International Journal of Scientific & Engineering Research, Volume 5, Issue 12, December-2014 1608

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HIV-2 Reverse Transcriptase Using Chemical Similarity

Process of Reducing Viral Attack and Increasing CD4

Counts in HIV-Infected Patients

Jerwin prabu.A, Dr. Manimegalai.P, Abbiramy.S.S, Jenifer.S

Abstract— The aim of this Research is to examine the Chemical processes focused to reduce viral attack and increasing CD4 counts, HIV viral load after initiation of combination antiretroviral treatment. However by purchasing and assaying of selected top-scoring compounds from the library active anti-HIV agents are created. Subsequent synthesis and assaying of S10087 analogs proposed by further computational analysis yielded anti- HIV agents. Thus, with the aid of computational tools, it was possible to evolve a false positive into a true active. Antiretroviral treatment–naive, chronically HIV-infected persons (n = 1376 and n = 1605 for each of the 2 cohorts) are untreated. During the observation period (5 months), at least 1 HIV RNA level and 2 CD4 cell counts may be stable. Approximately 35% were nonwhite, and 45% had risk factors. Currently, the data would generally support initiation of HAART in patients with CD4 cell counts more than 350 cells/µl. However, from the strong potential for confounding in observational studies and the lack of adjustment for lead- time bias in many analyses, it is not possible to rule out possible long-term detrimental effects of earlier use of HAART. In chemical process we can use these chemicals and it is possible to reduce the critical bond in HIV virus and increase the amount of CD 4 counts.

Index Terms— HAART, CD4 cell, cART, NA-ACCORD, S10087, Phenyl ting, Moderate electrophile, Antiretroviral Treatment

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1. INTRODUCTION

HIV/AIDS has caused more than 35 million deaths since 1973, and an estimated 64.2 million people are currently HIV- positive. Despite the availability of the highly active antiretro- viral therapy (HAART), 3 million HIV/AIDS-related deaths occurred in 2004. The target for the first three drug classes is HIV-1 reverse transcriptase (HIV-RT), which is vital to replica- tion of the HIV-1 virus by converting its single-stranded RNA into a double- stranded DNA. HIV-RT is a 1000-residue heter- odimer consisting of 66-kDa (p66) and 51-kDa (p51) subunits. Participants Antire tr ovira l treatment–naive, chronical- ly HIV-infected persons (n = 1376 and n = 1605 for each of the 2 cohorts) untreated during the observation period (5 months) and with at least 1 HIV RNA level and 2 CD4 cell counts available. We consider recent data to support the arguments for and against earlier initiation of HAART in patients with CD4 cell counts more than 350 cells/µl. The factors, as yet undefined, likely drive CD4 cell losses in HIV infection. These findings have implications for treatment decisions in HIV infection and for understanding the pathogenesis of progressive immune deficiency

2. BACKGROUND AND SCOPE OF REVIEW

The main effect of HAART is to suppress viral replication, allowing the individual's immune system to recover and pro- tecting him/her from the development of AIDS and death, treatment should be initiated at an early point in the individ- ual's course of disease, prior to a time when CD4 cell loss is such that there is substantial risk of clinical progression. On the basis of evidence that clinical progression rates were low while the CD4 cell count remained above 200 cells/µl but increased rapidly at lower levels, most early treatment guide- lines recommended that treatment be delayed until the CD4 cell count had fallen below 200 cells/µl. In addition to their
role as predictors of the clinical outcomes of HIV infection, CD4 cell count and plasma HIV RNA level are commonly used as markers of the success of highly active antiretroviral therapy (HAART). To sup- press viral replication so that the VL is below the level of detection w it h standard a s- sa y s is thus one of the aims at the start of a ntire tr oviral treatme nt. HIV-infected pa t i e n t s in most developing countries have limited second and third line antiretroviral treatment options. In many countries i n Asia, second-line com b ination antiretroviral treatm ent (cART) is not widely accessible.

3. METHODS AND ANALYSIS

The data were collected: patient baseline data, CD4 and CD8 count, HIV VL level, prior and new AIDS de- fining illness (ADI), date and cause of death, prior and current prescribed HAART, and reason for treatment change. CD4 count was calculated by linear regression with the values at time T, before T, and after T, and was expressed as changes of cells per micro liter (µL) per year. The HIV VL was related to the CD4 count slope at time T. Preliminary analyses in eligible TAHOD patients showed that the mean CD4 count slope was significantly higher in the f irst 6 month s af ter cART initiation than in the period afterwards (179 vs. 44 cells/µL per year, p <
0.001). The CD4 slopes were therefore calculated from CD4 counts measured 6 months a f t er cART initiation. We did not include CD4 count and HIV VL at baseline for the f ollowing three reason s: f irst, a large p rop o rti on of patients did not have the tests at treatm ent initia- tion (approximately 25% of patients had no CD4 count and 45% HIV VL, Table 1); second, the model aimed to help clinicians in this region to assess the status of im-

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mune system with the clinical information at hand (e.g., age, hepatitis status, cu rrent CD4 count, time since treatment initiation, etc) where the baseline in- formation on CD4 count and HIV VL may not be read- ily available; and third, when we included baseline CD4 and HIV VL in a sensitivity analyses based on the subset of patients with baseline data available, the results re- mained com- parable with the model without the base- line CD4 count and HIV VL. The multivariate models were built using a forward-step approach, the final model included covariates that remained significant at the
0.20 level. Non- significant variables were also present- ed and adjusted for in the final multivariate mo d e l s. Fi- nally, sensitivity analysis was also performed by restrict- ing th e records in patients contributin g at least 4 or more concurrent CD4 and HIV VL tests. The intermolecular struc- tural similarity can be measured through distance and associ- ation coefficients. Association coefficients are used with real- value descriptors or binary data, and are often normalized to lie within the range of zero (no similarity at all) and unity (identical sets of descriptors). The crystal structures for HIV- RT complexes with the inhibitor UC-781 (PDB ID: 1rt4) and the K103N variant complexes with the inhibitor TMC-125 (PDB ID: 1sv5). The top ranked compounds obtained in this way were redocked and rescored using the Glide extra- precision (XP) mode. Plasma HIV-2 RNA levels were meas- ured using either the Amplicor HIV-1 Monitor assay or the branched DNA assay, and all values were standardized to their branched DNA equivalents. The CD4 cell counts were measured by flow cytometry using standardized methods; specific instruments varied according to the institution. De- scriptive and other basic statistics were computed using In- tercooled Stata, version 8.0 (Stata Corp, College Station, Tex). To assess the association between plasma HIV RNA concen- tration and CD4 cell change, we used random-effects linear models (PROC MIXED, SAS software v.8.2; SAS Institute Inc, Cary, NC) assuming an un- structured correlation structure. We used log10-transformed values of plasma HIV RNA in all analyses. To determine the extent to which inter individual variability in CD4 cell change was explained by presenting HIV RNA measurement, a single value at explaining inter individual variability in CD4 T-cell change, we used a similar approach to generate model-based estimates of HIV RNA change per individual and regressed these estimates on model- derived individual rates of CD4 cell loss. Besides the protein energies, the energy-minimized structures for the complexes provided the intra molecular and salvation ener- gies for the ligands in the protein environment. In the bound state, it was assumed that there is only one conformation acces- sible to each ligand; its conformational entropy is therefore zero. This approximation should be revisited, though it may requMHire a conformational search in the bound state.

4. THE CURRENT EVIDENCE FOR AND AGAINST EARLIER INITIATION OF HAART AND MODIFICATIONS OF S10087

The main argument for delaying HAART related to the tox-
icities and inconvenience of these drugs and the fact that treatment was likely to be life-long. It was felt that patients would be unable to maintain the high levels of adherence that are required for successful outcomes. Given the perceived low risk of AIDS and mortality at CD4 cell counts more than 350 cells/µl, it was thought that little would be gained by exposing patients to antiretroviral therapy too soon. There is limited evidence to support an increased frequency of toxicities in those starting HAART with higher CD4 cell counts. The risk of non-Hodgkin's lymphoma was more than twice as high (adjusted hazard ratio of 2.28) in non- HAART users with CD4 cell counts of 200-349 cells/µl com- pared to those with counts ≥350 cells/µl. The risk of serious non-AIDS diseases was also significantly lower in the imme- diate arm. Which differ by replacement of the 4-methyl group with 3-fluoro (S10076), 3-chloro, 4-methyl (S10085), and 2, 4- dichloro (S10089). After purification, they were submitted to an anti-HIV assay using infected human T-cells, but they failed to inhibit HIV replication in the MT-2 cells at concentra- tions up to 100 µM.

5 CHEMICAL SIMILARITY SEARCH AND PROCESS

These four different solutions that minimize the HIV complex bond viral factors simultaneously were obtained, specifically

62% and 54% for the Euclidean and Tanimoto coefficients, respectively. In each solution, the Euclidean and Tanimoto coefficients have identical sets of descriptors, whereas the de- scriptors for the first are weighted. We used two chemicals for the HIV-I reverse transcriptase process. They are oxalamide linker and tetra methyl piperidine. In oxidation process can use H2N; but it is a triple bond highly react able chemical. In this chemical progress (CONH2)2 gets oxidized from hydrogen cyanide to cyanogens. These chemicals cause reaction with body fluids in a fraction of second and also it will block the hydrogen molecules in our body cells. Hence we use is called oxalamide linker and due to which single bond NH and double bond oxide is formed. For the HIV-2 reverse transcriptase pro- cess; we are adding P- substituted phenyl ring with these two chemi- cals.

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Fig.1. Chemical similarity process in reactive bond higher order chemical reaction

Please note that math equations might need to be reformatted from the original submission for page layout reAs a link Br is add- ed to P substituted phenyl ring. P denoted Para. It is used for purpose of producing cl. Why we do not go for Meta and ortho is that it pro- duces nitric. Phenyl is a normal chemical. Phenyl ring has a high bond and hence, it cannot be destructed. When HIV virus attacks phenyl ring; chlorine gets produced. The molecules in the chemicals are ar- ranged in the form of chair confirmation. According to genetics and the pattern used for chair confirmation is T257, G473, S375, E370, G429, N425, and W427. These chair confirmation keeps on changing. Phenyl is produced from benzene (C6H5). Phenyl groups tend to resist oxidation and reduction. It is used to lower cholesterol in people with hyper cholestrolaemia. Considering normal chemical reaction as base; if weak nudeophile and moderate electrophile are added; no reaction occurs. Considering the previous reaction; weak nudeophile is re- placed by bromo benzene and p substituted phenyl ring is added. Similarly moderate electrophile is replaced by oxalamide linker and tetra methyl piperidine. During the chemical similarity process Para isomers substitute bromo benzene phenyl ring reacts with HIV virus and hence chlorination occurs for 55-65%. So this chemical process acts as an antibiotic and it will reduce the critical bonding of HIV chemical bond. After that we will calculate CD4 counts. MW (molec- ular weight), FOSA (the hydrophobic component of the total solvent accessible surface area (SASA)), FISA (the hydrophilic component of SASA), and HB donor (number of hydrogen bonds donated by the solute to water molecules), appear in all solutions. The amino group in 23p and 23o is responsible for the larger de salvation and intra molecular penalties, but pro- vides a more favorable electrostatic interaction with the en- zyme due to hydrogen bonding with the Glu138 carboxyl ate group. The pyrimidine and the diarylamino nitrogens are now hydrogen bonded to the backbone nitrogen and oxygen atoms of Lys102, while the amino group of TMC-125 is no longer hydrogen bonded to Glu138. In spite of that, the activi- ty of TMC-125 is not significantly affected by the K103N mu- tation.

Fig.2. Energy-minimized complexes structure for chemical similarity process.

5.1 PROCESS OF CD4 COUNTS AND TREATMENT RESPONSE OF DIFFERENT CD4 LEVELS

In particular, reported that only 20, 26, and 46% of those starting HAART with CD4 cell counts of less than 50, 50-
200, and 200-350 cells/µl reached a CD4 cell count more than
800 cells/µl after 7 years of uninterrupted HAART compared
to 73 and 87% of those starting HAART with CD4 cell counts
of 350-500 and ≥500 cells/µl. It is important to consider that
there may be a CD4 cell count 'ceiling' above which an indi-
vidual's CD4 cell count is unlikely to rise - this may result in
an inverse association between the pre-HAART CD4 cell
count and CD4 increases. Thus, immune activation may be a
major determinant of T-cell turn- over and CD4 cell deple-
tion in chronic HIV infection both in human and animal
hosts. Our results provide further support for additional
studies exploring the relative contribution of immune acti-
vation to the pathogenesis of immune deterioration in
treat ment- naive, HIV-infected persons. Recently, investiga-
tors from the North American AIDS Cohort Collaboration
on Research and Design (NA-ACCORD) group reported
that initiation of HAART at a CD4 cell count between 350
and 500 cells/µl was associated with a 70% improvement in
survival compared to starting HAART at lower CD4 cell
counts; the authors also used methods to take account of
lead-time bias. The below slope was associated with age (-
5.7 cells/µL per year per 10-year age increase, p = 0.013),
concu rrent HIV VL (-42.1 per 1 log10 copies/mL VL
increase, p < 0.001), concurrent CD4 count (+1.9 per 100
cells/µL increase), disease stage (compared to CDC cat-
egory A illn esses: +29.2 if diagnosed with tuberculosis
[TB] with or without other ADI, p < 0.001; +15.7 if diag-
nosed with non-TB ADI, p = 0.011), hepatitis B or C co-
infection (-21.3 if co- inf ected, p = 0.007), and time since
cART initiation (compared to CD4 slope during 6-12

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months: -23.8 during 12-18 months, p = 0.130; -39.5 during
18-24 months, p = 0.005; -64.8 at 24 months or later, p <
0.001). The CD4 counts c ont i nu e s to increase with HIV
VL up to 5 000 copies/mL during 12 -18 m o nt hs af t er
cART. If this patient was hepatitis co-infected, the CD4
count s ta r ts to fall when the HIV VL increases up to 3
000 copies/mL .

6. RESULT AND DISSCUSSION

1378 to 1605 naïve patients initiated cART, and had three or more concurrent CD4 and HIV VL data pairs available beyond 6 months a f t er cART initiation. After cART initia- tion, viral logical suppression (HIV VL < 400 copies/ mL) was achieved in 83% of patients at 6 month a nd

82% in 12 months. Table shows the random- ef f ect linear

Difference*

Univariate

(95% CI) p value Difference*

Multivariate**

(95% CI) p value

Sex

Male* 0.0 0.0

Female 8.6 (0.1, 16.7) 0.039 8.9 (-1.7, 15.1) 0.097

Current age

per 10 years older -7.3 (-16.2, -3.1) 0.001 -5.7 (-14.4, -2.0) 0.013

Disease stag e

CDC Category A* 0.0 0.0

TB with or without other ADI 27.5 (17.2, 38.3) < 0.001 29.2 (15.6, 39.9) < 0.001

Hemoglobin level

Non-TB ADI(s) 5.3 (-7.2, 15 .3) 0.423 15.7 (3.5, 23.2) 0.011

per 1 g/dL higher 0.0 (-0.0, 0.1) 0.661 0.0 (-0.0, 0.1) 0.689

Concur rent CD4 count

Per 100 cells/μL higher 2.1 (-0.4, 4 .0) 0.321 2.9 (0.2, 4.7) 0.224

Concurrent viral load

per log10 copies/mL higher -42.3 (-51.8, -37.5) < 0.001 -42.1 (-51.3, -36.7) < 0.001

Hepatitis B or C co infection

No* 0 0

Yes -23.7 (-37.3, -7.6) 0.005 -21.3 (-34.9, -5.1) 0.007

Time since cART initiation

> 6 to ≤ 12 months* 0.0 0.0

> 12 to ≤ 18 months -23.6 (-39.7, -5.3) 0.131 -23.8 (-39.8, -5.5) 0.130

> 18 to ≤ 24 months -37.1 (-43.1, -7.4) 0.007 -39.5 (-46.2, -9.5) 0.005

> 24 or more months -63.7 (-82.4, -53.1) < 0.001 -64.8 (-83.5, -54.2) < 0.001

Initial cART containing NNRTI

No* 0.0 0.0

Initial cART containing boosted PI

Yes 7.1 (-1.4, 17.3) 0.235 -2.5 (-9.2, 8 .9 ) 0.874

No* 0.0 0.0

Initial cART containing abacavir

Yes -1.1 (-13.7, 6 .0) 0.893 -4.5 (-16.1, 3.3) 0.440

No* 0.0

Yes -13.7 (-26.3, 0.0) 0.078 -7.6 (-19.7, 7.3) 0.072

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regression analysis of the CD4 count sl o pe . Concu rrent hemoglobin level, initial cART containing NNR T I or boosted PI were not significantly associated with the study endpoint in both U n i var i at e a nd mul ti varia te analyses. Recommendations for earlier treatment are therefore unlikely to have any major effect on population-level outcomes, and it is argued that the resources required for earlier treatment may be better used to encourage earlier HIV testing in these countries, or enabling full access to HAART in countries where drugs are less readily available. Jerwin prabu et al observed in HIV-infected patients with HBV or HCV an initially delayed CD4 count recovery at week four after HAART treatment, but at week 48 the CD4 count in- crease was similar to the patients only infected with HI V . A decrease in CD4 count sl o pe of less than 20 cells might not be clinically significant in the early phase of cART. Phenyl groups tend to resist oxidation and reduction. It is used to lower cholesterol in people with hyper cholestrolaemia. Con- sidering normal chemical reaction as base; if weak nudeophile and moderate electrophile are added; no reaction occurs. Considering the previous reaction; weak nudeophile is replaced by bromo benzene and p substituted phenyl ring is added. Similarly moderate electro- phile is replaced by oxalamide linker and tetra methyl piperidine. During the chemical similarity process Para isomers substitute bromo benzene phenyl ring reacts with HIV virus.

Fig.3. Molecular reaction with strong chair confirmation

If CD4 count is the only way for monitoring treatment response, the result of this analysis showed that a patient can have a considerable duration of virological failure without meeting CD4 criteria recommended by WHO for switch of ART to second line, through the possible develop ment of HIV- drug resistance that could com- promise the efficacy of later cART regimens remains un- certain.

7 CONCLUSION

Subsequent synthesis and assaying revealed that S10087 was in fact a “near-miss” since several closely related analogs were found to be potent anti-HIV agents. A chemical similar- ity of the HIV-2 reverse transcriptase is used as reference structure in order to identify potentially active compounds. The results of our study challenge the concept that CD4 cell depletion in chronic HIV infection is mostly attributable to the direct effects of HIV replication. Thus, with the aid of computational tools, it was possible to evolve a false positive from the virtual screening into a true active. In this research we have summarized the evidence for and against earlier initiation of HAART in HIV- infected individuals with a CD4 cell count more than 350 cells/µl. The effect on long-term out- comes through the possible development of HIV drug re- sistance remains uncertain.

ACKNOWLEDGMENT

We thank M.M.Sowmiya, Usha for her advice and assis- tance in the calculation of confidence intervals for the coef- ficients of determination reported here in, M r.A .P r av e e n Ja s s o , Je fr i n , and Ms.S.Jackulin (Shaanu Gracia), Ms. S.Manju Lakshmi, Dr. C. Sangeetha Prabha, Ms. Monisha for their assistance in devising the statistical approach used in this Research Work.

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• Jerwin Prabu.A is currently pursuing Research Scholar program at department of Electronics and Communication Engineering at Karpagam University, Coimbatore, Tamilnadu, India. He has published papers in Journal at International and National level. His areas of interest are bio medical instrumentation, chemical engineering, robotics, PH-9585768465. E-mail: jerwinprabu @gmail.com

• Dr.Manimegalai.P is currently working as Professor at Department of Electronics and Communication Engineering at Karpagam University, Coimbatore Tamilnadu, India. She has published more than 20 papers in Journal at International and Na- tional level.Her areas of interest are bio signal processing and wavelets. PH-

9994291601. E-mail: manimegalai.vaivaran@gmail.com

• Abbiramy.S.S is currently pursuing Bachelor program at department of Electronics and Communication Engineering at St.Fransis Xavier college of Engineering, Tiru- nelveli, TamilNadu, India. E-mail: abbiramyece2014@gmail.com

• Jenifer.S is currently pursuing Bachelor program at department of Electronics and Communication Engineering at St.Fransis Xavier college of Engineering, Tirunel- veli, TamilNadu, India. E-mail: jeniferece2014@gmail.com

Cohort Study. JAMA. 1996; 276:105-110.