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Modelling: Big Data and Society Conference
A new PhD student publication
Dr. David Wright
For my PhD, I worked on a Molecular Dynamics Simulation of Drug Resistance in HIV-1 Protease and Reverse Transcriptase. The emergence of drug resistant strains of HIV represents a major challenge in the treatment of patients who contract the virus. I investigated the use of classical molecular dynamics to give quantitative and qualitative molecular insight into the causes of resistance in the two main drug targets in HIV, protease and reverse transcriptase.
We initially established a simulation and free energy analysis protocol for the study of resistance in protease. Focussing on the binding of the inhibitor lopinavir to a series of six mutants with increasing resistance we demonstrated that ensemble simulations exhibit significantly enhanced thermodynamic sampling over single long simulations. We achieved accurate and converged relative binding free energies, reproducible to within 0.5 kcal/mol. The experimentally derived ranking of the systems was reproduced with a correlation coefficient of 0.89 and a mean relative deviation from experiment of 0.9 kcal/mol.
Our protocol was then applied to investigate a patient derived viral
sequence for which contradictory resistance assessments for lopinavir
were obtained from existing clinical decision support systems (CDSS).
Mutations at only three locations (L10I, A71I/V and L90M) influenced the
ranking. Free energies were computed for HXB2 wildtype sequences
incorporating each mutation individually and all possible combinations,
along with the full patient sequence. Only in the case of the patient
sequence was any resistance observed. This observation suggests an
explanation for the discordance found using the CDSS. The effects on
drug binding of the mutations at positions 10, 71 and 90 appear to be
highly dependent on the background mutations present in the remainder
of the sequence.
In preparation for the extension of our simulation and free energy protocol to reverse transcriptase the impact of binding both natural DNA substrates and two non nucleoside reverse transcriptase inhibitor (NNRTI) class drugs on the dynamics of reverse transcriptase are investigated. Free energies of both inhibitors (efavirenz and neviripine) were determined which were seen to be independent of the subdomain motions of the protein observed during simulation. Preliminary calculations of the free energies for a set of NNRTI resistant mutants bound to efavirenz were also presented.
My next known destination is the Centre for Computational Science, Chemistry Department at University College of London, where I'll be a Research Assistant.
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