Automated Molecular Simulation Based Binding Affinity Calculator for Ligand-Bound HIV-1 Proteases

Abstract

The successful application of high throughput molecular simulations to determine biochemical properties would be of great importance to the biomedical community if such simulations could be turned around in a clinically relevant timescale. An important example is the determination of antiretroviral inhibitor efficacy against varying strains of HIV through calculation of drug-protein binding affinities. We describe the Binding Affinity Calculator (BAC), a tool for the automated calculation of HIV-1 protease-ligand binding affinities. The tool employs fully atomistic molecular simulations alongside the well established molecular mechanics Poisson-Boltzmann solvent accessible surface area (MMPBSA) free energy methodology to enable the calculation of the binding free energy of several ligand-protease complexes, including all nine FDA approved inhibitors of HIV-1 protease and seven of the natural substrates cleaved by the protease. This enables the efficacy of these inhibitors to be ranked across several mutant strains of the protease relative to the wildtype. BAC is a tool that utilizes the power provided by a computational grid to automate all of the stages required to compute free energies of binding: model preparation, equilibration, simulation, postprocessing, and data-marshaling around the generally widely distributed compute resources utilized. Such automation enables the molecular dynamics methodology to be used in a high throughput manner not achievable by manual methods. This paper describes the architecture and workflow management of BAC and the function of each of its components. Given adequate compute resources, BAC can yield quantitative information regarding drug resistance at the molecular level within 96 h. Such a timescale is of direct clinical relevance and can assist in decision support for the assessment of patient-specific optimal drug treatment and the subsequent response to therapy for any given genotype.

HIV decision support: from molecule to man

“…For instance, to tackle problems such as the development of drug resistance to saquinavir, we envisage being able to simulate the probability of drug resistance with the binding affinity calculator (BAC; Sadiq et al 2008) and identify compensatory mutations in the CSs. These results could then be integrated with a fitness landscape.…”

Clinically driven design of multi-scale cancer models: the ContraCancrum project paradigm

“…The simulator, called the binding affinity calculator (BAC) [28], is an automated workflow tool that performs …”

Virtualizing access to scientific applications with the Application Hosting Environment

“…These include the EU funded ImmunoGrid project [6], where AHE has been used as a backend engine of a web portal to allow researchers to run simulations on federated, international resources, and the ViroLab [38] project, where a grid-based workflow built on top of the AHE automates the whole process of building, running and analyzing ensembles of molecular dynamics simulations to calculate the binding affinities of drugs to HIV target enzymes [39].…”

“…These can range from the mundane (such as transferring an application's input files to a grid resource and then executing it), to the more complicated (such as executing a series of interdependent tasks represented by a directed acyclic graph). While workflows have to date found more take up in high throughput scenarios which automate many single CPU processing tasks, the advent of large, petascale machines means workflow scenarios that execute parameter sweeps and ensembles of simulations [75] using MPI codes to exploit many processing cores are likely to become increasingly popular [39]. User interaction with workflow management systems ranges from command line clients using textual descriptions of the workflow through graphical web portals [57] to rich desktop clients which allow workflows to be composed visually, using drag and drop interfaces.…”