Search results for "Druggability"

2015

Pseudomonas aeruginosa is a Gram-negative bacterium known to cause opportunistic infections in immune-compromised or immunosuppressed individuals that often prove fatal. New drugs to combat this organism are therefore sought after. To this end, we subjected the gene products of predicted perturbative genes to structure-based druggability predictions using DrugPred. Making this approach suitable for large-scale predictions required the introduction of new methods for calculation of descriptors, development of a workflow to identify suitable pockets in homologous proteins and establishment of criteria to obtain valid druggability predictions based on homologs. We were able to identify 29 pert…

Targeting SARS-CoV-2 RBD Interface: a Supervised Computational Data-Driven Approach to Identify Potential Modulators

2020

Coronavirus disease 2019 (COVID-19) has spread out as a pandemic threat affecting over 2 million people. The infectious process initiates via binding of SARS-CoV-2 Spike (S) glycoprotein to host angiotensin-converting enzyme 2 (ACE2). The interaction is mediated by the receptor-binding domain (RBD) of S glycoprotein, promoting host receptor recognition and binding to ACE2 peptidase domain (PD), thus representing a promising target for therapeutic intervention. Herein, we present a computational study aimed at identifying small molecules potentially able to target RBD. Although targeting PPI remains a challenge in drug discovery, our investigation highlights that interaction between SARS-CoV…

The tumor-agnostic treatment for patients with solid tumors: a position paper on behalf of the AIOM- SIAPEC/IAP-SIBioC-SIF Italian Scientific Societi…

2021

The personalized medicine is in a rapidly evolving scenario. The identification of actionable mutations is revolutionizing the therapeutic landscape of tumors. The morphological and histological tumor features are enriched by the extensive genomic profiling, and the first tumor-agnostic drugs have been approved regardless of tumor histology, guided by predictive and druggable genetic alterations. This new paradigm of "mutational oncology", presents a great potential to change the oncologic therapeutic scenario, but also some critical aspects need to be underlined. A process governance is mandatory to ensure the genomic testing accuracy and homogeneity, the economic sustainability, and the r…

Investigating the Molecular Mechanism of H3B-8800: A Splicing Modulator Inducing Preferential Lethality in Spliceosome-Mutant Cancers.

2021

The SF3B1 protein, part of the SF3b complex, recognizes the intron branch point sequence of precursor messenger RNA (pre-mRNA), thus contributing to splicing fidelity. SF3B1 is frequently mutated in cancer and is the target of distinct families of splicing modulators (SMs). Among these, H3B-8800 is of particular interest, as it induces preferential lethality in cancer cells bearing the frequent and highly pathogenic K700E SF3B1 mutation. Despite the potential of H3B-8800 to treat myeloid leukemia and other cancer types hallmarked by SF3B1 mutations, the molecular mechanism underlying its preferential lethality towards spliceosome-mutant cancer cells remains elusive. Here, microsecond-long a…

Epigenetic siRNA and Chemical Screens Identify SETD8 Inhibition as a Therapeutic Strategy for p53 Activation in High-Risk Neuroblastoma

2017

Given the paucity of druggable mutations in high-risk neuroblastoma (NB), we undertook chromatin-focused small interfering RNA and chemical screens to uncover epigenetic regulators critical for the differentiation block in high-risk NB. High-content Opera imaging identified 53 genes whose loss of expression led to a decrease in NB cell proliferation and 16 also induced differentiation. From these, the secondary chemical screen identified SETD8, the H4K20me1 methyltransferase, as a druggable NB target. Functional studies revealed that SETD8 ablation rescued the pro-apoptotic and cell-cycle arrest functions of p53 by decreasing p53K382me1, leading to activation of the p53 canonical pathway. I…

Single-cell analysis of population context advances RNAi screening at multiple levels

2012

Isogenic cells in culture show strong variability, which arises from dynamic adaptations to the microenvironment of individual cells. Here we study the influence of the cell population context, which determines a single cell's microenvironment, in image‐based RNAi screens. We developed a comprehensive computational approach that employs Bayesian and multivariate methods at the single‐cell level. We applied these methods to 45 RNA interference screens of various sizes, including 7 druggable genome and 2 genome‐wide screens, analysing 17 different mammalian virus infections and four related cell physiological processes. Analysing cell‐based screens at this depth reveals widespread RNAi‐induce…