Predicted Hotspot Residues Involved in Allosteric Signal Transmission in Pro-Apoptotic Peptide-Mcl1 Complexes

Mcl1 is a primary member of the Bcl-2 family-anti-apoptotic proteins (AAP)-that is overexpressed in several cancer pathologies. The apoptotic regulation is mediated through the binding of pro-apoptotic peptides (PAPs) (e.g., Bak and Bid) at the canonical hydrophobic binding groove (CBG) of Mcl1. Although all PAPs form amphipathic alpha-helices, their amino acid sequences vary to different degree. This sequence variation exhibits a central role in the binding partner selectivity towards different AAPs. Thus, constructing a novel peptide or small organic molecule with the ability to mimic the natural regulatory process of PAP is essential to inhibit various AAPs. Previously reported experimental binding free energies (BFEs) were utilized in the current investigation aimed to understand the mechanistic basis of different PAPs targeted to mMcl1. Molecular dynamics (MD) simulations used to estimate BFEs between mMcl1-PAP complexes using Molecular Mechanics-Generalized Born Solvent Accessible (MMGBSA) approach with multiple parameters. Predicted BFE values showed an excellent agreement with the experiment (R-2= 0.92). The van-der Waals (Delta G(vdw)) and electrostatic (Delta G(ele)) energy terms found to be the main energy components that drive heterodimerization of mMcl1-PAP complexes. Finally, the dynamic network analysis predicted the allosteric signal transmission pathway involves more favorable energy contributing residues. In total, the results obtained from the current investigation may provide valuable insights for the synthesis of a novel peptide or small organic inhibitor targeting Mcl1

Evaluation of tools for identifying large copy number variations from ultra-low-coverage whole-genome sequencing data

BackgroundDetection of copy number variations (CNVs) from high-throughput next-generation whole-genome sequencing (WGS) data has become a widely used research method during the recent years. However, only a little is known about the applicability of the developed algorithms to ultra-low-coverage (0.0005–0.8×) data that is used in various research and clinical applications, such as digital karyotyping and single-cell CNV detection.ResultHere, the performance of six popular read-depth based CNV detection algorithms (BIC-seq2, Canvas, CNVnator, FREEC, HMMcopy, and QDNAseq) was studied using ultra-low-coverage WGS data. Real-world array- and karyotyping kit-based validation were used as a benchmark in the evaluation. Additionally, ultra-low-coverage WGS data was simulated to investigate the ability of the algorithms to identify CNVs in the sex chromosomes and the theoretical minimum coverage at which these tools can accurately function. Our results suggest that while all the methods were able to detect large CNVs, many methods were susceptible to producing false positives when smaller CNVs (< 2 Mbp) were detected. There was also significant variability in their ability to identify CNVs in the sex chromosomes. Overall, BIC-seq2 was found to be the best method in terms of statistical performance. However, its significant drawback was by far the slowest runtime among the methods (> 3 h) compared with FREEC (~ 3 min), which we considered the second-best method.ConclusionsOur comparative analysis demonstrates that CNV detection from ultra-low-coverage WGS data can be a highly accurate method for the detection of large copy number variations when their length is in millions of base pairs. These findings facilitate applications that utilize ultra-low-coverage CNV detection.</div

Deciphering the crucial residues involved in heterodimerization of Bak peptide and anti-apoptotic proteins for apoptosis

<p>B-cell lymphoma 2 (Bcl-2) family proteins are the central regulators of apoptosis, functioning via mitochondrial outer membrane permeabilization. The family members are involved in several stages of apoptosis regulation. The overexpression of the anti-apoptotic proteins leads to several cancer pathological conditions. This overexpression is modulated or inhibited by heterodimerization of pro-apoptotic BH3 domain or BH3-only peptides to the hydrophobic groove present at the surface of anti-apoptotic proteins. Additionally, the heterodimerization displayed differences in binding affinity profile among the pro-apoptotic peptides binding to anti-apoptotic proteins. In light of discovering the novel peptide/drug molecules that contain the potential to inhibit specific anti-apoptotic protein, it is necessary to understand the molecular basis of recognition between the protein and its binding partner (peptide or ligand) along with its binding energies. Therefore, the present work focused on deciphering the molecular basis of recognition between pro-apoptotic Bak peptide binding to different anti-apoptotic (Bcl-xL, Bfl-1, Bcl-W, Mcl-1, and Bcl-2) proteins using advanced Molecular Dynamics (MD) approach such as Molecular Mechanics-Generalized Born Solvent Accessible. The results from our investigation revealed that the predicted binding free energies showed excellent correlation with the experimental values (<i>r</i>² = .95). The electrostatic (Δ<i>G</i>_ele) contributions are the major component that drives the interaction between Bak peptides and different anti-apoptotic peptides. Additionally, van der Waals (Δ<i>G</i>_vdw) energies also play an indispensible role in determining the binding free energy. Furthermore, the decomposition analysis highlighted the comprehensive information about the energy contributions of hotspot residues involved in stabilizing the interaction between Bak peptide and different anti-apoptotic proteins.</p

Investigating the Molecular Basis of <i>N</i>-Substituted 1-Hydroxy-4-Sulfamoyl-2-Naphthoate Compounds Binding to Mcl1

Myeloid cell leukemia-1 (Mcl1) is an anti&#8211;apoptotic protein that has gained considerable attention due to its overexpression activity prevents cell death. Therefore, a potential inhibitor that specifically targets Mcl1 with higher binding affinity is necessary. Recently, a series of N-substituted 1-hydroxy-4-sulfamoyl-2-naphthoate compounds was reported that targets Mcl1, but its binding mechanism remains unexplored. Here, we attempted to explore the molecular mechanism of binding to Mcl1 using advanced computational approaches: pharmacophore-based 3D-QSAR, docking, and MD simulation. The selected pharmacophore&#8212;NNRRR&#8212;yielded a statistically significant 3D-QSAR model containing high confidence scores (R2 = 0.9209, Q2 = 0.8459, and RMSE = 0.3473). The contour maps&#8212;comprising hydrogen bond donor, hydrophobic, negative ionic and electron withdrawal effects&#8212;from our 3D-QSAR model identified the favorable regions crucial for maximum activity. Furthermore, the external validation of the selected model using enrichment and decoys analysis reveals a high predictive power. Also, the screening capacity of the selected model had scores of 0.94, 0.90, and 8.26 from ROC, AUC, and RIE analysis, respectively. The molecular docking of the highly active compound&#8212;C40; 4-(N-benzyl-N-(4-(4-chloro-3,5-dimethylphenoxy) phenyl) sulfamoyl)-1-hydroxy-2-naphthoate&#8212;predicted the low-energy conformational pose, and the MD simulation revealed crucial details responsible for the molecular mechanism of binding with Mcl1

Cross-Genome Clustering of Human and G-Protein Coupled Receptors

G-protein coupled receptors (GPCRs) are one of the largest groups of membrane proteins and are popular drug targets. The work reported here attempts to perform cross-genome phylogeny on GPCRs from two widely different taxa, human versus C. elegans genomes and to address the issues on evolutionary plasticity, to identify functionally related genes, orthologous relationship, and ligand binding properties through effective bioinformatic approaches. Through RPS blast around 1106 nematode GPCRs were given chance to associate with previously established 8 types of human GPCR profiles at varying E -value thresholds and resulted 32 clusters were illustrating co-clustering and class-specific retainsionship. In the significant thresholds, 81% of the C. elegans GPCRs were associated with 32 clusters and 27 C. elegans GPCRs (2%) inferred for orthology. 177 hypothetical proteins were observed in cluster association and could be reliably associated with one of 32 clusters. Several nematode-specific GPCR clades were observed suggesting lineage-specific functional recruitment in response to environment

Deciphering the crucial molecular properties of a series of Benzothiazole Hydrazone inhibitors that targets anti-apoptotic Bcl-xL protein

<p>The Bcl-2 family proteins are the central regulators of apoptosis. Due to its predominant role in cancer progression, the Bcl-2 family proteins act as attractive therapeutic targets. Recently, molecular series of Benzothiazole Hydrazone (BH) inhibitors that exhibits drug-likeness characteristics, which selectively targets Bcl-xL have been reported. In the present study, docking was used to explore the plausible binding mode of the highly active BH inhibitor with Bcl-xL; and Molecular Dynamics (MD) simulation was applied to investigate the stability of predicted conformation over time. Furthermore, the molecular properties of the series of BH inhibitors were extensively investigated by pharmacophore based 3D-QSAR model. The docking correctly predicted the binding mode of the inhibitor inside the Bcl-xL hydrophobic groove, whereas the MD-based free energy calculation exhibited the binding strength of the complex over the time period. Furthermore, the residue decomposition analysis revealed the major energy contributing residues – F105, L108, L130, N136, and R139 – involved in complex stability. Additionally, a six-featured pharmacophore model – AAADHR.89 – was developed using the series of BH inhibitors that exhibited high survival score. The statistically significant 3D-QSAR model exhibited high correlation co-efficient (<i>R</i>² = .9666) and cross validation co-efficient (<i>Q</i>² = .9015) values obtained from PLS regression analysis. The results obtained from the current investigation might provide valuable insights for rational drug design of Bcl-xL inhibitor synthesis.</p

Probing the binding mechanism of mercaptoguanine derivatives as inhibitors of HPPK by docking and molecular dynamics simulations

<p>6-Hydroxymethyl-7,8-dihydropterin pyrophosphokinase (HPPK) is a promising antimicrobial target involved in the folate biosynthesis pathway. Although, the results from crystallographic studies of HPPK have attracted a great interest in the design of novel HPPK inhibitors, the mechanism of action of HPPK due to inhibitor binding remains questionable. Recently, mercaptoguanine derivatives were reported to inhibit the pyrophosphoryl transfer mechanism of <i>Staphylococcus aureus</i> HPPK (SaHPPK). The present study is an attempt to understand the SaHPPK-inhibitors binding mechanism and to highlight the key residues that possibly involve in the complex formation. To decipher these questions, we used the state-of-the-art advanced <i>insilico</i> approach such as molecular docking, molecular dynamics (MD), molecular mechanics-generalized Born surface area approach. Domain cross correlation and principle component analysis were applied to the snapshots obtained from MD revealed that the compounds with high binding affinity stabilize the conformational dynamics of SaHPPK. The binding free energy estimation showed that the van der Waals and electrostatic interactions played a vital role for the binding mechanism. Additionally, the predicted binding free energy was in good agreement with the experimental values (<i>R</i>² = .78). Moreover, the free energy decomposition on per-residue confirms the key residues that significantly contribute to the complex formation. These results are expected to be useful for rational design of novel SaHPPK inhibitors.</p