Objective
An association between bipolar disorder and cognitive impairment has repeatedly been described, even for euthymic patients. Findings are inconsistent both across primary studies and ...previous meta‐analyses. This study reanalysed 31 primary data sets as a single large sample (N = 2876) to provide a more definitive view.
Method
Individual patient and control data were obtained from original authors for 11 measures from four common neuropsychological tests: California or Rey Verbal Learning Task (VLT), Trail Making Test (TMT), Digit Span and/or Wisconsin Card Sorting Task.
Results
Impairments were found for all 11 test‐measures in the bipolar group after controlling for age, IQ and gender (Ps ≤ 0.001, E.S. = 0.26–0.63). Residual mood symptoms confound this result but cannot account for the effect sizes found. Impairments also seem unrelated to drug treatment. Some test‐measures were weakly correlated with illness severity measures suggesting that some impairments may track illness progression.
Conclusion
This reanalysis supports VLT, Digit Span and TMT as robust measures of cognitive impairments in bipolar disorder patients. The heterogeneity of some test results explains previous differences in meta‐analyses. Better controlling for confounds suggests deficits may be smaller than previously reported but should be tracked longitudinally across illness progression and treatment.
Hepatitis C constitutes an unresolved global health problem. This infectious disease is caused by the hepatotropic hepatitis C virus (HCV), and it can lead to the occurrence of life-threatening ...medical conditions, such as cirrhosis and liver cancer. Nowadays, major clinical concerns have arisen because of the appearance of multidrug resistance (MDR) and the side effects especially associated with long-term treatments. In this work, we report the first multitasking model for quantitative structure-biological effect relationships (mtk-QSBER), focused on the simultaneous exploration of anti-HCV activity and in vitro safety profiles related to the absorption, distribution, metabolism, elimination, and toxicity (ADMET). The mtk-QSBER model was created from a data set formed by 40 158 cases, displaying accuracy higher than 95% in both training and prediction (test) sets. Several molecular fragments were selected, and their quantitative contributions to anti-HCV activity and ADMET profiles were calculated. By combining the analysis of the fragments with positive contributions and the physicochemical meanings of the different molecular descriptors in the mtk-QSBER, six new molecules were designed. These new molecules were predicted to exhibit potent anti-HCV activity and desirable in vitro ADMET properties. In addition, the designed molecules have good druglikeness according to the Lipinski’s rule of five and its variants.
Quantitative structure activity relationships (QSAR) modelling is a well-known computational tool, often used in a wide variety of applications. Yet one of the major drawbacks of conventional QSAR ...modelling is that models are set up based on a limited number of experimental and/or theoretical conditions. To overcome this, the so-called multitasking or multitarget QSAR (mt-QSAR) approaches have emerged as new computational tools able to integrate diverse chemical and biological data into a
single
model equation, thus extending and improving the reliability of this type of modelling. We have developed
QSAR-Co-X
, an open source python–based toolkit (available to download at
https://github.com/ncordeirfcup/QSAR-Co-X
) for supporting mt-QSAR modelling following the Box-Jenkins moving average approach. The new toolkit embodies several functionalities for dataset selection and curation plus computation of descriptors, for setting up linear and non-linear models, as well as for a comprehensive results analysis. The workflow within this toolkit is guided by a cohort of multiple statistical parameters and graphical outputs onwards assessing both the predictivity and the robustness of the derived mt-QSAR models. To monitor and demonstrate the functionalities of the designed toolkit, four case-studies pertaining to previously reported datasets are examined here. We believe that this new toolkit, along with our previously launched
QSAR-Co
code, will significantly contribute to make mt-QSAR modelling widely and routinely applicable.
Leishmaniasis and trypanosomiasis occur primarily in undeveloped countries and account for millions of deaths and disability-adjusted life years. Limited therapeutic options, high toxicity of ...chemotherapeutic drugs and the emergence of drug resistance associated with these diseases demand urgent development of novel therapeutic agents for the treatment of these dreadful diseases. In the last decades, different in silico methods have been successfully implemented for supporting the lengthy and expensive drug discovery process. In the current review, we discuss recent advances pertaining to in silico analyses towards lead identification, lead modification and target identification of antileishmaniasis and anti-trypanosomiasis agents. We describe recent applications of some important in silico approaches, such as 2D-QSAR, 3D-QSAR, pharmacophore mapping, molecular docking, and so forth, with the aim of understanding the utility of these techniques for the design of novel therapeutic anti-parasitic agents. This review focuses on: (a) advanced computational drug design options; (b) diverse methodologies - e.g.: use of machine learning tools, software solutions, and web-platforms; (c) recent applications and advances in the last five years; (d) experimental validations of in silico predictions; (e) virtual screening tools; and (f) rationale or justification for the selection of these in silico methods.
Parasitic protozoa comprise diverse aetiological agents responsible for important diseases in humans and animals including sleeping sickness, Chagas disease, leishmaniasis, malaria, toxoplasmosis and ...others. They are major causes of mortality and morbidity in tropical and subtropical countries, and are also responsible for important economic losses. However, up to now, for most of these parasitic diseases, effective vaccines are lacking and the approved chemotherapeutic compounds present high toxicity, increasing resistance, limited efficacy and require long periods of treatment. Many of these parasitic illnesses predominantly affect low-income populations of developing countries for which new pharmaceutical alternatives are urgently needed. Thus, very low research funding is available. Amidine-containing compounds such as pentamidine are DNA minor groove binders with a broad spectrum of activities against human and veterinary pathogens. Due to their promising microbicidal activity but their rather poor bioavailability and high toxicity, many analogues and derivatives, including pro-drugs, have been synthesized and screened in vitro and in vivo in order to improve their selectivity and pharmacological properties. This review summarizes the knowledge on amidines and analogues with respect to their synthesis, pharmacological profile, mechanistic and biological effects upon a range of intracellular protozoan parasites. The bulk of these data may contribute to the future design and structure optimization of new aromatic dicationic compounds as novel antiparasitic drug candidates.
Antimicrobial peptides (AMPs) represent promising alternatives to fight against bacterial pathogens. However, cellular toxicity remains one of the main concerns in the early development of ...peptide-based drugs. This work introduces the first multitasking (mtk) computational model focused on performing simultaneous predictions of antibacterial activities, and cytotoxicities of peptides. The model was created from a data set containing 3592 cases, and it displayed accuracy higher than 96% for classifying/predicting peptides in both training and prediction (test) sets. The technique known as alanine scanning was computationally applied to illustrate the calculation of the quantitative contributions of the amino acids (in their respective positions of the sequence) to the biological effects of a defined peptide. A small library formed by 10 peptides was generated, where peptides were designed by considering the interpretations of the different descriptors in the mtk-computational model. All the peptides were predicted to exhibit high antibacterial activities against multiple bacterial strains, and low cytotoxicity against various cell types. The present mtk-computational model can be considered a very useful tool to support high throughput research for the discovery of potent and safe AMPs.
The present work aims at establishing multi-target chemometric models using the recently launched quantitative structure-activity relationship (QSAR)-Co tool for predicting the activity of inhibitor ...compounds against different isoforms of phosphoinositide 3-kinase (PI3K) under various experimental conditions. The inhibitors of class I phosphoinositide 3-kinase (PI3K) isoforms have emerged as potential therapeutic agents for the treatment of various disorders, especially cancer. The cell-based enzyme inhibition assay results of PI3K inhibitors were curated from the CHEMBL database. Factors such as the nature and mutation of cell lines that may significantly alter the assay outcomes were considered as important experimental elements for mt-QSAR model development. The models, in turn, were developed using two machine learning techniques as implemented in QSAR-Co: linear discriminant analysis (LDA) and random forest (RF). Both techniques led to models with high accuracy (ca. 90%). Several molecular fragments were extracted from the current dataset, and their quantitative contributions to the inhibitory activity against all the proteins and experimental conditions under study were calculated. This case study also demonstrates the utility of QSAR-Co tool in solving multi-factorial and complex chemometric problems. Additionally, the combination of different in silico methods employed in this work can serve as a valuable guideline to speed up early discovery of PI3K inhibitors.
Statins are inhibitors of cholesterol synthesis, but other biological properties, such as antimicrobial effects, have also been assigned to them, leading to their designation as pleiotropic agents. ...Our goal was to investigate the activity and selectivity of atorvastatin (AVA) against
by using
models, aiming for more effective and safer therapeutic options through drug repurposing proposals for monotherapy and therapy in combination with benznidazole (BZ). Phenotypic screening was performed with different strains (Tulahuen discrete typing unit {DTU} VI and Y DTU II) and forms (intracellular forms, bloodstream trypomastigotes, and tissue-derived trypomastigotes) of the parasite. On assay of the Tulahuen strain, AVA was more active against intracellular amastigotes (selectivity index SI = 3). Also, against a parasite of another DTU (Y strain), this statin was more active (2.1-fold) and selective (2.4-fold) against bloodstream trypomastigotes (SI = 51) than against the intracellular forms (SI = 20). A cytomorphological approach using phalloidin-rhodamine permitted us to verify that AVA did not induced cell density reduction and that cardiac cells (CC) maintained their typical cytoarchitecture. Combinatory approaches using fixed-ratio methods showed that AVA and BZ gave synergistic interactions against both trypomastigotes and intracellular forms (mean sums of fractional inhibitory concentration indexes ∑FICIs of 0.46 ± 0.12 and 0.48 ± 0.03, respectively). Thus, the repurposing strategy for AVA, especially in combination with BZ, which leads to a synergistic effect, is encouraging for future studies to identify novel therapeutic protocols for Chagas disease treatment.
Chagas disease is a life-threatening infection caused by a variety of genetically diverse strains of the protozoan parasite
The current treatment (benznidazole and nifurtimox) is unsatisfactory, and ...potential alternatives include inhibitors of sterol 14α-demethylase (CYP51), the cytochrome P450 enzyme essential for the biosynthesis of sterols in eukaryotes and the major target of clinical and agricultural antifungals. Here we performed a comparative investigation of two protozoon-specific CYP51 inhibitors, VNI and its CYP51 structure-based derivative VFV, in the murine models of infection caused by the Y strain of
The effects of different treatment regimens and drug delivery vehicles were evaluated in animals of both genders, with benznidazole serving as the reference drug. Regardless of the treatment scheme or delivery vehicle, VFV was more potent in both genders, causing a >99.7% peak parasitemia reduction, while the VNI values varied from 91 to 100%. Treatments with VNI and VFV resulted in 100% animal survival and 0% natural relapse after the end of therapy, though, except for the 120-day treatment schemes with VFV, relapses after three cycles of immunosuppression were observed in each animal group, and quantitative PCR analysis revealed a very light parasite load in the blood samples (sometimes below or near the detection limit, which was 1.5 parasite equivalents/ml). Our studies support further investigations of this class of compounds, including their testing against other
strains and in combination with other drugs.
Dias VV, Balanzá‐Martinez V, Soeiro‐de‐Souza MG, Moreno RA, Figueira ML, Machado‐Vieira R, Vieta E. Pharmacological approaches in bipolar disorders and the impact on cognition: a critical overview.
...Objective: Historically, pharmacological treatments for bipolar disorders (BD) have been associated with neurocognitive side‐effects. We reviewed studies which assessed the impact of several psychopharmacological drugs on the neurocognitive function of BD patients.
Method: The PubMed database was searched for studies published between January 1980 and February 2011, using the following terms: bipolar, bipolar disorder, mania, manic episode, or bipolar depression, cross‐referenced with cognitive, neurocognitive, or neuropsychological, cross‐referenced with treatment.
Results: Despite methodological flaws in the older studies and insufficient research concerning the newer agents, some consistent findings emerged from the review; lithium appears to have definite, yet subtle, negative effects on psychomotor speed and verbal memory. Among the newer anticonvulsants, lamotrigine appears to have a better cognitive profile than carbamazepine, valproate, topiramate, and zonisamide. More long‐term studies are needed to better understand the impact of atypical antipsychotics on BD patients’ neurocognitive functioning, both in monotherapy and in association with other drugs. Other agents, like antidepressants and cognitive enhancers, have not been adequately studied in BD so far.
Conclusion: Pharmacotherapies for BD should be chosen to minimize neurocognitive side‐effects, which may already be compromised by the disease process itself. Neurocognitive evaluation should be considered in BD patients to better evaluate treatment impact on neurocognition. A comprehensive neuropsychological evaluation also addressing potential variables and key aspects such as more severe cognitive deficits, comorbidities, differential diagnosis, and evaluation of multiple cognitive domains in longitudinal follow‐up studies are warranted.
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