1,721,016 research outputs found
Performances evaluation of selected web tools predicting changes in protein stability
No full textMotivation
The prediction on how a mutation can affect protein thermodynamic stability is a hard task for computational biology. Despite decades of research and so many predictors developed on purpose, there are still doubts about the reliability of their results. The issues can be ascribed both to the paucity of high quality and reliable data for the creation of a reference database, and to the different approaches developed so far to cope with this task [1]. In this work, we present the assessment we applied to five predictors available online, representing different approaches, and using a reference database of high-quality structures.
Methods
The predictors assessed were: INPS-3D [2], a machine-learning method tailored to face the problem of anti-symmetric property; PoPMuSiC [3], a method using a linear combination of statistical potentials, tailored to correct the bias toward destabilizing mutations; DynaMut [4], one of the most recent web servers developed, based on Normal Mode to take into account the contribution of protein flexibility; MAESTROweb [5], the only web server able to manage both multimeric proteins and compound heterozygous multiple mutations; DUET [6], a consensus predictor combining two other predictors previously developed by the same research group. Starting from VariBench dataset [7], we performed a filtering based on the selection of high-quality reference proteins, in terms of thermodynamic experimental data and quality of the structures associated to them. We created a balanced dataset for number and ΔΔG distribution of destabilizing and stabilizing mutations, in order to evaluate the bias of predictors with respect to abovementioned issue. Finally, we divided the monomeric proteins from the multimeric ones, and assessed separately the predictions made on these two groups, considering that most predictors are not able to handle directly multimeric proteins. To assess the reliability of the predictors, we evaluated if the sign of the ΔΔG predicted by the different tools was in agreement with the sign of the experimental measure associated to the same mutation, and we calculated several statistical parameters to compare the performances of the prediction methods. We computed all the statistics in R language.
Results
Our analysis shows that, although there have been improvements in this field over time, the performances of the assessed predictors are still far from an ideal condition. The most frequent problem detected is a bias towards destabilizing mutations, even in predictors in which this issue is claimed to be solved. Additionally, when the mutation causes a ΔΔG within the interval ±0.5 kcal/mol (generally accepted as the interval error for the measurement of this parameter), the predicted results are generally less reliable than those predicted for mutations causing a ΔΔG outside that interval. Finally, we found that a rough but effective way to increase the reliability of the predictors is the combination of their results into a consensus parameter, based principally on the prediction of the sign of ΔΔG.
For these reasons, we suggest to developers to consider in the future the usage of balanced data sets for training their future predictors, and to define the effect of a mutation on the stability of the protein as "uncertain" when its predicted ΔΔG falls within the range ±0.5 kcal/mol. Furthermore, we suggest to users to combine the results of multiple tools, in order to increase the chances of having correct predictions about the effect of mutations on the thermodynamic stability of a protein.
References
[1] Marabotti A, Scafuri B, Facchiano A. Brief Bioinform. 2020; epub ahead of print. doi: 10.1093/bib/bbaa074
[2] Savojardo C, Fariselli P, Martelli PL, Casadio R. Bioinformatics 2016;32: 2542–2544.
[3] Pucci F, Bernaerts KV, Kwasigroch JM, Rooman M. Bioinformatics 2018;34: 3659–3665.
[4] Rodrigues CH, Pires DEV, Ascher DB. Nucleic Acids Res. 2018;46: W350–W355.
[5] Laimer J, Hiebl-Flach J, Lengauer D, Lackner P. Bioinformatics 2016;32: 1414-1416.
[6] Pires DEV, Ascher DB, Blundell TL. Nucleic Acids Res. 2014; 42:W314–W319.
[7] Nair PS, Vihinen M. Hum Mutat. 2018;34: 42-49.
Acknowledgements
This work was supported by University of Salerno, Fondi di Ateneo per la Ricerca di base [grant numbers ORSA170308, ORSA180380, ORSA199808, ORSA208455 to A.M.]; and by Italian Ministry of University and Research, FFABR 2017 program, and PRIN 2017 program [grant number: 2017483NH8 to A.M.]. The work was made in the frame of ELIXIR-IIB (elixir-italy.org), the Italian Node of the European ELIXIR infrastructure (elixir-europe.org)
Early autonomic and cognitive dysfunction in PD, DLB and MSA: blurring the boundaries between α-synucleinopathies
No full textDifferential diagnosis between Parkinson's disease, dementia with Lewy bodies and multiple system atrophy can be difficult, especially because in early phase they might present with overlapping clinical features. Notably, orthostatic hypotension and cognitive dysfunction are common nonmotor aspects of parkinsonian syndromes and can be both present from the earliest stages of all α-synucleinopathies, indicating a common neurobiological basis in their strong relationship. In view of the increasing awareness about the prevalence of mild cognitive dysfunction in multiple system atrophy, the relevance of autonomic dysfunction in demented parkinsonian patients, the critical role of non-motor symptoms in clustering Parkinson's disease patients and the shift to studying patients in the prodromal phase, we will discuss some intrinsic limitations of current clinical diagnostic criteria, even when applied by movement disorder specialists. In particular, we will focus on the early coexistence of autonomic and cognitive dysfunction in the setting of overt or latent parkinsonism as pitfalls in the differential diagnosis of α-synucleinopathies. As early and accurate diagnosis remains of outmost importance for counselling of patients and timely enrolment into disease-modifying clinical trials, a continuous effort of research community is ongoing to further improve the clinical diagnostic accuracy of α-synucleinopathies
Exploratory data analysis applied on structural features selected from glycoside hydrolase subfamilies
No full text
Botulinum toxin for the treatment of dystonia and pain in corticobasal syndrome
Full text linkBackground: Dystonia is a key symptom in corticobasal syndrome (CBS), and upper limb dystonia is the most common phenotype. Dystonia-associated pain is frequently reported and can be disabling, with poor benefit from oral treatments. Aims of the Study: To investigate the role of botulinum toxin A (BoTNA) in the treatment of dystonia and associated pain in CBS. Methods: Ten consecutive patients with a clinical diagnosis of probable CBS and dystonia with/without associated pain were treated with BoTNA every 3 months. Treatment efficacy was assessed during the first follow-up visit, three months after the first injection, by means of caregiver impression (CI), evaluation of muscle tone with the Ashworth scale (AS), severity of pain measured with the visual analog scale (VAS). Results: Nine subjects underwent at least three treatments, four patients discontinued for progressive reduction in efficacy or disease progression, five patients are ongoing with good response, and one completed the 10th treatment. No local or systemic side effects were reported, and levodopa equivalent daily dose remained unchanged in most cases during the observational period. Significant improvement of AS was recorded (from 2.9 ± 0.7 to 2.0 ± 0.5, p = 0.003). CI ranged from mild to moderate benefit. All patients reported efficacy on pain, with a significant reduction of VAS score (from 7.7 ± 1.7 to 1.7 ± 0.7 in the Pain group, p = 0.016). Conclusions: Our study confirms safety, efficacy, and tolerability of BoTNA in the treatment of dystonia associated with CBS. Local treatment should be considered as a valid alternative to oral treatment modulation mainly in the presence of associated pain
Evaluation of airborne respirable particulate matter and polycyclic aromatic hydrocarbon exposure of asphalt workers
No full textA study was carried out during 2006 to assess exposure to airborne respirable particles (PM10) and polycyclic aromatic hydrocarbons (PAHs) of asphalt manufacturing and road paving workers in Campania region (Italy). At manufacturing plants the average airborne PM10 concentrations were 1125±445 g/m3 in HMA manufacturing workers’ areas; 314±81 g/m3 in process surveyors’ cabins; 92±27 g/m3 in the controls’ areas (administrative offices). At breathing worker’s level the average PAHs in air were 367±198 ng/m3 in HMA manufacturing workers; 348±172 ng/m3 in process surveyors; 21±2 ng/m3 in controls. At road paving sites the average airborne PM10 levels were 1435±325 g/m3 in roller operators; 1610±356 g/m3 in paver operators; 319±108 g/m in controls (traffic controllers). ΣPAHs were 1220±694 ng/m3 in paver operators’ breathing air; 1360±575 ng/m3 in roller operators’; 139±135 ng/m3 in traffic controllers’. The results show that the more consistent hazard for asphalt workers’ health derives from the airborne PM10 exposure, both in exposed as in no exposed (controls) workers
Understanding the Multiple Role of Mitochondria in Parkinson’s Disease and Related Disorders: Lesson From Genetics and Protein–Interaction Network
No full textAs neurons are highly energy-demanding cell, increasing evidence suggests that mitochondria play a large role in several age-related neurodegenerative diseases. Synaptic damage and mitochondrial dysfunction have been associated with early events in the pathogenesis of major neurodegenerative diseases, including Parkinson’s disease, atypical parkinsonisms, and Huntington disease. Disruption of mitochondrial structure and dynamic is linked to increased levels of reactive oxygen species production, abnormal intracellular calcium levels, and reduced mitochondrial ATP production. However, recent research has uncovered a much more complex involvement of mitochondria in such disorders than has previously been appreciated, and a remarkable number of genes and proteins that contribute to the neurodegeneration cascade interact with mitochondria or affect mitochondrial function. In this review, we aim to summarize and discuss the deep interconnections between mitochondrial dysfunction and basal ganglia disorders, with an emphasis into the molecular triggers to the disease process. Understanding the regulation of mitochondrial pathways may be beneficial in finding pharmacological or non-pharmacological interventions to delay the onset of neurodegenerative diseases
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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