MM-GBSA Analysis Research Articles

Machine learning driven drug repurposing strategy for identification of potential RET inhibitors against non-small cell lung cancer

Non-small cell lung cancer (NSCLC) remains the leading cause of mortality and morbidity worldwide accounting about 85% of total lung cancer cases. The receptor REarranged during Transfection (RET) plays an important role by ligand independent activation of kinase domain resulting in carcinogenesis. Presently, the treatment for RET driven NSCLC is limited to multiple kinase inhibitors. This situation necessitates the discovery of novel and potent RET specific inhibitors. Thus, we employed high throughput screening strategy to repurpose FDA approved compounds from DrugBank comprising of 2509 molecules. It is worth noting that the initial screening is accomplished with the aid of in-house machine learning model built using IC50 values corresponding to 2854 compounds obtained from BindingDB repository. A total of 497 compounds (19%) were predicted as actives by our generated model. Subsequent in silico validation process such as molecular docking, MMGBSA and density function theory analysis resulted in identification of two lead compounds named DB09313 and DB00471. The simulation study highlights the potency of DB00471 (Montelukast) as potential RET inhibitor among the investigated compounds. In the end, the half-minimal inhibitory activity of montelukast was also predicted against RET protein expressing LC-2/ad cell lines demonstrated significant anticancer activity. Collective analysis from our study highlights that montelukast could be a promising candidate for the management of RET specific NSCLC.

Toward the Discovery of SARS-CoV-2 Main Protease Inhibitors: Exploring Therapeutic Potentials of Evodiamine and Its Derivatives, Virtual Screening, Molecular Docking, and Molecular Dynamic Studies

Continuous scientific research is necessary to help in the discovery of new promising remedies for the treatment of COVID-19, caused by the SARS-CoV-2 virus. This current research was aimed at identifying potential novel inhibitors of the SARS-CoV-2 main protease, which represents one of the most important targets in the viral life cycle. Protein data bank file ID: 7JQ2 was used containing the co-crystallized inhibitor MPI5 with the Main protease. A virtual screening process for natural evodiamine compounds was performed through absorption, distribution, metabolism, elimination, and toxicity studies, and the promising hits were docked into the binding site of the enzyme. 13-(4-Chlorobenzoyl)-10-hydroxy-14-methyl-8,13,13 b,14-tetrahydroindolo[2′,3′:3,4]pyrido[2,1- b]-quinazolin-5(7 H)-one (29) interacted favorably with the enzyme; it showed high similarity to MPI5. Molecular dynamic simulations for 29 proved the stability of its binding to SARS-CoV-2 protease over 100 ns; subsequent MMGBSA analysis also supported this principle. Furthermore, 29 elucidated higher limiting action on enzymatic behavior throughout the whole process when compared to MPI5. This provides sufficient evidence for the potential of evodiamine compounds in modern antiviral research, especially compound 29, against the modern COVID-19 pandemic.

Integrativesubtractive proteomics, immunoinformatics, docking, and simulation approaches reveal candidate vaccine against Sin Nombre orthohantavirus

The emergence of Sin Nombre orthohantavirus, an etiological agent of hantavirus cardiopulmonary syndrome, exacerbates the situation and imposes a heavy financial burden on healthcare organizations. Multidrug-resistant forms of the disease are prevalent, and there is currently no licensed commercial vaccine. Due to the numerous limitations of experimental vaccines, vaccines against various bacterial and viral diseases have developed via computational vaccine design. Several subtractive proteomics, immunoinformatics, docking, and simulation approaches were used in this study to develop a multi-epitope-based vaccine against Sin Nombre orthohantavirus. One possible antigenic protein-the glycoprotein precursor of surface glycoproteins (accession number >AAC42202.1)-was selected as a candidate for B cell-derived T cell epitopes mapping the detailed analysis of the core genome. Among the predicted epitopes, four epitopes (QVDWTKKSST, GLAASPPHL, SSYSYRRKLV, and MESGWSDTA), which were probably antigenic, nonallergenic, nontoxic, and water soluble, were used in the multi-epitope vaccine's construction. The shortlisted epitopes have the potency to cover 99.78% of the world's population, 97.93% of the Chinese population, and 97.36% of the Indian population. The epitopes were connected through AAY linkers and joined with >50S ribosomal adjuvant to enhance their efficacy. The vaccine comprises 182 amino acids with a molecular weight of 19.03770 kDa and an instability index of 26.52, indicating that the protein is stable. A molecular docking study revealed that the vaccine has a good binding affinity with TLR-4 and TLR-8, which is vital for inducing the immune system. Top-1 docked complexes of vaccine- TLR-4 and TLR-8 with the lowest binding energy of -12.52 kc/mol and -5.42 kc/mol, respectively, were considered for molecular dynamic simulation analysis. Furthermore, we predicted that the docked complexes are properly stable throughout simulation time in both normal mode and AMBER-based simulation analysis. The MMGBSA analysis calculated -122.17 and -125.4 net binding energies for the TLR-8- and TLR4-vaccine complexes, respectively, while the MMPBSA analysis estimated -115.63 and -118.19 for the TLR-8- and TLR4-vaccine complex, respectively, confirming that the binding stability with receptors is stable, which is important for inducing a strong response. However, the current work is computation-based, so experimental validation is highly recommended.

A New Theobromine-Based EGFRWT and EGFRT790M Inhibitor and Apoptosis Inducer: Design, Semi-Synthesis, Docking, DFT, MD Simulations, and In Vitro Studies

The essential pharmacophoric structural properties were applied to design a new derivative of theobromine as an antiangiogenic EGFR inhibitor. The designed candidate is a (para-nitrophenyl)acetamide derivative of the natural alkaloid, theobromine (T-2-PNPA). The potentialities of T-2-PNPA to inhibit the EGFR protein were studied computationally in an extensive way. Firstly, the molecular docking against EGFRWT and EGFRT790M demonstrated T-2-PNPA’s capabilities of binding with the targeted receptors. Then, the MD experiments (for 100 ns) illustrated through six different studies the changes that occurred in the energy as well as in the structure of EGFR–T-2-PNPA complex. Additionally, an MM-GBSA analysis determined the exact energy of binding and the essential residues. Furthermore, DFT calculations investigated the stability, reactivity, and electrostatic potential of T-2-PNPA. Finally, ADMET and toxicity studies confirmed both the safety as well as the general likeness of T-2-PNPA. Consequently, T-2-PNPA was prepared for the in vitro biological studies. T-2-PNPA inhibited EGFRWT and EGFRT790M with IC50 values of 7.05 and 126.20 nM, respectively, which is comparable with erlotinib activities (5.91 and 202.40, respectively). Interestingly, T-2-PNPA expressed cytotoxic potentialities against A549 and HCT-116 cells with IC50 values of 11.09 and 21.01 µM, respectively, which is again comparable with erlotinib activities (6.73 and 16.35, respectively). T-2-PNPA was much safer against WI-38 (IC50 = 48.06 µM) than erlotinib (IC50 = 31.17 µM). The calculated selectivity indices of T-2-PNPA against A549 and HCT-116 cells were 4.3 and 2.3, respectively. This manuscript presents a new lead anticancer compound (T-2-PNPA) that has been synthesized for the first time and exhibited promising in silico and in vitro anticancer potentialities.

IN SILICO APPROACH TARGETING POLYPHENOL AS FABH INHIBITOR IN BACTERIAL INFECTION

Objective: The aim of the study is to perform a computational study consisting of molecular docking for polyphenols subjected to in silico studies to identify a new lead for antimicrobial activity which has been reported yet or not been used yet. Methods: The Schrödinger Maestro 11.3 performed molecular docking of the enzyme FabH (β-ketoacyl-acyl carrier protein synthase III) (PDB ID: 5BNR) with polyphenol. The targeted compounds were docked against FabH enzyme and also evaluated for MM-GBSA and ADMET analysis. Results: The top hits shows remarkable results and good binding interactions with a pocket of the enzyme. The best binding score are as-8.6 (kcal/mol) of Geniestein,-8.579 (kcal/mol) of 4-naphthoquinone,-7.651(kcal/mol) of Pelargonidin. All the targeted compounds were found in the given limits of ADMET parameters. They also showed good free-binding energy. Conclusion: The computational study reveals that the targeted polyphenols show good binding interactions and are also compatible with ADMET parameters. So, with this, we can conclude that the reported polyphenols can be potent against bacterial infection. In the future, if we derivatized these polyphenols with different substitutions, it can also lead to a potential drug moiety against bacterial infection.

Exploring actinomycetes natural products to identify potential multi-target inhibitors against Leishmania donovani.

Visceral leishmaniasis (VL) is a neglected tropical disease that mainly affects the poor population of the Indian, African, and South American subcontinent. The increasing resistance to antimonial and miltefosine and frequent toxicity of amphotericin B drives an urgent need to develop an anti-leishmanial drug with excellent efficacy and safety profile. In this study, three sequential docking protocols (HTVS, SP, and XP) were performed to screen the secondary metabolites (n = 6519) from the actinomycetes source against five key proteins involved in the metabolic pathway of Leishmania donovani. Those proteins were adenine phosphoribosyltransferase (PDB ID: 1QB7), trypanothione reductase (PDB ID: 2JK6), N-myristoyl transferase (PDB ID: 2WUU), pteridine reductase (PDB ID: 2XOX), and MAP kinase (PDB ID: 4QNY). Although the binding energy of top ligands was predicted using the MM-GBSA module of the Schrödinger suite. SP and XP docking mode resulted in 55 multi-targeted ligands against L donovani. MM-GBSA analysis selected the top 18 ligands with good-binding affinity and the binding-free energy for four proteins, as mentioned earlier, when compared with the miltefosine, paromomycin, and a reference ligand selected for each target. Finally, molecular dynamics simulation, post-MD-binding-free energy (MM-PBSA), and principal component analysis (PCA) proposed three best ligands (Adenosine pentaphosphate, Atetra P, and GDP-4-keto-6-deoxymannose) qualifying the above screening parameters and confirmed as a potential drug candidate to fight against Leishmania donovani parasites.

Novel 3-phenyl-1- (alkylphenyl)-9-oxa-4-azaphenanthren-10-ones as inhibitors of some enzymes: synthesis, characterization, biological evaluation and molecular docking studies

A series of novel 3-phenyl-1-(alkylphenyl)-9-oxa-4-azaphenanthren-10-ones and (E)-1-phenyl-3-(aryl)prop-2-en-1-ones were synthesized and characterized by IR, 1H NMR, 13C spectroscopy and elemental analysis. The synthesized Compounds 5a–f were subjected to molecular docking simulation with three proteins, namely, tyrosyl-tRNA synthetase, heme oxygenase 1 and acetylcholinesterase to evaluate the antibacterial, antioxidant and acetylcholinesterase inhibition, respectively. Moreover, the docked poses of all compounds inside the proteins were subjected to further dynamic simulation through the calculation of the binding free energy using MM-GBSA analysis. Compound 5d exhibits high potential inhibition against antibacterial, antioxidant and acetylcholinesterase activities. Compounds 3d, 3f, 5a and 5d recorded an important scavenging activity in DPPH and ABTS assays. Investigation of the anti-acetylcholinesterase activity of the synthesized compounds showed that Compounds 5a and 3d are the most potent inhibitors against AchE, with percent inhibition values of 38 and 30%, respectively. Communicated by Ramaswamy H. Sarma

QSAR Evaluations to Unravel the Structural Features in Lysine-Specific Histone Demethylase 1A Inhibitors for Novel Anticancer Lead Development Supported by Molecular Docking, MD Simulation and MMGBSA.

Using 84 structurally diverse and experimentally validated LSD1/KDM1A inhibitors, quantitative structure–activity relationship (QSAR) models were built by OECD requirements. In the QSAR analysis, certainly significant and understated pharmacophoric features were identified as critical for LSD1 inhibition, such as a ring Carbon atom with exactly six bonds from a Nitrogen atom, partial charges of lipophilic atoms within eight bonds from a ring Sulphur atom, a non-ring Oxygen atom exactly nine bonds from the amide Nitrogen, etc. The genetic algorithm–multi-linear regression (GA-MLR) and double cross-validation criteria were used to create robust QSAR models with high predictability. In this study, two QSAR models were developed, with fitting parameters like R2 = 0.83–0.81, F = 61.22–67.96, internal validation parameters such as Q2LOO = 0.79–0.77, Q2LMO = 0.78–0.76, CCCcv = 0.89–0.88, and external validation parameters such as, R2ext = 0.82 and CCCex = 0.90. In terms of mechanistic interpretation and statistical analysis, both QSAR models are well-balanced. Furthermore, utilizing the pharmacophoric features revealed by QSAR modelling, molecular docking experiments corroborated with the most active compound’s binding to the LSD1 receptor. The docking results are then refined using Molecular dynamic simulation and MMGBSA analysis. As a consequence, the findings of the study can be used to produce LSD1/KDM1A inhibitors as anticancer leads.

Polyphenolic Phytochemicals Exhibit Promising SARS-COV-2 Papain Like Protease (PLpro) Inhibition Validated through a Computational Approach

In the present study, in silico PLpro inhibitory potential of 28 polyphenolic compounds was validated, which possesses in vivo inhibitory potential against different SARS-CoV-2 replication enzymes. Among 28 polyphenolic compounds amentoflavone, tiliroside, papyriflavanol A and indinavir exhibited good binding affinity of toward PLpro has been considered for further virtual screening processes. Comprehensive analysis indicates that amentoflavone, tiliroside, and papyriflavanol A phenolic compounds demonstrate very high stability and higher inhibiting potential to bind with the Thr158 and Leu162 dyad of PLpro among 28 phenolic compounds. Further ADME and DFT analysis of amentoflavone, and papyrifalvanol A reveal that possess excellent pharmacokinetic and molecular electrostatic potentials. MD simulation and MM-GBSA analysis of amentoflavone, tiliroside, and one anti-viral drug indinavir toward PLpro (PDB ID 6W9C) result revealed that phenolic compounds amentoflavone, tiliroside possess excellent simulation trajectories toward the binding pocket of PLpro essential to inhibit SARS-CoV-2 multiplication. Further MM-GBSA analysis affirm that PLpro-amentoflavone complex exhibit high MMGBSA score of −106.56Kcal/mol. However, further human clinical trials are essential to justify their clinical pertinence.

Tuberculosis and HIV responses threatened by nCOVID-19: A situation prompting an in silico investigation of reported MbtA inhibitors for combined inhibition of SARS-CoV-2 and HIV-TB co-infection

The menace of infectious diseases has constantly been a reason of concern for humankind since time immemorial. As evident by the name, infectious diseases can infect a huge population within a short period, leading to an eruption of pandemics and epidemics. The present human era is fortunate enough to have a wide array of readily available drugs that help cure and prevent various diseases. Moreover, the scientific community has always responded to the needs of society through its drug discovery and development programs. The co-existence of multiple diseases calls forth the scientific community to design and develop drugs that could have a broad spectrum of activity. In this perspective, our goal was to investigate the potential of reported MbtA inhibitors (antitubercular molecules) in inhibiting HIV-1 RT and nCovid-19-RdRp and eventually leading to the identification of a multi-targeted ligand (triple co-infection inhibitor). In this study, the primary success was attained by capitalizing on the structure-based virtual screening drug discovery approach. Results were quite promising. Molecular docking results showed that GV17 interacted strongly with the active site residues of both the target proteins (HIV-1 RT and nCOVID-19-RdRp). Moreover, the docking score of GV17 was more than that of the internal ligands of both the target proteins, which indicates a firm binding. Molecular dynamics further validated these results as identical amino acid residues were observed in the protein’s docked pose with the ligand. The detailed atomic interactions of ligand GV17 with the protein residues have been discussed. Overall, the protein–ligand complexes remained stable throughout the simulation, and the system’s backbone fluctuations were modest. MM-GBSA analysis revealed free binding energy of − 72.30 ± 7.85 kcal/mol and − 65.40 ± 7.25 kcal/mol for 1RT2 and 7BV2, respectively. The more negative binding energy indicates a stronger affinity of GV17 with both the receptors. GV17 also gave satisfactory predictive in silico ADMET results. Overall, this computational study identified GV17 as a potential HIT molecule and findings can open up a new avenue to explore and develop inhibitors against nCOVID-19-HIV-TB triple-infections.

Deciphering the dynamics of cathepsin D as a potential drug target to enhance anticancer drug-induced apoptosis

The cathepsin D is a pepsin-family aspartic protease enzyme that is ubiquitous and is known for its vital role in tumor progression and metastasis. This study considered its therapeutic potential and aimed to employ a comprehensive computational approach to identify and understand possible inhibition mechanisms of drug molecules from the asinex database, comprehensive marine natural products database, and medicinal plant databases. By virtual screening of the said databases, three-hit molecules: hit-1 (2-(1-(4-fluoro-3-methylbenzoyl)pyrrolidin-3-yl)-4-hydroxy-6-(2-hydroxypyridin-1-ium-3-yl)pyrimidine-1,3-diium), hit-2 (4-(3-(3-(4-fluorophenyl)-1,7-dihydroimidazo[1,2-a]pyrimidin-8-ium-5-yl)-1H-pyrrol-1-yl)-2-methylpyrimidine-1,3-diium), and hit-3 (5-(1-(2-cyclopentylacetyl)pyrrolidin-2-yl)-3-(4-fluorophenyl)-1,7-dihydroimidazo[1,2-a]pyrimidin-8-ium) were identified against the cathepsin D enzyme. The compounds unveiled stable conformational dynamics and formed several key short-distance hydrophilic and hydrophobic interactions. It was found that hit-1, hit-2, and hit-3 molecules have a binding affinity of <−10 kcal/mol for the cathepsin D enzyme. Molecular dynamics simulation analysis examined the systems as significantly stable in terms of binding mode and chemical interactions. The system’s root mean square deviation (RMSD) in simulated time is <3 Å, which validates the docking and simulation data, binding free energies analysis including MM-GBSA, MM-PBSA, and WaterSwap analysis. The MM-GBSA analysis estimated −73.86, −75.8, and −87.02 net binding energies, while the MM-PBSA analysis estimated −70.58, −78.15, and −82.35 net free binding energies for Hit 1, Hit 2, and Hit 3, respectively. The binding interaction pointed towards stable interactions energy of compounds with cathepsin D, while the WaterSWAP analysis for the Hit-1 system, the Bennetts, FEP, and TI energy value is −36 kcal/mol, −37 kcal/mol, and −36 kcal/mol, respectively. The Hit-2 system has a binding energy of −39 kcal/mol (Bennetts), −39 kcal/mol (FEP), and −38 kcal/mol (TI). The Hit-3 complex was revealed to be more stable even than the control. The binding energy value of Bennetts, FEP, and TI is −42 kcal/mol, −41 kcal/mol, and −42 kcal/mol, respectively. Several hotspot residues were also highlighted in intermolecular interactions, and those, when mutated, impacted the overall binding energy of complexes. Lastly, the compounds were revealed to show favorable ADMET properties and thus could be regarded as promising leads for future experimental validation.

Design of a Multi-Epitopes Based Chimeric Vaccine against Enterobacter cloacae Using Pan-Genome and Reverse Vaccinology Approaches.

Enterobacter cloacae (EC) is a significant emerging pathogen that is occasionally associated with lung infection, surgical site infection, urinary infection, sepsis, and outbreaks in neonatal intensive care units. In light of the fact that there is currently no approved vaccine or therapeutic option for the treatment of EC, the current study was developed to concentrate on applications based on modern computational approaches to design a multi-epitope-based E. cloacae peptide vaccine (MEBEPV) expressing the antigenic determinants prioritized from the EC genome. Integrated computational analyses identified two potential protein targets (phosphoporin protein-PhoE and putative outer-membrane porin protein) for further exploration on the basis of pangenome subtractive proteomics and immunoinformatic in-depth examination of the core proteomes. Then, a multi-epitope peptide vaccine was designed, which comprised shortlisted epitopes that were capable of eliciting both innate and adaptive immunity, as well as the cholera toxin’s B-subunit, which was used as an adjuvant in the vaccine formulation. To ensure maximum expression, the vaccine’s 3D structure was developed and the loop was refined, improving the stability by disulfide engineering, and the physicochemical characteristics of the recombinant vaccine sequence were found to be ideal for both in vitro and in vivo experimentation. Blind docking was then used for the prediction of the MEBEPV predominant blinding mode with MHCI, MHCII, and TLR3 innate immune receptors, with lowest global energy of −18.64 kJ/mol, −48.25 kJ/mol, and −5.20 kJ/mol for MHC-I, MHC-II, and TLR-4, respectively, with docked complexes considered for simulation. In MD and MMGBSA investigations, the docked models of MEBEPV-TLR3, MEBEPV-MHCI, and MEBEPV-MHCII were found to be stable during the course of the simulation. MM-GBSA analysis calculated −122.17 total net binding free energies for the TLR3-vaccine complex, −125.4 for the MHC I-vaccine complex, and −187.94 for the MHC II-vaccine complex. Next, MM-PBSA analysis calculated −115.63 binding free energy for the TLR3-vaccine complex, −118.19 for the MHC I-vaccine complex, and −184.61 for the MHC II-vaccine complex. When the vaccine was tested in silico, researchers discovered that it was capable of inducing both types of immune responses (cell mediated and humoral) at the same time. Even though the suggested MEBEPV has the potential to be a powerful contender against E. cloacae-associated illnesses, further testing in the laboratory will be required before it can be declared safe and immunogenic.

Toward the Discovery of a Novel Class of Leads for High Altitude Disorders by Virtual Screening and Molecular Dynamics Approaches Targeting Carbonic Anhydrase.

For decades, carbonic anhydrase (CA) inhibitors, most notably the acetazolamide-bearing 1,3,4-thiadiazole moiety, have been exploited at high altitudes to alleviate acute mountain sickness, a syndrome of symptomatic sensitivity to the altitude characterized by nausea, lethargy, headache, anorexia, and inadequate sleep. Therefore, inhibition of CA may be a promising therapeutic strategy for high-altitude disorders. In this study, co-crystallized inhibitors with 1,3,4-thiadiazole, 1,3-benzothiazole, and 1,2,5-oxadiazole scaffolds were employed for pharmacophore-based virtual screening of the ZINC database, followed by molecular docking and molecular dynamics simulation studies against CA to find possible ligands that may emerge as promising inhibitors. Compared to the co-crystal ligands of PDB-1YDB, 6BCC, and 6IC2, ZINC12336992, ZINC24751284, and ZINC58324738 had the highest docking scores of −9.0, −9.0, and −8.9 kcal/mol, respectively. A molecular dynamics (MD) simulation analysis of 100 ns was conducted to verify the interactions of the top-scoring molecules with CA. The system’s backbone revealed minor fluctuations, indicating that the CA–ligand complex was stable during the simulation period. Simulated trajectories were used for the MM-GBSA analysis, showing free binding energies of −16.00 ± 0.19, −21.04 ± 0.17, and −19.70 ± 0.18 kcal/mol, respectively. In addition, study of the frontier molecular orbitals of these compounds by DFT-based optimization at the level of B3LYP and the 6-311G(d,p) basis set showed negative values of the HOMO and LUMO, indicating that the ligands are energetically stable, which is essential for forming a stable ligand–protein complex. These molecules may prove to be a promising therapy for high-altitude disorders, necessitating further investigations.

Computational Studies of Budesonide vs. Vilanterol: Asthma Drugs Against SARS-CoV-2 Mpro

Abstract: The global spread of SARS-CoV-2 and the mortality it has caused have prompted the research organization to develop novel medications to combat COVID-19 infection. The main protease (Mpro) of SARS-CoV-2 is crucial to the virus's replication and propagation in host cells. Therefore it is a promising therapeutic target. There are officially no certified specific drugs or available interventions for COVID-19 infection. Repurposing standard pharmaceutical drugs for COVID-19 interventions is a promising way of identifying potent therapeutic candidates quickly. In this work, Vilanterol over Budesonide was studied using Molecular docking, ADMET, and MMGBSA analysis using Schrodinger Software to find more potent drugs that can diminish the risk of rigorous SARS-CoV-2 infection and shorten the time to recovery. We have identified that Vilanterol showed a more promising inhibitor of COVID-19 Mpro than Budesonide (studied by the University of Oxford). Vilanterol has indicated docking score (-8.727), Human oral absorption (88.786%), and also the free binding energy (-60.457) than Budesonide presented docking score (-6.077), Human oral absorption (83.863), and the free binding energy (-36.078). In conclusion, our computational strategy identified promising and efficacious SARS-CoV-2 inhibitors, Vilanterol over Budesonide, that could be investigated further in clinical trials.

Identification of novel efflux pump inhibitors for Neisseria gonorrhoeae via multiple ligand-based pharmacophores, e-pharmacophore, molecular docking, density functional theory, and molecular dynamics approaches

Neisseria gonorrhoeae have progressively developed resistance to almost all antibiotics, and it has become imperative to develop novel approaches to combat its multi-drug resistance. Overexpression of the MtrCDE, an RND family efflux pump, is one of the primary causes of antibiotic resistance in the gonococcus and is considered an important target for combating anti-microbial resistance. PaβN, D13–9001, and other EPIs are identified to target the RND efflux pumps, but due to their cytotoxicity, they have failed in clinical trials. Herein, an extensive pharmacophore-based approach was performed to identify novel EPI inhibitors with improved pharmacology/safety profiles. An integrated computational framework comprising pharmacophore generation, virtual screening using HTVS, SP and XP Glide methodology, MM-GBSA analysis, Induced fit docking, QPLD, DFT, ADMET properties calculation, Molecular Dynamics, and MM-PBSA analysis was performed. The comprehensive study leads to the identification of five non-toxic bioactive compounds, namely - ZINC000008764610, ZINC000030879142, ZINC000030879358, ZINC000253414904, and ZINC000225394671, as potential EPIs for RND efflux pump of Neisseria gonorrhoeae. The five compounds were selected based on the pharmacophore mapping, higher dock score than the known EPIs, binding stability, molecular interactions with the critical residues of MtrD protein, higher ADMET properties, non-toxicity, and free energy estimations. In summary, the analysis led to the identification of five top hits from the natural compound subset of the ZINC database that has a higher binding affinity to the MtrD and adequate physiochemical/pharmacokinetic profile that can be used for the generation of novel EPIs against Neisseria gonorrhoeae.

Designing Novel Compounds for the Treatment and Management of RET-Positive Non-Small Cell Lung Cancer-Fragment Based Drug Design Strategy.

Rearranged during transfection (RET) is an oncogenic driver receptor that is overexpressed in several cancer types, including non-small cell lung cancer. To date, only multiple kinase inhibitors are widely used to treat RET-positive cancer patients. These inhibitors exhibit high toxicity, less efficacy, and specificity against RET. The development of drug-resistant mutations in RET protein further deteriorates this situation. Hence, in the present study, we aimed to design novel drug-like compounds using a fragment-based drug designing strategy to overcome these issues. About 18 known inhibitors from diverse chemical classes were fragmented and bred to form novel compounds against RET proteins. The inhibitory activity of the resultant 115 hybrid molecules was evaluated using molecular docking and RF-Score analysis. The binding free energy and chemical reactivity of the compounds were computed using MM-GBSA and density functional theory analysis, respectively. The results from our study revealed that the developed hybrid molecules except for LF21 and LF27 showed higher reactivity and stability than Pralsetinib. Ultimately, the process resulted in three hybrid molecules namely LF1, LF2, and LF88 having potent inhibitory activity against RET proteins. The scrutinized molecules were then subjected to molecular dynamics simulation for 200 ns and MM-PBSA analysis to eliminate a false positive design. The results from our analysis hypothesized that the designed compounds exhibited significant inhibitory activity against multiple RET variants. Thus, these could be considered as potential leads for further experimental studies.

Whole genome analysis and homology modeling of SARS-CoV-2 Indian isolate reveals potent FDA approved drug choice for treating COVID-19

Coronaviruses have caused enough devastation in the last two decades. These viruses have some rare features while sharing some common features. Novel coronavirus disease (nCoV-19) caused an outbreak with a fatality rate of 5%. It emerged from China and spread into many countries. The present research focused on genome analysis of Indian nCoV-19 Isolate and its translational product subjected to homology modeling and its subsequent molecular simulations to find out potent FDA approved drug for treating COVID-19. Phylogenetic analysis of SARS-CoV-2 Indian isolate shows close resemblance with 17 countries SARS-CoV-2 isolates. Homology modeling of four non-structural proteins translational product of Indian SARS-CoV-2 genome shows high similarity and allowed regions with the existing PDB deposited SARS-CoV-2 target proteins. Finally, these four generated proteins show more affinity with cobicistat, remdesivir and indinavir out of 14 screened FDA approved drugs in molecular docking which is further proven by molecular dynamics simulation and MMGBSA analysis of target ligand complex with best simulation trajectories. Overall our present research findings is that three proposed drugs namely cobicistat, remdesivir and indinavir showed higher interaction with the model SARS-CoV-2 viral target proteins from the Indian nCoV-19 isolate. These compounds could be used as a starting point for the creation of active antiviral drugs to combat the deadly COVID-19 virus during global pandemic and its subsequent viral infection waves across the globe. Communicated by Ramaswamy H. Sarma

Search for potentially biased epidermal growth factor receptor (EGFR) inhibitors through pharmacophore modelling, molecular docking, and molecular dynamics (MD) simulation approaches

Epidermal growth factor receptor (EGFR), being one of the most crucial receptor in cancer therapy, has been selected as a potential target for the present study. Ligand-based pharmacophore model (n = 30, R 2=0.93 with root mean square deviation = 1.14, ΔCost = 144.27 and configuration cost = 21) was developed and validated with Fischer’s randomisation (at 95% confidence), test set (n = 225, R 2 pred = 0.81), external data set (n = 13, R 2 pred = 0.95) and decoy set (n = 70), further the model has been used to search for novel EGFR inhibitors. The validated model was used for virtual screening of zinc database. A pool of 115,948 candidate molecules was screened through the model. Subsequently, molecules having predicted IC50<0.2 µM were selected for screening through drug-like properties filter. Based on pharmacokinetic profile (ADMET study), Lipinski’s rule of five and Veber’s rule, 62 molecules were shortlisted for molecular docking. Using consensus docking, five hit molecules were selected, which were further considered for molecular dynamics simulation. Additionally MM-GBSA analysis was carried which showed that affinity of hits towards the receptor of three compound mainly ZINC305, ZINC131796 and ZINC131785 were similar to the standard vanedtinib. The simulation, performed for 100 ns, revealed that two hit molecules, namely ZINC305 and ZINC131785, showing potential interactions at the ligand-binding domain of EGFR protein with good ligand–protein stability. Communicated by Ramaswamy H. Sarma

Designing of a multi-epitopes-based peptide vaccine against rift valley fever virus and its validation through integrated computational approaches

Since its discovery, the Rift Valley Fever virus (RVFV) has been the source of numerous outbreaks in the Arab Peninsulas and Africa, wreaking havoc on humans and animals. The lack of therapeutics or licensed human vaccines limits the options for controlling RVFV outbreaks. Therefore, RVFV has been prioritized for rapid research and innovation of prevention strategies to control and prevent its outbreaks. The purpose of this study was to design a multi-epitope-based peptide vaccine (MEBPV) against RVFV. Bioinformatics approaches were used to design a potent MEBPV that can potentially activate both CD8+ and CD4+ T-cell immune responses, and several computational tools were employed to investigate its biological activities. Three antigenic proteins (Nucleocapsid (N), Glycoprotein C (GC), and Glycoprotein N (GN)) from the RVFV were chosen and potential immunogenic T- and B -cell epitopes were predicted from them. Based on in silico analysis, a MEBPV based on highly scored T and B-cell epitopes (6 CTL, 5 HTL, and 4 LBL) combined with linkers and adjuvants was developed. The finest predicted model was used for docking studies with Toll-like receptors (TLR3 and TLR8) and MHC molecules (MHC I and MHC II) after predicting and analyzing the tertiary structure of MEBPV. The designed MEBPV was then tested for stability with TLR3 and TLR8 receptors using molecular dynamics (MD) simulation and MMGBSA analysis. The MEBPV –TLR3, MEBPV –TLR8, MEBPV–MHC I and MEBPV –MHC II docked models were found stable during simulation time in MD and MMGBSA studies. In silico analysis revealed that the constructed vaccine could elicit both cell-mediated and humoral immune responses simultaneously. The proposed MEBPV could be a strong candidate against RVFV, but it will need to be tested in the laboratory to guarantee its safety and immunogenicity.

Suramin, penciclovir, and anidulafungin exhibit potential in the treatment of COVID-19 via binding to nsp12 of SARS-CoV-2

COVID-19, for which no confirmed therapeutic agents are available, has claimed over 48,14,000 lives globally. A feasible and quicker method to resolve this problem may be ‘drug repositioning’. We investigated selected FDA and WHO-EML approved drugs based on their previously promising potential as antivirals, antibacterials or antifungals. These drugs were docked onto the nsp12 protein, which reigns the RNA-dependent RNA polymerase activity of SARS-CoV-2, a key therapeutic target for coronaviruses. Docked complexes were reevaluated using MM-GBSA analysis and the top three inhibitor-protein complexes were subjected to 100 ns long molecular dynamics simulation followed by another round of MM-GBSA analysis. The RMSF plots, binding energies and the mode of physicochemical interaction of the active site of the protein with the drugs were evaluated. Suramin, Penciclovir, and Anidulafungin were found to bind to nsp12 with similar binding energies as that of Remdesivir, which has been used as a therapy for COVID-19. In addition, recent experimental evidences indicate that these drugs exhibit antiviral efficacy against SARS-CoV-2. Such evidence, along with the significant and varied physical interactions of these drugs with the key viral enzyme outlined in this investigation, indicates that they might have a prospective therapeutic potential in the treatment of COVID-19 as monotherapy or combination therapy with Remdesivir.