AI-Driven De Novo Design and Molecular Modeling for Discovery of Small-Molecule Compounds as Potential Drug Candidates Targeting SARS-CoV-2 Main Protease.

Over the past three years, significant progress has been made in the development of novel promising drug candidates against COVID-19. However, SARS-CoV-2 mutations resulting in the emergence of new viral strains that can be resistant to the drugs used currently in the clinic necessitate the development of novel potent and broad therapeutic agents targeting different vulnerable spots of the viral proteins. In this study, two deep learning generative models were developed and used in combination with molecular modeling tools for de novo design of small molecule compounds that can inhibit the catalytic activity of SARS-CoV-2 main protease (Mpro), an enzyme critically important for mediating viral replication and transcription. As a result, the seven best scoring compounds that exhibited low values of binding free energy comparable with those calculated for two potent inhibitors of Mpro, via the same computational protocol, were selected as the most probable inhibitors of the enzyme catalytic site. In light of the data obtained, the identified compounds are assumed to present promising scaffolds for the development of new potent and broad-spectrum drugs inhibiting SARS-CoV-2 Mpro, an attractive therapeutic target for anti-COVID-19 agents.

SARS-CoV-2 Peptide Bioconjugates Designed for Antibody Diagnostics.

In the near future, the increase in the number of required tests for COVID-19 antibodies is expected to be many hundreds of millions. Obviously, this will be done using a variety of analytical methods and using different antigens, including peptides. In this work, we compare three method variations for detecting specific immunoglobulins directed against peptides of approximately 15-aa of the SARS-CoV-2 spike protein. These linear peptide epitopes were selected using antigenicity algorithms, and were synthesized with an additional terminal cysteine residue for their bioconjugation. In two of the methods, constructs were prepared where the peptide (F, function) is attached to a negatively charged hydrophilic spacer (S) linked to a dioleoylphosphatidyl ethanolamine residue (L, lipid) to create a function-spacer-lipid construct (FSL). These FSLs were easily and controllably incorporated into erythrocytes for serologic testing or in a lipid bilayer deposited on a polystyrene microplate for use in an enzyme immunoassays (EIA). The third method, also an EIA, used polyacrylamide conjugated peptides (peptide-PAA) prepared by controlled condensation of the cysteine residue of the peptide with the maleimide-derived PAA polymer which were immobilized on polystyrene microplates by physisorption of the polymer. In this work, we describe the synthesis of the PAA and FSL peptide bioconjugates, design of test systems, and comparison of the bioassays results, and discuss potential reasons for higher performance of the FSL conjugates, particularly in the erythrocyte-based serologic assay.

COVID-19 antibody screening with SARS-CoV-2 red cell kodecytes using routine serologic diagnostic platforms.

BACKGROUND: The Coronavirus disease 2019 (COVID-19) pandemic is having a major global impact, and the resultant response in the development of new diagnostics is unprecedented. The detection of antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a role in managing the pandemic. We evaluated the feasibility of using SARS-CoV-2 peptide Kode Technology-modified red cells (C19-kodecytes) to develop an assay compatible with existing routine serologic platforms. STUDY DESIGN AND METHODS: A panel of eight unique red cells modified using Kode Technology function-spacer-lipid constructs and bearing short SARS-CoV-2 peptides was developed (C19-kodecyte assay). Kodecytes were tested against undiluted expected antibody-negative and -positive plasma samples in manual tube and three column agglutination technology (CAT) platforms. Parallel analysis with the same peptides in solid phase by enzyme immunoassays was performed. Evaluation samples included >120 expected negative blood donor samples and >140 COVID-19 convalescent plasma samples, with independent serologic analysis from two centers. RESULTS: Specificity (negative reaction rate against expected negative samples) in three different CAT platforms against novel C19-kodecytes was >91%, which correlated with published literature. Sensitivity (positive reaction rate against expected positive convalescent, PCR-confirmed samples) ranged from 82% to 97% compared to 77% with the Abbott Architect SARS-CoV-2 IgG assay. Manual tube serology was less sensitive than CAT. Enzyme immunoassay results with some Kode Technology constructs also had high sensitivity. CONCLUSIONS: C19-kodecytes are viable for use as serologic reagent red cells for the detection of SARS-CoV-2 antibody with routine blood antibody screening equipment.

Computational discovery of small drug-like compounds as potential inhibitors of SARS-CoV-2 main protease.

A computational approach to in silico drug discovery was carried out to identify small drug-like compounds able to show structural and functional mimicry of the high affinity ligand X77, potent non-covalent inhibitor of SARS-COV-2 main protease (MPro). In doing so, the X77-mimetic candidates were predicted based on the crystal X77-MPro structure by a public web-oriented virtual screening platform Pharmit. Models of these candidates bound to SARS-COV-2 MPro were generated by molecular docking, quantum chemical calculations and molecular dynamics simulations. At the final point, analysis of the interaction modes of the identified compounds with MPro and prediction of their binding affinity were carried out. Calculation revealed 5 top-ranking compounds that exhibited a high affinity to the active site of SARS-CoV-2 MPro. Insights into the ligand - MPro models indicate that all identified compounds may effectively block the binding pocket of SARS-CoV-2 MPro, in line with the low values ​​of binding free energy and dissociation constant. Mechanism of binding of these compounds to MPro is mainly provided by van der Waals interactions with the functionally important residues of the enzyme, such as His-41, Met-49, Cys-145, Met-165, and Gln-189 that play a role of the binding hot spots assisting the predicted molecules to effectively interact with the MPro active site. The data obtained show that the identified X77-mimetic candidates may serve as good scaffolds for the design of novel antiviral agents able to target the active site of SARS-CoV-2 MPro.Communicated by Ramaswamy H. Sarma.

IDENTIFICATION OF POTENTIAL INHIBITORS OF CORONAVIRUS SARS-CoV-2 USING THE METHODS OF VIRTUAL SCREENING AND MOLECULAR MODELING

To find small-molecule compounds that can simulate the structural and functional properties of the high affinity X77 ligand of the main protease of SiRS-CoV-2 - etiologic agent of COVID-19, the virtual screening of 9 molecular libraries of the Pharmit web server containing over 213.5 million chemical structures was performed. Using molecular modeling, the neutralizing activity of the identified molecules was evaluated, resulting in 5 leader compounds promising for synthesis and testing for antiviral activity. The data obtained indicate that these compounds may be used as basic structures for the development of effective drugs to treat the novel coronavirus infection.