1,720,990 research outputs found
Application of Medicinal Chemistry Methods on Different Classes of Drugs
Full text linkThe present doctoral thesis is the result of the work carried out during the three
years of my PhD scholarship at the Rome Center for Molecular Design laboratory
(RCMD, Department of Chemistry and Drug Technologies, Sapienza University of
Rome), under the supervision of Prof. Rino Ragno. The research activity was
focused mainly on the design, optimization and application of computational
strategies to derive quantitative structure-activity relationships (QSAR, 3-D
QSAR, and COMBINE) on different molecular classes of current interest, such as:
opioid receptor antagonists (OPAs), Hepatitis C Virus NS5B-Polymerase
Inhibitors (NS5B-NNIs), Hystone Deacetylase Inhibitors (HDACIs), Anti-
tubercular agents, vascular endothelial growth factor receptor-2 (VEGFR-2)
inhibitors, HSP90 inhibitors, HIV-1 reverse transcriptase inhibitors (NNRTIs),
Bovine Serum Amine Oxidase (BSAO) substrates, etc... Moreover two research
periods abroad were performed: the first framed in a LLP Erasmus program
collaboration, was conducted for six months at the Laboratoire d'Ingénierie et
Moléculaire Pharmacologique Biochimie (LIMBP) of the Université de Lorraine
Metz (France), directed by Prof. Gilbert Kirsch, and characterized by the
application of organic synthesis to obtain new thienopyrimidinone derivatives as
potential inhibitors of vascular endothelial growth factor receptor-2 (VEGFR-2);
the second took place, for three months, at the Department of Biochemistry and
Molecular Biophysics in Washington University School of Medicine in Saint Louis
(MO, USA), under the supervision of Prof. Garland R. Marshall, investigating the
activity profile of new Histone Deacetylases (HDACs) inhibitors by the application
of the Mobility Shift Assay Technology. Main purpose of this doctoral thesis is to highlight the activities carried out in the different research projects, the applied methodologies and the obtained results. The text starts describing those studies whose results were published in scientific journals (chapters I-VI): the author decided to omit some procedural details, completely reported in the published papers, that would make the text too long, tedious and redundant; therefore readers who want to delve these aspects can also refer to Chapter XII in which is possible to read the original papers; on the contrary for studies that have not yet been published, as those characterizing the Chapters VII and VIII, discussion is adequately detailed. Chapters IX and X report the scientific activities carried out in France and in USA respectively; Chapter XI summarizes all the scientific activities accomplished during the entire PhD course, whereas Chapter XII, as mentioned, contains the published articles."Progetti per Avvio alla Ricerca" prot. C26N12JZC
Histone deacetylase inhibitors: Comparative Binding Energy and QSAR studies for target selectivity prediction
No full text3-D QSAutogrid/R: An alternative procedure to build 3-D QSAR models. methodologies and applications
No full textSince 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. © 2012 American Chemical Society
Beta-secretase: quantitative structure-activity relationships (3-D QSARs) and evaluation of predictive ability
No full textR/AUTOGRID/ADT Combination As An Alternative To Build 3-D QSAR Models. Methodologies And Applications
No full textComprehensive model of wild-type and mutant HIV-1 reverse transciptases
No full textAn 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
Histone Deacetylase inhibitors. The development of a model for target-selectivity prediction
No full text
Histone Deacetylase Inhibitors. The Development of a Model for Target Prediction
No full textThe design of selective HDAC inhibitors is of interest in
development of molecular scapels to define the biological role
of these enzymes, and ultimately, less toxic drugs.
Comparative Binding Energy Analyses1 (COMBINE), were
conducted on HDAC complexes to highlight the discriminant
interactions and generate predictions of target selectivity.
HDAC/inhibitor complexes (93 total) compiled from 12
experimental (HDAC-2, -4, -7, -8) and homology modeled
(HDAC-1, -3, -5, -6A, -6B, -9, -10, -11) HDAC deacetylase
domains and 9 HDAC inhibitors for which the experimental
activities were available from a single paper. Experimental
ligand/HDAC complexes were retrieved from the PDB, while
the other were obtained from four homology-model automated
servers. Compound with unknown bound conformation were
directly modeled into the HDAC catalytic sites and the
resulting complexes were energy minimized using AMBER.
After minimization a multi-sequence alignment of enzymes
was performed by the Modeller2 program; the complexes were
submitted to a COMBINE-like procedure generated by the
combination of the AutoGrid3 program with the R4
environment language. Interaction energies were calculated on
a per-residue basis considering electrostatic (ELE), steric
(STE) and desolvation (DRY), while statistical PLS5-based
models were build and validated using in-house R scripts; this
allowed identification of those residues responsible for both
inhibitory activity and selectivity. A COMBINE model was
obtained showing r2, q2
LOO, q2
LSO-5 and SDEPCV of 0.77, 0.72,
0.72 and 0.87, respectively. To test the predictive ability of the
model, 10 HDAC inhibitors with enzyme-inhibition data for
different isoforms were used to build an external test set of 73
complexes; the activities and isoform selectivity of the
HDACs inhibitors were correctly predicted in most cases. To
our knowledge, this is the first general attempt to obtain a
structure-based approach to rationalize the development of
novel compounds endowed with both high potency and selectivit
- …
