ArticleBiophysical journal2008
A quantum mechanic/molecular mechanic study of the wild-type and N155S mutant HIV-1 integrase complexed with diketo acid.
Article in Biophysical journal, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Article
- Quantum mechanics implementation in drug-design workflows: does it really help?Drug design, development and therapy · 2017Review
- Homology modeling, molecular dynamics and QM/MM study of the regulatory protein PhoP from Corynebacterium pseudotuberculosis.Journal of molecular modeling · 2012Article
- Computational analysis of aspartic protease plasmepsin II complexed with EH58 inhibitor: a QM/MM MD study.Journal of molecular modeling · 2011Article
- Binding modes of diketo-acid inhibitors of HIV-1 integrase: a comparative molecular dynamics simulation study.Journal of molecular graphics & modelling · 2011Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Integrase (IN) is one of the three human immunodeficiency virus type 1 (HIV-1) enzymes essential for effective viral replication. Recently, mutation studies have been reported that have shown that a certain degree of viral resistance to diketo acids (DKAs) appears when some amino acid residues of the IN active site are mutated. Mutations represent a fascinating experimental challenge, and we invite theoretical simulations for the disclosure of still unexplored features of enzyme reactions. The aim of this work is to understand the molecular mechanisms of HIV-1 IN drug resistance, which will be useful for designing anti-HIV inhibitors with unique resistance profiles. In this study, we use molecular dynamics simulations, within the hybrid quantum mechanics/molecular mechanics (QM/MM) approach, to determine the protein-ligand interaction energy for wild-type and N155S mutant HIV-1 IN, both complexed with a DKA. This hybrid methodology has the advantage of the inclusion of quantum effects such as ligand polarization upon binding, which can be very important when highly polarizable groups are embedded in anisotropic environments, for example in metal-containing active sites. Furthermore, an energy terms decomposition analysis was performed to determine contributions of individual residues to the enzyme-inhibitor interactions. The results reveal that there is a strong interaction between the Lys-159, Lys-156, and Asn-155 residues and Mg(2+) cation and the DKA inhibitor. Our calculations show that the binding energy is higher in wild-type than in the N155S mutant, in accordance with the experimental results. The role of the mutated residue has thus been checked as maintaining the structure of the ternary complex formed by the protein, the Mg(2+) cation, and the inhibitor. These results might be useful to design compounds with more interesting anti-HIV-1 IN activity on the basis of its three-dimensional structure.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.