Combination Of Different Programs Research Articles

PhyEffector, the First Algorithm That Identifies Classical and Non-Classical Effectors in Phytoplasmas.

Phytoplasmas are the causal agents of more than 100 plant diseases in economically important crops. Eleven genomes have been fully sequenced and have allowed us to gain a better understanding of the biology and evolution of phytoplasmas. Effectors are key players in pathogenicity and virulence, and their identification and description are becoming an essential practice in the description of phytoplasma genomes. This is of particular importance because effectors are possible candidates for the development of new strategies for the control of plant diseases. To date, the prediction of effectors in phytoplasmas has been a great challenge; the reliable comparison of effectoromes has been hindered because research teams have used the combination of different programs in their predictions. This is not trivial since significant differences in the results can arise, depending on the predictive pipeline used. Here, we tested different predictive pipelines to create the PhyEffector algorithm; the average value of the F1 score for PhyEffector was 0.9761 when applied to different databases or genomes, demonstrating its robustness as a predictive tool. PhyEffector can recover both classical and non-classical phytoplasma effectors, making it an invaluable tool to accelerate effectoromics in phytoplasmas.

Protein Surface Printer for Exploring Protein Domains

The surface of proteins is vital in determining protein functions. Herein, a program, Protein Surface Printer (PSP), is built that performs multiple functions in quantifying protein surface domains. Two proteins, PETase and cytochrome P450, are used to validate that the program supports atomistic simulations with different combinations of programs and force fields. A case study is conducted on the structural analysis of the spike proteins of SARS-CoV-2 and SARS-CoV and the human cell receptor ACE2. Although the surface domains of both spike proteins are highly similar, their receptor-binding domains (RBDs) and the O-linked glycan domains are structurally different. The O-linked glycan domain of SARS-CoV-2 is highly positively charged, which may promote binding to negatively charged human cells.

PLIDflow: an open-source workflow for the online analysis of protein-ligand docking using galaxy.

Molecular docking is aimed at predicting the conformation of small-molecule (ligands) within an identified binding site (BS) in a target protein (receptor). Protein-ligand docking plays an important role in modern drug discovery and biochemistry for protein engineering. However, efficient docking analysis of proteins requires prior knowledge of the BS, which is not always known. The process which covers BS identification and protein-ligand docking usually requires the combination of different programs, which require several input parameters. This is furtherly aggravated when factoring in computational demands, such as CPU-time. Therefore, these types of simulation experiments can become a complex process for researchers without a background in computer sciences. To overcome these problems, we have designed an automatic computational workflow (WF) to process protein-ligand complexes, which runs from the identification of the possible BSs positions to the prediction of the experimental binding modes and affinities of the ligand. This open-access WF runs under the Galaxy platform that integrates public domain software. The results of the proposed method are in close agreement with state-of-the-art docking software. Software is available at: https://pistacho.ac.uma.es/galaxy-bitlab. euv@uma.es. Supplementary data are available at Bioinformatics online.

Assessing the potential impacts of WWTP effluent reductions within the Reedy River watershed

The Reedy River Basin originates along the northern fringe of the Greenville Metro Area and flows southward through downtown Greenville and continues for about 40 miles through increasingly rural lands until it empties into Lake Greenwood. This project evaluated the potential downstream impact to the Reedy River, Boyd Millpond, and Lake Greenwood from the removal of 100% of the effluent generated from various wastewater treatment plants along the river. Evaluation was performed using the Reedy River Model which is a combination of different programs including the EPA’s Loading Simulation Program in C++ (LSPC) and the Water Quality Analysis Simulation Program (WASP).Both water quality and quantity were analyzed as part of this study. The nitrogen and phosphorus species investigated in this study were total nitrogen (TN) and total phosphorus (TP). Simulation runs were conducted for the Reedy River Model holding all original parameters constant to those used in the TMDL analysis. The second simulation consisted of eliminating wastewater treatment plants from the model to simulate 100% removal of their wastewater effluent. To reflect dry, wet, and average years of rainfall, seven years of actual weather data for Greenville County were used within these simulation runs. Flow was modeled from the headwaters to the Reedy River Arm of Lake Greenwood. River sections analyzed included the river section immediately upstream and downstream of the wastewater treatment plant locations and Boyd Millpond and Reedy River Arm of Lake Greenwood.Removal of effluent resulted in a reduced average flow at Boyd Millpond from 8.52m3/s (301.23cfs) to 7.34m3/s (259.21cfs), a reduction in flow of 14%; and reduced average flow at Reedy River Arm of Lake Greenwood from 9.15m3/s (323.13cfs) to 7.97m3/s (281.46cfs), a reduction in flow of 12.9%. The removal of wastewater effluent had the greatest impact during periods of minimum flow when effluent makes up the largest percentage of total flow. During periods of drought, effluent removal resulted in a reduction in flow of almost 70% at the upper wastewater treatment plant, 66% at the lower wastewater treatment plant, 59% at Boyd Millpond, and 55% at Reedy River Arm of Lake Greenwood. Based on daily flow values averaged over seven years, total nitrogen and total phosphorus concentration and mass loads at Boyd Millpond and Reedy Arm will both decrease by approximately 50% with the elimination of effluent. This report only considers the impacts of effluent removal to flow, total phosphorus and total nitrogen as modeled by LSPC and WASP. Other variables that may be influenced from effluent removal include, pH, Dissolved Oxygen, fecal matter, heavy metals, water temperature, habitat quality, species diversity, macroinvertabrates, recreational uses, and economic impacts but are not included in this study.

INVESTIGATING THE ROLE OF CLU, PICALM, AND CR1 IN ALZHEIMER'S DISEASE

In 2009, two large genome wide association studies (GWAS) found associations between common single nucleotide polymorphisms (SNPs) at three loci (CLU, PICALM and CR1) and Alzheimer’s disease (AD) risk. The causal variants underlying these associations and how these impact on AD susceptibility remain unclear. Target enrichment and next generation sequencing (NGS) were used to completely resequence the three associated loci in 96 AD patients in an attempt to uncover potentially causative and rare variants that may explain the observed association signals. A pipeline was developed for the handling of pooled NGS data following a comparison of several different combinations of programs. 33 exonic SNPs were found within the three genes, along with over 1000 non-coding variants. To identify the variants most likely to be affecting AD risk, a two pronged approach was adopted. The variants were imputed in a large case-control cohort (2067 cases, 7376 controls) to test for association with AD, and the likely functional consequences of the variants were assessed using in silico resources. Several of the analysed variants showed suggestive or significant association with AD in the imputed data, and/or were predicted to have consequences on the function or regulation of the genes, suggesting avenues for future research in AD genetics. The whole method of pooled, targeted NGS and prioritisation using imputed data for association testing and in silico resources for functional analysis represents a new strategy for tracking down the illusive causation of GWAS signals.

Computer-aided drug design platform using PyMOL

The understanding and optimization of protein-ligand interactions are instrumental to medicinal chemists investigating potential drug candidates. Over the past couple of decades, many powerful standalone tools for computer-aided drug discovery have been developed in academia providing insight into protein-ligand interactions. As programs are developed by various research groups, a consistent user-friendly graphical working environment combining computational techniques such as docking, scoring, molecular dynamics simulations, and free energy calculations is needed. Utilizing PyMOL we have developed such a graphical user interface incorporating individual academic packages designed for protein preparation (AMBER package and Reduce), molecular mechanics applications (AMBER package), and docking and scoring (AutoDock Vina and SLIDE). In addition to amassing several computational tools under one interface, the computational platform also provides a user-friendly combination of different programs. For example, utilizing a molecular dynamics (MD) simulation performed with AMBER as input for ensemble docking with AutoDock Vina. The overarching goal of this work was to provide a computational platform that facilitates medicinal chemists, many who are not experts in computational methodologies, to utilize several common computational techniques germane to drug discovery. Furthermore, our software is open source and is aimed to initiate collaborative efforts among computational researchers to combine other open source computational methods under a single, easily understandable graphical user interface.

Photoperiodic Control of the Molt Cycle in the Chaffinch (Fringilla coelebs)

Abstract The molt cycle in Chaffinches (Fringilla coelebs) has a circannual periodicity under constant photoperiodic conditions (12:12LD, 20:4LD). The molt cycle and/or rate, however, can be modified by artificial alteration of daylength. The time of onset and completion of the post-nuptial molt in Chaffinches under natural conditions is a remote expression of vernal photostimulation. The timing of the molt is initiated at the end of the unifactorial phase of photoperiodic control. The onset of molt is induced after a latent period and its termination after another period, i.e. the molt begins and ends spontaneously. Under natural conditions, daylength immediately before and during the molt does not control either the time of onset or of termination of molt. The additional control system increases the rate of the molt in its early phase under short days, whereas under long days it decreases the rate of molt in its late phase. This system may play an adaptive role in synchronizing the end of the molt among birds that begin molt at different times. The postjuvenal molt begins and finishes spontaneously under control of a program of the individual development of juveniles. Short days increase the rate of molt and initiate earlier onset and completion, whereas long days decrease the rate of the molt and delay the times of onset and completion. Juvenile birds from late broods molt more rapidly than those from early broods. A combination of different programs and photoperiodic control of the molt synchronizes the termination of the molt in juveniles from early and late broods under natural conditions in summer and autumn.