Vigneshwaran Namasivayam

Skin whitening agents: medicinal chemistry perspective of tyrosinase inhibitors

Abstract Melanogenesis is a process to synthesize melanin, which is a primary responsible for the pigmentation of human skin, eye and hair. Although numerous enzymatic catalyzed and chemical reactions are involved in melanogenesis process, the enzymes such as tyrosinase and tyrosinase-related protein-1 (TRP-1) and TRP-2 played a major role in melanin synthesis. Specifically, tyrosinase is a key enzyme, which catalyzes a rate-limiting step of the melanin synthesis, and the downregulation of tyrosinase is the most prominent approach for the development of melanogenesis inhibitors. Therefore, numerous inhibitors that target tyrosinase have been developed in recent years. The review focuses on the recent discovery of tyrosinase inhibitors that are directly involved in the inhibition of tyrosinase catalytic activity and functionality from all sources, including laboratory synthetic methods, natural products, virtual screening and structure-based molecular docking studies.

Classification of compounds with distinct or overlapping multi-target activities and diverse molecular mechanisms using emerging chemical patterns.

The emerging chemical patterns (ECP) approach has been introduced for compound classification. Thus far, only very few ECP applications have been reported. Here, we further investigate the ECP methodology by studying complex classification problems. The analysis involves multi-target data sets with systematically organized subsets of compounds having distinct or overlapping target activities and, in addition, data sets containing classes of specifically active compounds with different mechanism-of-action. In systematic classification trials focusing on individual compound subsets or mechanistic classes, ECP calculations utilizing numerical descriptors achieve moderate to high sensitivity, dependent on the data set, and consistently high specificity. Accurate ECP predictions are already obtained on the basis of very small learning sets with only three positive training instances, which distinguishes the ECP approach from many other machine learning techniques.

Searching for Coordinated Activity Cliffs Using Particle Swarm Optimization

Activity cliffs are formed by structurally similar compounds having large potency differences. Coordinated activity cliffs evolve when compounds within groups of structural neighbors form multiple cliffs with different partners, giving rise to local networks of cliffs in a data set. Using particle swarm optimization, a machine learning approach, we systematically searched for coordinated activity cliffs in different compound sets. Regardless of the global SAR characteristics of these data sets, coordinated activity cliffs introducing strong local SAR discontinuity were identified in most cases. Compound subsets forming coordinated activity cliffs represent centers of SAR discontinuity and have high SAR information content. Through particle swarm optimization guided by subset discontinuity scoring, compounds forming the largest coordinated activity cliffs can automatically be extracted from large compound data sets.

Role of extracellular cysteine residues in the adenosine A2A receptor

The G protein-coupled A2A adenosine receptor represents an important drug target. Crystal structures and modeling studies indicated that three disulfide bonds are formed between ECL1 and ECL2 (I, Cys712.69-Cys15945.43; II, Cys743.22-Cys14645.30, and III, Cys773.25-Cys16645.50). However, the A2BAR subtype appears to require only disulfide bond III for proper function. In this study, each of the three disulfide bonds in the A2AAR was disrupted by mutation of one of the cysteine residues to serine. The mutant receptors were stably expressed in Chinese hamster ovary cells and analyzed in cyclic adenosine monophosphate (cAMP) accumulation and radioligand binding studies using structurally diverse agonists: adenosine, NECA, CGS21680, and PSB-15826. Results were rationalized by molecular modeling. The observed effects were dependent on the investigated agonist. Loss of disulfide bond I led to a widening of the orthosteric binding pocket resulting in a strong reduction in the potency of adenosine, but not of NECA or 2-substituted nucleosides. Disruption of disulfide bond II led to a significant reduction in the agonists’ efficacy indicating its importance for receptor activation. Disulfide bond III disruption reduced potency and affinity of the small adenosine agonists and NECA, but not of the larger 2-substituted agonists. While all the three disulfide bonds were essential for high potency or efficacy of adenosine, structural modification of the nucleoside could rescue affinity or efficacy at the mutant receptors. At present, it cannot be excluded that formation of the extracellular disulfide bonds in the A2AAR is dynamic. This might add another level of G protein-coupled receptor (GPCR) modulation, in particular for the cysteine-rich A2A and A2BARs.

Exploring SAR Continuity in the Vicinity of Activity Cliffs

Activity cliffs are formed by structurally similar compounds with significant differences in potency and represent an extreme form of structure–activity relationships discontinuity. By contrast, regions of structure–activity relationships continuity in compound data sets result from the presence of structurally increasingly diverse compounds retaining similar activity. Previous studies have revealed that structure–activity relationships information extracted from large compound data sets is often heterogeneous in nature containing both continuous and discontinuous structure–activity relationships components. Structure–activity relationships discontinuity and continuity are often represented by different compound series, independent of each other. Here, we have searched different compound data sets for the presence of structure–activity relationships continuity within the vicinity of prominent activity cliffs. For this purpose, we have designed and implemented a computational approach utilizing particle swarm optimization to examine the structural neighborhood of activity cliffs for continuous structure–activity relationships components. Structure–activity relationships continuity in the structural neighborhood of activity cliffs was relatively rarely observed. However, in a number of cases, notable structure–activity relationships continuity was detected in the vicinity of prominent activity cliffs. Exemplary local structure–activity relationships environments displaying these characteristics were analyzed in detail. Thus, the structure–activity relationships environment of activity cliffs must not necessarily be discontinuous in nature, and local structure–activity relationships continuity and discontinuity can occur in a concerted manner in series of structurally related compounds.

The promiscuous ectonucleotidase NPP1: Molecular insights into substrate binding and hydrolysis.

Abstract Nucleotide pyrophosphatase/phosphodiesterase 1 (NPP1) represents the main subtype of the NPP family of nucleotide hydrolyzing enzymes. The ecto-enzyme hydrolyzes structurally diverse substrates and has recently been proposed as a drug target for immuno-oncology. To get more insights into the nature of the promiscuity of NPP1, we investigated its substrate preferences employing a broad range of natural nucleotides including ATP, UTP, diadenosine tetraphosphate (AP4A), cAMP, and cyclic guanosine-(2′,5′)-monophosphate-adenosine-(3″,5″)-monophosphate (2′,3″-cGAMP), as well as the artificial substrate p-nitrophenyl 5′-thymidine monophosphate (p-Nph-5′-TMP). Despite their diverse structures, all substrates were converted to nucleoside 5′-monophosphates; 2′,3″-cGAMP yielded exclusively the nucleoside 5′-monophosphates AMP and GMP. In contrast, 3′,3″-bridged cyclic dinucleotides were not hydrolyzed. ATP was the most efficiently hydrolyzed substrate of NPP1, followed by AP4A and 2′,3″-cGAMP. UTP, cAMP and p-Nph-5′-TMP were much poorer substrates. A homology model of the human NPP1 was built based on the X-ray structure of its mouse orthologue. Docking studies were performed based on previously published mutagenesis data to rationalize the interactions of the different substrates and to explain the enzymes preferences. The results provide an improved understanding of the interactions of NPP1 with its diverse substrates and will contribute to the validation of NPP1 as a drug target.

Prediction of Individual Compounds Forming Activity Cliffs Using Emerging Chemical Patterns

Activity cliffs are formed by structurally similar or analogous compounds having large potency differences. In medicinal chemistry, pairs or groups of compounds forming activity cliffs are of interest for structure-activity relationship (SAR) analysis and compound optimization. Thus far, activity cliff assessment has mostly been descriptive, i.e., compound data sets and activity landscape representations have been searched for activity cliffs in the context of SAR analysis. Only recently, first attempts have also been made to depart from descriptive analysis and predict activity cliffs. This has been done by building computational models that distinguish compound pairs forming activity cliffs from non-cliff pairs. However, it is principally more challenging to predict single compounds that participate in activity cliffs. Here, we show that individual compounds having high or low potency can be accurately predicted to form activity cliffs on the basis of emerging chemical patterns.

Characterization of P2X4 receptor agonists and antagonists by calcium influx and radioligand binding studies

Graphical abstract Figure. No Caption available. ABSTRACT Antagonists for ATP‐activated P2X4 ion channel receptors are currently in the focus as novel drug targets, in particular for the treatment of neuropathic and inflammatory pain. We stably expressed the human, rat and mouse P2X4 receptors in 1321N1 astrocytoma cells, which is devoid of functional nucleotide receptors, by retroviral transfection, and established monoclonal cell lines. Calcium flux assay conditions were optimized for high‐throughput screening resulting in a Z′‐factor of >0.8. The application of ready‐to‐use frozen cells did not negatively affect the results of the calcium assays, which is of great advantage for the screening of compound libraries. Species differences were observed, the rat P2X4 receptor being particularly insensitive to many ATP derivatives. Membrane preparations of the cell lines showed high levels of specific [35S]ATP&ggr;S binding with low nonspecific binding (<5% of total binding), while non‐transfected cells were devoid of specific binding sites for the radioligand. Conditions were employed which allow binding studies to be performed at room temperature. While a variety of nucleotide‐derived agonists and the antagonist TNP‐ATP displaced [35S]ATP&ggr;S from its binding site at human P2X4 receptors, the non‐nucleotidic antagonists paroxetine and 5‐BDBD did not compete with radioligand binding and were therefore characterized as allosteric antagonists. Homology modeling was applied to find an explanation for the observed species differences.

An Overview of Severe Acute Respiratory Syndrome–Coronavirus (SARS-CoV) 3CL Protease Inhibitors: Peptidomimetics and Small Molecule Chemotherapy

Severe acute respiratory syndrome (SARS) is caused by a newly emerged coronavirus that infected more than 8000 individuals and resulted in more than 800 (10–15%) fatalities in 2003. The causative agent of SARS has been identified as a novel human coronavirus (SARS-CoV), and its viral protease, SARS-CoV 3CLpro, has been shown to be essential for replication and has hence been recognized as a potent drug target for SARS infection. Currently, there is no effective treatment for this epidemic despite the intensive research that has been undertaken since 2003 (over 3500 publications). This perspective focuses on the status of various efficacious anti-SARS-CoV 3CLpro chemotherapies discovered during the last 12 years (2003–2015) from all sources, including laboratory synthetic methods, natural products, and virtual screening. We describe here mainly peptidomimetic and small molecule inhibitors of SARS-CoV 3CLpro. Attempts have been made to provide a complete description of the structural features and binding modes of these inhibitors under many conditions.

Probing the binding mechanism of mercaptoguanine derivatives as inhibitors of HPPK by docking and molecular dynamics simulations

6-Hydroxymethyl-7,8-dihydropterin pyrophosphokinase (HPPK) is a promising antimicrobial target involved in the folate biosynthesis pathway. Although, the results from crystallographic studies of HPPK have attracted a great interest in the design of novel HPPK inhibitors, the mechanism of action of HPPK due to inhibitor binding remains questionable. Recently, mercaptoguanine derivatives were reported to inhibit the pyrophosphoryl transfer mechanism of Staphylococcus aureus HPPK (SaHPPK). The present study is an attempt to understand the SaHPPK-inhibitors binding mechanism and to highlight the key residues that possibly involve in the complex formation. To decipher these questions, we used the state-of-the-art advanced insilico approach such as molecular docking, molecular dynamics (MD), molecular mechanics-generalized Born surface area approach. Domain cross correlation and principle component analysis were applied to the snapshots obtained from MD revealed that the compounds with high binding affinity stabilize the conformational dynamics of SaHPPK. The binding free energy estimation showed that the van der Waals and electrostatic interactions played a vital role for the binding mechanism. Additionally, the predicted binding free energy was in good agreement with the experimental values (R2 = .78). Moreover, the free energy decomposition on per-residue confirms the key residues that significantly contribute to the complex formation. These results are expected to be useful for rational design of novel SaHPPK inhibitors.