Soft Computing Techiniques for the Protein Folding Problem on High Performance Computing Architectures

The protein-folding problem has been extensively studied during the last fifty years. The understanding of the dynamics of global shape of a protein and the influence on its biological function can help us to discover new and more effective drugs to deal with diseases of pharmacological relevance. Different computational approaches have been developed by different researchers in order to foresee the threedimensional arrangement of atoms of proteins from their sequences. However, the computational complexity of this problem makes mandatory the search for new models, novel algorithmic strategies and hardware platforms that provide solutions in a reasonable time frame. We present in this revision work the past and last tendencies regarding protein folding simulations from both perspectives; hardware and software. Of particular interest to us are both the use of inexact solutions to this computationally hard problem as well as which hardware platforms have been used for running this kind of Soft Computing techniques.This work is jointly supported by the FundaciónSéneca (Agencia Regional de Ciencia y Tecnología, Región de Murcia) under grants 15290/PI/2010 and 18946/JLI/13, by the Spanish MEC and European Commission FEDER under grant with reference TEC2012-37945-C02-02 and TIN2012-31345, by the Nils Coordinated Mobility under grant 012-ABEL-CM-2014A, in part financed by the European Regional Development Fund (ERDF). We also thank NVIDIA for hardware donation within UCAM GPU educational and research centers.Ingeniería, Industria y Construcció

Estimation of aquifer properties using electrical resistivity data in parts of Nsukka L.G.A., Enugu State

Communications in Physical Sciences Vol. 2. No. 1, 1-13. (2017) The study was carried out to investigate the variation of hydrodynamic parameters in parts of Nsukka Local Government Area, Enugu State, via vertical electrical sounding (VES) technique employing Schlumberger electrode configuration. The results from measured parameters were used in estimating other parameters such as hydraulic conductivity, transmissivity, porosity, formation factor and tortuosity. The third layer was delineated as aquiferous layer, with relative thickness compared to the overlying layers. The range of results obtained shows a high variation of these parameters, hydraulic conductivity ranges from 0.0989 to 0.5079m/day with an average of 0.3025m/day. Transmissivity has range between 6.5779 and 57.9546m2/day, with the average value of 18.7491m2/day; porosity ranged from 27.6863 to 29.3226%, and its average is 28.6524%. Formation factor and tortuosity range from 0.00043 to 0.00049 and 0.1129 to 0.1167 respectively. Their variation was clearly displayed on the contour maps, and this was attributed to changes in properties of subsurface, such as grain sizes, pore shapes and sizes. The result of this study will be a useful guide in exploration and abstraction of groundwater repositories in the study area &nbsp

Algorithms & experiments for the protein chain lattice fitting problem

ix, 47 leaves ; 29 cm.This study seeks to design algorithms that may be used to determine if a given lattice is a good approximation to a given rigid protein structure. Ideal lattice models discovered using our techniques may then be used in algorithms for protein folding and inverse protein folding. In this study we develop methods based on dynamic programming and branch and bound in an effort to identify “ideal” lattice models. To further our understanding of the concepts behind the methods we have utilized a simple cubic lattice for our analysis. The algorithms may be adapted to work on any lattice. We describe two algorithms. One for aligning the protein backbone to the lattice as a walk. This algorithm runs in polynomial time. The second algorithm for aligning a protein backbone as a path to the lattice. Both the algorithms seek to minimize the CRMS deviation of the alignment. The second problem was recently shown to be NP-Complete, hence it is highly unlikely that an efficient algorithm exists. The first algorithm gives a lower bound on the optimal solution to the second problem, and can be used in a branch and bound procedure. Further, we perform an empirical evaluation of our algorithm on proteins from the Protein Data Bank (PDB)

Computer simulations of protein folding

Computer simulations of biological systems provide novel data while both supporting and challenging traditional experimental methods. However, continued innovation is required to ensure that these technologies are able to work with increasingly complex systems. Coarse–grained approximations of protein structure have been studied using a lattice model designed to find low–energy conformations. A hydrogen–bonding term has been introduced. The ability to form β–sheet has been demonstrated, and the intricacies of reproducing the more complex α–helix on a lattice have been considered. An alternative strategy, that of better utilising computing power through the technique of milestoning, has shown good agreement with previous experimental and computational work. The increased efficiency allows significantly less extreme simulation conditions to be applied than those used in alternative simulation methods, and allows more simulation repeats. Finally, the principles of Least Action Dynamics have been employed to combine the two approaches described above. By splitting a simulation trajectory into a number of smaller components, and using the lattice model to optimise the path from a start structure to an end structure, it has been possible to efficiently generate dynamical information using an alternative method to traditional molecular dynamics

Conformation of Transmembrane Segments of a Protein by a Coarse Grain Model

The human voltage-gated proton channels (hHV1) are critical in many physiological functions and control proton conduction in the cell. This process is governed by the cooperative response of different transmembrane segments of the protein. It is believed that the two subunits of the C-terminal dimer provide independent proton channel pathways through the membrane where the conformations of both monomers and dimer are key for selective proton transport. Conformational response of these transmembrane segments of the protein hHV1 is studied by a coarse-grained model as a function of temperature where structural detail of a residue is ignored and its specificity is captured by its unique interaction. How residues of the protein hHv1 assemble or disperse as the temperature varies is addressed using a coarse-grained Monte Carlo simulation where a knowledge-based residue-residue interaction matrix is used as input in the Metropolis algorithm. Contact maps, mobility, radius of gyration, and structure factors, are examined as functions of temperature due to the efficiency of this model. Thermal response of the radius of gyration of this protein in the low-temperature regime decreases on increasing temperature in which structure becomes more compact by reduced entropy while in the high-temperature regime, the radius of gyration increases with temperature before reaching a steady state value. The scaling of structure factor S(q) provides an estimate of the effective dimension (D) of the protein chain which becomes globular conformation (D~3) with more connectedness in the low-temperature region and random coil (D~2) and then linear conformation (D~1) on increasing temperature further

A Dance with Protein Assemblies : Analysis, Structure Prediction, and Design

Protein assemblies are some of the most complex molecular machines in nature. They facilitate many cellular functions, from DNA replication to molecular motion, energy production, and even the production of other proteins. In a series of 3 papers, we analyzed the structure, developed structure prediction tools, and design tools, for different protein assemblies. Many of the studies were centered around viral protein capsids. Viral capsids are protein coats found inside viruses that contain and protect the viral genome. In one paper, we studied the interfaces of these capids and their energy landscapes. We found that they differ from regular homomers in terms of the amino acid composition and size, but not in the quality of interactions. This contradicts existing experimental and theoretical studies that suggest that the interactions are weak. We hypothesise that the occlusion by our models of electrostatic and entropic contributions might be at play. In another paper, we developed methods to predict large cubic symmetrical protein assemblies, such as viral capsids, from sequence. This method is based upon AlphaFold, a new AI tool that has revolutionized protein structure prediction. We found that we can predict up to 50% of the structures of these assemblies. The method can quickly elucidate the structure of many relevant proteins for humans, and for understanding structures relevant to disease, such as the structures of viral capsids. In the final paper, we developed tools to design capsid-like proteins called cages – structures that can be used for drug delivery and vaccine design. A fundamental problem in designing cage structures is achieving different architectures and low porosity, goals that are important for vaccine design and the delivery of small drug molecules. By explicitly modelling the shapes of the subunits in the cage and matching the shapes with proteins from structural databases, we find that we can create structures with many different sizes, shapes, and porosities - including low porosities. While waiting for experimental validation, the design strategy described in the paper must be extended, and more designs must be tested