Sk. Abdul Amin

Exploring pyrazolo[3,4-d]pyrimidine phosphodiesterase 1 (PDE1) inhibitors: a predictive approach combining comparative validated multiple molecular modelling techniques

Phosphodiesterase 1 (PDE1) is a potential target for a number of neurodegenerative disorders such as Schizophrenia, Parkinson’s and Alzheimer’s diseases. A number of pyrazolo[3,4-d]pyrimidine PDE1 inhibitors were subjected to different molecular modelling techniques [such as regression-based quantitative structure-activity relationship (QSAR): multiple linear regression, support vector machine and artificial neural network; classification-based QSAR: Bayesian modelling and Recursive partitioning; Monte Carlo based QSAR; Open3DQSAR; pharmacophore mapping and molecular docking analyses] to get a detailed knowledge about the physicochemical and structural requirements for higher inhibitory activity. The planarity of the pyrimidinone ring plays an important role for PDE1 inhibition. The N-methylated function at the 5th position of the pyrazolo[3,4-d]pyrimidine core is required for interacting with the PDE1 enzyme. The cyclopentyl ring fused with the parent scaffold is necessary for PDE1 binding potency. The phenylamino substitution at 3rd position is crucial for PDE1 inhibition. The N2-substitution at the pyrazole moiety is important for PDE1 inhibition compared to the N1-substituted analogues. Moreover, the p-substituted benzyl side chain at N2-position helps to enhance the PDE1 inhibitory profile. Depending on these observations, some new molecules are predicted that may possess better PDE1 inhibition.

First molecular modeling report on novel arylpyrimidine kynurenine monooxygenase inhibitors through multi-QSAR analysis against Huntington’s disease: A proposal to chemists!

Huntingtons disease (HD) is caused by mutation of huntingtin protein (mHtt) leading to neuronal cell death. The mHtt induced toxicity can be rescued by inhibiting the kynurenine monooxygenase (KMO) enzyme. Therefore, KMO is a promising drug target to address the neurodegenerative disorders such as Huntingtons diseases. Fiftysix arylpyrimidine KMO inhibitors are structurally explored through regression and classification based multi-QSAR modeling, pharmacophore mapping and molecular docking approaches. Moreover, ten new compounds are proposed and validated through the modeling that may be effective in accelerating Huntingtons disease drug discovery efforts.

Combating breast cancer with non-steroidal aromatase inhibitors (NSAIs): Understanding the chemico-biological interactions through comparative SAR/QSAR study

It is a challenging task to design target-specific and less toxic non-steroidal aromatase inhibitors (NSAIs) though the modeling studies for designing anti-aromatase molecules have been continuing for more than two decades to fight the dreaded estrogen-dependent breast cancer. In this article, different validated QSAR models are developed and analyzed to understand important physicochemical and structural parameters modulating the aromatase inhibitory activity of NSAIs. Physicochemical properties such as molar refractivity and dipole moment are found to be the most important parameters for controlling aromatase inhibition. This indicates the characteristic of bulky, complex and steric properties as well as, the flexibility of molecules is playing pivotal roles for aromatase inhibition. In many cases, hydrophobicity also plays important contribution. Regarding the structural point of view, some important indicator parameters are also found to be important for aromatase inhibitory activity. Though azole function is playing a crucial role by coordinating the heme moiety of the aromatase enzyme, the imidazole or the imidazolylmethyl ring systems may be better NSAIs than triazole, tetrazole or other azoles. The 4-pyridylmethyl group containing compounds are also found to be better NSAIs. The QSAR study, in a nutshell, provides a detailed understanding of the effectivity of NSAIs which is dependent mainly on the shape and size as well as the steric features of molecules and the heme-coordinator azole functions. These findings may open up a new horizon for designing new potential NSAIs that can be effective to reduce the mortality rate of breast cancer in future.

Insight into the structural requirements of pyrimidine-based phosphodiesterase 10A (PDE10A) inhibitors by multiple validated 3D QSAR approaches

Abstract Schizophrenia is a complex disorder of thinking and behaviour (0.3−0.7% of the population is affected). The over-expression of phosphodiesterase 10A (PDE10A) enzyme may be a potential target for schizophrenia and Huntington’s disease. Because 3D QSAR analysis is one of the most frequently used modelling techniques, in the present study, five different 3D QSAR tools, namely CoMFA, CoMSIA, kNN-MFA, Open3DQSAR and topomer CoMFA methods, were used on a dataset of pyrimidine-based PDE10A inhibitors. All developed models were validated internally and externally. The non-commercial Open3DQSAR produced the best statistical results amongst 3D QSAR tools. The structural interpretations obtained from different methods were thoroughly analysed and were justified on the basis of information obtained from the crystal structure. Information from one method was mostly validated by the results of other methods and vice versa. In the current work, the use of multiple tools in the same analysis revealed more complete information about the structural requirements of these compounds. On the basis of the observations of the 3D QSAR studies, 12 new compounds were designed for better PDE10A inhibitory activity. The current investigation may help in further designing new PDE10A inhibitors with promising activity.

Is dual inhibition of metalloenzymes HDAC-8 and MMP-2 a potential pharmacological target to combat hematological malignancies?

&NA; For the last three decades, metalloenzymes such as histone deacetylases (HDACs) and matrix metalloproteinases (MMPs) have been identified in promoting solid as well as hematological carcinogenesis. Histone deacetylase 8 (HDAC‐8), a class I HDAC enzyme, may serve as ‘epigenetic player’ that affects in the regulation of transcription factors and alters the structure of chromosome associated with tumorigenesis. It is established that the influence of MMP‐2 in invasion, metastasis and angiogenenic events of hematological malignancies may be suppressed by HDAC inhibitors through reversion‐inducing‐cysteine‐rich protein with kazal motifs (RECK) protein. Therefore, the isoform‐specific HDAC‐8 and MMP‐2 inhibitors may provide synergistic medicinal benefit in leukemia. However, a paucity of articles is available on dual acting HDAC‐8/MMP‐2 inhibitors. In this circumstance, a lot of works are still necessary to identify novel dual HDAC‐8/MMP‐2 inhibitors and this review will surely provide an initial idea regarding the utility of designing such type of dual inhibitors. Here, the importance of MMP‐2 and HDAC‐8 inhibition in hematological malignancies are focussed for the first time as per our knowledge along with the structure‐activity relationships (SARs) of a handful of molecules, some of which were synthesised in‐house, have been highlighted that will inspire more interactions between the medicinal chemistry and biology community to harness their expertise in design and discovery of the better acting dual inhibitors in future. Graphical abstract Figure. No caption available.

Insight into the Structural Requirements of Theophylline-Based Aldehyde Dehydrogenase lAl (ALDHlAl) Inhibitors Through Multi-QSAR Modeling and Molecular Docking Approaches.

Over expression of aldehyde dehydrogenase (ALDH1A1) is one of the vital hallmarks of the self-renewal and differentiational cancer stem cells (CSCs). Till now, no selective ALDH1A1 inhibitor is commercially available in the market. So there is an urgent need to explore some novel molecules which can selectively inhibit ALDH1A1 to combat cancer. Presently, our work deals with the development of QSAR models of some theophylline-based molecules by conventional 2D-QSAR, hologram QSAR (HQSAR), and Bayesian classification modeling. The descriptors identified from these QSAR models give avenues to modulate the structure of theophylline-based compounds to a desirable biological end point. Molecular docking study reveals the selectivity of these molecules towards ALDH1A1 (PDB: 4WP7) and important binding residues (GLY 125, 458; THR 129; TRP 178; TYR 297; PHE 171, 466; VAL 174, 460; MET 175; HIS 293 etc.) for the interaction with the receptors. The current study may help to design novel compounds as selective ALDH1A1 inhibitors.

Structure–activity relationships of hydroxamate-based histone deacetylase-8 inhibitors: reality behind anticancer drug discovery

The pan-histone deacetylase (HDAC) inhibitors comprise a fish-like structural orientation where hydrophobic aryl- and zinc-binding groups act as head and tail, respectively of a fish. The linker moiety correlates the body of the fish linking head and tail groups. Despite these pan-HDAC inhibitors, selective HDAC-8 inhibitors are still in demand as a safe remedy. HDAC-8 is involved in invasion and metastasis in cancer. This review deals with the rationale behind HDAC-8 inhibitory activity and selectivity along with detailed structure-activity relationships of diverse hydroxamate-based HDAC-8 inhibitors. HDAC-8 inhibitory potency may be increased by modifying the fish-like pharmacophoric features of such type of pan-HDAC inhibitors. This review may provide a preliminary basis to design and optimize new lead molecules with higher HDAC-8 inhibitory activity. This work may surely enlighten in providing useful information in the field of target-specific anticancer therapy.

An Integrated Multi-QSAR Modeling Approach for Designing Knoevenagel- Type Indoles with Enhancing Cytotoxic Profiles

BACKGROUND Unconventional Knoevenagel-type indoles have been the topic of interest of many synthetic chemists because of its promising efficacy in different diseases including cancer. OBJECTIVE To explore the structural requirements of Knoevenagel-type cytotoxic indoles for higher efficacy. METHODS Multi-QSAR modeling (MLR, ANN, SVM, Bayesian classification, HQSAR and Topomer CoMFA) was performed on these analogs. RESULTS All these modeling techniques were validated individually and interpreted with the experimental SAR observations. Phenyl or p-methoxyphenyl substitution at 2nd position, electron withdrawing groups (such as sulphonyl, cyano etc.) at 3rd position and methoxy substation at 5th position of the indole scaffold may favor cytotoxicity. Eight new indole molecules were predicted from the developed QSAR models. CONCLUSION These newly designed compounds may bind to the colchicine binding site of the tubulin protein as suggested by the molecular docking study.

Pharmacoinformatics study of Piperolactam A from Piper betle root as new lead for non steroidal anti fertility drug development

Fertility control is a burning problem all over the world to regulate population overflow and maintain ecological balance. This study is an in-silico approach to explore a non-steroidal lead as contraceptive agent in order to avoid several contraindications generated by steroidal analogues. Piperolactam A, an aristolactam isolated from Piper betle Linn. showed binding affinity towards estrogen and progesterone receptor as -8.9 and -9.0Kcal/mol (inhibition constant Ki=0.294μM and 0.249μM) respectively which is even larger than that of reported antagonists such as Rohitukine and OrgC (binding affinity -8.7 and -8.4Kcal/mol; Ki 0.443μM and 0.685μM respectively). The binding site exploration displayed more hydrogen bonding of Piperolactam A (His 524, Leu 346, Thr 347) than Rohitukine and OrgC (Leu 718) with associated receptors which was further confirmed by molecular dynamics simulations. The drug-likeliness of the compound has been proved from its tally with Lipinskys Rule of Five and lowered toxicity such as cardiac toxicity, liver toxicity, mutagenicity and ecological toxicity. Endocrine disruptome and later docking guided molecular simulations revealed that Piperolactam A has weaker binding affinity and/or lower probability of binding with nuclear receptors especially hERG and cytochrome P450. The high Caco-2 permeability suggested more bioavailability hence more therapeutic efficacy of the drug.

Hydroxyethylamine derivatives as HIV-1 protease inhibitors: a predictive QSAR modelling study based on Monte Carlo optimization

Abstract Application of HIV-1 protease inhibitors (as an anti-HIV regimen) may serve as an attractive strategy for anti-HIV drug development. Several investigations suggest that there is a crucial need to develop a novel protease inhibitor with higher potency and reduced toxicity. Monte Carlo optimized QSAR study was performed on 200 hydroxyethylamine derivatives with antiprotease activity. Twenty-one QSAR models with good statistical qualities were developed from three different splits with various combinations of SMILES and GRAPH based descriptors. The best models from different splits were selected on the basis of statistically validated characteristics of the test set and have the following statistical parameters: r2 = 0.806, Q2 = 0.788 (split 1); r2 = 0.842, Q2 = 0.826 (split 2); r2 = 0.774, Q2 = 0.755 (split 3). The structural attributes obtained from the best models were analysed to understand the structural requirements of the selected series for HIV-1 protease inhibitory activity. On the basis of obtained structural attributes, 11 new compounds were designed, out of which five compounds were found to have better activity than the best active compound in the series.