Design of Potent and Druglike Nonphenolic Inhibitors for Catechol O-Methyltransferase Derived from a Fragment Screening Approach Targeting the S-Adenosyl-l-methionine Pocket

Practical Three-Component Regioselective Synthesis of Drug-Like 3-Aryl(or heteroaryl)-5,6-dihydrobenzo[h]cinnolines as Potential Non-Covalent Multi-Targeting Inhibitors To Combat Neurodegenerative Diseases

Neurodegenerative diseases (NDs) are one of the prominent health challenges facing contemporary society, and many efforts have been made to overcome and (or) control it. In this research paper, we described a practical one-pot two-step three-component reaction between 3,4-dihydronaphthalen-1(2H)-one (1), aryl(or heteroaryl)glyoxal monohydrates (2a-h), and hydrazine monohydrate (NH2NH2•H2O) for the regioselective preparation of some 3-aryl(or heteroaryl)-5,6-dihydrobenzo[h]cinnoline derivatives (3a-h). After synthesis and characterization of the mentioned cinnolines (3a-h), the in silico multi-targeting inhibitory properties of these heterocyclic scaffolds have been investigated upon various Homo sapiens-type enzymes, including hMAO-A, hMAO-B, hAChE, hBChE, hBACE-1, hBACE-2, hNQO-1, hNQO-2, hnNOS, hiNOS, hPARP-1, hPARP-2, hLRRK-2(G2019S), hGSK-3β, hp38α MAPK, hJNK-3, hOGA, hNMDA receptor, hnSMase-2, hIDO-1, hCOMT, hLIMK-1, hLIMK-2, hRIPK-1, hUCH-L1, hPARK-7, and hDHODH, which have confirmed their functions and roles in the neurodegenerative diseases (NDs), based on molecular docking studies, and the obtained results were compared with a wide range of approved drugs and well-known (with IC50, EC50, etc.) compounds. In addition, in silico ADMET prediction analysis was performed to examine the prospective drug properties of the synthesized heterocyclic compounds (3a-h). The obtained results from the molecular docking studies and ADMET-related data demonstrated that these series of 3-aryl(or heteroaryl)-5,6-dihydrobenzo[h]cinnolines (3a-h), especially hit ones, can really be turned into the potent core of new drugs for the treatment of neurodegenerative diseases (NDs), and/or due to the having some reactionable locations, they are able to have further organic reactions (such as cross-coupling reactions), and expansion of these compounds (for example, with using other types of aryl(or heteroaryl)glyoxal monohydrates) makes a new avenue for designing novel and efficient drugs for this purpose.

Fragment-based drug discovery for disorders of the central nervous system: designing better drugs piece by piece

Fragment-based drug discovery (FBDD) has emerged as a powerful strategy to confront the challenges faced by conventional drug development approaches, particularly in the context of central nervous system (CNS) disorders. FBDD involves the screening of libraries that comprise thousands of small molecular fragments, each no greater than 300 Da in size. Unlike the generally larger molecules from high-throughput screening that limit customisation, fragments offer a more strategic starting point. These fragments are inherently compact, providing a strong foundation with good binding affinity for the development of drug candidates. The minimal elaboration required to transition the hit into a drug-like molecule is not only accelerated, but also it allows for precise modifications to enhance both their activity and pharmacokinetic properties. This shift towards a fragment-centric approach has seen commercial success and holds considerable promise in the continued streamlining of the drug discovery and development process. In this review, we highlight how FBDD can be integrated into the CNS drug discovery process to enhance the exploration of a target. Furthermore, we provide recent examples where FBDD has been an integral component in CNS drug discovery programs, enabling the improvement of pharmacokinetic properties that have previously proven challenging. The FBDD optimisation process provides a systematic approach to explore this vast chemical space, facilitating the discovery and design of compounds piece by piece that are capable of modulating crucial CNS targets.

BioisoIdentifier: an online free tool to investigate local structural replacements from PDB

Within the realm of contemporary medicinal chemistry, bioisosteres are empirically used to enhance potency and selectivity, improve adsorption, distribution, metabolism, excretion and toxicity profiles of drug candidates. It is believed that bioisosteric know-how may help bypass granted patents or generate novel intellectual property for commercialization. Beside the synthetic expertise, the drug discovery process also depends on efficient in silico tools. We hereby present BioisoIdentifier (BII), a web server aiming to uncover bioisosteric information for specific fragment. Using the Protein Data Bank as source, and specific substructures that the user attempt to surrogate as input, BII tries to find suitable fragments that fit well within the local protein active site. BII is a powerful computational tool that offers the ligand design ideas for bioisosteric replacing. For the validation of BII, catechol is conceived as model fragment attempted to be replaced, and many ideas are successfully offered. These outputs are hierarchically grouped according to structural similarity, and clustered based on unsupervised machine learning algorithms. In summary, we constructed a user-friendly interface to enable the viewing of top-ranking molecules for further experimental exploration. This makes BII a highly valuable tool for drug discovery. The BII web server is freely available to researchers and can be accessed at http://www.aifordrugs.cn/index/ . Scientific Contribution: By designing a more optimal computational process for mining bioisosteric replacements from the publicly accessible PDB database, then deployed on a web server for throughly free access for researchers. Additionally, machine learning methods are applied to cluster the bioisosteric replacements searched by the platform, making a scientific contribution to facilitate chemists' selection of appropriate bioisosteric replacements. The number of bioisosteric replacements obtained using BII is significantly larger than the currently available platforms, which expanding the search space for effective local structural replacements.

Structural and Computational Analyses of the Unique Interactions of Opicapone in the Binding Pocket of Catechol O-Methyltransferase: A Crystallographic Study and Fragment Molecular Orbital Analyses

A third-generation inhibitor of catechol O-methyltransferase (COMT), opicapone (1), has the 3-nitrocatechol scaffold as do the second-generation inhibitors such as entacapone (2) and tolcapone (3), but only 1 can sustainably inhibit COMT activity making it suitable for a once-daily regimen. These improvements should be attributed to the optimized sidechain moiety (oxidopyridyloxadiazolyl group) of 1 substituted at the 5-position of the 3-nitrocatechol ring. We analyzed the role of the sidechain moiety by solving the crystal structures of COMT/S-adenosylmethionine (SAM)/Mg/1 and COMT/S-adenosylhomocysteine (SAH)/Mg/1 complexes. Fragment molecular orbital (FMO) calculations elucidated that the dispersion interaction between the sidechains of Leu 198 and Met 201 on the β6β7-loop and the oxidopyridine ring of 1 were unique and important in both complexes. In contrast, the catechol binding site made a remarkable difference in the sidechain conformation of Lys 144. The ε-amino group of Lys 144 was outside of the catalytic pocket and was replaced by a water molecule in the COMT/SAH/Mg/1 complex. No nitrocatechol inhibitor has ever been reported to make a complex with COMT and SAH. Thus, the conformational change of Lys 144 found in the COMT/SAH/Mg/1 complex is the first crystallographic evidence that supports the role of Lys 144 as a catalytic base to take out a proton ion from the reaction site to the outside of the enzyme. The fact that 1 generated a complex with SAH and COMT also suggests that 1 could inhibit COMT twofold, as a typical substrate mimic competitive inhibitor and as a product-inhibition enhancer.

Designer installation of a substrate recruitment domain to tailor enzyme specificity

Promiscuous enzymes that modify peptides and proteins are powerful tools for labeling biomolecules; however, directing these modifications to desired substrates can be challenging. Here, we use computational interface design to install a substrate recognition domain adjacent to the active site of a promiscuous enzyme, catechol O-methyltransferase. This design approach effectively decouples substrate recognition from the site of catalysis and promotes modification of peptides recognized by the recruitment domain. We determined the crystal structure of this novel multidomain enzyme, SH3-588, which shows that it closely matches our design. SH3-588 methylates directed peptides with catalytic efficiencies exceeding the wild-type enzyme by over 1,000-fold, whereas peptides lacking the directing recognition sequence do not display enhanced efficiencies. In competition experiments, the designer enzyme preferentially modifies directed substrates over undirected substrates, suggesting that we can use designed recruitment domains to direct post-translational modifications to specific sequence motifs on target proteins in complex multisubstrate environments.

Boosting caffeic acid performance as antioxidant and monoamine oxidase B/catechol-O-methyltransferase inhibitor

Increased oxidative stress (OS) and depletion of nigrostriatal dopamine (DA) are closely linked to the neurodegeneration observed in Parkinson's Disease (PD). Caffeic acid (CA)-based antioxidants were developed, and their inhibitory activities towards monoamine oxidases (MAOs) and catechol O-methyltransferases (COMT) were screened. The results showed that the incorporation of an extra double bond maintained or even boosted the antioxidant properties of CA. α-CN derivatives displayed redox potentials (E_p) similar to CA (1) and inhibited hMAO-B with low μM IC₅₀ values. Moreover, catechol amides acted as MB-COMT inhibitors, showing IC₅₀ values within the low μM range. In general, CA derivatives presented safe cytotoxicity profiles at concentrations up to 10 μM. The formation of reactive oxygen species (ROS) induced by CA derivatives may be underlying the cytotoxic effects observed at higher concentrations. Catechol amides 3-6, 8-11 at 10 μM protected cells against oxidative damage. Compounds 3 and 8 were predicted to cross the blood-brain barrier (BBB) by passive diffusion. In summary, we report for the first time BBB-permeant CA-based multitarget lead compounds that may restore DAergic neurotransmission (dual hMAO-B/MB-COMT inhibition) and prevent oxidative damage. The data represents a groundbreaking advancement towards the discovery of the next generation of new drugs for PD.

Methyltransferases, functions and applications

In this review the current state‐of‐the‐art of S‐adenosylmethionine (SAM)‐dependent methyltransferases and SAM are evaluated. Their structural classification and diversity is introduced and key mechanistic aspects presented which are then detailed further. Then, catalytic SAM as a target for drugs, and approaches to utilise SAM as a cofactor in synthesis are introduced with different supply and regeneration approaches evaluated. The use of SAM analogues are also described. Finally O‐, N‐, C‐ and S‐MTs, their synthetic applications and potential for compound diversification is given.

Cosolvent Simulations with Fragment-Bound Proteins Identify Hot Spots to Direct Lead Growth

In drug design, chemical groups are sequentially added to improve a weak-binding fragment into a tight-binding lead molecule. Often, the direction to make these additions is unclear, and there are numerous chemical modifications to choose. Lead development can be guided by crystal structures of the fragment-bound protein, but this alone is unable to capture structural changes like closing or opening of the binding site and any side-chain movements. Accounting for adaptation of the site requires a dynamic approach. Here, we use molecular dynamics calculations of small organic solvents with protein-fragment pairs to reveal the nearest "hot spots". These close hot spots show the direction to make appropriate additions and suggest types of chemical modifications that could improve binding affinity. Mixed-solvent molecular dynamics (MixMD) is a cosolvent simulation technique that is well established for finding binding "hot spots" in active sites and allosteric sites of proteins. We simulated 20 fragment-bound and apo forms of key pharmaceutical targets to map out hot spots for potential lead space. Furthermore, we analyzed whether the presence of a fragment facilitates the probes' binding in the lead space, a type of binding cooperativity. To the best of our knowledge, this is the first use of cosolvent MD conducted with bound inhibitors in the simulation. Our work provides a general framework to extract molecular features of binding sites to choose chemical groups for growing lead molecules. Of the 20 systems, 17 systems were well mapped by MixMD. For the three not-mapped systems, two had lead growth out into solution away from the protein, and the third had very small modifications which indicated no nearby hot spots. Therefore, our lack of mapping in three systems was appropriate given the experimental data (true-negative cases). The simulations are run for very short time scales, making this method tractable for use in the pharmaceutical industry.

Inhibition of catechol-O-methyltransferase by natural pentacyclic triterpenes: structure-activity relationships and kinetic mechanism

Inhibitors of COMT are clinically used for the treatment of Parkinson's disease. Here, we report the first natural pentacyclic triterpenoid-type COMT inhibitors and their structure-activity relationships and inhibition mechanism. The most potent compounds were found to be oleanic acid, betulinic acid and celastrol with IC₅₀ values of 3.89-5.07 μM, that acted as mixed (uncompetitive plus non-competitive) inhibitors of COMT, representing a new skeleton of COMT inhibitor. Molecular docking suggested that they can specifically recognise and bind with the unique hydrophobic residues surrounding the catechol pocket. Furthermore, oleanic acid and betulinic acid proved to be less disruptive of mitochondrial membrane potential (MMP) compared to tolcapone, thus reducing the risk of liver toxicity. These findings could be used to produce an ideal lead compound and to guide synthetic efforts in generating related derivatives for further preclinical testing.

Recent Developments in New Therapeutic Agents against Alzheimer and Parkinson Diseases: In-Silico Approaches

Neurodegenerative diseases (ND), including Alzheimer's (AD) and Parkinson's Disease (PD), are becoming increasingly more common and are recognized as a social problem in modern societies. These disorders are characterized by a progressive neurodegeneration and are considered one of the main causes of disability and mortality worldwide. Currently, there is no existing cure for AD nor PD and the clinically used drugs aim only at symptomatic relief, and are not capable of stopping neurodegeneration. Over the last years, several drug candidates reached clinical trials phases, but they were suspended, mainly because of the unsatisfactory pharmacological benefits. Recently, the number of compounds developed using in silico approaches has been increasing at a promising rate, mainly evaluating the affinity for several macromolecular targets and applying filters to exclude compounds with potentially unfavorable pharmacokinetics. Thus, in this review, an overview of the current therapeutics in use for these two ND, the main targets in drug development, and the primary studies published in the last five years that used in silico approaches to design novel drug candidates for AD and PD treatment will be presented. In addition, future perspectives for the treatment of these ND will also be briefly discussed.

Analytical methodologies for sensing catechol-O-methyltransferase activity and their applications

Mammalian catechol-O-methyltransferases (COMT) are an important class of conjugative enzymes, which play a key role in the metabolism and inactivation of catechol neurotransmitters, catechol estrogens and a wide range of endobiotics and xenobiotics that bear the catechol group. Currently, COMT inhibitors are used in combination with levodopa for the treatment of Parkinson's disease in clinical practice. The crucial role of COMT in human health has raised great interest in the development of more practical assays for highly selective and sensitive detection of COMT activity in real samples, as well as for rapid screening and characterization of COMT inhibitors as drug candidates. This review summarizes recent advances in analytical methodologies for sensing COMT activity and their applications. Several lists of biochemical assays for measuring COMT activity, including the probe substrates, along with their analytical conditions and kinetic parameters, are presented. Finally, the challenges and future perspectives in the field, such as visualization of COMT activity in vivo and in situ, are highlighted. Collectively, this review article overviews the practical assays for measuring COMT activities in complex biological samples, which will strongly facilitate the investigations on the relevance of COMT to human diseases and promote the discovery of COMT inhibitors via high-throughput screening.

Prospecting for new catechol-O-methyltransferase (COMT) inhibitors as a potential treatment for Parkinson's disease: a study by molecular dynamics and structure-based virtual screening

Parkinson's disease (PD) is a neurodegenerative, chronic, and progressive disease, common in the elderly. The catechol-O-methyltransferase (COMT) is a monomeric enzyme involved in dopamine (DA) degradation, the neurotransmitter in deficit in patients with PD. The reference treatment of PD consists of levodopa (L-dopa) administration, which is the precursor of DA. The inhibition of COMT is an adjuvant treatment in PD since it keeps DA levels constant. The goal of this study was to identify drug candidates capable of inhibiting COMT for the treatment of PD and identify important fragments of these molecules. Initially, we analyzed the flexibility of COMT and defined its main conformations in solution regarding the absence (system I) and presence of the S-adenosyl-L-methionine (SAM) cofactor (system II) through molecular dynamics (MD) simulations. Two regions in these structures were selected for molecular docking, firstly the entire cavity where the cofactor and substrates are bound and secondly the specific biding region of the enzyme substrates. Based on the conformations of the MD, the virtual screening (VS) was performed against FDA Approved and Zinc Natural Products databases aiming at the selection of the best compounds. Subsequently, the absorption, distribution, metabolization, excretion, and toxicity (ADMET) properties, as well as drug-score and drug-likeness indexes of the most promising compounds were analyzed. After a detailed analysis of the compounds selected by structure-based VS, it was possible to highlight the fragments most frequently involved in their stability: 2,3,4,9-tetrahydro-1H-pyrido[3,4-b]indole, 9H-Benz(c)indole(3,2,1-ij)(1,5)naphthyridin-9-one and (10R,13S)-10,13-dimethyl-1,2,6,7,8,9,11,12,14,15,16,17dodecahydrocyclopenta[a]phenanthren-3-one. The identification of these potential fragments is essential for the prospection of more specific inhibitors against COMT using the technique of Fragment-based lead discovery (FBLD). Besides, this study allowed us to identify the potential COMT inhibitors through a complete understanding of molecular-level interactions based on the flexibility of this protein.Communicated by Ramaswamy H. Sarma.

Coupling S-adenosylmethionine-dependent methylation to growth: Design and uses

We present a selection design that couples S-adenosylmethionine–dependent methylation to growth. We demonstrate its use in improving the enzyme activities of not only N-type and O-type methyltransferases by 2-fold but also an acetyltransferase of another enzyme category when linked to a methylation pathway in Escherichia coli using adaptive laboratory evolution. We also demonstrate its application for drug discovery using a catechol O-methyltransferase and its inhibitors entacapone and tolcapone. Implementation of this design in Saccharomyces cerevisiae is also demonstrated.

Many important biological processes require methylation, e.g., DNA methylation and synthesis of flavoring compounds, neurotransmitters, and antibiotics. Most methylation reactions in cells are catalyzed by S-adenosylmethionine (SAM)–dependent methyltransferases (Mtases) using SAM as a methyl donor. Thus, SAM-dependent Mtases have become an important enzyme category of biotechnological interests and as healthcare targets. However, functional implementation and engineering of SAM-dependent Mtases remains difficult and is neither cost effective nor high throughput. Here, we are able to address these challenges by establishing a synthetic biology approach, which links Mtase activity to cell growth such that higher Mtase activity ultimately leads to faster cell growth. We show that better-performing variants of the examined Mtases can be readily obtained by growth selection after repetitive cell passages. We also demonstrate the usefulness of our approach for discovery of Mtase-specific drug candidates. We further show our approach is not only applicable in bacteria, exemplified by Escherichia coli, but also in eurkaryotic organisms such as budding yeast Saccharomyces cerevisiae.

Fragment-to-Lead Medicinal Chemistry Publications in 2016

The popularity of fragment-based drug discovery (FBDD) is demonstrated by the number of recent successful fragment-to-lead (F2L) publications. This Miniperspective provides a tabulated summary of the F2L literature published in the year 2016, along with discussion of general trends. It uses the same format as our summary of the 2015 literature and is intended to be a resource for both FBDD practitioners and medicinal chemists in general.

Translating advances in the molecular basis of schizophrenia into novel cognitive treatment strategies

The presence and severity of cognitive symptoms, including working memory, executive dysfunction and attentional impairment, contributes materially to functional impairment in schizophrenia. Cognitive symptoms have proved to be resistant to both first- and second-generation antipsychotic drugs. Efforts to develop a consensus set of cognitive domains that are both disrupted in schizophrenia and are amenable to cross-species validation (e.g. the National Institute of Mental Health Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia and Research Domain Criteria initiatives) are an important step towards standardization of outcome measures that can be used in preclinical testing of new drugs. While causative genetic mutations have not been identified, new technologies have identified novel genes as well as hitherto candidate genes previously implicated in the pathophysiology of schizophrenia and/or mechanisms of antipsychotic efficacy. This review comprises a selective summary of these developments, particularly phenotypic data arising from preclinical genetic models for cognitive dysfunction in schizophrenia, with the aim of indicating potential new directions for pro-cognitive therapeutics. Linked Articles This article is part of a themed section on Pharmacology of Cognition: a Panacea for Neuropsychiatric Disease? To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v174.19/issuetoc.