Structure-based drug design, synthesis and screening of MmaA1 inhibitors as novel anti-TB agents.

Tuberculosis is one of the leading causes of death across the world. The treatment regimens for tuberculosis are well established, but still the control of the disease faces many challenges such as lengthy treatment protocols, drug resistance and toxicity. In the present work, mycolic acid methyl transferase (MmaA1), a protein involved in the maturation of mycolic acids in the biochemical pathway of the Mycobacterium, was studied for novel drug discovery. The homology model of the MmaA1 protein was built and validated by using computational techniques. The MmaA1 protein has 286 amino acid residues consisting of 10 α-helices and 7 ß-sheets. The active site of the MmaA1 protein was identified using CASTp, SiteMap and PatchDock. Virtual screening studies were performed with two small molecule ligand databases: Asinex synergy and Diverse_Elite_Gold_Platinum databases having a total of 43,446 molecules and generated 1,30,814 conformers against the predicted and validated active site of the MmaA1 protein. Binding analysis showed that the residues ASP 19, PHE 22, TRP 30, TYR 32, TRP 74 and ALA 77 of MmaA1 protein have consistent interactions with the ligands. The hit ligands were further filtered by in silico ADME properties to eliminate potentially toxic molecules. Of the top 10 molecules, 3-(2-morpholinoacetamido)-N-(1,4-dihydro-4-oxoquinazolin-6-yl) benzamide was synthesised and screened for in vitro anti-TB activity against Mtb H37Rv using MABA assay. The compound and its intermediates exhibited good in vitro anti-TB activity which can be taken up for future lead optimisation studies. Structure based virtual screening study was performed using a validated homology model against small molecules from two virtual compound libraries. Synthesised the lead compound 3-(2-morpholinoacetamido)-N-(1,4-dihydro-4-oxoquinazolin-6-yl)benzamide obtained from virtual screening. In vitro activity against Mtb H37Rv has given a promising result.

Structural insights into suppressor of cytokine signaling 1 protein- identification of new leads for type 2 diabetes mellitus.

The study considers the Suppressor of cytokine signaling 1 (SOCS1) protein as a novel Type 2 diabetes mellitus (T2DM) drug target. T2DM in human beings is also triggered by the over expression of SOCS proteins. The SOCS1 acts as a ubiquitin ligase (E3), degrades Insulin Receptor Substrate 1 and 2 (IRS1 and IRS2) proteins, and causes insulin resistance. Therefore, the structure of the SOCS1 protein was evaluated using homology-modeling and molecular dynamics methods and validated using standard computational protocols. The Protein-Protein docking study of SOCS1 with its natural substrates, IRS1 and IRS2, and subsequent solvent accessible surface area analysis gave insight into the binding region of the SOCS1 protein. The in silico active site prediction tools highlight the residues Val155 to Ile211 in SOCS1 being implicated in the ubiquitin mediated protein degradation of the proteins IRS1 and IRS2. Virtual screening in the active site region, using large structural databases, results in selective lead structures with 3-Pyridinol, Xanthine, and Alanine moieties as Pharmacophore. The virtual screening study shows that the residues Glu149, Gly187, Arg188, Leu191, and Ser205 of the SOCS1 are important for binding. The docking study with current anti-diabetic therapeutics shows that the drugs Glibenclamide and Glyclopyramide have a partial affinity towards SOCS1. The predicted ADMET and IC50 properties for the identified ligands are within the acceptable range with drug-like properties. The structural data of SOCS1, its active site, and the identified lead structures are expedient in the development of new T2DM therapeutics.

Identification of small molecular inhibitors for efflux protein Rv2688c of Mycobacterium tuberculosis.

Mycobacterium tuberculosis (Mtb) is the pathogen, which causes tuberculosis. The development of multidrug-resistant and extensively drug-resistant strains in Mtb is due to an efflux mechanism of antibiotics in the bacteria. The efflux pump proteins in the bacteria are implicated in the active efflux of antibiotics. The efflux pump protein, "fluoroquinolones export ATP-binding protein Rv2688c" (FEAB), is considered as a potential therapeutic target to prevent tuberculosis. In the present work, in silico protocols are applied to identify inhibitors for the FEAB protein to arrest the efflux mechanism. Comparative modeling techniques are used to build the protein structure. The generated structure consists of 9 helices, 13 beta strands, and 3 ß sheets. The active site is predicted using active site prediction server tools. The virtual screening protocols are carried out to generate small ligand inhibitor structures. The identified ligand molecules show selective binding with Ser97, Glu99, Lys149, Asp171, Glu172, and Ser175 amino acid residues of the protein. The ligand molecules are subjected to in silico prediction of pharmaco kinetic properties, and the predicted IC50 (HERG) of all the molecules are less than -5.0, which is indicative of the identified ligand molecules is being potentially good FEAB inhibitors.

Structural Evaluation and Binding Mode Analysis of CCL19 and CCR7 Proteins-Identification of Novel Leads for Rheumatic and Autoimmune Diseases: An Insilico study.

The Human Chemokine (C-C motif) ligand 19 (CCL19) protein plays a major role in rheumatic and autoimmune diseases. The 3D models of the CCL19 and its receptor CCR7 are generated using homology modeling and are validated using standard computational protocols. Disulfide bridges identified in 3D model of CCL19 protein give extra stability to the overall protein structure. The active site region of protein CCL19, containing N-terminal amino acid residues (Gly22 to Leu31), is predicted using in silico techniques. Protein-protein docking studies are carried out between the CCL19 and CCR7 proteins to analyse the active site binding interactions of CCL19. The binding domain of CCL19 is subjected to structure-based virtual screening of small molecule databases, and identified several bioisosteric ligand molecules having pyrrolidone and piperidone pharmacophores. The prioritized ligands with acceptable ADME properties are reported as new leads for the design of potential CCL19 antagonists for rheumatic and autoimmune disease therapies.

Selective ATP competitive leads of CDK4: Discovery by 3D-QSAR pharmacophore mapping and molecular docking approach.

The discovery of ATP competitive CDK4 inhibitors is an on-going challenging task in cancer therapy. Here, an attempt has been made to develop new leads targeting ATP binding site of CDK4 by applying 3D-QSAR pharmacophore mapping and molecular docking methods The outcome of 6 leads offers a significant contribution for selective CDK4 inhibition, since they show potential binding interactions with Val96, Arg101, and Glu144 residues of CDK4, that are unique and from other kinases. It is worth noting that there is a striking similarity in binding interactions of the leads and known CDK4 inhibitors, namely Abemaciclib, Palbociclib and Ribociclib. Further key features, including high dock score value, good predicted activity, scaffold diversity, and the acceptable ADME profile of leads, provide a great opportunity for the development of highly potent and selective ATP competitive inhibitors of CDK4.

Targeting the ubiquitin-conjugating enzyme E2D4 for cancer drug discovery-a structure-based approach.

Cancer progression is a global burden. The incidence and mortality now reach 30 million deaths per year. Several pathways of cancer are under investigation for the discovery of effective therapeutics. The present study highlights the structural details of the ubiquitin protein 'Ubiquitin-conjugating enzyme E2D4' (UBE2D4) for the novel lead structure identification in cancer drug discovery process. The evaluation of 3D structure of UBE2D4 was carried out using homology modelling techniques. The optimized structure was validated by standard computational protocols. The active site region of the UBE2D4 was identified using computational tools like CASTp, Q-site Finder and SiteMap. The hydrophobic pocket which is responsible for binding with its natural receptor ubiquitin ligase CHIP (C-terminal of Hsp 70 interacting protein) was identified through protein-protein docking study. Corroborating the results obtained from active site prediction tools and protein-protein docking study, the domain of UBE2D4 which is responsible for cancer cell progression is sorted out for further docking study. Virtual screening with large structural database like CB_Div Set and Asinex BioDesign small molecular structural database was carried out. The obtained new ligand molecules that have shown affinity towards UBE2D4 were considered for ADME prediction studies. The identified new ligand molecules with acceptable parameters of docking, ADME are considered as potent UBE2D4 enzyme inhibitors for cancer therapy.

Development of an in vitro Bioassay for Recombinant Human Erythropoietin (rHuEPO) Based on Proliferative Stimulation of an Erythroid Cell Line and Analysis of Sialic Acid Dependent Microheterogeneity: UT-7 Cell Bioassay.

Determination of biological activity and its comparison with clinical behavior is important in the quality assessment of therapeutic glycoproteins. In vivo studies are usually employed for evaluating bioactivity of these glycomolecules. However, alternative methods are required to simplify the bioassay and avoid ethical issues associated with in vivo studies. Negatively charged sialic acid residues are known to be critical for in vivo bioactivity of rHuEPO. To address this need, we employed the human acute myeloid leukemia cell line UT-7 for the determination of proliferative stimulation induced by rHuEPO. Relative potencies of various intact and sugar-trimmed rHuEPO preparations were estimated using the International Standard for Human r-DNA derived EPO (87/684) as a reference for bioactivity. The cellular response was measured with a multi-channel photometer using a colorimetric microassay, based on the metabolism of the Resazurin sodium by cell viability. For a resourceful probing of physiological features of rHuEPO with significance, we obtained partly or completely desialylated rHuEPO digested by the neuraminidase enzyme without degradation of carbohydrates. Two-fold higher specific activity was shown by asialoerythropoietin in in vitro analysis compared with the sialoerythropoietin. Further, computational studies were also carried out to construct the 3D model of the erythropoietin (EPO) protein structure using standard comparative modeling methods. The quality of the model was validated using Procheck and protein structure analysis (ProSA) server tools. N-glycan units were constructed; moreover, EPO protein was glycosylated at potential glycosylation amino acid residue sites. The method described should be suitable for potency assessments of pharmaceutical formulations of rHuEPO (European Pharmacopeia, 2016).

Identification of New Lead Molecules Against UBE2NL Enzyme for Cancer Therapy.

Cancer is characterized by abnormal growth of cells. Targeting ubiquitin proteins in the discovery of new anticancer therapeutics is an attractive strategy. The present study uses the structure-based drug discovery methods to identify new lead structures, which are selective to the putative ubiquitin-conjugating enzyme E2N-like (UBE2NL). The 3D structure of the UBE2NL was evaluated using homology modeling techniques. The model was validated using standard in silico methods. The hydrophobic pocket of UBE2NL that aids in binding with its natural receptor ubiquitin-conjugating enzyme E2 variant (UBE2V) was identified through protein-protein docking study. The binding site region of the UBE2NL was identified using active site prediction tools. The binding site of UBE2NL which is responsible for cancer cell progression is considered for docking study. Virtual screening study with the small molecular structural database was carried out against the active site of UBE2NL. The ligand molecules that have shown affinity towards UBE2NL were considered for ADME prediction studies. The ligand molecules that obey the Lipinski's rule of five and Jorgensen's rule of three pharmacokinetic properties like human oral absorption etc. are prioritized. The resultant ligand molecules can be considered for the development of potent UBE2NL enzyme inhibitors for cancer therapy.

Design of novel lead molecules against RhoG protein as cancer target - a computational study.

Cancer is a class of diseases characterized by uncontrolled cell growth. Every year more than 2 million people are affected by the disease. Rho family proteins are actively involved in cytoskeleton regulation. Over-expression of Rho family proteins show oncogenic activity and promote cancer progression. In the present work RhoG protein is considered as novel target of cancer. It is a member of Rho family and Rac subfamily protein, which plays pivotal role in regulation of microtubule formation, cell migration and contributes in cancer progression. In order to understand the binding interaction between RhoG protein and the DH domain of Ephexin-4 protein, the 3D structure of RhoG was evaluated and Molecular Dynamic Simulations was performed to stabilize the structure. The 3D structure of RhoG protein was validated and active site identified using standard computational protocols. Protein-protein docking of RhoG with Ephexin-4 was done to understand binding interactions and the active site structure. Virtual screening was carried out with ligand databases against the active site of RhoG protein. The efficiency of virtual screening is analysed with enrichment factor and area under curve values. The binding free energy of docked complexes was calculated using prime MM-GBSA module. The SASA, FOSA, FISA, PISA and PSA values of ligands were carried out. New ligands with high docking score, glide energy and acceptable ADME properties were prioritized as potential inhibitors of RhoG protein.

Identification of Novel Antagonists for Rab38 Protein by Homology Modeling and Virtual Screening.

BACKGROUND: The Rab family proteins are involved in membrane trafficking, cell growth and differentiation. Rab38 is implicated in the biogenesis of melanosomes that help in the synthesis, storage and transport of melanin pigments. The Rab38 protein is overexpressed at the RNA level in melanoma cancer. AIM AND OBJECTIVE: The protein Rab38 is targeted for identification of novel antagonists as cancer drug candidates. MATERIALS AND METHODS: The 3D structure of Rab38 was generated using homology modelling method. The 3D model was validated. The active site was identified by using standard computational prediction tools like CASTp, efindsite and SiteMap. The study of protein-protein docking was performed between Rab38 and its natural substrate BLOC-3 using patchDock server tool. Virtual screening protocols were carried out using glide module. Various informatics tools like 1) Schrodinger Suite 2) Modeller 3) Accelrys Discovery Studio 4) PyMOL 5) SPDBV etc. are applied for the identification of novel inhibitors of Rab38. RESULTS: The residues from SER35 to LEU63 of Rab38 protein are important for binding to ligands. The nineteen docked structures were obtained as an output of virtual screening. The compounds obtained show good glide score, and a common binding pattern at the active site. CONCLUSION: The benzosulfonamide and heterocyclic nitrogen moieties may be considered as pharmacophores for designing new anticancer leads with better docking score and admissible ADME properties. Our study helps in the identification of potential inhibitors against Rab38 and melanoma cancer.

Homology modeling and virtual screening studies of FGF-7 protein-a structure-based approach to design new molecules against tumor angiogenesis.

Keratinocyte growth factor (KGF) protein is a member of the fibroblast growth factor (FGF) family, which is also known as FGF-7. The FGF-7 plays an important role in tumor angiogenesis. In the present work, FGF-7 is treated as a potential therapeutic target to prevent angiogenesis in cancerous tissue. Computational techniques are applied to evaluate and validate the 3D structure of FGF-7 protein. The active site region of the FGF-7 protein is identified based on hydrophobicity calculations using CASTp and Q-site Finder active site prediction tools. The protein-protein docking study of FGF-7 with its natural receptor FGFR2b is carried out to confirm the active site region in FGF-7. The amino acid residues Asp34, Arg67, Glu116, and Thr194 in FGF-7 interact with the receptor protein (FGFR2b). A grid is generated at the active site region of FGF-7 using Glide module of Schrödinger suite. Subsequently, a virtual screening study is carried out at the active site using small molecular structural databases to identify the ligand molecules. The binding interactions of the ligand molecules, with piperazine moiety as a pharmacophore, are observed at Arg67 and Glu149 residues of the FGF-7 protein. The identified ligand molecules against the FGF-7 protein show permissible pharmacokinetic properties (ADME). The ligand molecules with good docking scores and satisfactory pharmacokinetic properties are prioritized and identified as novel ligands for the FGF-7 protein in cancer therapy.

Virtual screening studies to identify novel inhibitors for Sigma F protein of Mycobacterium tuberculosis.

Tuberculosis (TB) is one of the oldest threats to public health. TB is caused by the pathogen Mycobacterium tuberculosis (MTB). The Sigma factors are essential for the survival of MTB. The Sigma factor Sigma F (SigF) regulates genes expression under stress conditions. The SigF binds to RNA polymerase and forms a holoenzyme, which initiates the transcription of various genes. The Usfx, an anti-SigF protein, binds to SigF and alters the transcription initiation and gene expression. In the present work, virtual screening studies are taken up to identify the interactions between SigF and small molecular inhibitors which can inhibit the formation of holoenzyme. The studies reveal that ARG 104 and ARG 224 amino acid residues of SigF protein are forming important binding interactions with the ligands. The in silico ADME properties for the ligand data set are calculated to check the druggability of the molecules.

Homology modeling and virtual screening of ubiquitin conjugation enzyme E2A for designing a novel selective antagonist against cancer.

Cancer is a major health problem in the world. The initiation and progression of cancer is due to imbalance between the programmed cell growth and death. These processes are triggered by the ubiquitin family enzymes. The ubiquitin-like proteins are responsible for the cell metabolism. Ubiquitin-dependent proteolysis by the 26s proteasome plays a crucial role in cell cycle progression as well as in tumorigenesis. In the ubiquitin proteasomal degradation pathway, ubiquitin conjugation enzyme E2A (UBE2A) binds with ubiquitin ligase RAD18, results in polyubiquitation reaction and cell cycle progression. UBE2A is an important contributing factor for the control of tumorigenesis. In the present work, the 3D model of the protein UBE2A was generated by homology modeling technique. The generated 3D structure of the UBE2A was validated, and active site was identified using standard computational protocols. The active site was subjected to structure-based virtual screening using small molecule data banks, and new molecules were identified. The ADME properties of the new ligand molecules were predicted, and the new ligands are identified as potent UBE2A antagonists for cancer therapy.

Cellular uptake, cytotoxicity, apoptosis, DNA-binding, photocleavage and molecular docking studies of ruthenium(II) polypyridyl complexes.

Three new mononuclear [Ru (phen)2 ptip](2+) (1), [Ru (bpy)2 ptip](2+) (2) and [Ru (dmb)2 ptip](2+) (3) [ptip=(2-(5-phenylthiophen-2-yl)-1H-imidazo[4, 5-f][1,10 phenanthroline, phen=1, 10 phenanthroline, bpy=2, 2' bipyridine, dmb=4, 4'-dimethyl 2, 2' bipyridine] complexes were synthesized and characterised by elemental analysis, IR, NMR and Mass spectra. The DNA-binding behaviours were investigated by electronic absorption titration, luminescence spectra, viscosity measurements and photo-activated cleavage. The DNA-binding constants Kb of complexes 1, 2 and 3 were determined to be 7.0 (± 0.06)× 10(5), 3.87 (± 0.04) × 10(5), 2.79 (±0.07) × 10(5) respectively. The results showed that these complexes interact with CT-DNA by intercalative mode. Cell viability experiments indicated that the Ru(II) complex showed significant dose-dependent cytotoxicity to HeLa tumour cell lines. Further flow cytometry experiments showed that the cytotoxic Ru(II) complex induced apoptosis of HeLa tumour cell lines. Our data demonstrated that the Ru(II) polypyridyl complex binds to DNA and thereby induces apoptosis in tumor cells, suggesting that anti-tumor activity of the Ru(II) complex could be related to its interaction with DNA. The molecular dynamic simulations and docking methods were used to predict the DNA binding affinity of ruthenium complexes and with good visualisation images supporting with experimental results.

Macromolecular structure and interaction studies of SigF and Usfx in Mycobacterium tuberculosis.

Mycobacterium tuberculosis (Mtb) is an intracellular human parasite that causes tuberculosis (TB). The parasite is capable of surviving under stress conditions. The gene expression in Mtb is regulated by sigma factor family of proteins. The SigF protein belongs to the sigma factor family, expressed during stationary and growth phase, 14 genes are directly regulated by SigF and has a role in the expression of the principal sigma factor SigB as well. The interacting partner Usfx, the anti SigF protein, controls the regulation of SigF. The structures of SigF and Usfx were evaluated using comparative modelling techniques and validated. The active sites of the two proteins were identified. The protein-protein interaction studies between SigF and Usfx reveal His53, Phe226 and Asp227 residues of SigF protein to be involved in binding with Arg108, Arg130 and Glu140 amino acids of Usfx. The present study focuses on identification of important residues involved in binding of SigF protein with Usfx, which are essential in the inhibition of transcription initiation and survival of Mtb.

Identification of novel leads applying in silico studies for Mycobacterium multidrug resistant (MMR) protein.

Multidrug efflux mechanism is the main cause of intrinsic drug resistance in bacteria. Mycobacterium multidrug resistant (MMR) protein belongs to small multidrug resistant family proteins (SMR), causing multidrug resistance to proton (H(+))-linked lipophilic cationic drug efflux across the cell membrane. In the present work, MMR is treated as a novel target to identify new molecular entities as inhibitors for drug resistance in Mycobacterium tuberculosis. In silico techniques are applied to evaluate the 3D structure of MMR protein. The putative amino acid residues present in the active site of MMR protein are predicted. Protein-ligand interactions are studied by docking cationic ligands transported by MMR protein. Virtual screening is carried out with an in-house library of small molecules against the grid created at the predicted active site residues in the MMR protein. Absorption distribution metabolism and elimination (ADME) properties of the molecules with best docking scores are predicted. The studies with cationic ligands and those of virtual screening are analysed for identification of new lead molecules as inhibitors for drug resistance caused by the MMR protein.

Pharmacophore mapping and in silico screening to identify new potent leads for A(2A) adenosine receptor as antagonists.

A(2A) adenosine receptor (AR) antagonists play an important role in neurodegenerative diseases like Parkinson's disease. A 3D-QSAR study of A(2A) AR antagonists, was taken up to design best pharmacophore model. The pharmacophoric features (ADHRR) containing a hydrogen bond acceptor (A), a hydrogen bond donor (D), a hydrophobic group (H) and two aromatic rings (R), is projected as the best predictive pharmacophore model. The QSAR model was further treated as a template for in silico search of databases to identify new scaffolds. The binding patterns of the leads with A(2A) AR are analysed using docking studies and novel potent ligands of A(2A) AR are projected.

Identification of novel selective antagonists for cyclin C by homology modeling and virtual screening.

Cancer is a global multidrug resistant calamity, demanding an urgent need to design a novel/potent anti cancer agent. CDK8, 3/cyclin C biosynthetic pathway plays a specific role in G(0)/G(1)/S phases of cell cycle. Cyclin C is identified as a potential anti cancer target candidate. In order to understand the mechanism of ligand binding and interaction between ligand and cyclin C, a 3D homology model for cyclin C is generated. The cyclin C binding groove can be checked by small ligand molecules leading to inhibition. Virtual screening of molecules from an online data base of ChemBank library throws light to arrive at possible inhibitors for cyclin C inhibition. The molecules with better docking scores and acceptable ADME properties were prioritised to obtain potential lead molecules as cyclin C inhibitors.

Study of interactions between Mycobacterium tuberculosis proteins: SigK and anti-SigK.

The development of novel antituberculosis therapeutic molecules is a global health concern. Complex gene expression in Mycobacterium tuberculosis is mediated mainly by various sigma factors. The SigK protein binds to RNA polymerase, facilitating the expression of genes encoding the antigenic proteins mpt70 and mpt83. The anti-SigK protein is a negative regulator of SigK and inhibits the initiation of transcription. This study focuses on the interactions between SigK and the N-terminal domain of anti-SigK. The 3D structures of SigK (187 residues) and the N-terminal domain of anti-SigK (92 residues) are elucidated, using the crystal structures of the A and B chains of sigma E and anti-sigma ChrR of Rhodobacter spheroides (PDB code: 2Q1Z) as templates, respectively. Molecular dynamic simulations were performed for the SigK and anti-SigK proteins to refine their structures. The predicted active sites of SigK and anti-SigK and the results of protein-protein docking studies revealed the residues that are important for binding. The models generated and the binding site residues identified in this work throw new light on the interactions between the sigma K and anti-sigma K proteins, which should further aid the modulation of antigenic protein production in Mycobacterium tuberculosis.