Hassan Khachfe

Evolutionary Algorithm for Protein Structure Prediction

A protein is characterized by its 3D structure, which defines its biological function. The protein structure prediction problem has real-world significance where several diseases are associated with the wrong folding of proteins. Predicting protein structures is computationally intractable. In this paper, we present an improved genetic algorithm (GA) for predicting 3D structures of proteins based on the hydrophobic polar model. We evaluate our proposed GA on a number of protein sequences. The generated protein structures demonstrate improvement over previously published results.

Particle swarm optimization approach for protein structure prediction in the 3D HP model

The primary structure of proteins consists of a linear chain of amino acids that can vary in length. Proteins fold, under the influence of several chemical and physical factors, into their 3D structures, which determine their biological functions and properties. Misfolding occurs when the protein folds into a 3D structure that does not represent its native structure, which can lead to diseases. Due to the importance of this problem and since laboratory techniques are not always feasible, computational methods for characterizing protein structures have been proposed. In this paper, we present a particle swarm optimization (PSO) based algorithm for predicting protein structures in the 3D hydrophobic polar model. Starting from a small set of candidate solutions, our algorithm efficiently explores the search space and returns 3D protein structures with minimal energy. To test our algorithm, we used two sets of benchmark sequences of different lengths and compared our results to published results. Our algorithm performs better than previous algorithms by finding lower energy structures or by performing fewer numbers of energy evaluations.

Protein structure prediction in the 3D HP model

Proteins are initially linear chains of amino acids that fold, under the influence of several chemical and physical factors, into their 3-dimensional structures. Due to the importance of this problem and since laboratory techniques are not always feasible, computational methods for characterizing protein structures have been proposed. In this paper, we present a Particle Swarm Optimization (PSO) based algorithm for predicting protein structures in the 3D HP model. Starting from a small set of potential solutions, our algorithm efficiently explores the search space of candidate solutions and returns 3D protein structures with minimal energy. To test our algorithm, we use two sets of benchmark sequences of different lengths. It is found that the results of the PSO algorithm are better than those of previous algorithms.

Enhanced Genetic Algorithm for Protein Structure Prediction based on the HP Model

Proteins are organic compounds that are made up of combinations of amino acids and are of different types and roles in living organisms. Initially a protein is a linear chain of amino acids, ranging from a few tens up to thousands of amino acids. Proteins fold, under the influence of several chemical and physical factors, into their 3-dimensional structures which determine their biological functions and properties. Misfolding occurs when the protein folds into a 3D structure that does not represent its correct native structure, which can lead to many diseases such as Alzheimer, several types of cancer, etc... (Prusiner, 1998). Hence, predicting the native structure of a protein from its primary sequence is an important and challenging task especially that this protein structure prediction (PSP) problem is computationally intractable. The primary structure of a protein is a linear sequence of amino acids connected together via peptide bonds. Proteins fold due to hydrophobic effect, Vander Waals interactions, electrostatic forces, and Hydrogen bonding (Setubal & Meidanis, 1997). The secondary structures are three-dimensional structures characterized by repeating bonding patterns of ┙-helices and ┚-strands. Proteins further fold into a tertiary structure forming a bundle of secondary structures and loops. Furthermore, the aggregation of tertiary structure regions of separate protein sequences leads to quaternary structures. These structures are depicted in Fig. 1 (Rylance, 2004). Computational approaches for PSP can be classified as: homology modeling, threading, and ab initio methods (Floudas, 2007). Approaches in the first two groups use known protein structures from protein data banks (PDB). Approaches in the third group solely rely on the given amino acid sequence. A survey of PSP approaches appeared in Sikder and Zomaya (2005). Homology modeling uses sequences of known structures in the PDB to align with the target protein’s sequence for which the 3D structure is to be predicted (Kopp & Schwede, 2004; Notredame, 2002; Pandit et al., 2006). Threading is similar to homology modeling. But, instead of finding similar sequences to deduce the native conformation of the target protein, threading assumes that the target structure is similar to another existing structure, which should be searched for (Lathrop et al., 1998; Jones 1998; Skolnick et al., 2004). The threading of a sequence to a fold is evaluated by either environment-based or knowledge-based mean-force-potentials derived from the PDB.

From plastic to silicone: the novelties in porous polymer fabrications

Porous polymers are gaining increased interest in several areas due, in great part, to their large surface area and unique physiochemical properties. Porous polymers are conventionally manufactured using specific processes related to the chemical structure of each polymer. With the wide variety of porous polymers that have been designed, fabricated, and tested to date, this review aims to provide an overview of the advances and recent progress in the preparation processes and fabrication techniques. A detailed comparison between these techniques is also provided. Some of these techniques offer the advantage of controlling the porosity and the possibility to obtain porous 3D polymers. A new generic fabrication process that can be applied to all liquid polymers to texture their outer surfaces with a desired porosity is also presented. The proposed process, which is based on two micromolding steps, offers flexibility in terms of tailoring the texture of the final polymer by simply using porous silicon templates with different pore sizes and configurations. The anticipated process was successfully implemented to texture polyethyl hydrosiloxane (PMHS) using porous silicon and polymethyl methacrylate (PMMA) scaffolds.

Evolutionary algorithm for protein structure prediction

A protein is characterized by its 3D structure,which defines its biological function. In this paper, we present a scatter search algorithm for predicting 3D structures of proteins based on torsion angles representation. Given the protein¿s sequence of amino acids, our algorithm produces a 3D structure that aims to minimize the energy function associated with the structure. Scatter search is an evolutionary approach that is based on a population of candidate solutions. We evaluate our algorithm on proteins taken from a protein data bank. The results show that our algorithm is able to produce 3D structures with good sub-optimal energy values. Also, the root mean square deviations of these structures from the reference proteins are promising within limits imposed by the assumptions made.

Tremor Reduction at the Palm of a Parkinson’s Patient Using Dynamic Vibration Absorber

Parkinson’s patients suffer from severe tremor due to an abnormality in their central oscillator. Medications used to decrease involuntary antagonistic muscles contraction can threaten their life. However, mechanical vibration absorbers can be used as an alternative treatment. The objective of this study is to provide a dynamic modeling of the human hand that describes the biodynamic response of Parkinson’s patients and to design an effective tuned vibration absorber able to suppress their pathological tremor. The hand is modeled as a three degrees-of-freedom (DOF) system describing the flexion motion at the proximal joints on the horizontal plane. Resting tremor is modeled as dual harmonic excitation due to shoulder and elbow muscle activation operating at resonance frequencies. The performance of the single dynamic vibration absorber (DVA) is studied when attached to the forearm and compared with the dual DVA tuned at both excitation frequencies. Equations of motion are derived and solved using the complex transfer function of the non-Lagrangian system. The absorber’s systems are designed as a stainless steel alloy cantilevered beam with an attached copper mass. The dual DVA was the most efficient absorber which reduces 98.3%–99.5%, 97.0%–97.3% and 97.4%–97.5% of the Parkinson’s tremor amplitude at the shoulder, elbow and wrist joint.

Scatter Search algorithm for Protein Structure Prediction

In this paper, we present a Scatter Search (SS) algorithm for predicting 3D structures of proteins based on torsion angles representation. Given the proteins sequence of Amino Acids (AAs), our algorithm produces a 3D structure that aims to minimise the energy function associated with the structure. SS is an evolutionary approach that is based on a population of candidate solutions. These candidates undergo evolutionary operations that combine search intensification and diversification over a number of iterations. We evaluate our algorithm on three proteins taken from a Protein Data Bank (PDB). The results show that our algorithm is able to produce 3D structures with good sub-optimal energy values. Also, the Root Mean Square Deviations (RMSD) of these structures from the reference proteins are promising within limits imposed by the assumptions made.

Biomechanical treatment for rest tremor of Parkinson's patient

Vibration absorbers are effective devices used to reduce the unwanted motion of a vibrating system. It is recently used to reduce the involuntary tremor of a Parkinsons patient. The absorber can be attached to the forearm of the patient hand. Such system can be excited at resonance frequencies reflecting the resting tremor due to the shoulder and elbow muscles activation. Two single absorbers are designed and tested numerically in reducing the involuntary tremor: the conventional absorber having its spring and damper connected in parallel and the elastic-damper absorber having its spring and damper connected in series. Both absorbers are designed to satisfy the tuning conditions at the fundamental frequency of the primary system with the same total mass. The conventional absorber causes 75.5-97.4%, 11.1-48.0% and 41.2-49.7% reduction at the shoulder, elbow and the wrist joints, respectively. However, the elastic-damper absorber causes 74.0-78.7%, 5.0-35.0% and 29.3- 45.8% at the same positions, respectively. The elastic-damper absorber can cause this reduction with a device of shorter length.

Passive vibration absorber for tremor in hand of parkinsonian patients: Tuned vibration absorber for rest tremor

Parkinsons disease is characterized by involuntary movement of body parts resulting from antagonistic muscle contractions. In this paper, an effective passive vibration absorber is modeled to control the involuntary pathological rest tremor in the right hand of Parkinsons disease patient. The three-degree-of-freedom dynamic hand model capable to describe the flexion-extension planar motion at shoulder, elbow, and wrist joints in horizontal plane is designed. The passive tuned vibration absorber is modeled to suppress flexion motion of shoulder, elbow and wrist joints. Active inputs producing motion are considered at shoulder and elbow joints, and driven at resonance frequencies. The equations of motion for the dynamically coupled modeled hand system are derived. The responses are represented in time and frequency domains using the complex transfer function method. Optimum position of the absorber on the forearm is determined in terms of its effectiveness in reducing tremors amplitude.