Background:
To carry out wide range of cellular functionalities, proteins often associate with
one or more proteins in a phenomenon known as Protein-Protein Interaction (PPI). Experimental and
computational approaches were applied on PPIs in order to determine the interacting partners, and also
to understand how an abnormality in such interactions can become the principle cause of a disease.
Objective:
This review aims to elucidate the case studies where PPIs involved in various human diseases
have been proven or validated with computational techniques, and also to elucidate how small molecule
inhibitors of PPIs have been designed computationally to act as effective therapeutic measures against
certain diseases.
Results:
Computational techniques to predict PPIs are emerging rapidly in the modern day. They not
only help in predicting new PPIs, but also generate outputs that substantiate the experimentally determined
results. Moreover, computation has aided in the designing of novel inhibitor molecules disrupting
the PPIs. Some of them are already being tested in the clinical trials.
Conclusion:
This review delineated the classification of computational tools that are essential to investigate
PPIs. Furthermore, the review shed light on how indispensable computational tools have become
in the field of medicine to analyze the interaction networks and to design novel inhibitors efficiently
against dreadful diseases in a shorter time span.
The therapeutic use of bacteriophage-encoded endolysins as enzybiotics has increased significantly in recent years due to the emergence of antibiotic resistant bacteria. Phage endolysins lyse the bacteria by targeting their cell wall. Various engineering strategies are commonly used to modulate or enhance the utility of therapeutic enzymes. This study employed a structure-guided mutagenesis approach to engineer a T7 bacteriophage endolysin (T7L) with enhanced amidase activity and lysis potency via replacement of a noncatalytic gating residue (His 37). Two H37 variants (H37A and H37K) were designed and characterized comprehensively using integrated biophysical and biochemical techniques to provide mechanistic insights into their structure−stability−dynamics−activity paradigms. Among the studied proteins, cell lysis data suggested that the obtained H37A variant exhibits amidase activity (∼35%) enhanced compared to that of wild-type T7 endolysin (T7L-WT). In contrast to this, the H37K variant is highly unstable, prone to aggregation, and less active. Comparison of the structure and dynamics of the H37A variant to those of T7L-WT evidenced that the alteration at the site of H37 resulted in long-range structural perturbations, attenuated the conformational heterogeneity, and quenched the microsecond to millisecond time scale motions. Stability analysis confirmed the altered stability of H37A compared to that of its WT counterpart. All of the obtained results established that the H37A variant enhances the lysis activity by regulating the stability−activity trade-off. This study provided deeper atomic level insights into the structure−function relationships of endolysin proteins, thus aiding researchers in the rational design of engineered endolysins with enhanced therapeutic properties.
Incidence of vulvovaginal candidiasis are strikingly high and treatment options are limited with nearly 50% Candida glabrata cases left untreated or experience treatment failures. The vaginal microenvironment is rich in lactic acid, and the adaptation of C. glabrata to lactic acid (LA) is the main reason for clinical treatment failure. In the present study, C. glabrata and its vaginal clinical isolates were comprehensively investigated for their growth response, metabolic adaptation and altered cellular pathway to LA using different biochemical techniques, metabolic profiling and transcriptional studies. C. glabrata shown considerable variations in its topological and biochemical features without compromising growth in LA media. Chemical profiling data highlighted involvement of cell wall/membrane, ergosterol and oxidative stress related pathways in mediating adaptative response of C. glabrata towards LA. Further, one dimensional proton (1H) NMR spectroscopy based metabolic profiling revealed significant modulation in 19 metabolites of C. glabrata cells upon growth in LA. Interestingly myo-inositol, xylose, putrescine and betaine which are key metabolites for cell growth and viability were found to be differentially expressed by clinical isolates. These observations were supported by the transcriptional expression study of selected genes evidencing cell wall/membrane re-organisation, altered oxidative stress, and reprogramming of carbon metabolic pathways. Collectively, the study advances our understanding on adaptative response of C. glabrata in vaginal microenvironment to lactic acid for survival and virulence.
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