Homology modeling and structural validation of tissue factor pathway inhibitor

Abstract

Blood coagulation is a cascade of complex enzymatic reactions which involves specific proteins and cellular components to interact and prevent blood loss. The coagulation process begins by either “Tissue Dependent Pathway” (also known as extrinsic pathway) or by “contact activation pathway” (also known as intrinsic pathway). TFPI is an endogenous multivalent Kunitz type protease inhibitor which inhibits Tissue factor dependent pathway by inhibiting Tissue Factor:Factor VIIa (TF:FVIIa) complex and Factor Xa. TFPI is one of the most studied coagulation pathway inhibitor which has various clinical and potential therapeutic applications, however, its exact mechanism of inhibition is still unknown. Structure based mechanism elucidation is commonly employed technique in such cases. Therefore, in the current study the generated a complete TFPI structural model so as to understand the mechanistic details of it's functioning. The model was checked for stereochemical quality by PROCHECK-NMR, WHATIF, ProSA, and QMEAN servers. The model was selected, energy minimized and simulated for 1.5ns. The result of the study may be a guiding point for further investigations on TFPI and its role in coagulation mechanism.

Structure to function analysis with antigenic characterization of a hypothetical protein, HPAG1_0576 from Helicobacter pylori HPAG1

“…The QMEAN4 score for the protein was obtained 0.35 Figure 10D, which was in the range of estimated global model reliability score between 0 to 1 [38]. Hence, the protein of interest is in the dark region of the absolute model quality plot with a global score 0.7 which also supported the quality of the model [39]. Individual Z values for parameters such as C-β interaction energy, all atom interaction, solvation and torsion can also be observed in the plot Figure 10C.…”

“…The Z score obtained from ProSA for the obtained model was −6.5 Figure 10A, which was well fitted to the range that is typical for proteins of similar size. The local model quality is shown in the energy plot Figure 10B and minimum values in the plot account for nativity and stability of the molecules [5,39]. The QMEAN4 score for the protein was obtained 0.35 Figure 10D, which was in the range of estimated global model reliability score between 0 to 1 [38].…”

Interaction studies of Angelica polymorpha and Beilschmiedia pulverulenta phytochemicals with acetylcholinesterase as anti-Alzheimer's disease target

“…The estimated G-Factor was -0.11 while the Z-score (ProSA) was -10.45 indicating the good quality of the protein. In addition, the LG and Maxsub scores of 6.732 and 0.600 respectively suggest the extremely high quality of the model (Wallner and Elofsson, 2003;Agrawal et al, 2013). Till date, prediction of the threedimensional structure of a protein from its amino acid sequence is one of the major breakthrough in bioinformatics and theoretical chemistry.…”

“…Till date, prediction of the threedimensional structure of a protein from its amino acid sequence is one of the major breakthrough in bioinformatics and theoretical chemistry. It is believed that models built this way should be suitable for examining ligand interaction and binding affinity since possible errors in the X-ray or NMR crystal structures would have been corrected (Agrawal et al, 2013).…”

Binding Free Energy Calculations of Nine FDA‐approved Protease Inhibitors Against HIV‐1 Subtype C I36T↑T Containing 100 Amino Acids Per Monomer

“…The results of the Ramachandran plot (presented in the supporting material) demonstrated that 94.4% of the residues were present in the most favourable regions, 5.6% residues present in the additional allowed regions, and 0% residues present in both the generously allowed regions and disallowed regions. Generally, a structure with at least 90% of the residues occurring in the most favourable region is considered a good model (77,78).…”