key: cord-0257969-d33jn4ow authors: Chenna, Akshay; Khan, Wajihul H; Dash, Rozaleen; Rathore, Anurag S; Goel, Gaurav title: Template-based design of peptides to inhibit SARS-CoV-2 RNA-dependent RNA polymerase complexation date: 2022-01-25 journal: bioRxiv DOI: 10.1101/2022.01.24.477502 sha: d4cd69fac213f391983bbd95985a92e840815a73 doc_id: 257969 cord_uid: d33jn4ow The RNA-dependent RNA polymerase (RdRp) complex of SARS-CoV-2 lies at the core of its replication and transcription processes. The interfaces between the subunits of the RdRp complex are highly conserved, facilitating the design of inhibitors with high affinity for the interaction hotspots of the complex. Here, we report development and application of a structural bioinformatics protocol to design peptides that can inhibit RdRp complex formation by targeting the interface of its core subunit nonstructural protein (nsp) 12 with accesory factor nsp7. We adopt a top-down approach for protein design by using interaction hotspots of the nsp7-nsp12 complex obtained from a long molecular dynamics trajectory as template. A large library of peptide sequences constructed from multiple hotspot motifs of nsp12 is screened in silico to determine peptide sequences with highest shape and interaction complementarity for the nsp7-nsp12 interface. Two lead designed peptide are extensively characterized using orthogonal bioanalytical methods to determine their suitability for inhibition of RdRp complexation and anti-viral activity. Their binding affinity to nsp7 (target), as determined from surface plasmon resonance (SPR) assay, is found to be comparable to that of the nsp7-nsp12 complex. Further, one of the designed peptides gives 46 % inhibition of nsp7-nsp12 complex at 10:1 peptide:nsp7 molar concentration (from ELISA assay). Further optimization of cell penetrability and target affinity of these designed peptides is expected to provide lead candidates with high anti-viral activity against SARS-CoV-2. in the ressidue-wise area buried (eq 1). The trajectory was 141 clustered using a cutoff of 2.5 Å on the backbone atoms of 142 Rdrp. The residue-wise hotspot areas were weighted (∆Ai) 143 by the population fraction of the cluster. (Table 1) . We also generated sequences from the same segment To evaluate the quality of our designs we 222 adopted a multi-step docking process. We began with a global 223 blind docking of each of the five shortlisted peptides (P1-P5) 224 to allow for a complete 3 dimensional exploration of the tar-225 get surface. This exercise will narrow down on the binding 226 (Table 3A ). In contrast to the 283 experimentally predicted binding energies, ∆G MMPBSA−WSAS 284 has over-estimated the the binding energies by nearly two or-285 ders of magnitude. Though it is noteworthy that the binding 286 free energies are predicted similar trends as measured by SPR. 287 Peptide-NSP7 docked poses with the highest dot products 288 (cos θ) after flexible docking are depicted in figure 3A with the 289 interface patch of NSP7 with NSP12 is colored in yellow. Poses 290 with high dot products signifying better binding specificity 291 are a strong indicator of the peptides' ability to mimic the 292 binding modes of NSP12 and serve to validate our approach 293 of peptide design. Subsequently, the peptides were tested 294 for competitive binding with labelled NSP7 (his-taq) in the 295 presence of immobilised NSP12 using ELISA binding assays. 296 The signal in Figure 3B is a measure of the NSP7 bound to 297 the NSP12. P4 shows 46% inhibition in the binding of NSP7 298 with NSP12 at ten times the molar concentration of NSP7 299 translating to an IC50 of about 50 µM for P4. However, P5 300 did not show significant inhibition even at high concentrations 301 indicative of specificity at a non-neutralising site. ELISA based 302 competitive assays suggest that our peptide sequence needs 303 further optimisation for achieving higher affinities, highlight-304 ing a fundamental shortcoming of our approach in restricting 305 the sequences of peptides from the template. Similar observa- with 100 µl of anti-his antibody prepared in 1X PBST buffer 466 at 1:5,000 dilution and incubated at 37 • C for 30 min. The 467 wells were then washed three times with 200 µl of 1X PBS 468 buffer. One hundred microlitre 3,3' ,5,5' -tetramethylbenzidine 469 substrate (Thermo Fisher Scientific) was added to each well 470 and incubated for 10 min. The reaction was stopped by adding 471 100 µL of 0.18 M sulphuric acid and the optical densities of 472 the plate wells were measured using Biotek plate reader at 450 473 nm. A Novel Coronavirus from Patients with Pneumonia in China A new coronavirus associated with human respiratory disease in China Structure of replicating SARS-CoV-2 polymerase Structure of the RNA-dependent RNA polymerase from COVID-19 virus. Sci-484 ence 368 RdRP, a promising therapeutic target for cancer and potentially COVID-19 RNA-dependent RNA polymerase (RdRp) inhibitors: The current landscape 489 and repurposing for the COVID-19 pandemic Structure of the SARS-CoV nsp12 polymerase bound to nsp7 491 and nsp8 co-factors An orally bioavailable broad-spectrum antiviral inhibits SARS-CoV-2 in 493 human airway epithelial cell cultures and multiple coronaviruses in mice One severe acute respiratory syndrome coronavirus protein complex inte-496 grates processive RNA polymerase and exonuclease activities Biochemical characterization of a recombinant SARS 499 coronavirus nsp12 RNA-dependent RNA polymerase capable of copying viral RNA templates Structural basis for inhibition of the SARS-CoV-2 RNA polymerase by suramin Targeting SARS-CoV-2 Pro-504 teases and Polymerase for COVID-19 Treatment: State of the Art and Future Opportunities A SARS-CoV-2 protein interaction map reveals targets for drug repurpos-507 ing Molecular Dynamics Simulations Related to SARS-CoV-2," D. E. Shaw Re-509 search Technical Data SARS-CoV-2 Molecular Network Structure Structure-Based Design of Small Peptide Ligands to Inhibit Early-Stage 513 Protein Aggregation Nucleation HIV-1 anchor inhibitors and membrane fusion inhibitors target distinct but 515 overlapping steps in virus entry THPdb: Database of FDA-approved peptide and protein therapeutics Trends in peptide drug discovery Peptide and peptide-based inhibitors of SARS-CoV-2 entry Cell-penetrating peptides: Classes, origin, and current landscape REGN-COV2, a Neutralizing Antibody Cocktail De novo design of picomolar SARS-CoV-2 miniprotein inhibitors Synthetic Peptides That Antagonize the Angiotensin-Converting 529 Enzyme-2 (ACE-2) Interaction with SARS-CoV-2 Receptor Binding Spike Protein De Novo Discovery of High-Affinity Peptide Binders for the SARS-CoV-2 532 Computational Design of Potent D-Peptide Inhibitors of SARS-CoV-2 Discovery of Small Anti-ACE2 Peptides to Inhibit SARS-CoV-2 Infectivity Cross-linking peptide and repurposed drugs inhibit both entry pathways of 538 SARS-CoV-2 The race to treat COVID-19: Potential therapeutic agents for the preven-540 tion and treatment of SARS-CoV-2 Discovery of SARS-CoV-2 M pro peptide inhibitors from modelling substrate 542 and ligand binding Protein-protein interaction and quaternary structure A hot spot of binding energy in a hormone receptor interface De novo design of potent and resilient hACE2 decoys to neutralize SARS-548 Reaching for high-hanging fruit in drug discovery at protein-protein 550 interfaces Inhibition of protein interactions: co-crystalized pro-552 tein-protein interfaces are nearly as good as holo proteins in rigid-body ligand docking Can self-inhibitory peptides 555 be derived from the interfaces of globular protein-protein interactions? Druggable protein-protein interactions -from hot 558 spots to hot segments The Structural Basis of Peptide-Protein Structural conservation of druggable Hot spots in protein -Protein inter-562 faces Druggable Protein Interaction Sites Are More Predisposed to 564 Surface Pocket Formation than the Rest of the Protein Surface Insights into protein-ligand interactions: Mechanisms, models, and methods Principles of protein-protein interactions Peptide segments in protein-protein 569 interfaces The coarse-grained OPEP force field for non-amyloid 571 and amyloid proteins Improvements to the APBS biomolecular solvation software suite Massively parallel de novo protein design for targeted therapeutics TM-align: A protein structure alignment algorithm based on the TM-577 score Calculating protein-ligand binding affinities with MMPBSA: Method and error 579 analysis Develop and test a solvent accessible surface area-based model in confor-581 mational entropy calculations server -High resolution modeling of peptide-protein interactions Converting peptides into drugs targeting intracellular 585 protein-protein interactions Improved PEP-FOLD approach for peptide and 587 miniprotein structure prediction Scoring function for automated assessment of protein structure template 589 quality MATLAB version 9.9.0.1524771 (R2020b) Update The Rosetta All-Atom Energy Function for Macromolecular Modeling and 592 Author Affiliations. Department of Chemical Engineering,