VIRTUAL SCREENING OF NOVEL HIV-RT NNRT INHIBITORS USING ZINC DATABASE

Received on 01 February, 2014; received in revised form, 22 March, 2014; accepted, 03 May, 2014; published 01 July, 2014

VIRTUAL SCREENING OF NOVEL HIV-RT NNRT INHIBITORS USING ZINC DATABASE

Rituraj*and Md. Tanweer Alam

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

HIV, reverse transcriptase, nonnucleoside reverse transcriptase inhibitor(NNRTI), rilpivirine, docking, Schrodinger Software

INTRODUCTION: HIV infection is continuing vital issue in way to health concerns, and current studies revels that it remains for a while globally, in the year 2009 over 40 million people were infected worldwide with HIV and the number keeps on growing ¹. Acquired immunodeficiency syndrome (AIDS) is one of the leading causes of death in the world ².  After rigorous multidisciplinary research worldwide successful development of vaccine is still elusive ³ Importantly when HIV particle infects a host cell its body enzyme reverse transcriptase (RT), an asymmetric 986-amino acids heterodimer) ² inside its large claw shaped active site, copies the viral single stranded RNA genome into a double-stranded viral DNA.

The viral DNA is then integrated into the host chromosomal DNA, which then instructs various host cellular processes such as transcription and translation to reproduce the virus. The above mentioned biological processes occurs in HIV virus through the intervention of various enzymes importantly for our research concern pivotal reverse transcriptase (RT), others are protease, integrase etc.

The main functionality of RT is generating the complementary DNA (cDNA) from an RNA template, a process known as reverse transcription. The RT in retrovirus transcribe their single stranded RNA genome into single stranded DNA and to subsequently construct a complementary strand of the first strand of DNA copy, providing a DNA double helix, capable of integration into host cell chromosomes. Functional HIV-RT is a heterodimer containing subunit of 66kDa (p66) and 51kDa (p51), p66 subunit contains two domains, the N terminal polymerase domain(440 residues) and the terminal RNase H domain (120 residues) p51 is processed by proteolytic cleavage of the polymerase domain of p66 can be described as a “right hand” that contains four subunit⁽(fingers, palm, thumb & connection) ⁴, the role of the p66 subunits is to carry out the activity of RT whereas it contains the active sites of the enzyme. The p51 is believed to play mainly a structural role ⁵. Concern to discover anti retrovirus drug like leads to prohibit better to its biological influence; currently highly active anti retrovirus therapy ^{6, 7} (HAART, always given as part of combination therapy) includes various classes of RT inhibitors, are using clinically, among that which bind directly to polymerase active site nucleoside inhibitors(NRTIs) and nucleotide RT inhibitors (NtRTIs) or adjacent to it causing an allosteric influence disabling polymerase activity (non-nucleoside RT inhibitors), globally extensive work is under screening by these routes, our work is along the last one. Meanwhile NNRTIs do not bind to the active site of the polymerase but in a less conserved pocket near the active site in the p66 subdomain. Their binding results in a conformational change ⁴ in the residues that bind DNA that block reverse transcriptase to its enzymatic performance to polymerization and prevent completion of synthesis of the double stranded viral DNA, thus preventing HIV multiplication

MATERIALS AND METHODS:

Rilipivirine: Rilpivirine is an anti-retroviral drug under the umbrella of RT inhibitors (2^nd generation), which is used for hindering the activity of the virus (RT). In the work herein Rilpivirine is taken as reference molecule and find out 1% of similar molecules of each retrieved files of zinc drug bank (sd file) using similarity coefficient “Tanimoto” in DS 2.5. In a single job around 1350 molecules was find out as similar as Rilpivirine, we performed as like 50 jobs and a total 50×1350 molecules we found out and perform docking in Schrodinger software.

TABLE 1: DIFFERENT PDBS(RT), LIGAND, CRYSTALLOGRAPHIC PROPERTIES AND MUTATION DETAILS

Reverse transcriptase: X-ray crystal structures of ligand-protein co-complexes have been important tools for medicinal chemists in the discovery, design, and optimization of drug candidates ^{8, 9, 10}. These structural data, along with the computational analysis tools that have been developed to implement structure-based drug design (SBDD), have proved to be very successful in medicinal chemistry.

As a greater number of X-ray crystal structures become available to medicinal chemists, with the advent of structural genomics ¹¹, 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 4KFB, 4GIQ, 4IFY, 4IG3 & 3BGR (see table 1) Pbd files from rcsb.org for reverse transcriptase as target having  complexed with inhibitor Rilpivirine (T-27) (2^nd generation NNRTI, a diarylpyrimide (DAPY) compound, a better bioavailable, soluble and easily formable as medicine then their precursors, approved by the FDA for HIV therapy in May 2011) ¹², Crystal structure analysis of HIV-RT enzyme showed that the rilpivirine filled up an allosteric hydrophobic pocket (nonnucleoside binding site, NNBS) and bound the enzyme in a “travelling spaceship- like” (Fig. 1) mode.

The lower base of that “spaceship”, dimethyl substituted phenyl ring is made of π-electron-rich moiety that interacts through π-π interactions with a hydrophobic pocket formed mainly by the side chains of aromatic amino acids (Tyr-181(A), 188(A), Phe227 (A) and Trp229(A)). On the other hand the upper-half of “spaceship” have a N-phenyl* substituted pyrimidine ring capable of donating and accepting hydrogen bonds with the main chain of the Lys-101(A) (hydrophilic); Tyr181(A), Tyr188(A), Val-106(A), 179(A),Pro-236(A),Leu-100(A), 234(A) they altogether create a hydrophobic pocket (Fig. 1a), rilpivirine in reverse transcriptase (4KFB.pdb) surrounded with amino acids residues are visualized (Glu- 38(B), Lys-101(A), 102(A), 103(A), 238(A), Pro-95(A), 225(A), 226(A), 236(A), Leu-100(A), 228(A), 234(A), Tyr-181(A), 188(A), 318(A), Val-106(A), 179(A), Ile-94(A), 180(A), Asp-237(A), Trp-229(A), Hie-235(A), Glu-138(A), Phe-227(A), Gly-190(A)), during complexation rilpivirine takes a position in NNBS hydrophobic pocket in RT and change its conformation to inhibit the enzymatic activity. Different chemical and structural features make different conformation possibility for the ligands in that pocket which induce desired phenomena. Meanwhile mutation has also considerable impact for drug activity, particularly, the NNRTI resistance reduces due to mutation of Tyr 181(A), and Tyr 188(A) which decreases the π-π interactions; the Gly 190(A) mutation leads to a lower active site space on the front of steric conflict between methyl side chain and the inhibitor, and the formation of a hydrogen bond between K103N(mutant) and Tyr188 reduces the inhibitor entering in the NNBS ¹³,mutations of some amino acids cause a variation of the NNBS pocket properties, thus decreasing affinities of most the inhibitors.

FIG. 1(A): RILIPIVIRINE DOCKED IN PDB KFB, (B) ITS INTERACTION DIAGRAM

In view of the above observations, the design of new NNRTIs require high conformational freedom to accommodate different steric conformations of NNBS and, at the same time, and must contain suitable chemical features capable of interact with highly conserved residues such as Trp229(A) (part of the “primer grip”) ¹⁴.   

EXPERIMENT: 4KFB, 4IG3, 4IF3, 4GI3 & 3BGRall these pdbs are prepared in protein preparation wizard of  maestro with following steps- preprocess(default settings), deleting all water molecules  and other structures except rilipivirine and generated it states, optimization , and minimization(with OPLS2005 forcefield) and saved all in pre created directory folder corresponding Grids are generated in these prepared pdbs with the centre defined by the co-crystalized ligand T-27(Rilipivirine) with default settings, ligands  as similar to rilpivirine with DS V2.5 in job “ find similar molecules”  with settings 1% similar molecules identification as similar to rilipivirine and similarity coefficient ‘tanimoto’ which is very well known accurate similarity measures, remaining are default. Similar ligands are prepared for docking jobs in ‘ligprep’ with deselected options ‘desalt’ and ‘generate tautomers’  and generate low ring conformations 100 per ligands using ‘epik’ and docked in corresponding grids of pdbs.

All docking calculations are performed using the “Extra Precision”(XP) mode of Glide Program with default settings including various rewards calculations, partial charge of ligands and similarity to T-27, all jobs were done on Intel i-7 3770K (unlocked) quad core machine with bios setting 4.5 GHz with GSkill 8GB RAM & Corsair H-70 liquid cooling system. Medicinal parameters were calculated using qikprop (Tables 2-6)

TABLE 2: PDB-4KFB) DOCKING SCORE AND OTHER CALCULATED PROPERTIES DETAILS

(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), SASA(Total solvent accessible surface area (SASA) in square angstroms using a probe with a 1.4 Å radius, RANGE- 300.0 – 1000.0), QPlogHERG (Predicted IC50 value for blockage of HERG K+ channels, concern below –5), QPlogBB(Predicted brain/blood partition coefficient, –3.0 – 1.2), QPPMDCK(Predicted apparent MDCK cell permeability in nm/sec, <25 poor, >500 great ), QPlogKp (Predicted skin permeability, log Kp, –8.0 – –1.0), 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)

TABLE:-3(4IG3)

TABLE:-4(4IF3)

TABLE:-5(4GIQ)

TABLE:-6(3BGR)

RESULT AND DISCUSSION: In our virtual investigation we find following ‘ZINC’ molecules close similar in docking score in comparison to T-27 , in different pdbs (see Table 2) (4KFB), 3(4IG3), 4(4IF3), 5(4GIQ)& 6(3BGR) but through our investigation a no of screened molecules are failed in its various medicinal properties, ZINC52690626, ZINC70032478 both having marginally better docking score then T-27 the interaction for later one is noticeable (Fig. 2, 3)) due to π-π interaction between the ethyl substituted phenyl ring with TRP-229(A) and one additional H-bond between amino substituted triazine with the GLU-138(B) both interactions are in considerable strength which may make some different, lipophilic nature (Lip) is also close similar to T-27, rtvFG (reactive functional group) better for ZINC52690626, QPPMDCK (Predicted apparent MDCK cell permeability (in nm)) value is more noticeable for ZINC52690626 which is very much better then T-70, the PHOAbs(Predicted human oral absorption) is also 100%. In Table-3, (4IG3) ZINC52690626 again showing much better QPPMDCK properties with good increment.

In Table 4, (4IF3) shows the same trend as previous, but in Table-5(4GIQ) we see that the docking score change marginally for ZINC52690626 and in Table-6(3BGR) ZINC70032481(-16.37), ZINC70032478(16.21), ZINC49391715(-15.65) ZINC70032479(-16.1), ZINC05298157(-15.75) & ZINC49391718(-15.57)

show better docking score, ZINC70032481, ZINC70032478 & ZINC49391715 all these have three reactive functional groups as the computed data showing which may be some drawback for such molecules since rilpivirine shows no any reactive functional group, but ZINC05298157, ZINC49391715 & ZINC49391718 are nearly to T-27 in docking scores and these showing no any reactive functional group, so these may be an advantage, we see that  all molecules (in Table 6 (3BGR)) are showing CNS(Predicted central nervous system activity) negative, lipophilicity in between (-7.89 to -6.43), rilpivirine is in top but these ZINC molecules are also close to it, since lipophilicity has very important impact  on drug  design procedure.

ZINC70032481 (Fig. 3.) interact with following amino acids LYS-101(A) with both donar and acceptor H-bonding and another H-bond donar by substituted amino group on triazine ring to GLU-138(B), π-π interaction between ethyl substituted benzene ring of the ligand to TRP-229(A) these four major interaction increased significantly D.S. compare to T-27,  computed CNS activity is normal, calculated properties in desired range the interaction are considerable in strength additionally its other calculated properties are also in desired limits, its PHOAbs (Predicted qualitative human oral absorption) is 100% and QPPMDCK(Predicted apparent MDCK cell permeability) is also much better then T-70 and dipole moment is in range.

The 3BGR have five mutations (K103N, K172A, K173A, Y181C & C280S) in this regard the increment in docking result is very well and noticeable and it may be more effective towards such mutants, which is more advantageous in this regard.

In 4KFB (Fig 2.), ZINC70032478(-15.5) interacts with LYS-101(A) (both hydrogen bond donar with secondary amino group and H-bond acceptor by triazine nitrogen,TRP-229(A) interact with π-π interaction with substituted phenyl ring and GLU-138(B) acts as H-bond acceptor . ZINC70032481(-15.37) also interacts with corresponding same amino acids, both are diastereomeric to each other, this outcome is very important to synthesis point of view, protonated ZINC52690626(-15.6) is showing some better docking score and showing interactions  with LYS-101(A) both donar and acceptor for H-Bonding and π-π interaction with LYS-103(A) and TYR-181(A), its protonation is activated by α-dimethylamino substitution on pyridine ring, which may prone to get protonated at stomach pH range and if it will happen, become an advantage, protonated pyridine ring interact by H-bonding  with TRP-229(A), all above three have lipophilicity between -7.1 to 7.0 which is almost near to T-27(-7.8) QPPMDCK (Predicted apparent MDCK cell permeability in nm/sec, <25 poor, >500 great ) is noticeable for  ZINC52690626 is 975.2  which is very well and PHOAbs is also 100% which QPlogKhsa (Prediction of binding to human serum albumin, –1.5 –  1.5) value is 0.607, for rilpivirine its 0.329 so better complexion to albumin, QPlogKp(Predicted skin permeability, log Kp, –8.0 – –1.0) is -1.36 which is  more than two time to rilpivirine rtvFG(no. of reactive functional groups) is none but showing some CNS activity, ZINC15880588 have very high QPPMDCK value, QPlogKhsa values is very low but PHOAbs value is 100%, ZINC05298157 also showing 100% PHOAbs value. So herein both less mutant and more mutant showing some noticeable computationally calculated properties.

FIG. 2: 4KFB (RT) WITH DOCKED LIGAND ZINC52690626, 70032478 & 70032481 AND CORRESPONDING INTERACTION DIAGRAMS (BELOW)

 FIG. 3: (A) 3BGR (RT) WITH DOCKED LIGANDS ZINC70032481, ZINC70032478, ZINC49391715, ZINC70032479 ZINC05298157 & ZINC49391718, CORRESPONDING INTERACTION PATTERN IN (B)

CONCLUSION: In this work, we have tried to recognized some more/similar potent drug like leads instead ‘Rilipiviine (T-70)’ which may be more effective, we used five different RT crystallographic structures for better identification/verification for our results, ZINC70032481, ZINC70032478, ZINC70032479, ZINC05298157 & ZINC52690626 are showing very 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”.

ACKNOWLEDGEMENTS: We are thankful to Will Richard, Raghu Rangaswamy and Vinod Dewarjee for providing the Schrodinger Suite software.

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How to cite this article:

Rituraj and Alam T. MD: Virtual screening of novel HIV-RT NNRT inhibitors using^, zinc database. Int J Pharm Sci Res 2014; 5(7): 2947-54.doi: 10.13040/IJPSR.0975-8232.5 (7).2947-54.

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