A COMBINATORIAL APPROACH TO IDENTIFY NOVEL HIV-PROTEASE (WILD AND MUTANT) INHIBITORS (PIs) USING ZINC DRUG DATABASE

A COMBINATORIAL APPROACH TO IDENTIFY NOVEL HIV-PROTEASE (WILD AND MUTANT) INHIBITORS (PIs) USING ZINC DRUG DATABASE

K. K. Srivastava¹, Shubha Srivastava ², Tanweer Alam ¹ and Rituraj ^*1

Department of Chemistry ¹, Vinoba Bhave University, Hazaribagh, Jharkhand India

Department of Chemistry ², KBW College, Hazaribagh, Jharkhand, India

ABSTRACT: The Human immunodeficiency virus type-1 protease is one of the most important target to highly active anti retrovirus therapy(HAART) for the treatment of all acquired immune deficiency syndrome(AIDS). Protease inhibitor “Darunavir” is most recently included as a PI in the list of HARRT(highly active anti retrovirus therapy), more effective against mutant and wild type simultaneously of Protease with increased no. of H bonding then precursors approved by FDA, So herein we have taken Darunavir as a base structure for virtually identification of more/similar efficient drug like leads then Darunavir using ten different PDB structures (3EM6, 3OXW, 3BVB, 3CYW, 3D1Y, 4DQB, 4DQH, 4DQE, 4DQF, 4DQC & 3EKT) of Protease from PDB database ‘RCSB’ versus chemical compounds database ‘ZINC’ using Schrodinger and Discovery Studio software. Using molecular constraint search with similarity coefficient ‘Tanimoto’, 1,65,000 ligands were extracted and docking analysis were resulted some efficient in docking and in other computational medicinal parameters, we are reporting such lead molecules, and they may further undergo through high end extensive virtual investigation and beyond..

HIV, Protease inhibitors(PIs), Darunavir, docking, Tanimoto, Schrodinger

INTRODUCTION: Human immunodeficiency virus (HIV) Is a retrovirus that causes acquired immunodeficiency syndrome (AIDS), a condition of immunity to fail in human body to begin life threatening Infections lifelong. Presently acquired immunodeficiency syndrome(AIDS) is one of the leading cause of death in the world ^{1, 2}. After rigorous multidisciplinary research worldwide successful development of vaccine is still elusive (Human immunodeficiency virus type-1 protease(HIV-1 PR), a catalytic protein, in a role to cleaves the Gag and Gag-Pol viral poly-proteins, allowing the virus to efficiently infect new host cells. The HIV-1 PR, encoded in the 5’ end of the pol gene, is expressed as part of the gag-pol poly-protein. This gene encodes a 99 amino-acids protein.

Homodimeric of this protein, i.e. protease is a C2- symmetric enzyme consisting 99 amino acid monomer. Each monomer contributes an aspartic acid residue that is essential for catalysis ³. The two chains of this homodimer form a tunnel with a ‘flap” from each protein chain helping to secure the poly-protein in place ³. The Darunavir and many others inhibitory drugs interact with amino acids in between these dimeric protein flaps.

In HIV-1 Protease inhibitors (PIs) target to disruptanessential function in the life cycle of HIV to breaking up the viral polypeptide into components that can be used to form mature virus particles⁴. Darunavir and other PIs act as non-covalent inhibitor of HIV protease and compete with the natural substrate to occupy the active site. When a protease inhibitor binds, the HIV life cycle is halted as the protein components for new viral particles are not able to produce³, on this background we induce this work to find out more potent PIs as similar Darunavir like leads against mutant and wild with same efficiencies simultaneously.

Darunavir:

Darunavir is an anti-retroviral drug under the umbrella of Protease inhibitors, which is used for hindering the activity of the virus protease. In the work herein Darunavir is taken as reference molecule and find out 1% of similar molecules of each retrieved file of zinc drug bank(sd file) using similarity coefficient “Tanimoto” in D.S. 2.5 in a single job around 1390 molecules was find out as similar to Darunavir, we performed as like 118 jobs and a total 118x1390 molecules we found out and then perform docking with glide program of Schrodinger.

TABLE:1

Protease:

The HIV-1 protease is one of the most important target for antiretroviral therapy used in the treatment of AIDS, this HIV protein has an important key role in viral replication cycle as a catalytic protein. The chemical activity of the HIV-1 protease depends on the two residues in the active site, Asp 25, Asp25’, one from each copy of the homodimer. Darunavir interacts with these catalytic aspartates and surrounding backbone of the active site through hydrogen bonds, specifically binding to residues Asp29(B), Asp 30(B), Asp 30(A), Asn 25(B) and Gly27(B). This interaction prohibits viral replication as it competitively inhibits the viral polypeptides from gaining access to the active site and strongly binds to the enzymatic portions of this protein.

Protease inhibitors(PI) were developed to inhibit cleavage function of HIV-1protease by mimicking the reaction intermediates that arises during the hydrolysis of the substrate, disabling the enzyme to cleave the Gag and Gag-Pol viral polyproteins,   mutagenic X-ray crystallographic co-complexes ligand-protein structures have been important tools for medicinal chemists to the discovery, design, and optimization of drug candidates ^{5, 6, 7}. These structural data, along with the computational analysis tools that have been developed to implement structure-based drug design (SBDD), in in-vitro analysis high cost and the extensive time frame requirement to find out drug like leads necessarily important, but it make it still impractical to use these conventional methods to evaluate the effect of each mutation in view of the genetic background of HIV-1 protease. In this context computational methods are growing up as a very important tool to medicinal chemist and now popularity of such methodology seeing on floor, fast up-gradation in computation algorithm and better Hardware availability by day, and easy to use, improve the screening analysis much easier, revealing the role of individual mutation and its impact on the protein function, proved to be very successful in computational medicinal chemistry.

As a greater number of X-ray crystal structures become available to medicinal chemists and with the advent of structural genomics ⁸, computational methods that take advantage of protein-ligand structural data are becoming more critical to the drug design process, in this regard we retrieved following 3EM6, 3OXW, 3BVB, 3CYW, 3D1Y, 4DQB, 4DQH, 4DQE, 4DQF, 4DQC & 3EKT (see Table 1) Pbd files from rcsb.org for Protease as target having co-crystalized with inhibitor Darunavir (most recent HIV protease inhibitor to reach the market in 2009) HIV-1 protease is one of the most important drug able target in new drug candidate, a nonpeptidic analogus of Amprenavir, at the critical change at the terminal tetrahydrofuran (THF) group. Instead of a single THF group, Darunavir contains two THF group fused, form a bis-THF moiety which makes it more effective than Amprenavir. Protease inhibitors restrain the viral maturation by inhibiting the functional and structural proteins formation in virus so HIV produced immature, non-infectious. A single mutation in gene of HIV-PR cause double mutation in enzyme since HIV-PR is homodimeric protein, containing 99 amino acids in each chain with an active site located at the dimer interface.The crystal structure analysis shows  HIV-PR docked with Darunavir in the surrounding pocket of amino acids-Asp-25(A), 30(A), 29(A), 129(B), 130(B), Ala-28(A), 128(B), Gly-48(A), 49(A),  127(B), 148(B), 27(A), 149(B), Leu-123(B), 23(A), Ile-150(B), 182(B), 184(B), 132(B), 50(A), 82(A), 84(A), 32(A),  Ser-31(A), Met-76(A),  Thr180(B), Val-47(A),, 147(B), Ash-125(B), Arg-8(A), Pro-181(B), 81(A), from literature these amino acids constitutes three regions; catalytic-core(Asp-25(A), Gly-27(A), Ala-28(A), Asp-29(A) and Asp-30(A), flap (Ile-47(A), 54(A), Met-46(A) Phe-53(A), Gly-48(A) ,49(A) 51(A), 52(A) and Ile-50(A)) and the C-terminal region (Pro-81(A), Ile-84(A)). According to literature, Asp-25(A), Gly-27(A), Ala-28(A), Asp-29(A) and Gly-49(A) are known to be highly conserved residue in which a potential protease inhibitor bind effectively.

Experiment: All following steps- preprocess(default settings), deleting all unnecessary water molecules and other structures except Darunavir, added hydrogen, generated it states, optimization, and minimization (with OPLS2005 force field)with default constraint of the 0.3Å of RMSD and corresponding Grid are generated in these prepared pdbs with the centre defined by the co-crystalized ligand Darunavir with default settings included partial charge and saved all in pre-created directory folder. Ligands extracted as previously mentioned procedure as similar to Darunavir with DS V2.5 in job “ find similar molecules”  with settings 1% similar molecules to ‘Darunavir’ with similarity coefficient ‘tanimoto’ which is very well known accurate similarity measures, remaining are almost default. Similar ligands are prepared for docking jobs in ‘ligprep’ with force-field OPLS2005 using epik with deselected options ‘desalt’ and selected ‘generate tautomers’ and finally with the ligands whose docking score more than Darunavir selectively prepared in ‘ligprep’ with force field OPLS 2005 using ‘ioniser’ with included setting as previous, generate default no. of low ring conformations and all combination in default no. and were docked in corresponding grid of pdbs. All docking calculations were performed using the “Extra Precision”(XP) mode of Glide Program with settings including sampling ligands ‘flexible’, optionally available various protocols for ligands constraints as rewards measure, partial charge of ligands and similarity measures to ‘Darunavir’ were included, sometime ionized state of ligand (deprotonated/protonated) marginally make influence on the docking scores, sometimes they appear lift up the scores up to the 2 units or more; due to interactions get elevated. All jobs were done on Intel i-7 3770K (unlocked) quad core machine with bios setting 3.9-4.4GHz with G Skill 8GB RAM & Corsair H-70 liquid cooling system. Medicinal parameter were calculated using programme qik prop (table-2-6)

RESULTS AND DISCUSSION: In our virtual investigation we find the ZINC59485580(“L”)(((2S,3R,4S,5R,6S)-3,4,5,6-tetrahydroxytetrahydro-2H-pyran-2-yl)methyl L-phenylalaninate) molecule is very fine in docking calculation(-15.34, see Table-3BVB) having 2.5 unit more than to Darunavir(“DAR”, -12.63) which is likely appreciable to this work.

In other mutant state of protease (see table- 4DQB, 3OXW, 3CYW, 3D1Y, 4DQC, 4DQE, 4DQH, 3EM6 & 3EKT) the D.S. of “L” and other combinatorial structures are better than “DAR”. The interactions diagram of ZINC59485580(”L”) (Fig1.1(d) showing very strong interaction network within the protease grid cavity, in the interaction diagram the amino group of phenylalaniate part of the molecule doubly Hydrogen bond (NH₂) donar to ASN(asparagine):25(A) & 25(B), ASN-25(B) also play H-Bond donar to esteric carbonyl of phenylalaninate, and hydroxyl(“6S”) group at 6^th  position on (2H)-pyranyl ring to GLY:27(B) and ASP:29(B) respectively also ASP:29(B) play as H-Bond donar to “6S” Hydroxyl group another one to “5R” Hydroxyl group in addition. These all interaction network make very efficient binding to grid cavity of ZINC59485580. Computed medicinal parameters are not comprehensively supportive, the computed lipophilicity(lip) below to the bottom level, on the another hand, QPPCaco (Predicted apparent Caco-2 cell permeability in nm/sec. Caco-2 cells are a model for the gut blood Barrier, predictions are for non-active transport) and QPPMDCK (Predicted apparent MDCK cell permeability in nm/sec. MDCK cells are considered to be a good mimic for the blood-brain barrier) are also at lower level but QPlogBB (Predicted brain/blood partition coefficient) is in required limit.

Herein in ZINC59485580, we  have tried for some modification in its structure by substitution, addition with some appropriate organic moieties, and hetero atom exchange in appropriate sites, outcome of docking of such combinatorial prepared ligands gives some necessary relief in lipophilicity, which is one of the important necessities to identification as a drug like leads, but mentioned above two parameters were remain below to necessities, but all reported molecules are showing computed CNS inactive and computed brain/blood partition coefficient is much supportive to as drug like lead. The importance of the outcomes is that the binding efficacy of all listed molecules are more than Darunavir in docking score in all Pdbs either wild and in various different mutated state Pbds. Entry in each table (3BVB, 4DQB, 3OXW, 3CYW, 3D1Y, 4DQC, 4DQE, 4DQH, 3EM6 & 3EKT) from third row are modified structures of ZINC58485580 and its various properties are tabulated in the table for corresponding Pdbs structures. All modified structures (Fig 1.3) are showing good binding affinity with increased lipophilic nature.

TABLE: 3BVB

(D.S. (Docking Score, kcal/mol), Lip (Lipophilicity), rtvFG (no. of reactive functional groups, 0 – 2), CNS (Predicted central nervous system activity on a –2 (inactive) to +2 (active) scale), Dipole(computed dipole moment, 1.0 – 12.5), donarHB (Estimated number of hydrogen bonds that would be donated by the solute to water molecules in an aqueous solution. Values are averages taken over a number of configurations, so they can be non-integerm, 0.0 – 6.0), accptHB (Estimated number of hydrogen bonds that would be accepted by the solute from water molecules in an aqueous solution. Values are averages taken over a number of configurations, so they can be non-integer, 2.0 – 20.0), QPPCaco(Predicted apparent Caco-2 cell permeability in nm/sec. Caco-2 cells are a model for the gutblood barrier. QikProp predictions are for non-active transport, <25 poor, >500 great), QPlogBB(Predicted brain/blood partition coefficient, –3.0 – 1.2), QPPMDCK(Predicted apparent MDCK cell permeability in nm/sec. MDCK cells are considered to be  a good mimic for the blood-brain barrier.  QikProp predictions for non-active transport <25 poor, >500 great; metab (Number of likely metabolic reactions, 1-8), QPlogKhsa(Prediction of binding to human serum albumin, –1.5 – 1.5 ), PHOAbs(Predicted human oral absorption on 0 to 100% scale, >80% is high, <25%ispoor)

4DQB

3OXW

3CYW

3D1Y

4DQC

4DQE

4DQH

3EM6

3EKT

CONCLUSION: In this work, we have tried to recognized some more/similar potent drug like leads instead ‘Darunavir’ with effective binding capacity, we have used ten different RT crystallographic structures with either different mutagenic level or wild type for better identification/verification for our results,  modified and original structure showing  effective binding capacity to respective grid cavity of protease, showing some  fine computed properties, therefore, this study verify the importance of small drug like molecules libraries as like ‘ZINC. docking.org’and their use certainly help scientific groups to enhance their capabilities in drug discovery with reducing time, including drug discovery process prior synthesis. Herein identified molecules may further investigate instead “in silico” the more advanced level to the work needed in forward to look much better.

ACKNOWLEDGEMENTS: The authors wish to thank with proud and privilege to Will Richard, Raghu Rangaswamy and Vinod Dewarjee of Schrodinger ltd. for providing the Schrodinger Suite Software.

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How to cite this article:

Srivastava KK, Srivastava S, Alam T and Rituraj:  A Combinatorial Approach to Identify Novel HIV-Protease (Wild and Mutant) Inhibitors (PIs) Using Zinc Drug Database. Int J Pharm Sci Res 2015; 6(7): 2926-35.doi: 10.13040/IJPSR.0975-8232.6(7).2926-35.

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