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PyPLIF: Python-based Protein-Ligand Interaction Fingerprinting

Structure-based virtual screening (SBVS) methods often rely on docking score. The docking score is an over-simplification of the actual ligand-target binding. Its capability to model and predict the actual binding reality is limited. Recently, interaction fingerprinting (IFP) has come and offered us an alternative way to model reality. IFP provides us an alternate way to examine protein-ligand interactions. The docking score indicates the approximate affinity and IFP shows the interaction specificity. IFP is a method to convert three dimensional (3D) protein-ligand interactions into one dimensional (1D) bitstrings. The bitstrings are subsequently employed to compare the protein-ligand interaction predicted by the docking tool against the reference ligand. These comparisons produce scores that can be used to enhance the quality of SBVS campaigns. However, some IFP tools are either proprietary or using a proprietary library, which limits the access to the tools and the development of customized IFP algorithm. Therefore, we have developed PyPLIF, a Python-based open source tool to analyze IFP. In this article, we describe PyPLIF and its application to enhance the quality of SBVS in order to identify antagonists for estrogen α receptor (ERα). Availability PyPLIF is freely available at http://code.google.com/p/pyplif

Structure-based design of eugenol analogs as potential estrogen receptor antagonists

Eugenol is an essential oil mainly found in the buds and leaves of clove (Syzygium aromaticum (L.) Merrill and Perry), which has been reported to have activity on inhibition of cell proliferation and apoptosis induction in human MCF-7 breast cancer cells. This biological activity is correlated to its activity as an estrogen receptor antagonist. In this article, we present the construction and validation of structure-based virtual screening (SBVS) protocols to identify the potent estrogen receptor α (ER) antagonists. The selected protocol, which gave acceptable enrichment factors as a virtual screening protocol, subsequently used to virtually screen eugenol, its analogs and their dimers. Based on the virtual screening results, dimer eugenol of 4-[4-hydroxy-3-(prop-2-en-1- yl)phenyl]-2-(prop-2-en-1-yl)phenol is recommended to be developed further in order to discover novel and potent ER antagonists.

The importance of ARG513 as a hydrogen bond anchor to discover COX-2 inhibitors in a virtual screening campaign

Structure-based virtual screening (SBVS) protocols were developed to find cyclooxygenase-2 (COX-2) inhibitors using the Protein-Ligand ANT System (PLANTS) docking software. The directory of useful decoys (DUD) dataset for COX-2 was used to retrospectively validate the protocols; the DUD consists of 426 known inhibitors in 13289 decoys. Based on criteria used in the article describing DUD datasets, the default protocol showed poor results. However, having ARG513 as a hydrogen bond anchor increased the quality of the SBVS protocol. The modified protocol showed results that could be well considered, with a maximum enrichment factor (EFmax) value of 32.2.

PyPLIF-ASSISTED REDOCKING INDOMETHACIN-(R)-ALPHA-ETHYL-ETHANOLAMIDE INTO CYCLOOXYGENASE-1

Identification of Protein-Ligand Interaction Fingerprints (PLIF) has been performed as the rescoring strategy to identify the best pose for the docked poses of indomethacin-(R)-α-ethyl-etanolamide (IMM) in the binding site of cyclooxygenase-1 (COX-1) from simulations using PLANTS molecular docking software version 1.2 (PLANTS1.2). Instead of using the scoring functions included in the docking software, the strategy presented in this article used external software called PyPLIF that could identify the interactions of the ligand to the amino acid residues in the binding pocket and presents them as binary bitstrings, which subsequently were compared to the interaction bitstrings of the co-crystal ligand pose. The results show that PyPLIF-assisted redocking strategy could select the correct pose much better compared to the pose selection without rescoring. Out of 1000 iterative attempts, PyPLIFassisted redocking simulations could identify 971 correct poses (more than 95%), while the redocking simulations without PyPLIF could only identify 500 correct poses (50%).These works have also provided us with the initial step of the construction of a valid Structure-Based Virtual Screening (SBVS) protocol to identify COX-1 inhibitors.

Natural Peptides in Drug Discovery Targeting Acetylcholinesterase

Acetylcholinesterase-inhibitory peptide has gained much importance since it can inhibit acetylcholinesterase (AChE) and increase the availability of acetylcholine in cholinergic synapses, enhancing cholinergic transmission in pharmacological treatment of Alzheimer’s disease (AD). Natural peptides have received considerable attention as biologically important substances as a source of AChE inhibitors. These natural peptides have high potential pharmaceutical and medicinal values due to their bioactivities as neuroprotective and neurodegenerative treatment activities. These peptides have attracted great interest in the pharmaceutical industries, in order to design potential peptides for use in the prophylactic and therapy purposes. Some natural peptides and their derivatives have high commercial values and have succeeded in reaching the pharmaceutical market. A large number of peptides are already in preclinical and clinical pipelines for treatment of various diseases. This review highlights the recent researches on the various natural peptides and future prospects for AD management.

Formulation and physical properties observations of soy lecithin liposome containing 4-n-butylresorcinol

Liposomes are preparations which have many advantages such as high solubility and good stability. The 4-n-butylresorcinol has the effect of hypopigmentation and, similar to resorcinol, is unstable. Liposomes could, therefore, assist the development of 4-n-butylresorcinol in a more appropriate dosage form. The research presented in this article aimed to determine the effect of the concentration of soy lecithin phospholipids to the liposome particle size. Subsequently, the effect of adding 4-n-butylresorcinol as the active compound to the liposomes in the particle size and morphology of the liposomes is also presented. The preparation of liposomes was assisted by sonication, and subsequently, the active compound 4-n-butylrecorcinol was added. Particle size and morphology of liposomes were then characterized as the observed parameters. In this research, there was no evidence that the size of the liposomes was significantly affected by the concentration of phospholipids. Notably, the particle size and morphol...

Scarless wound healing gel with Binahong (Anredera cordifolia (Ten) Steenis) leaves extract and celecoxib as the active ingredients

An optimum formula for wound-healing gel containing ethanolic extract of Binahong (Anredera cordifolia (Ten) Steenis) leaves had been developed previously. In addition, inhibiting cyclooxygenase-2 (COX-2) enzyme during the wound-healing process was reported to minimize the formation of scars. In this article, the preliminary research on the development of the scarless wound healing gel formula by adding COX-2 inhibitor celecoxib into wound healing gel is presented. Additional cyclooxygenase-2 inhibitor celecoxib in wound healing gel containing ethanolic extract of binahong leaves showed wound healing with the statistically smaller size of newly formed epidermis compared to the optimum formula of wound healing gel containing ethanolic extract of binahong without additional celecoxib. This indicates that scarless wound healing could be obtained by the application of gel containing ethanolic extract of binahong leaves and cyclooxygenase-2 inhibitor.

CONSTRUCTION AND OPTIMIZATION OF STRUCTURE-BASED VIRTUAL SCREENING PROTOCOLS TO IDENTIFY CYCLOOXYGENASE-1 INHIBITORS USING OPEN BABEL, SPORES AND PLANTS

Structure-Based Virtual Screening (SBVS) protocols to identify cyclooxygenase-1 (COX-1) inhibitors have been constructed and optimized based on their Root Mean Square Deviation (RMSD) values of the docked pose and the crystal structure pose of the reference ligand. Employing a COX-1 structure obtained from the Protein Data Bank (pdb) with code 2OYE as the reference protein and PLANTS1.2 as the molecular docking simulation program, the SBVS protocols were mainly built. The preparation steps involved SPORES and Open Babel, while the results analysis involved PyMOL to calculate the RMSD and R computational statistics software to perform the statistics calculations. The results show that these construction and optimization processes could provide an SBVS protocol to identify COX-1 inhibitors that is accurately able to redock the reference ligand with the RMSD value of 0.633 A.