Structural analysis of the Aβ(15-40) amyloid fibril based on hydrophobicity distribution

The Aβ42 amyloid is the causative factor behind various neurodegenerative processes. It forms elongated fibrils which cause structural devastation in brain tissue. The structure of an amyloid seems to be a contradiction of protein folding principles. Our work focuses on the Aβ(15-40) amyloid containing the D23N mutation (also known as the “Iowa mutation”), upon which an in silico experiment is based. Models generated using I-Tasser software as well as the fuzzy oil drop model – regarded as alternatives to the amyloid conformation – are compared in terms of their respective distributions of hydrophobicity (i.e. the existence of a hydrophobic core). In this process, fuzzy oil drop model parameters are applied in assessing the propensity of selected fragments for undergoing amyloid transformation.

Download Full-text

Faculty Opinions recommendation of Conformational strain in the hydrophobic core and its implications for protein folding and design.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1007518.94555 ◽

2002 ◽

Author(s):

Laura Itzhaki

Keyword(s):

Protein Folding ◽

Hydrophobic Core

Download Full-text

In Silico Structural Modeling and Analysis of Interactions of Tremellomycetes Cytochrome P450 Monooxygenases CYP51s with Substrates and Azoles

International Journal of Molecular Sciences ◽

10.3390/ijms22157811 ◽

2021 ◽

Vol 22 (15) ◽

pp. 7811

Author(s):

Olufunmilayo Olukemi Akapo ◽

Joanna M. Macnar ◽

Justyna D. Kryś ◽

Puleng Rosinah Syed ◽

Khajamohiddin Syed ◽

...

Keyword(s):

Cytochrome P450 ◽

Structural Analysis ◽

In Silico ◽

Web Application ◽

Cytochrome P450 Monooxygenases ◽

Agglomerative Clustering ◽

Ligand Complex ◽

P450 Monooxygenase ◽

Study Results

Cytochrome P450 monooxygenase CYP51 (sterol 14α-demethylase) is a well-known target of the azole drug fluconazole for treating cryptococcosis, a life-threatening fungal infection in immune-compromised patients in poor countries. Studies indicate that mutations in CYP51 confer fluconazole resistance on cryptococcal species. Despite the importance of CYP51 in these species, few studies on the structural analysis of CYP51 and its interactions with different azole drugs have been reported. We therefore performed in silico structural analysis of 11 CYP51s from cryptococcal species and other Tremellomycetes. Interactions of 11 CYP51s with nine ligands (three substrates and six azoles) performed by Rosetta docking using 10,000 combinations for each of the CYP51-ligand complex (11 CYP51s × 9 ligands = 99 complexes) and hierarchical agglomerative clustering were used for selecting the complexes. A web application for visualization of CYP51s’ interactions with ligands was developed (http://bioshell.pl/azoledocking/). The study results indicated that Tremellomycetes CYP51s have a high preference for itraconazole, corroborating the in vitro effectiveness of itraconazole compared to fluconazole. Amino acids interacting with different ligands were found to be conserved across CYP51s, indicating that the procedure employed in this study is accurate and can be automated for studying P450-ligand interactions to cater for the growing number of P450s.

Download Full-text

Protein Folding and Recognition in the Cell -- an in Silico Approach

Biophysical Journal ◽

10.1016/j.bpj.2014.11.2031 ◽

2015 ◽

Vol 108 (2) ◽

pp. 370a

Author(s):

Margaret S. Cheung

Keyword(s):

Protein Folding ◽

In Silico

Download Full-text

Models of cooperativity in protein folding

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.1995.0046 ◽

1995 ◽

Vol 348 (1323) ◽

pp. 61-70 ◽

Cited By ~ 76

Keyword(s):

Protein Folding ◽

Molten Globule ◽

Core Collapse ◽

Hydrophobic Core ◽

Model Studies ◽

Helix Formation ◽

Collapse Model ◽

Folding Pathways ◽

State Behaviour ◽

Denatured States

What is the basis for the two-state cooperativity of protein folding? Since the 1950s, three main models have been put forward. 1. In ‘helix-coil’ theory, cooperativity is due to local interactions among near neighbours in the sequence. Helix-coil cooperativity is probably not the principal basis for the folding of globular proteins because it is not two-state, the forces are weak, it does not account for sheet proteins, and there is no evidence that helix formation precedes the formation of a hydrophobic core in the folding pathways. 2. In the ‘sidechain packing’ model, cooperativity is attributed to the jigsaw-puzzle-like complementary fits of sidechains. This too is probably not the basis of folding cooperativity because exact models and experiments on homopolymers with sidechains give no evidence that sidechain freezing is two-state, sidechain complementarities in proteins are only weak trends, and the molten globule model predicted by this model is far more native-like than experiments indicate. 3. In the ‘hydrophobic core collapse’ model, cooperativity is due to the assembly of non-polar residues into a good core. Exact model studies show that this model gives two-state behaviour for some sequences of hydrophobic and polar monomers. It is based on strong forces. There is considerable experimental evidence for the kinetics this model predicts: the development of hydrophobic clusters and cores is concurrent with secondary structure formation. It predicts compact denatured states with sizes and degrees of disorder that are in reasonable agreement with experiments.

Download Full-text

The Formation of Hydrophobic Core Regulates the Protein Folding of Villin Elucidated with Parallel Cascade Selection Molecular Dynamics

Chemistry Letters ◽

10.1246/cl.180596 ◽

2018 ◽

Vol 47 (10) ◽

pp. 1300-1303

Author(s):

Ryuhei Harada ◽

Hayato Aida ◽

Yasuteru Shigeta

Keyword(s):

Molecular Dynamics ◽

Protein Folding ◽

Hydrophobic Core

Download Full-text

An OGI model for personalized estimation of glucose and insulin concentration in plasma

Mathematical Biosciences and Engineering ◽

10.3934/mbe.2021420 ◽

2021 ◽

Vol 18 (6) ◽

pp. 8499-8523

Author(s):

Weijie Wang ◽

◽

Shaoping Wang ◽

Yixuan Geng ◽

Yajing Qiao ◽

...

Keyword(s):

Kalman Filtering ◽

Gaussian Noise ◽

Particle Filtering ◽

In Silico ◽

Insulin Concentration ◽

Model Parameters ◽

Bayesian Filtering ◽

Extended Kalman Filtering ◽

External Disturbances ◽

Non Gaussian

<abstract><p>Plasma glucose concentration (PGC) and plasma insulin concentration (PIC) are two essential metrics for diabetic regulation, but difficult to be measured directly. Often, PGC and PIC are estimated from continuous glucose monitoring and insulin delivery data. Nevertheless, the inter-individual variability and external disturbance (e.g. carbohydrate intake) bring challenges for accurate estimations. This study is to estimate PGC and PIC adaptively by identifying personalized parameters and external disturbances. An observable glucose-insulin (OGI) dynamic model is established to describe insulin absorption, glucose regulation, and glucose transport. The model parameters and disturbances can be extended to observable state variables and be identified dynamically by Bayesian filtering estimators. Two basic Gaussian noise based Bayesian filtering estimators, extended Kalman filtering (EKF) and unscented Kalman filtering (UKF), are implemented. Recognizing the prevalence of non-Gaussian noise, in this study, two new filtering estimators: particle filtering with Gaussian noise (PFG), and particle filtering with mixed non-Gaussian noise (PFM) are designed and implemented. The proposed OGI model in conjunction with the estimators is evaluated using the data from 30 in-silico subjects and 10 human participants. For in-silico subjects, the OGI with PFM estimator has the ability to estimate PIC and PGC adaptively, achieving RMSE of PIC $ 9.49\pm3.81 $ mU/L, and PGC $ 0.89\pm0.19 $ mmol/L. For human, the OGI with PFM has the promise to identify disturbances ($ 95.46\%\pm0.65\% $ accurate rate of meal identification). OGI model provides a way to fully personalize the parameters and external disturbances in real time, and has potential clinical utility for artificial pancreas.</p></abstract>

Download Full-text