Scoring Ligand Efficiency: Potency, Ligand Efficiency and Product Ligand Efficiency within Big Data Landscape

2019 ◽  
Vol 16 (11) ◽  
pp. 1258-1263 ◽  
Author(s):  
Jaroslaw Polanski ◽  
Anna Pedrys ◽  
Roksana Duszkiewicz ◽  
Johann Gasteiger
Keyword(s):  
Small Molecules ◽  
Physical Meaning ◽  
Inhibitory Concentration ◽  
Molecular Descriptor ◽  
Heavy Atom ◽  
Complex Problem ◽  
Ligand Efficiency ◽  
Activity Data ◽  
Drug Candidates ◽  
Maximum Value

Background: Potency is the broadest available biological activity data type. In turn, Ligand Efficiency (LE) is a molecular descriptor that probes the ratio of potency vs Heavy Atom Count (HAC), which emphasizes low HAC more than potency and thus has drawbacks as an estimator of drug candidates. The objective was to design a novel transform to probe potency and HAC interaction in which potency and HAC would be balanced more evenly. Methods: In this study, potency data of ChEMBL, PubChem, FDA approvals and drug (fragments) were analysed. A novel descriptor, a product of the pAC50 value with HAC, multiplicative or Product Ligand Efficiency (PLE) was designed and tested. Results: In particular PLE was compared with pAC50 and LE vs the HAC statistics for different series of ligands. This indicated that PLE is an informative estimator that can be used to recognize the potential of drugs. PLE has a maximum value in the range around 30-50 HAC. Conclusion: Drug design is a complex problem. Similarly, to drug-likeness, LE prefers small molecules. This makes LE a tool serendipitously improving drug likeness. In this context, LE performs unexpectedly well even despite the uncertainty of its physical meaning. PLE is a more evenly balanced estimator whose physical meaning is the Minimum Inhibitory Concentration (MIC).

Recent Updates in the Alzheimer’s Disease Etiopathology and Possible Treatment Approaches: A Narrative Review of Current Clinical Trials

2020 ◽  
Vol 13 (4) ◽  
pp. 273-294 ◽  
Author(s):  
Elahe Zarini-Gakiye ◽  
Javad Amini ◽  
Nima Sanadgol ◽  
Gholamhassan Vaezi ◽  
Kazem Parivar
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Trials ◽  
Small Molecules ◽  
Clinical Trial Design ◽  
Treatment Approaches ◽  
Drug Candidates ◽  
Novel Treatments ◽  
Approved Drugs ◽  
Tau Aggregation

Background: Alzheimer’s disease (AD) is the most frequent subtype of incurable neurodegenerative dementias and its etiopathology is still not clearly elucidated. Objective: Outline the ongoing clinical trials (CTs) in the field of AD, in order to find novel master regulators. Methods: We strictly reviewed all scientific reports from Clinicaltrials.gov and PubMed databases from January 2010 to January 2019. The search terms were “Alzheimer's disease” or “dementia” and “medicine” or “drug” or “treatment” and “clinical trials” and “interventions”. Manuscripts that met the objective of this study were included for further evaluations. Results: Drug candidates have been categorized into two main groups including antibodies, peptides or hormones (such as Ponezumab, Interferon β-1a, Solanezumab, Filgrastim, Levemir, Apidra, and Estrogen), and naturally-derived ingredients or small molecules (such as Paracetamol, Ginkgo, Escitalopram, Simvastatin, Cilostazo, and Ritalin-SR). The majority of natural candidates acted as anti-inflammatory or/and anti-oxidant and antibodies exert their actions via increasing amyloid-beta (Aβ) clearance or decreasing Tau aggregation. Among small molecules, most of them that are present in the last phases act as specific antagonists (Suvorexant, Idalopirdine, Intepirdine, Trazodone, Carvedilol, and Risperidone) or agonists (Dextromethorphan, Resveratrol, Brexpiprazole) and frequently ameliorate cognitive dysfunctions. Conclusion: The presences of a small number of candidates in the last phase suggest that a large number of candidates have had an undesirable side effect or were unable to pass essential eligibility for future phases. Among successful treatment approaches, clearance of Aβ, recovery of cognitive deficits, and control of acute neuroinflammation are widely chosen. It is predicted that some FDA-approved drugs, such as Paracetamol, Risperidone, Escitalopram, Simvastatin, Cilostazoand, and Ritalin-SR, could also be used in off-label ways for AD. This review improves our ability to recognize novel treatments for AD and suggests approaches for the clinical trial design for this devastating disease in the near future.

scholarly journals Transcriptome analysis of Escherichia coli K1 after therapy with hesperidin conjugated with silver nanoparticles

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Abdulkader Masri ◽  
Naveed Ahmed Khan ◽  
Muhammad Zarul Hanifah Md Zoqratt ◽  
Qasim Ayub ◽  
Ayaz Anwar ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Silver Nanoparticles ◽  
Minimum Inhibitory Concentration ◽  
Inhibitory Concentration ◽  
Neonatal Meningitis ◽  
E Coli ◽  
Drug Candidates ◽  
Metabolic Genes ◽  
Genetic Mechanisms ◽  
Cell Stress Response

Abstract Backgrounds Escherichia coli K1 causes neonatal meningitis. Transcriptome studies are indispensable to comprehend the pathology and biology of these bacteria. Recently, we showed that nanoparticles loaded with Hesperidin are potential novel antibacterial agents against E. coli K1. Here, bacteria were treated with and without Hesperidin conjugated with silver nanoparticles, and silver alone, and 50% minimum inhibitory concentration was determined. Differential gene expression analysis using RNA-seq, was performed using Degust software and a set of genes involved in cell stress response and metabolism were selected for the study. Results 50% minimum inhibitory concentration with silver-conjugated Hesperidin was achieved with 0.5 μg/ml of Hesperidin conjugated with silver nanoparticles at 1 h. Differential genetic analysis revealed the expression of 122 genes (≥ 2-log FC, P< 0.01) in both E. coli K1 treated with Hesperidin conjugated silver nanoparticles and E. coli K1 treated with silver alone, compared to untreated E. coli K1. Of note, the expression levels of cation efflux genes (cusA and copA) and translocation of ions, across the membrane genes (rsxB) were found to increase 2.6, 3.1, and 3.3- log FC, respectively. Significant regulation was observed for metabolic genes and several genes involved in the coordination of flagella. Conclusions The antibacterial mechanism of nanoparticles maybe due to disruption of the cell membrane, oxidative stress, and metabolism in E. coli K1. Further studies will lead to a better understanding of the genetic mechanisms underlying treatment with nanoparticles and identification of much needed novel antimicrobial drug candidates.

scholarly journals Bioactive Secondary Metabolites of the Genus Diaporthe and Anamorph Phomopsis from Terrestrial and Marine Habitats and Endophytes: 2010–2019

2021 ◽  
Vol 9 (2) ◽  
pp. 217
Author(s):  
Tang-Chang Xu ◽  
Yi-Han Lu ◽  
Jun-Fei Wang ◽  
Zhi-Qiang Song ◽  
Ya-Ge Hou ◽  
...  
Keyword(s):  
Secondary Metabolites ◽  
Small Molecules ◽  
Host Plants ◽  
Plant Pathogens ◽  
Bioactive Metabolites ◽  
Drug Candidates ◽  
The Past ◽  
Marine Habitats ◽  
Bioactive Secondary Metabolites ◽  
Unidentified Species

The genus Diaporthe and its anamorph Phomopsis are distributed worldwide in many ecosystems. They are regarded as potential sources for producing diverse bioactive metabolites. Most species are attributed to plant pathogens, non-pathogenic endophytes, or saprobes in terrestrial host plants. They colonize in the early parasitic tissue of plants, provide a variety of nutrients in the cycle of parasitism and saprophytism, and participate in the basic metabolic process of plants. In the past ten years, many studies have been focused on the discovery of new species and biological secondary metabolites from this genus. In this review, we summarize a total of 335 bioactive secondary metabolites isolated from 26 known species and various unidentified species of Diaporthe and Phomopsis during 2010–2019. Overall, there are 106 bioactive compounds derived from Diaporthe and 246 from Phomopsis, while 17 compounds are found in both of them. They are classified into polyketides, terpenoids, steroids, macrolides, ten-membered lactones, alkaloids, flavonoids, and fatty acids. Polyketides constitute the main chemical population, accounting for 64%. Meanwhile, their bioactivities mainly involve cytotoxic, antifungal, antibacterial, antiviral, antioxidant, anti-inflammatory, anti-algae, phytotoxic, and enzyme inhibitory activities. Diaporthe and Phomopsis exhibit their potent talents in the discovery of small molecules for drug candidates.

scholarly journals GENETIC INVOLVEMENT OF INTERLEUKIN 4 FOR ASTHMA AND IDENTIFICATION OF POTENTIAL PHYTOCHEMICAL SCAFFOLD THROUGH MOLECULAR DOCKING STUDIES

2018 ◽  
Vol 10 (1) ◽  
pp. 43 ◽  
Author(s):  
S. Sarithamol ◽  
Divya V. ◽  
Sunitha V. R. ◽  
Suchitra Surendran ◽  
V. L. Pushpa ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Small Molecules ◽  
In Silico ◽  
Mutational Analysis ◽  
Chromosome Region ◽  
Specific Treatment ◽  
Docking Studies ◽  
Interleukin 4 ◽  
Receptor Interaction ◽  
Drug Candidates

Objective: Interleukin 4, an important cytokine, has the major role in the immunomodulatory responses associated with asthma. The present study focused on the involvement of single nucleotide polymorphism variation (SNP) of interleukin 4 (IL4) in the development of disease, asthma and designing small molecules for the inhibition of IL4 through in silico strategy.Methods: Identification of disease causing SNP will be a wise approach towards the phenotype specific treatment. A human origin deleterious no synonymous SNP of IL4 were found out in the chromosome region 5q31-q33 (rs199929962) (T/C). Proteins of the corresponding nucleotide variation were identified and were subjected to characterization studies for selecting the most appropriate one for further mutational analysis and molecular docking studies.Results: Influence of microbes on SNP variation of IL4 gene leading to asthma was found to be insignificant by metagenomic studies. Gene responsive drugs were identified through environmental factor analysis. The drug candidates including corticosteroids were subjected to protein interaction studies by in silico means. The pharmacophoric feature derived from drug receptor interaction was utilized for virtual screening on a dataset of anti-inflammatory phytomolecules. The scaffolds of ellagic acid and quercetin were identified as potential nonsteroidal entities which can shield the asthmatic activities.Conclusion: Developing small molecules using these scaffolds taking interleukin 4 as a target will be an adequate solution for steroid resistant asthma.

scholarly journals Synthetic Heterocyclic Derivatives as Kinase Inhibitors Tested for the Treatment of Neuroblastoma

Molecules ◽  
2021 ◽  
Vol 26 (23) ◽  
pp. 7069
Author(s):  
Francesca Musumeci ◽  
Annarita Cianciusi ◽  
Ilaria D’Agostino ◽  
Giancarlo Grossi ◽  
Anna Carbone ◽  
...  
Keyword(s):  
Small Molecules ◽  
Pediatric Cancer ◽  
Kinase Inhibitors ◽  
Severe Disease ◽  
Chemotherapeutic Agents ◽  
Cytotoxic Agents ◽  
Specific Mechanism ◽  
Drug Candidates ◽  
Heterocyclic Derivatives ◽  
Tumor In Childhood

In the last few years, small molecules endowed with different heterocyclic scaffolds have been developed as kinase inhibitors. Some of them are being tested at preclinical or clinical levels for the potential treatment of neuroblastoma (NB). This disease is the most common extracranial solid tumor in childhood and is responsible for 10% to 15% of pediatric cancer deaths. Despite the availability of some treatments, including the use of very toxic cytotoxic chemotherapeutic agents, high-risk (HR)-NB patients still have a poor prognosis and a survival rate below 50%. For these reasons, new pharmacological options are urgently needed. This review focuses on synthetic heterocyclic compounds published in the last five years, which showed at least some activity on this severe disease and act as kinase inhibitors. The specific mechanism of action, selectivity, and biological activity of these drug candidates are described, when established. Moreover, the most remarkable clinical trials are reported. Importantly, kinase inhibitors approved for other diseases have shown to be active and endowed with lower toxicity compared to conventional cytotoxic agents. The data collected in this article can be particularly useful for the researchers working in this area.

Fragment-based drug design of nature-inspired compounds

2019 ◽  
Vol 4 (9) ◽  
Author(s):  
Abdulkarim Najjar ◽  
Abdurrahman Olğaç ◽  
Fidele Ntie-Kang ◽  
Wolfgang Sippl
Keyword(s):  
Drug Design ◽  
Small Molecules ◽  
Small Molecule ◽  
Binding Pocket ◽  
Biological Macromolecules ◽  
Drug Candidates ◽  
Fragment Screening ◽  
Small Molecule Drugs ◽  
Lead Generation ◽  
Hit Identification

Abstract Natural product (NP)-derived drugs can be extracts, biological macromolecules, or purified small molecule substances. Small molecule drugs can be originally purified from NPs, can represent semisynthetic molecules, natural fragments containing small molecules, or are fully synthetic molecules that mimic natural compounds. New semisynthetic NP-like drugs are entering the pharmaceutical market almost every year and reveal growing interests in the application of fragment-based approaches for NPs. Thus, several NP databases were constructed to be implemented in the fragment-based drug design (FBDD) workflows. FBDD has been established previously as an approach for hit identification and lead generation. Several biophysical and computational methods are used for fragment screening to identify potential hits. Once the fragments within the binding pocket of the protein are identified, they can be grown, linked, or merged to design more active compounds. This work discusses applications of NPs and NP scaffolds to FBDD. Moreover, it briefly reviews NP databases containing fragments and reports on case studies where the approach has been successfully applied for the design of antimalarial and anticancer drug candidates.

scholarly journals In VitroCombination Studies of Benzothiazinone Lead Compound BTZ043 against Mycobacterium tuberculosis

2012 ◽  
Vol 56 (11) ◽  
pp. 5790-5793 ◽  
Author(s):  
Benoit Lechartier ◽  
Ruben C. Hartkoorn ◽  
Stewart T. Cole
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Inhibitory Concentration ◽  
Bactericidal Effect ◽  
Lead Compound ◽  
Content Type ◽  
Drug Candidates ◽  
New Class ◽  
Novel Targets ◽  
Essential Enzyme ◽  
Strain H37rv

ABSTRACTBenzothiazinones (BTZ) are a new class of drug candidates to combat tuberculosis that inhibit decaprenyl-phosphoribose epimerase (DprE1), an essential enzyme involved in arabinan biosynthesis. Using the checkerboard method and cell viability assays, we have studied the interaction profiles of BTZ043, the current lead compound, with several antituberculosis drugs or drug candidates againstMycobacterium tuberculosisstrain H37Rv, namely, rifampin, isoniazid, ethambutol, TMC207, PA-824, moxifloxacin, meropenem with or without clavulanate, and SQ-109. No antagonism was found between BTZ043 and the tested compounds, and most of the interactions were purely additive. Data from two different approaches clearly indicate that BTZ043 acts synergistically with TMC207, with a fractional inhibitory concentration index of 0.5. TMC207 at a quarter of the MIC (20 ng/ml) used in combination with BTZ043 (1/4 MIC, 0.375 ng/ml) had a stronger bactericidal effect onM. tuberculosisthan TMC207 alone at a concentration of 80 ng/ml. This synergy was not observed when the combination was tested on a BTZ-resistantM. tuberculosismutant, suggesting that DprE1 inhibition is the basis for the interaction. This finding excludes the possibility of synergy occurring through an off-target mechanism. We therefore hypothesize that sub-MICs of BTZ043 weaken the bacterial cell wall and allow improved penetration of TMC207 to its target. Synergy between two new antimycobacterial compounds, such as TMC207 and BTZ043, with novel targets, offers an attractive foundation for a new tuberculosis regimen.

scholarly journals Inhibition of Antiapoptotic BCL-XL, BCL-2, and MCL-1 Proteins by Small Molecule Mimetics

2010 ◽  
Vol 9 ◽  
pp. CIN.S5065 ◽  
Author(s):  
D.S. Dalafave ◽  
G. Prisco
Keyword(s):  
Small Molecules ◽  
Cancer Cells ◽  
Molecular Design ◽  
Poor Response ◽  
Computational Design ◽  
Antiapoptotic Proteins ◽  
Drug Candidates ◽  
Preclinical Trials ◽  
Computer Based ◽  
Stress Signals

Informatics and computational design methods were used to create new molecules that could potentially bind antiapoptotic proteins, thus promoting death of cancer cells. Apoptosis is a cellular process that leads to the death of damaged cells. Its malfunction can cause cancer and poor response to conventional chemotherapy. After being activated by cellular stress signals, proapoptotic proteins bind antiapoptotic proteins, thus allowing apoptosis to go forward. An excess of antiapoptotic proteins can prevent apoptosis. Designed molecules that mimic the roles of proapoptotic proteins can promote the death of cancer cells. The goal of our study was to create new putative mimetics that could simultaneously bind several antiapoptotic proteins. Five new small molecules were designed that formed stable complexes with BCL-2, BCL-XL, and MCL-1 antiapoptotic proteins. These results are novel because, to our knowledge, there are not many, if any, small molecules known to bind all three proteins. Drug-likeness studies performed on the designed molecules, as well as previous experimental and preclinical studies on similar agents, strongly suggest that the designed molecules may indeed be promising drug candidates. All five molecules showed “drug-like” properties and had overall drug-likeness scores between 81% and 96%. A single drug based on these mimetics should cost less and cause fewer side effects than a combination of drugs each aimed at a single protein. Computer-based molecular design promises to accelerate drug research by predicting potential effectiveness of designed molecules prior to laborious experiments and costly preclinical trials.

scholarly journals Discovery of BAZ2A Bromodomain Ligands

2017 ◽  
Author(s):  
Dimitrios Spiliotopoulos ◽  
Eike-Christian Wamhoff ◽  
Graziano Lolli ◽  
Christoph Rademacher ◽  
Amedeo Caflisch
Keyword(s):  
Small Molecules ◽  
Binding Assay ◽  
Side Chain ◽  
Binding Modes ◽  
Zinc Finger Domain ◽  
Ligand Efficiency ◽  
Competition Binding Assay ◽  
Energy Evaluation ◽  
Natural Ligand ◽  
Competition Binding

The bromodomain adjacent to zinc finger domain protein 2A (BAZ2A) is implicated in aggressive prostate cancer. The BAZ2A bromodomain is a challenging target because of the shallow pocket of its natural ligand, the acetylated side chain of lysine. Here, we report the successful screening of a library of nearly 1500 small molecules by high-throughput docking and force field-based binding-energy evaluation. For seven of the 20 molecules selected in silico, evidence of binding to the BAZ2A bromodomain is provided by ligand-observed NMR spectroscopy. Two of these compounds show a favorable ligand efficiency of 0.42 kcal/mol per non-hydrogen atom in a competition-binding assay. The crystal structures of the BAZ2A bromodomain in complex with four fragment hits validate the predicted binding modes. The binding modes of compounds 1 and 3 are compatible with ligand growing for optimization of affinity for BAZ2A and selectivity against the close homologue BAZ2B.

scholarly journals In silico screening for the interaction of small molecules with their targets and evaluation of therapeutic efficacy by free online tools

2020 ◽  
Vol 11 (2) ◽  
pp. 168-178
Author(s):  
Praveen Kumar ◽  
Nayak Devappa Satyanarayan ◽  
Subba Rao Venkata Madhunapantula ◽  
Hulikal Shivashankara Santhosh Kumar ◽  
Rajeshwara Achur
Keyword(s):  
Small Molecules ◽  
Computational Methods ◽  
Active Sites ◽  
Pharmaceutical Chemistry ◽  
Lead Discovery ◽  
Drug Candidates ◽  
Biological Potential ◽  
Output Information ◽  
The Right ◽  
Almost All

Pharmaceutical chemistry deals with the process of isolating organic compounds from natural sources or chemically synthesizing them in order to explore potential drugs. Drugs are small molecules, used to prevent or treat various diseases. Of several lead molecules, only few of them reach clinical trial phases and emerge as effective drugs, whereas the majority will be eliminated at different stages. On the other hand, due to the lack of proper identification of their pharmacokinetic properties and biological potential, many small molecules fail to reach this stage. This could be because of the fact that it is either time consuming and costly or there is full of uncertainty due to lack of analyses that are necessary for the confirmation. In the post-genomic era, computational methods have been implemented in almost all stages of drug research and development owing to the drastic increase in the available knowledge about small molecules and the target biomacromolecule. This includes identifying the suitable and specific targets for drug candidates, lead discovery, lead optimization and ultimately preclinical phases. In this context, numerous websites have become highly valuable and influence the drug development and discovery process. Here, we have attempted to bring together some of the online computational approaches and tools that are available to facilitate research efforts in the field of drug discovery and drug design. The output information from these tools is extremely helpful in selecting and deciding about the future direction or specific path needed to be followed by the researchers. These computational methods are indeed help to focus the intended research in the right direction. As detailed in this review, the information provided about the servers and methods should be useful throughout the process of screening of synthesized or chemical database originated small molecules to find the appropriate targets along with the active sites without depending on any commercial tools or time-consuming and costly assays. It should however be remembered that the bioinformatics-based prediction cannot completely replace the wet lab data of chemical compounds or specific assays.

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