Saima Kalsoom

Identification of type-specific anticancer histone deacetylase inhibitors: road to success

Cancer is a serious and life-eliminating disease. Majority of anticancer agents are non-selective. Along with the cancerous cells they also target the normal ones. An important aspect is to hit the developing mechanism of the tumor, which is highlighted by in silico drug designing. On the basis of novel molecular targets, in silico (computational approach) drug discovery has emerged as today’s need. Histone deacetylases are an important therapeutic target for many human cancers. The first and only approved (in 2006) histone deacetylase inhibitors (HDACIs) is Zolinza. Depending on the types of the histone deacetylase (HDAC) enzymes, discovery of type-specific inhibitors is important. With continued research and development, in near future HDACIs are likely to figure prominently in cancer treatment plans. This review presents the overview of HDACs, their role in cancer, their structural classes, activity, catalytic domain and the inhibitors of HDACs for cancer therapy. Also it helps in understanding the open directions in this area of research and highlights the importance of computational approaches in discovering specific drugs for cancer therapy.

In silico studies on 2,3-dihydro-1,5-benzothiazepines as cholinesterase inhibitors

In vitro studies on cholinesterase inhibitory potential on the three sets of 2,3-dihydro-1,5-benzothiazepines have been carried out. The compounds in Set 1 were unsubstituted on ring A, while those in Sets 2 and 3 had a 2′- and 3′-hydoxy substituent, respectively, in ring A. These studies revealed that they are mixed inhibitors of both AChE and BChE as reflected from their IC50 values. It was further observed that 3′-hydroxy substituted benzothiazepines (Set 3) were found to have stronger affinity for both AChE and BChE compared with those of Sets 1 and 2. Moreover, all the compounds in Set 3 were found to be stronger BChE inhibitors than AChE. These experimental observations were rationalized by conducting in silico studies using molecular docking tool of Molecular Operating Environment (MOE) software, thereby, a good correlation was observed between IC50 values and their binding interactions within the enzyme active site. We have observed that these interactions were electrostatic and hydrophobic in nature besides hydrogen bonding. The high BChE inhibitory potential of 3′-hydroxy substituted benzothiazepines was found to be cumulative effect of hydrogen bonding and π–π interactions between the ligand and BChE. These findings may serve as a guideline for synthesizing more potent ChE inhibitors for the treatment of Alzheimer’s disease and related dementias.

Synthesis, molecular docking and biological evaluation of new thiazolopyrimidine carboxylates as potential antidiabetic and antibacterial agents

Abstract A series of new thiazolopyrimidine analogues were conveniently synthesized by one-pot multicomponent condensation reaction of ethyl acetoacetate, 2-aminothiazole and benzaldehyde substituted with different electron-donating and electron-withdrawing groups, in order to find some more potent antidiabetic and antibacterial drugs. The structures of the synthesized compounds were assigned based on elemental analyses and spectral data. An in vitro effect on total serum concentration of glucose, cholesterol and triglycerides was evaluated in adult male BALB/c mice, compared to two standard drugs “alloxan” and “glibenclamide,” and good results were observed with the presence of –Cl and –Br groups at the para position of the phenyl ring. The antibacterial activities were tested against five bacterial strains, Micrococcus luteus, Salmonella typhimurium, Bacillus subtilis, Bordetella bronchiseptica and Escherichia coli. Most of the compounds showed good to excellent bacterial zone inhibition compared to the reference drug “kanamycin.” An in silico molecular docking was also performed on synthesized compounds to support the experimental findings, which were in good agreement with computational results. The current study is expected to provide useful insights into the design of antidiabetic and antibacterial drugs, and understanding the mechanism by which such drugs interact with RNA and diabetes targets and exert their biochemical action.

In vitro and in silico exploration of IL-2 inhibition by small drug-like molecules

Interleukin-2 (IL-2) is an immunoregulatory cytokine produced by T lymphocytes in response to antigen. It is a potent growth and differentiation factor for several cell-types and is structurally related to the four-helix bundle family of cytokines. Here, we report IL-2 inhibitory potential and computational studies on different series of chalcones, benzothiazepines, semicarbazones, and dihydropyrimidines. These compounds were synthesized in wet lab and were then tested for their potency as IL-2 inhibitors through in vitro T cell proliferation, IL-2 cytokine production as well as their effect on oxidative burst. Compounds that showed significant suppressive activity were further evaluated for their cytotoxicity on normal two cell lines. Most of the chalcones were found to have a powerful inhibitory effect on T-lymphocytes proliferation and cytokine production. Among the aza heterocycles benzothiazepines, benzoxazepines, and benzodiazepinones were found to be the strongest IL-2 inhibitors. Molecular docking and MD simulation studies were carried out to correlate experimental and theoretical results whereby a good correlation was observed which indicated that computational studies could provide an alternate tool for the identification and designing of more potent IL-2 inhibitors.

An efficient anticancer histone deacetylase inhibitor and its analogues for human HDAC8

Histone deacetylase inhibitors (HDACIs) have emerged as efficient chemotherapeutic agents. Molecular docking studies of hydroxamtes, biphenyl and benzamide derivatives using Human HDAC8 with pdb id: 1T69 have been carried out in order to find the most active anticancer HDACI. AutoDock 4.0 has been used for docking. The most active lead compound has been identified on the basis of strong interactions and IC50 value from the chosen compounds. Five structural analogues have also been designed from the active lead compound.

In silico ligand-based pharmacophore model generation for the identification of novel Pneumocystis carinii DHFR inhibitors

The ubiquitous enzyme, dihydrofolate reductase (DHFR), is a well-studied metabolic enzyme of significant pharmacological relevance. The past research studies have shown that DHFR has emerged as an important therapeutic target for the treatment of various diseases including cancers, bacterial and protozoal infections, and the opportunistic infections that are associated with AIDS. DHFR has been successfully used and selected as a target for the purpose of devising a cure for various diseases by discovering the antimicrobial drugs against a range of pathogenic microorganisms including the opportunistic microorganisms Pneumocystis carinii (pc), Toxoplasma gondii and Mycobacterium avium complex. However, it has been reported that blockage of the enzymatic activity of DHFR is a crucial and most significant element in terms of the treatment of a wide range of diseases. DHFR is also a key enzyme in the treatment of Pneumocystosis. The discovery and development of type-specific pcDHFR inhibitors is of both research and clinical interests. Ligand-based pharmacophore modeling is playing a vital role for the identification of ligand features for the particular targets. In this study, we present a model for the design of ligand-based pharmacophore onto the set of 10 compounds of eight different classes along with the standard drug trimethoprim. The ligand-based pharmacophore model has been identified to facilitate the discovery of type-specific pcDHFR inhibitors. A pharmacophore model was generated using Ligand Scout 3.02 with diverse classes of pcDHFR inhibitors. The proposed pharmacophore model generated in this study revealed that the model contains two HBAs, two HBDs, and one HY/AR volume. Ligand Scout 3.02 has been used to predict the pharmacophore features for pcDHFR inhibitors, and the distances between pharmacophore features have been computed by the effective use of the software VMD. The results indicate that the in silico methods are valuable for the prediction of the biological activity of the compound or compound library by screening it against a predicted pharmacophore. Thus, the results obtained in this study can be considered to be useful and reliable tools for the identification of structurally diverse compounds with the desired biological activity. The model has also been validated, firstly by mapping of five test compounds on to our model and secondly by docking these test compounds into the active site of pcDHFR.