VIRTUAL TARGET CONSTRUCTION FOR STRUCTURE-BASED SCREENING IN THE DISCOVERY OF HISTAMINE H2 RECEPTOR LIGANDS

Objective: This study aimed to develop validated targets to be employed in structure-based virtual screening (SBVS) to discover ligands for the human histamine H2 receptor (hHRH2). Methods: The virtual targets construction was initiated by homology modeling with the reference compound ranitidine as the ligand followed by 100 ns molecular dynamics (MD) simulations. During MD simulations, the snapshot with the lowest value of the free energy of binding was selected for further validation by re-docking simulations. All simulations were performed in YASARA-Structure. Results: The research presented here resulted in one validated target for the SBVS. Additionally, by employing a clustering module in MD simulations analysis in YASARA-Structure, more than ten different virtual targets are also available for further uses. Conclusion: The virtual targets resulted in this research offer possibilities to construct valid SBVS protocols to identify ligands for the hHRH2

Identifikasi Determinan Molekul Interaksi STK630921 pada Interleukin-17A

Interleukin-17A (IL-17A) merupakan sitokin pro-inflamasi yang terlibat dalam patogenesis beberapa penyakit, antara lain psoriasis, rheumatoid arthritis, kanker, diabetes dan penyakit ginjal stadium akhir. Peningkatan kadar serum IL-17A memberikan petunjuk adanya keterkaitan antara IL-17A pada kejadian nefropati diabetik. Keterkaitan ini juga diperjelas dengan temuan bahwa penghambatan aktivitas IL-17A dapat menurunkan albuminuria, cedera ginjal dan menunda perkembangan nefropati diabetik. Peranan IL-17A ini menjadikannya sebagai pilihan target potensial terapi nefropati diabetik yang sejauh ini bertumpu pada pengendalian optimal sistem renin angiotensin. Penelitian ini bertujuan mengidentifikasi determinan molekul interaksi STK630921 pada IL-17A. Penelitian dilakukan dengan penambatan molekul STK630921 pada protein IL-17A, dilanjutkan dengan simulasi dinamika molekul selama 15 ns. Identifikasi determinan molekul dilakukan menggunakan bantuan perangkat lunak PyPLIF-HIPPOS terhadap hasil simulasi dinamika molekul. Penelitian ini berhasil mengidentifikasikan asam-asam amino yang berperan penting yaitu His29, Trp67, Asn27, Lys114 dan Glu95 dengan interaksi aromatik dan interaksi hidrogen sebagai jenis interaksi yang berperan pada aktivitas STK630921 pada struktur protein 4HR9

Computational Prediction of the Mode of Binding of Antitumor Lankacidin C to Tubulin

Lankacidin C, which is an antibiotic produced by the organism Streptomyces rochei, shows considerable antitumor activity. The mechanism of its antitumor activity remained elusive for decades until it was recently shown to overstabilize microtubules by binding at the taxol binding site of tubulin, causing mitotic arrest followed by apoptosis. However, the exact binding mode of lankacidin C inside the tubulin binding pocket remains unknown, an issue that impedes proper structure-based design, modification, and optimization of the drug. Here, we have used computational methods to predict the most likely binding mode of lankacidin C to tubulin. We employed ensemble-based docking in different software packages, supplemented with molecular dynamics simulation and subsequent binding-energy prediction. The molecular dynamics simulations performed on lankacidin C were collectively 1.1 μs long. Also, a multiple-trajectory approach was performed to assess the stability of different potential binding modes. The identified binding mode could serve as an ideal starting point for structural modification and optimization of lankacidin C to enhance its affinity to the tubulin binding site and therefore improve its antitumor activity.The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsomega.8b03470

MOLECULAR DYNAMICS STUDIES OF FULL HUMAN MATRIX METALLOPROTEINASE 9 LIGANDED WITH N-HYDROXY-2-[(4-PHENYLPHENYL) SULFONYL-PROPAN-2-YLOXYAMINO] ACETAMIDE

The research presented in this article aimed to provide a full quarternary structure of human matrix metalloproteinase 9 (MMP9) enzyme with a ligand in the catalytic site for structure-based virtual screening. The enzyme plays an important role in wound healing of diabetic foot ulcer. By employing the primary structure of the enzyme obtained from UniProt database (UniProt:P14780), the theoretical structure of full apoenzyme of the human MMP9 (PDB:1LKG), the crystal structures of the catalytic domain (PDB:4H3X) and the hemopexin domain (PDB:1ITV) of the human MMP9, homology modeling studies have been performed. The ligand N-2-(biphenyl-4-yl-sulfonyl)-N-2-(isopropyloxy)-acetohydroxamic acid (CC27) or N-hydroxy-2-[(4-phenylphenyl)sulfonyl-propan-2-yloxyamino]acetamide (IUPAC version) from PDB:4H3X was embedded in the catalytic site of the enzyme. The modeling made use of the modules of homology modeling in YASARA structure. Subsequently, molecular dynamics (MD) simulations in YASARA structure were performed to examine the stability of the enzyme. The homology model was found stable after 5.05 ns and the lowest energy of the model was found at the 6.40 ns of the MD production run. This lowest energy snapshot was then energetically minimized and analyzed for its applicability for virtual screening. This optimized model was then stored in Mendeley Data (DOI: 10.17632/4gsb4p75gz.1)

Molecular Dynamics Simulation of Serotonin Transport Protein Complex with 6-Hydroxy-1-Methyl-1,2,3,4-Tetrahydro-β-Carboline Ligand from Chocolate (Theobroma cacao L.) Isolate

6-hydroxy-1-methyl1,2,3,4-tetrahydro-β-carboline (6OHMTHβC) is a chocolate derivate that has antidepressant potency. It can increase dopamine and serotonin secretion, which leads to mood improvement. This method was carried out using computational molecular docking simulations (in silico). The research design was computational-based exploratory descriptive. The results of molecular docking showed the lowest energy score and the backbone RMSD value ≤2Å. The procedure performed was 6AWP receptor docking without ligand, with native ligand (6OHMTHβC), and with reference ligand (fluvoxamine). This study also performed molecular docking simulations of 6OHMTHβC towards 6AWP to find compounds in the receptor binding pocket. This study also performed dynamics simulations and identified the molecular determinants using PyPLIF-HIPPOS and YASARA Structure software 20.1.24.10 with the Windows 10 operating system. This study succeeded in determining the stability of the dynamics simulation of the serotonin transport protein complex with the reference ligand 6OHMTHβC for 50 ns, and this result corresponds to the RMSD value and binding energy. The determination of binding energy (BE) was calculated from the BE calculation available at YASARA and Ubuntu. The binding energy value of the original ligand was -11.6590 kJ/mol, and the reference ligand was -83880 kJ/mol. The highest RMSD value of the original ligand was 1.39292Å, while the RMSD value of the reference ligand was 1.71072Å. The essential amino acid carried out was 438Ser with hydrogen bond interactions, so 6OHMTHβC was considered a competent antidepressant candidate

Molecular Dynamics Study of Human MTHFR Wild-Type and A222V Mutant-Type: A Computational Approach

Methylenetetrahydrofolate reductase (MTHFR) is an essential enzyme for the homeostasis and metabolism of intracellular folate. However, it is known that one of the commonly found MTHFR gene SNPs (A222V) causes a decrease in activity which decreases folate levels and increases the accumulation of homocysteine in the blood. The purpose of this study was to investigate the molecular dynamics of MTHFR wild-type protein and MTHFR A222V mutant protein in silico. After some preparations, the crystal structure of MTHFR with code 6FCX obtained from the Protein Data Bank was used as the input file for molecular dynamics (MD) simulations. YASARA-Structure was employed for performing 50 ns production run of MD simulations. The deviation of the root-mean-squared deviation value of the backbone atoms (∆RMSDBb) of MTHFR wild-type is consistently less than 2 Å from the beginning of the MD simulations production runs. On the other hand, there is a sudden spike of ∆RMSDBb of MTHFR A222V from 15.01 to 20.00 ns of 2.221 Å. According to the analysis of ∆RMSDBb, MTHFR wild-type protein is considered stable and the MTHFR A222V mutant protein is considered unstable which may lead to various clinical problems for the person possessing this mutation

Identification of the Glimepiride and Metformin Hydrochloride Physical Interaction in Binary Systems

Glimepiride is often combined with metformin HCl as an oral antidiabetic in type II diabetes mellitus, which provides a complementary and synergistic effect with multiple targets for insulin secretion. Glimepiride includes class II of BCS, which solubility practically insoluble in water but high permeability, which will impact the drug's small bioavailability. In contrast, metformin HCl includes class III of BCS, which has a high solubility in water, but low permeability is absorbed approximately 50-60% in the digestive tract given orally. The co-crystallization method can be used to improve the glimepiride solubility properties and the permeability properties of metformin HCl by interrupting glimepiride with metformin HCl physically. This study aims to identify the physical interactions between glimepiride and metformin HCL using a thermal analysis of Differential Scanning Calorimetry (DSC) and then confirmed by a computational approach. Identifying the physical interactions between glimepiride and metformin HCL was carried out by plotting the melting points generated from the endothermic peaks of the DSC thermogram at various compositions versus the mole ratios of the two were further confirmed by the computational approach using PatchDock. The results of the phase diagram analysis of the binary system between glimepiride and metformin HCl show a congruent pattern, which indicates the formation of co-crystal or molecular compounds at a 1 : 1 mole ratio at 228°C. Computational approach results showed that the interaction between glimepiride and metformin HCl did not form new compounds but heterosinton formation that was stable in molecular dynamics simulations

Inhibicija ksantin oksidaze derivatima 1,2,3,4-tetrahidroizohinolina

Xanthine oxidase (XO) is a versatile metalloflavoprotein enzyme that is best known for its rate-limiting role in the purine degradation pathway. Therapeutic inhibition of XO is based on its role in a variety of diseases that is attributed either to the hyperproduction of uric acid, or the hyperproduction of reactive oxygen species. Herein, we report the assessment of XO inhibitory properties of 24 1,2,3,4-tetrahydroisoquinoline derivatives, among which compound 16 exhibited IC50 value of 135.72 ± 2.71 µM. The interaction of compound 16 with XO enzyme was simulated using the Site Finder module, molecular docking and molecular dynamics. Molecular modeling suggests that interactions with Met 1038, Gln 1040, Thr 1077, Gln 1194 and Val 1259 are an important factor for inhibitor affinity toward the XO enzyme. Our proposed binding model might be beneficial for the discovery of new active 1,2,3,4-tetrahydroisoquinoline-based inhibitors of XO enzyme.Ksantin oksidaza (XO) je metaloflavoproteinski enzim, koji je najpoznatiji po svojoj ulozi ograničavanja brzine razgradnje purinskih nukleotida. Terapijska inhibicija XO zasniva se na njenoj ulozi u brojnim bolestima, koje su povezane bilo sa hiperprodukcijom mokraćne kiseline ili hiperprodukcijom reaktivnih kiseoničnih vrsta. U ovom radu izvršeno je ispitivanje sposobnosti inhibicije XO 24 derivata 1,2,3,4-tetrahidroizohinolina, od kojih je jedinjenje 16 pokazalo IC50 vrednost od 135,72 µM ± 2,71 µM. Interakcija jedinjenja 16 sa XO enzimom simulirana je korišćenjem Site Finder modula molekularnog dokinga i molekularne dinamike. Molekulsko modelovanje ukazuje na to da su interakcije sa Met 1038, Gln 1040, Thr 1077, Gln 1194 i Val 1259 važan faktor postojanja afiniteta inhibitora prema XO enzimu. Naš predloženi model vezivanja mogao bi biti od značaja za razvoj novih aktivnih inhibitora XO zasnovanih na 1,2,3,4-tetrahidroizohinolinskom heterociklusu

Identification of a novel potassium channel (GiK) as a potential drug target in Giardia lamblia: Computational descriptions of binding sites

Background The protozoan Giardia lamblia is the causal agent of giardiasis, one of the main diarrheal infections worldwide. Drug resistance to common antigiardial agents and incidence of treatment failures have increased in recent years. Therefore, the search for new molecular targets for drugs against Giardia infection is essential. In protozoa, ionic channels have roles in their life cycle, growth, and stress response. Thus, they are promising targets for drug design. The strategy of ligand-protein docking has demonstrated a great potential in the discovery of new targets and structure-based drug design studies. Methods In this work, we identify and characterize a new potassium channel, GiK, in the genome of Giardia lamblia. Characterization was performed in silico. Because its crystallographic structure remains unresolved, homology modeling was used to construct the three-dimensional model for the pore domain of GiK. The docking virtual screening approach was employed to determine whether GiK is a good target for potassium channel blockers. Results The GiK sequence showed 24–50% identity and 50–90% positivity with 21 different types of potassium channels. The quality assessment and validation parameters indicated the reliability of the modeled structure of GiK. We identified 110 potassium channel blockers exhibiting high affinity toward GiK. A total of 39 of these drugs bind in three specific regions. Discussion The GiK pore signature sequence is related to the small conductance calcium-activated potassium channels (SKCa). The predicted binding of 110 potassium blockers to GiK makes this protein an attractive target for biological testing to evaluate its role in the life cycle of Giardia lamblia and potential candidate for the design of novel antigiardial drugs

Targeting allosteric sites of Escherichia coli heat shock protein 70 for antibiotic development

Hsp70s are members of the heat shock proteins family with a molecular weight of 70-kDa and are the most abundant group in bacterial and eukaryotic systems, hence the most extensively studied ones. These proteins are molecular chaperones that play a significant role in protein homeostasis by facilitating appropriate folding of proteins, preventing proteins from aggregating and misfolding. They are also involved in translocation of proteins into subcellular compartments and protection of cells against stress. Stress caused by environmental or biological factors affects the functionality of the cell. In response to these stressful conditions, up-regulation of Hsp70s ensures that the cells are protected by balancing out unfolded proteins giving them ample time to repair denatured proteins. Hsp70s is connected to numerous illnesses such as autoimmune and neurodegenerative diseases, bacterial infection, cancer, malaria, and obesity. The multi-functional nature of Hsp70s predisposes them as promising therapeutic targets. Hsp70s play vital roles in various cell developments, and survival pathways, therefore targeting this protein will provide a new avenue towards the discovery of active therapeutic agents for the treatment of a wide range of diseases. Allosteric sites of these proteins in its multi-conformational states have not been explored for inhibitory properties hence the aim of this study. This study aims at identifying allosteric sites that inhibit the ATPase and substrate binding activities using computational approaches. Using E. coli as a model organism, molecular docking for high throughput virtual screening was carried out using 623 compounds from the South African Natural Compounds Database (SANCDB; https://sancdb.rubi.ru.ac.za/) against identified allosteric sites. Ligands with the highest binding affinity (good binders) interacting with critical allosteric residues that are druggable were identified. Molecular dynamics (MD) simulation was also performed on the identified hits to assess for protein-inhibitor complex stability. Finally, principal component analysis (PCA) was performed to understand the structural dynamics of the ligand-free and ligand-bound structures during MD simulation