Prediction of Antimicrobial Potential of a Chemically Modified Peptide From Its Tertiary Structure.

Designing novel antimicrobial peptides is a hot area of research in the field of therapeutics especially after the emergence of resistant strains against the conventional antibiotics. In the past number of methods have been developed for predicting the antimicrobial property of the peptide containing natural residues. This study describes models developed for predicting the antimicrobial property of a chemically modified peptide.

Discovery of rare cells from voluminous single cell expression data.

Single cell messenger RNA sequencing (scRNA-seq) provides a window into transcriptional landscapes in complex tissues. The recent introduction of droplet based transcriptomics platforms has enabled the parallel screening of thousands of cells. Large-scale single cell transcriptomics is advantageous as it promises the discovery of a number of rare cell sub-populations.

AutoImpute: Autoencoder based imputation of single-cell RNA-seq data.

The emergence of single-cell RNA sequencing (scRNA-seq) technologies has enabled us to measure the expression levels of thousands of genes at single-cell resolution. However, insufficient quantities of starting RNA in the individual cells cause significant dropout events, introducing a large number of zero counts in the expression matrix. To circumvent this, we developed an autoencoder-based sparse gene expression matrix imputation method.

A Web Resource for Designing Subunit Vaccine Against Major Pathogenic Species of Bacteria.

Evolution has led to the expansion of survival strategies in pathogens including bacteria and emergence of drug resistant strains proved to be a major global threat. Vaccination is a promising strategy to protect human population. Reverse vaccinology is a more robust vaccine development approach especially with the availability of large-scale sequencing data and rapidly dropping cost of the techniques for acquiring such data from various organisms.

Bifurcation analysis of insulin regulated mTOR signalling pathway in cancer cells.

Insulin induced mTOR signalling pathway is a complex network implicated in many types of cancers. The molecular mechanism of this pathway is highly complex and the dynamics is tightly regulated by intricate positive and negative feedback loops. In breast cancer cell lines, metformin has been shown to induce phosphorylation at specific serine sites in insulin regulated substrate of mTOR pathway that results in apoptosis over cell proliferation.

Prediction of Antitubercular Peptides From Sequence Information Using Ensemble Classifier and Hybrid Features.

Tuberculosis is one of the leading cause of death worldwide, particularly due to evolution of drug resistant strains. Antitubercular peptides may provide an alternate approach to combat antibiotic tolerance. Sequence analysis reveals that certain residues (e.

Acceptability of Mobile Phone-Based Nurse-Delivered Counseling Intervention to Improve HIV Treatment Adherence and Self-Care Behaviors Among HIV-Positive Women in India.

We assessed the acceptability of nurse-delivered mobile phone-based counseling to support adherence to antiretroviral treatment (ART) and self-care behaviors among HIV-positive women in India. We conducted open-ended, in-depth interviews with 27 HIV-positive women and 19 key informants at a government ART center in Karnataka, India. Data were analyzed with interpretive techniques.

Structure-Aware Principal Component Analysis for Single-Cell RNA-seq Data.

With the emergence of droplet-based technologies, it has now become possible to profile transcriptomes of several thousands of cells in a day. Although such a large single-cell cohort may favor the discovery of cellular heterogeneity, it also brings new challenges in the prediction of minority cell types. Identification of any minority cell type holds a special significance in knowledge discovery.

Overview of Free Software Developed for Designing Drugs Based on Protein-Small Molecules Interaction.

One of the fundamental challenges in designing drug molecule against a disease target or protein is to predict binding affinity between target and drug or small molecule. In this review, our focus will be on advancement in the field of protein-small molecule interaction. This review has been divided into four major sections.

Graph structured autoencoder.

In this work, we introduce the graph regularized autoencoder. We propose three variants. The first one is the unsupervised version.

Computer-aided prediction of antigen presenting cell modulators for designing peptide-based vaccine adjuvants.

Background: Evidences in literature strongly advocate the potential of immunomodulatory peptides for use as vaccine adjuvants. All the mechanisms of vaccine adjuvants ensuing immunostimulatory effects directly or indirectly stimulate antigen presenting cells (APCs). While numerous methods have been developed in the past for predicting B cell and T-cell epitopes; no method is available for predicting the peptides that can modulate the APCs.

An autoencoder based formulation for compressed sensing reconstruction.

This work proposes a new formulation for image reconstruction based on the autoencoder framework. The work follows the adaptive approach used in prior dictionary and transform learning based reconstruction techniques. Existing autoencoder based reconstructions are non-adaptive; they are trained on a separate training set and applied on another.

In silico approaches for predicting the half-life of natural and modified peptides in blood.

This paper describes a web server developed for designing therapeutic peptides with desired half-life in blood. In this study, we used 163 natural and 98 modified peptides whose half-life has been determined experimentally in mammalian blood, for developing in silico models. Firstly, models have been developed on 261 peptides containing natural and modified residues, using different chemical descriptors.

Data-driven analysis of biomedical literature suggests broad-spectrum benefits of culinary herbs and spices.

Spices and herbs are key dietary ingredients used across cultures worldwide. Beyond their use as flavoring and coloring agents, the popularity of these aromatic plant products in culinary preparations has been attributed to their antimicrobial properties. Last few decades have witnessed an exponential growth of biomedical literature investigating the impact of spices and herbs on health, presenting an opportunity to mine for patterns from empirical evidence.

Survival outcomes post percutaneous coronary intervention: Why the hype about stent type? Lessons from a healthcare system in India.

A prospective, multicenter study was initiated by the Government of Maharashtra, India, to determine predictors of long-term outcomes of percutaneous coronary intervention (PCI) for coronary artery disease, and to compare the effectiveness of drug-eluting stents (DESs) and bare-metal stents (BMSs) in patients undergoing PCI under government-funded insurance. The present analysis included 4595 patients managed between August 2012 and November 2016 at any of 110 participating centers. Using the classical multivariable regression and propensity-matching approach, we found age to be the most important predictor of 1-year mortality and target lesion revascularization at 1 year post-PCI.

CellAtlasSearch: a scalable search engine for single cells.

Owing to the advent of high throughput single cell transcriptomics, past few years have seen exponential growth in production of gene expression data. Recently efforts have been made by various research groups to homogenize and store single cell expression from a large number of studies. The true value of this ever increasing data deluge can be unlocked by making it searchable.

Prediction of Cell-Penetrating Potential of Modified Peptides Containing Natural and Chemically Modified Residues.

Designing drug delivery vehicles using cell-penetrating peptides is a hot area of research in the field of medicine. In the past, number of methods have been developed for predicting cell-penetrating property of peptides containing natural residues. In this study, first time attempt has been made to predict cell-penetrating property of peptides containing natural and modified residues.

AntiTbPdb: a knowledgebase of anti-tubercular peptides.

http://webs.iiitd.edu.

In Silico Tools and Databases for Designing Peptide-Based Vaccine and Drugs.

The prolonged conventional approaches of drug screening and vaccine designing prerequisite patience, vigorous effort, outrageous cost as well as additional manpower. Screening and experimentally validating thousands of molecules for a specific therapeutic property never proved to be an easy task. Similarly, traditional way of vaccination includes administration of either whole or attenuated pathogen, which raises toxicity and safety issues.

I have no peace of mind-psychosocial distress expressed by rural women living with HIV in India as part of a mobile health intervention-a qualitative study.

This qualitative study assessed psychosocial concerns that rural women with HIV who had multiple psychosocial vulnerabilities were able to express and communicate during a mobile phone intervention delivered by nurses. The study is part of a pilot randomised controlled trial of an mHealth self-care intervention by nurses for women living with HIV in rural India. For the trial, 60 women were randomised to receive the mHealth intervention.

Approach for Prediction of Antifungal Peptides.

This paper describes models developed using a wide range of peptide features for predicting antifungal peptides (AFPs). Our analyses indicate that certain types of residue (e.g.

A hierarchical anatomical classification schema for prediction of phenotypic side effects.

Prediction of adverse drug reactions is an important problem in drug discovery endeavors which can be addressed with data-driven strategies. SIDER is one of the most reliable and frequently used datasets for identification of key features as well as building machine learning models for side effects prediction. The inherently unbalanced nature of this data presents with a difficult multi-label multi-class problem towards prediction of drug side effects.

RNA secondary structure profiling in zebrafish reveals unique regulatory features.

Background: RNA is known to play diverse roles in gene regulation. The clues for this regulatory function of RNA are embedded in its ability to fold into intricate secondary and tertiary structure.

Results: We report the transcriptome-wide RNA secondary structure in zebrafish at single nucleotide resolution using Parallel Analysis of RNA Structure (PARS).

TopicalPdb: A database of topically delivered peptides.

TopicalPdb (http://crdd.osdd.net/raghava/topicalpdb/) is a repository of experimentally verified topically delivered peptides.

Multifaceted remodeling by vitamin C boosts sensitivity of Mycobacterium tuberculosis subpopulations to combination treatment by anti-tubercular drugs.

Bacterial dormancy is a major impediment to the eradication of tuberculosis (TB), because currently used drugs primarily target actively replicating bacteria. Therefore, decoding of the critical survival pathways in dormant tubercle bacilli is a research priority to formulate new approaches for killing these bacteria. Employing a network-based gene expression analysis approach, we demonstrate that redox active vitamin C (vit C) triggers a multifaceted and robust adaptation response in Mycobacterium tuberculosis (Mtb) involving ~ 67% of the genome.