Structural and functional characterization of a unique hypothetical protein (WP_003901628.1) of Mycobacterium tuberculosis: a computational approach

Novel Mutations in MPT64 Secretory Protein of Mycobacterium tuberculosis Complex

Tuberculosis (TB) is a global health problem caused by the Mycobacterium tuberculosis complex (MTBC). These bacteria secrete various proteins involved in the pathogenesis and persistence of MTBC. Among the secretory proteins, MPT64 (Rv1980C) is highly conserved and is also known as a major culture filtrate that is used in rapid diagnosis of MTBC. In the current study, we aimed to find the mutation in this highly conserved protein in isolates from the Pashtun-dominant province of Pakistan. We analyzed 470 M. tuberculosis whole-genome sequences of Khyber Pakhtunkhwa Province. Mutations in the MPT64 gene were screened through TB-Profiler and BioEdit software tools. The DynaMut web server was used to analyze the impact of the mutation on protein dynamics and stability. Among 470 MTB genomes, three non-synonymous mutations were detected in nine isolates, and one synonymous mutation (G208A) was found in four isolates. Mutation G211T (F159L), which was detected at the C-terminal domain of the protein in six isolates, was the most prominent. The second novel mutation, T480C (I70V), was detected in two isolates at the C-terminal side of the protein structure. The third novel mutation, A491C (L66R), was detected in a single isolate at the N-terminal side of the MPT64 protein. The effect of these three mutations was destabilizing on the protein structure. The molecular flexibility of the first two mutations increased, and the last one decreased. MPT64 is a highly conserved secretory protein, harboring only a few mutations. This study provides useful information for better managing the diagnosis of MTB isolates in high TB-burden countries.

Subtractive genomics profiling for potential drug targets identification against Moraxella catarrhalis

Moraxella catarrhalis (M. catarrhalis) is a gram-negative bacterium, responsible for major respiratory tract and middle ear infection in infants and adults. The recent emergence of the antibiotic resistance M. catarrhalis demands the prioritization of an effective drug target as a top priority. Fortunately, the failure of new drugs and host toxicity associated with traditional drug development approaches can be avoided by using an in silico subtractive genomics approach. In the current study, the advanced in silico genome subtraction approach was applied to identify potential and pathogen-specific drug targets against M. catarrhalis. We applied a series of subtraction methods from the whole genome of pathogen based on certain steps i.e. paralogous protein that have extensive homology with humans, essential, drug like, non-virulent, and resistant proteins. Only 38 potent drug targets were identified in this study. Eventually, one protein was identified as a potential new drug target and forwarded to the structure-based studies i.e. histidine kinase (UniProt ID: D5VAF6). Furthermore, virtual screening of 2000 compounds from the ZINC database was performed against the histidine kinase that resulted in the shortlisting of three compounds as the potential therapeutic candidates based on their binding energies and the properties exhibited using ADMET analysis. The identified protein gives a platform for the discovery of a lead drug candidate that may inhibit it and may help to eradicate the otitis media caused by drug-resistant M. catarrhalis. Nevertheless, the current study helped in creating a pipeline for drug target identification that may assist wet-lab research in the future.

Challenges in Serologic Diagnostics of Neglected Human Systemic Mycoses: An Overview on Characterization of New Targets

Systemic mycoses have been viewed as neglected diseases and they are responsible for deaths and disabilities around the world. Rapid, low-cost, simple, highly-specific and sensitive diagnostic tests are critical components of patient care, disease control and active surveillance. However, the diagnosis of fungal infections represents a great challenge because of the decline in the expertise needed for identifying fungi, and a reduced number of instruments and assays specific to fungal identification. Unfortunately, time of diagnosis is one of the most important risk factors for mortality rates from many of the systemic mycoses. In addition, phenotypic and biochemical identification methods are often time-consuming, which has created an increasing demand for new methods of fungal identification. In this review, we discuss the current context of the diagnosis of the main systemic mycoses and propose alternative approaches for the identification of new targets for fungal pathogens, which can help in the development of new diagnostic tests.

Comparative Metabolic Pathways Analysis and Subtractive Genomics Profiling to Prioritize Potential Drug Targets Against Streptococcus pneumoniae

Streptococcus pneumoniae is a notorious pathogen that affects ∼450 million people worldwide and causes up to four million deaths per annum. Despite availability of antibiotics (i.e., penicillin, doxycycline, or clarithromycin) and conjugate vaccines (e.g., PCVs), it is still challenging to treat because of its drug resistance ability. The rise of antibiotic resistance in S. pneumoniae is a major source of concern across the world. Computational subtractive genomics is one of the most applied techniques in which the whole proteome of the bacterial pathogen is gradually reduced to a limited number of potential therapeutic targets. Whole-genome sequencing has greatly reduced the time required and provides more opportunities for drug target identification. The goal of this work is to evaluate and analyze metabolic pathways in serotype 14 of S. pneumonia to identify potential drug targets. In the present study, 47 potent drug targets were identified against S. pneumonia by employing the computational subtractive genomics approach. Among these, two proteins are prioritized (i.e., 4-oxalocrotonate tautomerase and Sensor histidine kinase uniquely present in S. pneumonia) as novel drug targets and selected for further structure-based studies. The identified proteins may provide a platform for the discovery of a lead drug candidate that may be capable of inhibiting these proteins and, therefore, could be helpful in minimizing the associated risk related to the drug-resistant S. pneumoniae. Finally, these enzymatic proteins could be of prime interest against S. pneumoniae to design rational targeted therapy.

Potential Drug Targets Identification Against Clostridioides Difficile (CD) and Characterization of Indispensable Proteins by a Subtractive Genomics Approach Followed by Virtual Screening

Background:

Clostridioides difficile (CD) is an enteric multi-drug resistant pathogenic bacterium. CD-associated infections are the leading cause of nosocomial diarrhea that can further lead to pseudomembranous colitis, toxic mega-colon or sepsis with greater mortality and morbidity risks. CD infection possesses higher rates of recurrence due to its greater resistance to antibiotics. Considering its higher rates of recurrence, it has become a major burden on healthcare facilities. Therefore, there is a dire need to identify novel drug targets to combat antibiotic resistance of Clostridioides difficile.

Objective:

To identify and propose new and novel drug targets against the Clostridioides difficile.

Methods:

In the current study, a computational subtractive genomics approach was applied to obtain a set of potential drug targets that exist in the multi-drug resistant strain of Clostridioides difficile. Here, the uncharacterized proteins were studied as potential drug targets. The methodology involved several bioinformatics databases and tools. The druggable proteins sequences were retrieved based on non-homology with host proteome and essentiality for the survival of the pathogen. The uncharacterized proteins were functionally characterized using different computational tools, and sub-cellular localization was also predicted. The metabolic pathways were analyzed using the KEGG database. Eventually, the druggable proteome has been fetched using sequence similarity with the already available drug targets present in the DrugBank database. These druggable proteins were further explored for the structural details to identify drug candidates.

Results :

A priority list of potential drug targets was provided with the help of the applied method on the complete proteome set of the C. difficile. Moreover, the drug-like compounds have been screened against the potential drug targets to prioritize potential drug candidates. To facilitate the need for drug targets and therapies, the study proposed five potential protein drug targets, out of which three proposed drug targets were subjected to homology modeling to explore their structural and functional activities

Conclusion:

In conclusion, we proposed three unique, unexplored drug targets against C. difficile. The structure-based methods were applied and resulted in a list of top-scoring compounds as potential inhibitors to proposed drug targets.

Therapeutic Potential of Novel Mastoparan-Chitosan Nanoconstructs Against Clinical MDR Acinetobacter baumannii: In silico, in vitro and in vivo Studies

PURPOSE

Acinetobacter baumannii antibiotic resistant infections in high-risk patients are a great challenge for researchers and clinicians worldwide. In an effort to achieve potent bactericidal outcomes, a novel chitosan-mastoparan nanoconstruct (Mast-Cs NC) was designed and assessed for its therapeutic potential through in silico, in vitro and in vivo experimentation against clinical multidrug-resistant (MDR) A. baumannii.

METHODS

Optimized 3D structures of mastoparan and chitosan were coupled computationally through an ionic cross-linker to generate a circular ring of chitosan encasing mastoparan. The complex was assessed for interactions and stability through molecular dynamic simulation (MDS). Binding pocket analysis was used to assess the protease-peptide interface. Mast-Cs NC were prepared by the ionic gelation method. Mast-Cs NC were evaluated in vitro and in vivo for their therapeutic efficacy against drug-resistant clinical A. baumannii.

RESULTS

MDS for 100 ns showed stable bonds between chitosan and mastoparan; the first at chitosan oxygen atom-46 and mastoparan isoleucine carbon atom with a distance of 2.77 Å, and the second between oxygen atom-23 and mastoparan lysine nitrogen atom with a distance of 2.80 Å, and binding energies of -3.6 and -7.4 kcal/mol, respectively. Mast-Cs complexes approximately 156 nm in size, with +54.9 mV zeta potential and 22.63% loading capacity, offered >90% encapsulation efficiency and were found to be geometrically incompatible with binding pockets of various proteases. The MIC90 of Mast-Cs NC was significantly lower than that of chitosan (4 vs 512 μg/mL, respectively, p<0.05), with noticeable bacterial damage upon morphological analysis. In a BALB/c mouse sepsis model, a significant reduction in bacterial colony count in the Mast-Cs treated group was observed compared with chitosan and mastoparan alone (p<0.005). Mast-Cs maintained good biocompatibility and cytocompatibility.

CONCLUSION

Novel mastoparan-loaded chitosan nanoconstructs signify a successful strategy for achieving a synergistic bactericidal effect and higher therapeutic efficacy against MDR clinical A. baumannii isolates. The Mast-Cs nano-drug delivery system could work as an alternative promising treatment option against MDR A. baumannii.