The use of hydroxychloroquine to aid in the disruption of the SARS-CoV-2 virus and to cure or at least treat the COVID-19 disease is recently being reviewed in various clinical trials worldwide, but with insufficient examination of the binding of human ACE2 to the viral spike. In order to understand and assess the efficacy of the drug or drug combination, this paper looks at the effect of the pharmaceutical drug hydroxychloroquine, as well as a common co-drug, azithromycin, on the SARS-CoV-2 spike-ACE2 complex by using virtualized quantum mechanical modeling to better characterize binding sites on the complex, assess the binding between these sites and the drug compounds, and enhance community PDB files.

The use of hydroxychloroquine to aid in the disruption of the SARS-CoV-2 virus and to cure or at least treat the COVID-19 disease is recently being reviewed in various clinical trials worldwide, but with insufficient examination of the binding of human ACE2 to the viral spike. In order to understand and assess the efficacy of the drug or drug combination, this paper looks at the effect of the pharmaceutical drug hydroxychloroquine, as well as a common co-drug, azithromycin, on the SARS-CoV-2 spike-ACE2 complex by using virtualized quantum mechanical modeling to better characterize binding sites on the complex, assess the binding between these sites and the drug compounds, and enhance community PDB files. <br>

The use of hydroxychloroquine to aid in the disruption of the SARS-CoV-2 virus and to cure or at least treat the COVID-19 disease is recently being reviewed in various clinical trials worldwide, but with insufficient examination of the binding of human ACE2 to the viral spike. In order to understand and assess the efficacy of the drug or drug combination, this paper looks at the effect of the pharmaceutical drug hydroxychloroquine, as well as a common co-drug, azithromycin, on the SARS-CoV-2 spike-ACE2 complex by using virtualized quantum mechanical modeling to better characterize binding sites on the complex, assess the binding between these sites and the drug compounds, and enhance community PDB files. <br>

The pulmonary surfactant protein A (SP-A) is a constitutively expressed immune-protective collagenous lectin (collectin) in the lung. It binds to the cell membrane of immune cells and opsonizes infectious agents such as bacteria, fungi, and viruses through glycoprotein binding. SARS-CoV-2 enters airway epithelial cells by ligating the Angiotensin Converting Enzyme 2 (ACE2) receptor on the cell surface using its Spike glycoprotein (S protein). We hypothesized that SP-A binds to the SARS-CoV-2 S protein and this binding interferes with ACE2 ligation. To study this hypothesis, we used a hybrid quantum and classical in silico modeling technique that utilized protein graph pruning. This graph pruning technique determines the best binding sites between amino acid chains by utilizing the Quantum Approximate Optimization Algorithm (QAOA)-based MaxCut (QAOA-MaxCut) program on a Near Intermediate Scale Quantum (NISQ) device. In this, the angles between every neighboring three atoms were Fourier-transformed into microwave frequencies and sent to a quantum chip that identified the chemically irrelevant atoms to eliminate based on their chemical topology. We confirmed that the remaining residues contained all the potential binding sites in the molecules by the Universal Protein Resource (UniProt) database. QAOA-MaxCut was compared with GROMACS with T-REMD using AMBER, OPLS, and CHARMM force fields to determine the differences in preparing a protein structure docking, as well as with Goemans-Williamson, the best classical algorithm for MaxCut. The relative binding affinity of potential interactions between the pruned protein chain residues of SP-A and SARS-CoV-2 S proteins was assessed by the ZDOCK program. Our data indicate that SP-A could ligate the S protein with a similar affinity to the ACE2-Spike binding. Interestingly, however, the results suggest that the most tightly-bound SP-A binding site is localized to the S2 chain, in the fusion region of the SARS-CoV-2 S protein, that is responsible for cell entry Based on these findings we speculate that SP-A may not directly compete with ACE2 for the binding site on the S protein, but interferes with viral entry to the cell by hindering necessary conformational changes or the fusion process.

Iff Technologies has constructed a tool named Polar+ that can predict protein-to-protein binding that operates faster and at a higher quality than the prominent industry standards for protein binding,including Autodock Vina and SwissDock. The ability to provide this advantage over other market leaders comes from a new approach to biophysics, dubbed many-body biological quantum systems, that are modeled using quantum processing units and quantum algorithms provided by Rigetti. This paper provides both experimental and theoretical evidence behind the validity of the quantum biology approach to protein modeling, an overview of the first experimental work completed by Polar+, and a review of results obtained compared to other tools and data found in the lab.