A folding study on IAPP (Islet Amyloid Polypeptide) using molecular dynamics simulations

Carlsson, JonasLinköpings universitet,Bioinformatik,Tekniska högskolan (författare)

Amyloidosis is the largest group among the protein misfolding diseases, and includes well known diseases such as Alzheimer’s disease and type 2 diabetes. In the latter, islet amyloid is present in the pancreas in almost all individuals. Today, more than 25 different proteins have been isolated from amyloid deposits in human. Even though these proteins differ in size, charge and sequence they all have the capacity to assemble in to fibrillar structures with inseparable morphological appearance. Therefore, it can be assumed that the fibril process is based upon principles that are general for all proteins and knowledge derived from one protein can be used for other amyloid proteins. In this paper, we study the process of amyloid formation in parts of islet amyloid polypeptide (residues 18-29 and 11-37) by analyzing mutations using three different in silico methods. Finally, we use the methods to predict the amyloidogenic properties of the native IAPP and 16 variants thereof and compare the result with in vitro measurements. Using a consensus prediction of the three methods we managed to correctly classify all but two peptides. We have also given further evidence to the importance of S28P for inhibiting amyloid fibre formation, found evidence for antiparallel stacking, and identified important regions for beta sheet stability.

Vahdat Shariatpanahi, AidaLandstinget i Östergötland (författare)
Schultz, SebastianLinköpings universitet,Cellbiologi,Hälsouniversitetet(Swepub:liu)sebsc19 (författare)
Westermark, GunillaLinköpings universitet,Cellbiologi,Hälsouniversitetet(Swepub:liu)gunwe13 (författare)
Persson, BengtLinköpings universitet,Bioinformatik,Tekniska högskolan(Swepub:liu)benpe05 (författare)
Linköpings universitetBioinformatik (creator_code:org_t)

Av författaren/redakt...: Carlsson, Jonas; Vahdat Shariatpa ...; Schultz, Sebasti ...; Westermark, Guni ...; Persson, Bengt

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.