Whole-genome sequencing identifies variants in ANK1, LRRN1, HAS1, and other genes and regulatory regions for stroke in type 1 diabetes.

Individuals with type 1 diabetes (T1D) carry a markedly increased risk of stroke, with distinct clinical and neuroimaging characteristics as compared to those without diabetes. Using whole-exome or whole-genome sequencing of 1,051 individuals with T1D, we aimed to find rare and low-frequency genomic variants associated with stroke in T1D. We analysed the genome comprehensively with single-variant analyses, gene aggregate analyses, and aggregate analyses on genomic windows, enhancers and promoters. In addition, we attempted replication in T1D using a genome-wide association study (N = 3,945) and direct genotyping (N = 3,263), and in the general population from the large-scale population-wide FinnGen project and UK Biobank summary statistics. We identified a rare missense variant on SREBF1 exome-wide significantly associated with stroke (rs114001633, p.Pro227Leu, p-value = 7.30 × 10-8), which replicated for hemorrhagic stroke in T1D. Using gene aggregate analysis, we identified exome-wide significant genes: ANK1 and LRRN1 displayed replication evidence in T1D, and LRRN1, HAS1 and UACA in the general population (UK Biobank). Furthermore, we performed sliding-window analyses and identified 14 genome-wide significant windows for stroke on 4q33-34.1, of which two replicated in T1D, and a suggestive genomic window on LINC01500, which replicated in T1D. Finally, we identified a suggestively stroke-associated TRPM2-AS promoter (p-value = 5.78 × 10-6) with borderline significant replication in T1D, which we validated with an in vitro cell-based assay. Due to the rarity of the identified genetic variants, future replication of the genomic regions represented here is required with sequencing of individuals with T1D. Nevertheless, we here report the first genome-wide analysis on stroke in individuals with diabetes.

FFParam-v2.0: A Comprehensive Tool for CHARMM Additive and Drude Polarizable Force-Field Parameter Optimization and Validation.

Developing production quality CHARMM force-field (FF) parameters is a very detailed process involving a variety of calculations, many of which are specific for the molecule of interest. The first version of FFParam was developed as a standalone Python package designed for the optimization of electrostatic and bonded parameters of the CHARMM additive and polarizable Drude FFs by using quantum mechanical (QM) target data. The new version of FFParam has multiple new capabilities for FF parameter optimization and validation, with an emphasis on the ability to use condensed-phase target data in optimization. FFParam-v2 allows optimization of Lennard-Jones (LJ) parameters using potential energy scans of interactions between selected atoms in a molecule and noble gases, viz., He and Ne, and through condensed-phase calculations, from which experimental observables such as heats of vaporization and free energies of solvation may be obtained. This functionality serves as a gold standard for both optimizing parameters and validating the performance of the final parameters. A new bonded parameter optimization algorithm has been introduced to account for simultaneously optimizing multiple molecules sharing parameters. FFParam-v2 also supports the comparison of normal modes and the potential energy distribution of internal coordinates towards each normal mode obtained from QM and molecular mechanics calculations. Such comparison capability is vital to validate the balance among various bonded parameters that contribute to the complex normal modes of molecules. User interaction has been extended beyond the original graphical user interface to include command-line interface capabilities that allow for integration of FFParam in workflows, thereby facilitating the automation of parameter optimization. With these new functionalities, FFParam is a more comprehensive parameter optimization tool for both beginners and advanced users.

L-type calcium channel blocker increases VEGF concentrations in retinal cells and human serum.

OBJECTIVE: Vascular endothelial growth factor (VEGF) plays a key role in diabetic retinopathy (DR). Previously, we have reported an association between mutations in a gene coding for the L-type calcium channel subunit, VEGF and DR. L-type calcium channel blockers (LTCCBs) have been widely used as antihypertensive medication (AHM), but their association with VEGF and DR is still unclear. Therefore, we explored the effect of LTCCBs compared to other AHMs on VEGF concentrations in retinal cells and human serum. Furthermore, we evaluated the association between the use of LTCCBs and the risk of severe diabetic eye disease (SDED). RESEARCH DESIGN AND METHODS: Müller cells (MIO-M1) were cultured as per recommended protocol and treated with LTCCBs and other AHMs. VEGF secreted from cells were collected at 24 hours intervals. In an interventional study, 39 individuals received LTCCBs or other AHM for four weeks with a four-week wash-out placebo period between treatments. VEGF was measured during the medication and placebo periods. Finally, we evaluated the risk of SDED associated with LTCCB usage in 192 individuals from the FinnDiane Study in an observational setting. RESULTS: In the cell cultures, the medium VEGF concentration increased time-dependently after amlodipine (P<0.01) treatment, but not after losartan (P>0.01), or lisinopril (P>0.01). Amlodipine, but no other AHM, increased the serum VEGF concentration (P<0.05) during the interventional clinical study. The usage of LTCCB was not associated with the risk of SDED in the observational study. CONCLUSIONS: LTCCB increases VEGF concentrations in retinal cells and human serum. However, the usage of LTCCBs does not appear to be associated with SDED in adults with type 1 diabetes.

Drude Polarizable Lipid Force Field with Explicit Treatment of Long-Range Dispersion: Parametrization and Validation for Saturated and Monounsaturated Zwitterionic Lipids.

Accurate empirical force fields of lipid molecules are a critical component of molecular dynamics simulation studies aimed at investigating properties of monolayers, bilayers, micelles, vesicles, and liposomes, as well as heterogeneous systems, such as protein-membrane complexes, bacterial cell walls, and more. While the majority of lipid force field-based simulations have been performed using pairwise-additive nonpolarizable models, advances have been made in the development of the polarizable force field based on the classical Drude oscillator model. In the present study, we undertake further optimization of the Drude lipid force field, termed Drude2023, including improved treatment of the phosphate and glycerol linker region of PC and PE headgroups, additional optimization of the alkene group in monounsaturated lipids, and inclusion of long-range Lennard-Jones interactions using the particle-mesh Ewald method. Initial optimization targeted quantum mechanical (QM) data on small model compounds representative of the linker region. Subsequent optimization targeted QM data on larger model compounds, experimental data, and dihedral potentials of mean force from the CHARMM36 additive lipid force field using a parameter reweighting protocol. The use of both experimental and QM target data during the reweighting protocol is shown to produce physically reasonable parameters that reproduce a collection of experimental observables. Target data for optimization included surface area/lipid for DPPC, DSPC, DMPC, and DLPC bilayers and nuclear magnetic resonance (NMR) order parameters for DPPC bilayers. Validation data include prediction of membrane thickness, scattering form factors, electrostatic potential profiles, compressibility moduli, surface area per lipid, water permeability, NMR T1 relaxation times, diffusion constants, and monolayer surface tensions for a variety of saturated and unsaturated lipid mono- and bilayers. Overall, the agreement with experimental data is quite good, though the results are less satisfactory for the NMR T1 relaxation times for carbons near the ester groups. Notable improvements compared to the additive C36 force field were obtained for membrane dipole potentials, lipid diffusion coefficients, and water permeability with the exception of monounsaturated lipid bilayers. It is anticipated that the optimized polarizable Drude2023 force field will help generate more accurate molecular simulations of pure bilayers and heterogeneous systems containing membranes, advancing our understanding of the role of electronic polarization in these systems.

The relationship between FGF23 and body composition according to albuminuria stage in type 1 diabetes.

AIMS: Fibroblast growth factor 23 (FGF23) and obesity are linked to kidney disease. However, the relationship between FGF23 and body composition is unclear. Associations between FGF23 and body composition were investigated in type 1 diabetes from the Finnish Diabetic Nephropathy Study according to albuminuria stages. METHODS: Data were available from 306 adults with type 1 diabetes (229 normal albumin excretion rate, T1Dnormo; 38 microalbuminuria, T1Dmicro; 39 macroalbuminuria, T1Dmacro), and 36 controls. Serum FGF23 was measured by ELISA. Body composition was assessed with dual-energy X-ray absorptiometry. Associations between body composition and serum FGF23 were investigated using linear regression models. RESULTS: Compared with T1Dnormo, individuals with more advanced kidney disease were older, had longer diabetes duration, higher serum hsCRP, and higher FGF23 concentration. However, FGF23 concentration was comparable between T1Dnormo and controls. Adjusted for potential confounders, in T1Dmicro, FGF23 was positively associated with the percentages of total fat, visceral fat, and android fat tissues, while negative associations between FGF23 and lean tissue were observed. FGF23 was not associated with body composition in T1Dnormo, T1Dmacro, and controls. CONCLUSIONS: In type 1 diabetes, the relationship between FGF23 and body composition is dependent on albuminuria stages.

Phytochemicals in the Synthetic Era: A Potential Oncosuppressor against Cancer Stem Cells.

CSCs (Cancer stem cells) are a subpopulation of transformed cells residing within the tumour that possesses properties of stem cells, like self-renewal and differentiation. Different signalling pathways, epigenetic changes, and interaction with a tumour microenvironment are found to be involved in the maintenance of stemness of CSCs and contribute to chemoresistance. Hence, it is difficult to prevent and control progression completely without considering CSCs as a crucial target. Some phytochemicals target different pathways and gene expression and modulate CSC markers to suppress the stemness properties of cancer cells. Thus, phytochemicals potentially impact CSCs which may be applied in chemo-prevention. This comprehensive review discusses some studied phytochemicals that suppress stemness characters in various cancer types both in vitro and in vivo animal models. However, the chemo-prevention ability of phytochemicals needs to be validated in further subsequent stages of clinical trials.

Constructing Potential Energy Surface with Correlated Theory for Dipeptides Using Molecular Tailoring Approach.

We demonstrate a cost-effective alternative employing the fragment-based molecular tailoring approach (MTA) for building the potential energy surface (PES) for two dipeptides viz. alanine-alanine and alanine-proline employing correlated theory, with augmented Dunning basis sets. About 1369 geometries are generated for each test dipeptide by systematically varying the dihedral angles Φ ${{\rm{\Phi }}}$ and Ψ ${{{\Psi }}}$ . These conformational geometries are partially optimized by relaxing all the other Z-matrix parameters, fixing the values of Φ ${{\rm{\Phi }}}$ and Ψ ${{{\Psi }}}$ . The MP2 level PES is constructed from the MTA-energies of chemically intact geometries using minimal hardware. The fidelity of MP2/aug-cc-pVDZ level PES is brought out by comparing it with its full calculation counterpart. Further, we bring out the power of the method by reporting the MTA-based CCSD/aug-cc-pVDZ level PES for these two dipeptides containing 498 and 562 basis functions respectively.

Harnessing Deep Learning for Optimization of Lennard-Jones Parameters for the Polarizable Classical Drude Oscillator Force Field.

The outcomes of computational chemistry and biology research, including drug design, are significantly influenced by the underlying force field (FF) used in molecular simulations. While improved FF accuracy may be achieved via inclusion of explicit treatment of electronic polarization, such an extension must be accompanied by optimization of van der Waals (vdW) interactions, in the context of the Lennard-Jones (LJ) formalism in the present study. This is particularly challenging due to the extensive nature of chemical space combined with the correlated nature of LJ parameters. To address this challenge, a deep learning (DL)-based parametrization framework is developed, allowing for sampling of wide ranges of LJ parameters targeting experimental condensed phase thermodynamic properties. The present work utilizes this framework to develop the LJ parameters for atoms associated with four distinct groups covering 10 different atom types. Final parameter selection was facilitated by quantum mechanical data on rare-gas interactions with the training set molecules. The chosen parameters were then validated through experimental hydration free energies and condensed phase thermodynamic properties of validation set molecules to confirm transferability. The ultimate outcome of utilizing this framework is a set of LJ parameters in the context of the polarizable Drude FF, which demonstrated improvement in the reproduction of both experimental pure solvent and crystal properties and hydration free energies of the molecules compared to the additive CHARMM General FF (CGenFF) including the ability of the Drude FF to accurately reproduce both experimental pure solvent properties and hydration free energies. The study also shows how correlations between difference in the reproduction of condensed phase data between model compounds may be used to direct the selection of new atom types and training set molecules during FF development.

Deep Neural Network Model to Predict the Electrostatic Parameters in the Polarizable Classical Drude Oscillator Force Field.

The Drude polarizable force field (FF) captures electronic polarization effects via auxiliary Drude particles that are attached to non-hydrogen atoms, distinguishing it from commonly used additive FFs that rely on fixed charges. The Drude FF currently includes parameters for biomolecules such as proteins, nucleic acids, lipids, and carbohydrates and small-molecule representative of those classes of molecules as well as a range of atomic ions. Extension of the Drude FF to novel small druglike molecules is challenging as it requires the assignment of partial charges, atomic polarizabilities, and Thole scaling factors. In the present article, deep neural network (DNN) models are trained on quantum mechanical (QM)-based partial charges and atomic polarizabilities along with Thole scale factors trained to target QM molecular dipole moments and polarizabilities. Training of the DNN model used a collection of 39 421 molecules with molecular weights up to 200 Da and containing H, C, N, O, P, S, F, Cl, Br, or I atoms. The DNN model utilizes bond connectivity, including 1,2, 1,3, 1,4, and 1,5 terms and distances of Drude FF atom types as the feature vector to build the model, allowing it to capture both local and nonlocal effects in the molecules. Novel methods have been developed to determine restrained electrostatic potential (RESP) charges on atoms and external points representing lone pairs and to determine Thole scale factors, which have no QM analogue. A penalty scheme is devised as a performance predictor of the trained model. Validation studies show that these DNN models can precisely predict molecular dipole and polarizabilities of Food and Drug Administration (FDA)-approved drugs compared to reference MP2 calculations. The availability of the DNN model allowing for the rapid estimation of the Drude electrostatic parameters will facilitate its applicability to a wider range of molecular species.

Targeting Ferroptosis Pathways: A Novel Strategy for Cancer Therapy.

Ferroptosis is an iron-dependent nonapoptotic kind of regulated cell death resulting from the destruction of redox balance in the cytosol. Unlike apoptosis, ferroptosis is caused by an increase in intracellular iron and lipid peroxides that causes significant damage to the membrane lipid bilayer and mitochondria leading to cell death. Increased iron level in the cell promotes ROS production. Ferroptosis inducer molecules increase ROS production and inhibit the antioxidant defence mechanism to facilitate ferroptosis in cancer cells. Inhibition of GPX4, redox-active iron availability, and lipid peroxidation are major contributors to ferroptosis. Ferroptosis is involved in many diseases like heart disease, neurodegenerative disease, and cancer. Ferroptosis induction recently emerged as an attractive strategy for cancer therapy. In this review, we discuss the regulatory mechanism of ferroptosis, its different hallmarks, including genetic and metabolic regulators and inducers that promote ferroptosis in the cancer cells. Finally, the latest progress and development in ferroptosis research in different cancers focusing on proposing a novel strategy in cancer therapy are discussed.

Inhibition Ability of Natural Compounds on Receptor-Binding Domain of SARS-CoV2: An In Silico Approach.

The lack of medication to treat COVID-19 is still an obstacle that needs to be addressed by all possible scientific approaches. It is essential to design newer drugs with varied approaches. A receptor-binding domain (RBD) is a key part of SARS-CoV-2 virus, located on its surface, that allows it to dock to ACE2 receptors present on human cells, which is followed by admission of virus into cells, and thus infection is triggered. Specific receptor-binding domains on the spike protein play a pivotal role in binding to the receptor. In this regard, the in silico method plays an important role, as it is more rapid and cost effective than the trial and error methods using experimental studies. A combination of virtual screening, molecular docking, molecular simulations and machine learning techniques are applied on a library of natural compounds to identify ligands that show significant binding affinity at the hydrophobic pocket of the RBD. A list of ligands with high binding affinity was obtained using molecular docking and molecular dynamics (MD) simulations for protein-ligand complexes. Machine learning (ML) classification schemes have been applied to obtain features of ligands and important descriptors, which help in identification of better binding ligands. A plethora of descriptors were used for training the self-organizing map algorithm. The model brings out descriptors important for protein-ligand interactions.

Genetic Profile of Endotoxemia Reveals an Association With Thromboembolism and Stroke.

Background Translocation of lipopolysaccharide from gram-negative bacteria into the systemic circulation results in endotoxemia. In addition to acute infections, endotoxemia is detected in cardiometabolic disorders, such as cardiovascular diseases and obesity. Methods and Results We performed a genome-wide association study of serum lipopolysaccharide activity in 11 296 individuals from 6 different Finnish study cohorts. Endotoxemia was measured by limulus amebocyte lysate assay in the whole population and by 2 other techniques (Endolisa and high-performance liquid chromatography/tandem mass spectrometry) in subpopulations. The associations of the composed genetic risk score of endotoxemia and thrombosis-related clinical end points for 195 170 participants were analyzed in FinnGen. Lipopolysaccharide activity had a genome-wide significant association with 741 single-nucleotide polymorphisms in 5 independent loci, which were mainly located at genes affecting the contact activation of the coagulation cascade and lipoprotein metabolism and explained 1.5% to 9.2% of the variability in lipopolysaccharide activity levels. The closest genes included KNG1, KLKB1, F12, SLC34A1, YPEL4, CLP1, ZDHHC5, SERPING1, CBX5, and LIPC. The genetic risk score of endotoxemia was associated with deep vein thrombosis, pulmonary embolism, pulmonary heart disease, and venous thromboembolism. Conclusions The biological activity of lipopolysaccharide in the circulation (ie, endotoxemia) has a small but highly significant genetic component. Endotoxemia is associated with genetic variation in the contact activation pathway, vasoactivity, and lipoprotein metabolism, which play important roles in host defense, lipopolysaccharide neutralization, and thrombosis, and thereby thromboembolism and stroke.

Additive CHARMM36 Force Field for Nonstandard Amino Acids.

Nonstandard amino acids are both abundant in nature, where they play a key role in various cellular processes, and can be synthesized in laboratories, for example, for the manufacture of a range of pharmaceutical agents. In this work, we have extended the additive all-atom CHARMM36 and CHARMM General force field (CGenFF) to a large set of 333 nonstandard amino acids. These include both amino acids with nonstandard side chains, such as post-translationally modified and artificial amino acids, as well as amino acids with modified backbone groups, such as chromophores composed of several amino acids. Model compounds representative of the nonstandard amino acids were parametrized for protonation states that are likely at the physiological pH of 7 and, for some more common residues, in both d- and l-stereoisomers. Considering all protonation, tautomeric, and stereoisomeric forms, a total of 406 nonstandard amino acids were parametrized. Emphasis was placed on the quality of both intra- and intermolecular parameters. Partial charges were derived using quantum mechanical (QM) data on model compound dipole moments, electrostatic potentials, and interactions with water. Optimization of all intramolecular parameters, including torsion angle parameters, was performed against information from QM adiabatic potential energy surface (PES) scans. Special emphasis was put on the quality of terms corresponding to PES around rotatable dihedral angles. Validation of the force field was based on molecular dynamics simulations of 20 protein complexes containing different nonstandard amino acids. Overall, the presented parameters will allow for computational studies of a wide range of proteins containing nonstandard amino acids, including natural and artificial residues.

The Collagen-Modifying Enzyme PLOD2 Is Induced and Required during L1-Mediated Colon Cancer Progression.

The overactivation of Wnt/ß-catenin signaling is a hallmark of colorectal cancer (CRC) development. We identified the cell adhesion molecule L1CAM (L1) as a target of ß-catenin-TCF transactivation in CRC cells. The overexpression of L1 in CRC cells confers enhanced proliferation, motility, tumorigenesis and liver metastasis, and L1 is exclusively localized in the invasive areas of human CRC tissue. A number of genes are induced after L1 transfection into CRC cells by a mechanism involving the cytoskeletal protein ezrin and the NF-κB pathway. When studying the changes in gene expression in CRC cells overexpressing L1 in which ezrin levels were suppressed by shRNA to ezrin, we discovered the collagen-modifying enzyme lysyl hydroxylase 2 (PLOD2) among these genes. We found that increased PLOD2 expression was required for the cellular processes conferred by L1, including enhanced proliferation, motility, tumorigenesis and liver metastasis, since the suppression of endogenous PLOD2 expression, or its enzymatic activity, blocked the enhanced tumorigenic properties conferred by L1. The mechanism involved in increased PLOD2 expression by L1 involves ezrin signaling and PLOD2 that affect the SMAD2/3 pathway. We found that PLOD2 is localized in the colonic crypts in the stem cell compartment of the normal mucosa and is found at increased levels in invasive areas of the tumor and, in some cases, throughout the tumor tissue. The therapeutic strategies to target PLOD2 expression might provide a useful approach for CRC treatment.

Luminescent naphthalimide-tagged ruthenium(ii)-arene complexes: cellular imaging, photocytotoxicity and transferrin binding.

Two water-soluble piano-stool shaped ruthenium(ii)-arene complexes, [RuII(η6-p-cymene)(L)Cl2] [RuLCl] and [RuII(η6-p-cymene)(L)(PTA)Cl] [RuLPTA], were designed as emissive photocytotoxic agents tagged with morpholine as the lysosome targeting moiety. Here, L = N-(2-morpholinoethyl)-4-(2-aminoethyl)amino-naphthalimide, and PTA = 1,3,5-triaza-7-phosphatricyclo-[3.3.1.1]decane. The crystal structure of [RuLCl] exhibits the pseudooctahedral 'three-legged piano-stool' geometry, wherein Ru(ii) is bound to the η6-p-cymene moiety as a base and two chlorides and the amine-N of the ligand L occupies the three legs of the stool. The complexes exhibited both the possibility of covalent adduct formation via the hydrolyzed Ru-Cl bond and non-covalent intercalation binding through planar naphthalimide moieties. The complexes showed enhanced photo-cytotoxicity under low-power blue LED light irradiation (λmax = 448 nm) mediated by 1O2, thereby acting as potential PDT agents. Fluorescence microscopy studies revealed that luminescent complexes preferentially localized in both the lysosomes and nucleus for effectively targeting and damaging the nuclear DNA for PDT effects. Due to enhanced lipophilicity of [RuLCl], it showed higher internalization into MCF-7 cell, measured in terms of the ruthenium content using ICP-MS. The interaction of the complexes with human transferrin (hTf) proteins was studied through molecular docking calculations, suggesting favorable binding through histidine residues and possible internalization into cancer cells via TfR-mediated endocytosis. The luminescence properties of the complexes were well-utilized to study their cellular uptake mechanism via endocytosis using fluorescence microscopy.

A Necessary Role for Increased Biglycan Expression during L1-Mediated Colon Cancer Progression.

Aberrant activation of Wnt/ß-catenin signaling and downstream ß-catenin-TCF target genes is a hallmark of colorectal cancer (CRC) development. We identified the immunoglobulin-like cell adhesion receptor L1CAM (L1) as a target of ß-catenin-TCF transactivation in CRC cells. Overexpression of L1 in CRC cells confers enhanced proliferation, motility, tumorigenesis, and liver metastasis, and L1 is exclusively localized at invasive areas of human CRC tissue. Several genes are induced after L1 transfection into CRC cells by a mechanism involving the L1-ezrin-NF-κB pathway. We conducted a secretomic analysis of the proteins in the culture medium of L1-overexpressing CRC cells. We detected a highly increased level of biglycan, a small leucine-rich ECM component, and a signaling molecule. We found that induction of biglycan is required for the cellular processes conferred by L1, including enhanced proliferation, motility, tumorigenesis, and liver metastasis. The suppression of endogenous biglycan levels or a point mutation in the L1 ectodomain that regulates cell-cell adhesion mediated by L1 blocked the enhanced tumorigenic properties conferred by L1. The mechanism of biglycan induction by L1 involves the L1-NF-κB pathway. Blocking NF-κB signaling in L1 expressing cells suppressed the induction of biglycan and the tumorigenic properties conferred by L1. Biglycan expression was undetectable in the normal colonic mucosa, but expressed at highly increased levels in the tumor tissue, especially in the stroma. The therapeutic strategies to target biglycan expression might provide a useful approach for CRC treatment in L1-overexpressing tumors.

Predicting Partition Coefficients of Neutral and Charged Solutes in the Mixed SLES-Fatty Acid Micellar System.

Sodium laureth sulfate (SLES) and fatty acids are common ingredients in many cosmetic products. Understanding how neutral and charged fatty acid compounds partition between micellar and water phases is crucial to achieve the optimal design of the product formulation. In this paper, we first study the formation of mixed SLES and fatty acid micelles using molecular dynamics (MD) simulations. Micelle/water partition coefficients of neutral and charged fatty acids are then calculated using COSMOmic as well as a MD approach based on the potential of mean force (PMF) calculations performed using umbrella sampling (US). The combined US/PMF approach was performed with both the additive, non-polarizable CHARMM general force field (CGenFF) and the classical Drude polarizable force field. The partition coefficients for the neutral solutes are shown to be accurately calculated with the COSMOmic and additive CGenFF US/PMF approaches, while only the US/PMF approach with the Drude polarizable force field accurately calculated the experimental partition coefficient of the charged solute. These results indicate the utility of the Drude polarizable force field as a tool for the rational development of mixed micelles.

FFParam: Standalone package for CHARMM additive and Drude polarizable force field parametrization of small molecules.

Accurate force-field (FF) parameters are key to reliable prediction of properties obtained from molecular modeling (MM) and molecular dynamics (MD) simulations. With ever-widening applicability of MD simulations, robust parameters need to be generated for a wider range of chemical species. The CHARMM General Force Field program (CGenFF, https://cgenff.umaryland.edu/) is a tool for obtaining initial parameters for a given small molecule based on analogy with the available CGenFF parameters. However, improvement of these parameters is often required and performing their optimization remains tedious and time consuming. In addition, tools for optimization of small molecule parameters in the context of the Drude polarizable FF are not yet available. To overcome these issues, the FFParam package has been designed to facilitate the parametrization process. The package includes a graphical user interface (GUI) created using Qt libraries. FFParam supports Gaussian and Psi4 for performing quantum mechanical calculations and CHARMM and OpenMM for MM calculations. A Monte Carlo simulated annealing (MCSA) algorithm has been implemented for automated fitting of partial atomic charge, atomic polarizabilities and Thole scale parameters. The LSFITPAR program is called for automated fitting of bonded parameters. Accordingly, FFParam provides all the features required for generation and analysis of CHARMM and Drude FF parameters for small molecules. FFParam-GUI includes a text editor, graph plotter, molecular visualization, and text to table converter to meet various requirements of the parametrization process. It is anticipated that FFParam will facilitate wider use of CGenFF as well as promote future use of the Drude polarizable FF.

CACNB2 Is a Novel Susceptibility Gene for Diabetic Retinopathy in Type 1 Diabetes.

Diabetic retinopathy is a common diabetes complication that threatens the eyesight and may eventually lead to acquired visual impairment or blindness. While a substantial heritability has been reported for proliferative diabetic retinopathy (PDR), only a few genetic risk factors have been identified. Using genome-wide sib pair linkage analysis including 361 individuals with type 1 diabetes, we found suggestive evidence of linkage with PDR at chromosome 10p12 overlapping the CACNB2 gene (logarithm of odds = 2.73). Evidence of association between variants in CACNB2 and PDR was also found in association analysis of 4,005 individuals with type 1 diabetes with an odds ratio of 0.83 and P value of 8.6 × 10-4 for rs11014284. Sequencing of CACNB2 revealed two coding variants, R476C/rs202152674 and S502L/rs137886839. CACNB2 is abundantly expressed in retinal cells and encodes the ß2 subunit of the L-type calcium channel. Blocking vascular endothelial growth factor (VEGF) by intravitreous anti-VEGF injections is a promising clinical therapy to treat PDR. Our data show that L-type calcium channels regulate VEGF expression and secretion from retinal pigment epithelial cells (ARPE19) and support the role of CACNB2 via regulation of VEGF in the pathogenesis of PDR. However, further genetic and functional studies are necessary to consolidate the findings.

Vimentin activation in early apoptotic cancer cells errands survival pathways during DNA damage inducer CPT treatment in colon carcinoma model.

Epithelial to mesenchymal transitions (EMT) is a preparatory process for cancer cells to attain motility and further metastasis to distant sites. Majority of DNA damaging drugs have shown to develop EMT as one of the major mechanisms to attain drug resistance. Here we sought to understand the resistance/survival instincts of cancer cells during initial phase of drug treatment. We provide a tangible evidence of stimulation of EMT factors in Apc knockout colorectal carcinoma model. Our results implied that CPT-treated Apc knockout cohorts depicted increased pro-invasive and pro-survival factors (Vimentin/pser38Vimentin & NFκB). Moreover, by cell sorting experiment, we have observed the expression of Vimentin in early apoptotic cells (AnnexinV positive) from 36 to 48 h of CPT treatment. We also observed the expression of chimeric Sec-AnnexinV-mvenus protein in migrated cells on transwell membrane recapitulating signatures of early apoptosis. Notably, induction of Vimentin-mediated signaling (by CPT) delayed apoptosis progression in cells conferring survival responses by modulating the promoter activity of NFκB. Furthermore, our results unveiled a novel link between Vimentin and ATM signaling, orchestrated via binding interaction between Vimentin and ATM kinase. Finally, we observed a significant alteration of crypt-villus morphology upon combination of DIM (EMT inhibitor) with CPT nullified the background EMT signals thus improving the efficacy of the DNA damaging agent. Thus, our findings revealed a resistance strategy of cancer cells within a very initial period of drug treatment by activating EMT program, which hinders the cancer cells to achieve later phases of apoptosis thus increasing the chances of early migration.