key: cord-0795530-d4xtbe3t
authors: Liang, Hualou; Zhao, Liang; Gong, Xiajing; Hu, Meng; Wang, Hongbin
title: Virtual Screening FDA Approved Drugs against Multiple Targets of SARS‐CoV‐2
date: 2021-02-19
journal: Clin Transl Sci
DOI: 10.1111/cts.13007
sha: ef542611a6b810afb4d2809caa17eb21f4fc7cc7
doc_id: 795530
cord_uid: d4xtbe3t

The outbreak of the novel coronavirus SARS‐CoV‐2, the causative agent of COVID‐19 respiratory disease, leads to a global pandemic with high morbidity and mortality. Despite frenzied efforts in therapeutic development, there are currently no effective drugs for treatment, nor are there vaccines for its prevention. Drug repurposing, representing as an effective drug discovery strategy from existing drugs, is one of the most practical treatment options against the outbreak. In this study, we present a novel strategy for in‐silico molecular modeling screening for potential drugs that may interact with multiple main proteins of SARS‐CoV‐2. Targeting multiple viral proteins is a novel drug discovery concept in that it enables the potential drugs to act on different stages of the virus' life cycle, thereby potentially maximizing the drug potency. We screened 2,631 FDA‐approved small molecules against four key proteins of SARS‐CoV‐2 that are known as attractive targets for anti‐viral drug development. In total, we identified 29 drugs that could actively interact with two or more target proteins, with 5 drugs (Avapritinib, Bictegravir, Ziprasidone, Capmatinib and Pexidartinib) being common candidates for all four key host proteins and 3 of them possessing the desirable molecular properties. By overlaying docked positions of drug candidates onto individual host proteins, it has been further confirmed that the binding site conformations are conserved. The drugs identified in our screening provide potential guidance for experimental confirmation such as in vitro molecular assays, in vivo animal testing as well as incorporation into ongoing clinical studies.

A novel coronavirus (SARS-CoV-2) outbreak has caused a global pandemic resulting in millions of infections and tens of thousands of deaths worldwide. Given the scale and rapid spread of the COVID-19, there is an urgent need for treatment options before a vaccine can be produced. Since the emerging virus represents new pathogens that interact with human cells in complicated ways, effective treatment options have been hard to find. Several drug candidates, deemed promising in the early phase of the pandemic, have recently been reported to have no or only moderate efficacy (Beigel et al. 2020 ). The need for quickly identifying effective drugs is becoming even more urgent as nations start to ease the lockdowns and vaccines are still months away. In this regard, finding currently approved drugs that could be repurposed against the new virus is a sound strategy.

To devise therapeutic strategies to counteract SARS-CoV-2 infection, it is crucial to understand how this coronavirus hijacks the host during the course of infection, and to apply this knowledge towards repurposing existing drugs. SARS-CoV-2 possesses the typical coronavirus structure with the spike (S) protein and encodes more than two dozen proteins, including both structural and nonstructural proteins, some of which are essential to viral entry and replication. The coronavirus begins its life cycle when S protein binds to the cellular receptor called angiotensin-converting enzyme 2 (ACE2) 

This article is protected by copyright. All rights reserved A large body of emerging work on repurposing the existing drugs has been exclusively focused on one single protein target (e.g., Pushpakom et al. 2019; Harrison 2020) . For example, recently FDAapproved drug, remdesivir, is an inhibitor of the viral RdRp. Considering the existence of different stages of the virus' life cycle, it is desirable to target multiple viral proteins in that it enables the potential drugs to disrupt the viral infection and replication process in different stages, hence maximizing the drug potency and spectrum. In addition, extant work rarely considers the molecular properties important for drug discovery. It is generally recognized that an ideal drug, besides being pharmacologically active, should additionally possess certain features regarding its bioavailability and its toxicological profile, such as Absorption, Distribution, Metabolization, and Elimination/Toxicological (ADME-Tox). In this study, we present a novel drug repurposing strategy for performing in-silico molecular modeling screening for potential drugs that interact with four target proteins of SARS-CoV-2. To check the impact of the ADME-Tox filtering on the potential drugs identified, we also perform the same screening procedure, but with ADME-Tox filtering. Overall, we screened all available FDA-approved small molecules, and found 5 promising candidates with potential therapeutic ability against four key proteins of SARS-CoV-2. Among these 5 drugs, three possess the ADME-Tox properties.

The list of the FDA approved drug was downloaded from DrugBank database (Wishart et al. 2018 ).

At the time of writing, the database contains 2,632 approved small molecule drugs along with their Simplified Molecular-Input Line-Entry System (SMILES) representations (Weininger 1988 

This article is protected by copyright. All rights reserved structure files downloaded include 3CLpro (PDB ID: 6LU7), RdRp (PDB ID: 6M71), S-Protein-RBD (PDB ID: 6LZG), and PLpro (PDB ID: 6W9C). PDB protein structures normally lack hydrogen atoms, which are required for appropriate treatment of electrostatics during docking. As such, hydrogens for pH 7.0 and Gasteiger charges were added to the protein and a pdbqt format file, as required by molecular docking below (AutoDock Vina), was generated by using Open Babel (O'Boyle et al, 2011) .

An ideal drug not only must be active against target proteins, but also should possess the appropriate ADME-Tox (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties. The ADME in silico screening leads to the widely-used Lipinski's rule of five (Lipinski et al. 2001 ) for determining whether it is probable or not for a drug candidate to reach its site of action. These simple rules state that bioavailability is likely to occur if at least three of the following rules are obeyed: molecular weight below 500 daltons; no more than five hydrogen bond donors and less than 10 hydrogen bond acceptors; and a calculated logarithm of the partition coefficient of the compound between water and octanol (log P) below 5. Moreover, to ensure good bioavailability, the polar surface area no greater than 140 Å 2 and the number of rotaS bonds less than 10 are further imposed (Veber et al. 2002) . The values of these molecular descriptors were obtained using the RDKit Python library (Landrum 2006) .

Considering that the drug toxicity is closely related to its approved dose, we additionally assess the possible toxic effects of drug candidates. We use ProTox (Drwal et al. 2014 ) to compute the toxic doses, known as median lethal doses (LD50) values in mg/kg body weight. We use the well-defined toxicity classes according to the Globally Harmonized System of classification of labelling of chemicals. The molecule is hence considered toxic when LD50 ≤ 300 mg/kg. This additional estimation of toxicity, while complementing the existing tox profiles, offers the potential comparison across all products and allows one to get the least toxic.

This article is protected by copyright. All rights reserved We used molecular docking software AutoDock Vina (Trott et al. 2010 ) to perform protein-ligand docking analysis, with the above prepared ligands and proteins as docking inputs. To dock drug molecules into the binding sites of the target proteins of SARS-CoV-2, we need to define the 3D search space that encloses the known binding sites and where ligand docking should be attempted.

The 3D search space for each targeted SARS-CoV-2 protein is generated based on its known or contains no ligand binding information (Osipiuk et al. 2020) . Given the fact that PLpro is conserved well between SARS-CoV and SARS-CoV-2, we inferred its spatial binding information by first aligning its structure with SARS-CoV PLpro with known ligand binding information (PDB ID: 4OW0) and then grabbed the corresponding search space using PyMOL.

We inspected the docking results with PyMOL (DeLano, 2002) by visualizing the docks and comparing to the crystal conformation of the ligands. Finally, the candidate molecules were selected by their docking scores that represent the binding affinity to individual protein structures. The docking score is an estimation of the free energy of binding (in kcal/mol); the more negative the value is, the tighter the hit binds to the target.

To illustrate how our drug screening method works for multiple proteins, we used two target proteins (S-Protein-RBD and PLpro) to show the selection process. The rationale was to choose drug candidates that showed higher binding affinity (i.e. low binding free energy) to both proteins, as shown in Figure 1 . Thus, we defined a simple screening criterion to select top candidates having low docking scores on both proteins. All candidates having scores lower than the screening line (the shaded area) were screened for further consideration. Also shown in Figure 1 are the identified three out of five potential drug candidates (Avapritinib, Ziprasidone and Bictegravir) binding to all the four Accepted Article key host proteins (3CLpro, RdRp, S-Protein-RBD and PLpro) while possessing the desirable molecular properties in this study.

Since the docking scores are sensitive to the choice of target structures, we chose the top 40 hits (accounting for 2% drugs) that were ranked based on their docking scores for each protein to make the screening target-dependent. We then identified the overlapping drugs between two, three and four proteins, respectively. While how to choose the ranking score cutoff remains a long-standing question in docking, it has been a general practice that has been widely in drug screening (e.g. Lyu To check the impact of the ADME-Tox filtering on the potential drugs identified, we also performed the same screening procedure above, but with ADME-Tox filtering.

A list of 2,631 FDA-approved small molecules was downloaded from DrugBank (version 5.1.6, released 2020-04-22). For some molecules, the SMILES representation could not be resolved correctly and, therefore were filtered out. We ended up with 2,028 molecules for further analysis.

After ADME-Tox screening was conducted for all these molecules, the number of candidates was reduced to 1,366.

For each molecule, the molecule-protein docking was carried out between the molecule and one of the 4 target protein structures (6LU7, 6M71, 6LZG and 6W9C). We applied our screening procedure to pick the top-40 hits for each protein based on the binding affinity. Next, we identified a short list of drug candidates common in combination of 2, 3, 4 proteins, respectively. In total, we identified 29 high-ranked drugs that could actively interact with two or more target proteins, with 5 drugs (avapritinib, bictegravir, ziprasidone, capmatinib and pexidartinib) being common candidates for all four key targeted proteins. Table 1 lists the detailed binding affinity between protein-molecule pairs for all the drug candidates specific to each protein target, with the identified five drugs shaded.

This article is protected by copyright. All rights reserved As a comparison, we have performed the same screening procedure above, with ADME-Tox filtering imposed. As a result, 3 out of 5 drugs (avapritinib, bictegravir, ziprasidone) were identified. With the ADME-Tox filtering, the resulted top-list drugs are provided in Table S1 as Supplementary Information. Figure 2 shows the chemical structures of these three identified drugs, with their desirable molecular properties provided in Table 2 . The screening results are provided in the Venn diagram (Figure 3) , showing all possible drug candidates overlapping between/among different host proteins (3CLpro, RdRp, S-Protein-RBD and PLpro). For example, the identified three core drug candidates (avapritinib, bictegravir and ziprasidone) are in the intersection among all four proteins, whereas bisoxatin, along with these three core drugs, are the overlap among three proteins (3CLpro, RdRp and PLpro). We confirmed that all the potential drug candidates selected meet the ADME-Tox screening criteria (Table 2) . We note that the drug substance can be delivered as orally inhaled product or administered via IV infusion.

By overlaying docked positions of the selected three drug candidates binding to individual host proteins (Figure 4) , we further observed that the binding site conformations are conserved despite docking variation in some of the drugs.

With the rapidly expanding knowledge about SARS-CoV-2, there have been a growing number of registered clinical trials with potential drugs against COVID-19 (Kuleshov et al. 2020). It is natural to ask how these drugs, albeit not necessarily FDA-approved, are evaluated against our screening method. This also provides us a means of negative control to cross-check our method. Table 3 provides the docking scores (i.e., the binding affinity) with all the four target proteins for select proposed COVID-19 treatments from recent studies (for recent comprehensive reviews, see Liu et al. 2020; Sanders et al. 2020) . It is generally observed that these drugs have weaker binding affinity than those selected in Table 1 . Several factors, either individually or in combination, may contribute to the outcome that none of these drugs makes into our short list: 1) they are investigational drugs (e.g., umifenovir and favipiravir); 2) there is at least one violation of the ADME-Tox screening rule (lopinavir and ritonavir; each has a molecular mass greater than 500 daltons); and 3) lower binding affinity to meet our screening criteria, e.g. chloroquine and hydroxychloroquine, in addition, both act

This article is protected by copyright. All rights reserved on ACE2 receptor (not the target proteins under the current study) as a potential mechanism against SARS-CoV-2. Importantly, it has been recently reported that treatment with an antiviral drug alone may not be sufficient (Beigel et al. 2020 ).

In this work, we present a novel drug repurposing strategy for performing in-silico molecular modeling screening for potential drug candidates that interact with multiple target proteins of SARS-CoV-2. We additionally conduct the drug screening procedure while considering the desirable molecular properties such as ADME-Tox. Overall, we screened over 2000 FDA-approved small molecules, and found 5 candidates with potential therapeutic ability against four key proteins of SARS-CoV-2. Among these 5 drugs, three possess the ADME-Tox properties.

The definition of a drug target is crucial to the success of drug discovery (Santos et al. 2017).

Targeting multiple viral proteins is a novel concept for drug repurposing. In the same vein as drug cocktail or drug combination screening, the rationale for protein combinations is to choose drug candidates that target and block different stages of the virus' life cycle. This is in stark contrast to most existing work for repurposed drugs that exclusively focuses on one single protein target.

Therefore, our approach, if successful, has great potential to attack the virus from different angles.

Although the drugs screened in this study are already FDA-approved, they do not have the same safety, quality, and effectiveness assurances. The FDA-approved drugs do not always comply with the 'rule-of-five' since they were approved to serve a particular medical need for patients. The trade-offs could have adverse drug reaction and severe side-effect for treatments (such as COVID-19) other than original purpose. Modern drug discovery stresses the importance of simultaneous optimization of many physicochemical and biological properties, and incorporation of optimal ADME-Tox properties 

This article is protected by copyright. All rights reserved for new drug development. Therefore, it is prudent to include ADME-Tox properties which allow resources to be focused on potential drug candidates. We also caution that a more balanced approach to drug discovery should be more productive than to rely on an overemphasis of 'rule-of-five' compliance.

A couple of findings strongly support that targeting RdRp, 3CLpro, PLpro and S-Protein-RBD, in combination, is a viable strategy for repurposed drugs. First, among the five drugs (avapritinib, bictegravir, ziprasidone, capmatinib and pexidartinib) identified being common candidates among the four key host proteins considered, bictegravir is an antiviral drug that has been reported as one of the reveals that some drug candidates do not solely interact with one single protein target; instead, they actively bind to multiple viral proteins. Take a widely-publicized example of the antiviral drug, remdesivir, we confirmed that it indeed has the strongest binding affinity (-7.5 kcal/mol) to RdRp among the four proteins we considered, which is consistent with the recent experimental data (Yin et al. 2020).Therefore, our method not only is useful for selection of candidate drugs, but also can be utilized for identification of protein binding sites.

This article is protected by copyright. All rights reserved We note, however, that remdesivir, albeit just FDA-approved, does not make the cut for our short list.

It has at least two reasons: (1) its molecular weight (602.58 daltons) is greater than 500 daltons, which may limit pulmonary drug delivery following oral route (Fan et al. 2020); and (2) its binding affinities to other three proteins (3CLpro, PLpro and S-Protein-RBD) are, respectively, -5.5, -7.2 and -6.3 kcal/mol, which do not meet our screening criteria. Caveat should be given that all of the reasons are purely rooted from the proposed computational approach and may not be consistent with the actual drug performance in the clinic. For instance, a product's clinical performance can be different if there are factors overlooked or not sufficiently addressed by the current approach and/or the drug is given through a different delivery route (e.g., through oral inhalation). This exception, while providing a negative control over our method, also raises the question about the limitation of our screening method, which is primarily based on the binding affinity. The additional evaluation of toxicity should complement the existing tox profiles, allowing one to compare across all products including investigational drugs and get the least toxic. Although the drugs selected by our screening procedure show excellent binding affinity to the target proteins, other drugs that do not possess the binding affinity as strong as ours and/or do not meet the ADME-Tox screening criteria can be potential candidates if additional knowledge of the molecular details of SARS-CoV-2 infection is considered.

As such, it should be pointed out that drugs that have not been identified through our screening process may still have beneficial effects.

We note that a pH 7.0 is used in this study to estimate the binding affinity (i.e. binding free energy) with the molecular docking software AutoDock Vina (Trott et al. 2010) . It has been known that pH that prevails in the human body is approximately 7.4. However, it may vary across different tissues.

For lung tissues, it has been reported that pH is around 6.6 for epithelial fluid and 6.7 for lung tissues Table 4 , where we observe that the variations in the affinity are rather small when the pH values vary, indicating a relatively insensitivity of our screening method to the pH values. Although we found that the binding free energy is quite robust to the variations in pH values, we acknowledge that the use of pH of 7.0 may not be optimal given multiple viral proteins involved and various stages of the viral dynamic cycle.

Drug repurposing is an effective strategy for identifying new therapeutic purposes from existing drugs, which could shorten the time and reduce the cost compared to de novo drug discovery. Among various drug repurposing strategies, this work represents our effort to identify additional unanticipated therapeutic options with accelerated evaluation for the treatment of COVID-19 disease. The elucidation of additional candidate therapies would greatly enhance the probability of rapidly identifying safe and efficacious treatment options. As such, it would mitigate the potential drug shortage during current pandemic outbreak, and further provide an opportunity to develop generic drug products with equivalent therapeutic effect. Therefore, it is critical that multiple therapeutic options that demonstrate efficacy against SARS-CoV-2 are available to mitigate potential emergence of drug resistance and drug shortage.

The use of repurposed drugs relies on the assumption that the benefits outweigh associated risks (adverse drug reactions). One key consideration to using repurposed agents is the propensity of these agents to cause acute toxicity, which has not yet been carefully vetted by drug repurposing methods currently available. This acute toxicity, particularly for combination therapy ("drug cocktail"), may outweigh the undefined benefit of a specific antiviral agent. This is of upmost concern in patients at high risk for toxicity and in situations where adverse events may preclude entry into investigational trials. Therefore, toxicity of the potential candidates should be properly assessed, as we have done in this work.

In conclusion, in-silico screening the FDA approved drugs against multiple proteins of SARS-CoV-2 can provide valuable insights to fast-track clinical trials for drugs with an established safety profile.

Several top hits from our short list, including the five drug candidates actively binding to all four key host proteins, could be beneficial for treatment of coronaviral infections. The targets identified in this paper provide new candidates for future research studies and clinical intervention protocols.

Additionally, we propose a novel screening strategy targeting multiple viral proteins which may provide guidance in screening antiviral drugs from other drug databases.

What is the current knowledge on the topic?

The pandemic of coronavirus disease 2019 (COVID-19) caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) 2 has become a global crisis. Currently there are no effective drugs for treatment, nor are there vaccines for its prevention. Extant work on drug repurposing has exclusively focused on one single protein target, neither considered multiple proteins at different stages of the virus' life cycle nor accounted for molecular properties important for drug discovery.

This work describes a novel drug repurposing strategy for performing in-silico molecular modeling screening for potential drugs that interact with multiple proteins of SARS-CoV-2 while at the same time taking into consideration the desirable molecular properties.

We provide a drug repurposing strategy targeting multiple viral proteins that enables the potential drugs to act on different stages of the virus' life cycle, thereby potentially maximizing the drug potency. Of 29 identified drugs that actively interact with two or more target proteins, we find 5 drugs that harbor antiviral activity against all four key host proteins of SARS-CoV-2.

This work identifies key drug repurposing opportunities and dramatically highlights the importance of considering multiple target proteins of SARS-CoV-2 while taking into consideration the desirable molecular properties important for drug discovery. 

This article is protected by copyright. All rights reserved 

This article is protected by copyright. All rights reserved 

This article is protected by copyright. All rights reserved Table 4 : The binding affinity, represented as the minimum binding free energy in kcal/mol, for the top-listed three drugs at the selected pH value ranging from 5.0 to 8.0 with a step of 0.5 for all four key proteins (RdRp, 3CLpro, PLpro and S-Protein-RBD) of SARS-CoV-2.

Shaded are the binding affinities calculated at the pH value of 7.0, as reported in this study.

Note that that the binding affinity is quite robust to the variations in pH values. 

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Remdesivir for the Treatment of Covid-19 -Preliminary Report

COVID-19 infection: Origin, transmission, and characteristics of human coronaviruses

The spike protein of SARS-CoV -A target for vaccine and therapeutic development

Cryo-EM structure of the 2019-nCoV Spike in the prefusion conformation

SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor

Virus-Encoded Proteinases and Proteolytic Processing in the Nidovirales

The SARS-coronavirus papain-like protease: structure, function and inhibition by designed antiviral compounds

Molecular Model of SARS Coronavirus Polymerase: Implications for Biochemical Functions and Drug Design

Drug repurposing: progress, challenges and recommendations

Accepted Article This article is protected by copyright. All rights reserved

Coronavirus puts drug repurposing on the fast track

DrugBank 5.0: a major update to the DrugBank database

SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules

Pybel: a Python wrapper for the OpenBabel cheminformatics toolkit

The Protein Data Bank

Computational Approach for Designing and Development of Potent Inhibitor for Hepatitis -B Virus X-Associated Protein through Molecular Docking Studies

Open Babel: An open chemical toolbox

Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings

Molecular properties that influence the oral bioavailability of drug candidates

Rdkit documentation, Release. 1, 1−

ProTox: a web server for the in silico prediction of rodent oral toxicity

Accepted Article This article is protected by copyright. All rights reserved

AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading

Structure of Mpro from SARS-CoV-2 and discovery of its inhibitors

The PyMOL Molecular Graphics System

Structure of the RNA-dependent RNA polymerase from COVID-19 virus

Structural and Functional Basis of SARS-CoV-2 Entry by Using Human ACE2

Center for Structural Genomics of Infectious Diseases (CSGID)

Ultralarge library docking for discovering new chemotypes

An open-source drug discovery platform enables ultralarge virtual screens

Research and Development on Therapeutic Agents and Vaccines for COVID-19 and Related Human Coronavirus Diseases

Pharmacologic Treatments for Coronavirus Disease 2019 (COVID-19): A Review

This article is protected by copyright. All rights reserved 

This article is protected by copyright. All rights reserved