DruGAN: An Advanced Generative Adversarial Autoencoder Model for de Novo Generation of New Molecules with Desired Molecular Properties in Silico

© 2017 American Chemical Society. Deep generative adversarial networks (GANs) are the emerging technology in drug discovery and biomarker development. In our recent work, we demonstrated a proof-of-concept of implementing deep generative adversarial autoencoder (AAE) to identify new molecular fingerprints with predefined anticancer properties. Another popular generative model is the variational autoencoder (VAE), which is based on deep neural architectures. In this work, we developed an advanced AAE model for molecular feature extraction problems, and demonstrated its advantages compared to VAE in terms of (a) adjustability in generating molecular fingerprints; (b) capacity of processing very large molecular data sets; and (c) efficiency in unsupervised pretraining for regression model. Our results suggest that the proposed AAE model significantly enhances the capacity and efficiency of development of the new molecules with specific anticancer properties using the deep generative models

The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology

Recent advances in deep learning and specifically in generative adversarial networks have demonstrated surprising results in generating new images and videos upon request even using natural language as input. In this paper we present the first application of generative adversarial autoencoders (AAE) for generating novel molecular fingerprints with a defined set of parameters. We developed a 7-layer AAE architecture with the latent middle layer serving as a discriminator. As an input and output the AAE uses a vector of binary fingerprints and concentration of the molecule. In the latent layer we also introduced a neuron responsible for growth inhibition percentage, which when negative indicates the reduction in the number of tumor cells after the treatment. To train the AAE we used the NCI-60 cell line assay data for 6252 compounds profiled on MCF-7 cell line. The output of the AAE was used to screen 72 million compounds in PubChem and select candidate molecules with potential anticancer properties. This approach is a proof of concept of an artificially-intelligent drug discovery engine, where AAEs are used to generate new molecular fingerprints with the desired molecular properties

Two cases of hydrophobia in the Republic of Tatarstan: In vivo and postmortem laboratory diagnosis

The results of rabies in vivo and postmortem laboratory detection in two cases registered in the Republic of Tatarstan are reported: a victim bitten by a wolf in 2002 and another one bitten by a stray dog on Goa Island, India, in 2013. In the patient bitten by a wolf cornea imprints studies using the method of fluorescent antibodies (MFA) showed rabies-positive result 6 days before the patient's death. The results were confirmed by postmortem examination of different parts of the brain and salivary glands using the MFA, enzyme-linked immunosorbent assay (ELISA), optical microscopy, and bioassay methods. In the patient bitten by a stray dog the rabies virus specific antigen was detected by eye cornea studies using the MFA method and saliva studies using the ELISA. The rabies virus genome was also isolated from saliva and tear fluid using nested reverse-transcription polymerase chain reaction (RT-PCR) 9 days before the patient's death. The in vivo studies results were consistent with the postmortem study of different parts of the brain using the MFA, enzyme-linked immunosorbent assay (ELISA), optical microscopy, and bioassay methods. All the infection-positive results of both in vivo and postmortem studies were consistent with the clinical studies, i.e. rabies diagnosis was confirmed. The analysis of the rabies virus gene G fragment nucleotide sequence of 238 nd length showed a slight difference between the studied isolates (2 rabies) and the RABV AY956319 (1.68%), difference by 10.5% from the Vnukovo-32 vaccine strains and by 10.9 % from the SAD B19 rabies strain, respectively (rabies viruses of 1st genotype). It was also significantly different from the lissaviruses of 2,4,5, and 6 genotypes (21.0-32.7%). The obtained results indicate phylogenetic closeness of the studied isolates (2 rabies) with the RABV AY956319 rabies virus strain belonging to the 1st genotype

New function of the myostatin/activin type I receptor (ALK4) as a mediator of muscle atrophy and muscle regeneration

Skeletal muscle fibrosis and impaired muscle regeneration are major contributors to muscle wasting in Duchenne muscular dystrophy (DMD). Muscle growth is negatively regulated by myostatin (MSTN) and activins. Blockage of these pathways may improve muscle quality and function in DMD. Antisense oligonucleotides (AONs) were designed specifically to block the function of ALK4, a key receptor for the MSTN/activin pathway in skeletal muscle. AON-induced exon skipping resulted in specific Alk4 down-regulation, inhibition of MSTN activity, and increased myoblast differentiation in vitro Unexpectedly, a marked decrease in muscle mass (10%) was found after Alk4 AON treatment in mdx mice. In line with in vitro results, muscle regeneration was stimulated, and muscle fiber size decreased markedly. Notably, when Alk4 was down-regulated in adult wild-type mice, muscle mass decreased even more. RNAseq analysis revealed dysregulated metabolic functions and signs of muscle atrophy. We conclude that ALK4 inhibition increases myogenesis but also regulates the tight balance of protein synthesis and degradation. Therefore, caution must be used when developing therapies that interfere with MSTN/activin pathways

Novel robust biomarkers for human bladder cancer based on activation of intracellular signaling pathways

Sherpa Romeo blue journal. Open access article. Creative Commons Attribution 3.0 License (CC BY 3.0) applies.We recently proposed a new bioinformatic algorithm called OncoFinder for quantifying the activation of intracellular signaling pathways. It was proved advantageous for minimizing errors of high-throughput gene expression analyses and showed strong potential for identifying new biomarkers. Here, for the first time, we applied OncoFinder for normal and cancerous tissues of the human bladder to identify biomarkers of bladder cancer. Using Illumina HT12v4 microarrays, we profiled gene expression in 17 cancer and seven non-cancerous bladder tissue samples. These experiments were done in two independent laboratories located in Russia and Canada. We calculated pathway activation strength values for the investigated transcriptomes and identified signaling pathways that were regulated differently in bladder cancer (BC) tissues compared with normal controls. We found, for both experimental datasets, 44 signaling pathways that serve as excellent new biomarkers of BC, supported by high area under the curve (AUC) values. We conclude that the OncoFinder approach is highly efficient in finding new biomarkers for cancer. These markers are mathematical functions involving multiple gene products, which distinguishes them from “traditional” expression biomarkers that only assess concentrations of single genes.Ye

imPlatelet classifier: image-converted RNA biomarker profiles enable blood-based cancer diagnostics

Liquid biopsies offer a minimally invasive sample collection, outperforming traditional biopsies employed for cancer evaluation. The widely used material is blood, which is the source of tumor-educated platelets. Here, we developed the imPlatelet classifier, which converts RNA-sequenced platelet data into images in which each pixel corresponds to the expression level of a certain gene. Biological knowledge from the Kyoto Encyclopedia of Genes and Genomes was also implemented to improve accuracy. Images obtained from samples can then be compared against standard images for specific cancers to determine a diagnosis. We tested imPlatelet on a cohort of 401 non-small cell lung cancer patients, 62 sarcoma patients, and 28 ovarian cancer patients. imPlatelet provided excellent discrimination between lung cancer cases and healthy controls, with accuracy equal to 1 in the independent dataset. When discriminating between noncancer cases and sarcoma or ovarian cancer patients, accuracy equaled 0.91 or 0.95, respectively, in the independent datasets. According to our knowledge, this is the first study implementing an image-based deep-learning approach combined with biological knowledge to classify human samples. The performance of imPlatelet considerably exceeds previously published methods and our own alternative attempts of sample discrimination. We show that the deep-learning image-based classifier accurately identifies cancer, even when a limited number of samples are available.publishedVersio

Genome Characterization of a Pathogenic Porcine Rotavirus B Strain Identified in Buryat Republic, Russia in 2015

Citation: Alekseev, K.P.; Penin, A.A.; Mukhin, A.N.; Khametova, K.M.; Grebennikova, T.V.; Yuzhakov, A.G.; Moskvina, A.S.; Musienko, M.I.; Raev, S.A.; Mishin, A.M.; Kotelnikov, A.P.; Verkhovsky, O.A.; Aliper, T.I.; Nepoklonov, E.A.; Herrera-Ibata, D.M.; Shepherd, F.K.; Marthaler, D.G. Genome Characterization of a Pathogenic Porcine Rotavirus B Strain Identified in Buryat Republic, Russia in 2015. Pathogens 2018, 7, 46.An outbreak of enteric disease of unknown etiology with 60% morbidity and 8% mortality in weaning piglets occurred in November 2015 on a farm in Buryat Republic, Russia. Metagenomic sequencing revealed the presence of rotavirus B in feces from diseased piglets while no other pathogens were identified. Clinical disease was reproduced in experimentally infected piglets, yielding the 11 RVB gene segments for strain Buryat15, with an RVB genotype constellation of G12-P[4]-I13-R4-C4-M4-A8-N10-T4-E4-H7. This genotype constellation has also been identified in the United States. While the Buryat15 VP7 protein lacked unique amino acid differences in the predicted neutralizing epitopes compared to the previously published swine RVB G12 strains, this report of RVB in Russian swine increases our epidemiological knowledge on the global prevalence and genetic diversity of RVB