Efficient Conformational Search Method for Peptides and Proteins:  Monte Carlo Minimization with an Adaptive Bias

2003 ◽  
Vol 107 (34) ◽  
pp. 9128-9131 ◽  
Author(s):  
S. Banu Ozkan ◽  
Hagai Meirovitch
Keyword(s):  
Monte Carlo ◽  
Search Method ◽  
Conformational Search

scholarly journals Study on conformational search of new thiosemicarbazone reagent and complexes with metal ions integrating semi-empirical quantum and molecular mechanics calculation and Monte Carlo simulation

2020 ◽  
Vol 129 (1D) ◽  
Author(s):  
Nguyen Minh Quang ◽  
Tran Xuan Mau ◽  
Pham Van Tat ◽  
Pham Nu Ngoc Han
Keyword(s):  
Monte Carlo ◽  
Molecular Mechanics ◽  
Molecular System ◽  
Search Method ◽  
Conformational Search ◽  
Monte Carlo Techniques ◽  
Molecular Mechanics Calculation ◽  
Semi Empirical ◽  
Complexes With Metal Ions ◽  
Initial Selection

In this study, the conformational analysis of the ML2 complexes of new thiosemicarbazone reagents with metal cations Cd2+, Ni2+, Cu2+, Hg2+, Pb2+, Mn2+ and Zn2+ is to find the conformations with the most suitable energy of the whole molecular system. The search method incorporates MM+ and PM3 calculations with Monte Carlo techniques using the Metropolis algorithm in terms of T = 298K to 473K. The initial selection conformation was done randomly after 15 repeatable conformations and 30 conformations rejected. The conformations are chosen to change by changing the torsional-dihedral angle at the position of the metal cation associated with the donor atoms N and S of thiosemicarbazone reagents. The search method is performed by random changes of the dihedral angles to create new structures and then minimize the energy for each of these angles using molecular mechanics. The unique low energy suitability is stored while high or duplicate energy structures are discarded.

A FAST AND EFFECTIVE CONFORMATIONAL SEARCH METHOD FOR PEPTIDES

2003 ◽  
Vol 14 (07) ◽  
pp. 985-991 ◽  
Author(s):  
HANDAN ARKIN ◽  
TARIK ÇELIK
Keyword(s):  
Monte Carlo ◽  
Hybrid Algorithm ◽  
Energy Landscape ◽  
Search Method ◽  
Low Energy ◽  
Conformational Search ◽  
Energy Landscape Paving ◽  
Low Energy Conformations

We propose a hybrid algorithm, which combines the features of the energy landscape paving (ELP) and Monte Carlo Minimization (MCM) methods. We have tested its performance in studying the low-energy conformations of the heptapeptide deltorphin.

Hardware Efficient Massive MIMO Detector Based on the Monte Carlo Tree Search Method

2017 ◽  
Vol 7 (4) ◽  
pp. 523-533 ◽  
Author(s):  
Jienan Chen ◽  
Chao Fei ◽  
Hao Lu ◽  
Gerald E. Sobelman ◽  
Jianhao Hu
Keyword(s):  
Monte Carlo ◽  
Massive Mimo ◽  
Search Method ◽  
Tree Search ◽  
Monte Carlo Tree Search

MULTIHYDRO and MONTEHYDRO: Conformational search and Monte Carlo calculation of solution properties of rigid or flexible bead models

2005 ◽  
Vol 116 (2) ◽  
pp. 121-128 ◽  
Author(s):  
J. Garcia de la Torre ◽  
A. Ortega ◽  
H.E. Perez Sanchez ◽  
J.G. Hernandez Cifre
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Calculation ◽  
Conformational Search ◽  
Solution Properties

scholarly journals Vehicle Routing Problem with Deadline and Stochastic Service Times: Case of the Ice Cream Industry in Santiago City of Chile

Mathematics ◽  
2021 ◽  
Vol 9 (21) ◽  
pp. 2750
Author(s):  
Sebastián Dávila ◽  
Miguel Alfaro ◽  
Guillermo Fuertes ◽  
Manuel Vargas ◽  
Mauricio Camargo
Keyword(s):  
Monte Carlo ◽  
Tabu Search ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Search Method ◽  
Superior Performance ◽  
Real Problem ◽  
Routing Problem ◽  
Chaotic Search ◽  
Number Of Customers

The research evaluates the vehicular routing problem for distributing refrigerated products. The mathematical model corresponds to the vehicle routing problem with hard time windows and a stochastic service time (VRPTW-ST) model applied in Santiago de Chile. For model optimization, we used tabu search, chaotic search and general algebraic modeling. The model’s objective function is to minimize the total distance traveled and the number of vehicles using stochastic waiting restrictions at the customers’ facilities. The experiments were implemented in ten scenarios by modifying the number of customers. Experiments were established with several customers that can be solved using the general algebraic modeling technique in order to validate the tabu search and the chaotic search methods. The study considered two algorithms modified with Monte Carlo (tabu search and chaotic search). Additionally, two modified algorithms, TSv2 and CSv2, were proposed to reduce execution time. These algorithms were modified by delaying the Monte Carlo procedure until the first set of sub-optimal routes were found. The results validate the metaheuristic chaotic search to solve the VRPTW-ST. The chaotic search method obtained a superior performance than the tabu search method when solving a real problem in a large city. Finally, the experiments demonstrated a direct relationship between the percentage of customers with stochastic waiting time and the model resolution time.

scholarly journals A Conformational Search Method for Protein Systems Using Genetic Crossover and Metropolis Criterion

2014 ◽  
Vol 487 ◽  
pp. 012003 ◽  
Author(s):  
Yoshitake Sakae ◽  
Tomoyuki Hiroyasu ◽  
Mitsunori Miki ◽  
Katsuya Ishii ◽  
Yuko Okamoto
Keyword(s):  
Search Method ◽  
Conformational Search ◽  
Metropolis Criterion
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