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Rubio-Martinez, J.

Publications and source records attributed to Rubio-Martinez, J..

3 recordsLinked to original sources

Dominant induction of the inflammasome by the SARS-CoV-2 accessory protein ORF9b, abrogated by small-molecule ORF9b homodimerization inhibitors

Viral accessory proteins play critical roles in viral escape form host innate immune responses and in viral inflammatory pathogenesis. Here we show that the SARS-CoV-2 accessory protein, ORF9b, but not other SARS-CoV-2 accessory proteins (ORF3a, ORF3b, ORF6, ORF7, ORF8, ORF9c, ORF10), strongly activates inflammasome-dependent caspase-1 in A549 lung carcinoma cells and THP-1 monocyte-macrophage cells. Exposure to lipopolysaccharide (LPS) and ATP additively enhanced the activation of caspase-1 by ORF9b, suggesting that ORF9b and LPS follow parallel pathways in the activation of the inflammasome and caspase-1. Following rational in silico approaches, we have designed small molecules capable of inhibiting the homodimerization of ORF9b, which experimentally inhibited ORF9b-ORF9b homotypic interactions, caused mitochondrial eviction of ORF9b, inhibited ORF9b-induced activation of caspase-1 in A549 and THP-1 cells, cytokine release in THP-1 cells, and restored type I interferon (IFN-I) signaling suppressed by ORF9b in both cell models. These small molecules are first-in-class compounds targeting a viral accessory protein critical for viral-induced exacerbated inflammation and escape from innate immune responses, with the potential of mitigating the severe immunopathogenic damage induced by highly pathogenic coronaviruses and restoring antiviral innate immune responses curtailed by viral infection.

microbiology↗

Assessment of the bound conformation of Bombesin to the BB1 and BB2 Receptors

Bombesin is an endogenous peptide involved in a wide spectrum of physiological activities ranging from satiety, control of circadian rhythm and thermoregulation in the central nervous system, to stimulation of gastrointestinal hormone release, activation of macrophages and effects on development in peripheral tissues. Actions of the peptide are mediated through the two high affinity G-protein coupled receptors BB1 and BB2. Under pathophysiological conditions, these receptors are overexpressed in many different types of tumors, such as prostate cancer, breast cancer, small and non-small cell lung cancer and pancreatic cancer. This knowledge has been used for designing cell markers, but it has not been yet exploited for therapeutical purposes. Despite the enormous biological interest of the peptide, little is known about the stereochemical features that contribute to their activity. On the one hand, mutagenesis studies identified a few receptor residues important for high bombesin affinity and on the other, a few studies focused on the relevance of diverse residues of the peptide for receptor activation. Models of the peptide bound to BB1 and BB2 can be helpful to improve our understanding of the stereochemical features granting bombesin activity. Accordingly, the present study describes the computational process followed to construct such models from models of the peptide and its receptors by means of Steered Molecular Dynamics. Present results provide new insights into the structure-activity relationships of bombesin and its receptors, as well as render an explanation for the differential binding affinity observed towards the BB1 and BB2 receptors. Finally, these models can be further exploited to help for designing novel small molecule peptidomimetics with improved pharmacokinetics profile. AUTHOR SUMMARYThe goal of the present work is to construct models of bombesin bound to its receptors BB1 and BB2. The work represents an attempt to conceal experimental information available for bombesin activity on key residues of the sequence, as well as on specific residues in the receptors derived from site-directed mutagenesis with its structure. For this purpose, models of the two receptors were constructed homology using endothelin B as template and a model of bombesin structure in solution. Next, bombesin was docked onto each of the two receptors by means of Steered Molecular Dynamics, by pulling the peptide into the receptor using a constant force. Ten trials were performed on each receptor. After each trial, the resulting complex was relaxed using a 200 ns MD trajectory. In addition, the binding free energy was computed by means of the MMPBSA method for each of these simulations. Next, residue contributions to the binding free energy permitted to select the most suitable complex by comparison of their contributions to their importance deduced from experimental results. The best-fitted complex for each receptor was subject of a 2 s MD simulation that permitted to compute a difference of the binding free energy of the peptide that agrees well with pharmacology data. Finally, a study of the binding free energy contributions per residue permitted to understand specific differences between the bound conformation of bombesin in two receptors that explain the observed differential affinity. Specifically, a non-conserved residue in ECL3 (Pro in BB1 and Thr in BB2) appears to be responsible of a differential interaction of Arg(6.58) with the peptide, in addition to provide an extra interaction with Gln7 of bombesin (in the case of Thr(ECL3)). These models permit to explain the differential pharmacological profile, despite the high sequence identity between the two receptors, shedding light into the structure-activity relationships of the peptide available.

biophysics↗

Effect of automation on the accuracy of alchemical free energy calculation protocols

Hit-to-lead virtual screening frequently relies on a cascade of computational methods that starts with rapid calculations applied to a large number of compounds and ends with more expensive computations restricted to a subset of compounds that passed initial filters. This work focuses on set up protocols for alchemical free energy (AFE) scoring in the context of a Docking - MM/PBSA - AFE cascade. A dataset of 15 congeneric inhibitors of the ACK1 protein was used to evaluate the performance of AFE set up protocols that varied in the steps taken to prepare input files (using previously docked and best scored poses, manual selection of poses, manual placement of binding site water molecules). The main finding is that use of knowledge derived from X-ray structures to model binding modes, together with the manual placement of a bridging water molecule, improves the R2 from 0.45 {+/-} 0.06 to 0.76 {+/-} 0.02 and decreases the mean unsigned error from 2.11 {+/-} 0.08 to 1.24 {+/-} 0.04 kcal mol-1. By contrast a brute force automated protocol that increased the sampling time ten-fold lead to little improvements in accuracy. Besides, it is shown that for the present dataset hysteresis can be used to flag poses that need further attention even without prior knowledge of experimental binding affinities.

molecular biology↗