Cancer and aging: a multidisciplinary medicinal chemistry approach on relevant biological targets such as proteasome, sirtuins and interleukin 6

It is well known that ageing and cancer have common origins due to internal and environmental stress and share some common hallmarks such as genomic instability, epigenetic alteration, aberrant telomeres, inflammation and immune injury. Moreover, ageing is involved in a number of events responsible for carcinogenesis and cancer development at the molecular, cellular, and tissue levels. Ageing could represent a “blockbuster” market because the target patient group includes potentially every person; at the same time, oncology has become the largest therapeutic area in the pharmaceutical industry in terms of the number of projects, clinical trials and research and development (R&D) spending, but cancer remains one of the leading causes of mortality worldwide. The overall aim of the work presented in this thesis was the rational design of new compounds able to modulate activity of relevant targets involved in cancer and aging-related pathologies, namely proteasome and immunoproteasome, sirtuins and interleukin 6. These three targets play different roles in human cells, but the modulation of its activity using small molecules could have beneficial effects on one or more aging-related diseases and cancer. We identified new moderately active and selective non-peptidic compounds able to inhibit the activity of both standard and immunoproteasome, as well as novel and selective scaffolds that would bind and inhibit SIRT6 selectively and can be used to sensitize tumor cells to commonly used anticancer agents such gemcitabine and olaparib. Moreover, our virtual screening approach led us also to the discovery of new putative modulators of SIRT3 with interesting in-vitro and cellular activity. Although the selectivity and potency of the identified chemical scaffolds are susceptible to be further improved, these compounds can be considered as highly promising leads for the development of future therapeutics

CMS physics technical design report : Addendum on high density QCD with heavy ions

Peer reviewe

Alignment of the CMS muon system with cosmic-ray and beam-halo muons

This is the Pre-print version of the Article. The official published version of the Paper can be accessed from the link below - Copyright @ 2010 IOPThe CMS muon system has been aligned using cosmic-ray muons collected in 2008 and beam-halo muons from the 2008 LHC circulating beam tests. After alignment, the resolution of the most sensitive coordinate is 80 microns for the relative positions of superlayers in the same barrel chamber and 270 microns for the relative positions of endcap chambers in the same ring structure. The resolution on the position of the central barrel chambers relative to the tracker is comprised between two extreme estimates, 200 and 700 microns, provided by two complementary studies. With minor modifications, the alignment procedures can be applied using muons from LHC collisions, leading to additional significant improvements.This work is supported by FMSR (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES (Croatia); RPF (Cyprus); Academy of Sciences and NICPB (Estonia); Academy of Finland, ME, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NKTH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); NRF (Korea); LAS (Lithuania); CINVESTAV, CONACYT, SEP, and UASLP-FAI (Mexico); PAEC (Pakistan); SCSR (Poland); FCT (Portugal); JINR(Armenia, Belarus, Georgia, Ukraine, Uzbekistan); MST and MAE (Russia); MSTDS (Serbia); MICINN and CPAN (Spain); Swiss Funding Agencies (Switzerland); NSC (Taipei); TUBITAK and TAEK (Turkey); STFC (United Kingdom); DOE and NSF (USA)

Alignment of the CMS muon system with cosmic-ray and beam-halo muons

This is the Pre-print version of the Article. The official published version of the Paper can be accessed from the link below - Copyright @ 2010 IOPThe CMS muon system has been aligned using cosmic-ray muons collected in 2008 and beam-halo muons from the 2008 LHC circulating beam tests. After alignment, the resolution of the most sensitive coordinate is 80 microns for the relative positions of superlayers in the same barrel chamber and 270 microns for the relative positions of endcap chambers in the same ring structure. The resolution on the position of the central barrel chambers relative to the tracker is comprised between two extreme estimates, 200 and 700 microns, provided by two complementary studies. With minor modifications, the alignment procedures can be applied using muons from LHC collisions, leading to additional significant improvements.This work is supported by FMSR (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES (Croatia); RPF (Cyprus); Academy of Sciences and NICPB (Estonia); Academy of Finland, ME, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NKTH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); NRF (Korea); LAS (Lithuania); CINVESTAV, CONACYT, SEP, and UASLP-FAI (Mexico); PAEC (Pakistan); SCSR (Poland); FCT (Portugal); JINR(Armenia, Belarus, Georgia, Ukraine, Uzbekistan); MST and MAE (Russia); MSTDS (Serbia); MICINN and CPAN (Spain); Swiss Funding Agencies (Switzerland); NSC (Taipei); TUBITAK and TAEK (Turkey); STFC (United Kingdom); DOE and NSF (USA)

BEAR, a novel virtual screening methodology for drug discovery

BEAR (binding estimation after refinement) is a new virtual screening technology based on the conformational refinement of docking poses through molecular dynamics and prediction of binding free energies using accurate scoring functions. Here, the authors report the results of an extensive benchmark of the BEAR performance in identifying a smaller subset of known inhibitors seeded in a large (1.5 million) database of compounds. BEAR performance proved strikingly better if compared with standard docking screening methods. The validations performed so far showed that BEAR is a reliable tool for drug discovery. It is fast, modular, and automated, and it can be applied to virtual screenings against any biological target with known structure and any database of compounds

BEAR, a Novel Virtual Screening Methodology for Drug Discovery

BEAR (binding estimation after refinement) is a new virtual screening technology based on the conformational refinement of docking poses through molecular dynamics and prediction of binding free energies using accurate scoring functions. Here, the authors report the results of an extensive benchmark of the BEAR performance in identifying a smaller subset of known inhibitors seeded in a large (1.5 million) database of compounds. BEAR performance proved strikingly better if compared with standard docking screening methods. The validations performed so far showed that BEAR is a reliable tool for drug discovery. It is fast, modular, and automated, and it can be applied to virtual screenings against any biological target with known structure and any database of compounds

Improving enrichment and hit rate in virtual screening

In the drug discovery process, accurate methods of computing the affinity of small molecules with a desired biological target are strongly needed. Even if, in the last years, the accuracy and efficiency of the available virtual screening algorithms have been improved, many drawbacks and limitations still exist. For example, docking methods lack a reliable simulation of both ligand and receptor flexibilities, as well as good scoring functions able to estimate ligand binding energies in reasonable agreement with experimental data. These limitations often lead to a high level of false positives or false negatives in the hit list. For that reason, it is generally agreed that docking results need to be post-processed with more accurate tools.To this end, we developed Binding Estimation After Refinement (BEAR), a new and automated post-docking procedure for the conformational refinement of docking poses through molecular dynamics (MD) followed by accurate prediction of binding free energies using MM-PBSA and MM-GBSA1 (Figure1). The BEAR performance in virtual screening was evaluated on several macromolecular targets and related sets of known ligands, determining the enrichment factors and assessing the correlation between predicted and experimental binding affinities. These analyses suggested critical improvements with respect to standard docking softwares2,3. Moreover, when applied in virtual screening campaigns, BEAR was able to discover novel and potent inhibitors of Plasmodium falciparum plasmepsin II with an impressive hit rate 4, and has been successful in identifying promising scaffolds for the design of irreversible protein kinase inhibitors5. Therefore, taken as a whole, the results obtained so far prospect that BEAR may become a prominent tool in the drug discovery pipeline.The BEAR virtual screening procedure is reliable and strongly automated, and can be tailored to the needs of the end-user in terms of computational time and the desired accuracy of the results. BEAR is under constant development and validation on additional biological targets in order to further improve accuracy, automation and calculation speed

BEAR: una piattaforma di screening virtuale al servizio delle aziende farmaceutiche e biotecnologiche.

Il gruppo di ricerca diretto dal Prof. Giulio Rastelli (Dipartimento di Scienze Farmaceutiche, Università di Modena e Reggio Emilia) ha ideato e sviluppato un sistema computazionale, automatizzato e innovativo, di screening virtuale denominato BEAR (“Binding Estimation After Refinement”). BEAR utilizza una combinazione di algoritmi di “molecular docking”, dinamica molecolare e metodi accurati per il calcolo dell’energia libera di legame, valutando l’affinità di ogni molecola per un determinato target. I numerosi studi di messa a punto e validazione, condotti su molteplici target biologici e diverse classi di molecole, hanno permesso di ottimizzare le condizioni sperimentali, la velocità di esecuzione degli screening e la qualità dei risultati ottenuti da BEAR. BEAR è in grado di fornire, in tempi rapidi, liste di molecole prioritarizzate in base alla loro potenziale affinità per ognuno dei target biologici studiati, identificando nelle migliori posizioni sia molecole attive già note (validazione) che classi totalmente nuove di inibitori (predizione). Spesso, tra le migliori molecole identificate da BEAR vi sono classi di composti diverse da quelle generalmente ottenute con piattaforme di screening standard. Questo, in aggiunta all’elevato potenziale in termini di molecole biologicamente attive, rappresenta un ulteriore punto di forza di BEAR, in quanto l’identificazione di inibitori aventi strutture originali rende meno gravosa la competizione brevettuale nelle prime fasi di individuazione di potenziali farmaci. Infine, è importante sottolineare che BEAR può essere applicato per scoprire molecole attive contro qualunque tipo di patologia

BEAR: una piattaforma di screening virtuale al servizio delle aziende farmaceutiche e biotecnologiche.

Il gruppo di ricerca diretto dal Prof. Giulio Rastelli (Dipartimento di Scienze Farmaceutiche, Universit\ue0 di Modena e Reggio Emilia) ha ideato e sviluppato un sistema computazionale, automatizzato e innovativo, di screening virtuale denominato BEAR (\u201cBinding Estimation After Refinement\u201d). BEAR utilizza una combinazione di algoritmi di \u201cmolecular docking\u201d, dinamica molecolare e metodi accurati per il calcolo dell\u2019energia libera di legame, valutando l\u2019affinit\ue0 di ogni molecola per un determinato target. I numerosi studi di messa a punto e validazione, condotti su molteplici target biologici e diverse classi di molecole, hanno permesso di ottimizzare le condizioni sperimentali, la velocit\ue0 di esecuzione degli screening e la qualit\ue0 dei risultati ottenuti da BEAR. BEAR \ue8 in grado di fornire, in tempi rapidi, liste di molecole prioritarizzate in base alla loro potenziale affinit\ue0 per ognuno dei target biologici studiati, identificando nelle migliori posizioni sia molecole attive gi\ue0 note (validazione) che classi totalmente nuove di inibitori (predizione). Spesso, tra le migliori molecole identificate da BEAR vi sono classi di composti diverse da quelle generalmente ottenute con piattaforme di screening standard. Questo, in aggiunta all\u2019elevato potenziale in termini di molecole biologicamente attive, rappresenta un ulteriore punto di forza di BEAR, in quanto l\u2019identificazione di inibitori aventi strutture originali rende meno gravosa la competizione brevettuale nelle prime fasi di individuazione di potenziali farmaci. Infine, \ue8 importante sottolineare che BEAR pu\uf2 essere applicato per scoprire molecole attive contro qualunque tipo di patologia

Selectivity hot-spots of sirtuin catalytic cores

Sirtuins are NAD(+)-dependent deacetylases with several biological roles in DNA regulation, genomic stability, metabolism, longevity and immune cell functions. Numerous disease conditions are linked to sirtuins including metabolic disorders, inflammatory and autoimmune processes and cancer. Although few specific small molecule modulators have been reported to date, the need to identify selective ligands would be crucial not only for the development of active pharmaceutical ingredients for new targeted therapies but also as a tool for dissecting the biological roles of sirtuin family members. Herein, we report a comprehensive study aimed to classify and identify the selectivity hot-spots for targeting the catalytic cores of human sirtuins using small molecule modulators. Our selectivity analysis suggests that catalytic cores can be divided into different clusters that can constitute the basis for the development of selective ligands. The ensemble of hot-spot information is expected to be helpful to devise new selective chemicals targeting sirtuin family members