Heat shock proteins (HSPs) constitute a large family of proteins involved in protein folding and maturation whose expression is induced by heat shock or other stressors. HSPs play important roles in carcinogenesis via the regulation of angiogenesis, cell proliferation, migration, invasion, and metastasis. One of the most attractive targets for novel antitumor agents during recent years is the Heat shock proteins 90 (Hsp90), which is an essential molecular chaperone and it is responsible for the folding and maturation of nascent proteins.1 In this context, inhibition of Hsp90 has potential to disrupt multiple oncogenic pathways by an indirect attack on critical proteins and has become an attractive target for cancer therapy.2
This work aims to develop of new molecules based on quinone scaffold due that quinones derivatives have demonstrated potent anti-proliferative activity against estrogen-dependent cancers cell, as well as, induce the degradation of oncogenic Hsp90 client proteins. The set of 35 molecules reported by Blagg et al.3 were studied based in a hybrid strategy including Molecular Docking, Molecular Dynamics and 3D-QSAR analysis to identify the most relevant ligand-receptor interactions.4 The Correlation between the free energy of binding and binding modes for nafthoquinones derivatives are discussed. These results provide a new insight into protein–ligand interactions into the Hsp90, in addition, the analysis of the contour maps derived for 3D-QSAR provide helpful way about the rational modification of molecules in order to design more potent Hsp90 inhibitors.

The process of drug discovery or lead optimization involves the efficient synthesis of molecules and the creation of chemical libraries. For this reason, the rapid generation of new molecules is essential. Originally defined by Professors Barry K. Sharpless and M. G. Finn in 2001, Click chemistry is a very powerful tool to develop a set of original, selective, and modular building blocks such as azide and alkyne in small and large scales. It is a new type of chemistry that allow to synthesize complex molecules in an efficient way. The applications of this modular approach concern several domains of drug discovery, extending from lead finding through combinatorial chemistry, bionanoparticles, target-template to proteomics and DNA research using bioconjugation reactions. This article summarizes some progress and applications of click chemistry in drug discovery. We also describe the synthesis and characterization of a new triarylmethane prepared in our laboratory using this chemical strategy.

pKa values have a significant impact on the structure and function of biomolecules, influencing many physicochemical and ADME properties. Thus, the calculation of pKa values is widely used in different scientific communities, including bioinformatics, structural biology and medicinal chemistry. We have implemented a flexible tool to predict Poisson-Boltzmann-based pKa values of biomolecules. This is a free and open source project that provides a simple, reusable and extensible python API for pKa calculations with a valuable trade-off between fast and accurate predictions. With PypKa one can enable pKa calculations, including optional proton tautomerism, within existing protocols by adding two extra lines of code. PypKa supports CPU parallel computing on anisotropic (membrane) and isotropic (protein) systems, and allows the user to find a balance between accuracy and speed. Due to its open source nature, there is an opportunity to continually evolve a user-friendly, reliable and flexible API that has applicability across a wide range of fields.

We acknowledge financial support from FCT through grant SFRH/BPD/110491/2015 and projects PTDC/QEQCOM/5904/2014, UID/MULTI/00612/2013 and UID/MULTI/04046/2013.

The production and consumption of mushrooms of the genus Pleurotus in the present day has grown due to the fact they are a source of nutrients, are developed in a short time, and because of the diversity of substrates used in cultivation. The objective of the following work is to determine the best alternative of substrate for the cultivation of the mushroom Pleurotus ostreatus in agroindustrial waste of the sierra and the Ecuadorian Amazon (barley straw, wheat straw, bean peel, sugar cane bagasse, maize waste) in an individual form. An experimental design of a factor was used and variables were evaluated statistically such as the yield, the biological efficiency, precocity and the growth speed. The results statistically obtained indicate the barley straw as the best treatment, with a performance of 21.08%, biological efficiency of 84.83%, precocity of 18.6 days, growth speed of 5 days, pileus diameter of 4.9-5.9 cm, and protein content of 3.08%.

Sugar cane (Saccharum officinarum L.) is a crop with a high worldwide demand due to being the main source of sucrose and the wide range of products obtained. The production of granulated sugar non-centrifugal in the province of Pastaza is currently part of the diverse products that are obtained through sugar cane, being of great agroindustrial interest. By means of a descriptive questionnaire applied to 13 panela producers of the parish of Tarqui, identified that only one had sanitary registration and has faced problems such as: price instability, insufficient demand, regular infrastructure, limited process conditions, a lack of knowledge of the quality and control. The following presentation carried out a diagnostic of the operational parameters (pH, Brix, Temperature, Performance) of the process and the quality of the panela (% humidity, % cinder y color) in the industry “El Valle” for the duration of three months and determined that in the reception, extraction, clarification and evaporation (1,2,3,4), the pH values, brix and temperature are below the lower limit, while the performance of the trapiche is in an range 53,2 – 71,2% σ 5,3. With respect to the quality parameters, the values are outside what is established in the NTE INEN 2 332:2002 for granulated sugar non centrifugal with the humidity content of 2.8% σ 0,53, pH: 5,98 σ 0,13 and cinder 0,62 %; σ 0,03 at a level of confidence 95,0 %.

Molecular machines have recently been associated with the development of molecular carriers to enhance drug properties, such as solubility or bioavailability. One possible approach is through drug encapsulation by a host molecule, such as cucurbituril (CB) rings, which modifies the environment of the guest molecule. CB rings are able to encapsulate guest molecules providing a hydrophobic cavity and several carbonyl groups that stabilize cationic hosts that interact with this region. This results in significant pKa shifts for drugs with titrable (cationic) groups that can be exploited in order to improve drug bioavailability, whether by enhancing their solubility, stabilizing their active form or by protecting them against external agents. The aforementioned approach can be used for medical targeting, such as cancer therapy, by designing carriers that deliver guest molecules at specific conditions, knowing the specific target properties [1].

Computational tools are a powerful way to help the rational design of CB-guest complexes. In particular, the stochastic titration constant-pH MD (CpHMD) method allows a molecular dynamics simulation to have the pH value as an external parameter and, consequently, obtain full titration curves and pKa values. Our main goal is to develop a strategy to model benzimidazole (BZ) pKa shifts, a «proof-of-concept» molecule, and then extrapolate this process to other host-guest complexes. BZ has a well-known shift of ~3.5 pKa units when encapsulated by a CB ring and, with a CpHMD method, it is possible to elucidate the molecular details of these host-guest interactions.

Cryptosporidium is an intracellular protozoan described since 1907 by Tyzzer. Cryptosporidiosis is a cosmopolitan disease, whose incidence is higher in summer and rainy season. The objective of this research was to report the prevalence of Cryptosporidium spp. in sheep from 4 commercial sites in 3 Municipalities in the State of Mexico, Mexico in summer. 200 stool samples were taken from pregnant, non-pregnant and nursing ewes and lambs under one year old. All sheep were clinically healthy. A general prevalence of 61% was observed. Texcaltitlán had the highest prevalence (70%). Ewes (63 %) had higher prevalence than lambs (55%). Nursing ewes showed the highest prevalence (67%), which represents a high risk for lambs.

Abstract

Back ground: Amnesia is defined as an abnormal mental state in which memory and learning are affected out of all proportion to other cognitive functions. Memory loss may result from two-sided damage to parts of the brain vital for memory storage, processing or recall. Benzodiazepines are known to produce anterograde amnesia by involvement of GABAergic system and by interference of long term potentiation (LTP).In this study, we aimed to evaluate the effect of Morus alba fruit ethanolic extract (MAFEE) on diazepam induced amnesia in rats.

Materials and methods: MAFEE was administered for 14 successive days to rats (50 mg/kg). By using piracetam as the standard (dose 200 mg/kg), the ability of Morus alba fruit extract on diazepam induced amnesia in wistar rats was studied. The animals were randomly divided into 4 groups of Control, Diazepam treated (2mg/kg), MAFEE (50mg/kg) treated and Piracetam (200mg/kg) treated respectively. Y maze and open field habituation were employed parameters. The test methods like Y-Maze (to evaluate learning and memory), open field exploration studies are used to evaluate the anti –amnesic effect.

Result: Diazepam administration in rats at 2mg /kg for 14 days has induced anterograde amnesia.The parameters like % alterations (Y –Maze),line crossings, rearings and nose pokings ( open field test ) are used to assess the anti-amnesic effect of MAFEE in rats .Phytochemical investigation of ethanolic extract of Morus alba showed presence of both total phenolics (+++) and flavonoids (+++) . After the administration of MAFEE the behavioral analysis in rats was performed using Y -Maze and Open Field tests .MAFEE administration in rats has shown a significant increase (p<0.001) in spontaneous alterations on y-maze and line crossings and rearings on open field apparatus (p<0.05 ; p<0.01) when compared to diazepam treated group.How ever MAFEE administration has not shown any significant effect on nose pokings when compared to diazepam (p>0.05).

Conclusion: From our study results we validated the medicinal use of Morusalba for its anti-amnesic effect but still further research at molecular level has to be initiated to evaluate its role in cognitive dysfunction.

The manuscript presents three of my deep learning projects: mDL-ArtTranfer – Deep Learning Art Transfer using Multiple AIs (https://github.com/muntisa/mDL-ArtTransfer), CNN4Polyps - Colonoscopy polyp detection with Convolutional Neural Networks (https://github.com/muntisa/Colonoscopy-polyps-detection-with-CNNs), Deep-Politics - Prediction of Spanish Political Affinity with Deep Neural Nets: Socialist vs People's Party (PSOE vs PP, https://github.com/muntisa/Deep-Politics).

mDL-ArtTranfer is a mix of adapted scripts using three AI algorithms from fchollet, anishathalye, and ShafeenTejani (GitHub users). Thus, using content images and style pictures, three versions of art transfer will be apply with only one single call.

CNN4Polyps represents the first open GitHub repository for polyp detection and localization into colonoscopy images. The use of small CNNs with 2-3 convolutions, in only 2 minutes with GPU Nvidia Titan Xp, will generate a model with of 92%. The VGG16 transfer learning is no improving this accuracy. The fine tuning of the last convolutional block and the full connected layer of the pre-trained Imagenet VGG16 will generate an accuracy over 98%.

Deep-Politics is using the politician’s portrait to predict the affinity for two political parties in Spain. Both small CNNs with augmented data and VGG16 transfer learning without data augmentation can generate models with accuracy over 80%. The VGG16 fine tuning of the last two convolutional blocks and the full connected layer will raise the accuracy to 85%.

Protein tunnels and gates are attractive targets for drug design [1]. The drug molecules blocking the access of natural substrate or release of products are very efficient modulators of biological activity. Tunnels are important for the transport of ligands, solvent, and ions, and can be found in many proteins. We have developed a user-friendly graphical interface for a study of protein tunnels and channels Caver Analyst 2.0 [2]. Caver Analyst, part of the Caver suit [3], can be used to identify tunnels in both static structures as well as molecular dynamics trajectories. Studying tunnels in protein assemblies from molecular dynamics simulations offers possibilities to observe transient tunnels and their changes in time. Study of the transport of ligands through the protein tunnels can be carried out using the software CaverDock [4-6]. CaverDock is a fast, robust and accurate tool, which allows the screening of binding and unbinding processes for pharmacologically interesting compounds. It is based on a modified AutoDock Vina algorithm [6]. CaverDock is fast enough to be used in virtual screening studies. It is possible to choose how to treat the residues along the tunnel, this means that both rigid and flexible runs are available on this tool. The user can also define how many flexible residues to use.

The software Caver 3.0 and CaverAnalyst 2.0 are available free of charge at the website http://www.caver.cz/, while the software CaverDock 1.0 is available at the website https://loschmidt.chemi.muni.cz/caverdock/.

1. Marques, S.M., et al. 2016: Enzyme Tunnels and Gates as Relevant Targets in Drug Design. Medicinal Research Reviews 37: 1095-1139.
2. Adam Jurcik, David Bednar, Jan Byska, Sergio M. Marques, Katarina Furmanova, Lukas Daniel, Piia Kokkonen, Jan Brezovsky, Ondrej Strnad, Jan Stourac, Antonin Pavelka, Martin Manak, Jiri Damborsky, Barbora Kozlikova. 2018: Caver Analyst 2.0: Analysis and Visualization of Channels and Tunnels in Protein Structures and Molecular Dynamics Trajectories. Bioinformatics,34(20), 2018, 3586–3588 .
3. Chovancova, E. et al. (2012) PLOS Computational Biology 8: e1002708
4. Vavra, O., et al. 2018: CaverDock: A New Tool for Analysis of Ligand Binding and Unbinding Based on Molecular Docking. Bioinformatics (under review).
5. Filipovic, J., et al. 2018: A Novel Method for Analysis of Ligand Binding and Unbinding Based on Molecular Docking. IEEE/ACM Transactions on Computational Biology (under review).
6. Trott, O. and Olson, A.J., 2010: AutoDock Vina: Improving the Speed and Accuracy of Docking with a New Scoring Function, Efficient Optimization and Multithreading. Journal of Computational Chemistry 31: 455-461.