Computational approaches to amino acid side-chain conformation using combined NMR theoretical and experimental results: leucine-67 in Desulfovibrio vulgaris flavodoxin.

In this paper, we show that the combination of NMR theoretical and experimental results can help to solve the molecular structure of peptides, here it is used as an example the residue Leucine-67 in Desulfovibrio vulgaris flavodoxin. We apply a computational protocol based on the leucine amino acid dipeptide, which, using calculated and experimental spin-spin coupling constants, allows us to obtain the conformation of the amino acid side chain. Calculated results show that the best agreement is obtained when three conformers around the lateral chain angle $\chi _1$ are considered or when the dynamic effect in the torsional angles is included. The population of each structure is estimated and analyzed according to the correlation between those two approaches. Independently of the approach, the estimated $\chi _1$ angle in solution is close to the staggered value of -60$^\circ $ and deviates significantly from the average x-ray angle of -90$^\circ $.

Serially improved GTOs for molecular applications (SIGMA): Basis sets from H to Ne.

A new approach for generating Gaussian basis sets is reported and tested for atoms from H to Ne. The basis sets thus calculated, named SIGMA basis sets, range from DZ to QZ sizes and have the same composition per shell as Dunning basis sets but with different treatment of the contractions. The standard SIGMA basis sets and their augmented versions have proven to be very suitable for providing good results in atomic and molecular calculations. The performance of the new basis sets is analyzed in terms of total, correlation, and atomization energies, equilibrium distances, and vibrational frequencies in several molecules, and the results are compared at several computational levels with those obtained with the corresponding Dunning and other basis sets.

Molecular similarity between the mechanisms of epithelial fusion and fetal wound healing during the closure of the caudal neural tube in mouse embryos.

BACKGROUND: Neural tube (NT) closure is a complex developmental process that takes place in the early stages of embryogenesis and that is a key step in neurulation. In mammals, the process by which the neural plate generates the NT requires organized cell movements and tissue folding, and it terminates with the fusion of the apposed ends of the neural folds. RESULTS: Here we describe how almost identical cellular and molecular machinery is used to fuse the spinal neural folds as that involved in the repair of epithelial injury in the same area of the embryo. For both natural and wound activated closure of caudal neural tissue, hyaluronic acid and platelet-derived growth factor signaling appear to be crucial for the final fusion step. CONCLUSIONS: There seems to be no general wound healing machinery for all tissues but rather, a tissue-specific epithelial fusion machinery that embryos activate when necessary after abnormal epithelial opening.

The non-canonical Wnt-PCP pathway shapes the mouse caudal neural plate.

The last stage of neural tube (NT) formation involves closure of the caudal neural plate (NP), an embryonic structure formed by neuromesodermal progenitors and newly differentiated cells that becomes incorporated into the NT. Here, we show in mouse that, as cell specification progresses, neuromesodermal progenitors and their progeny undergo significant changes in shape prior to their incorporation into the NT. The caudo-rostral progression towards differentiation is coupled to a gradual reliance on a unique combination of complex mechanisms that drive tissue folding, involving pulses of apical actomyosin contraction and planar polarised cell rearrangements, all of which are regulated by the Wnt-PCP pathway. Indeed, when this pathway is disrupted, either chemically or genetically, the polarisation and morphology of cells within the entire caudal NP is disturbed, producing delays in NT closure. The most severe disruptions of this pathway prevent caudal NT closure and result in spina bifida. In addition, a decrease in Vangl2 gene dosage also appears to promote more rapid progression towards a neural fate, but not the specification of more neural cells.

Toward a Computational NMR Procedure for Modeling Dipeptide Side-Chain Conformation.

Theoretical relationships between the vicinal spin-spin coupling constants (SSCCs) and the χ1 torsion angles have been studied to predict the conformations of protein side chains. An efficient computational procedure is developed to obtain the conformation of dipeptides through theoretical and experimental SSCCs, Karplus equations, and quantum chemistry methods, and it is applied to three aliphatic hydrophobic residues (Val, Leu, and Ile). Three models are proposed: unimodal-static, trimodal-static-stepped, and trimodal-static-trigonal, where the most important factors are incorporated (coupled nuclei, nature and orientation of the substituents, and local geometric properties). Our results are validated by comparison with NMR and X-ray empirical data described in the literature, obtaining successful results on the 29 residues considered. Using out trimodal residue treatment, it is possible to detect and resolve residues with a simple conformation and those with two or three staggered conformers. In four residues, a deeper analysis explains that they do not have a unique conformation and that the population of each conformation plays an important role.

Undersampling: case studies of flaviviral inhibitory activities.

Imbalanced datasets, comprising of more inactive compounds relative to the active ones, are a common challenge in ligand-based model building workflows for drug discovery. This is particularly true for neglected tropical diseases since efforts to identify therapeutics for these diseases are often limited. In this report, we analyze the performance of several undersampling strategies in modeling the Dengue Virus 2 (DENV2) inhibitory activity, as well as the anti-flaviviral activities for the West Nile (WNV) and Zika (ZIKV) viruses. To this end, we build datasets comprising of 1218 (159 actives and 1059 inactives), 1044 (132 actives and 912 inactives) and 302 (75 actives and 227 inactives) molecules with known DENV2, WNV and ZIKV inhibitory activity profiles, respectively. We develop ensemble classifiers for these endpoints and compare the performance of the different undersampling algorithms on external sets. It is observed that data pruning algorithms yield superior performance relative to data selection algorithms. The best overall performance is provided by the one-sided selection algorithm with test set balanced accuracy (BACC) values of 0.84, 0.74 and 0.77 for the DENV2, WNV and ZIKV inhibitory activities, respectively. For the model building, we use the recently proposed GT-STAF information indices, and compare the predictivity of 3 molecular fragmentation approaches: connected subgraphs, substructure and alogp atom types, which are observed to show comparable performance. On the other hand, a combination of indices based on these fragmentation strategies enhances the predictivity of the built ensembles. The built models could be useful for screening new molecules with possible DENV, WNV and ZIKV inhibitory activities. ADMET modelers are encouraged to adopt undersampling algorithms in their workflows when dealing with imbalanced datasets.

Pan-American League of Associations for Rheumatology-Central American, Caribbean and Andean Rheumatology Association Consensus-Conference Endorsements and Recommendations on the Diagnosis and Treatment of Chikungunya-Related Inflammatory Arthropathies in Latin America.

BACKGROUND/OBJECTIVE: Although mortality rates related with chikungunya (CHIK) outbreaks in Latin America's (LA's) dengue-endemic rural and new urban regions are low, dealing with symptoms and sequelae can both produce a significant burden of disease and diminish quality of life-from many months to years-after the acute phase of the infection, with a significant impact on public and individual health.The aim of this work was to establish Pan-American League of Associations for Rheumatology-Central American, Caribbean and Andean Rheumatology Association (ACCAR) consensus-conference endorsements and recommendations on the diagnosis and treatment of CHIK-related inflammatory arthropathies transmitted by Aedes aegypti and Aedes albopictus in LA. METHODS: Based on the Consensus Development Conference format, a panel of ACCAR rheumatologist voting members (n = 10) took part in this Pan-American League of Associations for Rheumatology initiative. Experts voted from a previous content analysis of the medical literature on CHIK, 4 subsequent topic conferences, and a workshop. Consensus represents the majority agreement (≥80%) achieved for each recommendation. RESULTS: The experts' panel reached 4 overarching principles: (1) CHIK virus (CHIKV) is a re-emergent virus transmitted by 2 species of mosquitoes: A. aegypti and A. albopictus; (2) CHIKV caused massive outbreaks in LA; (3) chronic CHIKV infection produces an inflammatory joint disease that, in some cases, can last for several months to years, and (4) currently, there are no vaccines or antivirals licensed for CHIKV infections. RECOMMENDATIONS: Pan-American League of Associations for Rheumatology-ACCAR achieved 13 endorsements and recommendations on CHIK categorized in 3 groups: (1) epidemiology and clinical manifestations, (2) diagnosis, and (3) treatment, representing the consensus agreement from the panel's members.

The role of errors related to DFT methods in calculations involving ion pairs of ionic liquids.

Ionic liquids (ILs) play a key role in many chemical applications. As regards the theoretical approach, ILs show added difficulties in calculations due to the composition of the ion pair and to the fact that they are liquids. Although density functional theory (DFT) can treat this kind of systems to predict physico-chemical properties, common versions of these methods fail to perform accurate predictions of geometries, interaction energies, dipole moments, and other properties related to the molecular structure. In these cases, dispersion and self-interaction error (SIE) corrections need to be introduced to improve DFT calculations involving ILs. We show that the inclusion of dispersion is needed to obtain good geometries and accurate interaction energies. SIE needs to be corrected to describe the charges and dipoles in the ion pair correctly. The use of range-separated functionals allows us to obtain interaction energies close to the CCSD(T) level. © 2017 Wiley Periodicals, Inc.

Safety and efficacy of vinorelbine in combination with pertuzumab and trastuzumab for first-line treatment of patients with HER2-positive locally advanced or metastatic breast cancer: VELVET Cohort 1 final results.

BACKGROUND: Pertuzumab, trastuzumab, and docetaxel is standard of care for first-line treatment of HER2-positive metastatic breast cancer (MBC). However, alternative chemotherapy partners are required to align with patient/physician preferences and to increase treatment flexibility. We report VELVET Cohort 1 results in which the efficacy and safety of pertuzumab and trastuzumab, administered sequentially in separate infusions, followed by vinorelbine, were evaluated. Cohort 2, where pertuzumab and trastuzumab were administered in a single infusion, followed by vinorelbine, recruited after Cohort 1 was fully enrolled, will be reported later. METHODS: In this multicenter, two-cohort, open-label, phase II study, patients with HER2-positive locally advanced or MBC who had not received chemotherapy or biological therapy for their advanced disease received 3-weekly pertuzumab (840 mg loading, 420 mg maintenance doses) and trastuzumab (8 mg/kg loading, 6 mg/kg maintenance doses), followed by vinorelbine (25 mg/m2 initial dose, 30-35 mg/m2 maintenance doses) on days 1 and 8 or 2 and 9 of each 3-weekly cycle. Study treatment was given until investigator-assessed disease progression or unacceptable toxicity. The primary endpoint was investigator-assessed objective response rate (ORR) in patients with measurable disease at baseline per RECIST v1.1. Secondary endpoints included progression-free survival (PFS) and safety. RESULTS: Cohort 1 enrolled 106 patients. Investigator-assessed ORR was 74.2% (95% CI 63.8-82.9) in intent-to-treat patients with measurable disease (89/106 [84.0%]). Median PFS was 14.3 months (95% CI 11.2-17.5) in the intent-to-treat population. Treatment was reasonably well tolerated, with no unexpected toxicities. Diarrhea (61/106 patients [57.5%]) and neutropenia (54/106 [50.9%]) were the most common adverse events (AEs); neutropenia (33/106 [31.1%]) and leukopenia (14/106 [13.2%]) were the most common grade ≥3 AEs. Serious AEs were reported in 32/106 (30.2%) patients. AEs led to study drug discontinuation in 36/106 patients (34.0%). Eighteen of 106 patients (17.0%) had AEs suggestive of congestive heart failure; however, there were no confirmed cases. CONCLUSIONS: The vinorelbine, pertuzumab, and trastuzumab combination is active and reasonably well tolerated. This regimen offers an alternative for patients who cannot receive docetaxel for first-line treatment of HER2-positive locally advanced or MBC. TRIAL REGISTRATION: ClinicalTrials.gov: NCT01565083 , registered on 26 March 2012.

Amyotrophic Lateral Sclerosis in Northern Spain 40 Years Later: What Has Changed?

BACKGROUND: In the last years different studies have reported an increase of amyotrophic lateral sclerosis (ALS) incidence, highlighting the role of the environment in this disease. This prompted us to review ALS cases diagnosed at our hospital in the last decade and to compare them with a previous ALS series reported in our region 30 years ago. METHODS: We reviewed those ALS cases diagnosed at our centre between 2004 and 2013. Subsequently, we compared them with the previous series regarding clinical and epidemiological features. RESULTS: A total of 53 patients (30 males, 23 females) were included. The annual incidence was 1.7 cases per 100,000 inhabitants (2.2 and 1.2 per 100,000 in males and females, respectively), which was significantly higher than in the previous series (1 case per 100,000 inhabitants). Otherwise, the clinical and epidemiological features were similar in both series. The median age at symptom onset was 67 years, with a median diagnosis delay of 6 months. About two thirds of the patients presented with systemic ALS, whereas the remaining had a bulbar onset. Weakness, dysphagia, and dysarthria were the most common clinical symptoms at diagnosis. The median survival from symptom onset was 22 months. CONCLUSION: After 3 decades, the annual incidence of ALS has almost doubled in our region. We did not find significant differences regarding other clinical or epidemiological features.

Analysis of the changes induced by bevacizumab using a high temporal resolution DCE-MRI as prognostic factors for response to further neoadjuvant chemotherapy.

BACKGROUND: Antiangiogenic drugs are being used in the treatment of locally advanced breast cancer. The effect of these drugs can be monitorized using high temporal resolution dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). PURPOSE: To evaluate changes in tumor microvasculature induced by bevacizumab and the usefulness of these changes predicting response to further neoadjuvant therapy. MATERIAL AND METHODS: Seventy patients with locally advanced breast cancers were treated with one cycle of bevacizumab followed by neoadjuvant therapy, combining bevacizumab and cytotoxic chemotherapy. Two DCE-MRI were performed before and after bevacizumab. Changes in tumoral volume, pharmacodynamic curves, and pharmacokinetic variables (K(trans), Kep, Ve, AUC90) in a ROI (ROI 1) encompassing the entire tumor and in another ROI (ROI 2) in the area of higher values of K(trans) were analyzed. Correlations with pathological response were made: parametrical and non-parametrical statistical analysis and ROC curves were used; a P < 0.05 was considered significant. RESULTS: Significant changes in tumoral volume (-4%), pharmacodynamic curves, and pharmacokinetic variables in ROI 1 K(trans) (-45%), Kep (-38%), Ve (-11%), and AUC90 (-44%) and ROI 2 K(trans) (-43%), Kep (-39%), Ve (-5%), and AUC90 (-45%) were observed after bevacizumab (P < 0.05). The effect of bevacizumab was not different between responders and non-responders (P > 0.05), and these changes could not predict response to further neoadjuvant therapy. CONCLUSION: Bevacizumab induces remarkable tumoral volume, pharmacodynamics, and pharmacokinetic changes. However, these changes could not be used as early predictors for response to further neoadjuvant therapy.

Electron density deformations provide new insights into the spectral shift of rhodopsins.

Spectral shifts of rhodopsin, which are related to variations of the electron distribution in 11-cis-retinal, are investigated here using the method of deformed atoms in molecules. We found that systems carrying the M207R and S186W mutations display large perturbations of the π-conjugated system with respect to wild-type rhodopsins. These changes agree with the predicted behavior of the bond length alternation (BLA) and the blue shifts of vertical excitation energies of these systems. The effect of the planarity of the central and Schiff-base regions of retinal chain on the electronic structure of the chromophore is also investigated. By establishing nonlinear polynomial relations between BLA, chain distortions, and vertical excitation energies, we are also able to provide a semiquantitative approach for the understanding of the mechanisms regulating spectral shifts in rhodopsin and its mutants.

The loop-tail mouse model displays open and closed caudal neural tube defects.

Neural tube defects (NTDs) are the second most common cause of congenital malformations and are often studied in animal models. Loop-tail (Lp) mice carry a mutation in the Vangl2 gene, a member of the Wnt-planar cell polarity pathway. In Vangl2+/Lp embryos, the mutation induces a failure in the completion of caudal neural tube closure, but only a small percentage of embryos develop open spina bifida. Here, we show that the majority of Vangl2+/Lp embryos developed caudal closed NTDs and presented cellular aggregates that may facilitate the sealing of these defects. The cellular aggregates expressed neural crest cell markers and, using these as a readout, we describe a systematic method to assess the severity of the neural tube dorsal fusion failure. We observed that this defect worsened in combination with other NTD mutants, Daam1 and Grhl3. Besides, we found that in Vangl2+/Lp embryos, these NTDs were resistant to maternal folic acid and inositol supplementation. Loop-tail mice provide a useful model for research on the molecular interactions involved in the development of open and closed NTDs and for the design of prevention strategies for these diseases.

Dunn's index for cluster tendency assessment of pharmacological data sets.

Cluster tendency assessment is an important stage in cluster analysis. In this sense, a group of promising techniques named visual assessment of tendency (VAT) has emerged in the literature. The presence of clusters can be detected easily through the direct observation of a dark blocks structure along the main diagonal of the intensity image. Alternatively, if the Dunn's index for a single linkage partition is greater than 1, then it is a good indication of the blocklike structure. In this report, the Dunn's index is applied as a novel measure of tendency on 8 pharmacological data sets, represented by machine-learning-selected molecular descriptors. In all cases, observed values are less than 1, thus indicating a weak tendency for data to form compact clusters. Other results suggest that there is an increasing relationship between the Dunn's index as a measure of cluster separability and the classification accuracy of various cluster algorithms tested on the same data sets.

Comparison of combinatorial clustering methods on pharmacological data sets represented by machine learning-selected real molecular descriptors.

Cluster algorithms play an important role in diversity related tasks of modern chemoinformatics, with the widest applications being in pharmaceutical industry drug discovery programs. The performance of these grouping strategies depends on various factors such as molecular representation, mathematical method, algorithmical technique, and statistical distribution of data. For this reason, introduction and comparison of new methods are necessary in order to find the model that best fits the problem at hand. Earlier comparative studies report on Ward's algorithm using fingerprints for molecular description as generally superior in this field. However, problems still remain, i.e., other types of numerical descriptions have been little exploited, current descriptors selection strategy is trial and error-driven, and no previous comparative studies considering a broader domain of the combinatorial methods in grouping chemoinformatic data sets have been conducted. In this work, a comparison between combinatorial methods is performed,with five of them being novel in cheminformatics. The experiments are carried out using eight data sets that are well established and validated in the medical chemistry literature. Each drug data set was represented by real molecular descriptors selected by machine learning techniques, which are consistent with the neighborhood principle. Statistical analysis of the results demonstrates that pharmacological activities of the eight data sets can be modeled with a few of families with 2D and 3D molecular descriptors, avoiding classification problems associated with the presence of nonrelevant features. Three out of five of the proposed cluster algorithms show superior performance over most classical algorithms and are similar (or slightly superior in the most optimistic sense) to Ward's algorithm. The usefulness of these algorithms is also assessed in a comparative experiment to potent QSAR and machine learning classifiers, where they perform similarly in some cases.

Early Imaging and Molecular Changes with Neoadjuvant Bevacizumab in Stage II/III Breast Cancer.

This prospective, phase II study evaluated novel biomarkers as predictors of response to bevacizumab in patients with breast cancer (BC), using serial imaging methods and gene expression analysis. Patients with primary stage II/III BC received bevacizumab 15 mg/kg (cycle 1; C1), then four cycles of neoadjuvant docetaxel doxorubicin, and bevacizumab every 3 weeks (C2-C5). Tumour proliferation and hypoxic status were evaluated using 18F-fluoro-3'-deoxy-3'-L-fluorothymidine (FLT)- and 18F-fluoromisonidazole (FMISO)-positron emission tomography (PET) at baseline, and during C1 and C5. Pre- and post-bevacizumab vascular changes were evaluated using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Molecular biomarkers were assessed using microarray analysis. A total of 70 patients were assessed for treatment efficacy. Significant decreases from baseline in tumour proliferation (FLT-PET), vascularity, and perfusion (DCE-MRI) were observed during C1 (p ≤ 0.001), independent of tumour subtype. Bevacizumab treatment did not affect hypoxic tumour status (FMISO-PET). Significant changes in the expression of 28 genes were observed after C1. Changes in vascular endothelial growth factor receptor (VEGFR)-2p levels were observed in 65 patients, with a > 20% decrease in VEGFR-2p observed in 13/65. Serial imaging techniques and molecular gene profiling identified several potentially predictive biomarkers that may predict response to neoadjuvant bevacizumab therapy in BC patients.

Electrochemical oxidation of acetaminophen and its transformation products in surface water: effect of pH and current density.

Several studies have been conducted worldwide to develop effective and affordable methods to degrade pharmaceuticals and their metabolites/intermediates/oxidation products found in surface water, wastewater and drinking water. In this work, acetaminophen and its transformation products were successfully degraded in surface water by electrochemical oxidation using stainless steel electrodes. The effect of pH and current density on the oxidation process was assessed and the oxidation kinetics and mechanisms involved were described. Additionally, the results were compared with those obtained in acetaminophen synthetic solutions. It was found that conducting the electrochemical oxidation at 16.3 mA/cm2 and pH 5, good performance of the process was achieved and not only acetaminophen, but also its transformation products were totally degraded in only 7.5 min; furthermore, small number of transformation products were generated. On the other hand, degradation rates of acetaminophen and its transformation products in surface water were much faster (more than 2.5 times) and the reaction times much shorter (more than 4.0 times) than in synthetic solutions at all current densities and pH values evaluated. At pH 3 and pH 5, greater soluble chlorine formation due to the higher HCl amount used to acidify the surface water solutions could enhance the degradation rates of acetaminophen and its transformation products. However, constituents of surface water (ions and solids) could also have an important role on the oxidation process because at pH 9 (non-acidified solutions) the degradation rates were also much greater and the reaction times were much shorter in surface water than in acetaminophen synthetic solutions.

Survival impact of primary tumor resection in de novo metastatic breast cancer patients (GEICAM/El Alamo Registry).

The debate about surgical resection of primary tumor (PT) in de novo metastatic breast cancer (MBC) patients persists. We explored this approach's outcomes in patients included in a retrospective registry, named El Álamo, of breast cancer patients diagnosed in Spain (1990-2001). In this analysis we only included de novo MBC patients, 1415 of whom met the study's criteria. Descriptive, Kaplan-Meier and Cox regression analyses were carried out. Median age was 63.1 years, 49.2% of patients had single-organ metastasis (skin/soft tissue [16.3%], bone [33.8%], or viscera [48.3%]). PT surgery (S) was performed in 44.5% of the cases. S-group patients were younger, had smaller tumors, higher prevalence of bone and oligometastatic disease, and lower prevalence of visceral involvement. With a median follow-up of 23.3 months, overall survival (OS) was 39.6 versus 22.4 months (HR = 0.59, p < 0.0001) in the S- and non-S groups, respectively. The S-group OS benefit remained statistically and clinically significant regardless of metastatic location, histological type, histological grade, hormone receptor status and tumor size. PT surgery (versus no surgery) was associated with an OS benefit suggesting that loco-regional PT control may be considered in selected MBC patients. Data from randomized controlled trials are of utmost importance to confirm these results.

Applying pattern recognition methods plus quantum and physico-chemical molecular descriptors to analyze the anabolic activity of structurally diverse steroids.

The great cost associated with the development of new anabolic-androgenic steroid (AASs) makes necessary the development of computational methods that shorten the drug discovery pipeline. Toward this end, quantum, and physicochemical molecular descriptors, plus linear discriminant analysis (LDA) were used to analyze the anabolic/androgenic activity of structurally diverse steroids and to discover novel AASs, as well as also to give a structural interpretation of their anabolic-androgenic ratio (AAR). The obtained models are able to correctly classify 91.67% (86.27%) of the AASs in the training (test) sets, respectively. The results of predictions on the 10% full-out cross-validation test also evidence the robustness of the obtained model. Moreover, these classification functions are applied to an "in house" library of chemicals, to find novel AASs. Two new AASs are synthesized and tested for in vivo activity. Although both AASs are less active than some commercially AASs, this result leaves a door open to a virtual variational study of the structure of the two compounds, to improve their biological activity. The LDA-assisted QSAR models presented here, could significantly reduce the number of synthesized and tested AASs, as well as could increase the chance of finding new chemical entities with higher AAR.