Helicobacter pylori infection in stomach leads to gastric cancer, gastric ulcer, and duodenal ulcer. More than 1 million people die each year due to these diseases, but why most H. pylori-infected individuals remain asymptomatic while a certain proportion develops such severe gastric diseases remained an enigma. Several studies indicated that gastric and intestinal microbiota may play a critical role in the development of the H. pylori-associated diseases. However, no specific microbe in the gastric or intestinal microbiota has been clearly linked to H. pylori infection and related gastric diseases. Here, we studied H. pylori infection, its virulence genes, the intestinal microbiota, and the clinical status of Trivandrum residents (N = 375) in southwestern India by standard H. pylori culture, PCR genotype, Sanger sequencing, and microbiome analyses using Illumina Miseq and Nanopore GridION. Our analyses revealed that gastric colonization by virulent H. pylori strains (vacAs1i1m1cagA+) is necessary but not sufficient for developing these diseases. Conversely, distinct microbial pools exist in the lower gut of the H. pylori-infected vs. H. pylori-non-infected individuals. Bifidobacterium (belonging to the phylum Actinobacteria) and Bacteroides (belonging to the phylum Bacteroidetes) were present in lower relative abundance for the H. pylori+ group than the H. pylori- group (p < 0.05). On the contrary, for the H. pylori+ group, genus Dialister (bacteria belonging to the phylum Firmicutes) and genus Prevotella (bacteria belonging to the phylum Bacteroidetes) were present in higher abundance compared to the H. pylori- group (p < 0.05). Notably, those who carried H. pylori in the stomach and had developed aggressive gastric diseases also had extremely low relative abundance (p < 0.05) of several Bifidobacterium species (e.g., B. adolescentis, B. longum) in the lower gut suggesting a protective role of Bifidobacterium. Our results show the link between lower gastrointestinal microbes and upper gastrointestinal diseases. Moreover, the results are important for developing effective probiotic and early prognosis of severe gastric diseases.

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The designing of drugs that can simultaneously affect different protein targets is one novel and promising way to treat complex diseases. Multitarget drugs act on multiple protein receptors each implicated in the same disease state, and may be considered to be more beneficial than conventional drug therapies. For example, these drugs can have improved therapeutic potency due to synergistic effects on multiple targets, as well as improved safety and resistance profiles due to the combined regulation of potential primary therapeutic targets and compensatory elements and lower dosage typically required. This review analyzes in‐silico methods that facilitate multitarget drug design that facilitate the discovery and development of novel therapeutic agents. Here presented is a summary of the progress in structure‐based drug discovery techniques that study the process of molecular recognition of targets and ligands, moving from static molecular docking to improved molecular dynamics approaches in multitarget drug design, and the advantages and limitations of each.

PKSIIIexplorer, a web server based on ‘transductive Support Vector Machine’ allows fast and reliable prediction of Type III polyketide synthase proteins. It provides a simple unique platform to identify the probability of a particular sequence, being a type III polyketide synthases or not with moderately high accuracy. We hope that our method could serve as a useful program for the type III polyketide researchers. The tool is available at “http://type3pks.in/tsvm/pks3”.AbbreviationsPKS - Polyketide synthase, CHS - Chalcone synthase, SVM - Support vector machine, MCC - Matthews Correlation Coefficient.