Protein aggregation: in silico algorithms and applications

Prabakaran, R.; Rawat, Puneet; Thangakani, A. Mary; Kumar, Sandeep; Gromiha, M. Michael

doi:10.1007/s12551-021-00778-w

Cited by 45 publications

(31 citation statements)

References 167 publications

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“…These algorithms have utilized sequence and structure-based properties such as patterns of hydrophobic and polar residues, β-strand propensity, charge, ability to form cross-β motif, aggregation propensity scales determined from experimental data, solvent-exposed hydrophobic patches on molecular surface and so on. Advantages and limitations of these algorithms have been reviewed elsewhere 14 . A common wisdom emerging from these studies is that the presence of an aggregation-prone region (APR) may be a necessary but not sufficient condition for protein aggregation to occur.…”

Section: Introductionmentioning

confidence: 99%

Exploring the sequence features determining amyloidosis in human antibody light chains

Rawat

Prabakaran

Kumar

et al. 2021

Sci Rep

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The light chain (AL) amyloidosis is caused by the aggregation of light chain of antibodies into amyloid fibrils. There are plenty of computational resources available for the prediction of short aggregation-prone regions within proteins. However, it is still a challenging task to predict the amyloidogenic nature of the whole protein using sequence/structure information. In the case of antibody light chains, common architecture and known binding sites can provide vital information for the prediction of amyloidogenicity at physiological conditions. Here, in this work, we have compared classical sequence-based, aggregation-related features (such as hydrophobicity, presence of gatekeeper residues, disorderness, β-propensity, etc.) calculated for the CDR, FR or VL regions of amyloidogenic and non-amyloidogenic antibody light chains and implemented the insights gained in a machine learning-based webserver called “VLAmY-Pred” (https://web.iitm.ac.in/bioinfo2/vlamy-pred/). The model shows prediction accuracy of 79.7% (sensitivity: 78.7% and specificity: 79.9%) with a ROC value of 0.88 on a dataset of 1828 variable region sequences of the antibody light chains. This model will be helpful towards improved prognosis for patients that may likely suffer from diseases caused by light chain amyloidosis, understanding origins of aggregation in antibody-based biotherapeutics, large-scale in-silico analysis of antibody sequences generated by next generation sequencing, and finally towards rational engineering of aggregation resistant antibodies.

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Section: Introductionmentioning

confidence: 99%

Exploring the sequence features determining amyloidosis in human antibody light chains

Rawat

Prabakaran

Kumar

et al. 2021

Sci Rep

Self Cite

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“…As a starting point to uncover possible physical explanations for the dependence on even/odd spacing, we analyzed representative sequences -- 60:Q 3 N, 60:Q 4 N, 60:Q 5 N, 60:Q, 60:N -- with state-of-the-art amyloid predictors (Charoenkwan et al, 2021; Keresztes et al, 2021; Prabakaran et al, 2021). Using their respective default parameters, we found that most predictors failed entirely to detect amyloid propensity among these sequences.…”

Section: Resultsmentioning

confidence: 99%

The polyglutamine amyloid nucleus in living cells is a monomer with competing dimensions of order

Kandola

Zhang

Venkatesan

et al. 2021

Preprint

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A long-standing goal of the study of amyloids has been to characterize the physical nature of the rate-determining nucleating event. However, the transience and rarity of that event within the heterogeneous ensemble of states populated by amyloid-forming proteins make it inaccessible to classical biochemistry, structural biology, and computational approaches. Here, we address these limitations by measuring the dependence of amyloid formation on concentration and conformational templates in living cells, whose volumes are sufficiently small to resolve independent nucleation events. We characterized over one hundred rationally designed sequence variants of polyglutamine (polyQ), a polypeptide that precipitates Huntingtons and other amyloid-associated neurodegenerative diseases when its length exceeds a characteristic threshold. We deduce that amyloid formation by polyQ begins with a steric zipper embryo of approximately twelve interdigitated glutamine side chains within an individual polypeptide molecule. Formation of the embryo was limited to polypeptides longer than the pathogenic threshold, and involved neither phase separation nor oligomerization. We found that different amyloid propensities of polyQ sequence variants can be rationalized by steric zipper ordering orthogonally to the axis of polymerization, and validated this intuition using all-atom molecular dynamics simulations. The unique ability of the polyQ sequence to fold in this fashion not only allowed for polyQ amyloid to nucleate from low concentrations; it also stalled amyloid growth with a concomitant accumulation of partially-ordered oligomers. By illuminating the structural mechanism of polyQ amyloid formation in cells, our findings reveal a potential molecular etiology for polyQ diseases, and may provide a roadmap for the design of new therapies.

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“…This is attributed to the highly heterogeneous and dynamic structural states of proteins in their aggregation-prone states ( Kelly, 1996 ; Yang et al, 2021 ). To overcome these challenges, NMR spectroscopy ( Daskalov et al, 2021 ; Dyson and Wright, 2021 ) and MD simulation techniques ( Prabakaran et al, 2021 ; Strodel, 2021 ) are the two major methodologies that significantly contributed to advancing our understanding of the aggregation and amyloidosis mechanisms of various proteins. Indeed, NMR spectroscopy has been a major technique for investigating the mobile structural features of IDPs and amyloidogenic proteins, such as amyloid beta ( Crescenzi et al, 2002 ), tau ( Mukrasch et al, 2009 ), and α-synuclein ( Ulmer et al, 2005 ).…”

Section: Discussionmentioning

confidence: 99%

Aggregation-Prone Structural Ensembles of Transthyretin Collected With Regression Analysis for NMR Chemical Shift

Yang

Kim

Muniyappan

et al. 2021

Front. Mol. Biosci.

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Monomer dissociation and subsequent misfolding of the transthyretin (TTR) is one of the most critical causative factors of TTR amyloidosis. TTR amyloidosis causes several human diseases, such as senile systemic amyloidosis and familial amyloid cardiomyopathy/polyneuropathy; therefore, it is important to understand the molecular details of the structural deformation and aggregation mechanisms of TTR. However, such molecular characteristics are still elusive because of the complicated structural heterogeneity of TTR and its highly sensitive nature to various environmental factors. Several nuclear magnetic resonance (NMR) spectroscopy and molecular dynamics (MD) studies of TTR variants have recently reported evidence of transient aggregation-prone structural states of TTR. According to these studies, the stability of the DAGH β-sheet, one of the two main β-sheets in TTR, is a crucial determinant of the TTR amyloidosis mechanism. In addition, its conformational perturbation and possible involvement of nearby structural motifs facilitates TTR aggregation. This study proposes aggregation-prone structural ensembles of TTR obtained by MD simulation with enhanced sampling and a multiple linear regression approach. This method provides plausible structural models that are composed of ensemble structures consistent with NMR chemical shift data. This study validated the ensemble models with experimental data obtained from circular dichroism (CD) spectroscopy and NMR order parameter analysis. In addition, our results suggest that the structural deformation of the DAGH β-sheet and the AB loop regions may correlate with the manifestation of the aggregation-prone conformational states of TTR. In summary, our method employing MD techniques to extend the structural ensembles from NMR experimental data analysis may provide new opportunities to investigate various transient yet important structural states of amyloidogenic proteins.

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Protein aggregation: in silico algorithms and applications

Cited by 45 publications

References 167 publications

Exploring the sequence features determining amyloidosis in human antibody light chains

Exploring the sequence features determining amyloidosis in human antibody light chains

The polyglutamine amyloid nucleus in living cells is a monomer with competing dimensions of order

Aggregation-Prone Structural Ensembles of Transthyretin Collected With Regression Analysis for NMR Chemical Shift

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