High-throughput prioritization of target proteins for development of new antileishmanial compounds

Leishmaniasis, a vector-borne disease, is caused by the infection of Leishmania spp., obligate intracellular protozoan parasites. Presently, human vaccines are unavailable, and the primary treatment relies heavily on systemic drugs, often presenting with suboptimal formulations and substantial toxicity, making new drugs a high priority for LMIC countries burdened by the disease, but a low priority in the agenda of most pharmaceutical companies due to unattractive profit margins. New ways to accelerate the discovery of new, or the repositioning of existing drugs, are needed. To address this challenge, our study aimed to identify potential protein targets shared among clinically-relevant Leishmania species. We employed a subtractive proteomics and comparative genomics approach, integrating high-throughput multi-omics data to classify these targets based on different druggability metrics. This effort resulted in the ranking of 6502 ortholog groups of protein targets across 14 pathogenic Leishmania species. Among the top 20 highly ranked groups, metabolic processes known to be attractive drug targets, including the ubiquitination pathway, aminoacyl-tRNA synthetases, and purine synthesis, were rediscovered. Additionally, we unveiled novel promising targets such as the nicotinate phosphoribosyltransferase enzyme and dihydrolipoamide succinyltransferases. These groups exhibited appealing druggability features, including less than 40% sequence identity to the human host proteome, predicted essentiality, structural classification as highly druggable or druggable, and expression levels above the 50th percentile in the amastigote form. The resources presented in this work also represent a comprehensive collection of integrated data regarding trypanosomatid biology.

iTRAQ-based proteomic analysis reveals the molecule mechanism of reducing higher alcohols in Chinese rice wine by nitrogen compensation

Purpose

Higher alcohol is a by-product of the fermentation of wine, and its content is one of the most important parameters that affect and are used to appraise the final quality of Chinese rice wine. Ammonium compensation is an efficient and convenient method to reduce the content of higher alcohols, but the molecule mechanism is poorly understood. Therefore, an iTRAQ-based proteomic analysis was designed to reveal the proteomic changes of Saccharomyces cerevisiae to elucidate the molecular mechanism of ammonium compensation in reducing the content of higher alcohols.

Methods

The iTRAQ proteomic analysis method was used to analyze a blank group and an experimental group with an exogenous addition of 200 mg/L (NH4)2HPO4 during inoculation. The extracted intracellular proteins were processed by liquid chromatography-mass spectrometry and identified using bioinformatics tools. Real-time quantitative polymerase chain reaction was used to verify the gene expression of differentially expressed proteins.

Results

About 4062 proteins, including 123 upregulated and 88 downregulated proteins, were identified by iTRAQ-based proteomic analysis. GO and KEGG analysis uncovered that significant proteins were concentrated during carbohydrate metabolism, such as carbon metabolism, glyoxylate, and dicarboxylate metabolism, pyruvate metabolism, and the nitrogen metabolism, such as amino acid synthesis and catabolism pathway. In accordance with the trend of differential protein regulation in the central carbon metabolism pathway and the analysis of carbon metabolic flux, a possible regulatory model was proposed and verified, in which ammonium compensation facilitated glucose consumption, regulated metabolic flow direction into tricarboxylic acid, and further led to a decrease in higher alcohols. The results of RT-qPCR confirmed the authenticity of the proteomic analysis results at the level of gene.

Conclusion

Ammonium assimilation promoted by ammonium compensation regulated the intracellular carbon metabolism of S. cerevisiae and affected the distribution of metabolic flux. The carbon flow that should have gone to the synthesis pathway of higher alcohols was reversed to the TCA cycle, thereby decreasing the content of higher alcohols. These findings may contribute to an improved understanding of the molecular mechanism for the decrease in higher alcohol content through ammonium compensation.

In silico Metabolic Pathway Analysis Identifying Target Against Leishmaniasis - A Kinetic Modeling Approach

The protozoan Leishmania donovani, from trypanosomatids family is a deadly human pathogen responsible for causing Visceral Leishmaniasis. Unavailability of proper treatment in the developing countries has served as a major threat to the people. The absence of vaccines has made treatment possibilities to rely solely over chemotherapy. Also, reduced drug efficacy due to emerging resistant strains magnifies the threat. Despite years of formulations for an effective drug therapy, complexity of the disease is also unfortunately increasing. Absence of potential drug targets has worsened the scenario. Therefore exploring new therapeutic approach is a priority for the scientific community to combat the disease. One of the most reliable ways to alter the adversities of the infection is finding new biological targets for designing potential drugs. An era of computational biology allows identifying targets, assisting experimental studies. It includes sorting the parasite’s metabolic pathways that pins out proteins essential for its survival. We have directed our study towards a computational methodology for determining targets against L. donovani from the “purine salvage” pathway. This is a mainstay pathway towards the maintenance of purine amounts in the parasitic pool of nutrients proving to be mandatory for its survival. This study represents an integration of metabolic pathway and Protein-Protein Interactions analysis. It consists of incorporating the available experimental data to the theoretical methods with a prospective to develop a kinetic model of Purine salvage pathway. Simulation data revealed the time course mechanism of the enzymes involved in the synthesis of the metabolites. Modeling of the metabolic pathway helped in marking of crucial enzymes. Additionally, the PPI analysis of the pathway assisted in building a static interaction network for the proteins. Topological analysis of the PPI network through centrality measures (MCC and Closeness) detected targets found common with Dynamic Modeling. Therefore our analysis reveals the enzymes ADSL (Adenylosuccinate lyase) and IMPDH (Inosine-5′-monophosphate dehydrogenase) to be important having a central role in the modeled network based on PPI and kinetic modeling techniques. Further the available three dimensional structure of the enzyme “ADSL” aided towards the search for potential inhibitors against the protein. Hence, the study presented the significance of integrating methods to identify key proteins which might be putative targets against the treatment of Visceral Leishmaniasis and their potential inhibitors.

An integrative approach using systems biology, mutational analysis with molecular dynamics simulation to challenge the functionality of a target protein

Visceral leishmaniasis affects millions of people worldwide in areas where Leishmania donovani is endemic. The protozoan species serves a greater threat as it has gradually evolved drug resistance whereby requiring newer approaches to treat the infection. State-of-art techniques are mostly directed toward finding better targets extracted from the available proteome data. In light of recent computational advancements, we ascertain and validate one such target, adenylosuccinate lyase (ADSL) by implementation of in-silico methods which led to the identification of critical amino acid residues that affects its functional attributes. Our target selection was based on comprehensive topological analysis of a knowledge-based protein-protein interaction network. Subsequently, mutations were incorporated and the dynamic behavior of mutated and native proteins was traced using MD simulations for a total time span of 600 ns. Comparative analysis of the native and mutated structures exhibited perceptible changes in the ligand-bound catalytic region with respect to time. The unfavorable changes in the orientations of specific catalytic residues, His118 and His196, induced by generated mutations reduce the enzyme specificity. In summary, this integrative approach is able to select a target against pathogen, identify crucial residues, and challenge its functionality through the selected mutations.