Hydrophobic docking: A proposed enhancement to molecular recognition techniques

In the classical procedures for predicting the structure of protein complexes two molecules are brought in contact at multiple relative positions, the extent of complementarity (geometric and/or energy) at the surface of contact is assessed at each position, and the best fits are retrieved. In view of the higher occurrence of hydrophobic groups at contact sites, their contribution results in more intermolecular atom–atom contacts per unit area for correct matches than for false positive fits. The hydrophobic groups are also potentially less flexible at the surface. Thus, from a practical point of view, a partial representation of the molecules based on hydrophobic groups should improve the quality of the results in finding molecular recognition sites, as compared to full representation. We tested this proposal by applying the idea to an existing geometric fit procedure and compared the results obtained with full vs. hydrophobic representations of molecules in known molecular complexes. The hydrophobic docking yielded distinctly higher signal-to-noise ratio so that the correct match is discriminated better from false positive fits. It appears that nonhydrophobic groups contribute more to false matches. The results are discussed in terms of their relevance to molecular recognition techniques as compared to energy calculations. © 1994 Wiley-Liss, Inc.     

APFA:Ameliorated Pathfinder Algorithm for Engineering Applications

Pathfinder algorithm(PFA)is a swarm intelligent optimization algorithm inspired by the collective activity behavior of swarm animals,imitating the leader in the population to guide followers in finding the best food source.This algorithm has the characteristics of a simple structure and high performance.However,PFA faces challenges such as insufficient popula-tion diversity and susceptibility to local optima due to its inability to effectively balance the exploration and exploitation capabilities.This paper proposes an Ameliorated Pathfinder Algorithm called APFA to solve complex engineering optimiza-tion problems.Firstly,a guidance mechanism based on multiple elite individuals is presented to enhance the global search capability of the algorithm.Secondly,to improve the exploration efficiency of the algorithm,the Logistic chaos mapping is introduced to help the algorithm find more high-quality potential solutions while avoiding the worst solutions.Thirdly,a comprehensive following strategy is designed to avoid the algorithm falling into local optima and further improve the convergence speed.These three strategies achieve an effective balance between exploration and exploitation overall,thus improving the optimization performance of the algorithm.In performance evaluation,APFA is validated by the CEC2022 benchmark test set and five engineering optimization problems,and compared with the state-of-the-art metaheuristic algo-rithms.The numerical experimental results demonstrated the superiority of APFA.     

Modelling and Characterization of Basalt/Vinyl Ester/SiC Micro-and Nano-hybrid Biocomposites Properties Using Novel ANN-GA Approach

Basalt fiber reinforcement in polymer matrix composites is becoming more and more popular because of its environmental friendliness and mechanical qualities that are comparable to those of synthetic fibers.Basalt fiber strengthened vinyl ester matrix polymeric composite with filler addition of nano-and micro-sized silicon carbide(SiC)element spanning from 2 weight percent to 10 weight percent was studied for its mechanical and wear properties.The application of Artificial Neu-ral Network(ANN)to correlate the filler addition composition for optimum mechanical properties is required due to the non-linear mechanical and tribological features of composites.The stuffing blend and composition of the composite are optimized using the hybrid model and Genetic Algorithm(GA)to maximize the mechanical and wear-resistant properties.The predicted and tested ANN-GA optimal values obtained for the composite combination had a tensile,flexural,impact resilience,hardness and wear properties of 202.93 MPa,501.67 MPa,3.460 J/s,43 HV and 0.196 g,respectively,for its optimum combination of filler and reinforcement.It can be noted that the nano-sized SiC filler particle enhances most of the properties of the composite which diversifies its applications.The predicted mechanical and wear values of the developed ANN-GA model were in closer agreement with the experimental values which validate the model.     

The new HNO donor, 1-nitrosocyclohexyl acetate, increases contractile force in normal and β-adrenergically desensitized ventricular myocytes

Haplotype, which is the sequence of SNPs in a specific chromosome, plays an important role in disease association studies. However, current sequencing techniques can detect the presence of SNP sites, but they cannot tell which copy of a pair of chromosomes the alleles belong to. Moreover, sequencing errors that occurred in sequencing SNP fragments make it difficult to determine a pair of haplotypes from SNP fragments. To help overcome this difficulty, the haplotype assembly problem is defined from the viewpoint of computation, and several models are suggested to tackle this problem. However, there are no freely available web-based tools to overcome this problem as far as we are aware. In this paper, we present a web-based application based on the genetic algorithm, named HapAssembler, for assembling a pair of haplotypes from SNP fragments. Numerical results on real biological data show that the correct rate of the proposed application in this paper is greater than 95% in most cases. HapAssembler is freely available at http://alex.chonnam.ac.kr/~drminor/hapHome.htm. Users can choose any model among four models for their purpose and determine haplotypes from their input data.     

Evaluation of mesh- and binary-based contour propagation methods in 4D thoracic radiotherapy treatments using patient 4D CT images

Based on four dimensional (4D) computed tomography (CT) images, mesh- and binary-based contour propagation algorithms for 4D thoracic radiotherapy treatments were evaluated. Gross tumor volumes (GTVs), lungs, hearts and spinal cords on the CT images at the end-exhale and end-inhale phases for six patients were delineated by the physician. All volumes of interest (VOIs) were automatically propagated from the end-exhale phase to the end-inhale phase using two propagation methods. The propagated VOIs were quantitatively compared with the VOIs contoured at the end-inhale phase by the physician using Dice Similarity Coefficient (DSC), Mean Slicewise Hausdorff Distance (MSHD), Center Of Mass (COM) displacement and volume difference. A two-sided Student’s t test was implemented to examine the significance of the differences between the results obtained from the two algorithms. For GTVs, statistically significant differences between the two algorithms were not observed. For all the other VOIs, the mesh-based method showed higher mean DSCs for the heart, left lung, right lung and spinal cord, lower mean MSHD for the spinal cord, lower mean COM displacement for the heart, and lower mean volume differences for the left lung, right lung and spinal cord with statistically significant differences than the binary-based method. The running time for propagation was approximately 3 s and 3 min for the mesh- and binary-based methods, respectively. Collectively, the mesh-based algorithm provides superiorities in running time and reliability for contour propagation in 4D radiotherapy.     

3D HUMAN MOTION RETRIEVAL BASED ON HUMAN HIERARCHICAL INDEX STRUCTURE

With the development and wide application of motion capture technology, the captured motion data sets are becoming larger and larger. For this reason, an efficient retrieval method for the motion database is very important. The retrieval method needs an appropriate indexing scheme and an effective similarity measure that can organize the existing motion data well. In this paper, we represent a human motion hierarchical index structure and adopt a nonlinear method to segment motion sequences. Based on this, we extract motion patterns and then we employ a fast similarity measure algorithm for motion pattern similarity computation to efficiently retrieve motion sequences. The experiment results show that the approach proposed in our paper is effective and efficient.