živim organizmima, „peptidome“ hrane obuhvaća sve peptide u prehrambenom proizvodu ili sirovini, a i one proizvedene tijekom prerade i/ili njihova skladištenja. Ova grana znanosti obuhvaća istraživanje podrijetla peptida, dinamičnosti njihove promjene pri preradi i/ili skladištenju, utjecaja peptida, njihova sastava i promjene sastava na svojstva prehrambenih proizvoda i sirovina, te metode istraživanja. To uključuje ispitivanje njihove biološke aktivnosti, funkcionalnih, alergenskih i senzorskih svojstava, informacije o autentičnosti i porijeklu proizvoda ili izvora, te povijesni razvoj i odnose. U radu su opisane metode istraživanja peptida, s posebnim naglaskom na računske metode

Analiza peptida iz hrane

The aim of this review is to discuss the definition of food peptidomics and highlight the role of this approach in food and nutrition sciences. Similar to living organisms, food peptidome may be defined as the whole peptide pool present in a food product or raw material. This definition also covers peptides obtained during technological processes and/or storage. The area of interest of food peptidomics covers research concerning the origin of peptidome, its dynamic changes during processing and/or storage, the influence of its presence, the composition and changes in the pool of peptides on the properties of food products or raw materials as well as the methods applied in research into this group of compounds. The area of interests of food peptidomics would include biological activity, functional properties, allergenicity, sensory properties and information on the product or resource authenticity and origin as well as its history and relationships. Research methods applied in food peptidomics, with special emphasis on computational methods, are also summarized.Ovaj revijalni prikaz razmatra definiciju pojma „food peptidomics“, tj. istraživanje peptida iz hrane i njihovu ulogu u prehrambenoj tehnologiji i nutricionizmu. Slično živim organizmima, „peptidome“ hrane obuhvaća sve peptide u prehrambenom proizvodu ili sirovini, a i one proizvedene tijekom prerade i/ili njihova skladištenja. Ova grana znanosti obuhvaća istraživanje podrijetla peptida, dinamičnosti njihove promjene pri preradi i/ili skladištenju, utjecaja peptida, njihova sastava i promjene sastava na svojstva prehrambenih proizvoda i sirovina, te metode istraživanja. To uključuje ispitivanje njihove biološke aktivnosti, funkcionalnih, alergenskih i senzorskih svojstava, informacije o autentičnosti i porijeklu proizvoda ili izvora, te povijesni razvoj i odnose. U radu su opisane metode istraživanja peptida, s posebnim naglaskom na računske metode

BIOPEP-PBIL alat za analizu biološki aktivnih motiva, izdvojenih iz proteina hrane

This work describes a flexible technique for the analysis of protein sequences as a source of motifs affecting bodily functions. The BIOPEP database, along with the Pôle Bioinformatique Lyonnais (PBIL) server, were applied to define which activities of peptides dominated in their protein precursors and which structure of the protein contained the most of the revealed activities. Such an approach could be helpful in finding some structural requirements for peptide(s) to be regarded as biologically active (bioactive). It was found that apart from the activities of peptides that commonly occur in the majority of proteins (e.g. ACE inhibitors), all analyzed proteins can be a source of motifs involved in e.g. activation of ubiquitin-mediated proteolysis. This could be important in designing diets for patients who suffer from neural diseases. The structure and bioactivity analyses revealed that if peptides were to be \u27bioactive\u27, it is essential that they assume the position of a coil (or combination of coil and a-helix) in the sequence of their protein precursors. However, it is recommended to consider the factors such as the length of peptide chains, the number of peptides in the database as well as the repeatability of the occurrence of characteristic amino acids, both in the peptide and in the protein when studying the bioactivity and structure of biomolecules.U radu je opisana prilagodljiva tehnika analize sekvencije proteina koji sadrže motive što utječu na funkcije organizma. BIOPEP baza podataka i Pôle Bioinformatique Lyonnais (PBIL) server upotrijebljeni su da bi se odredile aktivnosti peptida što prevladavaju u prekurzorima proteina, te koje strukture proteina imaju najveću aktivnost. Takav bi pristup mogao pomoći u otkrivanju strukturnih značajka koje pridonose biološkoj aktivnosti peptida. Utvrđeno je da ispitani proteini, osim što pokazuju aktivnost uobičajenu za većinu proteina (npr. inhibiraju acetilkolinesterazu), mogu sadržavati motive koji sudjeluju u ubikvitin-ovisnoj proteolizi. To bi moglo biti važno za određivanje prehrane bolesnika koji pate od neuroloških poremećaja. Analizom strukture i biološke aktivnosti uočeno je da bioaktivni peptidi moraju imati konformaciju uzvojnice (ili kombinaciju uzvojnice i α-ploče) u sekvencijama prekurzora proteina da bi imali to svojstvo. Međutim, pri proučavanju bioaktivnosti i strukture biomolekula treba uzeti u obzir i duljinu peptidnih lanaca, broj peptida u bazi podataka, te ponovljivost karakterističnih aminokiselina u peptidu i proteinu

In silico ispitivanje biljnih i životinjskih proteina kao prekurzora inhibitora angiotenzin konvertirajućeg enzima

This paper presents a modern in silico approach useful in the evaluation of proteins as a source of ACE inhibitors. All protein sequences analyzed were derived from the BIOPEP database. To determine the protein value, the following criteria of evaluation were applied: the profile of potential biological (ACE inhibitory) activity of a protein, the frequency of the occurrence of fragments with ACE inhibitory activity (A) and the potential biological activity of a protein (B). The results, based on a statistical analysis, indicate that milk proteins can be a better source of ACE inhibitors than wheat gliadins. Moreover, all analyzed gliadins possessed more potent ACE inhibitors than chicken meat proteins. No significant differences were observed when comparing A values between soy globulins and β-lactoglobulins. Although criteria such as the profile of potential biological activity of protein, as well as parameters A and B, can be suitable tools in protein evaluation, the proteolytic digestion of protein needs to be considered. Moreover, computerised methods of classifying proteins according to different algorithms are often subjective due to discretion in interpretation of the results.U ovom je radu prikazan suvremen in silico pristup ispitivanju proteinskih izvora inhibitora angiotenzin konvertirajućeg enzima (engl. angiotensin-converting enzyme - ACE). Sve ispitane sekvencije proteina izvađene su iz BIOPEP baze podataka, te procijenjene njihove vrijednosti prema ovim kriterijima: profil biološke aktivnosti proteina inhibitora ACE, učestalost pojave fragmenata koji inhibiraju ACE (A) i biološka aktivnost proteina (B). Rezultati dobiveni statističkom analizom pokazuju da su proteini mlijeka bolji izvor inhibitora ACE od glijadina pšenice. Svi ispitani glijadini sadrže jače inhibitore ACE od proteina piletine. Nije utvrđena značajna razlika između A vrijednosti globulina soje i β-laktoglobulina. Profil biološke aktivnosti te A i B vrijednosti mogu poslužiti kao alat za ispitivanje proteina, ali treba razmotriti i njihovu proteolitičku razgradnju. Valja imati na umu da kompjutorizirane metode klasifikacije proteina prema različitim algoritmima često mogu dati subjektivne rezultate

Programi i baze podataka o peptidima i proteolitičkim enzimima na internetu – kratak osvrt na 2007. i 2008. godinu

Bioinformatics methods have become one of the most important tools in peptide science. The number of available peptide databases is growing rapidly. The number of online programs able to process peptide sequences to extract information concerning their structure, physicochemical and biological properties is also increasing. Many of such programs were designed to manipulate protein sequences, but they have no built-in restrictions disabling their application to process oligopeptides containing less than 20 amino acid residues. Publications addressing these programs cannot be found in literature databases using the keyword \u27peptide\u27 or \u27peptides\u27, in connection with the term \u27bioinformatics\u27 or related terms, thus a reference source summarizing data from such publications seems necessary. This paper provides a brief review of bioactive peptide databases and sequence alignment programs enabling the search for peptide motifs, determination of physicochemical properties of amino acid residues, prediction of peptide structure, the occurrence of posttranslational glycosylation and immunogenicity, as well as the support of peptide design process. The review also includes databases and programs providing information about proteolytic enzymes. The databases and programs discussed in this paper were developed or updated between September 2007 and December 2008.Bioinformatičke metode postale su jedan od najvažnijih alata u području istraživanja peptida. Sve je veći broj dostupnih baza podataka o peptidima, a i „online” programa koji obradom aminokiselinskih sljedova daju informacije o strukturi peptida te njihovim fizikalno-kemijskim i biološkim svojstvima. Mnogi od tih programa dizajnirani su za obradu aminokiselinskih sljedova proteina, ali nemaju ugrađenu restrikciju njihove primjene na oligopeptide koji sadrže manje od 20 aminokiselinskih ostataka. Radovi o takvim programima ne mogu se pronaći u bazama publikacija uporabom ključnih riječi „peptid” ili „peptidi”, u kombinaciji s pojmom „bioinformatika” ili sličnim terminima. Stoga je važno sažeti rezultate objavljenih radova u jednom izvoru. U ovom je radu dan kratak pregled baza podataka o bioaktivnim peptidima i programima za analizu aminokiselinskoga slijeda koji omogućuju: pronalazak peptidnih motiva; određivanje fizikalno-kemijskih svojstava aminokiselinskih ostataka; predviđanje strukture peptida, pojave posttranslacijske glikozilacije i imunogenosti; te programsku podršku za dizajn peptida. Također su prikazani programi i baze podataka o proteolitičkim enzimima. Svi navedeni programi i baze razvijeni su i ažurirani od rujna 2007. do prosinca 2008

Czynniki ryzyka rozwoju migotania przedsionków, nie zawsze ciężkiej i nie zawsze izolowanej choroby serca

Dotychczas nie poznano dokładnych mechanizmów wpływających na powstanie migotania przedsionków (AF). Każdorazowo klinicysta musi sobie odpowiedzieć na pytanie, czy ma do czynienia z izolowanym AF czy wywołanym innymi zamaskowanymi zaburzeniami. Migotanie przedsionków ma bowiem silne związki epidemiologiczne z innymi chorobami sercowo-naczyniowymi, takimi jak niewydolność serca, choroba wieńcowa, wady zastawkowe, cukrzyca czy nadciśnienie tętnicze. W pracy omówiono tak zwane nowe czynniki ryzyka i mechanizmy, w wyniku których prowadzą one do powstania migotania przedsionków. Na podstawie najnowszych badań zaprezentowano obecny stan wiedzy o związku występowania AF z następującymi zaburzeniami: zespołem metabolicznym i jego składowymi, bezdechem sennym oraz procesem zapalnym. Opisano również niektóre aspekty wpływu stylu życia (spożycie alkoholu i aktywność fizyczna) na pojawianie się epizodów migotania przedsionków. (Folia Cardiologica Excerpta 2010; 5, 5: 285-291

BIOPEP-PBIL Tool for the Analysis of the Structure of Biologically Active Motifs Derived from Food Proteins

This work describes a flexible technique for the analysis of protein sequences as a source of motifs affecting bodily functions. The BIOPEP database, along with the Pôle Bioinformatique Lyonnais (PBIL) server, were applied to define which activities of peptides dominated in their protein precursors and which structure of the protein contained the most of the revealed activities. Such an approach could be helpful in finding some structural requirements for peptide(s) to be regarded as biologically active (bioactive). It was found that apart from the activities of peptides that commonly occur in the majority of proteins (e.g. ACE inhibitors), all analyzed proteins can be a source of motifs involved in e.g. activation of ubiquitin-mediated proteolysis. This could be important in designing diets for patients who suffer from neural diseases. The structure and bioactivity analyses revealed that if peptides were to be 'bioactive', it is essential that they assume the position of a coil (or combination of coil and a-helix) in the sequence of their protein precursors. However, it is recommended to consider the factors such as the length of peptide chains, the number of peptides in the database as well as the repeatability of the occurrence of characteristic amino acids, both in the peptide and in the protein when studying the bioactivity and structure of biomolecules

Animal and Plant Proteins as Precursors of Peptides with ACE Inhibitory Activity – An in silico Strategy of Protein Evaluation

This paper presents a modern in silico approach useful in the evaluation of proteins as a source of ACE inhibitors. All protein sequences analyzed were derived from the BIOPEP database. To determine the protein value, the following criteria of evaluation were applied: the profile of potential biological (ACE inhibitory) activity of a protein, the frequency of the occurrence of fragments with ACE inhibitory activity (A) and the potential biological activity of a protein (B). The results, based on a statistical analysis, indicate that milk proteins can be a better source of ACE inhibitors than wheat gliadins. Moreover, all analyzed gliadins possessed more potent ACE inhibitors than chicken meat proteins. No significant differences were observed when comparing A values between soy globulins and β-lactoglobulins. Although criteria such as the profile of potential biological activity of protein, as well as parameters A and B, can be suitable tools in protein evaluation, the proteolytic digestion of protein needs to be considered. Moreover, computerised methods of classifying proteins according to different algorithms are often subjective due to discretion in interpretation of the results

Food Peptidomics

The aim of this review is to discuss the definition of food peptidomics and highlight the role of this approach in food and nutrition sciences. Similar to living organisms, food peptidome may be defined as the whole peptide pool present in a food product or raw material. This definition also covers peptides obtained during technological processes and/or storage. The area of interest of food peptidomics covers research concerning the origin of peptidome, its dynamic changes during processing and/or storage, the influence of its presence, the composition and changes in the pool of peptides on the properties of food products or raw materials as well as the methods applied in research into this group of compounds. The area of interests of food peptidomics would include biological activity, functional properties, allergenicity, sensory properties and information on the product or resource authenticity and origin as well as its history and relationships. Research methods applied in food peptidomics, with special emphasis on computational methods, are also summarized

Online Programs and Databases of Peptides and Proteolytic Enzymes – A Brief Update for 2007–2008

Bioinformatics methods have become one of the most important tools in peptide science. The number of available peptide databases is growing rapidly. The number of online programs able to process peptide sequences to extract information concerning their structure, physicochemical and biological properties is also increasing. Many of such programs were designed to manipulate protein sequences, but they have no built-in restrictions disabling their application to process oligopeptides containing less than 20 amino acid residues. Publications addressing these programs cannot be found in literature databases using the keyword 'peptide' or 'peptides', in connection with the term 'bioinformatics' or related terms, thus a reference source summarizing data from such publications seems necessary. This paper provides a brief review of bioactive peptide databases and sequence alignment programs enabling the search for peptide motifs, determination of physicochemical properties of amino acid residues, prediction of peptide structure, the occurrence of posttranslational glycosylation and immunogenicity, as well as the support of peptide design process. The review also includes databases and programs providing information about proteolytic enzymes. The databases and programs discussed in this paper were developed or updated between September 2007 and December 2008