Rational Design of Allosteric and Selective Inhibitors of the Molecular Chaperone TRAP1

Summary: TRAP1 is the mitochondrial paralog of the heat shock protein 90 (HSP90) chaperone family. Its activity as an energy metabolism regulator has important implications in cancer, neurodegeneration, and ischemia. Selective inhibitors of TRAP1 could inform on its mechanisms of action and set the stage for targeted drug development, but their identification was hampered by the similarity among active sites in HSP90 homologs. We use a dynamics-based approach to identify a TRAP1 allosteric pocket distal to its active site that can host drug-like molecules, and we select small molecules with optimal stereochemical features to target the pocket. These leads inhibit TRAP1, but not HSP90, ATPase activity and revert TRAP1-dependent downregulation of succinate dehydrogenase activity in cancer cells and in zebrafish larvae. TRAP1 inhibitors are not toxic per se, but they abolish tumorigenic growth of neoplastic cells. Our results indicate that exploiting conformational dynamics can expand the chemical space of chaperone antagonists to TRAP1-specific inhibitors with wide therapeutic opportunities. : The molecular chaperone TRAP1 regulates energy metabolism, and its activity is relevant in cancer and degenerative diseases. Here, Sanchez-Martin et al. identify highly selective allosteric inhibitors of TRAP1. These compounds revert biochemical and pro-neoplastic effects of TRAP1 and could both enlighten its mode of action and disclose novel therapeutic strategies. Keywords: chaperone inhibitors, anticancer compound, molecular dynamics, allosteric ligands, TRAP1, HSP90, mitochondria, mitochondrial biology, zebrafish, cancer cells, neurofibrom

Aggressiveness pattern and second primary tumor risk associated with basaloid squamous cell carcinoma of the larynx

Basaloid squamous cell carcinoma (BSCC) is a rare, aggressive and distinct variant of squamous cell carcinoma (SCC) of the upper respiratory and digestive tract. We have evaluated disease specific survival (DSS) and overall survival (OS) through Kaplan-Meier method and mortality risk through univariate statistical analysis of Cox in 42 cases of BSCC and other 42 of laryngeal SCC (LSCC) matched for both age and sex. We demonstrated that laryngeal BSCC is a more aggressive tumor than LSCC as is associated to higher nodal recurrence of pathology (5 vs 2 patients, median survival, OR 2.7), a reduced survival (median survival 34 vs 40 months, OR 3.2 for mortality); in addition, basaloid patients have a higher risk to be affected by second primary tumors (13 vs 3 patients, OR 5.8) and a higher probability to die for this second tumor (Hazard Risk, HR 4.4). The analysis of survival shows an increased mortality risk concurrent with the parameters assessed by univariate analyses that assume a predictive and statistical significance in second tumor and grading in basaloid LSSC.Basaloid squamous cell carcinoma (BSCC) is a rare, aggressive and distinct variant of squamous cell carcinoma (SCC) of the upper respiratory and digestive tract. We have evaluated disease specific survival (DSS) and overall survival (OS) through Kaplan-Meier method and mortality risk through univariate statistical analysis of Cox in 42 cases of BSCC and other 42 of laryngeal SCC (LSCC) matched for both age and sex. We demonstrated that laryngeal BSCC is a more aggressive tumor than LSCC as is associated to higher nodal recurrence of pathology (5 vs 2 patients, median survival, OR 2.7), a reduced survival (median survival 34 vs 40 months, OR 3.2 for mortality); in addition, basaloid patients have a higher risk to be affected by second primary tumors (13 vs 3 patients, OR 5.8) and a higher probability to die for this second tumor (Hazard Risk, HR 4.4). The analysis of survival shows an increased mortality risk concurrent with the parameters assessed by univariate analyses that assume a predictive and statistical significance in second tumor and grading in basaloid LSSC

Targeting Difficult Protein-Protein Interactions with Plain and General Computational Approaches

Investigating protein-protein interactions (PPIs) holds great potential for therapeutic applications, since they mediate intricate cell signaling networks in physiological and disease states. However, their complex and multifaceted nature poses a major challenge for biochemistry and medicinal chemistry, thereby limiting the druggability of biological partners participating in PPIs. Molecular Dynamics (MD) provides a solid framework to study the reciprocal shaping of proteins’ interacting surfaces. Here, we review successful applications of MD-based methods developed in our group to predict interfacial areas involved in PPIs of pharmaceutical interest. We report two interesting examples of how structural, dynamic and energetic information can be combined into efficient strategies which, complemented by experiments, can lead to the design of new small molecules with promising activities against cancer and infections. Our advances in targeting key PPIs in angiogenic pathways and antigen-antibody recognition events will be discussed for their role in drug discovery and chemical biology

Targeting Difficult Protein-Protein Interactions with Plain and General Computational Approaches

Investigating protein-protein interactions (PPIs) holds great potential for therapeutic applications, since they mediate intricate cell signaling networks in physiological and disease states. However, their complex and multifaceted nature poses a major challenge for biochemistry and medicinal chemistry, thereby limiting the druggability of biological partners participating in PPIs. Molecular Dynamics (MD) provides a solid framework to study the reciprocal shaping of proteins’ interacting surfaces. Here, we review successful applications of MD-based methods developed in our group to predict interfacial areas involved in PPIs of pharmaceutical interest. We report two interesting examples of how structural, dynamic and energetic information can be combined into efficient strategies which, complemented by experiments, can lead to the design of new small molecules with promising activities against cancer and infections. Our advances in targeting key PPIs in angiogenic pathways and antigen-antibody recognition events will be discussed for their role in drug discovery and chemical biology

Diaryl urea:A privileged structure in anticancer agents

Abstract: The diaryl urea is an important fragment/pharmacophore in constructing anticancer molecules due to its near-perfect binding with certain acceptors. The urea NH moiety is a favorable hydrogen bond donor, while the urea oxygen atom is regarded as an excellent acceptor. Many novel compounds have been synthesized and evaluated for their antitumor activity with the successful development of sorafenib. Moreover, this structure is used to link alkylating pharmacophores with high affinity DNA binders. In addition, the diaryl urea is present in several kinase inhibitors, such as RAF, KDR and Aurora kinases. Above all, this moiety is used in the type II inhibitors: it usually forms one or two hydrogen bonds with a conserved glutamic acid and one with the backbone amide of the aspartic acid in the DFG motif. In addition, some diaryl urea derivatives act as Hedgehog (Hh) ligands, binding and inhibiting proteins involved in the homonymous Hh signaling pathway. In this review we provide some of the methodologies adopted for the synthesis of diaryl ureas and a description of the most representative antitumor agents bearing the diaryl urea moiety, focusing on their mechanisms bound to the receptors and structure-activity relationships (SAR). An increased knowledge of these derivatives could prompt the search to find new and more potent compounds

Diaryl Urea: A Privileged Structure in Anticancer Agents

Abstract: The diaryl urea is an important fragment/pharmacophore in constructing anticancer molecules due to its near-perfect binding with certain acceptors. The urea NH moiety is a favorable hydrogen bond donor, while the urea oxygen atom is regarded as an excellent acceptor. Many novel compounds have been synthesized and evaluated for their antitumor activity with the successful development of sorafenib. Moreover, this structure is used to link alkylating pharmacophores with high affinity DNA binders. In addition, the diaryl urea is present in several kinase inhibitors, such as RAF, KDR and Aurora kinases. Above all, this moiety is used in the type II inhibitors: it usually forms one or two hydrogen bonds with a conserved glutamic acid and one with the backbone amide of the aspartic acid in the DFG motif. In addition, some diaryl urea derivatives act as Hedgehog (Hh) ligands, binding and inhibiting proteins involved in the homonymous Hh signaling pathway. In this review we provide some of the methodologies adopted for the synthesis of diaryl ureas and a description of the most representative antitumor agents bearing the diaryl urea moiety, focusing on their mechanisms bound to the receptors and structure-activity relationships (SAR). An increased knowledge of these derivatives could prompt the search to find new and more potent compounds

Multi-Target Dopamine D3 Receptor Modulators: Actionable Knowledge for Drug Design from Molecular Dynamics and Machine Learning

Local changes in the structure of G-protein coupled receptors (GPCR) binders largely affect their pharmacological profile. While the sought efficacy can be empirically obtained by introducing local modifications, the underlining structural explanation can remain elusive. Here, molecular dynamics (MD) simulations of the eticlopride-bound inactive state of the Dopamine D3 Receptor (D3DR) have been clustered using a machine learning-based approach in the attempt to rationalize the efficacy change in four congeneric modulators. Accumulating extended MD trajectories of receptor-ligand complexes, we observed how the increase in ligand flexibility progressively destabilized the crystal structure of the inactivated receptor. To prospectively validate this model, a partial agonist was rationally designed based on structural insights and computational modeling, and eventually synthesized and tested. Results turned out to be in line with the predictions. This case study suggests that the investigation of ligand flexibility in the framework of extended MD simulations can assist and inform drug design strategies, highlighting its potential role as a powerful in silico counterpart to functional assays

Mapping Cholesterol Interaction Sites on Serotonin Transporter through Coarse-Grained Molecular Dynamics

<div><p>Serotonin transporter (SERT) modulates serotonergic signaling via re-uptake of serotonin in pre-synaptic cells. The inclusion in cholesterol-enriched membrane domains is crucial for SERT activity, suggesting a cross-talk between the protein and the sterol. Here, we develop a protocol to identify potential cholesterol interaction sites coupling statistical analysis to multi-microsecond coarse-grained molecular dynamics simulations of SERT in a previously validated raft-like membrane model. Six putative sites were found, including a putative CRAC motif on TM4 and a CARC motif on TM10. Among them, four hot-spots near regions related to ion binding, transport, and inhibition were detected. Our results encourage prospective studies to unravel mechanistic features of the transporter and related drug discovery implications.</p></div