Benchmarking the Performance of Irregular Computations in AutoDock-GPU Molecular Docking.

Irregular applications can be found in different scientific fields. In computer-aided drug design, molecular docking simulations play an important role in finding promising drug candidates. AutoDock is a software application widely used for predicting molecular interactions at close distances. It is characterized by irregular computations and long execution runtimes. In recent years, a hardware-accelerated version of AutoDock, called AutoDock-GPU, has been under active development. This work benchmarks the recent code and algorithmic enhancements incorporated into AutoDock-GPU. Particularly, we analyze the impact on execution runtime of techniques based on early termination. These enable AutoDock-GPU to explore the molecular space as necessary, while safely avoiding redundant computations. Our results indicate that it is possible to achieve average runtime reductions of 50% by using these techniques. Furthermore, a comprehensive literature review is also provided, where our work is compared to relevant approaches leveraging hardware acceleration for molecular docking.

Accelerating AutoDock4 with GPUs and Gradient-Based Local Search.

AutoDock4 is a widely used program for docking small molecules to macromolecular targets. It describes ligand-receptor interactions using a physics-inspired scoring function that has been proven useful in a variety of drug discovery projects. However, compared to more modern and recent software, AutoDock4 has longer execution times, limiting its applicability to large scale dockings. To address this problem, we describe an OpenCL implementation of AutoDock4, called AutoDock-GPU, that leverages the highly parallel architecture of GPU hardware to reduce docking runtime by up to 350-fold with respect to a single-threaded process. Moreover, we introduce the gradient-based local search method ADADELTA, as well as an improved version of the Solis-Wets random optimizer from AutoDock4. These efficient local search algorithms significantly reduce the number of calls to the scoring function that are needed to produce good results. The improvements reported here, both in terms of docking throughput and search efficiency, facilitate the use of the AutoDock4 scoring function in large scale virtual screening.

El medio ambiente sano como derecho fundamental en Colombia / A healthy environment as a fundamental right in Colombia

El presente trabajo investigativo tiene por objetivo defender la tesis que el medio ambiente sano se ha configurado en la práctica y con suficientes bases teórico normativas como un derecho fundamental en el sistema jurídico colombiano; no solo por las decisiones que sobre él han tomado las altas cortes, sino además por la gran defensa que sobre él se hace en diferentes instrumentos internacionales. Se observarán tanto fuentes legales como doctrinarias con el objetivo de mostrar esta naturaleza (AU)

The present article aims to defend the thesis that the healthy environment has been configured in practice and with sufficient theoretical and normative bases as a fundamental right in the Colombian legal system, not only because of the decisions that the High Courts have made about it. but also for the great defense that it is done in different international instruments. Both legal and doctrinal sources will be observed to show this nature (AU)

El present article té per objectiu defensar la tesi que el medi ambient sa s'ha configurat en la pràctica i amb suficients bases teòric normatives com un dret fonamental en el sistema jurídic colombià; no només per les decisions que sobre ell han pres les altes corts, sinó a més per la gran defensa que sobre ell es fa en diferents instruments internacionals. S'observaran tant fonts legals com doctrinàries amb l'objectiu de mostrar aquesta naturalesa (AU)

GPU-Accelerated Drug Discovery with Docking on the Summit Supercomputer: Porting, Optimization, and Application to COVID-19 Research.

Protein-ligand docking is an in silico tool used to screen potential drug compounds for their ability to bind to a given protein receptor within a drug-discovery campaign. Experimental drug screening is expensive and time consuming, and it is desirable to carry out large scale docking calculations in a high-throughput manner to narrow the experimental search space. Few of the existing computational docking tools were designed with high performance computing in mind. Therefore, optimizations to maximize use of high-performance computational resources available at leadership-class computing facilities enables these facilities to be leveraged for drug discovery. Here we present the porting, optimization, and validation of the AutoDock-GPU program for the Summit supercomputer, and its application to initial compound screening efforts to target proteins of the SARS-CoV-2 virus responsible for the current COVID-19 pandemic.

D3R Grand Challenge 4: prospective pose prediction of BACE1 ligands with AutoDock-GPU.

In this paper we describe our approaches to predict the binding mode of twenty BACE1 ligands as part of Grand Challenge 4 (GC4), organized by the Drug Design Data Resource. Calculations for all submissions (except for one, which used AutoDock4.2) were performed using AutoDock-GPU, the new GPU-accelerated version of AutoDock4 implemented in OpenCL, which features a gradient-based local search. The pose prediction challenge was organized in two stages. In Stage 1a, the protein conformations associated with each of the ligands were undisclosed, so we docked each ligand to a set of eleven receptor conformations, chosen to maximize the diversity of binding pocket topography. Protein conformations were made available in Stage 1b, making it a re-docking task. For all calculations, macrocyclic conformations were sampled on the fly during docking, taking the target structure into account. To leverage information from existing structures containing BACE1 bound to ligands available in the PDB, we tested biased docking and pose filter protocols to facilitate poses resembling those experimentally determined. Both pose filters and biased docking resulted in more accurate docked poses, enabling us to predict for both Stages 1a and 1b ligand poses within 2 Å RMSD from the crystallographic pose. Nevertheless, many of the ligands could be correctly docked without using existing structural information, demonstrating the usefulness of physics-based scoring functions, such as the one used in AutoDock4, for structure based drug design.

Comparison of affinity ranking using AutoDock-GPU and MM-GBSA scores for BACE-1 inhibitors in the D3R Grand Challenge 4.

Molecular docking has been successfully used in computer-aided molecular design projects for the identification of ligand poses within protein binding sites. However, relying on docking scores to rank different ligands with respect to their experimental affinities might not be sufficient. It is believed that the binding scores calculated using molecular mechanics combined with the Poisson-Boltzman surface area (MM-PBSA) or generalized Born surface area (MM-GBSA) can predict binding affinities more accurately. In this perspective, we decided to take part in Stage 2 of the Drug Design Data Resource (D3R) Grand Challenge 4 (GC4) to compare the performance of a quick scoring function, AutoDock4, to that of MM-GBSA in predicting the binding affinities of a set of [Formula: see text]-Amyloid Cleaving Enzyme 1 (BACE-1) ligands. Our results show that re-scoring docking poses using MM-GBSA did not improve the correlation with experimental affinities. We further did a retrospective analysis of the results and found that our MM-GBSA protocol is sensitive to details in the protein-ligand system: (i) neutral ligands are more adapted to MM-GBSA calculations than charged ligands, (ii) predicted binding affinities depend on the initial conformation of the BACE-1 receptor, (iii) protonating the aspartyl dyad of BACE-1 correctly results in more accurate binding affinity predictions.

Automatic classification of pediatric pneumonia based on lung ultrasound pattern recognition.

Pneumonia is one of the major causes of child mortality, yet with a timely diagnosis, it is usually curable with antibiotic therapy. In many developing regions, diagnosing pneumonia remains a challenge, due to shortages of medical resources. Lung ultrasound has proved to be a useful tool to detect lung consolidation as evidence of pneumonia. However, diagnosis of pneumonia by ultrasound has limitations: it is operator-dependent, and it needs to be carried out and interpreted by trained personnel. Pattern recognition and image analysis is a potential tool to enable automatic diagnosis of pneumonia consolidation without requiring an expert analyst. This paper presents a method for automatic classification of pneumonia using ultrasound imaging of the lungs and pattern recognition. The approach presented here is based on the analysis of brightness distribution patterns present in rectangular segments (here called "characteristic vectors") from the ultrasound digital images. In a first step we identified and eliminated the skin and subcutaneous tissue (fat and muscle) in lung ultrasound frames, and the "characteristic vectors"were analyzed using standard neural networks using artificial intelligence methods. We analyzed 60 lung ultrasound frames corresponding to 21 children under age 5 years (15 children with confirmed pneumonia by clinical examination and X-rays, and 6 children with no pulmonary disease) from a hospital based population in Lima, Peru. Lung ultrasound images were obtained using an Ultrasonix ultrasound device. A total of 1450 positive (pneumonia) and 1605 negative (normal lung) vectors were analyzed with standard neural networks, and used to create an algorithm to differentiate lung infiltrates from healthy lung. A neural network was trained using the algorithm and it was able to correctly identify pneumonia infiltrates, with 90.9% sensitivity and 100% specificity. This approach may be used to develop operator-independent computer algorithms for pneumonia diagnosis using ultrasound in young children.

Evaluating Different Virulence Traits of Klebsiella pneumoniae Using Dictyostelium discoideum and Zebrafish Larvae as Host Models.

Multiresistant and invasive hypervirulent Klebsiella pneumoniae strains have become one of the most urgent bacterial pathogen threats. Recent analyses revealed a high genomic plasticity of this species, harboring a variety of mobile genetic elements associated with virulent strains, encoding proteins of unknown function whose possible role in pathogenesis have not been addressed. K. pneumoniae virulence has been studied mainly in animal models such as mice and pigs, however, practical, financial, ethical and methodological issues limit the use of mammal hosts. Consequently, the development of simple and cost-effective experimental approaches with alternative host models is needed. In this work we described the use of both, the social amoeba and professional phagocyte Dictyostelium discoideum and the fish Danio rerio (zebrafish) as surrogate host models to study K. pneumoniae virulence. We compared three K. pneumoniae clinical isolates evaluating their resistance to phagocytosis, intracellular survival, lethality, intestinal colonization, and innate immune cells recruitment. Optical transparency of both host models permitted studying the infective process in vivo, following the Klebsiella-host interactions through live-cell imaging. We demonstrated that K. pneumoniae RYC492, but not the multiresistant strains 700603 and BAA-1705, is virulent to both host models and elicits a strong immune response. Moreover, this strain showed a high resistance to phagocytosis by D. discoideum, an increased ability to form biofilms and a more prominent and irregular capsule. Besides, the strain 700603 showed the unique ability to replicate inside amoeba cells. Genomic comparison of the K. pneumoniae strains showed that the RYC492 strain has a higher overall content of virulence factors although no specific genes could be linked to its phagocytosis resistance, nor to the intracellular survival observed for the 700603 strain. Our results indicate that both zebrafish and D. discoideum are advantageous host models to study different traits of K. pneumoniae that are associated with virulence.

Grado de conocimiento acerca de la prevención de osteoporosis en cesantes y jubilados del sector educación de Lambayeque - junio del 2015 / Degree of knowledge about the prevention of osteoporosis in unemployed and retired education sector Lambayeque - June 2015

Objetivo: Determinar el grado de conocimiento acerca de la prevención de osteoporosis (OP) en cesantes y jubilados del sector educación de Lambayeque. Material y Métodos: Estudio transversal, descriptivo, observacional, sobre 311 personas perteneciente al Fondo de cesantes y jubilados del sector de educación en Lambayeque, para el grado de conocimiento acerca de la OP se utilizó un cuestionario previamente validado y estructurado a partir del modelo OKAT. El Análisis estadístico se realizó con Excel y SPSS, nivel de confianza del 95% y significancia de 0, 05. Resultados: El 56,59% tenía un conocimiento apropiado de osteoporosis, con una calificación promedio de 12 preguntas acertadas. El 62,7% mencionaron haber recibido información previa sobre OP. El 57,23% afirma haber escuchado información acerca de la osteoporosis en la televisión, seguido del consultorio médico 24,76% . Solo el 10,93% afirma tener el hábito de fumar y el 13,18% afirma tener el hábito de consumir alcohol. Conclusiones: El grado de conocimiento sobre la osteoporosis es bajo en los cesantes y jubilados del sector educación. La información recibida sobre la enfermedad previamente es pobre. La información que reciben las personas sobre OP no proviene de los médicos. Las actitudes hacia la osteoporosis demandan mayor compromiso por el personal de salud para difundir un mejor conocimiento y evitar las complicaciones propias de esta enfermedad.

Objetive: Determine the extent of knowledge about the prevention of osteoporosis (OP) in unemployed and retired Lambayeque education sector. Materials and Methods: Cross-sectional non-experimental type, on a random sample of 311 people belonging to the Fund of Retirees of the education sector in Lambayeque. Information on the degree of knowledge about the OPwas obtained by a previously validated and structured from OKAT model questionnaire. Statistical analysis was performed using Excel and SPSS software, with a confidence level of 95% and a significance level of 0.5. Results: During the study 56.59% hadaproper understanding of osteoporosis, with an average score of 12 right questions. 62.7% mentioned having received prior information on OP. The 57.23% say they have heard about osteoporosis on television, followed by 24.76% medical office. Only 10.93% claims to have smoking and 13.18% say they have the habit of consuming alcohol. Conclusions: The level of knowledge about osteoporosis according to the questionnaire is low in unemployed and retired education sector. The reports of the disease is previously poor. The information received by people on OPcomes not from doctors. Attitudes towards osteoporosis demand greater commitment by health workers to spread a better understanding and to avoid the complications of this disease.

Induced reproduction and early development histology of Oscar Astronotus ocellatus (Agassiz, 1831).

Oscar (Astronotus ocellatus) is an important fish from the Amazon Basin that has great potential for fish farming, human consumption, sport fishing and fish keeping. This study aimed to evaluate the effect of two hormonal treatments on the induction of artificial reproduction in broodstock and to describe the histological development of embryos and larvae. Broodstocks were selected and induced using two different hormones: (i) extract of carp pituitary (ECP); and (ii) synthetic human chorionic gonadotropin (hCG). Spawnings were transferred to hatcheries, collected at pre-established times, processed and analysed by histology. Astronotus ocellatus did not respond well to induced reproduction. From 16 couples of breeding fish, only five out of the eight females released oocytes after the hormonal action time, three with hCG and two with ECP; just one male responded positively to hCG. Oscar eggs were oval, and semi-adhesive, the yolk contained granules, and egg diameter was approximately 1.65 ± 0.057 to 1.98 ± 0.038 mm. Development from the initial collection (IC) point until the total absorption of the yolk lasted 315 h, at an average temperature of 27.45 ± 2.13°C. Several events marked embryonic and larval development, including the formation of the optic cup, forebrain, otic vesicle and cephalic divisions. The newly hatched larvae had non-pigmented eyes, and a closed mouth and anus, as well as the presence of adhesive glands on the head. Larval development was characterized by formation of the heart, liver, gaseous bladder, gills, pronephros, brain, fins and also the digestive tract. These results provide important information for the rearing and reproduction of A. ocellatus.

Early development of Astronotus ocellatus under stereomicroscopy and scanning electron microscopy.

Astronotus ocellatus, popularly known as Oscar, is a cichlid fish from the Amazon basin (Brazil) with a great potential for fish farming. The aim of this research is to describe the morphology of eggs and larvae of A. ocellatus under stereomicroscopy and scanning electron microscopy. Eggs from natural spawnings were taken to hatcheries, collected at previously established time periods and then analysed. Oscar's eggs are demersal, adhesive and fragile to touch, with a slightly oval shape. The fertile eggs are yellowish in colour and when unfertilized are a white opaque colour. In the initial collection (IC), the majority of eggs were found to be at the gastrula phase with 30% epiboly. At 12 h after the IC, the formation of the embrionary axis and somites was observed, followed by differentiation of the tail and of the head. Fifteen hours after the IC, the emergence of the optic and otic vesicles, and of adhesive glands and the yolk pigmentation was observed. Larval hatching took place between 46 and 58 h after the first collection, at an average temperature of 27.45 ± 2.13°C. The larval stage was characterized by the development of the heart, fins, branchial apparatus, neuromasts, taste buds and adhesive glands on the head. Larval development to yolk absorption took a period of 257 h. These results provide important information for reproduction, rearing and preservation of A. ocellatus.