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Computational drug design strategies applied to the modelling of human immunodeficiency virus-1 reverse transcriptase inhibitors.

Santos LH, Ferreira RS, Caffarena ER - Mem. Inst. Oswaldo Cruz (2015)

Bottom Line: Two classes of RT inhibitors, the nucleoside RT inhibitors (NRTIs) and the nonnucleoside transcriptase inhibitors are prominently used in the highly active antiretroviral therapy in combination with other anti-HIV drugs.However, the rapid emergence of drug-resistant viral strains has limited the successful rate of the anti-HIV agents.Successful applications of these methodologies are also highlighted.

View Article: PubMed Central - PubMed

Affiliation: Fundação Oswaldo Cruz, Rio de Janeiro, RJ, Brasil.

ABSTRACT
Reverse transcriptase (RT) is a multifunctional enzyme in the human immunodeficiency virus (HIV)-1 life cycle and represents a primary target for drug discovery efforts against HIV-1 infection. Two classes of RT inhibitors, the nucleoside RT inhibitors (NRTIs) and the nonnucleoside transcriptase inhibitors are prominently used in the highly active antiretroviral therapy in combination with other anti-HIV drugs. However, the rapid emergence of drug-resistant viral strains has limited the successful rate of the anti-HIV agents. Computational methods are a significant part of the drug design process and indispensable to study drug resistance. In this review, recent advances in computer-aided drug design for the rational design of new compounds against HIV-1 RT using methods such as molecular docking, molecular dynamics, free energy calculations, quantitative structure-activity relationships, pharmacophore modelling and absorption, distribution, metabolism, excretion and toxicity prediction are discussed. Successful applications of these methodologies are also highlighted.

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compound 1 and compound 2; B: chlorine scan results performed in compound2; C, D: resulting compounds from free energy perturbation guided optimisation;EC50: half maximal effective concentration.
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f06: compound 1 and compound 2; B: chlorine scan results performed in compound2; C, D: resulting compounds from free energy perturbation guided optimisation;EC50: half maximal effective concentration.

Mentions: Zeevaart et al. (2008), following the earlysuccess of searching and optimising of a top scoring compound (1) from a screeninglibrary [described Barreiro et al. (2007a)], reported a series of FEP guided simulationswith analogues of the modified compound (2), with potencies in the 10-20 nM range. Topredict relative free energies of binding, the calculations were carried out in thecontext of FEP/MC statistical mechanics simulations. These calculations were performedusing the thermodynamic cycle theory, to interconvert two ligands unbound in water andbound to the protein. The systems were calculated using dual-topology sampling with 14windows or simple topology with 11 windows. In FEP calculations, a window refers to asimulation at one point along the mutation coordinate λ, which interconverts two ligandsas λ goes from 0-1; the free energy changes are computed for each window, correspondingto a forward and backward increment (the space between windows ∆λ) (Lu et al. 2004). When dual-topology is chosen, thesystem is prepared in a way that the two complete versions (initial state and finalstate) of the changing group coexist at every λ (Pearlman 1994). First, a so-called chlorine scan was performed, in which FEPcalculations were used to transform each hydrogen individually in the phenyl rings intochlorine, resulting in 10 structures to be converted into compound 2. These FEP resultsindicated the most promising places for chlorine atoms were at positions 3, 4, 2' and 6'(Fig. 6B). Further optimisation guided thesubstitution at position 4, resulted in compounds with activity (EC50) of 820nM (3), 310 nM (4) and 130 nM (5) (Fig. 6C). OtherFEP scans and ring modifications were made producing compounds with activity(EC50) of 22 nM (6), 13 nM (7) and 6 nM (8) (Fig. 6C), the last two found in a later study (Leung et al. 2010).


Computational drug design strategies applied to the modelling of human immunodeficiency virus-1 reverse transcriptase inhibitors.

Santos LH, Ferreira RS, Caffarena ER - Mem. Inst. Oswaldo Cruz (2015)

compound 1 and compound 2; B: chlorine scan results performed in compound2; C, D: resulting compounds from free energy perturbation guided optimisation;EC50: half maximal effective concentration.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4660614&req=5

f06: compound 1 and compound 2; B: chlorine scan results performed in compound2; C, D: resulting compounds from free energy perturbation guided optimisation;EC50: half maximal effective concentration.
Mentions: Zeevaart et al. (2008), following the earlysuccess of searching and optimising of a top scoring compound (1) from a screeninglibrary [described Barreiro et al. (2007a)], reported a series of FEP guided simulationswith analogues of the modified compound (2), with potencies in the 10-20 nM range. Topredict relative free energies of binding, the calculations were carried out in thecontext of FEP/MC statistical mechanics simulations. These calculations were performedusing the thermodynamic cycle theory, to interconvert two ligands unbound in water andbound to the protein. The systems were calculated using dual-topology sampling with 14windows or simple topology with 11 windows. In FEP calculations, a window refers to asimulation at one point along the mutation coordinate λ, which interconverts two ligandsas λ goes from 0-1; the free energy changes are computed for each window, correspondingto a forward and backward increment (the space between windows ∆λ) (Lu et al. 2004). When dual-topology is chosen, thesystem is prepared in a way that the two complete versions (initial state and finalstate) of the changing group coexist at every λ (Pearlman 1994). First, a so-called chlorine scan was performed, in which FEPcalculations were used to transform each hydrogen individually in the phenyl rings intochlorine, resulting in 10 structures to be converted into compound 2. These FEP resultsindicated the most promising places for chlorine atoms were at positions 3, 4, 2' and 6'(Fig. 6B). Further optimisation guided thesubstitution at position 4, resulted in compounds with activity (EC50) of 820nM (3), 310 nM (4) and 130 nM (5) (Fig. 6C). OtherFEP scans and ring modifications were made producing compounds with activity(EC50) of 22 nM (6), 13 nM (7) and 6 nM (8) (Fig. 6C), the last two found in a later study (Leung et al. 2010).

Bottom Line: Two classes of RT inhibitors, the nucleoside RT inhibitors (NRTIs) and the nonnucleoside transcriptase inhibitors are prominently used in the highly active antiretroviral therapy in combination with other anti-HIV drugs.However, the rapid emergence of drug-resistant viral strains has limited the successful rate of the anti-HIV agents.Successful applications of these methodologies are also highlighted.

View Article: PubMed Central - PubMed

Affiliation: Fundação Oswaldo Cruz, Rio de Janeiro, RJ, Brasil.

ABSTRACT
Reverse transcriptase (RT) is a multifunctional enzyme in the human immunodeficiency virus (HIV)-1 life cycle and represents a primary target for drug discovery efforts against HIV-1 infection. Two classes of RT inhibitors, the nucleoside RT inhibitors (NRTIs) and the nonnucleoside transcriptase inhibitors are prominently used in the highly active antiretroviral therapy in combination with other anti-HIV drugs. However, the rapid emergence of drug-resistant viral strains has limited the successful rate of the anti-HIV agents. Computational methods are a significant part of the drug design process and indispensable to study drug resistance. In this review, recent advances in computer-aided drug design for the rational design of new compounds against HIV-1 RT using methods such as molecular docking, molecular dynamics, free energy calculations, quantitative structure-activity relationships, pharmacophore modelling and absorption, distribution, metabolism, excretion and toxicity prediction are discussed. Successful applications of these methodologies are also highlighted.

Show MeSH
Related in: MedlinePlus