Synthesis of sp2-Iminosugar Selenoglycolipids as Multitarget Drug Candidates with Antiproliferative, Leishmanicidal and Anti-Inflammatory Properties

sp2-Iminosugar glycolipids (sp2-IGLs) represent a consolidated family of glycoconjugate mimetics encompassing a monosaccharide-like glycone moiety with a pseudoamide-type nitrogen replacing the endocyclic oxygen atom of carbohydrates and an axially-oriented lipid chain anchored at the pseudoanomeric position. The combination of these structural features makes them promising candidates for the treatment of a variety of conditions, spanning from cancer and inflammatory disorders to parasite infections. The exacerbated anomeric effect associated to the putative sp2-hybridized N-atom imparts chemical and enzymatic stability to sp2-IGLs and warrants total α-anomeric stereoselectivity in the key glycoconjugation step. A variety of O-, N-, C- and S-pseudoglycosides, differing in glycone configurational patterns and lipid nature, have been previously prepared and evaluated. Here we expand the chemical space of sp2-IGLs by reporting the synthesis of α-d-gluco-configured analogs with a bicyclic (5N,6O-oxomethylidene)nojirimycin (ONJ) core incorporating selenium at the glycosidic position. Structure–activity relationship studies in three different scenarios, namely cancer, Leishmaniasis and inflammation, convey that the therapeutic potential of the sp2-IGLs is highly dependent, not only on the length of the lipid chain (linear aliphatic C12 vs. C8), but also on the nature of the glycosidic atom (nitrogen vs. sulfur vs. selenium). The ensemble of results highlights the α-dodecylseleno-ONJ-glycoside as a promising multitarget drug candidate.

Download Full-text

Identification of Potent VHZ Phosphatase Inhibitors with Structure-Based Virtual Screening

CrossRef Listing of Deleted DOIs ◽

10.1177/1087057112463067 ◽

2012 ◽

Vol 18 (2) ◽

pp. 226-231 ◽

Cited By ~ 6

Author(s):

Hwangseo Park ◽

So Ya Park ◽

Jung Jin Oh ◽

Seong Eon Ryu

Keyword(s):

Virtual Screening ◽

Active Site ◽

Structural Features ◽

Drug Candidate ◽

The Novel ◽

Anticancer Activities ◽

Phosphatase Inhibitors ◽

Structure Activity ◽

Promising Target ◽

Further Development

VH1-like phosphatase Z (VHZ) has proved to be a promising target for the development of therapeutics for the treatment of human cancers. Here, we report the first example for a successful application of structure-based virtual screening to identify the novel small-molecule inhibitors of VHZ. These inhibitors revealed high potencies with the associated IC50 values ranging from 3 to 20 µM and were also screened for having desirable physicochemical properties as a drug candidate. Therefore, they deserve consideration for further development by structure-activity relationship studies to optimize inhibitory and anticancer activities. Structural features relevant to the stabilization of the newly identified inhibitors in the active site of VHZ are discussed in detail.

Download Full-text

Chemical Patterns of Proteasome Inhibitors: Lessons Learned from Two Decades of Drug Design

International Journal of Molecular Sciences ◽

10.3390/ijms20215326 ◽

2019 ◽

Vol 20 (21) ◽

pp. 5326 ◽

Cited By ~ 3

Author(s):

Guedes ◽

Aniceto ◽

Andrade ◽

Salvador ◽

Guedes

Keyword(s):

Drug Discovery ◽

Chemical Space ◽

Decision Rules ◽

Proteasome Inhibitors ◽

Proteasome Inhibition ◽

Lessons Learned ◽

Drug Candidates ◽

Making Sense ◽

Structure Activity ◽

Future Drug

Drug discovery now faces a new challenge, where the availability of experimental data is no longer the limiting step, and instead, making sense of the data has gained a new level of importance, propelled by the extensive incorporation of cheminformatics and bioinformatics methodologies into the drug discovery and development pipeline. These enable, for example, the inference of structure-activity relationships that can be useful in the discovery of new drug candidates. One of the therapeutic applications that could benefit from this type of data mining is proteasome inhibition, given that multiple compounds have been designed and tested for the last 20 years, and this collection of data is yet to be subjected to such type of assessment. This study presents a retrospective overview of two decades of proteasome inhibitors development (680 compounds), in order to gather what could be learned from them and apply this knowledge to any future drug discovery on this subject. Our analysis focused on how different chemical descriptors coupled with statistical tools can be used to extract interesting patterns of activity. Multiple instances of the structure-activity relationship were observed in this dataset, either for isolated molecular descriptors (e.g., molecular refractivity and topological polar surface area) as well as scaffold similarity or chemical space overlap. Building a decision tree allowed the identification of two meaningful decision rules that describe the chemical parameters associated with high activity. Additionally, a characterization of the prevalence of key functional groups gives insight into global patterns followed in drug discovery projects, and highlights some systematically underexplored parts of the chemical space. The various chemical patterns identified provided useful insight that can be applied in future drug discovery projects, and give an overview of what has been done so far.

Download Full-text

Chemi-Informatic approach to investigate putative pharmacoactive agents of plant origin to eradicate COVID-19

Coronaviruses ◽

10.2174/2666796701999201203210036 ◽

2020 ◽

Vol 01 ◽

Author(s):

Amit Joshi ◽

Vandna Sharma ◽

Joginder Singh ◽

Vikas Kaushik

Keyword(s):

Rna Binding ◽

Simulation Analysis ◽

Therapeutic Potential ◽

Binding Energies ◽

Drug Candidate ◽

Local Alignment ◽

Viral Agent ◽

Drug Candidates ◽

Hydrogen Bond Interactions ◽

Feasible Range

Background:: The scientific community has supported from the medicinal flora of ancient as well as modern times in extracting chemicals, which holds therapeutic potential. In many previous studies, it was discovered Amentoflavone as an anti-viral agent and its presence as a bioactive constituent in many plants of different families Selaginellaceae, Euphorbiaceae, and Calophyllaceae etc. Withania somnifera (Ashwagandha) is already considered significant anti-viral agent in traditional medicine, and it is the main source of Somniferine-A, Withanolide-B. Objective:: In this study phytochemicals such as Withanolide-B, Somniferine-A, Stigmasterol, Amentoflavone, and Chavicine were analyzed to screen protein inhibitors out of them; such proteins are involved in SARS-Cov-2's internalization and interaction with human cytological domains. This will help in developing check point for SARS-Cov-2 internalization. Material and methods:: Chemi-informatic tools like basic local alignment search tool (BLAST), AutoDock-vina, SwissADME, MDWeb, Molsoft, ProTox-II, and LigPlot were deployed to examine the action of pharmacoactive agents against SARS-Cov-2. The many tools deployed in the study were based on finest algorithms like Artificial neural networking, Machine Learning, and Artificial intelligence. Results:: On the basis of binding energies less than equal to -8.5 kcal/mol. Amentoflavone, Stigmasterol, and Somniferine-A were found to be most effective against COVID-19 disease as these chemical agents exhibit hydrogen bond interactions and competitively inhibit major proteins (SARS-Cov-2 Spike, Human ACE-2 receptor, Human Furin protease, SARS-Cov-2 RNA binding protein) that are found to involved in its infection and pathogenesis. Simulation analysis provides more validity to the selection of drug candidate Amentoflavone. ADMET properties were found to be in feasible range for putative drug candidates. Conclusion:: Computational analysis was successfully deployed in searching pharmacoactive phytochemicals Like Amentoflavone, Somniferine-A, and Stigmasterol that can bring control over COVID-19 expansion. This new methodology was found to be efficient, as reduces monetary expenditures and time consumption, aftermath molecular wet-lab validations will provide better approval for finalizing our selected drug model for controlling COVID-19 pandemic.

Download Full-text

Coumarin sulfonamide derivatives: An emerging class of therapeutic agents

Heterocyclic Communications ◽

10.1515/hc-2020-0008 ◽

2020 ◽

Vol 26 (1) ◽

pp. 46-59 ◽

Cited By ~ 1

Author(s):

Ali Irfan ◽

Laila Rubab ◽

Mishbah Ur Rehman ◽

Rukhsana Anjum ◽

Sami Ullah ◽

...

Keyword(s):

Therapeutic Potential ◽

Biological Activities ◽

Wide Spectrum ◽

Structural Features ◽

Therapeutic Agents ◽

Review Article ◽

Structural Motif ◽

Structure Activity ◽

Anti Cancer ◽

Novel Therapeutic

AbstractCoumarin sulfonamide is a heterocyclic pharmacophore and an important structural motif which is a core and integral part of different therapeutic scaffolds and analogues. Coumarin sulfonamides are privileged and pivotal templates which have a broad spectrum of applications in the fields of medicine, pharmacology and pharmaceutics. Coumarin sulfonamide exhibited versatile and myriad biomedical activities such as anti-bacterial, antiviral, antifungal, anti-inflammatory and anti-cancer. This review article focuses on the structural features of coumarin sulfonamide derivatives in the treatment of different lethal diseases on the basis of structure-activity relationships (SAR). The plethora of research cited in this review article summarizes and discusses the various substitutions around the coumarin sulfonamide nucleus which have provided a wide spectrum of biological activities and therapeutic potential that has proved attractive to many researchers looking to exploit the coumarin sulfonamide skeleton for drug discovery and the development of novel therapeutic agents.

Download Full-text

The antimitotic Podophyllotoxin and its derivatives- recent synthetic advances

Current Nutraceuticals ◽

10.2174/2665978602666211102103152 ◽

2021 ◽

Vol 02 ◽

Author(s):

Sharon Riaz ◽

Khalid Mohammed Khan ◽

Ghayoor Abbas Chotana ◽

Amir Faisal ◽

Rahman Shah Zaib Saleem

Keyword(s):

Total Synthesis ◽

Chemical Space ◽

Structural Features ◽

Biological Evaluation ◽

One Pot ◽

Antimitotic Activity ◽

Structure Activity ◽

Synthetic Approaches ◽

Podophyllotoxin Derivatives ◽

Synthesis And Biological Evaluation

: The substantial antimitotic potential of podophyllotoxin and its derivatives has attracted both synthetic and medicinal chemists to expand the chemical space for the subsequent biological evaluation of these compounds. The interest ranges from total synthesis, hemi-synthesis, one-pot synthetic approaches and structure-activity relationship studies. In the first segment of the review, we present recent development in the synthesis of podophyllotoxin and also describe its mode of action. The second section covers the synthesis and the structure-activity relationships of podophyllotoxin derivatives, along with the discussion of important structural features required by the molecule for displaying antimitotic activity. The last part describes the synthesis and biological evaluation of potent 4-aza podophyllotoxin derivatives. This review is of interest to chemists who study natural and synthetic compounds for drug discovery.

Download Full-text

HAZARD: An Expert System for Risk Assessment of Environmental Chemicals

Methods of Information in Medicine ◽

10.1055/s-0038-1635482 ◽

1987 ◽

Vol 26 (01) ◽

pp. 13-23 ◽

Cited By ~ 2

Author(s):

H. W. Gottinger

Keyword(s):

Expert System ◽

Structural Information ◽

Chemical Carcinogenesis ◽

Structural Features ◽

Environmental Chemicals ◽

Chemical Carcinogens ◽

Carcinogenic Activity ◽

Current State ◽

Structure Activity ◽

Carcinogenic Potential

AbstractThe purpose of this paper is to report on an expert system in design that screens for potential hazards from environmental chemicals on the basis of structure-activity relationships in the study of chemical carcinogenesis, particularly with respect to analyzing the current state of known structural information about chemical carcinogens and predicting the possible carcinogenicity of untested chemicals. The structure-activity tree serves as an index of known chemical structure features associated with carcinogenic activity. The basic units of the tree are the principal recognized classes of chemical carcinogens that are subdivided into subclasses known as nodes according to specific structural features that may reflect differences in carcinogenic potential among chemicals in the class. An analysis of a computerized data base of known carcinogens (knowledge base) is proposed using the structure-activity tree in order to test the validity of the tree as a classification scheme (inference engine).

Download Full-text

Applications of Quantitative Structure-Activity Relationships (QSAR) based Virtual Screening in Drug Design: A Review

Mini-Reviews in Medicinal Chemistry ◽

10.2174/1389557520666200429102334 ◽

2020 ◽

Vol 20 (14) ◽

pp. 1375-1388 ◽

Cited By ~ 2

Author(s):

Patnala Ganga Raju Achary

Keyword(s):

Machine Learning ◽

Drug Discovery ◽

Virtual Screening ◽

Model Building ◽

Chemical Space ◽

Qsar Model ◽

Quantitative Structure ◽

Efficient Manner ◽

Qsar Analysis ◽

Structure Activity

The scientists, and the researchers around the globe generate tremendous amount of information everyday; for instance, so far more than 74 million molecules are registered in Chemical Abstract Services. According to a recent study, at present we have around 1060 molecules, which are classified as new drug-like molecules. The library of such molecules is now considered as ‘dark chemical space’ or ‘dark chemistry.’ Now, in order to explore such hidden molecules scientifically, a good number of live and updated databases (protein, cell, tissues, structure, drugs, etc.) are available today. The synchronization of the three different sciences: ‘genomics’, proteomics and ‘in-silico simulation’ will revolutionize the process of drug discovery. The screening of a sizable number of drugs like molecules is a challenge and it must be treated in an efficient manner. Virtual screening (VS) is an important computational tool in the drug discovery process; however, experimental verification of the drugs also equally important for the drug development process. The quantitative structure-activity relationship (QSAR) analysis is one of the machine learning technique, which is extensively used in VS techniques. QSAR is well-known for its high and fast throughput screening with a satisfactory hit rate. The QSAR model building involves (i) chemo-genomics data collection from a database or literature (ii) Calculation of right descriptors from molecular representation (iii) establishing a relationship (model) between biological activity and the selected descriptors (iv) application of QSAR model to predict the biological property for the molecules. All the hits obtained by the VS technique needs to be experimentally verified. The present mini-review highlights: the web-based machine learning tools, the role of QSAR in VS techniques, successful applications of QSAR based VS leading to the drug discovery and advantages and challenges of QSAR.

Download Full-text

A novel orally active HDAC6 inhibitor T-518 shows a therapeutic potential for Alzheimer’s disease and tauopathy in mice

Scientific Reports ◽

10.1038/s41598-021-94923-w ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Tomohiro Onishi ◽

Ryouta Maeda ◽

Michiko Terada ◽

Sho Sato ◽

Takahiro Fujii ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Therapeutic Potential ◽

Drug Candidate ◽

Histone Deacetylase 6 ◽

Cellular Assays ◽

Age Related ◽

Acetylation State ◽

Hdac6 Inhibitor ◽

Orally Active

AbstractAccumulation of tau protein is a key pathology of age-related neurodegenerative diseases such as Alzheimer's disease and progressive supranuclear palsy. Those diseases are collectively termed tauopathies. Tau pathology is associated with axonal degeneration because tau binds to microtubules (MTs), a component of axon and regulates their stability. The acetylation state of MTs contributes to stability and histone deacetylase 6 (HDAC6) is a major regulator of MT acetylation status, suggesting that pharmacological HDAC6 inhibition could improve axonal function and may slow the progression of tauopathy. Here we characterize N-[(1R,2R)-2-{3-[5-(difluoromethyl)-1,3,4-oxadiazol-2-yl]-5-oxo-5H,6H,7H-pyrrolo[3,4-b]pyridin-6-yl}cyclohexyl]-2,2,3,3,3-pentafluoropropanamide (T-518), a novel, potent, highly selective HDAC6 inhibitor with clinically favorable pharmacodynamics. T-518 shows potent inhibitory activity against HDAC6 and superior selectivity over other HDACs compared with the known HDAC6 inhibitors in the enzyme and cellular assays. T-518 showed brain penetration in an oral dose and blocked HDAC6-dependent tubulin deacetylation at Lys40 in mouse hippocampus. A 2-week treatment restored impaired axonal transport and novel object recognition in the P301S tau Tg mouse, tauopathy model, while a 3-month treatment also decreased RIPA-insoluble tau accumulation. Pharmaceutical inhibition of HDAC6 is a potential therapeutic strategy for tauopathy, and T-518 is a particularly promising drug candidate.

Download Full-text

Flavonoids from the Genus Euphorbia: Isolation, Structure, Pharmacological Activities and Structure–Activity Relationships

Pharmaceuticals ◽

10.3390/ph14050428 ◽

2021 ◽

Vol 14 (5) ◽

pp. 428

Author(s):

Douglas Kemboi Magozwi ◽

Mmabatho Dinala ◽

Nthabiseng Mokwana ◽

Xavier Siwe-Noundou ◽

Rui W. M. Krause ◽

...

Keyword(s):

Therapeutic Potential ◽

Antioxidant Properties ◽

Structure Activity Relationship ◽

Biological Properties ◽

Therapeutic Agents ◽

Skeletal Structure ◽

Activity Relationship ◽

Hydroxyl Groups ◽

Structure Activity ◽

Review Reports

Plants of the genus Euphorbia are widely distributed across temperate, tropical and subtropical regions of South America, Asia and Africa with established Ayurvedic, Chinese and Malay ethnomedical records. The present review reports the isolation, occurrence, phytochemistry, biological properties, therapeutic potential and structure–activity relationship of Euphorbia flavonoids for the period covering 2000–2020, while identifying potential areas for future studies aimed at development of new therapeutic agents from these plants. The findings suggest that the extracts and isolated flavonoids possess anticancer, antiproliferative, antimalarial, antibacterial, anti-venom, anti-inflammatory, anti-hepatitis and antioxidant properties and have different mechanisms of action against cancer cells. Of the investigated species, over 80 different types of flavonoids have been isolated to date. Most of the isolated flavonoids were flavonols and comprised simple O-substitution patterns, C-methylation and prenylation. Others had a glycoside, glycosidic linkages and a carbohydrate attached at either C-3 or C-7, and were designated as d-glucose, l-rhamnose or glucorhamnose. The structure–activity relationship studies showed that methylation of the hydroxyl groups on C-3 or C-7 reduces the activities while glycosylation loses the activity and that the parent skeletal structure is essential in retaining the activity. These constituents can therefore offer potential alternative scaffolds towards development of new Euphorbia-based therapeutic agents.

Download Full-text

Small and Simple, yet Sturdy: Conformationally Constrained Peptides with Remarkable Properties

International Journal of Molecular Sciences ◽

10.3390/ijms22041611 ◽

2021 ◽

Vol 22 (4) ◽

pp. 1611

Author(s):

Krištof Bozovičar ◽

Tomaž Bratkovič

Keyword(s):

Chemical Space ◽

Structure Optimization ◽

Peptide Chain ◽

Conformationally Constrained ◽

Drug Candidates ◽

Conformational Constraints ◽

Macrocyclic Peptides ◽

Constrained Peptides ◽

Sheer Size

The sheer size and vast chemical space (i.e., diverse repertoire and spatial distribution of functional groups) underlie peptides’ ability to engage in specific interactions with targets of various structures. However, the inherent flexibility of the peptide chain negatively affects binding affinity and metabolic stability, thereby severely limiting the use of peptides as medicines. Imposing conformational constraints to the peptide chain offers to solve these problems but typically requires laborious structure optimization. Alternatively, libraries of constrained peptides with randomized modules can be screened for specific functions. Here, we present the properties of conformationally constrained peptides and review rigidification chemistries/strategies, as well as synthetic and enzymatic methods of producing macrocyclic peptides. Furthermore, we discuss the in vitro molecular evolution methods for the development of constrained peptides with pre-defined functions. Finally, we briefly present applications of selected constrained peptides to illustrate their exceptional properties as drug candidates, molecular recognition probes, and minimalist catalysts.

Download Full-text