The Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2). The virus has rapidly spread in humans, causing the ...ongoing Coronavirus pandemic. Recent studies have shown that, similarly to SARS-CoV, SARS-CoV-2 utilises the Spike glycoprotein on the envelope to recognise and bind the human receptor ACE2. This event initiates the fusion of viral and host cell membranes and then the viral entry into the host cell. Despite several ongoing clinical studies, there are currently no approved vaccines or drugs that specifically target SARS-CoV-2. Until an effective vaccine is available, repurposing FDA approved drugs could significantly shorten the time and reduce the cost compared to de novo drug discovery. In this study we attempted to overcome the limitation of in silico virtual screening by applying a robust in silico drug repurposing strategy. We combined and integrated docking simulations, with molecular dynamics (MD), Supervised MD (SuMD) and Steered MD (SMD) simulations to identify a Spike protein - ACE2 interaction inhibitor. Our data showed that Simeprevir and Lumacaftor bind the receptor-binding domain of the Spike protein with high affinity and prevent ACE2 interaction.
Transient receptor potential vanilloid 1 (TRPV1) was reported to be a putative target for recovery from chronic pain, producing analgesic effects after its inhibition. A series of drug candidates ...were previously developed, without the ability to ameliorate the therapeutic outcome. Starting from previously designed compounds, derived from the hybridization of antagonist SB-705498 and partial agonist MDR-652, we performed a virtual screening on a pharmacophore model built by exploiting the Cryo-EM 3D structure of a nanomolar antagonist in complex with the human TRPV1 channel. The pharmacophore model was described by three pharmacophoric features, taking advantage of both the bioactive pose of the antagonist and the receptor exclusion spheres. The results of the screening were implemented inside a 3D-QSAR model, correlating with the negative decadic logarithm of the inhibition rate of the ligands. After the validation of the obtained 3D-QSAR model, we designed a new series of compounds by introducing key modifications on the original scaffold. Again, we determined the compounds’ binding poses after alignment to the pharmacophoric model, and we predicted their inhibition rates with the validated 3D-QSAR model. The obtained values resulted in being even more promising than parent compounds, demonstrating that ongoing research still leaves much room for improvement.
Multi-Omics Model Applied to Cancer Genetics Pettini, Francesco; Visibelli, Anna; Cicaloni, Vittoria ...
International journal of molecular sciences,
05/2021, Letnik:
22, Številka:
11
Journal Article
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In this review, we focus on bioinformatic oncology as an integrative discipline that incorporates knowledge from the mathematical, physical, and computational fields to further the biomedical ...understanding of cancer. Before providing a deeper insight into the bioinformatics approach and utilities involved in oncology, we must understand what is a system biology framework and the genetic connection, because of the high heterogenicity of the backgrounds of people approaching precision medicine. In fact, it is essential to providing general theoretical information on genomics, epigenomics, and transcriptomics to understand the phases of multi-omics approach. We consider how to create a multi-omics model. In the last section, we describe the new frontiers and future perspectives of this field.
The study of rare diseases is important not only for the individuals affected but also for the advancement of medical knowledge and a deeper understanding of human biology and genetics. The wide ...repertoire of structural information now available from reliable and accurate prediction methods provides the opportunity to investigate the molecular origins of most of the rare diseases reviewed in the Orpha.net database. Thus, it has been possible to analyze the topology of the pathogenic missense variants found in the 2515 proteins involved in Mendelian rare diseases (MRDs), which form the database for our structural bioinformatics study. The amino acid substitutions responsible for MRDs showed different mutation site distributions at different three-dimensional protein depths. We then highlighted the depth-dependent effects of pathogenic variants for the 20,061 pathogenic variants that are present in our database. The results of this structural bioinformatics investigation are relevant, as they provide additional clues to mitigate the damage caused by MRD.
Alkaptonuria (AKU), a rare genetic disorder, is characterized by the accumulation of homogentisic acid (HGA) in organs, which occurs because the homogentisate 1,2-dioxygenase (HGD) enzyme is not ...functional due to gene variants. Over time, HGA oxidation and accumulation cause the formation of the ochronotic pigment, a deposit that provokes tissue degeneration and organ malfunction. Here, we report a comprehensive review of the variants so far reported, the structural studies on the molecular consequences of protein stability and interaction, and molecular simulations for pharmacological chaperones as protein rescuers. Moreover, evidence accumulated so far in alkaptonuria research will be re-proposed as the bases for a precision medicine approach in a rare disease.
Emerging machine learning (ML) technologies have the potential to significantly improve the research and treatment of rare diseases, which constitute a vast set of diseases that affect a small ...proportion of the total population. Artificial Intelligence (AI) algorithms can help to quickly identify patterns and associations that would be difficult or impossible for human analysts to detect. Predictive modeling techniques, such as deep learning, have been used to forecast the progression of rare diseases, enabling the development of more targeted treatments. Moreover, AI has also shown promise in the field of drug development for rare diseases with the identification of subpopulations of patients who may be most likely to respond to a particular drug. This review aims to highlight the achievements of AI algorithms in the study of rare diseases in the past decade and advise researchers on which methods have proven to be most effective. The review will focus on specific rare diseases, as defined by a prevalence rate that does not exceed 1-9/100,000 on Orphanet, and will examine which AI methods have been most successful in their study. We believe this review can guide clinicians and researchers in the successful application of ML in rare diseases.
Alkaptonuria (AKU) is a rare metabolic disorder caused by a deficient enzyme in the tyrosine degradation pathway, homogentisate 1,2-dioxygenase (HGD). In 172 AKU patients from 39 countries, we ...identified 28 novel variants of the HGD gene, which include three larger genomic deletions within this gene discovered via self-designed multiplex ligation-dependent probe amplification (MLPA) probes. In addition, using a reporter minigene assay, we provide evidence that three of eight tested variants potentially affecting splicing cause exon skipping or cryptic splice-site activation. Extensive bioinformatics analysis of novel missense variants, and of the entire HGD monomer, confirmed mCSM as an effective computational tool for evaluating possible enzyme inactivation mechanisms. For the first time for AKU, a genotype-phenotype correlation study was performed for the three most frequent HGD variants identified in the Suitability Of Nitisinone in Alkaptonuria 2 (SONIA2) study. We found a small but statistically significant difference in urinary homogentisic acid (HGA) excretion, corrected for dietary protein intake, between variants leading to 1% or >30% residual HGD activity. There was, interestingly, no difference in serum levels or absolute urinary excretion of HGA, or clinical symptoms, indicating that protein intake is more important than differences in HGD variants for the amounts of HGA that accumulate in the body of AKU patients.
Currently, many environmental and energy-related problems are threatening the future of our planet. In October 2022, the Worldmeter recorded the world population as 7.9 billion people, estimating ...that there will be an increase of 2 billion by 2057. The rapid growth of the population and the continuous increase in needs are causing worrying conditions, such as pollution, climate change, global warming, waste disposal, and natural resource reduction. Looking for novel and innovative methods to overcome these global troubles is a must for our common welfare. The circular bioeconomy represents a promising strategy to alleviate the current conditions using biomass-like natural wastes to replace commercial products that have a negative effect on our ecological footprint. Applying the circular bioeconomy concept, we propose an integrated in silico and in vitro approach to identify antioxidant bioactive compounds extracted from chestnut burrs (an agroforest waste) and their potential biological targets. Our study provides a novel and robust strategy developed within the circular bioeconomy concept aimed at target and drug discovery for a wide range of diseases. Our study could open new frontiers in the circular bioeconomy related to target and drug discovery, offering new ideas for sustainable scientific research aimed at identifying novel therapeutical strategies.
Avena sativa L. is a wholegrain cereal and an important edible crop. Oats possesses high nutritional and health promoting values and contains high levels of bioactive compounds, including a group of ...phenolic amides, named avenanthramides (Avns), exerting antioxidant, anti-inflammatory, and anticancer activities. Epidermal growth factor receptor (EGFR) represents one of the most known oncogenes and it is frequently up-regulated or mutated in human cancers. The oncogenic effects of EGFR include enhanced cell growth, angiogenesis, and metastasis, and down-regulation or inhibition of EGFR signaling has therapeutic benefit. Front-line EGFR tyrosine kinase inhibitor therapy is the standard therapy for patients with EGFR-mutated lung cancer. However, the clinical effects of EGFR inhibition may be lost after a few months of treatment due to the onset of resistance. Here, we showed the anticancer activity of Avns, focusing on EGFR activation and signaling pathway. Lung cancer cellular models have been used to evaluate the activity of Avns on tumor growth, migration, EMT, and anoikis induced by EGF. In addition, docking and molecular dynamics simulations showed that the Avns bind with high affinity to a region in the vicinity of αC-helix and the DGF motif of EGFR, jeopardizing the target biological function. Altogether, our results reveal a new pharmacological activity of Avns as EGFR tyrosine kinase inhibitors.
The glycoprotein CD93 has recently been recognized to play an important role in the regulation of the angiogenic process. Moreover, CD93 is highly expressed in the endothelial cells of tumor blood ...vessel and faintly expressed in the non-proliferating endothelium. Much evidence suggests that CD93 mediates adhesion in the endothelium. Here we identify Multimerin 2 (MMRN2), a pan-endothelial extracellular matrix protein, as a specific ligand for CD93. We found that CD93 and MMRN2 are co-expressed in the blood vessels of various human tumors. Moreover, disruption of the CD93-MMRN2 interaction reduced endothelial cell adhesion and migration, making the interaction of CD93 with MMRN2 an ideal target to block pathological angiogenesis. Model structures and docking studies served to envisage the region of CD93 and MMRN2 involved in the interaction. Site-directed mutagenesis identified different residue hotspots either directly or indirectly involved in the binding. We propose a molecular model in which the coiled-coil domain of MMRN2 is engaged by F238 of CD93. Altogether, these studies identify the key interaction surfaces of the CD93-MMRN2 complex and provide a framework for exploring how to inhibit angiogenesis by hindering the CD93-MMRN2 interaction.
•CD93 and MMRN2 are molecular partners on the EC surface.•CD93 and MMRN2 are co-expressed in the blood vessels of various tumors.•The blockage of the CD93-MMRN2 interaction using a CD93 protein fragment inhibits in vitro angiogenesis.•A molecular model of the CD93-MMRN2 protein complex is described.•An amino acid residue of CD93 is essential for interaction with MMRN2 and for EC migration.
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