@article{nokey,

title = {Structure-Based Virtual Screening for Ligands of G Protein–Coupled Receptors: What Can Molecular Docking Do for You?},

author = {Flavio Ballante and Albert J Kooistra and Stefanie Kampen and Chris de Graaf and Jens Carlsson},

url = {https://pharmrev.aspetjournals.org/content/73/4/527},

doi = {10.1124/pharmrev.120.000246},

issn = {1521-0081},

year  = {2021},

date = {2021-12-14},

urldate = {2021-12-14},

journal = {Pharmacological Reviews},

volume = {73},

pages = {527-565},

abstract = {G protein–coupled receptors (GPCRs) constitute the largest family of membrane proteins in the human genome and are important therapeutic targets. During the last decade, the number of atomic-resolution structures of GPCRs has increased rapidly, providing insights into drug binding at the molecular level. These breakthroughs have created excitement regarding the potential of using structural information in ligand design and initiated a new era of rational drug discovery for GPCRs. The molecular docking method is now widely applied to model the three-dimensional structures of GPCR-ligand complexes and screen for chemical probes in large compound libraries. In this review article, we first summarize the current structural coverage of the GPCR superfamily and the understanding of receptor-ligand interactions at atomic resolution. We then present the general workflow of structure-based virtual screening and strategies to discover GPCR ligands in chemical libraries. We assess the state of the art of this research field by summarizing prospective applications of virtual screening based on experimental structures. Strategies to identify compounds with specific efficacy and selectivity profiles are discussed, illustrating the opportunities and limitations of the molecular docking method. Our overview shows that structure-based virtual screening can discover novel leads and will be essential in pursuing the next generation of GPCR drugs.},

keywords = {GPCR, Molecular Docking, Review, Structure-Based Drug Design, Virtual Screening},

pubstate = {published},

tppubtype = {article}

}

@article{Kapla2021,

title = {Can molecular dynamics simulations improve the structural accuracy and virtual screening performance of GPCR models? },

author = {Jon Kapla and Ismael Rodriguez Espigares and Flavio Ballante and Jana Selent and Jens Carlsson

},

url = {https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008936},

doi = {10.1371/journal.pcbi.1008936},

year  = {2021},

date = {2021-05-13},

journal = {PLOS Computational Biology},

keywords = {GPCR, Molecular Docking, Molecular Dynamics, Molecular Modeling},

pubstate = {published},

tppubtype = {article}

}

@article{Nencetti2020,

title = {Identification of histone deacetylase inhibitors with (arylidene)aminoxy scaffold active in uveal melanoma cell lines},

author = {Susanna Nencetti and Doretta Cuffaro and Elisa Nuti and Lidia Ciccone and Armando Rossello and Marina Fabbi and Flavio Ballante and Gabriella Ortore and Grazia Carbotti and Francesco Campelli and Irene Banti and Rosaria Gangemi and Garland R. Marshall and Elisabetta Orlandini},

url = {https://www.tandfonline.com/doi/full/10.1080/14756366.2020.1835883},

doi = {10.1080/14756366.2020.1835883},

year  = {2020},

date = {2020-10-26},

urldate = {2020-10-26},

journal = {Journal of Enzyme Inhibition and Medicinal Chemistry},

volume = {36},

number = {1},

pages = {34–47},

abstract = {Uveal melanoma (UM) represents an aggressive type of cancer and currently, there is no effective treat-ment for this metastatic disease. In the last years, histone deacetylase inhibitors (HDACIs) have beenstudied as a possible therapeutic treatment for UM, alone or in association with other chemotherapeuticagents. Here we synthesised a series of new HDACIs based on the SAHA scaffold bearing an (arylidene)a-minoxy moiety. Their HDAC inhibitory activity was evaluated on isolated human HDAC1, 3, 6, and 8 byfluorometric assay and their binding mode in the catalytic site of HDACs was studied by molecular dock-ing. The most promising hit was the quinoline derivativeVS13, a nanomolar inhibitor of HDAC6, whichexhibited a good antiproliferative effect on UM cell lines at micromolar concentration and a capability tomodify the mRNA levels of HDAC target genes similar to that of SAHA.},

keywords = {Biochemistry, HDAC, Molecular Docking, Molecular Modeling},

pubstate = {published},

tppubtype = {article}

}

@article{Ballante2019,

title = {Docking finds GPCR ligands in dark chemical matter},

author = {Flavio Ballante and Axel Rudling and Alexey Zeifman and Andreas Luttens and Duy Duc Vo and John Irwin and Jan Kihlberg and José Brea and Maria Loza and Jens Carlsson},

url = {https://pubs.acs.org/doi/abs/10.1021/acs.jmedchem.9b01560},

year  = {2019},

date = {2019-12-17},

journal = {Journal of Medicinal Chemistry},

volume = {Just accepted manuscript},

abstract = {High-throughput screening has revealed dark chemical matter, a set of drug-like compounds that has never shown bioactivity despite being extensively assayed. If dark molecules are found active at a therapeutic target, their extraordinary selectivity profiles make excellent starting-points for drug development. We explored if ligands of therapeutically relevant G-protein-coupled receptors could be discovered by structure-based virtual screening of the dark chemical matter. Molecular docking screens against crystal structures of the A2A adenosine and the D4 dopamine receptors were carried out and 53 top-ranked molecules were evaluated experimentally. Two ligands of each receptor were discovered and the most potent had submicromolar affinities. Analysis of bioactivity data showed that the ligands lacked activity at hundreds of off-targets, including several that are associated with adverse effects. Our results demonstrate that virtual screening provides an efficient means to mine the dark chemical space, which could contribute to development of drugs with improved safety profiles.},

keywords = {Biochemistry, Dark Chemical Matter, GPCR, Molecular Docking, Virtual Screening},

pubstate = {published},

tppubtype = {article}

}

@article{Kennedy2018,

title = {Structural characterization of agonist binding to protease-activated receptor 2 through mutagenesis and computational modeling},

author = {Amanda J. Kennedy and Flavio Ballante and Johan R. Johansson and Graeme Milligan and Linda Sundström and Anneli Nordqvist and Jens Carlsson},

url = {https://pubs.acs.org/doi/10.1021/acsptsci.8b00019},

doi = {10.1021/acsptsci.8b00019},

issn = {2575-9108},

year  = {2018},

date = {2018-10-16},

journal = {ACS Pharmacology & Translational Science},

volume = {1},

number = {2},

pages = {119-133},

abstract = {Protease-activated receptor 2 (PAR2) is a G protein-coupled receptor that is activated by proteolytic cleavage of its N-terminus. The unmasked N-terminal peptide then binds to the transmembrane bundle, leading to activation of intracellular signaling pathways associated with inflammation and cancer. Recently determined crystal structures have revealed binding sites of PAR2 antagonists, but the binding mode of the peptide agonist remains unknown. In order to generate a model of PAR2 in complex with peptide SLIGKV, corresponding to the trypsin-exposed tethered ligand, the orthosteric binding site was probed by iterative combinations of receptor mutagenesis, agonist ligand modifications and data-driven structural modeling. Flexible-receptor docking identified a conserved binding mode for agonists related to the endogenous ligand that was consistent with the experimental data and allowed synthesis of a novel peptide (1-benzyl-1H[1,2,3]triazole-4-yl-LIGKV) with higher functional potency than SLIGKV. The final model may be used to understand the structural basis of PAR2 activation and in virtual screens to identify novel PAR2 agonist and competitive antagonists. The combined experimental and computational approach to characterize agonist binding to PAR2 can be extended to study the many other G protein-coupled receptors that recognize peptides or proteins.},

keywords = {Biochemistry, Clusterizer, Homology Modeling, Molecular Docking},

pubstate = {published},

tppubtype = {article}

}

@article{R2017,

title = {Limiting Assumptions in the Design of Peptidomimetics},

author = {Garland R. Marshall and Flavio Ballante},

editor = {Wiley Periodicals, Inc.},

url = {http://onlinelibrary.wiley.com/doi/10.1002/ddr.21406/full},

doi = {10.1002/ddr.21406},

issn = {1098-2299},

year  = {2017},

date = {2017-09-06},

journal = {Drug Development Research},

volume = {78},

number = {6},

pages = {245–267},

keywords = {Beta-sheet mimetics, Helix mimetics reverse-turn mimetics, Peptidomimetics, Semi-rigid analogs},

pubstate = {published},

tppubtype = {article}

}

@article{Ballante2017,

title = {Structural Insights of SmKDAC8 Inhibitors: Targeting Schistosoma Epigenetics Through a Combined Structure-Based 3D QSAR, in vitro and Synthesis Strategy},

author = {Flavio Ballante and D. Rajasekhar Reddy and Nancy J. Zhou and Garland R. Marshall},

editor = {Elsevier},

url = {http://www.sciencedirect.com/science/article/pii/S0968089616314134},

year  = {2017},

date = {2017-02-13},

journal = {Bioorganic & Medicinal Chemistry},

keywords = {3D QSAR, Biochemistry, COMBINEr, Molecular Docking, Molecular Modeling, Organic Chemistry, PLS, Schistosoma mansoni, Virtual Screening},

pubstate = {published},

tppubtype = {article}

}

@article{Reddy2016,

title = {Design and synthesis of benzodiazepine analogs as isoform-selective human lysine deacetylase inhibitors},

author = {D. Rajasekhar Reddy and Flavio Ballante and Nancy J. Zhou and Garland R. Marshall},

url = {http://www.sciencedirect.com/science/article/pii/S0223523416310388?np=y},

doi = {10.1016/j.ejmech.2016.12.032},

year  = {2016},

date = {2016-12-16},

journal = {European Journal of Medicinal Chemistry},

volume = {127},

pages = {Pages 531–553},

abstract = {A comprehensive investigation was performed to identify new benzodiazepine (BZD) derivatives as potent and selective human lysine deacetylase inhibitors (hKDACis). A total of 108 BZD compounds were designed, synthesized and from that 104 compounds were biologically evaluated against human lysine deacetylases (hKDACs) 1, 3 and 8 (class I) and 6 (class IIb). The most active compounds showed mid-nanomolar potencies against hKDACs 1, 3 and 6 and micromolar activity against hKDAC8, while a promising compound (6q) showed selectivity towards hKDAC3 among the different enzyme isoforms. An hKDAC6 homology model, refined by molecular dynamics simulation was generated, and molecular docking studies performed to rationalize the dominant ligand-residue interactions as well as to define structure-activity-relationships. Experimental results confirmed the usefulness of the benzodiazepine moiety as capping group when pursuing hKDAC isoform-selectivity inhibition, suggesting its continued use when designing new hKDACis.},

keywords = {Biochemistry, HDAC, Molecular Docking},

pubstate = {published},

tppubtype = {article}

}

@article{Ballante2015,

title = {An Automated Strategy for Binding-Pose Selection and Docking Assessment in Structure-Based Drug Design},

author = {Flavio, Ballante and Garland R. Marshall },

editor = {American Chemical Society},

url = {http://pubs.acs.org/doi/abs/10.1021/acs.jcim.5b00603},

doi = {10.1021/acs.jcim.5b00603},

year  = {2015},

date = {2015-12-18},

urldate = {2015-12-18},

journal = {Journal of Chemical Information and Modeling},

volume = {56},

number = {1},

pages = {54-72},

abstract = {Molecular docking is a widely used technique in drug design to predict the binding pose of a candidate compound in a defined therapeutic target. Numerous docking protocols are available, each characterized by different search methods and scoring functions, thus providing variable predictive capability on a same ligand-protein system. To validate a docking protocol, it is necessary to determine a priori the ability to reproduce the experimental binding pose (i.e. by determining the Docking Accuracy, DA) to select the most appropriate docking procedure, and thus estimate the rate of success in docking novel compounds. As common docking programs use generally different RMSD formulas, scoring functions and format results, it is both difficult and time consuming to: consistently determine and compare their predictive capability to identify the best protocol to be used for the target of interest; extrapolate the binding poses (i.e. Best- docked (BD), Best-cluster (BC) and Best-fit (BF) poses) when applying a given docking program over thousands/millions of molecules during virtual screening. To reduce this difficulty, two new procedures, called Clusterizer and DockAccessor have been developed and implemented for use with some common and “free-for-academics” programs, such as: AutoDock4, AutoDock4(Zn), AutoDock Vina, DOCK, MpSDockZn, PLANTS, and Surflex-Dock to automatically extrapolate BD, BC and BF poses, as well as perform consistent cluster and docking accuracy (DA) analyses. Clusterizer and DockAccessor represent two novel tools, (code available over the internet) to collect computationally determined poses as well as detect the most predictive docking approach. Herein, an application to lysine deacetylase (KDAC) inhibitors is illustrated.},

keywords = {Chemoinformatics, Clusterizer, DockAccessor, Docking Assessment, Molecular Docking, Molecular Modeling},

pubstate = {published},

tppubtype = {article}

}

@article{Reddy2015,

title = {Design and Synthesis of Simplified Largazole Analogs as Isoform-Selective Human Lysine Deacetylase Inhibitors},

author = {Reddy Nandarapu Damodara and Ballante Flavio and Chuang Timothy and Pirolli Adele and Marrocco Biagina and Garland R, Marshall },

editor = {American Chemical Society},

url = {http://pubs.acs.org/doi/abs/10.1021/acs.jmedchem.5b01632},

doi = {10.1021/acs.jmedchem.5b01632},

year  = {2015},

date = {2015-12-17},

journal = {Journal of Medicinal Chemistry},

volume = {in press},

abstract = {Selective inhibition of KDAC6isoforms while maintaining potency remains a challenge. Using the largazole macrocyclic depsipeptide structure as a starting point for developing new KDACIs with increased  selectivity,  a  combination  of four  different  simplified  largazole  analog  (SLA)  scaffolds with  diverse  zinc6binding  groups  (for  a  total  of  60

  compounds)  were  designed,  synthesized  and evaluated against class I KDACs 1, 3 and 8, and class II KDAC6. Experimental evidence as well as molecular  docking  poses  converged  to  establish  the cyclic  tetrapeptides  (CTPs)  as  the  primary determinant of both potency and selectivity, by influencing the correct alignment of the zinc6binding 

group  in  the  KDAC  active  site,  providing  a  further basis  for  developing  new  KDACIs  of  higher isoform selectivity and potency.  },

keywords = {Biochemistry, HDAC, Molecular Docking, Organic Chemistry},

pubstate = {published},

tppubtype = {article}

}

@article{Ragno2015,

title = {Vascular endothelial growth factor receptor-2 (VEGFR-2) inhibitors: development and validation of predictive 3-D QSAR models through extensive ligand-and structure-based approaches},

author = {Ragno Rino and Ballante Flavio and Pirolli Adele and Richard B, Wickersham III and Patsilinakos Alexandros and Hesse Stéphanie and Perspicace Enrico and Kirsch Gilbert},

editor = {Springer International Publishing},

url = {http://link.springer.com/article/10.1007%2Fs10822-015-9859-y},

doi = {10.1007/s10822-015-9859-y},

year  = {2015},

date = {2015-07-21},

urldate = {2015-07-21},

journal = {Journal of Computer-Aided Molecular Design},

volume = {29},

number = {8},

pages = {757-776},

abstract = {Vascular endothelial growth factor receptor-2, (VEGFR-2), is a key element in angiogenesis, the process by which new blood vessels are formed, and is thus an important pharmaceutical target. Here, 3-D quantitative structure-activity relationship (3-D QSAR) were used to build a quantitative screening and pharmacophore model of the VEGFR-2 receptors for design of inhibitors with improved activities. Most of available experimental data information has been used as training set to derive optimized and fully cross-validated eight mono-probe and a multi-probe quantitative models. Notable is the use of 262 molecules, aligned following both structure-based and ligand-based protocols, as external test set confirming the 3-D QSAR models' predictive capability and their usefulness in design new VEGFR-2 inhibitors. From a survey on literature, this is the first generation of a wide-ranging computational medicinal chemistry application on VEGFR2 inhibitors. },

keywords = {3-D QSAutogrid/R, 3D QSAR, Ligand-Based Design, Molecular Docking, Molecular Modeling, Pharmacophoric Model, PLS, VEGFR-2},

pubstate = {published},

tppubtype = {article}

}

@article{Rotili2014,

title = {Exploring the Role of 2 ‑ Chloro-6- fluoro Substitution in 2 ‑ Alkylthio-6- benzyl-5-alkylpyrimidin-4(3 H ) ‑ ones: Effects in HIV-1-Infected Cells and in HIV ‑ 1 Reverse Transcriptase Enzymes},

author = {Rotili Dante and Tarantino Domenico and Maxim B, Nawrozkij and Alexandre S, Babushkin and Botta Giorgia and Marrocco Biagina and Cirilli Roberto and Menta Sergio and Badia Roger and Crespan Emmanuele and Ballante Flavio and Ragno Rino and José A, Esté and Maga Giovanni and Mai Antonello},

editor = {American Chemical Society},

url = {http://pubs.acs.org/doi/abs/10.1021/jm500284x},

doi = {10.1021/jm500284x},

year  = {2014},

date = {2014-06-16},

journal = {Journal of Medicinal Chemistry},

volume = {57},

number = {12},

pages = {5212-5225},

abstract = {A comparison of the effects of the 6-(2-chloro-6-fluorobenzyl)-2-(alkylthio)pyrimidin-4(3H)-ones (2-Cl-6-F-S-DABOs) 7–12 and the related 6-(2,6-difluorobenzyl) counterparts 13–15 in HIV-1 infected cells and in the HIV-1 reverse transcriptase (RT) assays is here described. The new 2-Cl-6-F-S-DABOs showed up to picomolar activity against wt HIV-1. Against clinically relevant HIV-1 mutants and in enzyme assays, the simultaneous C5(methyl)/C6(methyl/ethyl) substitution in the 2-Cl-6-F- and 2,6-F2-benzyl series furnished compounds with the highest, wide-spectrum inhibitory activity against HIV-1. Three representative 2-Cl-6-F-S-DABOs carrying two (9c, 10c) or one (10a) stereogenic centers were resolved into their individual stereoisomers and showed a significant diastereo- and enantioselectivity in HIV-1 inhibition, the highest antiviral activity well correlating with the R absolute configuration to the stereogenic center of the C6-benzylic position in both cellular and enzymatic tests. Application of previously reported COMBINEr protocol on 9c and 10c confirmed the influence of the stereogenic centers on their binding modes in the HIV-1 RT.},

keywords = {Biochemistry, COMBINEr, DABO, HIV-1, HIV-RT, Molecular Docking, Molecular Modeling, NNRTIs, Organic Chemistry, PLS},

pubstate = {published},

tppubtype = {article}

}

@article{Ballante2014,

title = {Hsp90 inhibitors, part 1: definition of 3-D QSAutogrid/R models as a tool for virtual screening},

author = { Ballante Flavio and Caroli Antonia and Richard B, Wickersham III and Ragno Rino},

editor = {American Chemical Society},

url = {http://pubs.acs.org/doi/abs/10.1021/ci400759t},

doi = {10.1021/ci400759t},

year  = {2014},

date = {2014-03-04},

journal = {Journal of Chemical Information and Modeling},

volume = {54},

number = {3},

pages = {956-969},

abstract = {The multichaperone heat shock protein (Hsp) 90 complex mediates the maturation and stability of a variety of oncogenic signaling proteins. For this reason, Hsp90 has emerged as a promising target for anticancer drug development. Herein, we describe a complete computational procedure for building several 3-D QSAR models used as a ligand-based (LB) component of a comprehensive ligand-based (LB) and structure-based (SB) virtual screening (VS) protocol to identify novel molecular scaffolds of Hsp90 inhibitors. By the application of the 3-D QSAutogrid/R method, eight SB PLS 3-D QSAR models were generated, leading to a final multiprobe (MP) 3-D QSAR pharmacophoric model capable of recognizing the most significant chemical features for Hsp90 inhibition. Both the monoprobe and multiprobe models were optimized, cross-validated, and tested against an external test set. The obtained statistical results confirmed the models as robust and predictive to be used in a subsequent VS.},

keywords = {3-D QSAutogrid/R, 3D QSAR, HSP90, Ligand-Based Design, Molecular Docking, Pharmacophoric Model, PLS, Virtual Screening},

pubstate = {published},

tppubtype = {article}

}

@article{Caroli2014,

title = {Hsp90 Inhibitors, Part 2: Combining Ligand-Based and Structure-Based Approaches for Virtual Screening Application},

author = { Caroli Antonia and Ballante Flavio and Richard B, Wickersham III and Corelli Federico and Ragno Rino},

editor = {American Chemical Society},

url = {http://pubs.acs.org/doi/abs/10.1021/ci400760a},

doi = {10.1021/ci400760a},

year  = {2014},

date = {2014-03-04},

journal = {Journal of Chemical Information and Modeling},

volume = {54},

number = {3},

pages = {970-977},

abstract = {Hsp90 continues to be an important target for pharmaceutical discovery. In this project, virtual screening (VS) for novel Hsp90 inhibitors was performed using a combination of Autodock and Surflex-Sim (LB) scoring functions with the predictive ability of 3-D QSAR models, previously generated with the 3-D QSAutogrid/R procedure. Extensive validation of both structure-based (SB) and ligand-based (LB), through realignments and cross-alignments, allowed the definition of LB and SB alignment rules. The mixed LB/SB protocol was applied to virtually screen potential Hsp90 inhibitors from the NCI Diversity Set composed of 1785 compounds. A selected ensemble of 80 compounds were biologically tested. Among these molecules, preliminary data yielded four derivatives exhibiting IC50 values ranging between 18 and 63 μM as hits for a subsequent medicinal chemistry optimization procedure.},

keywords = {3-D QSAutogrid/R, 3D QSAR, HSP90, Ligand-Based Design, Molecular Docking, Molecular Modeling, MPGRS, Pharmacophoric Model, PLS, Virtual Screening},

pubstate = {published},

tppubtype = {article}

}

@article{Perspicace2013,

title = {Design, synthesis and biological evaluation of new classes of thieno [3, 2-d] pyrimidinone and thieno [1, 2, 3] triazine as inhibitor of vascular endothelial growth factor receptor-2 (VEGFR-2)},

author = { Perspicace Enrico and Jouan-Hureaux Valérie and Ragno Rino and Ballante Flavio and Sartini Stefania and La Motta Concettina and Da Settimo Federico and Chen Binbin and Kirsch Gilbert and Schneider Serge and Faivre Béatrice and Hesse Stéphanie},

editor = {Elsevier Masson},

url = {http://www.sciencedirect.com/science/article/pii/S0223523413001700},

doi = {10.1016/j.ejmech.2013.03.022},

year  = {2013},

date = {2013-05-31},

journal = {European Journal of Medicinal Chemistry},

volume = {63},

pages = {765-781},

abstract = {Driven by a multidisciplinary approach combination (Structure-Based (SB) Three-Dimensional Quantitative Structure–Activity Relationships (3-D QSAR), molecular modeling, organic chemistry and various biological evaluations) here is reported the disclosure of new thienopyrimidines 1–3 as inhibitors of KDR activity and human umbilical vein endothelial cell (HUVEC) proliferation. More specifically, compound 2f represents a new lead compound that inhibits VEGFR-2 and HUVEC at μM concentration. Moreover by the mean of an endothelial cell tube formation in vitro model 2f tartaric acid salt proved to block angiogenesis of HUVEC at μM level.},

keywords = {3-D QSAutogrid/R, 3D QSAR, Biochemistry, HUVEC, Organic Chemistry, PLS, VEGFR-2},

pubstate = {published},

tppubtype = {article}

}

@article{Friggeri2013,

title = {Pharmacophore assessment through 3-D QSAR: Evaluation of the predictive ability on new derivatives by the application on a series of antitubercular agents},

author = { Friggeri Laura and Ballante Flavio and Ragno Rino and Musmuca Ira and De Vita Daniela and Manetti Fabrizio and Biava Mariangela and Scipione Luigi and Di Santo Roberto and Costi Roberta and Feroci Marta and Tortorella Silvano},

editor = {American Chemical Society},

url = {http://pubs.acs.org/doi/abs/10.1021/ci400132q},

doi = {10.1021/ci400132q},

year  = {2013},

date = {2013-05-17},

journal = {Journal of Chemical Information and Modeling},

volume = {53},

number = {6},

pages = {1463-1474},

abstract = {Pharmacophoric mapping is a useful procedure to frame, especially when crystallographic receptor structures are unavailable as in ligand-based studies, the hypothetical site of interaction. In this study, 71 pyrrole derivatives active against M. tuberculosis were used to derive through a recent new 3-D QSAR protocol, 3-D QSAutogrid/R, several predictive 3-D QSAR models on compounds aligned by a previously reported pharmacophoric application. A final multiprobe (MP) 3-D QSAR model was then obtained configuring itself as a tool to derive pharmacophoric quantitative models. To stress the applicability of the described models, an external test set of unrelated and newly synthesized series of R-4-amino-3-isoxazolidinone derivatives found to be active at micromolar level against M. tuberculosis was used, and the predicted bioactivities were in good agreement with the experimental values. The 3-D QSAutogrid/R procedure proved to be able to correlate by a single multi-informative scenario the different activity molecular profiles thus confirming its usefulness in the rational drug design approach.},

keywords = {3-D QSAutogrid/R, 3D QSAR, Ligand-Based Design, MPGRS, Organic Chemistry, Pharmacophoric Model, PLS, Tuberculosis},

pubstate = {published},

tppubtype = {article}

}

@article{Ballante2012b,

title = {Comprehensive model of wild-type and mutant HIV-1 reverse transciptases},

author = { Ballante Flavio and Musmuca Ira and Garland R Marshall and Ragno Rino},

editor = {Springer Netherlands},

url = {http://link.springer.com/article/10.1007/s10822-012-9586-6#},

doi = {10.1007/s10822-012-9586-6},

year  = {2012},

date = {2012-07-26},

urldate = {2012-07-26},

journal = {Journal of Computer-Aided Molecular Design},

volume = {26},

number = {8},

pages = {907-919},

abstract = {An enhanced version of COMBINE that uses both ligand-based and structure-based alignment of ligands has been used to build a comprehensive 3-D QSAR model of wild-type HIV-1 reverse transcriptase and drug-resistant mutants. The COMBINEr model focused on 7 different RT enzymes complexed with just two HIV-RT inhibitors, niverapine (NVP) and efavirenz (EFV); therefore, 14 inhibitor/enzyme complexes comprised the training set. An external test set of chiral 2-(alkyl/aryl)amino-6-benzylpyrimidin-4(3H)-ones (DABOs) was used to test predictability. The COMBINEr model MC4, although developed using only two inhibitors, predicted the experimental activities of the test set with an acceptable average absolute error of prediction (0.89 pK i). Most notably, the model was able to correctly predict the right eudismic ratio for two R/S pairs of DABO derivatives. The enhanced COMBINEr approach was developed using only software freely available to academics.},

keywords = {3D QSAR, COMBINEr, DABO, HIV-1, HIV-RT, PLS},

pubstate = {published},

tppubtype = {article}

}

@article{Silvestri2012,

title = {Histone Deacetylase Inhibitors: Structure-Based Modeling and Isoform-Selectivity Prediction},

author = { Silvestri Laura and Ballante Flavio and Mai Antonello and Garland R, Marshall and Ragno Rino},

editor = {American Chemical Society},

url = {http://pubs.acs.org/doi/abs/10.1021/ci300160y},

doi = {10.1021/ci300160y},

year  = {2012},

date = {2012-07-19},

journal = {Journal of Chemical Information and Modeling},

volume = { 52},

number = {8},

pages = {2215-2235},

abstract = {An enhanced version of comparative binding energy (COMBINE) analysis, named COMBINEr, based on both ligand-based and structure-based alignments has been used to build several 3-D QSAR models for the eleven human zinc-based histone deacetylases (HDACs). When faced with an abundance of data from diverse structure–activity sources, choosing the best paradigm for an integrative analysis is difficult. A common example from studies on enzyme–inhibitors is the abundance of crystal structures characterized by diverse ligands complexed with different enzyme isoforms. A novel comprehensive tool for data mining on such inhomogeneous set of structure–activity data was developed based on the original approach of Ortiz, Gago, and Wade, and applied to predict HDAC inhibitors’ isoform selectivity. The COMBINEr approach (apart from the AMBER programs) has been developed to use only software freely available to academics.},

keywords = {3D QSAR, COMBINEr, HDAC, Molecular Docking, Molecular Modeling, PLS},

pubstate = {published},

tppubtype = {article}

}

@article{Ballante2012,

title = {3-D QSAutogrid/R: An Alternative Procedure To Build 3-D QSAR Models. Methodologies and Applications},

author = { Ballante Flavio and Ragno Rino},

editor = {American Chemical Society},

url = {http://pubs.acs.org/doi/abs/10.1021/ci300123x},

doi = {10.1021/ci300123x},

year  = {2012},

date = {2012-06-25},

journal = {Journal of Chemical Information and Modeling},

volume = {52},

number = {6},

pages = {1674},

abstract = {Since it first appeared in 1988 3-D QSAR has proved its potential in the field of drug design and activity prediction. Although thousands of citations now exist in 3-D QSAR, its development was rather slow with the majority of new 3-D QSAR applications just extensions of CoMFA. An alternative way to build 3-D QSAR models, based on an evolution of software, has been named 3-D QSAutogrid/R and has been developed to use only software freely available to academics. 3-D QSAutogrid/R covers all the main features of CoMFA and GRID/GOLPE with implementation by multiprobe/multiregion variable selection (MPGRS) that improves the simplification of interpretation of the 3-D QSAR map. The methodology is based on the integration of the molecular interaction fields as calculated by AutoGrid and the R statistical environment that can be easily coupled with many free graphical molecular interfaces such as UCSF-Chimera, AutoDock Tools, JMol, and others. The description of each R package is reported in detail, and, to assess its validity, 3-D QSAutogrid/R has been applied to three molecular data sets of which either CoMFA or GRID/GOLPE models were reported in order to compare the results. 3-D QSAutogrid/R has been used as the core engine to prepare more that 240 3-D QSAR models forming the very first 3-D QSAR server (www.3d-qsar.com) with its code freely available through R-Cran distribution.},

keywords = {3-D QSAutogrid/R, 3D QSAR, Chemoinformatics, Chemometrics, CoMFA, HCV NS5B, Molecular Modeling, MPGRS, Opioid-Receptor Antagonists, PLS},

pubstate = {published},

tppubtype = {article}

}

@article{Rotili2012,

title = {2-(Alkyl/aryl) amino-6-benzylpyrimidin-4 (3H)-ones as inhibitors of wild-type and mutant HIV-1: enantioselectivity studies},

author = { Rotili Dante and Samuele Alberta and Tarantino Domenico and Ragno Rino and Musmuca Ira and Ballante Flavio and Botta Giorgia and Morera Ludovica and Pierini Marco and Cirilli Roberto and Maxim B, Nawrozkij and Gonzalez Emmanuel and Clotet Bonaventura and Artico Marino and José A, Esté and Maga Giovanni and Mai Antonello},

editor = {American Chemical Society},

url = {https://pubs.acs.org/doi/10.1021/jm201308v},

doi = {10.1021/jm201308v},

year  = {2012},

date = {2012-03-26},

journal = {Journal of Medicinal Chemistry},

volume = {55},

number = {7},

pages = {3558-3562},

abstract = {The single enantiomers of two pyrimidine-based HIV-1 non-nucleoside reverse transcriptase inhibitors, 1 (MC1501) and 2 (MC2082), were tested in both cellular and enzyme assays. In general, the R forms were more potent than their S counterparts and racemates and (R)-2 was more efficient than (R)-1 and the reference compounds, with some exceptions. Interestingly, (R)-2 displayed a faster binding to K103N RT with respect to WT RT, while (R)-1 showed the opposite behavior.},

keywords = {Biochemistry, COMBINEr, DABO, HIV-1, Molecular Docking, Molecular Modeling, NNRTIs, Organic Chemistry},

pubstate = {published},

tppubtype = {article}

}