Computational development of rubromycin-based lead compounds for HIV-1 reverse transcriptase inhibition

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1 Universidade Fernando Pessoa, Porto, Portugal
2 REQUIMTE, Universidade Fernando Pessoa, Porto, Portugal
DOI
10.7287/peerj.preprints.348v1
Published
Accepted
Subject Areas
Biochemistry, Biophysics, Computational Biology
Keywords
molecular dynamics, docking, computer-aided drug design
Copyright
© 2014 Silva et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
Cite this article
Silva PJ, Bernardo CEP. 2014. Computational development of rubromycin-based lead compounds for HIV-1 reverse transcriptase inhibition. PeerJ PrePrints 2:e348v1

Abstract

The binding of several rubromycin-based ligands to HIV1-reverse transcriptase was analyzed using molecular docking and molecular dynamics simulations. MM-PBSA analysis and examination of the trajectories allowed the identification of several promising compounds with predicted high affinity towards reverse transcriptase mutants which have proven resistant to current drugs. Important insights on the complex interplay of factors determining the ability of ligands to selectively target each mutant have been obtained.

Supplemental Information

Optimized geometries of all moleucles used in the docking stage of the work

DOI: 10.7287/peerj.preprints.348v1/supp-1

AutoDock 4.2.3 docking energies of all tested gamma-rubromycin derivatives

DOI: 10.7287/peerj.preprints.348v1/supp-2

Stable H-bonds between ligands and WT and mutated reverse transcriptase

DOI: 10.7287/peerj.preprints.348v1/supp-3

Energetic contributions to binding, for all mutants and ligands

DOI: 10.7287/peerj.preprints.348v1/supp-4

Correlations in the distances between K219, D67, L289 and N137 throughout the2nd half of the simulations of wild-type and mutant RT bound to ligand 46

DOI: 10.7287/peerj.preprints.348v1/supp-5

Correlations in the distances between K219, D67, L289 and N137 throughout the2nd half of the simulations of wild-type and mutant RT bound to ligand 36

DOI: 10.7287/peerj.preprints.348v1/supp-6

Correlations in the distances between K219, D67, L289 and N137 throughout the2nd half of the simulations of wild-type and mutant RT bound to ligand 37

DOI: 10.7287/peerj.preprints.348v1/supp-7

Correlations in the distances between K219, D67, L289 and N137 throughout the2nd half of the simulations of wild-type and mutant RT bound to ligand 38

DOI: 10.7287/peerj.preprints.348v1/supp-8

Correlations in the distances between K219, D67, L289 and N137 throughout the2nd half of the simulations of wild-type and mutant RT bound to ligand 13

DOI: 10.7287/peerj.preprints.348v1/supp-9

Correlations in the distances between K219, D67, L289 and N137 throughout the2nd half of the simulations of wild-type and mutant RT bound to ligand 45

DOI: 10.7287/peerj.preprints.348v1/supp-10

Correlations in the distances between K219, D67, L289 and N137 throughout the2nd half of the simulations of wild-type and mutant RT bound to ligand 27

DOI: 10.7287/peerj.preprints.348v1/supp-11

Correlations in the distances between K219, D67, L289 and N137 throughout the2nd half of the simulations of wild-type and mutant RT bound to gamma-rubromycin

DOI: 10.7287/peerj.preprints.348v1/supp-12

Correlations in the distances between K219, D67, L289 and N137 throughout the2nd half of the simulations of wild-type and mutant RT bound to rilpivirine

DOI: 10.7287/peerj.preprints.348v1/supp-13