l

Repurposing existing drugs for coronavirus 2019-nCoV (covid-19): in silico trial

In a previous post entitled "Drug Repurposing for coronavirus (COVID-19): in silico screening of known drugs against SARS-CoV-2 Spike protein" already approved drugs that have some efficacy against similar type of viruses were tested with SARS-CoV-2 Spike protein bound to angiotensin converting enzyme 2 (ACE2) (6M0J: Receptor binding domain, RBD) using computational chemistry methods and molecular docking. These drugs listed in Table I.1 of the above post were as follows: darunavir, remdesivir, chloroquine, hydroxychloroquine, colchicine, favipavir, oceltamivir.

Amongst the above drugs the highest binding affinity for 6M0J is shown by darunavir (-8.4 kcal/mol) according to Autodock Vina (the second highest affinity is shown by remdesivir -6.4 and the third by remdesivir -8.0 kcal/mol) . Darunavir shows the second highest affinity according to iGemDock (-117.0429) while remdesivir scores higher (-129.6619).

It should be mentioned that computational chemistry methods and molecular docking results of drug efficacies not to be taken as medical advice or evidence supporting a specific treatment.

The same procedure is followed in this post to test the binding affinity of lopinavir for the SARS-CoV-2 Spike protein bound to angiotensin converting enzyme 2 (ACE2) (6M0J: Receptor binding domain, RBD). It is known that the virus enter the host cell by binding of the viral spike glycoprotein to the host receptor, angiotensin converting enzyme 2 (ACE2). Lopinavir is an antiretrovial of the protease inhibitor class. It is an approved drug used against HIV infections in combination with another protease inhibitor, ritonavir.

The steps required for drug screening are as follows:

Find the 3D molecular structures of Covid-19 from the Protein Data Bank PDB.

The crystallized SARS-CoV-2 spike receptor-binding domain bound with ACE2 (6M0J) was selected. It is shown in Fig. I.1 below:



Find the molecular structures of drugs (ligands) with efficacy against similar viruses.

Hundrends of drugs can be found. In this case lopinavir is going to be tested. The 3D and 2D structures of lopinavir is shown in Fig. I.2 below:



Find the ground state optimization of these drugs (ligands).

The ground state optimization of a compound is the molecular geometry with the lowest energy (the most stable molecular geometry). There are several computational chemistry softwares that use semiempirical and ab initio methods to obtain the ground state geometry of a compound. Some of them are: Gamess, Gaussian, Orca, Avogadro, Firefly, Arguslab. The Arguslab software was used and the PM3 method was selected. This method is semiempirical and fast but not as accurate as the high level ab intio methods. PM3, or Parametric Method 3, is based on the Neglect of Differential Diatomic Overlap integral approximation. The Orca software was also used for two ab initio methods STO3G/def2SVP and PBE0/def2SVP. The accuracy of the methods regarding molecular geometry optimization (ground state energy) is as follows: PM3 < STO3G/def2SVP < PBE0/def2SVP.

The ground state optimized structure of lopinavir using the PBE0/def2SVP method is shown in Fig. I.3:



Calculate the HOMO - LUMO gap (energy difference gap between the HOMO and LUMO molecular orbitals) at the ground state molecular geometry of the drug (ligand) (from the above step).

The energy gap between the HOMO (highest occupied molecular orbital) and the LUMO (lowest unoccupied molecular orbital) is an important quantum chemical parameter that characterizes the chemical reactivity of a molecule. A molecule with a small energy gap is more reactive compared to a molecule with a large HOMO - LUMO gap. The HOMO - LUMO gap energy of each drug was calculated and is shown in Tables I.1 - I.3

The interaction of the above mentioned drugs (ligands) with SARS-CoV-2 spike receptor-binding domain bound with ACE2 (6M0J) (receptor) were determined using Molecular Docking.

The interaction of drugs with Covid-19 SARS-CoV-2 spike receptor-binding domain bound with ACE2 (6M0J) (receptor) were determined using two softwares Autodock Vina and iGemDock. During the docking process, the receptor and the ligand are rotated around their own coordinate origin and the separation between the two origins is varied. A score is calculated for each orientation and the lower binding energy obtained corresponds to the best interaction between the receptor and the ligand (highest binding affinity).

The results obtained are shown in Tables I.1 - I.3 below:

Table I1: Semiempirical PM3 Chemical & Docking Results for the Interaction of selected Drugs with Covid-19 6M0J
	Compound	HOMO-LUMO energy gap (a.u.)	Docking iGemDock	Docking AutoDock - Vina (kcal/mol)
	remdesivir	0.299555	-129.6619	-8.0
	chloroquine	0.292904	-77.8347	-6.7
	hydroxychloroquine	0.292930	-82.8867	-6.1
	colchicine	0.305204	-85.0525	-7.3
	darunavir	0.315079	-117.0429	-8.4
	favipavir	0.328258	-65.3097	-6.0
	oceltamivir	0.343420	-83.5736	-6.0
	lopinavir	0.343073	-130.8427	-9.0

 

Table I2: Ab Initio STO3G/def2SVP Chemical & Docking Results for the Interaction of Lopinavir with Covid-19 6M0J
	Compound	HOMO-LUMO energy gap (a.u.)	Docking iGemDock	Docking AutoDock - Vina (kcal/mol)
	lopinavir		-138.2157	-9.2

 

Table I3: Ab Initio PBE0/def2SVP Chemical & Docking Results for the Interaction of Lopinavir with Covid-19 6M0J
	Compound	HOMO-LUMO energy gap (a.u.)	Docking iGemDock	Docking AutoDock - Vina (kcal/mol)
	lopinavir		-144.6062	-9.5

 

As it can be seen from Table I.1 the lowest HOMO-LUMO gaps at the PM3 level are observed for chloroquine, hydroxychloroquine and remdesivir. These molecules are the most reactive. However, the docking results for these three drugs show that remdesivir has the lowest binding energy and therefore the highest binding affinity for the receptor.

Amongst the drugs listed in Table I.1 the highest binding affinity for the protease of Covid-19 5R82 is shown by lopinavir (-9.0 kcal/mol), darunavir (-8.4 kcal/mol) and remdesivir (-8.0 kcal/mol) respectively according to Autodock Vina. Lopinavir appears to have the highest binding affinity for the receptor 6M0J.

Lopinavir also appears to have the highest affinity according to iGemDock (-130.843) while remdesivir is second (-129.661).

The ground state optimization of Lopinavir was also obtained using two ab initio methods STO3G/def2SVP and PBE0/def2SVP. The corresponding molecular structures obtained were tested with molecular docking to study their binding affinity with the receptor 6M0J (Table I.2 & I.3). As was expected even better binding affinities were observed. The most accurate must be considered the PBE0/def2SVP optimized and docked structure.

It is worth stressing that binding is not synonymous with inhibition. Even the most well bound molecule may have little effect on a protein if it targets the wrong site. One limitation of the work is the choice of binding site all the above drugs were tested against. This was constrained by the ligand used to stabilize the protein crystal structure.

 

---

 

Relevant Posts - Relevant Videos

A search to Medications to treat Covid-19 via Comput. Chem. methods and Molecular Docking

Drug Repurposing for COVID-19: in silico screening of known drugs against SARS-CoV-2 Spike protein

Drug Repurposing for Coronavirus (COVID-19): In Silico Screening of Known Drugs Against the SARS-CoV-2 Spike Protein Bound to Angiotensin Converting Enzyme 2 (ACE2) (6M0J). ChemRxiv. Preprint.

In Silico Drug Repurposing for coronavirus (COVID-19): Screening known HCV drugsagainst the SARS-CoV-2 Spike protein ACE2. Molecular Diversity (2022)

In Silico Drug Repurposing for coronavirus (COVID-19): Screening known HCV drugsagainst the SARS-CoV-2 Spike protein ACE2. ChemRxiv. Preprint.

 

---

References

1. M. A. Thompson, “Molecular docking using ArgusLab, an efficient shape-based search algorithm and AScore scoring function,” in Proceedings of the ACS Meeting, Philadelphia, Pa, USA, March-April 2004, 172, CINF 42.
2. O. Trott, A. J. Olson, "AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading", Journal of Computational Chemistry 31 (2010) 455-461
3. K. Hsu, Y. Chen, S. Lin,. et al. "iGEMDOCK: a graphical environment of enhancing GEMDOCK using pharmacological interactions and post-screening analysis" BMC Bioinformatics 12, S33 (2011).
4. J. Lan, J. Ge, J. Yu, et al. "Structure of the SARS-CoV-2 spike receptor-binding domain bound to the ACE2 receptor" Nature (2020). https://doi.org/10.1038/s41586-020-2180-5
5. K. Kalamatianos et al. " Drug Repurposing for Coronavirus (COVID-19): In Silico Screening of Known Drugs Against the SARS-CoV-2 Spike Protein Bound to Angiotensin Converting Enzyme 2 (ACE2) (6M0J). ChemRxiv. Preprint. " ChemRxiv. Preprint. (2020). https://doi.org/10.1038/s41586-020-2180-5
6. K. Kalamatianos et al. " In silico drug repurposing for coronavirus (COVID-19): screening known HCV drugs against the SARS-CoV-2 spike protein bound to angiotensin-converting enzyme 2 (ACE2)(6M0J)" Mol Divers (2022) https://link.springer.com/article/10.1007s11030-022-10469-7
7. F. Neese, “The ORCA program system” Wiley Interdisciplinary Reviews: Computational Molecular Science, 2012, Vol. 2, Issue 1, Pages 73–78.

---

 

Key Terms

covid-19,HOMO , LUMO,ground state optimization, medication for covid-19, drugs for covid-19, molecular docking, ab initio methods, computational chemistry, binding energy, binding affinity,