Role of TAM Receptors in Antimalarial Humoral Immune Response.

Immune response against malaria and the clearance of Plasmodium parasite relies on germinal-center-derived B cell responses that are temporally and histologically layered. Despite a well-orchestrated germinal center response, anti-Plasmodium immune response seldom offers sterilizing immunity. Recent studies report that certain pathophysiological features of malaria such as extensive hemolysis, hypoxia as well as the extrafollicular accumulation of short-lived plasmablasts may contribute to this suboptimal immune response. In this review, we summarize some of those studies and attempt to connect certain host intrinsic features in response to the malarial disease and the resultant gaps in the immune response.

Molecular Property Diagnostic Suite for COVID-19 (MPDSCOVID-19): an open-source disease-specific drug discovery portal.

Molecular Property Diagnostic Suite (MPDS) was conceived and developed as an open-source disease-specific web portal based on Galaxy. MPDSCOVID-19 was developed for COVID-19 as a one-stop solution for drug discovery research. Galaxy platforms enable the creation of customized workflows connecting various modules in the web server. The architecture of MPDSCOVID-19 effectively employs Galaxy v22.04 features, which are ported on CentOS 7.8 and Python 3.7. MPDSCOVID-19 provides significant updates and the addition of several new tools updated after six years. Tools developed by our group in Perl/Python and open-source tools are collated and integrated into MPDSCOVID-19 using XML scripts. Our MPDS suite aims to facilitate transparent and open innovation. This approach significantly helps bring inclusiveness in the community while promoting free access and participation in software development. Availability & Implementation: The MPDSCOVID-19 portal can be accessed at https://mpds.neist.res.in:8085/.

Analyzing the cation-aromatic interactions in proteins: Cation-aromatic database V2.0.

The cation-aromatic database (CAD) is a comprehensive repository of cation-aromatic motifs found in experimentally determined protein structures, first reported in 2007 [Proteins, 2007, 67, 1179]. The present article is an update of CAD that contains information of approximately 27.26 million cation-aromatic motifs. CAD uses three distance parameters (r, d1, and d2) to determine the position of the cation relative to the centroid of the aromatic residue and classifies the motifs as cation-π or cation-σ interactions. As of June 2023, about 193 936 protein structures were retrieved from Protein Data Bank, and this resulted in the identification of an impressive number of 27 255 817 cation-aromatic motifs. Among these motifs, spherical motifs constituted 94.09%, while cylindrical motifs made up the remaining 5.91%. When considering the interaction of metal ions with aromatic residues, 965 564 motifs are identified. Remarkably, 82.08% of these motifs involved the binding of metal ions to the amino acid HIS. Moreover, the analysis of binding preferences between cations and aromatic residues revealed that the HIS-HIS, PHE-ARG, and TRP-ARG pairs exhibited a preferential geometry. The motif pair HIS-HIS was the most prevalent, accounting for 19.87% of the total, closely followed by TYR-LYS at 10.17%. Conversely, the motif pair TRP-HIS had the lowest occurrence, representing only 4.20% of the total. The data generated help in revealing the characteristics and biological functions of cation-aromatic interactions in biological molecules. The updated version of CAD (Cation-Aromatic Database V2.0) can be accessed at https://acds.neist.res.in/cadv2.

Molecular Property Diagnostic Suite Compound Library (MPDS-CL): a structure-based classification of the chemical space.

Molecular Property Diagnostic Suite Compound Library (MPDS-CL) is an open-source Galaxy-based cheminformatics web portal which presents a structure-based classification of the molecules. A structure-based classification of nearly 150 million unique compounds, obtained from 42 publicly available databases and curated for redundancy removal through 97 hierarchically well-defined atom composition-based portions, has been done. These are further subjected to 56-bit fingerprint-based classification algorithm which led to the formation of 56 structurally well-defined classes. The classes thus obtained were further divided into clusters based on their molecular weight. Thus, the entire set of molecules was put into 56 different classes and 625 clusters. This led to the assignment of a unique ID, named as MPDS-AadharID, for each of these 149,169,443 molecules. MPDS-AadharID is akin to the unique number given to citizens in India (similar to SSN in the US and NINO in the UK). The unique features of MPDS-CL are (a) several search options, such as exact structure search, substructure search, property-based search, fingerprint-based search, using SMILES, InChIKey and key-in; (b) automatic generation of information for the processing for MPDS and other galaxy tools; (c) providing the class and cluster of a molecule which makes it easier and fast to search for similar molecules and (d) information related to the presence of the molecules in multiple databases. The MPDS-CL can be accessed at https://mpds.neist.res.in:8086/ .

Identification of CCZ1 as an essential lysosomal trafficking regulator in Marburg and Ebola virus infections.

Marburg and Ebola filoviruses are two of the deadliest infectious agents and several outbreaks have occurred in the last decades. Although several receptors and co-receptors have been reported for Ebola virus, key host factors remain to be elucidated. In this study, using a haploid cell screening platform, we identify the guanine nucleotide exchange factor CCZ1 as a key host factor in the early stage of filovirus replication. The critical role of CCZ1 for filovirus infections is validated in 3D primary human hepatocyte cultures and human blood-vessel organoids, both critical target sites for Ebola and Marburg virus tropism. Mechanistically, CCZ1 controls early to late endosomal trafficking of these viruses. In addition, we report that CCZ1 has a role in the endosomal trafficking of endocytosis-dependent SARS-CoV-2 infections, but not in infections by Lassa virus, which enters endo-lysosomal trafficking at the late endosome stage. Thus, we have identified an essential host pathway for filovirus infections in cell lines and engineered human target tissues. Inhibition of CCZ1 nearly completely abolishes Marburg and Ebola infections. Thus, targeting CCZ1 could potentially serve as a promising drug target for controlling infections caused by various viruses, such as SARS-CoV-2, Marburg, and Ebola.

Detection of lytic phage infecting flavour-producing strain of Lacticaseibacillus paracasei in the dairy effluents of Kerala.

The performance of the starter culture is a critical factor that decides the quality of fermented milk. Dahi is a fermented milk product popular in India made using a mixed starter culture of lactic acid bacteria comprising acid and flavour producers. The prevalence of bacteriophages in the dairy environment can critically affect the activity of these starter cultures resulting in starter failure. As there is little information available on the occurrence of bacteriophages in the dairy environment of Kerala, this research communication examines the presence of lytic bacteriophages acting against three potential flavour-producing strains of Lacticaseibacillus paracasei (Lc. paracasei). Dairy effluent samples were screened for the presence of phages against the strains of Lc. paracasei by the multiple host enrichment method. Plates showing clearance zone in spot assay were confirmed for the presence of phages by double-layer agar assay. The plaques obtained in the double-layer agar assay were purified for further identification by next-generation sequencing. A bacteriophage infecting one of the three strains of Lc. paracasei was detected by the plaque assay and the blast annotation of the bacteriophage sequence found 86.05% similarity of the phage to Siphoviridae family. The study endorses the need for monitoring phages in the dairy environment to control phage-related starter failure in the state of Kerala.

Assessing machine learning approaches for predicting failures of investigational drug candidates during clinical trials.

One of the major challenges in drug development is having acceptable levels of efficacy and safety throughout all the phases of clinical trials followed by the successful launch in the market. While there are many factors such as molecular properties, toxicity parameters, mechanism of action at the target site, etc. that regulates the therapeutic action of a compound, a holistic approach directed towards data-driven studies will invariably strengthen the predictive toxicological sciences. Our quest for the current study is to find out various reasons as to why an investigational candidate would fail in the clinical trials after multiple iterations of refinement and optimization. We have compiled a dataset that comprises of approved and withdrawn drugs as well as toxic compounds and essentially have used time-split based approach to generate the training and validation set. Five highly robust and scalable machine learning binary classifiers were used to develop the predictive models that were trained with features like molecular descriptors and fingerprints and then validated rigorously to achieve acceptable performance in terms of a set of performance metrics. The mean AUC scores for all the five classifiers with the hold-out test set were obtained in the range of 0.66-0.71. The models were further used to predict the probability score for the clinical candidate dataset. The top compounds predicted to be toxic were analyzed to estimate different dimensions of toxicity. Apparently, through this study, we propose that with the appropriate use of feature extraction and machine learning methods, one can estimate the likelihood of success or failure of investigational drugs candidates thereby opening an avenue for future trends in computational toxicological studies. The models developed in the study can be accessed at https://github.com/gnsastry/predicting_clinical_trials.git.

Phylogenetic analysis of Babesia gibsoni isolates of south India using apical membrane antigen, 50 kDa surface antigen, and 70 kDa heat shock protein genes.

The prevalence of canine babesiosis due to Babesia gibsoni has increased throughout the world including in southern India. The polymerase chain reaction (PCR) based molecular characterization of B. gibsoni in dogs of Kerala, south India, targeting three specific genes viz., apical membrane antigen (AMA1), 50 kDa surface antigen (P50), and heat shock protein (HSP70) was undertaken in this study. Out of 297 blood samples collected from clinically suspected animals, microscopy detected piroplasms of B. gibsoni in 60 (20.20 per cent), while the PCR targeting the BgP50 gene detected 85 (28.61 per cent). Polymerase chain reaction targeting the BgAMA1 and BgHSP70 detected a lesser number of samples (60 and 65 respectively) as positive. The phylogenetic analysis of BgHSP70 gene sequences did not reveal genetic heterogeneity among the B. gibsoni isolates of South India and from other countries, while the BgP50 gene differentiated the Indian isolates from Japanese isolates. When BgAMA1 was used for phylogenetic analysis, genetic variation was not observed among Indian and Taiwanese isolates, however, differentiated them from the Japanese isolates.

Towards systematic exploration of chemical space: building the fragment library module in molecular property diagnostic suite.

A fragment-based drug discovery (FBDD) approach has traditionally been of utmost significance in drug design studies. It allows the exploration of large chemical space to find novel scaffolds and chemotypes which can be improved into selective inhibitors with good affinity. In the current work, several public domain chemical libraries (ChEMBL, DrugCentral, PDB ligands, COCONUT, and SAVI) comprising bioactive and virtual molecules were retrieved to develop a fragment library. A systematic fragmentation method that breaks a given molecule into rings, linkers, and substituents was used to cleave the molecules and the fragments were analyzed. Further, only the ring framework was taken into the consideration to develop a fragment library that consists of a total number of 107,614 unique fragments. This set represents a rich diverse structure framework that covers a wide variety of yet-to-be-explored fragments for a wide range of small molecule-based applications. This fragment library is an integral part of the molecular property diagnostic suite (MPDS) suite that can be used with other modeling and informatics methods for FBDD approaches. The fragment library module of MPDS can be accessed at http://mpds.neist.res.in:8085 .

Green Synthesized Silver Nanoparticles Using Lactobacillus Acidophilus as an Antioxidant, Antimicrobial, and Antibiofilm Agent Against Multi-drug Resistant Enteroaggregative Escherichia Coli.

The present study was envisaged to employ the green synthesis and characterization of silver nanoparticles (AgNPs) using the potential probiotic strain Lactobacillus acidophilus, to assess its antibacterial as well as antibiofilm activity against multi-drug-resistant enteroaggregative Escherichia coli (MDR-EAEC) strains and to investigate their antioxidant activity. In this study, AgNPs were successfully synthesized through an eco-friendly protocol, which was then confirmed by its X-ray diffraction (XRD) pattern. A weight loss of 15% up to 182 °C with a narrow exothermic peak between 170 °C and 205 °C was observed in thermogravimetric analysis-differential thermal analysis (TGA-DTA), while aggregated nanoclusters were observed in scanning electron microscopy (SEM). Moreover, the transmission electron microscopy (TEM) imaging of AgNPs revealed a spherical morphology and crystalline nature with an optimum size ranging from 10 to 20 nm. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) values of green synthesized AgNPs against the MDR-EAEC strains were found to be 7.80 mg/L and 15.60 mg/L, respectively. In vitro time-kill kinetic assay revealed a complete elimination of the MDR-EAEC strains after 180 min on co-incubation with the AgNPs. Moreover, the green synthesized AgNPs were found safe by in vitro haemolytic assay. Besides, the green synthesized AgNPs exhibited significant biofilm inhibition (P < 0.001) formed by MDR-EAEC strains. Additionally, a concentration-dependent antioxidant activity was observed in 2,2'-azinobis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) and 2,2-diphenyl-1-picrylhydrazyl (DPPH) assays. Hence, this study demonstrated potential antibacterial as well as antibiofilm activity of green synthesized AgNPs against MDR-EAEC strains with antioxidant properties and warrants further in-depth studies to explore it as an effective antimicrobial agent against MDR infections.