Discovery and in silico evaluation of aminoarylbenzosuberene molecules as novel checkpoint kinase 1 inhibitor determinants

The molecular interaction of human anti-apoptotic proteins and in silico ADMET, drug-likeness and toxicity computation of N-cyclohexylmethacrylamide

Cancer is an uncontrolled growth of normal cells and apoptosis has an important role in cancer progression and cancer treatment. Antiapoptotic proteins are overexpressed in several tumors including breast, brain, lung cancer cells. The protein-ligand interaction has a critical role in drug designing. The present study aims to evaluate the interaction of synthesized N-cyclohexylmethacrylamide (NCMA) with proteins using in silico molecular docking and toxicity analyses. The NCMA monomer was synthesized and characterized by our team, previously. Kinetics stability, binding affinities and toxic potential of protein-NCMA complex were examined with the aid of molecular simulation. The toxicity results of this study indicate that NCMA is a sample with low toxic potential. According to the docking results, NCMA may be a drug active substance with chemical modifications and toxicity results support this situation. The drug-likeness and ADMET parameters were screened properties of NCMA.

In silico drug repositioning based on the integration of chemical, genomic and pharmacological spaces

BACKGROUND

Drug repositioning refers to the identification of new indications for existing drugs. Drug-based inference methods for drug repositioning apply some unique features of drugs for new indication prediction. Complementary information is provided by these different features. It is therefore necessary to integrate these features for more accurate in silico drug repositioning.

RESULTS

In this study, we collect 3 different types of drug features (i.e., chemical, genomic and pharmacological spaces) from public databases. Similarities between drugs are separately calculated based on each of the features. We further develop a fusion method to combine the 3 similarity measurements. We test the inference abilities of the 4 similarity datasets in drug repositioning under the guilt-by-association principle. Leave-one-out cross-validations show the integrated similarity measurement IntegratedSim receives the best prediction performance, with the highest AUC value of 0.8451 and the highest AUPR value of 0.2201. Case studies demonstrate IntegratedSim produces the largest numbers of confirmed predictions in most cases. Moreover, we compare our integration method with 3 other similarity-fusion methods using the datasets in our study. Cross-validation results suggest our method improves the prediction accuracy in terms of AUC and AUPR values.

CONCLUSIONS

Our study suggests that the 3 drug features used in our manuscript are valuable information for drug repositioning. The comparative results indicate that integration of the 3 drug features would improve drug-disease association prediction. Our study provides a strategy for the fusion of different drug features for in silico drug repositioning.

Enhancing the catalytic activity of a GH5 processive endoglucanase from Bacillus subtilis BS-5 by site-directed mutagenesis

Processive endoglucanases possess both endo- and exoglucanase activity, making them attractive discovery and engineering targets. Here, a processive endoglucanase EG5C-1 from Bacillus subtilis was employed as the starting point for enzyme engineering. Referring to the complex structure information of EG5C-1 and cellohexaose, the amino acid residues in the active site architecture were identified and subjected to alanine scanning mutagenesis. The residues were chosen for a saturation mutagenesis since their variants showed similar activities to EG5C-1. Variants D70Q and S235W showed increased activity towards the substrates CMC and Avicel, an increase was further enhanced in D70Q/S235W double mutant, which displayed a 2.1- and 1.7-fold improvement in the hydrolytic activity towards CMC and Avicel, respectively. In addition, kinetic measurements showed that double mutant had higher substrate affinity (K_m) and a significantly higher catalytic efficiency (k_cat/K_m). The binding isotherms of wild-type EG5C-1 and double mutant D70Q/S235W suggested that the binding capability of EG5C-1 for the insoluble substrate was weaker than that of D70Q/S235W. Molecular dynamics simulations suggested that the collaborative substitutions of D70Q and S235W altered the hydrogen bonding network within the active site architecture and introduced new hydrogen bonds between the enzyme and cellohexaose, thus enhancing both substrate affinity and catalytic efficiency.

Sensing the interactions between carbohydrate-binding agents and N-linked glycans of SARS-CoV-2 spike glycoprotein using molecular docking and simulation studies

A recent surge in finding new candidate vaccines and potential antivirals to tackle atypical pneumonia triggered by the novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) needs new and unexplored approaches in solving this global pandemic. The homotrimeric transmembrane spike (S) glycoprotein of coronaviruses which facilitates virus entry into the host cells is covered with N-linked glycans having oligomannose and complex sugars. These glycans provide a unique opportunity for their targeting via carbohydrate-binding agents (CBAs) which have shown their antiviral potential against coronaviruses and enveloped viruses. However, CBA-ligand interaction is not fully explored in developing novel carbohydrate-binding-based antivirals due to associated unfavorable responses with CBAs. CBAs possess unique carbohydrate-binding specificity, therefore, CBAs like mannose-specific plant lectins/lectin-like mimic Pradimicin-A (PRM-A) can be used for targeting N-linked glycans of S glycoproteins. Here, we report studies on the binding and stability of lectins (NPA, UDA, GRFT, CV-N and wild-type and mutant BanLec) and PRM-A with the S glycoprotein glycans via docking and MD simulation. MM/GBSA calculations were also performed for docked complexes. Interestingly, stable BanLec mutant (H84T) also showed similar docking affinity and interactions as compared to wild-type BanLec, thus, confirming that uncoupling the mitogenic activity did not alter the lectin binding activity of BanLec. The stability of the docked complexes, i.e. PRM-A and lectins with SARS-CoV-2 S glycoprotein showed favorable intermolecular hydrogen-bond formation during the 100 ns MD simulation. Taking these together, our predicted in silico results will be helpful in the design and development of novel CBA-based antivirals for the SARS-CoV-2 neutralization.Communicated by Ramaswamy H. Sarma.

Evaluation of acridinedione analogs as potential SARS-CoV-2 main protease inhibitors and their comparison with repurposed anti-viral drugs

Background

The main protease (Mpro) of SARS-CoV-2 is involved in the processing of vital polypeptides required for viral genome replication and transcription and is one of the best-characterized targets to inhibit the progression of SARS-CoV-2 in infected individuals.

Methods

We screened a set of novel classes of acridinediones molecules to efficiently bind and inhibit the activity of the SARS-CoV-2 by targeting the Mpro. The repurposed FDA-approved antivirals were taken as standard molecules for this study. Long term (1.1 μs) MD simulations were performed to analyze the conformational space of the binding pocket of Mpro bound to the selected molecules.

Results

The molecules DSPD-2 and DSPD-6 showed more favorable MM-PBSA interaction energies and were seated more deeply inside the binding pocket of Mpro than the topmost antiviral drug (Saquinavir). Moreover, DSPD-5 also exhibited comparable binding energy to Saquinavir. The analysis of per residue contribution energy and SASA studies indicated that the molecules showed efficient binding by targeting the S1 subsite of the Mpro binding pocket.

Conclusion

The DSPD-2, DSPD-6, and DSPD-5 could be developed as potential inhibitors of SARS-CoV-2. Moreover, we suggest that targeting molecules to bind effectively to the S1 subsite could potentially increase the binding of molecules to the SARS-CoV-2 Mpro.

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A robust computational strategy applied to identify the potential lead for COVID-19.

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Repurposed FDA approved antiviral drugs were compared with a set of acridinedione analogs against Mpro of SARS-CoV-2.

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The acridinedione analogs have acceptable ADMET values and low toxicity profile.

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In-house synthesized acridinedione analogs showed good amount of interaction with Mpro of SARS-CoV-2.