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\def\RunningAuthor{Sathianarayanan S et al.}
\firstPage{7790}
\articleType{Original Article}
\receivedDate{10 Sep 2020}
\acceptedDate{15 Oct 2020}
\revisedDate{10 Oct 2020}
\journalVolume{2020, 11}
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\journalDoi{ijrps.v11i4.4286}
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\title{\textit{\textbf{Insilico}} \textbf{ analysis of acridone against TNF-\ensuremath{\alpha } and PDE4 targets for the treatment of psoriasis}}
\author{Sunitha~Sukumaran,  
            Meghna~M,  
            Sneha~S,  
            Arjun~B,  
            Sathianarayanan~S\textsuperscript{*}, 
            Saranya~T~S~\\[5pt]{Department of Pharmaceutical Chemistry and Analysis, Amrita School of Pharmacy, Amrita Vishwa Vidyapeetham, Amrita Institute of Medical Science, Amrita Health Science Campus, Kochi {\textendash} 682041, Kerala, India}}

\begin{abstract}
Psoriasis is an autoimmune disorder. Phosphodiesterase is a family of 1-11 among which PDE4 is most predominant enzymes present in inflammatory cells. Commercially available drugs are synthetic, and these may cause various side effects and are expensive. Dimethyl fumarate is the most frequently used systematic treatment for psoriasis with significant side effects such as myelosuppression, hepatic fibrosis and pulmonary fibrosis. Immune compromise drugs having various side effects, so this project is aimed to propose a novel drug that has more potency, efficiency and least side effects. The docking analysis was carried out to identify the best ligands by predicting the ligand conformation in the active protein sites and ligand binding affinity towards protein. Ligands were docked with the proteins, and all exhibited higher docking score than the standard drug dimethyl fumarate. The TNF- \ensuremath{\alpha } inhibitors with PDB id such as 2ZJC, 2ZPX and PDE4 Inhibitors with PDB ID such as 3SL3, 1PTW are selected as target proteins, acridone had the best docking score of 19.3502 than standard value 12.997, and with PDB ID 3SL3, acridone showed 26.025 as docking score over the standard value 21.995. it interacted well with the active sites of the proteins. Thus, we infer that these studies will be a leader, in designing new and improved drug target for psoriatic therapy.  
\end{abstract}\def\keywordstitle{Keywords}

\begin{keywords}cyclic AMP pathway,\newline Docking studies,\newline Inflammation,\newline Phosphodiesterase-4,\newline Tumor necrotic factor- \ensuremath{\alpha }
\end{keywords}
\twocolumn[ \maketitle {\printKwdAbsBox}]
\makeatletter{\raggedright\textsuperscript{*}Corresponding Author\par Name:\ Sathianarayanan~S~\\ Phone:\ ~\\  Email:\ ssnvij@yahoo.co.in
        \par}\vspace*{-11pt}\hrulefill\par{\fontsize{12}{14}\selectfont ISSN: 0975-7538}\par% 
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        \makeatother
        
    
\section{Introduction}
Psoriasis, affecting about 125 million people globally, is a chronic inflammatory disease that arises due to immunological modification \unskip~\citep{921502:20664506,921502:20664511}. In Europe, the prevalence range of psoriasis was between 2.0 \% and 6.5 \%. The highest prevalence of 11.8 \% was reported in the Arctic region of Russia. In North America, the prevalence range was between 2.2 \% and 4.7 \% whereas, in Canada, it was 4.6 \%. Many psoriasis surveys have been conducted in Asia. The reported prevalence of psoriasis in Malaysia, Japan and Kuwait was 0.5 \%-1.5 \%, 0.29 \%-1.18 \% and 3.1 \% respectively. In India, the occurrence of psoriasis ranged from 4 to 5.5 \% \unskip~\citep{921502:20664512}. Clinical data showed the prevalence in areas including Dibrugarh, Calcutta, Patna, Darbhanga, Lucknow, New Delhi and Amritsar to be anywhere from 0.44 to 2.2 \% with an incidence of around 1 \% specifically in Amritsar, a statistic attributed to the prevailing climatic condition \unskip~\citep{921502:20664501}.

Whereas in the northern parts of our nation, 2.3 \% of dermatological patients were affected by psoriasis, the prevalence rate is 2.5 \% in South India \unskip~\citep{921502:20664495}. A prospective study reported that in the Indian population, around 60 \% of the patients are affected relatively early in their lives (before the age of 30 years) and that the male gender was more affected than females with a male to female ratio of 2.5:1 \unskip~\citep{921502:20664504}.

Over the last few years, the research in this field is mainly focused on an understanding of the pathophysiology. Psoriatic patients are affected by immunological changes that can activate T cells \unskip~\citep{921502:20664498}. This activation, in turn, induces the proliferation of keratinocytes, enhances the T cell receptor signalling and related CD2 pathways, leads to chronic inflammation in the skin via over-expression of IL2 TNF\ensuremath{\alpha }, IFN\ensuremath{\gamma }, NF-\ensuremath{\kappa }B etc. \unskip~\citep{921502:20664505}. Some genetic factors and environmental factors play some significant role in psoriasis. The disease can cause inflammation on the joints, also known as psoriatic arthritis \unskip~\citep{921502:20664496}. As it is a chronic disease, it tends to relapse. They also show psoriatic plaques due to the rapid multiplication of epidermal cells. The plaques are defined by epidermal hyperplasia, epidermal infiltration and dermal infiltration by leukocytes.Size of the plaque varies from few millimetres to large surface of the skin. Differentiation and activation of the cells will take place, and the proliferating keratinocytes along with the production of other pro-inflammatory cytokines, adhesion molecules and antimicrobial peptides also increases. The mechanism of inflammation is immune-based, and it is mainly due to T cells in the dermis. Langerhans cell-an antigen-presenting cell in the skin migrate to the lymph node, and there they interact with T cells.\ensuremath{^{}} The activation of T cells takes place as a result of the immune response and leads to the release of cytokines.\ensuremath{^{}} It increases the production of interleukin-23, Tumor Necrotic Factor-\ensuremath{\alpha } and Nitric Oxide synthase, which are cytokines that cause keratinocyte proliferation and lack of maturation which are characterized in psoriasis. The effects in psoriasis include the action of cytokine, TNF- \ensuremath{\alpha } and the action of phosphodiesterase enzyme. 

Monocytes and macrophages produce tumour necrotic factor. Along with these, mast cells, T cells, NK cells can also produce TNF-\ensuremath{\alpha }. It is capable of differentiation, mitogenesis, inflammation, immune-modulation, wound healing etc. The action begins by binding of TNF- \ensuremath{\alpha } on receptors namely TNF \ensuremath{\alpha } -R1 and TNF-\ensuremath{\alpha } R2 that present in the dermis. The cross-linking of these receptors results in transduction of signal and activates interleukin-6 (IL-6), protein1, nuclear factor, camp pathway. As a response to this, the transcription takes place then leads to gene expression, which is a characteristic reason for psoriasis \unskip~\citep{921502:20664508}.

TNF- \ensuremath{\alpha } inhibitors include the agents that block the binding of TNF- \ensuremath{\alpha } on receptors and act on the keratinocytes and causes decreased proliferation and prevent the secretion of chemoattractants. The TNF- \ensuremath{\alpha } antagonists are first-line agents used in the treatment of psoriasis and more studies on these are still proceeding for more efficient inhibition of this skin disorder \unskip~\citep{921502:20664499}. 

Phosphodiesterase 4 enzyme (PDE4) is another factor that causes psoriasis. PDE4 is a phosphodiesterase enzyme in the subtype 4, which is an intracellular enzyme that promotes the production of pro-inflammatory agents and reduces the production of anti-inflammatory mediators. PDE4 promotes the inflammation by degrading intracellular level of cyclic adenosine monophosphate (camp) that acts as a second messenger that helps to maintain immune homeostasis \unskip~\citep{921502:20664507}. As part of the degradation of camp, activation of immune cells take place followed by the release of pro-inflammatory mediators like TNF- \ensuremath{\alpha }, interleukin, interferon. At the same time reduces the amount of anti-inflammatory mediator, IL-10 and these causes inflammation in a different part of the skin which is associates with psoriasis.  

 Agents which increase intracellular cyclic adenosine monophosphate (camp) may show an antagonistic effect on the production of a pro-inflammatory molecule, so inhibitors of the camp degrading phosphodiesterase have been identified as promising drugs in psoriasis which is a chronic skin disorder. One of the PDE4 inhibitor, such as Apremilast that have an improved therapeutic index and shows assumable activity in dermatological and rheumatologic conditions \unskip~\citep{921502:20664509}. 

So TNF- \ensuremath{\alpha } inhibitors and PDE4 inhibitors are attractive target sites for the treatment of psoriasis. The involvement of computational software performs drug-likeness and toxicity studies. New and improved drugs can be designed with fewer side effects by performing docking approach that predicts the affinity of binding on the active sites.
    
\section{Materials and Methods}
In this study, we collected the data from biological database like PubChem, a database of chemical molecules and their activities, protein data bank (PDB), it contains information about the experimentally evaluated structure of a protein. Chemdraw is a molecule editor to draw chemical structures. Molinspiration is a tool to calculate the properties and bioactivity of ligands, SOPMA (secondary structure prediction method with alignment), a tool to predict the secondary characters of a protein, ProtParam, a tool which allows the computation of various physical and chemical properties of a protein, BIOVIA a software to predict the interaction between proteins and ligands by docking as well as to predict the toxicity.  

\textbf{Preparation of protein} \textbf{\space }

The three-dimensional crystal structures of some proteins with PDB id- 4TSV, 2E7A,3L9J, 2AZ5, 1A8M, 5TSW,2ZJC, 1TNF, 2ZPX, 2TUN that inhibit PDE4 and TNF- \ensuremath{\alpha } with PDB id- 2PW3,4MYQ,5K32,1F0J, 4WCU, 4NWF,1PTW,3O0J, 3SL3 were collected from protein data bank. By the involvement of tools such as PROTPARAM and SOPMA were used to analyzed the primary characterization such as Various physical and chemical parameters of the selected proteins like molecular weight, amino acid composition, atomic composition, theoretical pI, extinction coefficient, aliphatic index, estimated half-life and grand average of hydropathicity (GRAVY) these parameters were calculated and tabulated a neural network system calculated same like the secondary structure of proteins. It also tabulated \unskip~\citep{921502:20664510,921502:20664502}.

\textbf{Preparation of ligands}

Twenty chemical entities, based on the literature review of anti-psoriatic and anti-inflammatory ligands, were selected to identify the activity against PDE4 and TNF- \ensuremath{\alpha }. The 3D structure of these ligands was obtained from Chemdraw pro 12.0. The ligands that show the best binding affinity towards the protein were selected. The ligands must follow Lipinski rule and its parameters which are associated with Molinspiration tool \unskip~\citep{921502:20664497}. 

\textbf{ADME and toxicity studies}

Pharmacokinetic studies like the efficiency of absorption, distribution, metabolism and excretion of the drugs throughout the body were studied by ADMETox Studies using Discovery Studio v.17. The toxicity and carcinogenicity of these are also theoretically identified in these studies \unskip~\citep{921502:20664500}. These studies are associated with admetSAR prediction tool.  

\textbf{Molecular docking studies} \textbf{\space }

Molecular docking is computational in silico drug design tool that predicts the intermolecular complexes formed between two or more constituent molecules \unskip~\citep{921502:20664514}. It includes the process of generating a model based on the known 3D structure of its component that is, target and ligand \unskip~\citep{921502:20664513}. The docking procedure searches for near-native ligand conformation and orientation concerning target proteins \unskip~\citep{921502:20664503}. The targets proteins that inhibit different targets are docked with selected ligands are performed using Biovia discovery studio. These predominant structures of ligands are made to interact with target sites on the proteins. They predict the flexible docking simulations, and then the energy values are calculated from the docking conformations of PDE4 Inhibitor complexes and TNF- \ensuremath{\alpha } inhibitor complexes. The interaction energy between the protein and the ligands are examined from their docking score.
    
\section{Results and Discussion}
In the present examination, nearly around 20 target proteins have been assembled that exhibits its target movement on picked focuses, for instance, TNF-\ensuremath{\alpha } and PDE4. The suitable target proteins have been selected based on its characterization that had been involved in docking analysis. The results of primary and secondary characterizations of proteins that inhibit TNF- \ensuremath{\alpha } are tabulated in Tables~\ref{tw-766dfae500b9} and~\ref{tw-3586556343fe}, respectively. The proteins that inhibit PDE4 target are also tabulated based on primary and secondary characterization in Tables~\ref{tw-857a56c691ef} and~\ref{tw-b96370cf9d7b}, respectively. The TNF- \ensuremath{\alpha } inhibitors with PDB id such as 2ZJC, 2ZPX and PDE4 Inhibitors with PDB id such as 3SL3, 1PTW are selected as target proteins for the ligand to bind as they have the parameters with the higher value of half-life, gravy, instability index, aliphatic index from ProtParam and random coil from SOPMA.


\bgroup
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\caption{\boldmath {Docking of PDB id 3SL3 with acridone}}
\label{f-aa0fda40989f}
\end{figure}
\egroup
Ligands which bind with the selected target proteins are also estimated for their molecular properties and toxicity prediction. 8 ligands that show anti-inflammatory and anti-psoriatic properties were selected. Drug likeness of these ligands was determined based on the parameters mentioned in Lipinski rule. The properties and parameters of these ligands are tabulated in Table~\ref{tw-d3539e25eda4}. From this, it was


\begin{table*}[!htbp]
\caption{\boldmath {Primary Characterization (Protparam) of Proteins that Inhibits TNF- \ensuremath{\alpha }} }
\label{tw-766dfae500b9}
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\tblmidrule 
\cAlignHack 4TSV   &
  \cAlignHack 150   &
  \cAlignHack 5.92  &
  \cAlignHack 16562.8   &
  \cAlignHack 27.01   &
  \cAlignHack 99.47   &
  \cAlignHack -0.134   &
  \cAlignHack 20 \\
\cAlignHack 2E7A  &
  \cAlignHack  157   &
  \cAlignHack 5.26   &
  \cAlignHack 17285.4   &
  \cAlignHack 47.91   &
  \cAlignHack 94.39   &
  \cAlignHack -0.201   &
  \cAlignHack 100\\
\cAlignHack 3L9J   &
  \cAlignHack 134   &
  \cAlignHack 7.76   &
  \cAlignHack 15296.1   &
  \cAlignHack 31.77   &
  \cAlignHack 59.03   &
  \cAlignHack -0.589   &
  \cAlignHack 5.5  \\
\cAlignHack 2AZ5   &
  \cAlignHack 148 &
  \cAlignHack 5.91   &
  \cAlignHack 16394.6   &
  \cAlignHack 26.40   &
  \cAlignHack 100.8   &
  \cAlignHack -0.132   &
  \cAlignHack 1.1  \\
\cAlignHack 1A8M   &
  \cAlignHack 157  &
  \cAlignHack 5.91   &
  \cAlignHack 17311.6   &
  \cAlignHack 29.04   &
  \cAlignHack 96.88   &
  \cAlignHack -0.203   &
  \cAlignHack 100 \\
\cAlignHack 5TSW   &
  \cAlignHack 150  &
  \cAlignHack 5.92   &
  \cAlignHack 16562.8   &
  \cAlignHack 27.01   &
  \cAlignHack 99.47   &
  \cAlignHack -0.134   &
  \cAlignHack 20\\
\cAlignHack 2ZJC   &
  \cAlignHack 157   &
  \cAlignHack 5.04   &
  \cAlignHack 17069.2   &
  \cAlignHack 38.91   &
  \cAlignHack 95.03   &
  \cAlignHack -0.089   &
  \cAlignHack 100\\
\cAlignHack 1TNF   &
  \cAlignHack 157   &
  \cAlignHack 7.94   &
  \cAlignHack 17350.7   &
  \cAlignHack 33.65   &
  \cAlignHack 99.36   &
  \cAlignHack -0.162   &
  \cAlignHack 100\\
\cAlignHack 2ZPX   &
  \cAlignHack 157   &
  \cAlignHack 5.30  &
  \cAlignHack 17269.5   &
  \cAlignHack 48.11   &
  \cAlignHack 97.52   &
  \cAlignHack -0.148   &
  \cAlignHack 100\\
\cAlignHack 2TUN   &
  \cAlignHack 157   &
  \cAlignHack 7.94  &
  \cAlignHack 17378.6   &
  \cAlignHack 33.11   &
  \cAlignHack 100.57   &
  \cAlignHack -0.147   &
  \cAlignHack 100\\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Secondary characterization (SOPMA) of protein that inhibits TNF- \ensuremath{\alpha }} }
\label{tw-3586556343fe}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.1884\linewidth-2\tabcolsep}p{\dimexpr.22990000000000002\linewidth-2\tabcolsep}p{\dimexpr.2266\linewidth-2\tabcolsep}p{\dimexpr.15680000000000001\linewidth-2\tabcolsep}p{\dimexpr.1983\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\cAlignHack PDB id  & \cAlignHack Alpha Helix & \cAlignHack Pi Helix & \cAlignHack Beta-Turn & \cAlignHack Random Coil\\
\tblmidrule 
\cAlignHack 4TSV   &
  \cAlignHack 35   &
  \cAlignHack 0   &
  \cAlignHack 16   &
  \cAlignHack 52 \\
\cAlignHack 2E7A   &
  \cAlignHack 29   &
  \cAlignHack 0   &
  \cAlignHack 12 &
  \cAlignHack 69\\
\cAlignHack 3L9J   &
  \cAlignHack 33   &
  \cAlignHack 0   &
  \cAlignHack 11 &
  \cAlignHack 59\\
\cAlignHack 2AZ5   &
  \cAlignHack 37 &
  \cAlignHack 0   &
  \cAlignHack 14 &
  \cAlignHack 52\\
\cAlignHack 1A8M   &
  \cAlignHack 36 &
  \cAlignHack 0 &
  \cAlignHack 15 &
  \cAlignHack 60\\
\cAlignHack 5TSW   &
  \cAlignHack 35 &
  \cAlignHack 0 &
  \cAlignHack 16 &
  \cAlignHack 52\\
\cAlignHack 2ZJC   &
  \cAlignHack 22 &
  \cAlignHack 0 &
  \cAlignHack 16 &
  \cAlignHack 64\\
\cAlignHack 1TNF   &
  \cAlignHack 33 &
  \cAlignHack 0 &
  \cAlignHack 14 &
  \cAlignHack 61\\
\cAlignHack 2ZPX   &
  \cAlignHack 28 &
  \cAlignHack 0 &
  \cAlignHack 12 &
  \cAlignHack 71\\
\cAlignHack 2TUN   &
  \cAlignHack 33 &
  \cAlignHack 0 &
  \cAlignHack 14 &
  \cAlignHack 60\\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Primary Characterization (ProtParam) of Protein that Inhibit PDE4} }
\label{tw-857a56c691ef}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.0993\linewidth-2\tabcolsep}p{\dimexpr.1666\linewidth-2\tabcolsep}p{\dimexpr.1335\linewidth-2\tabcolsep}p{\dimexpr.1065\linewidth-2\tabcolsep}p{\dimexpr.1314\linewidth-2\tabcolsep}p{\dimexpr.1481\linewidth-2\tabcolsep}p{\dimexpr.10129999999999997\linewidth-2\tabcolsep}p{\dimexpr.11330000000000002\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\cAlignHack PDB id & \cAlignHack No of Amino Acid & \cAlignHack Theoretical Pi & \cAlignHack MW & \cAlignHack Instability Index & \cAlignHack Aliphatic Index & \cAlignHack Gravy & \cAlignHack Half Life\\
\tblmidrule 
\cAlignHack 2PW3  &
  \cAlignHack 327   &
  \cAlignHack 37661.8   &
  \cAlignHack 5.07   &
  \cAlignHack 37.08   &
  \cAlignHack 98.65   &
  \cAlignHack -0.266   &
  \cAlignHack 7.2  \\
\cAlignHack 4MYQ   &
  \cAlignHack 372 &
  \cAlignHack 42766.2   &
  \cAlignHack 4.78  &
  \cAlignHack 42.59   &
  \cAlignHack 86.24   &
  \cAlignHack -0.367   &
  \cAlignHack 30\\
\cAlignHack 5K32   &
  \cAlignHack 325 &
  \cAlignHack 37375.5   &
  \cAlignHack 5.06   &
  \cAlignHack 34.74   &
  \cAlignHack 99.57   &
  \cAlignHack -0.238   &
  \cAlignHack 4.4\\
\cAlignHack 1F0J   &
  \cAlignHack 377   &
  \cAlignHack 43272.7   &
  \cAlignHack 4.74   &
  \cAlignHack 38.78   &
  \cAlignHack 85.62   &
  \cAlignHack -0.397   &
  \cAlignHack 1.9  \\
\cAlignHack 4WCU   &
  \cAlignHack 359  &
  \cAlignHack 41233.7   &
  \cAlignHack 4.97   &
  \cAlignHack 40.96   &
  \cAlignHack 93.12   &
  \cAlignHack -0.348   &
  \cAlignHack 20  \\
\cAlignHack 4NWF  &
  \cAlignHack 539  &
  \cAlignHack 61913.0   &
  \cAlignHack 7.04   &
  \cAlignHack 41.61   &
  \cAlignHack 73.69   &
  \cAlignHack -0.710   &
  \cAlignHack 30\\
\cAlignHack 1PTW  &
  \cAlignHack 360  &
  \cAlignHack 41346.8   &
  \cAlignHack 4.97   &
  \cAlignHack 40.88   &
  \cAlignHack 93.94   &
  \cAlignHack -0.336   &
  \cAlignHack 20\\
\cAlignHack 3O0J  &
  \cAlignHack 323  &
  \cAlignHack 37270.2   &
  \cAlignHack 5.00   &
  \cAlignHack 36.53   &
  \cAlignHack 92.98   &
  \cAlignHack -0.264   &
  \cAlignHack 1.4\\
\cAlignHack 3SL3   &
  \cAlignHack 361   &
  \cAlignHack 41476.0   &
  \cAlignHack 4.93   &
  \cAlignHack 40.79   &
  \cAlignHack 93.68   &
  \cAlignHack -0.345   &
  \cAlignHack 20\\
\cAlignHack 5K32   &
  \cAlignHack 325   &
  \cAlignHack 37375.0   &
  \cAlignHack 5.06   &
  \cAlignHack 34.74   &
  \cAlignHack 99.57   &
  \cAlignHack -0.238   &
  \cAlignHack 4.4\\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Secondary Characterization (SOPMA) of Protein that Inhibits PDE4} }
\label{tw-b96370cf9d7b}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.215\linewidth-2\tabcolsep}p{\dimexpr.1966\linewidth-2\tabcolsep}p{\dimexpr.22\linewidth-2\tabcolsep}p{\dimexpr.1684\linewidth-2\tabcolsep}p{\dimexpr.20\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\cAlignHack PDB id & \cAlignHack Alpha Helix & \cAlignHack Pi Helix & \cAlignHack Beta-Turn & \cAlignHack Random Coil\\
\tblmidrule 
\cAlignHack 2PW3   &
  \cAlignHack 189 &
  \cAlignHack 0   &
  \cAlignHack 16   &
  \cAlignHack 80 \\
\cAlignHack 4MYQ   &
  \cAlignHack 209 &
  \cAlignHack 0   &
  \cAlignHack 20 &
  \cAlignHack 98\\
\cAlignHack 5K32   &
  \cAlignHack 187 &
  \cAlignHack 0   &
  \cAlignHack 16 &
  \cAlignHack 80\\
\cAlignHack 1F07   &
  \cAlignHack 207 &
  \cAlignHack 0   &
  \cAlignHack 20 &
  \cAlignHack 107\\
\cAlignHack 4WCU  &
  \cAlignHack 195 &
  \cAlignHack 0 &
  \cAlignHack 16 &
  \cAlignHack 102\\
\cAlignHack 4NWF  &
  \cAlignHack 209 &
  \cAlignHack 0 &
  \cAlignHack 20 &
  \cAlignHack 98\\
\cAlignHack 1PTW   &
  \cAlignHack 194 &
  \cAlignHack 0 &
  \cAlignHack 16 &
  \cAlignHack 102\\
\cAlignHack 3O0J  &
  \cAlignHack 199 &
  \cAlignHack 0 &
  \cAlignHack 20 &
  \cAlignHack 70\\
\cAlignHack 3SL3  &
  \cAlignHack 196 &
  \cAlignHack 0 &
  \cAlignHack 16 &
  \cAlignHack 102\\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Evaluation of drug-likeness} }
\label{tw-d3539e25eda4}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.2196\linewidth-2\tabcolsep}p{\dimexpr.10240000000000002\linewidth-2\tabcolsep}p{\dimexpr.10760000000000002\linewidth-2\tabcolsep}p{\dimexpr.1137\linewidth-2\tabcolsep}p{\dimexpr.10959999999999999\linewidth-2\tabcolsep}p{\dimexpr.1169\linewidth-2\tabcolsep}p{\dimexpr.1137\linewidth-2\tabcolsep}p{\dimexpr.1165\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\cAlignHack Chemical constituent & \cAlignHack Milogp  & \cAlignHack TPSA  & \cAlignHack N atoms & \cAlignHack MW & \cAlignHack N ON & \cAlignHack N OHNH  & \cAlignHack Volume\\
\tblmidrule 
\cAlignHack Acridine  &
  \cAlignHack 3.17 &
  \cAlignHack 12.89 &
  \cAlignHack 14 &
  \cAlignHack 179.2 &
  \cAlignHack 1 &
  \cAlignHack 0 &
  \cAlignHack 167.87  \\
\cAlignHack Acridone   &
  \cAlignHack 1.78   &
  \cAlignHack 32.86   &
  \cAlignHack 15   &
  \cAlignHack 195.2   &
  \cAlignHack 2  &
  \cAlignHack 1   &
  \cAlignHack 176.00 \\
\cAlignHack Anthracenone   &
  \cAlignHack 3.49 &
  \cAlignHack 17.07 &
  \cAlignHack 15 &
  \cAlignHack 194.2 &
  \cAlignHack 1 &
  \cAlignHack 0 &
  \cAlignHack 180.40 \\
\cAlignHack Dithranol  &
  \cAlignHack 3.38   &
  \cAlignHack 57.53   &
  \cAlignHack 17   &
  \cAlignHack 226.2   &
  \cAlignHack 3  &
  \cAlignHack 2  &
  \cAlignHack 196.43 \\
\cAlignHack 5-amino-4-hydroxyAnthranone  &
  \cAlignHack 2.87   &
  \cAlignHack 63.32   &
  \cAlignHack 17 &
  \cAlignHack 225.2   &
  \cAlignHack 3 &
  \cAlignHack 3 &
  \cAlignHack 199.70  \\
 &
   &
   &
   &
   &
   &
   &
  \\
\cAlignHack 5-carb \mbox{}\protect\newline 5hydroxy anthranone &
  \cAlignHack 2.38 &
  \cAlignHack 60.16   &
  \cAlignHack 19 &
  \cAlignHack 255.2   &
  \cAlignHack 3 &
  \cAlignHack 2 &
  \cAlignHack 215.60  \\
 &
   &
   &
   &
   &
   &
   &
  \\
\cAlignHack 5-carboxamide-4 Hydroxy anthranone  &
  \cAlignHack 2.21   &
  \cAlignHack 80.39   &
  \cAlignHack 19   &
  \cAlignHack 253.2   &
  \cAlignHack 4 &
  \cAlignHack 3 &
  \cAlignHack 218.69 \\
 &
   &
   &
   &
   &
   &
   &
  \\
\cAlignHack Triacetoxy anthracene   &
  \cAlignHack 2.60 &
  \cAlignHack 78.92   &
  \cAlignHack 26 &
  \cAlignHack 352.3  &
  \cAlignHack 6 &
  \cAlignHack 0 &
  \cAlignHack 305.62 \\
 &
   &
   &
   &
   &
   &
   &
  \\
\cAlignHack Dihydroxyacyl Anthracene  &
  \cAlignHack 1.71 &
  \cAlignHack 100.6 &
  \cAlignHack 20 &
  \cAlignHack 269.2   &
  \cAlignHack 5 &
  \cAlignHack 4 &
  \cAlignHack 226.73 \\
\cAlignHack 8-hydroxy-9-oxo \mbox{}\protect\newline Anthranoic acid   &
  \cAlignHack 2.96   &
  \cAlignHack 74.60  &
  \cAlignHack 19   &
  \cAlignHack 254.2   &
  \cAlignHack 4 &
  \cAlignHack 2 &
  \cAlignHack 215.41 \\
\cAlignHack Capsaicin  &
  \cAlignHack 3.10 &
  \cAlignHack 58.56 &
  \cAlignHack 22 &
  \cAlignHack 305.4 &
  \cAlignHack 4 &
  \cAlignHack 2 &
  \cAlignHack 310.37 \\
\cAlignHack Berberine  &
  \cAlignHack 0.20 &
  \cAlignHack 40.82 &
  \cAlignHack 25 &
  \cAlignHack 336.3 &
  \cAlignHack 5 &
  \cAlignHack 0 &
  \cAlignHack 296.30\\
\cAlignHack Curcumin  &
  \cAlignHack 2.30 &
  \cAlignHack 93.07 &
  \cAlignHack 27 &
  \cAlignHack 368.3 &
  \cAlignHack 6 &
  \cAlignHack 2 &
  \cAlignHack 332.18\\
\cAlignHack Indirubin  &
  \cAlignHack 2.90 &
  \cAlignHack 65.72 &
  \cAlignHack 20 &
  \cAlignHack 262.2 &
  \cAlignHack 4 &
  \cAlignHack 2 &
  \cAlignHack 223.96\\
\cAlignHack Aloe-emodin   &
  \cAlignHack 2.42 &
  \cAlignHack 94.83 &
  \cAlignHack 20 &
  \cAlignHack 240.2 &
  \cAlignHack 5 &
  \cAlignHack 3 &
  \cAlignHack 223.43\\
\cAlignHack Herbacetin   &
  \cAlignHack 1.91 &
  \cAlignHack 131.3 &
  \cAlignHack 22 &
  \cAlignHack 302.3 &
  \cAlignHack 7 &
  \cAlignHack 5 &
  \cAlignHack 240.08\\
\cAlignHack Cianidonol  &
  \cAlignHack 1.37 &
  \cAlignHack 110.3 &
  \cAlignHack 21 &
  \cAlignHack 290.2 &
  \cAlignHack 6 &
  \cAlignHack 5 &
  \cAlignHack 244.14\\
\cAlignHack Glaucine  &
  \cAlignHack 3.08 &
  \cAlignHack 40.17 &
  \cAlignHack 26 &
  \cAlignHack 355.4 &
  \cAlignHack 5 &
  \cAlignHack 0 &
  \cAlignHack 332.74\\
\cAlignHack Sinomenine  &
  \cAlignHack 0.85 &
  \cAlignHack 59.01 &
  \cAlignHack 24 &
  \cAlignHack 329.4 &
  \cAlignHack 5 &
  \cAlignHack 1 &
  \cAlignHack 303.74\\
\cAlignHack Dihydroxysanguinarine  &
  \cAlignHack 4.27 &
  \cAlignHack 40.17 &
  \cAlignHack 25 &
  \cAlignHack 333.3 &
  \cAlignHack 5 &
  \cAlignHack 0 &
  \cAlignHack 282.6\\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {ADME Tox prediction} }
\label{tw-cd2586bcb14f}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.2103\linewidth-2\tabcolsep}p{\dimexpr.0878\linewidth-2\tabcolsep}p{\dimexpr.08160000000000002\linewidth-2\tabcolsep}p{\dimexpr.10959999999999999\linewidth-2\tabcolsep}p{\dimexpr.11590000000000002\linewidth-2\tabcolsep}p{\dimexpr.121\linewidth-2\tabcolsep}p{\dimexpr.15329999999999998\linewidth-2\tabcolsep}p{\dimexpr.1205\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}{\multirow{2}{*}{\cAlignHack Ligands }} & \cAlignHack  & \cAlignHack HIA & \multicolumn{4}{p{\dimexpr(.4998\linewidth-2\tabcolsep)}}{\cAlignHack CYP Inhibitor} & {\multirow{2}{*}{\cAlignHack Log S}}\\
\rowcolor{kwdboxcolor} & \cAlignHack  & \cAlignHack  & \cAlignHack CYP1A2 & \cAlignHack CYP2C9 & \cAlignHack CYP2D6 & \cAlignHack CYP3A4 & \\
\tblmidrule 
\cAlignHack Acridine  &
  \cAlignHack 0.986   &
  \cAlignHack 0.996   &
  \cAlignHack Inhibit &
  \cAlignHack Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack -2.84 \\
 &
   &
   &
   &
   &
   &
   &
  \\
\cAlignHack Acridone   &
  \cAlignHack 0.986   &
  \cAlignHack 0.997   &
  \cAlignHack Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack -3.63 \\
\cAlignHack Anthracenone   &
  \cAlignHack 0.969   &
  \cAlignHack 1.000   &
  \cAlignHack Inhibit &
  \cAlignHack Inhibit &
  \cAlignHack Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack -4.1 \\
\cAlignHack Dithranol  &
  \cAlignHack 0.610   &
  \cAlignHack 1.000   &
  \cAlignHack Inhibit &
  \cAlignHack Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack -3.64 \\
\cAlignHack 5amino4hydroxy  &
  \cAlignHack -0.805 &
  \cAlignHack 0.991  &
  \cAlignHack Inhibit &
  \cAlignHack Non-Inhibit  &
  \cAlignHack Non-Inhibit  &
  \cAlignHack Non-Inhibit  &
  \cAlignHack -3.54\\
\cAlignHack 5-carb \mbox{}\protect\newline 5Carboxamide-4-Flone  &
  \cAlignHack 0.94 &
  \cAlignHack 0.997 &
  \cAlignHack Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack Inhibit &
  \cAlignHack -3.81\\
\cAlignHack 4 Hydroxy- \mbox{}\protect\newline 5-carboxamide- anthranone  &
  \cAlignHack 0.833 &
  \cAlignHack 0.995 &
  \cAlignHack Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack -3.31\\
 &
   &
   &
   &
   &
   &
   &
  \\
\cAlignHack Triacetoxy anthracene   &
  \cAlignHack 0.921 &
  \cAlignHack 0.994 &
  \cAlignHack Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack -4.40\\
 &
   &
   &
   &
   &
   &
   &
  \\
\cAlignHack Dihydroxyacyl Anthracene  &
  \cAlignHack 0.796 &
  \cAlignHack 0.993 &
  \cAlignHack Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack -3.74\\
 &
   &
   &
   &
   &
   &
   &
  \\
\cAlignHack 8-hydroxy-9-oxo \mbox{}\protect\newline Anthranoic acid   &
  \cAlignHack 0.521 &
  \cAlignHack 0.963 &
  \cAlignHack Non Inhibit &
  \cAlignHack Inhibit &
  \cAlignHack Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack -3.39\\
 &
   &
   &
   &
   &
   &
   &
  \\
\cAlignHack Capsaicin  &
  \cAlignHack 0.621   &
  \cAlignHack 0.992   &
  \cAlignHack Inhibit &
  \cAlignHack Inhibit &
  \cAlignHack Inhibit &
  \cAlignHack Inhibit &
  \cAlignHack -2.92\\
\cAlignHack Berberine  &
  \cAlignHack 0.927   &
  \cAlignHack 0.500   &
  \cAlignHack Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack -2.97\\
\cAlignHack Curcumin  &
  \cAlignHack 0.616   &
  \cAlignHack 0.953   &
  \cAlignHack Inhibit &
  \cAlignHack Inhibit &
  \cAlignHack Inhibit &
  \cAlignHack  Inhibit &
  \cAlignHack -3.36\\
\cAlignHack Indirubin  &
  \cAlignHack 0.874   &
  \cAlignHack 1.000   &
  \cAlignHack Inhibit &
  \cAlignHack Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack -4.22\\
\cAlignHack Aloe-emodin   &
  \cAlignHack 0.738   &
  \cAlignHack 0.981   &
  \cAlignHack Inhibit &
  \cAlignHack Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack -2.52\\
\cAlignHack Herbacetin   &
  \cAlignHack 0.571   &
  \cAlignHack 0.965   &
  \cAlignHack Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack Inhibit &
  \cAlignHack -2.99\\
\cAlignHack Cianidonol  &
  \cAlignHack 0.533   &
  \cAlignHack 0.965   &
  \cAlignHack Non Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack -3.10\\
\cAlignHack Glaucine  &
  \cAlignHack 0.992   &
  \cAlignHack 0.995   &
  \cAlignHack Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack -2.90\\
\cAlignHack Sinomenine  &
  \cAlignHack 0.983   &
  \cAlignHack 0.97   &
  \cAlignHack Non Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack -2.44\\
\cAlignHack Dimethyl fumarate  &
  \cAlignHack 0.995   &
  \cAlignHack 0.955   &
  \cAlignHack Non Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack Non Inhibit &
  \cAlignHack -0.99\\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Docking score} }
\label{tw-eeba8fe21e27}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.3039\linewidth-2\tabcolsep}p{\dimexpr.21060000000000002\linewidth-2\tabcolsep}p{\dimexpr.2376\linewidth-2\tabcolsep}p{\dimexpr.2479\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\multicolumn{2}{p{\dimexpr(.5145\linewidth-2\tabcolsep)}}{\cAlignHack 2ZJC (Tumor Necrotic Factor inhibitor)} & \multicolumn{2}{p{\dimexpr(.4855\linewidth-2\tabcolsep)}}{\cAlignHack 3SL3 (Phosphodiesterase 4 inhibitor)}\\
\rowcolor{kwdboxcolor}\cAlignHack Ligands & \cAlignHack Interaction energy (kcal/mol) & \cAlignHack Ligand & \cAlignHack Interaction energy (kcal/mol)\\
\tblmidrule 
\cAlignHack Acridone  &
  \cAlignHack 19.3502   &
  \cAlignHack Acridone  &
  \cAlignHack 26.025 \\
\cAlignHack 4-hydroxy-5-carboxamide anthrone   &
  \cAlignHack 27.36   &
  \cAlignHack 4- Hydroxyl-5- carboxamide anthrone  &
  \cAlignHack 42.105 \\
\cAlignHack Herbacetin  &
  \cAlignHack 32.324   &
  \cAlignHack Herbacetin   &
  \cAlignHack no binding \\
\cAlignHack Cianidanol  &
  \cAlignHack 44.614   &
  \cAlignHack Cianidanol  &
  \cAlignHack 41.762 \\
\cAlignHack Curcumin  &
  \cAlignHack 43.871   &
  \cAlignHack Curcumin  &
  \cAlignHack no binding \\
\cAlignHack Dimethyl fumarate   &
  \cAlignHack 12.997 &
  \cAlignHack Dimethyl fumarate   &
  \cAlignHack 21.995\\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}
found that Acridine, Acridone, Indirubin, Dithranol, 5-amino-4-hydroxy Anthranone and Dihydroxysanguinarine had 0 as the number of rotatable bonds while 5-carboxamide-4-fluoro anthracnose, 5-carboxamide-4-hydroxy anthranone, Dihydroxyacyl anthranone, 8-hydroxy-9-oxo anthranoic acid, aloe-emodin, Herbacetin, Ciandonol were having 1 as the number of rotatable bonds. Compounds such as Baberine and Sinomenine had 2 as the number of rotatable bonds.


\bgroup
\fixFloatSize{images/0ec11618-eb5f-431c-a7d9-65d7fb2327d5-upicture2.png}
\begin{figure}[!htbp]
\centering \makeatletter\IfFileExists{images/0ec11618-eb5f-431c-a7d9-65d7fb2327d5-upicture2.png}{\includegraphics{images/0ec11618-eb5f-431c-a7d9-65d7fb2327d5-upicture2.png}}{}
\makeatother 
\caption{\boldmath {Docking of PDB id 2ZJC with acridone}}
\label{f-8916f7d53b2f}
\end{figure}
\egroup
In contrast, Glaucine had 4, Triacetoxy anthracene had 6, Curcumin had 8 and Capsaicin had 9 as their number of rotatable bonds respectively. The ligands are selected as they follow up the parameters mentioned in Lipinski rule of five, to evaluate drug-likeness and to predict high anticipation of success or failure can be satisfied with two or more of following criteria: Molecular mass must be less than 500 Dalton, high lipophilicity (log p), less than 5 H bond donor, less than 10 H bond acceptor, molar refractivity should be between 40-130.

As there is no violation of the rule, these ligands possess better drug-likeness and are selected to dock with target proteins. Pharmacokinetic properties such as adsorption, distribution, metabolism, excretion and toxicity of the ligands are predicted, evaluated, and ligands were found to be effective.

The results of evaluated ligands were tabulated in Table~\ref{tw-cd2586bcb14f}, and from the given information all ligands were found to be non- carcinogens except 5-amino-4-hydroxy anthranone and 5-Carboxamide-4-Fluroanthranone also the following ligands are found as toxic they are; Dihydroxyacyl anthracene, 8-hydroxy-9-oxo anthranoic acid, Capsaicin, 5-amino-4-hydroxy anthranone and 5-Carboxamide-4-Fluroanthranone and aloe-emodin other ligands are non- toxic. On screening the ligands in ADMET, it demonstrated their blood-brain penetration, absorption, carcinogenicity.

Some of the ligands inhibit CYP1A2, CYP2C9, CYP2D6, CYP3A4 enzymes. It is clear from the table that the chosen ligands have good intestinal absorption, less penetration and less toxic when compared to the standard ligand, Dimethyl fumarate. The toxicity parameters like hepatotoxicity, carcinogenicity and mutagenicity were investigated. The selected ligands don't have much toxicity.  

The docking studies carried out between the selected target protein and ligands are screened, and the strength of interaction/affinity was predicted. The extend of ligand docking on protein structure was interpreted as C docker interaction energy or docking score. The best docking score obtained is presented in Table~\ref{tw-eeba8fe21e27}. From the table, it is clear that among the ligands docked with the protein. Figures~\ref{f-aa0fda40989f} and~\ref{f-8916f7d53b2f} shows the docking interaction of Acridone with PDB id-3SL3 and PDB id-2ZJC.  Docking interaction of Acridone with PDB id-2ZJC had the best docking score of 19.3502 than standard value 12.997, and with PDB id 3SL3, acridone was shown 26.025 as docking score over the standard value 21.995. It interacted well with the active sites of the proteins.
    
\section{Conclusion}
Our studies manifested that among the selected ligands, acridone has the best docking score with protein id such as 2ZJC and 3SL3 compared to a standard ligand. In general, it can be concluded that acridone could be an effectual ligand to inhibit both PDE4 and TNF\ensuremath{\alpha }, the selected target sites in psoriasis. Along with acridone, some other ligands are also having suitable docking mechanism and also will contribute to the treatment of psoriasis. Further analysis can be done on these studies for developing these drug targets both in vivo and in vitro studies.
    
\section{Acknowledgement}
The authors are thankful to the Department of Pharmaceutical Chemistry and analysis, Amrita school of pharmacy. Amrita Vishwa Vidyapeetham, Coimbatore.

\textbf{Conflict of Interest}

The authors declare that they have no conflict of interest for this study.

\textbf{Funding Support}

The authors declare that they have no funding support for this study.
    

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