Integration of network pharmacology, molecular docking, and simulations to evaluate phytochemicals from Drymaria cordata against cervical cancer.

Introduction: Cervical cancer is prevalent among women worldwide. It is a type of cancer that occurs in the cells of the cervix, the lower part of the uterus. Mostly, it is observed in developing nations due to limited access to screening tools. Natural products with anticancer properties and fewer side effects have gained attention. Therefore, this study evaluates the potential of Drymaria cordata as a natural source for treating cervical cancer. Methodology: Phytocompounds present in Drymaria cordata were screened for their molecular properties and drug-likeness. The selected compounds were studied using systems biology tools such as network pharmacology, molecular docking, and molecular dynamics simulations, including MMGBSA studies. Results: Through network pharmacology, molecular docking, and molecular dynamics simulations, quercetin 3-O-ß-d-glucopyranosyl-(1→2)-rhamnopyranoside was identified as a hit compound targeting HRAS and VEGFA proteins. These proteins were found to be responsible for the maximum number of pathway modulations in cervical cancer. Conclusion: Drymaria cordata exhibits potential for treating cervical cancer due to the presence of quercetin 3-O-ß-d-glucopyranosyl-(1→2)-rhamnopyranoside. Further validation of these findings through in vitro and in vivo studies is required.

Gex2SGen: Designing Drug-like Molecules from Desired Gene Expression Signatures.

Drug-induced gene expression profiling provides a lot of useful information covering various aspects of drug discovery and development. Most importantly, this knowledge can be used to discover drugs' mechanisms of action. Recently, deep learning-based drug design methods are in the spotlight due to their ability to explore huge chemical space and design property-optimized target-specific drug molecules. Recent advances in accessibility of open-source drug-induced transcriptomic data along with the ability of deep learning algorithms to understand hidden patterns have opened opportunities for designing drug molecules based on desired gene expression signatures. In this study, we propose a deep learning model, Gex2SGen (Gene Expression 2 SMILES Generation), to generate novel drug-like molecules based on desired gene expression profiles. The model accepts desired gene expression profiles in a cell-specific manner as input and designs drug-like molecules which can elicit the required transcriptomic profile. The model was first tested against individual gene-knocked-out transcriptomic profiles, where the newly designed molecules showed high similarity with known inhibitors of the knocked-out target genes. The model was next applied on a triple negative breast cancer signature profile, where it could generate novel molecules, highly similar to known anti-breast cancer drugs. Overall, this work provides a generalized method, where the method first learned the molecular signature of a given cell due to a specific condition, and designs new small molecules with drug-like properties.

Neuropharmacological Alterations by a Rice Contaminant Stenotrophomonas maltophilia: a Detailed Bio-molecular and Mechanistic Landscape.

Contaminated rice is a major source of food poisoning in human communities where our earlier study showed Stenotrophomonas maltophilia, a Gram-negative bacillus, has been a major contaminant of the stored rice. In the present study, mono- and di-unsaturated fatty acids (UFAs) such as 18:1 ω 7 c, 16:1 ω 6 c, 16:1 ω 7 c, and 18:2 ω 6,9 c long-chain fatty acids have been found as the chief constituents of S. maltophilia boiled cell lysate. Throughout the study, both acute and chronic exposure of the cell lysate showed a decrease in the locomotor activity and a time-dependent increase of the depression (p < 0.001-0.0001, two-way ANOVA), supported by bioamine (dopamine, noradrenaline, adrenaline, serotonin, and GABA) depletion in rodents' brain possibly due to UFA-amino acid decarboxylase interaction favoring bioamine depletion as revealed by our study. Furthermore, the UFA-rich cell lysate revealed dose-dependent inhibition of murine brain microglial cell viability in vitro with concomitant increase of reactive oxygen species (ROS) inside the cell. Destruction of neuroprotective and neurotrophin releasing microglial cells, augmentation of brain ROS, and inflaming brain tissue resulting in infiltration of polymorphonuclear leucocytes also suggest to cause neurotoxicity by UFA derived from Stenotrophomonas maltophilia.

Network-Based Analysis of Fatal Comorbidities of COVID-19 and Potential Therapeutics.

COVID-19 is a highly contagious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The case-fatality rate is significantly higher in older patients and those with diabetes, cancer or cardiovascular disorders. The human proteins, angiotensin-converting enzyme 2 (ACE2), transmembrane protease serine 2 (TMPRSS2) and basigin (BSG), are involved in high-confidence host-pathogen interactions with SARS-CoV-2 proteins. We considered these three proteins as seed nodes and applied the random walk with restart method on the human interactome to construct a protein-protein interaction sub-network, which captures the effects of viral invasion. We found that 'Insulin resistance', 'AGE-RAGE signaling in diabetic complications' and 'adipocytokine signaling' were the common pathways associated with diabetes, cancer and cardiovascular disorders. The association of these critical pathways with aging and its related diseases explains the molecular basis of COVID-19 fatality. We further identified drugs that have effects on these proteins/pathways based on gene expression studies. We particularly focused on drugs that significantly downregulate ACE2 along with other critical proteins identified by the network-based approach. Among them, COL-3 had earlier shown activity against acute lung injury and acute respiratory distress, while entinostat and mocetinostat have been investigated for non-small-cell lung cancer. We propose that these drugs can be repurposed for COVID-19.

Protocol to ensure continued pediatric liver transplantation service during the COVID pandemic and the encouraging outcomes.

Coronavirus disease 2019 is a global pandemic, and to deal with the unexpected, enormous burden on healthcare system, liver transplantation (LT) services have been suspended in many centers. Development of robust and successful protocols in preventing the disease among the recipients, donors and healthcare workers would help in re-starting the LT programs. We adapted a protocol at our center, which is predominantly a living donor liver transplant center based in north India, and continued the service as the pandemic unfolded and peaked in India with good results and shared the experience of the same. Between March 24 and June 7, 2020, during the government-enforced public curfew-"lockdown"-7 children received LT. The protocols of infection control were drafted in our team by local customization of published guidelines. The number of pediatric LT done during the lockdown period in 2020 was similar to that done in corresponding pre-COVID period in 2019. The outcomes were of 100% survival, and none of recipients developed COVID. One potential donor was asymptomatic positive for COVID, responded well to conservative treatment, and was later accepted as a donor. LT program during the COVID pandemic can successfully function after putting in place standard protocols for infection control. These can be implemented with minimal extra involvement of healthcare infrastructure, hence without diversion of resources from COVID management. In conclusion, pediatric liver transplantation services can be continued amid COVID-19 pandemic after establishing a properly observed protocol with minimum additional resources.

Outcome of Pediatric Liver Transplants in Patients With Less Than 10 kg of Body Weight Is Not Worse.

OBJECTIVES: Liver transplant in pediatric patients with body weight < 10 kg poses a challenge to the entire liver transplant team. Many reports have considered 10 kg to be a cutoff pointfor body weightforfavorable posttransplant outcomes. With evolving surgical techniques and postoperative management, there is potential to improve outcomes in this subset of recipients. We compared the outcomes in pediatric patients with body weight < 10 kg with those > 10 kg; also, we studied the factors of influence. MATERIALS AND METHODS: We performed a retrospective analysis to evaluate the outcomes of liver transplants in pediatric patients with < 10 kg body weight. The cohort consisted of 90 children subdivided into the following 2 subgroups: group A (n = 35) with > 10 kg body weight at liver transplant and group B (n = 55) with < 10 kg body weight at liver transplant. We compared the following pretransplant characteristics between the groups: graft weight, graft-to-recipient weightratio, cold ischemia time, warm ischemia times, and liver transplant outcomes. RESULTS: Pediatric End-stage Liver Disease score was significantly higher in group B (score of 24) versus group A (score of 18). Group B had significantly higher graft-to-recipient weight ratio (2.8 in group B vs 1.7 in group A). Graft function showed no significant difference between the 2 groups. Portal vein thrombosis was seen only in group B, whereas biliary leaks were observed among 5 patients in group B and 1 patientin group A. Patient survivalrate was higherin group B (86%) than in group A (77%). CONCLUSIONS: Pediatric patients weighing < 10 kg have similarif not better survivalrates after liver transplant compared with patients > 10 kg. Advancements in surgical techniques and a careful monitoring for complications and timely intervention are important to facilitate these outcomes.

Network analysis of hydroxymethylbilane synthase dynamics.

Hydroxymethylbilane synthase (HMBS) is one of the key enzymes of the heme biosynthetic pathway that catalyzes porphobilinogen to form the linear tetrapyrrole 1-hydroxymethylbilane through four intermediate steps. Mutations in the human HMBS (hHMBS) can lead to acute intermittent porphyria (AIP), a lethal metabolic disorder. The molecular basis of importance of the amino acid residues at the catalytic site of hHMBS has been well studied. However, the role of non-active site residues toward the activity of the enzyme and hence the association of their mutations with AIP is not known. Network-based analyses of protein structures provide a systems approach to understand the correlations of the residues through a series of inter-residue interactions. We analyzed the dynamic network representation of HMBS protein derived from five molecular dynamics trajectories corresponding to the five steps of pyrrole polymerization. We analyzed the network clusters for each stage and identified the amino acid residues and interactions responsible for the structural stability and catalytic function of the protein. The analysis of high betweenness nodes and interaction paths from the active site help in understanding the molecular basis of the effect of non-active site AIP-causing mutations on the catalytic activity.

A network-based approach reveals novel invasion and Maurer's clefts-related proteins in Plasmodium falciparum.

Malaria continues to be a major concern in developing countries despite continuous efforts to find a cure for the disease. Understanding the pathogenesis mechanism is necessary to identify more effective drug targets against malaria. Many years of experimental research have generated a large amount of data for the malarial parasite, Plasmodium falciparum. These data are useful to understand the importance of certain parasite proteins, but it often remains unclear how these proteins come together, interact with other proteins and carry out their function. Identification of all proteins involved in pathogenesis is an important step towards understanding the molecular mechanism of pathogenesis. In this study, dynamic stage-specific protein-protein interaction networks were created based on gene expression data during the parasite's intra-erythrocytic stages and static protein-protein interaction data. Using previously known proteins of a biological event as seed proteins, the random walk with restart (RWR) method was used on the dynamic protein-protein interaction networks to identify novel proteins related to that event. Two screening procedures namely, permutation test and GO enrichment test were performed to increase the reliability of the RWR predictions. The proposed method was first validated on Plasmodium falciparum proteins related to invasion, where it could reproduce the existing knowledge from a small set of seed proteins. It was then used to identify novel Maurer's clefts resident proteins, where it could identify 152 parasite proteins. We show that the current approach can annotate conserved proteins with unknown function. The predicted proteins can help build a mechanistic model for disease pathogenesis, which will be useful in identifying new drug targets.

Human hydroxymethylbilane synthase: Molecular dynamics of the pyrrole chain elongation identifies step-specific residues that cause AIP.

Hydroxymethylbilane synthase (HMBS), the third enzyme in the heme biosynthetic pathway, catalyzes the head-to-tail condensation of four molecules of porphobilinogen (PBG) to form the linear tetrapyrrole 1-hydroxymethylbilane (HMB). Mutations in human HMBS (hHMBS) cause acute intermittent porphyria (AIP), an autosomal-dominant disorder characterized by life-threatening neurovisceral attacks. Although the 3D structure of hHMBS has been reported, the mechanism of the stepwise polymerization of four PBG molecules to form HMB remains unknown. Moreover, the specific roles of each of the critical active-site residues in the stepwise enzymatic mechanism and the dynamic behavior of hHMBS during catalysis have not been investigated. Here, we report atomistic studies of HMB stepwise synthesis by using molecular dynamics (MD) simulations, mutagenesis, and in vitro expression analyses. These studies revealed that the hHMBS active-site loop movement and cofactor turn created space for the elongating pyrrole chain. Twenty-seven residues around the active site and water molecules interacted to stabilize the large, negatively charged, elongating polypyrrole. Mutagenesis of these active-site residues altered the binding site, hindered cofactor binding, decreased catalysis, impaired ligand exit, and/or destabilized the enzyme. Based on intermediate stages of chain elongation, R26 and R167 were the strongest candidates for proton transfer to deaminate the incoming PBG molecules. Unbiased random acceleration MD simulations identified R167 as a gatekeeper and facilitator of HMB egress through the space between the enzyme's domains and the active-site loop. These studies identified the specific active-site residues involved in each step of pyrrole elongation, thereby providing the molecular bases of the active-site mutations causing AIP.

Signals in the promoter regions of several cancerous genes.

The eukaryotic core promoter regions are complex and fuzzy, usually lacking any conserved regions. However, they contain signals in the form of short stretches of nucleic acid sequences, for transcription start sites (TSS) that are recognized by the transcription factors (TFs). The core promoter region thus plays an important role in biological pathways (gene network and activation). It has been reported that these signals are composed of nucleotide hexamers in the promoter sequence (smaller sequences are likely to have too little information to be useful and longer sequences are too complex to be recognized by proteins) reasonably close to the TSS. The signals (nucleotide hexamers) have been identified by a similarity search on the eukaryotic promoter database (EPD, Homo sapiens). The signals have been classified, depending on their base composition. They have been have clustered using an algorithm, such that there are two and three nucleotide differences between the classes and a single nucleotide difference within a class. We have reclassified the hexamers taking the highest frequent hexamers present in the EPD (Homo sapiens) as the class representatives. Also we have tried to find whether the same composition is reflected on the miRNAs but found that they probably have other functions unrelated to promoter recognition. In this report melanoma carcinoma pathway has been chosen as the reference pathway and the promoters of the driver genes has been searched for the presence of the major classes. A few of these were found and are reported here. Several non-cancerous genes have also been studied as reference and comparison.