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Elucidating the enhanced binding affinity of a double mutant SP-D with trimannose on the influenza A virus using molecular dynamics.
Li, Deng; Minkara, Mona S.
  • Li D; Laboratory for Computational Modeling for BioInterface Engineering (COMBINE), Department of Bioengineering, Northeastern University, Boston, MA 02120, USA.
  • Minkara MS; Laboratory for Computational Modeling for BioInterface Engineering (COMBINE), Department of Bioengineering, Northeastern University, Boston, MA 02120, USA.
Comput Struct Biotechnol J ; 20: 4984-5000, 2022.
Article in English | MEDLINE | ID: covidwho-2007640
ABSTRACT
Surfactant protein D (SP-D) is an essential component of the human pulmonary surfactant system, which is crucial in the innate immune response against glycan-containing pathogens, including Influenza A viruses (IAV) and SARS-CoV-2. Previous studies have shown that wild-type (WT) SP-D can bind IAV but exhibits poor antiviral activities. However, a double mutant (DM) SP-D consisting of two point mutations (Asp325Ala and Arg343Val) inhibits IAV more potently. Presently, the structural mechanisms behind the point mutations' effects on SP-D's binding affinity with viral surface glycans are not fully understood. Here we use microsecond-scale, full-atomistic molecular dynamics (MD) simulations to understand the molecular mechanism of mutation-induced SP-D's higher antiviral activity. We find that the Asp325Ala mutation promotes a trimannose conformational change to a more stable state. Arg343Val increases the binding with trimannose by increasing the hydrogen bonding interaction with Glu333. Free energy perturbation (FEP) binding free energy calculations indicate that the Arg343Val mutation contributes more to the increase of SP-D's binding affinity with trimannose than Asp325Ala. This study provides a molecular-level exploration of how the two mutations increase SP-D binding affinity with trimannose, which is vital for further developing preventative strategies for related diseases.
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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Comput Struct Biotechnol J Year: 2022 Document Type: Article Affiliation country: J.csbj.2022.08.045

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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Comput Struct Biotechnol J Year: 2022 Document Type: Article Affiliation country: J.csbj.2022.08.045