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

2019 ◽  
Vol 20 (21) ◽  
pp. 5326 ◽  
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.

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

2020 ◽  
Vol 20 (14) ◽  
pp. 1375-1388 ◽  
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.

scholarly journals Natural Products as Modulators of Sirtuins

Molecules ◽  
2020 ◽  
Vol 25 (14) ◽  
pp. 3287 ◽  
Author(s):  
Berin Karaman Mayack ◽  
Wolfgang Sippl ◽  
Fidele Ntie-Kang
Keyword(s):  
Natural Products ◽  
Drug Discovery ◽  
Histone Deacetylases ◽  
High Throughput Screening ◽  
Chemical Space ◽  
Class Iii ◽  
Drug Candidates ◽  
Starting Point ◽  
Recent Developments ◽  
Potent Drug

Natural products have been used for the treatment of human diseases since ancient history. Over time, due to the lack of precise tools and techniques for the separation, purification, and structural elucidation of active constituents in natural resources there has been a decline in financial support and efforts in characterization of natural products. Advances in the design of chemical compounds and the understanding of their functions is of pharmacological importance for the biomedical field. However, natural products regained attention as sources of novel drug candidates upon recent developments and progress in technology. Natural compounds were shown to bear an inherent ability to bind to biomacromolecules and cover an unparalleled chemical space in comparison to most libraries used for high-throughput screening. Thus, natural products hold a great potential for the drug discovery of new scaffolds for therapeutic targets such as sirtuins. Sirtuins are Class III histone deacetylases that have been linked to many diseases such as Parkinson`s disease, Alzheimer’s disease, type II diabetes, and cancer linked to aging. In this review, we examine the revitalization of interest in natural products for drug discovery and discuss natural product modulators of sirtuins that could serve as a starting point for the development of isoform selective and highly potent drug-like compounds, as well as the potential application of naturally occurring sirtuin inhibitors in human health and those in clinical trials.

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

Molecules ◽  
2021 ◽  
Vol 26 (24) ◽  
pp. 7501
Author(s):  
Elena M. Sánchez-Fernández ◽  
Raquel García-Hernández ◽  
Francisco Gamarro ◽  
Ana I. Arroba ◽  
Manuel Aguilar-Diosdado ◽  
...  
Keyword(s):  
Oxygen Atom ◽  
Therapeutic Potential ◽  
Chemical Space ◽  
Structural Features ◽  
Drug Candidate ◽  
Anomeric Effect ◽  
Drug Candidates ◽  
Structure Activity ◽  
Lipid Chain ◽  
Parasite Infections

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.

Biophysical and computational fragment-based approaches to targeting protein–protein interactions: applications in structure-guided drug discovery

2012 ◽  
Vol 45 (4) ◽  
pp. 383-426 ◽  
Author(s):  
Anja Winter ◽  
Alicia P. Higueruelo ◽  
May Marsh ◽  
Anna Sigurdardottir ◽  
Will R Pitt ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Protein Interactions ◽  
Active Sites ◽  
Current Knowledge ◽  
Chemical Space ◽  
Isothermal Calorimetry ◽  
Protein Protein Interactions ◽  
Regulatory Pathways ◽  
Drug Candidates ◽  
X Ray Crystallography

AbstractDrug discovery has classically targeted the active sites of enzymes or ligand-binding sites of receptors and ion channels. In an attempt to improve selectivity of drug candidates, modulation of protein–protein interfaces (PPIs) of multiprotein complexes that mediate conformation or colocation of components of cell-regulatory pathways has become a focus of interest. However, PPIs in multiprotein systems continue to pose significant challenges, as they are generally large, flat and poor in distinguishing features, making the design of small molecule antagonists a difficult task. Nevertheless, encouragement has come from the recognition that a few amino acids – so-called hotspots – may contribute the majority of interaction-free energy. The challenges posed by protein–protein interactions have led to a wellspring of creative approaches, including proteomimetics, stapled α-helical peptides and a plethora of antibody inspired molecular designs. Here, we review a more generic approach: fragment-based drug discovery. Fragments allow novel areas of chemical space to be explored more efficiently, but the initial hits have low affinity. This means that they will not normally disrupt PPIs, unless they are tethered, an approach that has been pioneered by Wells and co-workers. An alternative fragment-based approach is to stabilise the uncomplexed components of the multiprotein system in solution and employ conventional fragment-based screening. Here, we describe the current knowledge of the structures and properties of protein–protein interactions and the small molecules that can modulate them. We then describe the use of sensitive biophysical methods – nuclear magnetic resonance, X-ray crystallography, surface plasmon resonance, differential scanning fluorimetry or isothermal calorimetry – to screen and validate fragment binding. Fragment hits can subsequently be evolved into larger molecules with higher affinity and potency. These may provide new leads for drug candidates that target protein–protein interactions and have therapeutic value.

scholarly journals Antitumor Effect of Inula viscosa Extracts on DMBA-Induced Skin Carcinoma Are Mediated by Proteasome Inhibition

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Ouadie Mohamed El Yaagoubi ◽  
Ayoub Lahmadi ◽  
Abdelhakim Bouyahya ◽  
Hassan Filali ◽  
Hamid Samaki ◽  
...  
Keyword(s):  
Antitumor Effect ◽  
Proteasome Inhibitors ◽  
Proteasome Inhibition ◽  
Docking Studies ◽  
Skin Carcinogenesis ◽  
Structure Activity ◽  
Potent Inhibition ◽  
Skin Histology ◽  
Before And After ◽  
Skin Papillomas

The aim of this work is to evaluate the antitumor effect mediated by the proteasome inhibitors of Inula viscosa extracts on skin carcinogenesis. Female Swiss albino mice were divided into five groups depending on the combination of skin cancer-inducing 7,12-dimethylbenz(a)anthracene (DMBA) and extract of Inula viscosa treatments. Histology of the affected skin and measurement of proteasome activity were performed to demonstrate the effect of Inula viscosa on mice. The identification of the molecules responsible for this inhibitory activity was carried out through the docking studies. The results showed that Inula viscosa extracts inhibit the development of papilloma in mice. Therefore, the best chemopreventive action of Inula viscosa was observed on mice in which extract treatment was performed before and after the induction of skin carcinogenesis. It was revealed that the ingestion of extracts Inula viscosa delays the formation of skin papillomas in animals and simultaneously decreases the size and number of papillomas, which is also reflected on the skin histology of the mice treated. Structure–activity relationship information obtained from component of Inula viscosa particularly tomentosin, inuviscolide, and isocosticacid demonstrated that distinct bonding modes in β1, β2, and β5 subunits determine its selectivity and potent inhibition for β5 subunit.

Structure-Activity Relationships of Natural and Synthetic Indole-Derived Scaffolds as α-Glucosidase Inhibitors: A Mini-Review

2020 ◽  
Vol 20 (17) ◽  
pp. 1791-1818
Author(s):  
Jiangming Wang ◽  
Silei Lu ◽  
Ruilong Sheng ◽  
Junting Fan ◽  
Wenhui Wu ◽  
...  
Keyword(s):  
Side Effects ◽  
Oral Absorption ◽  
Positive Control ◽  
Structure Activity Relationships ◽  
Drug Candidates ◽  
Structure Activity ◽  
Glucosidase Inhibitors ◽  
Future Drug ◽  
Gastrointestinal Side Effects ◽  
Treatment Of Diabetes

α-Glucosidase plays an important role in carbohydrate metabolism and is an attractive drug target for the treatment of diabetes, obesity and other related complications. Currently, acarbose, miglitol and voglibose have been approved by the FDA for the treatment of diabetes by oral α-glucosidase inhibitors. With the development of anti-diabetic drugs, the emergence of novel drugs with various chemotypes has overshadowed α-glucosidase inhibitors. Since the 1990s, the FDA has not approved new chemical entities against α-glucosidase, which has resulted in restricted clinical medication. Nevertheless, this type of inhibitors possess several unparalleled advantages over other drugs, especially mild side effects (non-systemic gastrointestinal side effects and occasional allergic reactions). Additionally, α-glucosidase inhibitors for monotherapy or in combination with other drugs have been proved to be a feasible approach for the treatment of diabetes. In the last decade, the discovery of natural or synthetic indole derivatives possessing the inhibitory activity of α-glucosidase has received great attention. Herein, we have summarized indoles as inhibitors of α-glucosidase activity, their mechanism of action, synthetic methodologies and structure-activity relationships. Moreover, we have compared the inhibitory potencies of all compounds under their corresponding positive control as well as oral absorption in silico evaluated by tPSA. This review will provide a medium on which future drug design and development for the treatment of diabetes may be modeled as many drug candidates with present great potential as effective anti-diabetic chemotherapy.

Indolizidine Alkaloids: Prospective Lead Molecules in Medicinal Chemistry

2019 ◽  
Vol 05 ◽  
Author(s):  
Vikas Sharma ◽  
Raj Kamal ◽  
Dinesh Kumar ◽  
Vipan Kumar
Keyword(s):  
Drug Discovery ◽  
Medicinal Chemistry ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Indolizidine Alkaloids ◽  
Structure Activity ◽  
Future Drug ◽  
Relationship Of ◽  
Biological Actions

: Alkaloids having indolizidine moiety are well known for their biological actions. In this review, indolizidine alkaloids like antofine, castanospermine, swainsonine, tylophorine, gephyrotoxins, lentiginosine, pergularinine etc and their derivatives have been discussed. Furthermore, important points related to the structure-activity relationship of selected alkaloids are also summarized. All these studies indicate the lead potential of indolizidine alkaloids that in turn could be effective for future drug discovery.

scholarly journals Natural Products as Modulators of Sirtuins

2020 ◽  
Author(s):  
Berin Karaman Mayack ◽  
Wolfgang Sippl ◽  
Fidele Ntie-Kang
Keyword(s):  
Natural Products ◽  
Drug Discovery ◽  
Histone Deacetylases ◽  
High Throughput Screening ◽  
Chemical Space ◽  
Class Iii ◽  
Drug Candidates ◽  
Starting Point ◽  
Recent Developments ◽  
Potent Drug

Natural products have been used for the treatment of human diseases since ancient history. Over time, due to the lack of precise tools and techniques for the separation, purification, and structural elucidation of active constituents in natural resources there has been a decline in financial support and efforts in characterization of natural products. Advances in the design of chemical compounds and the understanding of their functions is of pharmacological importance for the biomedical field. However, natural products regained attention as sources of novel drug candidates upon recent developments and progress in technology. Natural compounds were shown to bear an inherent ability to bind to biomacromolecules and cover an unparalleled chemical space in comparison to most libraries used for high-throughput screening. Thus, natural products hold a great potential for the drug discovery of new scaffolds for therapeutic targets such as Sirtuins. Sirtuins are Class III histone deacetylases that have been linked to many diseases such as Parkinson`s disease, Alzheimer’s disease, type II diabetes, and cancer linked to aging. In this review, we examine the revitalization of interest in natural products for drug discovery and discuss natural product modulators of Sirtuins that could serve as a starting point for the development of isoform selective and highly potent drug-like compounds.

scholarly journals Three novel piperidones exhibit tumor-selective cytotoxicity on leukemia cells via protein degradation and stress-mediated mechanisms

2021 ◽  
Author(s):  
Lisett Contreras ◽  
Stephanie Medina ◽  
Austre Y. Schiaffino Bustamante ◽  
Edgar A. Borrego ◽  
Carlos A. Valenzuela ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Proteasome Inhibitors ◽  
Proteasome Inhibition ◽  
Intrinsic Pathway ◽  
Drug Candidates ◽  
Cycle Arrest ◽  
M Phase ◽  
Stress Related Genes ◽  
The One ◽  
Post Hoc

Abstract Background Cancer is an ongoing worldwide health problem. Although chemotherapy remains the mainstay therapy for cancer, it is not always effective and has detrimental side effects. Here, we present piperidone compounds P3, P4, and P5 that selectively target cancer cells via protein- and stress-mediated mechanisms. Methods We assessed typical apoptotic markers including phosphatidylserine externalization, caspase-3 activation, and DNA fragmentation through flow cytometry. Then, specific markers of the intrinsic pathway of apoptosis including the depolarization of the mitochondria and the generation of reactive oxygen species (ROS) were investigated. Finally, we utilized western blot techniques, RT-qPCR, and observed the cell cycle profile after compound treatment to evaluate the possible behavior of these compounds as proteasome inhibitors. For statistical analyses, we employed the one-way ANOVA followed by Bonferroni post hoc test. Results P3, P4, and P5 induce cytotoxic effects towards tumorigenic cells, as opposed to non-cancerous cells, at the low micromolar range. Compound treatment leads to the activation of the intrinsic pathway of apoptosis. The accumulation of poly-ubiquitinated proteins and the pro-apoptotic protein Noxa, both typically observed after proteasome inhibition, occurs after P3, P4, and P5 treatment. The stress-related genes PMAIP1, ATF3, CHAC1, MYC, and HMOX-1 were differentially regulated to contribute to the cytotoxic activity of P3–P5. Finally, compound P5 causes cell cycle arrest at the G2/M phase. Conclusion Taken together, compounds P3, P4, and P5 exhibit strong potential as anticancer drug candidates as shown by strong cytotoxic potential, activation of the intrinsic pathway of apoptosis, and show typical proteasome inhibitor characteristics.

scholarly journals Analysis of the uncharted, druglike property space by self-organizing maps

2021 ◽  
Author(s):  
Gergely Takács ◽  
Márk Sándor ◽  
Zoltán Szalai ◽  
Róbert Kiss ◽  
György T. Balogh
Keyword(s):  
Drug Discovery ◽  
Chemical Space ◽  
Chemical Databases ◽  
Library Design ◽  
Self Organizing Maps ◽  
Chemical Libraries ◽  
Drug Candidates ◽  
Property Space ◽  
Hit Identification ◽  
Self Organizing

AbstractPhysicochemical properties are fundamental to predict the pharmacokinetic and pharmacodynamic behavior of drug candidates. Easily calculated descriptors such as molecular weight and logP have been found to correlate with the success rate of clinical trials. These properties have been previously shown to highlight a sweet-spot in the chemical space associated with favorable pharmacokinetics, which is superior against other regions during hit identification and optimization. In this study, we applied self-organizing maps (SOMs) trained on sixteen calculated properties of a subset of known drugs for the analysis of commercially available compound databases, as well as public biological and chemical databases frequently used for drug discovery. Interestingly, several regions of the property space have been identified that are highly overrepresented by commercially available chemical libraries, while we found almost completely unoccupied regions of the maps (commercially neglected chemical space resembling the properties of known drugs). Moreover, these underrepresented portions of the chemical space are compatible with most rigorous property filters applied by the pharma industry in medicinal chemistry optimization programs. Our results suggest that SOMs may be directly utilized in the strategy of library design for drug discovery to sample previously unexplored parts of the chemical space to aim at yet-undruggable targets. Graphic abstract

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