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        <datestamp>2026-09-30T17:52:03Z</datestamp>
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          <dc:title>&lt;p&gt;The degree of spatial overlap between the 3D structures of distant homologs.&lt;/p&gt;</dc:title>
          <dc:creator>Shouzhen Song (25145501)</dc:creator>
          <dc:creator>Hua Shi (7282)</dc:creator>
          <dc:creator>Hongfeng Wu (10227425)</dc:creator>
          <dc:creator>Dachen Liu (23461465)</dc:creator>
          <dc:creator>Yihang Lin (10198502)</dc:creator>
          <dc:creator>Nor Ashidi Mat Isa (25145504)</dc:creator>
          <dc:creator>Quan Zou (157931)</dc:creator>
          <dc:creator>Leyi Wei (3959444)</dc:creator>
          <dc:subject>Biophysics</dc:subject>
          <dc:subject>Biochemistry</dc:subject>
          <dc:subject>Microbiology</dc:subject>
          <dc:subject>Biotechnology</dc:subject>
          <dc:subject>Biological Sciences not elsewhere classified</dc:subject>
          <dc:subject>Information Systems not elsewhere classified</dc:subject>
          <dc:subject>Infectious Diseases</dc:subject>
          <dc:subject>t6se prediction tasks</dc:subject>
          <dc:subject>substantial application potential</dc:subject>
          <dc:subject>spatial conformational patterns</dc:subject>
          <dc:subject>maintaining stable performance</dc:subject>
          <dc:subject>local spatial topology</dc:subject>
          <dc:subject>linear functional motifs</dc:subject>
          <dc:subject>grained token level</dc:subject>
          <dc:subject>developing precise anti</dc:subject>
          <dc:subject>module enhances consistency</dc:subject>
          <dc:subject>existing leading models</dc:subject>
          <dc:subject>effector proteins secreted</dc:subject>
          <dc:subject>although existing methods</dc:subject>
          <dc:subject>model integrates sequence</dc:subject>
          <dc:subject>enable effective cross</dc:subject>
          <dc:subject>models associations</dc:subject>
          <dc:subject>effector functions</dc:subject>
          <dc:subject>based methods</dc:subject>
          <dc:subject>attention module</dc:subject>
          <dc:subject>virulence functions</dc:subject>
          <dc:subject>tokenized self</dc:subject>
          <dc:subject>synergistic modeling</dc:subject>
          <dc:subject>residue orientations</dc:subject>
          <dc:subject>protein sequence</dc:subject>
          <dc:subject>negative bacteria</dc:subject>
          <dc:subject>modal fusion</dc:subject>
          <dc:subject>modal alignment</dc:subject>
          <dc:subject>infective strategies</dc:subject>
          <dc:subject>geometric spaces</dc:subject>
          <dc:subject>fully capture</dc:subject>
          <dc:subject>extensive evaluations</dc:subject>
          <dc:subject>extensible architecture</dc:subject>
          <dc:subject>contrastive learning</dc:subject>
          <dc:subject>contextual embeddings</dc:subject>
          <dc:description>&lt;p&gt;A: Three-dimensional protein structures predicted by AlphaFold2, colored according to pLDDT scores (higher scores indicate higher confidence). B: Three-dimensional protein structures predicted by ESMFold. C: The middle panel displays the structural alignment of two proteins from each group. “Train” indicates samples from the training set, while “Test” indicates samples from the test set. Sequence identity represents the percentage of aligned amino acid positions that are identical between two protein sequences. TM-score quantifies the structural similarity between two protein structures, with higher scores indicating greater similarity.&lt;/p&gt;</dc:description>
          <dc:date>2026-09-30T18:01:24Z</dc:date>
          <dc:type>Image</dc:type>
          <dc:type>Figure</dc:type>
          <dc:identifier>10.1371/journal.pcbi.1014344.g004</dc:identifier>
          <dc:relation>https://figshare.com/articles/figure/_p_The_degree_of_spatial_overlap_between_the_3D_structures_of_distant_homologs_p_/34036484</dc:relation>
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