Identification and characterization of a nonbiological small-molecular mimic of a Zika virus conformational neutralizing epitope.

Antigenic similarities between Zika virus (ZIKV) and other flaviviruses pose challenges to the development of virus-specific diagnostic tools and effective vaccines. Starting with a DNA-encoded one-bead-one-compound combinatorial library of 508,032 synthetic, non-natural oligomers, we selected and characterized small molecules that mimic ZIKV epitopes. High-throughput fluorescence-activated cell sorter-based bead screening was used to select molecules that bound IgG from ZIKV-immune but not from dengue-immune sera. Deep sequencing of the DNA from the "Zika-only" beads identified 40 candidate molecular structures. A lead candidate small molecule "CZV1-1" was selected that correctly identifies serum specimens from Zika-experienced patients with good sensitivity and specificity (85.3% and 98.4%, respectively). Binding competition studies of purified anti-CZV1-1 IgG against known ZIKV-specific monoclonal antibodies (mAbs) showed that CZV1-1 mimics a nonlinear, neutralizing conformational epitope in the domain III of the ZIKV envelope. Purified anti-CZV1-1 IgG neutralized infection of ZIKV in cell cultures with potencies comparable to highly specific ZIKV-neutralizing mAbs. This study demonstrates an innovative approach for identification of synthetic non-natural molecular mimics of conformational virus epitopes. Such molecular mimics may have value in the development of accurate diagnostic assays for Zika, as well as for other viruses.

Randomized Trial of BCG Vaccine to Protect against Covid-19 in Health Care Workers.

BACKGROUND: The bacille Calmette-Guérin (BCG) vaccine has immunomodulatory "off-target" effects that have been hypothesized to protect against coronavirus disease 2019 (Covid-19). METHODS: In this international, double-blind, placebo-controlled trial, we randomly assigned health care workers to receive the BCG-Denmark vaccine or saline placebo and followed them for 12 months. Symptomatic Covid-19 and severe Covid-19, the primary outcomes, were assessed at 6 months; the primary analyses involved the modified intention-to-treat population, which was restricted to participants with a negative test for severe acute respiratory syndrome coronavirus 2 at baseline. RESULTS: A total of 3988 participants underwent randomization; recruitment ceased before the planned sample size was reached owing to the availability of Covid-19 vaccines. The modified intention-to-treat population included 84.9% of the participants who underwent randomization: 1703 in the BCG group and 1683 in the placebo group. The estimated risk of symptomatic Covid-19 by 6 months was 14.7% in the BCG group and 12.3% in the placebo group (risk difference, 2.4 percentage points; 95% confidence interval [CI], -0.7 to 5.5; P = 0.13). The risk of severe Covid-19 by 6 months was 7.6% in the BCG group and 6.5% in the placebo group (risk difference, 1.1 percentage points; 95% CI, -1.2 to 3.5; P = 0.34); the majority of participants who met the trial definition of severe Covid-19 were not hospitalized but were unable to work for at least 3 consecutive days. In supplementary and sensitivity analyses that used less conservative censoring rules, the risk differences were similar but the confidence intervals were narrower. There were five hospitalizations due to Covid-19 in each group (including one death in the placebo group). The hazard ratio for any Covid-19 episode in the BCG group as compared with the placebo group was 1.23 (95% CI, 0.96 to 1.59). No safety concerns were identified. CONCLUSIONS: Vaccination with BCG-Denmark did not result in a lower risk of Covid-19 among health care workers than placebo. (Funded by the Bill and Melinda Gates Foundation and others; BRACE ClinicalTrials.gov number, NCT04327206.).

Evolutionary deletions within the SARS-CoV-2 genome as signature trends for virus fitness and adaptation.

Coronaviruses are large RNA viruses that can infect and spread among humans and animals. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), responsible for coronavirus disease 2019, has evolved since its first detection in December 2019. Deletions are a common occurrence in SARS-CoV-2 evolution, particularly in specific genomic sites, and may be associated with the emergence of highly competent lineages. While deletions typically have a negative impact on viral fitness, some persist and become fixed in viral populations, indicating that they may confer advantageous benefits for the virus's adaptive evolution. This work presents a literature review and data analysis on structural losses in the SARS-CoV-2 genome and the potential relevance of specific signatures for enhanced viral fitness and spread.

Assessing the incorporation of latent variables in the estimation of the value of a statistical life.

For many years, the economic literature has recognized the role of attitudes, beliefs, and perceptions in estimating the value of a statistical life (VSL). However, few applications have attempted to include them. This article incorporates the perceived controllability and concern about traffic and cardiorespiratory risks to estimate VSL using a hybrid choice model (HCM). The HCM allows us to include unobserved heterogeneity and improve behavioral realism explicitly. Using data from a choice experiment conducted in Santiago, Chile, we estimate a VSL of US$3.78 million for traffic risks and US$2.06 million for cardiorespiratory risks. We found that higher controllability decreases the likelihood that the respondents would be willing to pay for risk reductions in both risks. On the other hand, concern about these risks decreases the willingness to pay for traffic risk reductions but increases it for cardiorespiratory risk reductions.

Determination of prognostic markers for COVID-19 disease severity using routine blood tests and machine learning.

The need for the identification of risk factors associated to COVID-19 disease severity remains urgent. Patients' care and resource allocation can be potentially different and are defined based on the current classification of disease severity. This classification is based on the analysis of clinical parameters and routine blood tests, which are not standardized across the globe. Some laboratory test alterations have been associated to COVID-19 severity, although these data are conflicting partly due to the different methodologies used across different studies. This study aimed to construct and validate a disease severity prediction model using machine learning (ML). Seventy-two patients admitted to a Brazilian hospital and diagnosed with COVID-19 through RT-PCR and/or ELISA, and with varying degrees of disease severity, were included in the study. Their electronic medical records and the results from daily blood tests were used to develop a ML model to predict disease severity. Using the above data set, a combination of five laboratorial biomarkers was identified as accurate predictors of COVID-19 severe disease with a ROC-AUC of 0.80 ​±â€‹ 0.13. Those biomarkers included prothrombin activity, ferritin, serum iron, ATTP and monocytes. The application of the devised ML model may help rationalize clinical decision and care.

Estimation of genetic parameters for maintenance energy requirements and residual feed intake in Nellore cattle.

We estimated heritabilities and genetic and phenotypic correlation estimates for maintenance energy requirements (NEmR), residual feed intake (RFI), growth, carcass and reproductive indicator traits, using data from 41 feed efficiency trials in Brazil, comprising 4381 males and females. Continuous traits were analysed using a linear animal model and threshold traits were analysed using a threshold animal model. The heritability estimates were low for RFI (0.190) and NEmR (0.193); other heritabilities were mainly moderate (growth and carcass traits) or high (sexual precocity traits). The genetic correlation of RFI with NEmR was high (0.701). The genetic correlations of NEmR were low with carcass and reproductive traits, and moderate with growth traits. Thus, selection to improve weaning weight and female sexual precocity indicator traits would not affect maintenance energy requirement. Genetic selection to reduce maintenance energy requirements is feasible and would also reduce DMI and RFI. Selection to improve RFI can be used to identify animals with lower maintenance energy requirements. Long-term selection to reduce RFI and NEmR would have favourable effects on yearling weight, carcass muscle indicator traits and female sexual precocity. Genetic (co)variance component estimates for NEmR, in conjunction with economic values of selection criteria, may be used to develop novel approaches for genetic selection to improve efficiency of beef production.

Valosin-Containing Protein (VCP): A Review of Its Diverse Molecular Functions and Clinical Phenotypes.

In this review we examine the functionally diverse ATPase associated with various cellular activities (AAA-ATPase), valosin-containing protein (VCP/p97), its molecular functions, the mutational landscape of VCP and the phenotypic manifestation of VCP disease. VCP is crucial to a multitude of cellular functions including protein quality control, endoplasmic reticulum-associated degradation (ERAD), autophagy, mitophagy, lysophagy, stress granule formation and clearance, DNA replication and mitosis, DNA damage response including nucleotide excision repair, ATM- and ATR-mediated damage response, homologous repair and non-homologous end joining. VCP variants cause multisystem proteinopathy, and pathology can arise in several tissue types such as skeletal muscle, bone, brain, motor neurons, sensory neurons and possibly cardiac muscle, with the disease course being challenging to predict.

Economic valuation of Harmful Algal Blooms (HAB): Methodological challenges, policy implications, and an empirical application.

This paper presents a literature review on the economic valuation of Harmful Algal Bloom (HAB) impacts, identifying methodological challenges, policy implications, and gaps. Unlike previous literature reviews, we are particularly interested in determining whether the economic valuations of HABs have included a policy analysis. Our paper provides a conceptual framework that allows us to evaluate whether applications of economic studies of HABs are consistent with a well-defined economic welfare analysis. It links methodologies and techniques with welfare measures, data types, and econometric methods. Based on this literature review, we present an example of economic valuation that closes the gap between policy analysis and valuation methodology. We use a stated preferences study to estimate a "seafood price premium" to create a fund to support monitoring systems and for damage compensation to producers in the presence of HABs. Results show that most economic studies on HAB valuation do not consider any cost-benefit analysis of a defined policy intervention. The predominant economic valuation methodology uses market information to estimate a proxy for welfare measure of the impact of HABs (loss revenue, sales, exports). Moreover, nonuse and indirect use values are ignored in the literature, while stated preference methodologies are underrepresented. Finally, results from 1293 surveys found that people are willing to pay an increase in the price of mussels to support a policy that informs on HAB. However, the lack of institutional trust affects the probability of paying negatively.

Dapagliflozin in Patients with Chronic Kidney Disease.

BACKGROUND: Patients with chronic kidney disease have a high risk of adverse kidney and cardiovascular outcomes. The effect of dapagliflozin in patients with chronic kidney disease, with or without type 2 diabetes, is not known. METHODS: We randomly assigned 4304 participants with an estimated glomerular filtration rate (GFR) of 25 to 75 ml per minute per 1.73 m2 of body-surface area and a urinary albumin-to-creatinine ratio (with albumin measured in milligrams and creatinine measured in grams) of 200 to 5000 to receive dapagliflozin (10 mg once daily) or placebo. The primary outcome was a composite of a sustained decline in the estimated GFR of at least 50%, end-stage kidney disease, or death from renal or cardiovascular causes. RESULTS: The independent data monitoring committee recommended stopping the trial because of efficacy. Over a median of 2.4 years, a primary outcome event occurred in 197 of 2152 participants (9.2%) in the dapagliflozin group and 312 of 2152 participants (14.5%) in the placebo group (hazard ratio, 0.61; 95% confidence interval [CI], 0.51 to 0.72; P<0.001; number needed to treat to prevent one primary outcome event, 19 [95% CI, 15 to 27]). The hazard ratio for the composite of a sustained decline in the estimated GFR of at least 50%, end-stage kidney disease, or death from renal causes was 0.56 (95% CI, 0.45 to 0.68; P<0.001), and the hazard ratio for the composite of death from cardiovascular causes or hospitalization for heart failure was 0.71 (95% CI, 0.55 to 0.92; P = 0.009). Death occurred in 101 participants (4.7%) in the dapagliflozin group and 146 participants (6.8%) in the placebo group (hazard ratio, 0.69; 95% CI, 0.53 to 0.88; P = 0.004). The effects of dapagliflozin were similar in participants with type 2 diabetes and in those without type 2 diabetes. The known safety profile of dapagliflozin was confirmed. CONCLUSIONS: Among patients with chronic kidney disease, regardless of the presence or absence of diabetes, the risk of a composite of a sustained decline in the estimated GFR of at least 50%, end-stage kidney disease, or death from renal or cardiovascular causes was significantly lower with dapagliflozin than with placebo. (Funded by AstraZeneca; DAPA-CKD ClinicalTrials.gov number, NCT03036150.).

An artificial neural network model to predict structure-based protein-protein free energy of binding from Rosetta-calculated properties.

The prediction of the free energy (ΔG) of binding for protein-protein complexes is of general scientific interest as it has a variety of applications in the fields of molecular and chemical biology, materials science, and biotechnology. Despite its centrality in understanding protein association phenomena and protein engineering, the ΔG of binding is a daunting quantity to obtain theoretically. In this work, we devise a novel Artificial Neural Network (ANN) model to predict the ΔG of binding for a given three-dimensional structure of a protein-protein complex with Rosetta-calculated properties. Our model was tested using two data sets, and it presented a root-mean-square error ranging from 1.67 kcal mol-1 to 2.45 kcal mol-1, showing a better performance compared to the available state-of-the-art tools. Validation of the model for a variety of protein-protein complexes is showcased.

Estimates of genetic and phenotypic parameters for feeding behaviour and feed efficiency-related traits in Nelore cattle.

The objective of this study was to obtain (co)variance components, heritability, and genetic and phenotypic correlation estimates for feed efficiency and feed behaviour-related indicator traits. Further, it aimed to predict the direct and correlated responses for feed efficiency traits when selection was applied for feeding behaviour-related traits in Nelore cattle. Phenotypic records (n = 4840) from 125 feed efficiency tests (RFI: Residual feed intake and DMI: Dry matter intake) carried out between 2011 and 2018 were considered in this study. Animals belonged to five farms located in two Brazilian geographical regions (Midwest and Southeast). Animals under similar management and environmental conditions in the feedlot were evaluated when they attained an average of 13.5 ± 4.15 months of age. Feed behaviour-related traits were also obtained, including meal criteria (MC), meal frequency (MF), average meal duration (AMD), meal duration (MD), average consumption per meal (ACM), and consumption rate (CR) through the GrowSafe System® electronic bunk system. The contemporary groups for all traits were composed of farm, management group, feed efficiency test, sex, and birth year. The (co)variance components were estimated using the restricted maximum likelihood method considering a multi-trait (n = 8) animal model. The heritability estimates for RFI (0.23 ± 0.02), DMI (0.31 ± 0.02), MF (0.65 ± 0.02), AMD (0.29 ± 0.02), ACM (0.24 ± 0.02), MD (0.41 ± 0.02), MC (0.48 ± 0.02), and CR (0.42 ± 0.02) were moderate to high. The highest genetic correlation was obtained between CR and MD (-0.91 ± 0.04), MD and AMD (0.73 ± 0.03), CR and AMD (-0.68 ± 0.04), and RFI and DMI (0.81 ± 0.02). The highest phenotypic correlation was between ACM and AMD (0.76 ± 0.02), DMI and MD (0.77 ± 0.02), and DMI and RFI (0.77 ± 0.02). Genetic improvement for feed efficiency and feeding behaviour-related traits is feasible and the results obtained herein provided valuable information regarding the genetic background of Nelore feeding behaviour-related traits. The genetic association between feeding behaviour and feed efficiency-related traits suggested that animals spending less time feeding at a low feeding rate also had lower DMI and higher feed efficiency (RFI), and likely had lower energy maintenance requirements. The relative efficiency of selection showed that feeding behaviour-related traits were not adequate indicator traits to improve RFI and DMI. The DMI might be an effective selection criterion to improve RFI and reduce the herd's maintenance requirements.

The economics impacts of long-run droughts: Challenges, gaps, and way forward.

Quantifying drought's economic impacts has been key for decision-making to build future strategies and improve the development and implementation of proactive plans. However, climate change is changing drought frequency, intensity, and durability. These changes imply modifications of their economic impact, as longer droughts result in greater cumulative economic losses for water users. Though the longer the drought lasts, other factors also play a crucial role in its economic outcomes, such as Infrastructure capacity (IC), the Amount of Water in Storage (AWS) in reservoirs and aquifers, and short- and long-term responses to it. This study proposes and applies an analytical framework for the economic assessment of long-run droughts, assessing and explaining central Chile megadrought economic effects through the factors that begin to influence the economic impact level in this setting. High levels of both IC and the AWS, as well as short- and long-term responses of water users, allow for high resilience to long-run droughts, tolerating extraordinary water disruption in its society with relatively low total economic impacts. Despite this adaptability, long-term droughts bring places to a water-critical threshold where long-term adaptation strategies may be less flexible than short-term strategies, escalating the adverse economic effects. This fact suggests that the economic evaluation of megadrought needs to focus on future tipping points (substantial water scarcity). The tipping point depends on the IC, how water users manage the AWS, and adaptation strategies. Establishing the tipping point should be a priority for future interdisciplinary research.

Long-term oncological and surgical outcomes after Video Endoscopic Inguinal Lymphadenectomy (VEIL) in patients with penile cancer.

OBJECTIVE: To report outcomes from the largest multicenter series of penile cancer patients undergoing video endoscopic inguinal lymphadenectomy (VEIL). MATERIALS AND METHODS: Retrospective multicenter analysis. Authors of 21 centers from the Penile Cancer Collaborative Coalition-Latin America (PeC-LA) were included. All centers performed the procedure following the same previously described standardized technique. Inclusion criteria included penile cancer patients with no palpable lymph nodes and intermediate/high-risk disease and those with non-fixed palpable lymph nodes less than 4 cm in diameter. Categorical variables are shown as percentages and frequencies whereas continuous variables as mean and range. RESULTS: From 2006 to 2020, 210 VEIL procedures were performed in 105 patients. Mean age was 58 (45-68) years old. Mean operative time was 90 minutes (60-120). Mean lymph node yield was 10 nodes (6-16). Complication rate was 15.7%, including severe complications in 1.9% of procedures. Lymphatic and skin complications were noted in 8.6 and 4.8% of patients, respectively. Histopathological analysis revealed lymph node involvement in 26.7% of patients with non-palpable nodes. Inguinal recurrence was observed in 2.8% of patients. 10y- overall survival was 74.2% and 10-y cancer specific survival was 84.8%. CSS for pN0, pN1, pN2 and pN3 were 100%, 82.4%, 72.7% and 9.1%, respectively. CONCLUSION: VEIL seems to offer appropriate long term oncological control with minimal morbidity. In the absence of non-invasive stratification measures such as dynamic sentinel node biopsy, VEIL emerged as the alternative for the management of non-bulky lymph nodes in penile cancer.

Effect of Dapagliflozin on Clinical Outcomes in Patients With Chronic Kidney Disease, With and Without Cardiovascular Disease.

BACKGROUND: Dapagliflozin reduces the risk of end-stage renal disease in patients with chronic kidney disease. We examined the relative risk of cardiovascular and renal events in these patients and the effect of dapagliflozin on either type of event, taking account of history of cardiovascular disease. METHODS: In the DAPA-CKD trial (Dapagliflozin and Prevention of Adverse Outcomes in Chronic Kidney Disease), 4304 participants with chronic kidney disease were randomly assigned to dapagliflozin 10 mg once daily or placebo. The primary end point was a composite of sustained decline in estimated glomerular filtration rate ≥50%, end-stage kidney disease, or kidney or cardiovascular death. The secondary end points were a kidney composite outcome (primary end point, minus cardiovascular death), the composite of hospitalization for heart failure or cardiovascular death, and all-cause death. In a prespecified subgroup analysis, we divided patients into primary and secondary prevention subgroups according to history of cardiovascular disease. RESULTS: Secondary prevention patients (n=1610; 37.4%) were older, were more often male, had a higher blood pressure and body mass index, and were more likely to have diabetes. Mean estimated glomerular filtration rate and median urinary albumin-to-creatinine ratio were similar in the primary and secondary prevention groups. The rates of adverse cardiovascular outcomes were higher in the secondary prevention group, but kidney failure occurred at the same rate in the primary and secondary prevention groups. Dapagliflozin reduced the risk of the primary composite outcome to a similar extent in both the primary (hazard ratio, 0.61 [95% CI, 0.48-0.78]) and secondary (0.61 [0.47-0.79]) prevention groups (P-interaction=0.90). This was also true for the composite of heart failure hospitalization or cardiovascular death (0.67 [0.40-1.13] versus 0.70 [0.52-0.94], respectively; P-interaction=0.88), and all-cause mortality (0.63 [0.41-0.98] versus 0.70 [0.51-0.95], respectively; P-interaction=0.71). Rates of adverse events were low overall and did not differ between patients with and without cardiovascular disease. CONCLUSIONS: Dapagliflozin reduced the risk of kidney failure, death from cardiovascular causes or hospitalization for heart failure, and prolonged survival in people with chronic kidney disease, with or without type 2 diabetes, independently of the presence of concomitant cardiovascular disease. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03036150.

GM2/GM3 controls the organizational status of CD82/Met microdomains: further studies in GM2/GM3 complexation.

At cell surface gangliosides might associate with signal transducers proteins, grown factor receptors, integrins, small G-proteins and tetraspanins establishing microdomains, which play important role in cell adhesion, cell activation, motility, and growth. Previously, we reported that GM2 and GM3 form a heterodimer that interacts with the tetraspanin CD82, controlling epithelial cell mobility by inhibiting integrin-hepatocyte growth factor-induced cMet tyrosine kinase signaling. By using molecular dynamics simulations to study the molecular basis of GM2/GM3 interaction we demonstrate, here, that intracellular levels of Ca2+ mediate GM2/GM3 complexation via electrostatic interaction with their carboxyl groups, while hydrogen bonds between the ceramide groups likely aid stabilizing the complex. The presence of GM2/GM3 complex alters localization of CD82 on cell surface and therefore downstream signalization. These data contribute for the knowledge of how glycosylation may control signal transduction and phenotypic changes.

Quantitative and Anisotropic Mechanochromism of Polydiacetylene at Nanoscale.

Quantitative and anisotropic mechanochromism of polydiacetylene over nanoscale distances remains unaddressed even after 50 years of extensive research. This is because its anisotropic structure on substrates necessitates the application of both vertical and lateral forces (shear forces) to characterize it, whereas atomic force microscopy, which is the usual technique used to investigate nanoscale forces, is only capable of quantifying vertical forces. In this study, we address this lacuna by utilizing quantitative friction force microscopy that measures lateral forces. Our data confirm that polydiacetylene reacts only to lateral forces, F//, and disprove the previously claimed hypothesis that the edges of the polymer crystals exhibit higher force sensitivity than the rest of the crystal. In addition, we report a correlation between mechanochromism and thermochromism, which can be attributed to the fact that both work and heat are different means of providing the same transition energy.

Differential Frequencies of HLA-DRB1, DQA1, and DQB1 Alleles and Haplotypes Are Observed in the Arbovirus-Related Neurological Syndromes.

BACKGROUND: We took advantage of the 2015-2016 Brazilian arbovirus outbreak (Zika [ZIKV]/dengue/chikungunya viruses) associated with neurological complications to type HLA-DRB1/DQA1/DQB1 variants in patients exhibiting neurological complications and in bone marrow donors from the same endemic geographical region. METHODS: DRB1/DQA1/DQB1 loci were typed using sequence-specific oligonucleotides. In silico studies were performed using X-ray resolved dimer constructions. RESULTS: The DQA1*01, DQA1*05, DQB1*02, or DQB1*06 genotypes/haplotypes and DQA1/DQB1 haplotypes that encode the putative DQA1/DQB1 dimers were overrepresented in the whole group of patients and in patients exhibiting peripheral neurological spectrum disorders (PSD) or encephalitis spectrum disorders (ESD). The DRB1*04, DRB1*13, and DQA1*03 allele groups protected against arbovirus neurological manifestation, being underrepresented in whole group of patients and ESD and PSD groups. Genetic and in silico studies revealed that DQA1/DQB1 dimers (1) were primarily associated with susceptibility to arbovirus infections; (2) can bind to a broad range of ZIKV peptides (235 of 1878 peptides, primarily prM and NS2A); and (3) exhibited hydrophilic and highly positively charged grooves when compared to the DRA1/DRB1 cleft. The protective dimer (DRA1/DRB1*04) bound a limited number of ZIKV peptides (40 of 1878 peptides, primarily prM). CONCLUSION: Protective haplotypes may recognize arbovirus peptides more specifically than susceptible haplotypes.

Design and Validation of a Scalable, Reconfigurable and Low-Cost Structural Health Monitoring System.

This paper presents the design, development and testing of a low-cost Structural Health Monitoring (SHM) system based on MEMS (Micro Electro-Mechanical Systems) triaxial accelerometers. A new control system composed by a myRIO platform, managed by specific LabVIEW software, has been developed. The LabVIEW software also computes the frequency response functions for the subsequent modal analysis. The proposed SHM system was validated by comparing the data measured by this set-up with a conventional SHM system based on piezoelectric accelerometers. After carrying out some validation tests, a high correlation can be appreciated in the behavior of both systems, being possible to conclude that the proposed system is sufficiently accurate and sensitive for operative purposes, apart from being significantly more affordable than the traditional one.

SuAVE: A Tool for Analyzing Curvature-Dependent Properties in Chemical Interfaces.

Curvature is an intrinsic feature of biological membranes underlying vital cellular processes such as endocytosis, membrane fusion-fission, trafficking, and remodeling. The continuous expansion of the spatiotemporal scales accessible to computational simulations nowadays makes possible quasi-atomistic molecular dynamics simulations of these processes. In despite of that, computation of the shapes and curvatures associated with the dynamics of biological membranes remains challenging. For this reason, the effect of curvature is often neglected in the analysis of quantities essential for the accurate description of membrane properties (e.g., area and volume per lipid, density profiles, membrane thickness). We propose an algorithm for surface assessment via grid evaluation (SuAVE) that relies on the application of a radial base function to interpolate points scattered across an interface of any shape. This enables the representation of the chemical interface as fully differentiable so that related geometrical properties can be calculated through the straightforward employment of well-established differential geometry techniques. Hence, the effect of different types or degrees of curvature can be accurately taken into account in the calculations of structural properties of any interfaces regardless of chemical composition, asymmetry, and level of atom coarseness. The main functionalities implemented in SuAVE are featured for a number of tetraacylated and hexaacylated Lipid-A membranes of distinct curvatures and a surfactant micelle. We show that the properties calculated for moderately to highly curved membranes differ significantly between curvature-dependent and -independent algorithms. The SuAVE software is freely available from www.biomatsite.net/suave-software .

Rotational Profiler: A Fast, Automated, and Interactive Server to Derive Torsional Dihedral Potentials for Classical Molecular Simulations.

Rotational Profiler provides an analytical algorithm to compute sets of classical torsional dihedral parameters by fitting an empirical energy profile to a reference one that can be obtained experimentally or by quantum-mechanical methods. The resulting profiles are compatible with the functional forms in the most widely used biomolecular force fields (e.g., GROMOS, AMBER, OPLS, and CHARMM). The linear least-squares regression method is used to generate sets of parameters that best satisfy the fitting. Rotational Profiler is free to use, analytical, and force field/package independent. The formalism is herein described, and its usage, in an interactive and automated manner, is made available as a Web server at http://rotprof.lncc.br.