A QSAR Model for in Silico Screening of MAO-A Inhibitors. Prediction, Synthesis, and Biological Assay of Novel Coumarins†

2006 ◽  
Vol 49 (3) ◽  
pp. 1149-1156 ◽  
Author(s):  
Lourdes Santana ◽  
Eugenio Uriarte ◽  
Humberto González-Díaz ◽  
Giuseppe Zagotto ◽  
Ramón Soto-Otero ◽  
...  
2019 ◽  
Vol 20 (19) ◽  
pp. 4730
Author(s):  
Koffi Charles Kouman ◽  
Melalie Keita ◽  
Raymond Kre N’Guessan ◽  
Luc Calvin Owono Owono ◽  
Eugene Megnassan ◽  
...  

Background: During the previous decade a new class of benzamide-based inhibitors of 2-trans enoyl-acyl carrier protein reductase (InhA) of Mycobacterium tuberculosis (Mt) with unusual binding mode have emerged. Here we report in silico design and evaluation of novel benzamide InhA-Mt inhibitors with favorable predicted pharmacokinetic profiles. Methods: By using in situ modifications of the crystal structure of N-benzyl-4-((heteroaryl)methyl) benzamide (BHMB)-InhA complex (PDB entry 4QXM), 3D models of InhA-BHMBx complexes were prepared for a training set of 19 BHMBs with experimentally determined inhibitory potencies (half-maximal inhibitory concentrations IC50exp). In the search for active conformation of the BHMB1-19, linear QSAR model was prepared, which correlated computed gas phase enthalpies of formation (∆∆HMM) of InhA-BHMBx complexes with the IC50exp. Further, taking into account the solvent effect and entropy changes upon ligand, binding resulted in a superior QSAR model correlating computed complexation Gibbs free energies (∆∆Gcom). The successive pharmacophore model (PH4) generated from the active conformations of BHMBs served as a virtual screening tool of novel analogs included in a virtual combinatorial library (VCL) of compounds containing benzamide scaffolds. The VCL filtered by Lipinski’s rule-of-five was screened by the PH4 model to identify new BHMB analogs. Results: Gas phase QSAR model: −log10(IC50exp) = pIC50exp = −0.2465 × ∆∆HMM + 7.95503, R2 = 0.94; superior aqueous phase QSAR model: pIC50exp = −0.2370 × ∆∆Gcom + 7.8783, R2 = 0.97 and PH4 pharmacophore model: p IC 50 exp = 1.0013 × p IC 50 exp − 0.0085, R2 = 0.95. The VCL of more than 114 thousand BHMBs was filtered down to 73,565 analogs Lipinski’s rule. The five-point PH4 screening retained 90 new and potent BHMBs with predicted inhibitory potencies IC50pre up to 65 times lower than that of BHMB1 (IC50exp = 20 nM). Predicted pharmacokinetic profile of the new analogs showed enhanced cell membrane permeability and high human oral absorption compared to current anti-tuberculotics. Conclusions: Combined use of QSAR models that considered binding of the BHMBs to InhA, pharmacophore model, and ADME properties helped to recognize bound active conformation of the benzamide inhibitors, permitted in silico screening of VCL of compounds sharing benzamide scaffold and identification of new analogs with predicted high inhibitory potencies and favorable pharmacokinetic profiles.


Author(s):  
Kouakou Kouakou Jean-Louis ◽  
◽  
Melalie Keita ◽  
Akori Elvice Esmel ◽  
Brice Dali ◽  
...  

Background: In recent years, there has been a growing interest in Denv NS5 inhibition, with several reported RdRp inhibitors such as sulfonylbenzamides, non-nucleo-side inhibitors without any 3D-QSAR pharmacophore (PH4) available. In this context, we report here, in silico design and virtual evaluation of novel sulfonylbenzamides Denv RdRp inhibitors with favorable predicted pharmacokinetic profile. Methods: By using in situ modifications of the crystal structure of 5-(5-(3-hydroxyprop-1-yn-1-yl)thiophen-2-yl)-4- methoxy-2-methyl-N-(methylsulfonyl) benzamide (EHB)-RdRp complex (PDB entry 5HMZ), 3D models of RdRp-EHBx complexes were prepared for a training set of 18 EHBs with experimentally determined inhibitory potencies (half-maximal inhibitory concentrations IC50exp). In the search for active conformation of the EHB1-18, linear QSAR model was prepared, which correlated computed gas phase enthalpies of formation ∆∆HMM of RdRp-EHBx complexes with the IC50exp. Further, considering the solvent effect and entropy changes upon ligand binding resulted in a superior QSAR model correlating computed complexation Gibbs free energies (∆∆Gcom). The successive pharmacophore model (PH4) generated from the active conformations of EHBs served as a virtual screening tool of novel analogs included in a virtual combinatorial library (VCL) of compounds with scaffolds restricted to phenyl. The VCL filtered by the Lipinski’s rule-of-five was screened by the PH4 model to identify new EHB analogs. Results: Gas phase QSAR model: -log10(IC50exp) = p IC50exp =-0.1403 x ∆∆HMM _ 7.0879, R2 = 0.73; superior aqueous phase QSAR model: p IC50exp = -0.2036 x ∆∆Gcom + 7.4974, R2 = 0.81 and PH4 pharmacophore model: p IC50exp = 1.0001 x p IC50pre -0.0017, R2 = 0.97. The VCL of more than 30 million EHBs was filtered down to 125,915 analogs Lipinski’s rule. The five-point PH4 screening retained 329 new and potent EHBs with predicted inhibitory potencies p IC50pre up to 30 times lower than that of EHB1 (IC50exp = 23nM). Predicted pharmacokinetic profile of the new analogs showed enhanced cell membrane permeability and high human oral absorption compared to the alone drug to treat dengue virus. Conclusions: Combined use of QSAR models, which considered binding of the EHBs to RdRp, pharmacophore model and ADME properties helped to recognize bound active conformation of the sulfonylbenzamide inhibitors, permitted in silico screening of VCL of compounds sharing sulfonylbenzamide scaffold and identify new analogs with predicted high inhibitory potencies and favorable pharmacokinetic profiles. Keywords: ADME properties prediction, Dengue, 3-(5-ethynylthiophen-2-yl)-N-hydrosulfonylbenzamides, in silico screening, RNA-dependent RNA polymerase.


2011 ◽  
Vol 21 (8) ◽  
pp. 2419-2424 ◽  
Author(s):  
Suhas M. Shelke ◽  
Sharad H. Bhosale ◽  
Radha Charan Dash ◽  
Mugdha R. Suryawanshi ◽  
Kakasaheb R. Mahadik
Keyword(s):  
3D Qsar ◽  

2019 ◽  
Author(s):  
Veeren Chauhan ◽  
Mohamed M Elsutohy ◽  
C Patrick McClure ◽  
Will Irving ◽  
Neil Roddis ◽  
...  

<p>Enteroviruses are a ubiquitous mammalian pathogen that can produce mild to life-threatening disease. Bearing this in mind, we have developed a rapid, accurate and economical point-of-care biosensor that can detect a nucleic acid sequences conserved amongst 96% of all known enteroviruses. The biosensor harnesses the physicochemical properties of gold nanoparticles and aptamers to provide colourimetric, spectroscopic and lateral flow-based identification of an exclusive enteroviral RNA sequence (23 bases), which was identified through in silico screening. Aptamers were designed to demonstrate specific complementarity towards the target enteroviral RNA to produce aggregated gold-aptamer nanoconstructs. Conserved target enteroviral nucleic acid sequence (≥ 1x10<sup>-7</sup> M, ≥1.4×10<sup>-14</sup> g/mL), initiates gold-aptamer-nanoconstructs disaggregation and a signal transduction mechanism, producing a colourimetric and spectroscopic blueshift (544 nm (purple) > 524 nm (red)). Furthermore, lateral-flow-assays that utilise gold-aptamer-nanoconstructs were unaffected by contaminating human genomic DNA, demonstrated rapid detection of conserved target enteroviral nucleic acid sequence (< 60 s) and could be interpreted with a bespoke software and hardware electronic interface. We anticipate our methodology will translate in-silico screening of nucleic acid databases to a tangible enteroviral desktop detector, which could be readily translated to related organisms. This will pave-the-way forward in the clinical evaluation of disease and complement existing strategies at overcoming antimicrobial resistance.</p>


Author(s):  
Bichismita Sahu ◽  
Santosh Kumar Behera ◽  
Rudradip Das ◽  
Tanay Dalvi ◽  
Arnab Chowdhury ◽  
...  

Introduction: The outburst of the novel coronavirus COVID-19, at the end of December 2019 has turned itself into a pandemic taking a heavy toll on human lives. The causal agent being SARS-CoV-2, a member of the long-known Coronaviridae family, is a positive sense single-stranded enveloped virus and quite closely related to SARS-CoV. It has become the need of the hour to understand the pathophysiology of this disease, so that drugs, vaccines, treatment regimens and plausible therapeutic agents can be produced. Methods: In this regard, recent studies uncovered the fact that the viral genome of SARS-CoV-2 encodes nonstructural proteins like RNA dependent RNA polymerase (RdRp) which is an important tool for its transcription and replication process. A large number of nucleic acid based anti-viral drugs are being repurposed for treating COVID-19 targeting RdRp. Few of them are in the advanced stage of clinical trials including Remdesivir. While performing close investigation of the large set of nucleic acid based drugs, we were surprised to find that the synthetic nucleic acid backbone is explored very little or rare. Results: We have designed scaffolds derived from peptide nucleic acid (PNA) and subjected them for in-silico screening systematically. These designed molecules have demonstrated excellent binding towards RdRp. Compound 12 was found to possess similar binding affinity as Remdesivir with comparable pharmacokinetics. However, the in-silico toxicity prediction indicates compound 12 may be a superior molecule which can be explored further due to its excellent safety-profile with LD50 (12,000mg/kg) as opposed to Remdesivir (LD50 =1000mg/kg). Conclusion: Compound 12 falls in the safe category of class 6. Synthetic feasibility, equipotent binding and very low toxicity of this peptide nucleic acid derived compounds can serve as a leading scaffold to design, synthesize and evaluate many of similar compounds for the treatment of COVID-19.


Author(s):  
Dnyaneshwar Baswar ◽  
Abha Sharma ◽  
Awanish Mishra

Background: Alzheimer’s disease (AD), an irreversible complex neurodegenerative disorder, is most common type of dementia, with progressive loss of cholinergic neurons. Based on the multi- factorial etiology of Alzheimer’s disease, novel ligands strategy appears as up-coming approach for the development of newer molecules against AD. This study is envisaged to investigate anti-Alzheimer’s potential of 10 synthesized compounds. The screening of compounds (1-10) was carried out using in silico techniques. Methods: For in silico screening of physicochemical properties of compounds molinspiration property engine v.2018.03, Swiss ADME online web-server and pkCSM ADME were used. For pharmacodynamic prediction PASS software while toxicity profile of compounds were analyzed through ProTox-II online software. Simultaneously, molecular docking analysis was performed on mouse AChE enzyme (PDB ID:2JGE, obtained from RSCB PDB) using Auto Dock Tools 1.5.6. Results: Based on in silico studies, compound 9 and 10 have been found to have better drug likeness, LD50 value, and better anti-Alzheimer’s, nootropic activities. However, these compounds had poor blood brain barrier (BBB) permeability. Compound 4 and 9 were predicted with better docking score for AChE enzyme. Conclusion: The outcome of in silico studies have suggested, out of various substitutions at different positions of pyridoxine-carbamate, compound 9 have shown promising drug likeness, with better safety and efficacy profile for anti-Alzheimer’s activity. However, BBB permeability appears as one the major limitation of all these compounds. Further studies are required to confirm its biological activities.


2018 ◽  
Vol 12 (2) ◽  
pp. 181-190 ◽  
Author(s):  
Priya P. Panigrahi ◽  
Ramit Singla ◽  
Ankush Bansal ◽  
Moacyr Comar Junior ◽  
Vikas Jaitak ◽  
...  

Author(s):  
Martin Balouch ◽  
Martin Šrejber ◽  
Marek Šoltys ◽  
Petra Janská ◽  
František Štěpánek ◽  
...  

In silico methodology for compound suitability for liposomal formulation has been developed. Water–lipid partitioning and permeation of candidate compounds from the DrugBank were calculated, and the most appropriate targets validated experimentally.


Biomolecules ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 216
Author(s):  
Nadia A. Rivero-Segura ◽  
Juan C. Gomez-Verjan

The COVID-19 pandemic has already taken the lives of more than 2 million people worldwide, causing several political and socio-economic disturbances in our daily life. At the time of publication, there are non-effective pharmacological treatments, and vaccine distribution represents an important challenge for all countries. In this sense, research for novel molecules becomes essential to develop treatments against the SARS-CoV-2 virus. In this context, Mexican natural products have proven to be quite useful for drug development; therefore, in the present study, we perform an in silico screening of 100 compounds isolated from the most commonly used Mexican plants, against the SARS-CoV-2 virus. As results, we identify ten compounds that meet leadlikeness criteria (emodin anthrone, kaempferol, quercetin, aesculin, cichoriin, luteolin, matricin, riolozatrione, monocaffeoyl tartaric acid, aucubin). According to the docking analysis, only three compounds target the key proteins of SARS-CoV-2 (quercetin, riolozatrione and cichoriin), but only one appears to be safe (cichoriin). ADME (absorption, distribution, metabolism and excretion) properties and the physiologically based pharmacokinetic (PBPK) model show that cichoriin reaches higher lung levels (100 mg/Kg, IV); therefore, it may be considered in developing therapeutic tools.


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