scholarly journals Application of the Subtractive Genomics and Molecular Docking Analysis for the Identification of Novel Putative Drug Targets against Salmonella enterica subsp. enterica serovar Poona

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Tanvir Hossain ◽  
Mohammad Kamruzzaman ◽  
Talita Zahin Choudhury ◽  
Hamida Nooreen Mahmood ◽  
A. H. M. Nurun Nabi ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Salmonella Enterica ◽  
Drug Targets ◽  
Subcellular Location ◽  
Essential Genes ◽  
Scoring Functions ◽  
Essential Proteins ◽  
Cellular Processes ◽  
Subtractive Genomics ◽  
Resistance Patterns

The emergence of novel pathogenic strains with increased antibacterial resistance patterns poses a significant threat to the management of infectious diseases. In this study, we aimed at utilizing the subtractive genomic approach to identify novel drug targets against Salmonella enterica subsp. enterica serovar Poona strain ATCC BAA-1673. We employed in silico bioinformatics tools to subtract the strain-specific paralogous and host-specific homologous sequences from the bacterial proteome. The sorted proteome was further refined to identify the essential genes in the pathogenic bacterium using the database of essential genes (DEG). We carried out metabolic pathway and subcellular location analysis of the essential proteins of the pathogen to elucidate the involvement of these proteins in important cellular processes. We found 52 unique essential proteins in the target proteome that could be utilized as novel targets to design newer drugs. Further, we investigated these proteins in the DrugBank databases and 11 of the unique essential proteins showed druggability according to the FDA approved drug bank databases with diverse broad-spectrum property. Molecular docking analyses of the novel druggable targets with the drugs were carried out by AutoDock Vina option based on scoring functions. The results showed promising candidates for novel drugs against Salmonella infections.

Proteome Mining for the Identification of Putative Drug Targets For Human Pathogen Clostridium Tetani

2019 ◽  
Vol 14 (6) ◽  
pp. 532-540 ◽  
Author(s):  
Anum Munir ◽  
Shaukat Iqbal Malik ◽  
Khalid Akhtar Malik
Keyword(s):  
Drug Targets ◽  
Cellular Localization ◽  
Pathogenic Bacteria ◽  
Homo Sapiens ◽  
Proteome Analysis ◽  
Essential Genes ◽  
Homologous Proteins ◽  
Clostridium Tetani ◽  
Essential Proteins ◽  
Localization Analysis

Background: Clostridium tetani are rod-like, anaerobic types of pathogenic bacteria of the genus Clostridium. It is Gram-positive in nature and appears as a tennis racket or drumsticks on staining with the dye. Tetanus is a neuromuscular disease wherein the Clostridium tetani exotoxin produces muscle fits in the host. Tetanus is the second leading cause of worldwide deaths occurring from the family of immunization-preventable diseases. Methods: In this research, subtractive proteome analysis of C. tetani was performed to identify putative drug targets. The proteins were subjected to blast analysis against Homo sapiens to exclude homologous proteins. The database of Essential Genes was used to determine the essential proteins of the pathogen. These basic proteins were additionally analyzed to anticipate the corresponding metabolic pathways. Results: Cellular localization analysis was carried out to determine the possibility of the protein presence in the outer membrane. The study has recognized 29 essential genes and 20 unique pathways of 2314 proteins as potential drug targets. There are 29 essential proteins, out of which, 3 membrane proteins were also identified as putative drug targets. Conclusion: Virtual screening in contrast to these proteins can be valuable in the identification of novel clinical compounds for the C. tetani infections in Homo sapiens.

scholarly journals In Silico Identification of New Targets for Diagnosis, Vaccine, and Drug Candidates against Trypanosoma cruzi

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Rafael Obata Trevisan ◽  
Malú Mateus Santos ◽  
Chamberttan Souza Desidério ◽  
Leandro Gomes Alves ◽  
Thiago de Jesus Sousa ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Trypanosoma Cruzi ◽  
Chagas Disease ◽  
Drug Targets ◽  
Hot Spot ◽  
Mhc I ◽  
Drug Candidates ◽  
Subtractive Genomics

Chagas disease is a neglected tropical disease caused by the parasite Trypanosoma cruzi. Despite the efforts and distinct methodologies, the search of antigens for diagnosis, vaccine, and drug targets for the disease is still needed. The present study is aimed at identifying possible antigens that could be used for diagnosis, vaccine, and drugs targets against T. cruzi using reverse vaccinology and molecular docking. The genomes of 28 T. cruzi strains available in GenBank (NCBI) were used to obtain the genomic core. Then, subtractive genomics was carried out to identify nonhomologous genes to the host in the core. A total of 2630 conserved proteins in 28 strains of T. cruzi were predicted using OrthoFinder and Diamond software, in which 515 showed no homology to the human host. These proteins were evaluated for their subcellular localization, from which 214 are cytoplasmic and 117 are secreted or present in the plasma membrane. To identify the antigens for diagnosis and vaccine targets, we used the VaxiJen software, and 14 nonhomologous proteins were selected showing high binding efficiency with MHC I and MHC II with potential for in vitro and in vivo tests. When these 14 nonhomologous molecules were compared against other trypanosomatids, it was found that the retrotransposon hot spot (RHS) protein is specific only for T. cruzi parasite suggesting that it could be used for Chagas diagnosis. Such 14 proteins were analyzed using the IEDB software to predict their epitopes in both B and T lymphocytes. Furthermore, molecular docking analysis was performed using the software MHOLline. As a result, we identified 6 possible T. cruzi drug targets that could interact with 4 compounds already known as antiparasitic activities. These 14 protein targets, along with 6 potential drug candidates, can be further validated in future studies, in vivo, regarding Chagas disease.

In-silico Subtractive Proteomic Analysis Approach for Therapeutic Targets in MDR Salmonella enterica subsp. enterica serovar Typhi str. CT18

2019 ◽  
Vol 19 (29) ◽  
pp. 2708-2717 ◽  
Author(s):  
Noor Rahman ◽  
Ijaz Muhammad ◽  
Gul E. Nayab ◽  
Haroon Khan ◽  
Rosanna Filosa ◽  
...  
Keyword(s):  
Proteomic Analysis ◽  
Metabolic Pathways ◽  
Salmonella Enterica ◽  
Drug Targets ◽  
Protein Sequences ◽  
Analysis Approach ◽  
Essential Proteins ◽  
Pathways Analysis

Objective: In the present study, an attempt has been made for subtractive proteomic analysis approach for novel drug targets in Salmonella enterica subsp. enterica serover Typhi str.CT18 using computational tools. Method: Paralogous, redundant and less than 100 amino acid protein sequences were removed by using CD-HIT. Further detection of bacterial proteins which are non-homologous to host and are essential for the survival of pathogens by using BLASTp against host proteome and DEG`s, respectively. Comparative Metabolic pathways analysis was performed to find unique and common metabolic pathways. The non-redundant, non-homologous and essential proteins were BLAST against approved drug targets for drug targets while Psortb and CELLO were used to predict subcellular localization. Result: There were 4473 protein sequences present in NCBI Database for Salmonella enterica subsp. enterica serover Typhi str. CT18 out of these 327 were essential proteins which were non-homologous to human. Among these essential proteins, 124 proteins were involved in 19 unique metabolic pathways. These proteins were further BLAST against approved drug targets in which 7 cytoplasmic proteins showed druggability and can be used as a therapeutic target. Conclusion: Drug targets identification is the prime step towards drug discovery. We identified 7 cytoplasmic druggable proteins which are essential for the pathogen survival and non-homologous to human proteome. Further in vitro and in vivo validation is needed for the evaluation of these targets to combat against salmonellosis.

Subtractive Proteome Mining Approach Towards Unique Putative Drug Targets Identification for Salmonella Typhimurium

2019 ◽  
Vol 19 ◽  
Author(s):  
Rabia Iftikhar ◽  
Muhammad Rizwan ◽  
Sajid Khan ◽  
Azhar Mehmood ◽  
Anum Munir
Keyword(s):  
Salmonella Typhimurium ◽  
Drug Targets ◽  
Homo Sapiens ◽  
Essential Genes ◽  
Intestinal Lumen ◽  
Homologous Proteins ◽  
Essential Proteins ◽  
Contaminated Food ◽  
Potential Drug Targets ◽  
Infants And Young Children

: Salmonella typhimurium is rod-shaped bacteria with a Gram-negative genus, belonging to the Enterobacteriaceae family of microbes, invades the intestinal lumen of Human. Salmonella typhimurium is a root source, accounting for gastroenteritis in humans as well as in other mammals. Gastroenteritisis associated with Salmonella Typhimurium by interacting with the contaminated food and water, spread to nearby people in the area. Small intestines are attacked by Salmonella and then enter into the bloodstream momentarily, and are responsible for millions of mortalities and morbidities around the globe. Salmonella typhimurium toxins cause gastrointestiritis due to inflammation in the stomach and intestine in infants and young children. It accounts for millions of deaths with a higher incidence rate in developing countries. Methods: : In the current research, subtractive proteome mining has been done to recognize putative drug targets. The proteome was analyzed through blast in order to exclude homologous proteins. Bacterial essential proteins were predicted and the participation of the essential genes in the metabolic pathways has been analyzed. Results: : 36 essential genes and 15 unique pathways have been identified as potential drug targets among the total of 1934 proteins. The location of proteins is determined as an outer membrane. 3 proteins out of 36 essential proteins are recognized as putative drug targets. Conclusion:: In the future, virtual screening for the evaluation of novel clinical compounds for the identified proteins is effective and valuable for Salmonella Typhimurium infection in Homo sapiens.

CRDS: Consensus Reverse Docking System for target fishing

2019 ◽  
Author(s):  
Aeri Lee ◽  
Dongsup Kim
Keyword(s):  
Molecular Docking ◽  
Drug Targets ◽  
Large Scale ◽  
Protein Structures ◽  
Web Server ◽  
Target Prediction ◽  
Supplementary Information ◽  
Scoring Functions ◽  
Interaction Sites ◽  
The Web

Abstract Motivation Identification of putative drug targets is a critical step for explaining the mechanism of drug action against multiple targets, finding new therapeutic indications for existing drugs and unveiling the adverse drug reactions. One important approach is to use the molecular docking. However, its widespread utilization has been hindered by the lack of easy-to-use public servers. Therefore, it is vital to develop a streamlined computational tool for target prediction by molecular docking on a large scale. Results We present a fully automated web tool named Consensus Reverse Docking System (CRDS), which predicts potential interaction sites for a given drug. To improve hit rates, we developed a strategy of consensus scoring. CRDS carries out reverse docking against 5254 candidate protein structures using three different scoring functions (GoldScore, Vina and LeDock from GOLD version 5.7.1, AutoDock Vina version 1.1.2 and LeDock version 1.0, respectively), and those scores are combined into a single score named Consensus Docking Score (CDS). The web server provides the list of top 50 predicted interaction sites, docking conformations, 10 most significant pathways and the distribution of consensus scores. Availability and implementation The web server is available at http://pbil.kaist.ac.kr/CRDS. Supplementary information Supplementary data are available at Bioinformatics online.

Machine Learning-Based Scoring Functions. Development and Applications with SAnDReS.

2020 ◽  
Vol 27 ◽  
Author(s):  
Gabriela Bitencourt-Ferreira ◽  
Camila Rizzotto ◽  
Walter Filgueira de Azevedo Junior
Keyword(s):  
Machine Learning ◽  
Binding Affinity ◽  
Drug Targets ◽  
Computational Models ◽  
Factor Xa ◽  
Coagulation Factor ◽  
Predictive Performance ◽  
Machine Learning Techniques ◽  
Scoring Functions ◽  
Molegro Virtual Docker

Background: Analysis of atomic coordinates of protein-ligand complexes can provide three-dimensional data to generate computational models to evaluate binding affinity and thermodynamic state functions. Application of machine learning techniques can create models to assess protein-ligand potential energy and binding affinity. These methods show superior predictive performance when compared with classical scoring functions available in docking programs. Objective: Our purpose here is to review the development and application of the program SAnDReS. We describe the creation of machine learning models to assess the binding affinity of protein-ligand complexes. Method: SAnDReS implements machine learning methods available in the scikit-learn library. This program is available for download at https://github.com/azevedolab/sandres. SAnDReS uses crystallographic structures, binding, and thermodynamic data to create targeted scoring functions. Results: Recent applications of the program SAnDReS to drug targets such as Coagulation factor Xa, cyclin-dependent kinases, and HIV-1 protease were able to create targeted scoring functions to predict inhibition of these proteins. These targeted models outperform classical scoring functions. Conclusion: Here, we reviewed the development of machine learning scoring functions to predict binding affinity through the application of the program SAnDReS. Our studies show the superior predictive performance of the SAnDReS-developed models when compared with classical scoring functions available in the programs such as AutoDock4, Molegro Virtual Docker, and AutoDock Vina.

A Survey on Computational Methods for Essential Proteins and Genes Prediction

2019 ◽  
Vol 14 (3) ◽  
pp. 211-225 ◽  
Author(s):  
Ming Fang ◽  
Xiujuan Lei ◽  
Ling Guo
Keyword(s):  
Computational Methods ◽  
Drug Targets ◽  
Disease Genes ◽  
Essential Proteins ◽  
Experimental Identification ◽  
Cellular Life ◽  
Different Types ◽  
The Stability ◽  
Human Disease Genes ◽  
Biology Research

Background: Essential proteins play important roles in the survival or reproduction of an organism and support the stability of the system. Essential proteins are the minimum set of proteins absolutely required to maintain a living cell. The identification of essential proteins is a very important topic not only for a better comprehension of the minimal requirements for cellular life, but also for a more efficient discovery of the human disease genes and drug targets. Traditionally, as the experimental identification of essential proteins is complex, it usually requires great time and expense. With the cumulation of high-throughput experimental data, many computational methods that make useful complements to experimental methods have been proposed to identify essential proteins. In addition, the ability to rapidly and precisely identify essential proteins is of great significance for discovering disease genes and drug design, and has great potential for applications in basic and synthetic biology research. Objective: The aim of this paper is to provide a review on the identification of essential proteins and genes focusing on the current developments of different types of computational methods, point out some progress and limitations of existing methods, and the challenges and directions for further research are discussed.

scholarly journals Intrinsically Disordered Proteins as Regulators of Transient Biological Processes and as Untapped Drug Targets

Molecules ◽  
2021 ◽  
Vol 26 (8) ◽  
pp. 2118
Author(s):  
Yusuke Hosoya ◽  
Junko Ohkanda
Keyword(s):  
Drug Targets ◽  
Intrinsically Disordered Proteins ◽  
Dynamic Control ◽  
Disordered Proteins ◽  
Biological Processes ◽  
Phase Separations ◽  
Cellular Processes ◽  
Intrinsically Disordered ◽  
New Drug ◽  
Liquid Phase Separations

Intrinsically disordered proteins (IDPs) are critical players in the dynamic control of diverse cellular processes, and provide potential new drug targets because their dysregulation is closely related to many diseases. This review focuses on several medicinal studies that have identified low-molecular-weight inhibitors of IDPs. In addition, clinically relevant liquid–liquid phase separations—which critically involve both intermolecular interactions between IDPs and their posttranslational modification—are analyzed to understand the potential of IDPs as new drug targets.

scholarly journals Virulence and Antimicrobial Resistance Profiles of Salmonella enterica Serovars Isolated from Chicken at Wet Markets in Dhaka, Bangladesh

2021 ◽  
Vol 9 (5) ◽  
pp. 952
Author(s):  
Nure Alam Siddiky ◽  
Md Samun Sarker ◽  
Md. Shahidur Rahman Khan ◽  
Ruhena Begum ◽  
Md. Ehsanul Kabir ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Salmonella Enterica ◽  
Virulence Genes ◽  
Health Concern ◽  
Production Cycle ◽  
Salmonella Spp ◽  
Native Chicken ◽  
Resistance Patterns ◽  
Research Findings ◽  
Native Chickens

Virulent and multi drug resistant (MDR) Salmonellaenterica is a foremost cause of foodborne diseases and had serious public health concern globally. The present study was undertaken to identify the pathogenicity and antimicrobial resistance (AMR) profiles of Salmonellaenterica serovars recovered from chicken at wet markets in Dhaka, Bangladesh. A total of 870 cecal contents of broiler, sonali, and native chickens were collected from 29 wet markets. The overall prevalence of S. Typhimurium, S. Enteritidis, and untyped Salmonella spp., were found to be 3.67%, 0.57%, and 1.95% respectively. All isolates were screened by polymerase chain reaction (PCR) for eight virulence genes, namely invA, agfA, IpfA, hilA, sivH, sefA, sopE, and spvC. S. Enteritidis isolates carried all virulence genes whilst S. Typhimurium isolates carried six virulence genes except sefA and spvC. A diverse phenotypic and genotypic AMR pattern was found. Harmonic descending trends of resistance patterns were observed among the broiler, sonali, and native chickens. Interestingly, virulent and MDR Salmonella enterica serovars were found in native chicken, although antimicrobials were not used in their production cycle. The research findings anticipate that virulent and MDR Salmonella enterica are roaming in the wet markets which can easily anchor to the vendor, consumers, and in the food chain.

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