Contributions to the analysis of proteins

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 131-145).Proteins are essential to organisms and play a central role in almost every biological process. The analysis of the conformational dynamics and mechanics of proteins using numerical methods, such as normal mode analysis (NMA), provides insight into their functional mechanisms. However, despite the fact that much effort has been focused on improving NMA over the last few decades, the analysis of large-scale protein motions is still infeasible due to computational limitations. In this work, first, we identify the usefulness and effectiveness of the subspace iteration (SSI) procedure, otherwise widely used in structural engineering, for the analysis of proteins. We also develop a novel technique for the selection of iteration vectors in protein NMA, which significantly increases the effectiveness of the method. The SSI procedure also lends itself naturally to efficient NMA of multiple neighboring macromolecular conformations, as demonstrated in a conformational change pathway analysis of adenylate kinase. Next, we present a new algorithm to account for the effects of solvent-damping on slow protein conformational dynamics. The algorithm proves to be an effective approach to calculating the diffusion coefficients of proteins with various molecular weights, as well as their Langevin modes and corresponding relaxation times, as demonstrated for the small molecule crambin. Finally, the structure of Homo sapiens fascin-1, an actin-binding protein that is present predominantly in filopodia, is examined and described in detail. Application of a sequence conservation analysis to the protein indicates highly conserved surface patches near the putative actin-binding domains of fascin. A novel conformational dynamics analysis suggests that these domains are coupled via an allosteric mechanism that may have important functional implications for F-actin bundling by fascin.by Reza Sharifi Sedeh.Ph.D

Public-Private-People Partnerships (4P) for Improving the Response to COVID-19 in Iran

Public-Private-People Partnership is a significant element in disaster response. COVID-19 as a pandemic has been the worst disaster in the last decades in Iran in terms of exposure and magnitude. In order to respond effectively, the Iranian government needs an extra capacity which may be provided by the private sector and people. This study aims to collect evidences of Public-Private-People partnerships pertaining to COVID-19 response in Iran from February to April 2020. Partnership case studies are classified into three categories as follows: 1) Public-private partnerships; 2) public-people partnerships; and 3) private-people partnerships. It was found that the Iranian government has removed or diminished some of the barriers to cooperation. There was also more cooperation between the people, the private sector, and the public sector than during normal times (vs disasters). People participated in the response procedure through some associations or groups, such as religious and ethnic communities, as well as through non-governmental organizations. It is showed that 4P is vital in disasters response and in particular to epidemics. The government can be more active in partnerships with private sector, and people in emergencies such as COVID-19 Pandemic. Enhancing social capital, institutionalization, and developing required infrastructures by the government will improve public-private partnerships

REDUCING HARMFUL EFFECTS OF ROAD EXCITATIONS ON HUMAN HEALTH BY DESIGNING CAR ACTIVE SUSPENSION SYSTEMS

Nowadays people are strongly dependent on cars for doing their tasks, but they usually are not aware of hazards which are awaiting them. For instance, since people travel with cars, their human bodies undergo in fatigue, restlessness, and sometimes health problems. Human body reaction under external vibration depends on the amplitude, frequency, and acceleration of the applied external excitation. These limitations which are usually announced by the bureau of standards imply the necessity of control of amplitude, vibration, frequency, and acceleration received by human body due to cars passing humps and bumps. In this paper, a quarter car model with active suspension system is considered and three control approaches namely optimal control, fuzzy control, and optimal neural network control (ONNC) are applied. Moreover, the performance of different controllers is compared. Findings indicate optimal neural network control leads to smooth ride with optimal amplitude and acceleration transformation, while keeping the holding force at minimum variation. Therefore, it can eliminate undesirable effects of road excitations on human health in the best way

Dynamics of High Molecular Weight Macromolecular Assemblies

Solvent-damped, thermally activated motions of high molecular weight proteins and nucleic acid assemblies are key to understanding and controlling their functions and activities. The finite element method is a well-established approach to analyzing protein conformational fluctuations that are not accessible to all-atom representations. However, like conventional all-atom normal mode analysis, the finite element method has previously been used only to model protein dynamics in vacuum. Here, we extend the finite element based modeling approach to incorporate solvent damping for proteins and nucleic acid assemblies to compute non-equilibrium conformational properties. The proposed model is computationally effective for calculating translational and rotational diffusion coefficients in addition to dynamical motions in solvent, as demonstrated for Taq polymerase and several nanometer-scale DNA assemblies. A distinct advantage of the finite element-based approach is that computational cost does not increase with increasing molecular weight, rendering the procedure applicable to long time-scale structure-based simulations of high molecular weight assemblies including chaperones, molecular motors, and nucleic acid nanostructures

Shape optimization of segmental porous baffles for enhanced thermo-hydraulic performance of shell-and-tube heat exchanger

This study presents the development and evaluation of a novel shell-and-tube heat exchanger (STHX) design with segmental porous baffles. Computational fluid dynamics (CFD) in combination with machine learning tools are utilized to investigate the thermo-hydraulic impacts of segmental porous baffles on shell side flow of a STHX. Three geometric parameters (number of baffles, baffle angle, and baffle thickness) of these baffles, which are placed inside the STHX, are selected to perform the parametric study and multi-objective optimization. Higher number of baffles are beneficial to increase the rate of heat exchange; however, it would escalate the pressure drop considerably. Results also show that baffles angle plays a critical role on the performance of a STHX. An artificial neural network (ANN) is trained to predict the system's performance. As lowering the pressure drop and increasing the heat transfer are the two main objectives in STHX, a multi-objective optimization study is conducted. Different decision-making algorithms are also applied to find the best alternative among the Pareto frontier points. Results of optimization show that a STHX with 10 porous baffles, baffle angle of 111.9, and baffle thickness of 16.69 mm would be the best geometrical configuration which results in a heat transfer rate of 523.81 kW while the pressure drop of the shell side flow would be 48.87 kPa. With this novel design, it is also possible to improve both pressure drop and heat transfer rate of STHX, simultaneously. A particular configuration of the introduced STHX could reduce the pressure drop by 61.3% while heat transfer enhances by 11.15% simultaneously

Rapid Assessment of COVID-19 Screening Program for Travelers in Iran: A Qualitative Study

Objective: COVID-19 screening stations set up by Iranian Red Crescent Society have been available for seventeen days with the aim of identifying and treating people with coronavirus, reducing road trips, and sensitizing people to the problem. This study aims to investigate the challenges of the procedure. Methods: A qualitative study was used to find the challenges of the COVID-19 screening centers. Volunteers, branch managers, and headquarter managers of the Iranian Red Crescent Society participated in this study applying snowball sampling. Data were collected via in-depth semi-structured telephone interviews in April 2020 after completion of the fever screening plan. All interviews were recorded and transcribed verbatim, always with prior permission of interviewees. Results: The interviews with 20 participants in the plan indicated six relevant challenges including logistics, lack of planning, lack of coordination, legal challenges, mental health, and ethical challenges. Conclusions: The results indicated that although establishing fever detection centers in Iran was a rapid response to COVID-19, it had significant flaws in the structure and adversely affected volunteers and staffs’ health and financial resources. Therefore, well-structured protocols are required for similar responses in the future

Naphtoyl-Glycyl-Glycyl-Glycine: A New Substrate for Angiotensin Converting Enzyme (ACE) Assay Using HPLC

Background: Several in vitro assays are used to determine Angiotensin Converting Enzyme (ACE) activity. The purpose of the present investigation, was developing a practical and extraction-free chromatographic method to determine ACE activity. Methods: The method relies on UV-detection of Naphthoyl-glycine (NG), which is resulted from enzymatic hydrolysis of the synthetic substrate, Naphthoyl-glycyl-glycyl-glycine (NGGG), applying a reverse phase chromatographic separation. In this regard, experimental conditions for the assay such as Enzyme/Substrate (E/S) ratio and incubation time were optimized. Chromatographic separation was performed on a reverse phase C18 column (250 × 4.6 mm), using a mobile phase consisting of acetonitrile/water (20:80, v/v), pH = 5.0 with a flow rate of 2.0 mL/min and a detection wavelength of 280 nm. Results: The optimized Enzyme/Substrate (E/S) ratio and incubation time were 10 mU/nmol and 35 min respectively. The results indicated that the calibration curve was linear (r2 = 0.994) and the average recovery (n = 6) of NG was 99.5 ± 1.3% (mean ± RSD). Conclusion: In this study, we introduced a method which is an efficient approach to determine ACE activity due to its sensitive, accurate, and reliable performance with great repeatability