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Owono Owono L.C.,University of Yaounde I | Owono Owono L.C.,University of Douala | Owono Owono L.C.,HIGH-TECH | Ntie-Kang F.,University of Douala | And 12 more authors.
Molecular Informatics | Year: 2015

We report here new chemical structures of predicted nanomolar triclosan-based inhibitors (TCLs) of Mycobacterium tuberculosis enoyl-acyl carrier protein reductase (InhA) virtually proposed by computer-assisted molecular design. 3D models of InhA-TCL complexes were prepared by in situ modifications of the reference crystal structure (PDB entry 1P45) for a training set of 15 TCLs with known InhA inhibitory activities. A QSAR model was built leading to linear correlation between the calculated free energies of complexation (ΔΔGcom) and experimental values IC50exp: pIC50=-0.0657×ΔΔGcom+3.0502, R2=0.96. In addition, ligand-based quantitative pharmacophore model (PH4) was built from bound conformations of the training set compounds and confirmed the correlation between molecular models and observed activities: pIC50exp=0.8929×pIC50pre-0.441, R2=0.95. Structural information from both models helped us to propose new TCL analogues. A virtual library of TCLs with known predicted activities against enoyl-acyl carrier protein reductase of Plasmodium falciparum (PfENR) was evaluated, revealing dual target TCLs. Moreover, analysis of binding site interactions suggested enriching substitutions, which led to more potent TCLs with predicted pIC50pre as low as 7 nM. The computational approach, which used both free energy estimated from molecular modeling and 3D-QSAR pharmacophore model, was helpful in virtually proposing the dual-targeted drugs and provided valuable information for the design of novel potential antituberculotic agents. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. Source

Seneci P.,University of Milan | Fassina G.,Xeptagen S.p.A. | Frecer V.,Comenius University | Frecer V.,International Center for Applied Research and Sustainable Technology | And 2 more authors.
Nova Biotechnologica et Chimica | Year: 2014

The review will focus on the aspects of combinatorial chemistry and technologies that are more relevant in the modern pharmaceutical process. An historical, critical introduction is followed by three chapters, dealing with the use of combinatorial chemistry/high throughput synthesis in medicinal chemistry; the rational design of combinatorial libraries using computer-assisted combinatorial drug design; and the use of combinatorial technologies in biotechnology. The impact of "combinatorial thinking" in drug discovery in general, and in the examples reported in details, is critically discussed. Finally, an expert opinion on current and future trends in combinatorial chemistry and combinatorial technologies is provided. © University of SS. Cyril and Methodius. Source

Berti F.,University of Trieste | Frecer V.,Comenius University | Frecer V.,International Center for Applied Research and Sustainable Technology | Miertus S.,International Center for Applied Research and Sustainable Technology | Miertus S.,University of Trnava
Current Pharmaceutical Design | Year: 2014

Despite the fact that HIV-Protease is an over 20 years old target, computational approaches to rational design of its inhibitors still have a great potential to stimulate the synthesis of new compounds and the discovery of new, potent derivatives, ever capable to overcome the problem of drug resistance. This review deals with successful examples of inhibitors identified by computational approaches, rather than by knowledge-based design. Such methodologies include the development of energy and scoring functions, docking protocols, statistical models, virtual combinatorial chemistry. Computations addressing drug resistance, and the development of related models as the substrate envelope hypothesis are also reviewed. In some cases, the identified structures required the development of synthetic approaches in order to obtain the desired target molecules; several examples are reported. © 2014 Bentham Science Publishers. Source

Bonini C.,University of Basilicata | Chiummiento L.,University of Basilicata | Di Blasio N.,University of Basilicata | Funicello M.,University of Basilicata | And 10 more authors.
Bioorganic and Medicinal Chemistry | Year: 2014

New structurally simple indolic non peptidic HIV Protease inhibitors were synthesized from (S)-glycidol by regioselective methods. Following the concept of targeting the protein backbone, different substitution patterns were introduced onto the common stereodefined isopropanolamine core modifying the type of functional group on the indole, the position of the functional group on the indole and the type of the nitrogen containing group (sulfonamides or perhydroisoquinoline), alternatively. The systematic study on in vitro inhibition activity of such compounds confirmed the general beneficial effect of the 5-indolyl substituents in presence of arylsulfonamide moieties, which furnished activities in the micromolar range. Preliminary docking analysis allowed to identify several key features of the binding mode of such compounds to the protease. © 2014 Elsevier Ltd. All rights reserved. Source

Kouassi A.F.,University of Abobo AdjameNangui Abrogoua | Kone M.,HIGH-TECH | Keita M.,HIGH-TECH | Esmel A.,University of Abobo AdjameNangui Abrogoua | And 8 more authors.
International Journal of Molecular Sciences | Year: 2015

We have carried out a computational structure-based design of new potent pyrrolidine carboxamide (PCAMs) inhibitors of enoyl-acyl carrier protein reductase (InhA) of Mycobacterium tuberculosis (MTb). Three-dimensional (3D) models of InhA-PCAMx complexes were prepared by in situ modification of the crystal structure of InhA-PCAM1 (Protein Data Bank (PDB) entry code: 4U0J), the reference compound of a training set of 20 PCAMs with known experimental inhibitory potencies (IC50 exp). First, we built a gas phase quantitative structure-activity relationships (QSAR) model, linearly correlating the computed enthalpy of the InhA-PCAM complex formation and the IC50 exp. Further, taking into account the solvent effect and loss of inhibitor entropy upon enzyme binding led to a QSAR model with a superior linear correlation between computed Gibbs free energies (Γ ΓGcom) of InhA-PCAM complex formation and IC50 exp (pIC50 exp = -0.1552.Γ ΓDDGcom+ 5.0448, R2 = 0.94), which was further validated with a 3D-QSAR pharmacophore model generation (PH4). Structural information from the models guided us in designing of a virtual combinatorial library (VL) of more than 17 million PCAMs. The VL was adsorption, distribution, metabolism and excretion (ADME) focused and reduced down to 1.6 million drug like orally bioavailable analogues and PH4 in silico screened to identify new potent PCAMs with predicted IC50 pre reaching up to 5 nM. Combining molecular modeling and PH4 in silico screening of the VL resulted in the proposed novel potent antituberculotic agent candidates with favorable pharmacokinetic profiles. © 2015 by the authors; licensee MDPI, Basel, Switzerland. Source

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