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		<title>WikiSysop: Created page with &quot;== Citation ==  Behkamal, Bahareh / Naghibzadeh, Mahmoud / Saberi, Mohammad Reza / Tehranizadeh, Zeinab Amiri / Pagnani, Andrea / Al Nasr, Kamal. Three-Dimensional Graph Match...&quot;</title>
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		<updated>2022-03-23T08:19:34Z</updated>

		<summary type="html">&lt;p&gt;Created page with &amp;quot;== Citation ==  Behkamal, Bahareh / Naghibzadeh, Mahmoud / Saberi, Mohammad Reza / Tehranizadeh, Zeinab Amiri / Pagnani, Andrea / Al Nasr, Kamal. Three-Dimensional Graph Match...&amp;quot;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;== Citation ==&lt;br /&gt;
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Behkamal, Bahareh / Naghibzadeh, Mahmoud / Saberi, Mohammad Reza / Tehranizadeh, Zeinab Amiri / Pagnani, Andrea / Al Nasr, Kamal. Three-Dimensional Graph Matching to Identify Secondary Structure Correspondence of Medium-Resolution Cryo-EM Density Maps. 2021-11, Biomolecules, Vol. 11&lt;br /&gt;
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== Abstract ==&lt;br /&gt;
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Cryo-electron microscopy (cryo-EM) is a structural technique that has played a significant role in protein structure determination in recent years. Compared to the traditional methods of X-ray crystallography and NMR spectroscopy, cryo-EM is capable of producing images of much larger protein complexes. However, cryo-EM reconstructions are limited to medium-resolution (&amp;amp;nbsp;4-10 Å) for some cases. At this resolution range, a cryo-EM density map can hardly be used to directly determine the structure of proteins at atomic level resolutions, or even at their amino acid residue backbones. At such a resolution, only the position and orientation of secondary structure elements (SSEs) such as α-helices and β-sheets are observable. Consequently, finding the mapping of the secondary structures of the modeled structure (SSEs-A) to the cryo-EM map (SSEs-C) is one of the primary concerns in cryo-EM modeling. To address this issue, this study proposes a novel automatic computational method to identify SSEs correspondence in three-dimensional (3D) space. Initially, through a modeling of the target sequence with the aid of extracting highly reliable features from a generated 3D model and map, the SSEs matching problem is formulated as a 3D vector matching problem. Afterward, the 3D vector matching problem is transformed into a 3D graph matching problem. Finally, a similarity-based voting algorithm combined with the principle of least conflict (PLC) concept is developed to obtain the SSEs correspondence. To evaluate the accuracy of the method, a testing set of 25 experimental and simulated maps with a maximum of 65 SSEs is selected. Comparative studies are also conducted to demonstrate the superiority of the proposed method over some state-of-the-art techniques. The results demonstrate that the method is efficient, robust, and works well in the presence of errors in the predicted secondary structures of the cryo-EM images. &lt;br /&gt;
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== Keywords ==&lt;br /&gt;
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== Links ==&lt;br /&gt;
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https://www.mdpi.com/2218-273X/11/12/1773&lt;br /&gt;
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== Related software ==&lt;br /&gt;
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== Related methods ==&lt;br /&gt;
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== Comments ==&lt;/div&gt;</summary>
		<author><name>WikiSysop</name></author>
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