key: cord-0860753-c6qdf2bk
authors: Luis Vique-Sánchez, José
title: Potential inhibitors interacting in Neuropilin-1 to develop an adjuvant drug against COVID-19, by molecular docking
date: 2021-01-23
journal: Bioorg Med Chem
DOI: 10.1016/j.bmc.2021.116040
sha: a58b1de0772b9e3a657c0b6ad4785b060cc9a8c1
doc_id: 860753
cord_uid: c6qdf2bk

The COVID-19 pandemic continues without specific treatment. In this study it is proposed compounds that can be developed as adjuvant / complementary drugs against COVID-19. Through a search for molecular docking, for the development of a new drug using pharmacological compounds targeting the b1 region in neuropilin-1 (NRP1), which is important for the interaction with the S1 region of the S-Protein of SARS-CoV-2, to slow down the infection process of this virus. A molecular docking was performed using almost 500,000 compounds targeted to interact in the region between amino acids (Thr316, Asp320, Ser346, Thr349, and Tyr353) in NRP1 to determine compounds able to hinder the interaction with the S1 region in the S-Protein. In this study, ten compounds are proposed as potential inhibitors between S1 region in the S-protein of SARS-CoV-2 with the b1 region in NRP1, to develop a new adjuvant / complementary drug against COVID-19, and to hinder the interaction between SARS-CoV-2 and human cells, with a high probability to be safe in humans, validated by web servers for prediction of ADME and toxicity (PreADMET).

The COVID-19 pandemic continues today without a specific treatment, infections and deaths continue, 1 2 3 4 . In this pandemic, different treatments have been proposed, the development of new antivirals with different therapeutic targets, studies with therapeutic targets in RNA-Dependent RNA Polymerase (RdRp), Polyproteins (3CLpro and PLpro), Spike Protein (S-Protein) 5 6 and membrane fusion inhibitors 7 8 9 10 from SARS-CoV-2, as well as, there are works that use as therapeutic targets the interaction regions between RBD in the S-Protein and the ACE2 11 12 .

Studies aimed at describing the role of angiotensin-converting enzyme 2 (ACE2) as an entry receptor for SARS-CoV-2 have gone into this pandemic. There is current evidence that describes that there is a low expression of ACE2 at the pulmonary level, with a higher expression in the kidney and intestines, so there are proposals that there must be other mechanisms in the interaction process between the virus and the cell. Co-receptors / binding factors have been identified, such as neuropilins 13 14 15 16 . S-Protein of SARS-CoV-2 has been proposed to contain a furin cleavage site that has the potential to generate a C-terminus (CendR) which, according to predictions from molecular models, is capable of binding to the b1 domain in the Neuropilin-1 (NRP1) 13 17 . This could describe another component in the infectious process in COVID-19 and that there are variables in the population that cause a tropism in SARS-CoV-2, due to the presence in the cell membrane of the ACE2 and NRP1 proteins that they interact with the S-Protein. Therefore, Neuropilin-1 has taken a more important role in COVID-19 to develop studies that identify the impact on the infectious process of this disease.

Neuropilin-1 (NRP1) is a transmembrane glycoprotein expressed on the cell surface, multifunctional; NRP1 is present in various physiological processes, has been identified in various signaling and interaction functions with different ligands (as pleiotropic coreceptors), with various diseases including leukemia / adult T-cell lymphoma (ATL) 18 , as well as NRP1 works in several steps of the angiogenic cascade (with VEGF ligand binding) 19 20 ; to study the above, there are studies that demonstrate the role of NRP1 as a receptor and risk factor for developing viral diseases, such as those caused by the Epstein Barr Virus (EBV) and the Human Tlymphotropic Virus Type-1 (HTLV-1); in which it has been shown how NRP1 interacts directly with EBV 21 , and the NRP1 is a risk factor that favors the entry of EBV into nasopharyngeal epithelial cells (in which this type of cells has more expression of NRP1), as well as the relationship with a CendR interaction region of HTLV-1, which facilitates interaction with NRP1 and favors penetration into cells 18 22 23 , as well as S1 of SARS-CoV-2 Protein-S, showing that NRP1 can potentiate infection in the presence of other host factors 16 . Therefore, NRP1 is a therapeutic target that can have an effect in different diseases, there are reports of NRP1 inhibitors since the year 2000, using peptides, such as ATWLPPR 24 , in which favorable effects of its use in retinopathies, since it is related to an anti-angiogenesis effect 20 25 , but most of these peptides do not have important characteristics for the development of a drug, such as the Lipinski's rule 26 , since most of the peptides reported are above of 500 MW (example Ala-Thr-Trp-Lys-Pro-Pro-Arg: 855 MW), however the residues that are important for the interaction between these peptides with NRP1, as well as the concentrations for the IC 50 of these peptides in a range between 5.86 to 10.22 µM 27 , also antibodies against NRP1 have been proposed 20 28 , which shows that the development of molecules that impede the function of NRP1 is possible. Subsequently, the use of small molecules as inhibitors of NRP1 (EG00299) 29 , in which the concentrations and probable sites of interaction have been reported, which are also taken into account to carry out this study, for which the compound EG00299 has shown a selective inhibitory effect on NRP1 with some of its ligands 20 29 , in addition evaluating its effects in in vivo tests with cancer cells 30 and as a molecule to perform derivatives 31 (such as EG01377), in which they have reported the important residues to achieve the inhibitory effect and a range of concentrations used between 10 to 30 µM. Therefore, we use data from the references that use the compound EG00299 in NRP1 and its interaction with VEGF-A, there is an antagonist effect on NRP1 that inhibits the binding of VEGF-A, as well as, it was determined that it inhibited the interaction between the b1 domain with the S1 region of SARS-CoV -2, showing that the infectious process is hindered by the virus 14 15 17 32 , since this study seeks to develop an inhibitor (small molecule), which it can accomplish the Lipinski's rule 26 , because these molecules have better pharmacokinetic properties in comparison with peptide-based molecules.

It is reported the crystallographic structure of the interaction between NRP1 with EG00229 (PDB:3I97); which is demonstrating that the main amino acids important are: Thr316, Asp320, Ser346, Thr349 and Tyr353 in NRP1 to interact with EG00229, in which the same corresponding amino acids are identified when NRP1 interacts with VEGF-A 33 . Therefore, we used the crystallographic structure of NRP1 (PDB:2QQI) to carried out a docking directed to the region between amino acids: Thr316, Asp320, Ser346, Thr349 and Tyr353, using a library of compounds (EXPRESS-pick Collection from Chembridge Corp.) to select the compounds with the best binding average, to propose compounds that can be tested as adjuvants in the treatment against COVID-19.

Atomic coordinates of the NRP1 (Crystal Structure of the b1b2, domains from Human Neuropilin-1) were obtained from the Protein Data Bank (PDB: 2QQI). The structure was used as protein targets for docking procedures. The protonation and energy minimization of PDB file was performed using Molecular Operating Environment (MOE) software with the default parameters and the CHARMM27 force field 34 35 . We select one region to interact in NRP1 (T316, D320, S346, T349 and Y353) 14 15 17 .

The EXPRESS-pick Collection Stock screening library from Chembridge Corp. was used for docking 36 . This collection of compounds contains over 500,000 chemical compounds that fulfill the druggable properties of Lipinski's rules 26 37 and cover a broad area of chemical space, as well as, the structure of EG00229 to evaluate the interaction with NRP1 14 .

For docking, the receptors were kept rigid, while the ligand atoms were released to move to a maximal number of rotatable bonds. All crystallographic water molecules were deleted from the initial structures. High-throughput virtual molecular docking was carried out by means of the software AutoDock and MOE 36 38 , using default parameters (Placement: Triangle Matcher, Rescoring 1: London ΔG, Refinement: Forcefield, Rescoring 2: London ΔG, for each compound up to 100 conformations were generated).

The binding affinity of each complex (Ligand-protein) was estimated by the ratio of General Born vs Volume Integral (GB/VI), using parameters in MOE 39 40 . General Born or nonbonded interaction energies comprise Van der Waals, Coulomb electrostatic interactions and implied solvent interaction energies 40 .

The results of up to 30 confomers of each compound were used to select the best compounds, determining the best average ΔG binding value between NRP1 with each compound, as well as the standard deviation for each one, using the Excel software (Microsoft-365), the description of chemical properties by PhysChem -ACD/Labs 41 , the theoretical toxicity 42 , carcinogenicity and mutagenicity were considered 43 42 . The calculated interactions between NRP1 with each compound were visualized with Ligand-interaction interactions implemented in MOE.

For docking, we used 502530 compounds, and up to 100 conformers of each compound, interacting in the NRP1 (the region between amino acids: Thr316, Asp320, Ser346, Thr349 and Tyr353, Figure 1 ), the selection criteria of the best compounds was based on the calculation of the ΔG binding average of each compound, using the values of conformers (24 to 29 conformers), determining an average range from -7.72 to -8.11 kcal/mol -1 for the best compounds (Table 1, and details on the supplementary material Table S1 ). We selected ten compounds depicted here as N1 to N10 from the Express-pick Collection Stock from Chembridge library (ChemBridge Corp.) and the analysis of the interaction of each compound with NRP1 was carried out with the interaction report (Table 2 and details in Table S1 -S11). In addition, it was determined the average interaction for compound EG00229 and EG01377 (with reports of inhibitory effect between NRP1 with VEGF-A 29 31 and S-protein of SARS-CoV-2 32 ), with an average value of -4.95 kcal/mol -1 and -4.86 kcal/mol -1 respectively (interaction details in Table S1 and S12).

Afterwards, the theoretical toxicity for the ten compounds was evaluated with two websites (Prediction of Toxicity and PreADMET web server).

The description of the theoretical toxicity (Table S13) , ADME characteristics (Table S14) and chemical properties of each compound (N1 -N10, Table S15), are presented in the supplemental material. 

To describe the probable interaction sites between each compound (N1 -N10, EG00229

and EG01377) with NRP1, we analyzed up to 30 conformers of each compound with the better ΔG binding average values of interaction in the region between amino acids: Thr316, Asp320, Ser346, Thr349 and Tyr353 (Figure 1 ). From docking´s result (Table S2 -S12), we determined the main amino acids in NRP1 to interact with the ten compounds, these are Tyr297, Asn300, Trp301, Thr316, Gly318, Glu319, Asp320, Ser321, Arg323, Glu348, Lys351, Tyr353, Trp411, Thr413 and Gly414 for N1 -N10 compounds, and for EG00229 and EG01377 the amino acids:

Tyr297, Trp301, Gly318, Asp320, Glu348, Thr349, Lys351, Thr413 and Ile415 (Table 2 ). It is reported that Asp320 is very important for NRP1 to interact with different ligands and VEGF-A 29 33 , as well as for the CendR region in HTLV-1 18 22 23 and the SARS-CoV-2 17 , which is present in the analyzed interactions. (Table S2 and S3), as well as in the ten selected compounds, all the conformers demonstrate interactions of hydrogen bridge bonds with amino acids of the proposed potential site (average range from -7.72 to -8.11 kcal/mol -1 , Table   S2 -S11), and these interactions together are better than the determined by EG00299 and EG01377 compounds (average of -4.95 kcal/mol -1 and -4.86 kcal/mol -1 respectively, Table S12 ).

The details of the interaction between NRP1 with conformers of each compound are shown in the supplementary material ( Figure S1 -S11).

Today, the development of vaccines and drugs to attend the pandemic caused by SARS-CoV-2 is booming around the world. 8 9 10 11 45 46 47 , almost 1 year after the first work against COVD-19 began, there is still no treatment that demonstrates a therapeutic advantage, which shows the need for the development of drugs directed at a selective target that can alter the evolution of this disease.

As it was mentioned already, the amino acid Asp320 is very important for NRP1 to interact with different ligands and VEGF-A 29 33 , as well as for the CendR region in the SARS-CoV-2 17 32 , therefore, the region between the amino acids Thr316, Asp320, Ser346, Thr349 and Tyr353 has a very important role for the S1 region of SARS-CoV-2 to interact with NRP1; in this study was carried out a docking directed to amino acids in the b1 region reported in the NRP1 (Thr316, Asp320, Ser346, Thr349 and Tyr353) 17 , that is important to interact with the S-Protein (S1 region) of SARS-CoV-2 16 , since it has been shown that by preventing this interaction, the infectious process caused by this virus could be reduced 14 15 17 .

It was determined that the amino acids Tyr297, Asn300, Trp301, Thr316, Gly318, Glu319, Asp320, Ser321, Arg323, Glu348, Lys351, Tyr353, Trp411, Thr413 and Gly414 are important for the majority of the ten compounds to interact with the NRP1 (Table 2 ) and the chosen compounds have a better ΔG binding average value than the reference compounds (EG00229 -4.95 kcal/mol-1 and EG01377 -4.86 kcal/mol-1, Table S1), although this difference obtained theoretically, it does not guarantee that a better ΔG binding value of the chosen compounds causes a greater inhibition when comparing them with EG00229 30 32 . To justify the selection of these ten compounds, it is necessary to show that N1 -N10 compounds have a higher probability of

interaction with NRP1, according to the results of the docking, the EG00229 and EG01377 compounds, are less specific, since the 30 conformers and the 29 conformers respectively are interacting in a bigger region (Figure 2 , Table 2 and Figure S11 -S12), and if this is compared with the results of the conformers of the N1 -N10 compounds, these are interacting in smaller regions (as example N1 and N2 compound, Figure 2) ; therefore, the ten compounds proposed should have a better interaction, more specific, and it achieves a better ΔG binding value to each conformer, which is demonstrated in the ΔG binding averages of them (Table 2 and Figure S1 -S10). The development of new drugs requires a high investment of time and financial resources, so it is necessary to be able to offer potential drugs to development them, even if it is to start in a theoretical way, since this is already developing in the world 20 32 . On the other hand, there is still much to know about COVID-19, since the tropism that SARS-CoV-2 has, it is a challenge to understand it. NRP1 has become important to determine the evolution of the infectious process, since it has been identified that this protein can increase the degree of infection when it is present 14 15 16 17 . Therefore, evaluating the effect and control of NRP1 could generate new theories about the tropism of SARS-CoV-2.

Proposing NRP1 as a therapeutic target, and being able to develop a compound that has an interaction in the b1 region of NRP1, could help to develop drugs that can be complementary or independent to reduce the infectious process 14 For the selection of the compounds (taking into account the results of up to 30 conformers of each compound), these were also validated by two toxicity prediction web servers (Table 2 and Table S13-S14), since in previous works 48 49 50 , in our team work, we have correlated these theoretical results with experimental toxicity tests, in this way, it is proposed that these ten compounds have acceptable potential values, as well as a very low probability of toxicity. From theoretical toxicity results (Table S13) 43 , the compounds EG00299 and EG01377 are positive in the Ames-TA1535_NA test, conversely, the ten proposed compounds are negative in the same test, in addition the LD 50 determined ( Table 2) 42 for all compounds it is above 500 mg/kg, these results are important to propose that the compounds are probably safe for use in humans.

In the dosage of drugs, a synergy could be sought between compounds that are directed towards the regions that are important for the S-Protein of SARS-CoV-2 to interact with the cell, such as the ACE2 and NRP1 proteins, this could increase the effect therapeutic and reduce the infectious process of SARS-CoV-2. Using these ten compounds in combination with some of the compounds that are already proposed against ACE2 11 12 .

The compounds proposed do not have any specific registered use, nor a scientific article or registered patent, all the compounds are available at many laboratories to acquire them, to perform in vitro assays and to determine the effect on the interaction between NRP1-with Sprotein of SARS-CoV-2.

The neuropilin-1 (NRP1) is a multifunctional protein on the cell membrane, with an impact on physiological functions and diseases in the human organism 16 18 19 20 21 22 23 , for which for more than 20 years specific molecules have been developed that can inhibit/regulate some of its functions 20 24 25 27 28 29 30 31 , but they are still developments today and the NRP1 continues to demonstrate new signals/functions, which need further investigation. Therefore, the role of NRP1 in the infectious process of COVID-19 has taken on greater relevance 16 32 , since by being able to limit these functions on COVID-19, they could generate a disease with less impact on the human organism and this could help the immune system and being able to alter as it is known today, the natural history of the COVID-19 disease.

In this study are propose ten compounds with a high probability of interacting in the specific region in the NRP1 (Thr316, Asp320, Ser346, Thr349 and Tyr353), in order to develop a drug that could be complementary to COVID-19 treatments or as a drug that can limit the infectious process of SARS-CoV-2. Furthermore, these ten compounds have a high probability of being safe in humans, as they were validated by the PreADMET server (ADME and Toxicity Predictor).

Supporting information includes figures and tables of interactions for compounds with NRP1, as well as details of the interaction of each compound with NRP1 per amino acid, toxicity theoretical results, ADME characteristics and physical chemistry which support the information given in the results and discussion.

The author is very grateful for the financial support from PRODEP-SEP, SNI-CONACyT, GGF, FMM-UABC and Dr. José Manuel Avendaño Reyes.

The author declare, I have no conflict of interest. Table S13 . Toxicity -PreADMET | Prediction of ADME/Tox of compounds N1-N10 Table S14 . Table S14 : ADME -PreADMET | Prediction of ADME/Tox of compounds N1-N10 Table S15 : Properties predicted by PhysChem -ACD/Labs of compounds N1-N10

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Article title:

Author name:José Luis Vique-SánchezThe author declares that he has no conflict of interest.Signature : Jose Luis Vique-Sanchez