A real-time proximity querying algorithm for haptic-based molecular docking

Intermolecular binding underlies every 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 us to study the binding process. Haptic-based docking provides an immersive virtual docking environment where the user can interact with and guide the molecules to their binding pose. Moreover, it allows human perception, intuition and knowledge to assist and accelerate the docking process, and reduces incorrect binding poses. Crucial for interactive docking is the real-time calculation of interaction forces. For smooth and accurate haptic exploration and manipulation, force-feedback cues have to be updated at a rate of 1 kHz. Hence, force calculations must be performed within 1ms. To achieve this, modern haptic-based docking approaches often utilize pre-computed force grids and linear interpolation. However, such grids are time-consuming to pre-compute (especially for large molecules), memory hungry, can induce rough force transitions at cell boundaries and cannot be applied to flexible docking. Here we propose an efficient proximity querying method for computing intermolecular forces in real time. Our motivation is the eventual development of a haptic-based docking solution that can model molecular flexibility. Uniquely in a haptics application we use octrees to decompose the 3D search space in order to identify the set of interacting atoms within a cut-off distance. Force calculations are then performed on this set in real time. The implementation constructs the trees dynamically, and computes the interaction forces of large molecular structures (i.e. consisting of thousands of atoms) within haptic refresh rates. We have implemented this method in an immersive, haptic-based, rigid-body, molecular docking application called Haptimol_RD. The user can use the haptic device to orientate the molecules in space, sense the interaction forces on the device, and guide the molecules to their binding pose. Haptimol_RD is designed to run on consumer level hardware, i.e. there is no need for specialized/proprietary hardware

Molecular Docking on Azepine Derivatives as Potential Inhibitors for H1N1-A Computational Approach

Azepine are an important class of organic compounds. They are effective in a wide range of biological activity such as antifeedants, antidepressants, CNS stimulants, calcium channel blocker, antimicrobial and antifungal properties. In our continue efforts to search for a potent inhibitor for H1N1 virus using molecular docking. In this study, 15 azepine (ligands) derivatives were docked to the neuraminidase of A/Breving Mission/1/1918 H1N1 strain in complex with zanamivir (protein). The Cdocker energy was then calculated for these complexes (protein-ligand). Based on the calculation, the lowest Cdocker interaction energy was selected and potential inhibitors can be identified. Compounds MA4, MA7, MA8, MA10, MA11 and MA12 with promising Cdocker energy was expected to be very effective against the neuraminidase H1N1

A New Multi-Objective Approach for Molecular Docking Based on RMSD and Binding Energy

Ligand-protein docking is an optimization problem based on predicting the position of a ligand with the lowest binding energy in the active site of the receptor. Molecular docking problems are traditionally tackled with single-objective, as well as with multi-objective approaches, to minimize the binding energy. In this paper, we propose a novel multi-objective formulation that considers: the Root Mean Square Deviation (RMSD) difference in the coordinates of ligands and the binding (intermolecular) energy, as two objectives to evaluate the quality of the ligand-protein interactions. To determine the kind of Pareto front approximations that can be obtained, we have selected a set of representative multi-objective algorithms such as NSGA-II, SMPSO, GDE3, and MOEA/D. Their performances have been assessed by applying two main quality indicators intended to measure convergence and diversity of the fronts. In addition, a comparison with LGA, a reference single-objective evolutionary algorithm for molecular docking (AutoDock) is carried out. In general, SMPSO shows the best overall results in terms of energy and RMSD (value lower than 2A for successful docking results). This new multi-objective approach shows an improvement over the ligand-protein docking predictions that could be promising in in silico docking studies to select new anticancer compounds for therapeutic targets that are multidrug resistant.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Adaptive GPU-accelerated force calculation for interactive rigid molecular docking using haptics

Molecular docking systems model and simulate in silico the interactions of intermolecular binding. Haptics-assisted docking enables the user to interact with the simulation via their sense of touch but a stringent time constraint on the computation of forces is imposed due to the sensitivity of the human haptic system. To simulate high fidelity smooth and stable feedback the haptic feedback loop should run at rates of 500 Hz to 1 kHz. We present an adaptive force calculation approach that can be executed in parallel on a wide range of Graphics Processing Units (GPUs) for interactive haptics-assisted docking with wider applicability to molecular simulations. Prior to the interactive session either a regular grid or an octree is selected according to the available GPU memory to determine the set of interatomic interactions within a cutoff distance. The total force is then calculated from this set. The approach can achieve force updates in less than 2 ms for molecular structures comprising hundreds of thousands of atoms each, with performance improvements of up to 90 times the speed of current CPU-based force calculation approaches used in interactive docking. Furthermore, it overcomes several computational limitations of previous approaches such as pre-computed force grids, and could potentially be used to model receptor flexibility at haptic refresh rates

Kajian Pendekatan Penempatan Ligan Pada Protein Menggunakan Algoritma Genetika

Penempatan ligan pada protein atau molecule docking merupakan bidang komputasi yang sedang berkembang. Metode molecular docking adalah metode yang bermanfaat untuk mencari kombinasi interaksi protein dan  ligan serta menjadi dasar penemuan obat secara simulasi. Molecular docking yang digunakan adalah flexible docking dan jenis protein-ligand docking. Pendekatan algoritma genetika merupakan metode alternatif yang bisa digunakan untuk simulasi molecular docking. Hasil dari pendekatan algoritma genetika yaitu berupa penempatan posisi docking yang optimum. Penerapan algoritma genetika dalam docking tidak berlaku untuk semua protein dan ligan.  Dalam penerapannya tingkat homologi mempengaruhi keberhasilan dari docking

Molecular Docking Sianidin dan Peonidin sebagai Antiinflamasi pada Aterosklerosis secara In Silico

Atherosclerosis is a chronic inflammatory disease that begins with endothelial dysfunction resulting in plaque growth in the inner walls of the arteries. Endothelial dysfunction causes endothelial activates NF-?B resulting in a transcription of proinflammatory gene supporting the growth of atherosclerotic plaque. The purple sweet potato anthocyanin is a compound known to have activity inhibiting the inflammatory process. The major anthocyanins contained in purple sweetpotato are cyanidine and peonidine. The cyanidine and peonidin activity test was performed as antiinflammatory at atherosclerosis based on their interaction on NF-?B protein using molecular docking method in silico. The stages of this research are preparation of protein structure database of NF-?B, protein preparation using Chimera1.10.1 application, preparation and optimization of cyanidin and peonidin 3D structure using HyperChem8 application, and validation of molecular docking and docking method of cyanidin and peonidin on NF-?B protein using application Autodock4.2. The results showed that cyanidine and peonidine had affinity and formed a hydrogen bond with the NF-?B protein. The bond energy between cyanidine and peonidine with the NF-?B protein is -7.92 kcal/mol and -7.86 kcal/mol which together form the hydrogen bond with the LEU472 amino acid on the binding site equal to the native ligand. Cyanidin and peonidine have the potential of activity as antiatherosklerosis because it has an affinity with the NF-?B protein so that it prevents the inflammatory process in the formation of atherosclerotic plaque