Investigation of the MDM2-binding potential of de novo designed peptides using enhanced sampling simulations.

The tumor suppressor p53 plays a crucial role in cellular responses to various stresses, regulating key processes such as apoptosis, senescence, and DNA repair. Dysfunctional p53, prevalent in approximately 50 % of human cancers, contributes to tumor development and resistance to treatment. This study employed deep learning-based protein design and structure prediction methods to identify novel high-affinity peptide binders (Pep1 and Pep2) targeting MDM2, with the aim of disrupting its interaction with p53. Extensive all-atom molecular dynamics simulations highlighted the stability of the designed peptide in complex with the target, supported by several structural analyses, including RMSD, RMSF, Rg, SASA, PCA, and free energy landscapes. Using the steered molecular dynamics and umbrella sampling simulations, we elucidate the dissociation dynamics of p53, Pep1, and Pep2 from MDM2. Notable differences in interaction profiles were observed, emphasizing the distinct dissociation patterns of each peptide. In conclusion, the results of our umbrella sampling simulations suggest Pep1 as a higher-affinity MDM2 binder compared to p53 and Pep2, positioning it as a potential inhibitor of the MDM2-p53 interaction. Using state-of-the-art protein design tools and advanced MD simulations, this study provides a comprehensive framework for rational in silico design of peptide binders with therapeutic implications in disrupting MDM2-p53 interactions for anticancer interventions.

CHAPERONg: A tool for automated GROMACS-based molecular dynamics simulations and trajectory analyses.

Molecular dynamics (MD) simulation is a powerful computational tool used in biomolecular studies to investigate the dynamics, energetics, and interactions of a wide range of biological systems at the atomic level. GROMACS is a widely used free and open-source biomolecular MD simulation software recognized for its efficiency, accuracy, and extensive range of simulation options. However, the complexity of setting up, running, and analyzing MD simulations for diverse systems often poses a significant challenge, requiring considerable time, effort, and expertise. Here, we introduce CHAPERONg, a tool that automates the GROMACS MD simulation pipelines for protein and protein-ligand systems. CHAPERONg also integrates seamlessly with GROMACS modules and third-party tools to provide comprehensive analyses of MD simulation trajectories, offering up to 20 post-simulation processing and trajectory analyses. It also streamlines and automates established pipelines for conducting and analyzing biased MD simulations via the steered MD-umbrella sampling workflow. Thus, CHAPERONg makes MD simulations more accessible to beginner GROMACS users whilst empowering experts to focus on data interpretation and other less programmable aspects of MD simulation workflows. CHAPERONg is written in Bash and Python, and the source code is freely available at https://github.com/abeebyekeen/CHAPERONg. Detailed documentation and tutorials are available online at dedicated web pages accessible via https://abeebyekeen.com/chaperong-online.

CSC01 shows promise as a potential inhibitor of the oncogenic G13D mutant of KRAS: an in silico approach.

About 30% of malignant tumors include KRAS mutations, which are frequently required for the development and maintenance of malignancies. KRAS is now a top-priority cancer target as a result. After years of research, it is now understood that the oncogenic KRAS-G12C can be targeted. However, many other forms, such as the G13D mutant, are yet to be addressed. Here, we used a receptor-based pharmacophore modeling technique to generate potential inhibitors of the KRAS-G13D oncogenic mutant. Using a comprehensive virtual screening workflow model, top hits were selected, out of which CSC01 was identified as a promising inhibitor of the oncogenic KRAS mutant (G13D). The stability of CSC01 upon binding the switch II pocket was evaluated through an exhaustive molecular dynamics simulation study. The several post-simulation analyses conducted suggest that CSC01 formed a stable complex with KRAS-G13D. CSC01, through a dynamic protein-ligand interaction profiling analysis, was also shown to maintain strong interactions with the mutated aspartic acid residue throughout the simulation. Although binding free energy analysis through the umbrella sampling approach suggested that the affinity of CSC01 with the switch II pocket of KRAS-G13D is moderate, our DFT analysis showed that the stable interaction of the compound might be facilitated by the existence of favorable molecular electrostatic potentials. Furthermore, based on ADMET predictions, CSC01 demonstrated a satisfactory drug likeness and toxicity profile, making it an exemplary candidate for consideration as a potential KRAS-G13D inhibitor.

ZBTB7A regulates primed-to-naïve transition of pluripotent stem cells via recognition of the PNT-associated sequence by zinc fingers 1-2 and recognition of γ-globin -200 gene element by zinc fingers 1-4.

ZBTB7A, a transcription factor containing a tandem array of four Cys2-His2 zinc fingers (ZFs), is vital for multiple physiological events through directional binding to different genomic loci. Our previously determined crystal structure of ZBTB7A in complex with a GCCCCTTCCCC sequence revealed that all four ZFs (ZF1-4) are involved in binding to γ-globin -200 gene element to repress fetal haemoglobin expression. Recently, it has been reported that ZBTB7A drives primed-to-naïve transition (PNT) of pluripotent stem cells through binding to a 12-bp consensus sequence ([AAGGACCCAGAT], referred to as PNT-associated sequence). Here, we report a crystal structure of ZBTB7A ZF1-3 in complex with the PNT-associated sequence. The structure shows that ZF1 and ZF2 primarily contribute to recognizing the GACCC core sequence mimicking the half part (GCCCC) of γ-globin -200 gene element via specific hydrogen bonding and van der Waals contacts. The mutations of key residues in ZF1-2 remarkably reduce their binding affinities for the PNT-associated sequence in vitro and cannot restore epiblast stem cells to the naïve pluripotent state in vivo. Collectively, our studies demonstrate that ZBTB7A mainly employs its ZF1-2 to recognize the PNT-associated sequence but recognizes γ-globin -200 gene element via ZF1-4, providing insights into the molecular mechanism for the diversity of ZBTB7A's genomic localization.

Identification of a Potential mRNA-based Vaccine Candidate against the SARS-CoV-2 Spike Glycoprotein: A Reverse Vaccinology Approach.

The emergence of the novel coronavirus (SARS-CoV-2) in December 2019 has generated a devastating global consequence which makes the development of a rapidly deployable, effective and safe vaccine candidate an imminent global health priority. The design of most vaccine candidates has been directed at the induction of antibody responses against the trimeric spike glycoprotein of SARS-CoV-2, a class I fusion protein that aids ACE2 (angiotensin-converting enzyme 2) receptor binding. A variety of formulations and vaccinology approaches are being pursued for targeting the spike glycoprotein, including simian and human replication-defective adenoviral vaccines, subunit protein vaccines, nucleic acid vaccines and whole-inactivated SARS-CoV-2. Here, we directed a reverse vaccinology approach towards the design of a nucleic acid (mRNA-based) vaccine candidate. The "YLQPRTFLL" peptide sequence (position 269-277) which was predicted to be a B cell epitope and likewise a strong binder of the HLA*A-0201 was selected for the design of the vaccine candidate, having satisfied series of antigenicity assessments. Through the codon optimization protocol, the nucleotide sequence for the vaccine candidate design was generated and targeted at the human toll-like receptor 7 (TLR7). Bioinformatics analyses showed that the sequence "UACCUGCAGCCGCGUACCUUCCUGCUG" exhibited a strong affinity and likewise was bound to a stable cavity in the TLR7 pocket. This study is therefore expected to contribute to the research efforts directed at securing definitive preventive measures against the SARS-CoV-2 infection.

Dietary polyphenols mitigate SARS-CoV-2 main protease (Mpro)-Molecular dynamics, molecular mechanics, and density functional theory investigations.

The recent evolution of the SARS-like Coronavirus has ravaged the world. The deadly virus has claimed over millions of lives across the world and hence highlights the need to develop effective therapeutic drugs to contain the disease posed by this parasite. In this study, the inhibitory potential of fifty (50) dietary polyphenols against Coronavirus (SARS-CoV-2) main protease (Mpro) was conducted using the Autodock Vina Molecular docking tool. In the virtual screening process, the binding affinity of Remdesivir (-7.7 kcal/mol) currently used to treat COVID-19 patients was set as the cut-off value to screen out less probable inhibitors. Ellagic acid, Kievitone, and Punicalin were the only promising ligands with binding affinities (-8.9 kcal/mol, -8.0 kcal/mol and -7.9 kcal/mol respectively) lower than the set cut-off value. Furthermore, we validated Ellagic acid and Kievitone efficacy by subjecting them to molecular dynamics simulation and further stability was assessed at the molecular mechanics and quantum levels. The overall analysis indicates both compounds demonstrate higher stability and inhibitory potential to bind to the crucial His41 and Cys145 catalytic dyad of Mpro than the standard drug. However, further analysis of punicalin after evaluating its docking score was not conducted as the ligand pharmacokinetics properties suggests it could pose serious adverse effect to the health of participants in clinical trials. Hence, we employed a more safe approach by filtering out the compound during this study. Conclusively, while Ellagic acid and kievitone polyphenolic compounds have been demonstrated to be promising under this in silico research, further studies are needed to substantiate their clinical relevance.

Exploring the inhibitory potentials of Momordica charantia bioactive compounds against Keap1-Kelch protein using computational approaches.

The search for Keap1 inhibitors as potential Nrf2 activator is a way of increasing the antioxidant status of the human cellular environ. In this research, we used in silico methods to investigate Keap1-kelch inhibitory potential of Momordica charantia's bioactive compounds in order to predict their Nrf2 activating potential. ADMET profiling, physicochemical properties, molecular docking, molecular dynamics, and Molecular Mechanics-Poisson Boltzmann Surface Area (g_MMPBSA) free energy calculation studies were executed to drive home our aim. Out of all the bioactive compounds of Momordica charantia, catechin (CAT) and chlorogenic acid (CGA) were selected based on their ADMET profile, physicochemical properties, and molecular docking analysis. Molecular docking studies of CAT and CGA to Keap1 kelch domain showed that they have - 9.2 kJ/mol and - 9.1 kJ/mol binding energies respectively with CAT having four hydrogen bond interactions with Keap1 while CGA had three. Analysis after the 30 ns molecular dynamics simulation revealed that CAT and CGA were both stable, although with minimal conformational alterations at the kelch pocket of Keap1. Finally, MMPBSA calculation of the Gibbs free energy of each amino acid interaction with CAT and CGA revealed that CAT had a higher total binding energy than CGA. Therefore, the Keap1 inhibitory capacities and the molecular dynamic characters of CAT and CGA at the Kelch domain of Keap1 suggest a putative Nrf2 signaling activating prowess. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40203-021-00100-2.

Molecular dynamics, quantum mechanics and docking studies of some Keap1 inhibitors - An insight into the atomistic mechanisms of their antioxidant potential.

Inhibitors of Keap1 would disrupt the covalent interaction between Keap1 and Nrf2 to unleash Nrf2 transcriptional machinery that orchestrates its cellular antioxidant, cytoprotective and detoxification processes thereby, protecting the cells against oxidative stress mediated diseases. In this in silico research, we investigated the Keap1 inhibiting potential of fifty (50) antioxidants using pharmacokinetic ADMET profiling, bioactivity assessment, physicochemical studies, molecular docking investigation, molecular dynamics and Quantum mechanical-based Density Functional Theory (DFT) studies using Keap1 as the apoprotein control. Out of these 50 antioxidants, Maslinic acid (MASA), 18-alpha-glycyrrhetinic acid (18-AGA) and resveratrol stand out by passing the RO5 (Lipinski rule of 5) for the physicochemical properties and ADMET studies. These three compounds also show high binding affinity of -10.6 kJ/mol, -10.4 kJ/mol and -7.8 kJ/mol at the kelch pocket of Keap1 respectively. Analysis of the 20ns trajectories using RMSD, RMSF, ROG and h-bond parameters revealed the stability of these compounds after comparing them with Keap1 apoprotein. Furthermore, the electron donating and accepting potentials of these compounds was used to investigate their reactivity using Density Functional Theory (HOMO and LUMO) and it was revealed that resveratrol had the highest stability based on its low energy gap. Our results predict that the three compounds are potential drug candidates with domiciled therapeutic functions against oxidative stress-mediated diseases. However, resveratrol stands out as the compound with the best stability and therefore, could be the best candidate with the best therapeutic efficacy.

Computer-aided screening for potential TMPRSS2 inhibitors: a combination of pharmacophore modeling, molecular docking and molecular dynamics simulation approaches.

Transmembrane serine protease 2 (TMPRSS2) has been established as one of the host proteins that facilitate entry of coronaviruses into host cells. One of the approaches often employed towards preventing the entry and proliferation of viruses is computer-aided inhibition studies to identify potent compounds that can inhibit activity of viral targets in the host through binding at the active site. In this study, we developed a pharmacophore model of reportedly potent drugs against severe acute respiratory syndrome coronaviruses 1 and 2 (SARS-CoV-1 and -2). The model was used to screen the ZINC database for commercially available compounds having similar features with the experimentally tested drugs. The top 3000 compounds retrieved were docked into the active sites of a homology-modelled TMPRSS2. Docking scores of the top binders were validated and the top-ranked compounds were subjected to ADME, Lipinski's and medicinal Chemistry property predictions for druglikeness analyses. Two lead compounds, ZINC64606047 and ZINC05296775, were identified having binding affinities higher than those of the reference inhibitors, favorable interactions with TMPRSS2 active site residues and good ADME and medicinal chemistry properties. Molecular dynamics simulation was used to assess the stability and dynamics of the interactions of these compounds with TMPRSS2. Binding free energy and contribution energy evaluations were determined using MMPBSA method. Analyses of the trajectory dynamics collectively established further that the lead compounds bound and interacted stably with active site residues of TMPRSS2. Nonetheless, experimental studies are needed to further assess the potentials of these compounds as possible therapeutics against coronaviruses.Communicated by Ramaswamy H. Sarma.