Simulating molecular docking with haptics

Intermolecular binding underlies various metabolic and regulatory processes of the cell, and the therapeutic and pharmacological properties of drugs. Molecular docking systems model and simulate these interactions in silico and allow the study of the binding process. In molecular docking, haptics enables the user to sense the interaction forces and intervene cognitively in the docking process. Haptics-assisted docking systems provide an immersive virtual docking environment where the user can interact with the molecules, feel the interaction forces using their sense of touch, identify visually the binding site, and guide the molecules to their binding pose. Despite a forty-year research e�ort however, the docking community has been slow to adopt this technology. Proprietary, unreleased software, expensive haptic hardware and limits on processing power are the main reasons for this. Another signi�cant factor is the size of the molecules simulated, limited to small molecules. The focus of the research described in this thesis is the development of an interactive haptics-assisted docking application that addresses the above issues, and enables the rigid docking of very large biomolecules and the study of the underlying interactions. Novel methods for computing the interaction forces of binding on the CPU and GPU, in real-time, have been developed. The force calculation methods proposed here overcome several computational limitations of previous approaches, such as precomputed force grids, and could potentially be used to model molecular exibility at haptic refresh rates. Methods for force scaling, multipoint collision response, and haptic navigation are also reported that address newfound issues, particular to the interactive docking of large systems, e.g. force stability at molecular collision. The i ii result is a haptics-assisted docking application, Haptimol RD, that runs on relatively inexpensive consumer level hardware, (i.e. there is no need for specialized/proprietary hardware)

Interactive molecular docking with haptics and advanced graphics

Biomolecular interactions underpin many of the processes that make up life. Molecular docking is the study of these interactions in silico. Interactive docking applications put the user in control of the docking process, allowing them to use their knowledge and intuition to determine how molecules bind together. Interactive molecular docking applications often use haptic devices as a method of controlling the docking process. These devices allow the user to easily manipulate the structures in 3D space, whilst feeling the forces that occur in response to their manipulations. As a result of the force refresh rate requirements of haptic devices, haptic assisted docking applications are often limited, in that they model the interacting proteins as rigid, use low fidelity visualisations or require expensive propriety equipment to use. The research in this thesis aims to address some of these limitations. Firstly, the development of a visualisation algorithm capable of rendering a depiction of a deforming protein at an interactive refresh rate, with per-pixel shadows and ambient occlusion, is discussed. Then, a novel approach to modelling molecular flexibility whilst maintaining a stable haptic refresh rate is developed. Together these algorithms are presented within Haptimol FlexiDock, the first haptic-assisted molecular docking application to support receptor flexibility with high fidelity graphics, whilst also maintaining interactive refresh rates on both the haptic device and visual display. Using Haptimol FlexiDock, docking experiments were performed between two protein-ligand pairs: Maltodextrin Binding Protein and Maltose, and glutamine Binding Protein and Glucose. When the ligand was placed in its approximate binding site, the direction of over 80% of the intra-molecular movement aligned with that seen in the experimental structures. Furthermore, over 50% of the expected backbone motion was present in the structures generated with FlexiDock. Calculating the deformation of a biomolecule in real time, whilst maintaining an interactive refresh rate on the haptic device (> 500Hz) is a breakthrough in the field of interactive molecular docking, as, previous approaches either model protein flexibility, but fail to achieve the required haptic refresh rate, or do not consider biomolecular flexibility at all

Graphics Processing Unit Accelerated Coarse-Grained Protein-Protein Docking

Graphics processing unit (GPU) architectures are increasingly used for general purpose computing, providing the means to migrate algorithms from the SISD paradigm, synonymous with CPU architectures, to the SIMD paradigm. Generally programmable commodity multi-core hardware can result in significant speed-ups for migrated codes. Because of their computational complexity, molecular simulations in particular stand to benefit from GPU acceleration. Coarse-grained molecular models provide reduced complexity when compared to the traditional, computationally expensive, all-atom models. However, while coarse-grained models are much less computationally expensive than the all-atom approach, the pairwise energy calculations required at each iteration of the algorithm continue to cause a computational bottleneck for a serial implementation. In this work, we describe a GPU implementation of the Kim-Hummer coarse-grained model for protein docking simulations, using a Replica Exchange Monte-Carlo (REMC) method. Our highly parallel implementation vastly increases the size- and time scales accessible to molecular simulation. We describe in detail the complex process of migrating the algorithm to a GPU as well as the effect of various GPU approaches and optimisations on algorithm speed-up. Our benchmarking and profiling shows that the GPU implementation scales very favourably compared to a CPU implementation. Small reference simulations benefit from a modest speedup of between 4 to 10 times. However, large simulations, containing many thousands of residues, benefit from asynchronous GPU acceleration to a far greater degree and exhibit speed-ups of up to 1400 times. We demonstrate the utility of our system on some model problems. We investigate the effects of macromolecular crowding, using a repulsive crowder model, finding our results to agree with those predicted by scaled particle theory. We also perform initial studies into the simulation of viral capsids assembly, demonstrating the crude assembly of capsid pieces into a small fragment. This is the first implementation of REMC docking on a GPU, and the effectuate speed-ups alter the tractability of large scale simulations: simulations that otherwise require months or years can be performed in days or weeks using a GPU

NASA Tech Briefs, December 1989

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