Exploring the selectivity of inhibitor complexes with Bcl-2 and Bcl-XL: A molecular dynamics simulation approach

Evaluation of Pregabalin bioadhesive multilayered microemulsion IOP-lowering eye drops

In spite of available treatment options, glaucoma continues to be a leading cause of irreversible blindness in the world. Current glaucoma medications have multiple limitations including: lack of sustained action; requirement for multiple dosing per day, ocular irritation and limited options for drugs with different mechanisms of action. Previously, we demonstrated that pregabalin, a drug with high affinity and selectivity for CACNA2D1, lowered IOP in a dose-dependent manner. The current study was designed to evaluate pregabalin microemulsion eye drops and to estimate its efficacy in humans using in silico methods. Molecular docking studies of pregabalin against CACNA2D1 of mouse, rabbit, and human were performed. Pregabalin microemulsion eye drops were characterized using multiple in vivo studies and its stability was evaluated over one year at different storage conditions. Molecular docking analyses and QSPR of pregabalin confirmed its suitability as a new IOP-lowering medication that functions using a new mechanism of action by binding to CACNA2D1 in all species evaluated. Because of its prolonged corneal residence time and corneal penetration enhancement, a single topical application of pregabalin ME can provide an extended IOP reduction of more than day in different animal models. Repeated daily dosing for 2 months confirms the lack of any tachyphylactic effect, which is a common drawback among marketed IOP-lowering medications. In addition, pregabalin microemulsion demonstrated good physical stability for one year, and chemical stability for 3-6 months if stored below 25 °C. Collectively, these outcomes greatly support the use of pregabalin eye drops as once daily IOP-lowering therapy for glaucoma management.

Prediction of the binding mechanism of a selective DNA methyltransferase 3A inhibitor by molecular simulation

DNA methylation is an epigenetic mechanism that introduces a methyl group at the C5 position of cytosine. This reaction is catalyzed by DNA methyltransferases (DNMTs) and is essential for the regulation of gene transcription. The DNMT1 and DNMT3A or -3B family proteins are known targets for the inhibition of DNA hypermethylation in cancer cells. A selective non-nucleoside DNMT3A inhibitor was developed that mimics S-adenosyl-l-methionine and deoxycytidine; however, the mechanism of selectivity is unclear because the inhibitor-protein complex structure determination is absent. Therefore, we performed docking and molecular dynamics simulations to predict the structure of the complex formed by the association between DNMT3A and the selective inhibitor. Our simulations, binding free energy decomposition analysis, structural isoform comparison, and residue scanning showed that Arg688 of DNMT3A is involved in the interaction with this inhibitor, as evidenced by its significant contribution to the binding free energy. The presence of Asn1192 at the corresponding residues in DNMT1 results in a loss of affinity for the inhibitor, suggesting that the interactions mediated by Arg688 in DNMT3A are essential for selectivity. Our findings can be applied in the design of DNMT-selective inhibitors and methylation-specific drug optimization procedures.

Identification of a 1, 8-naphthyridine-containing compound endowed with the inhibition of p53-MDM2/X interaction signaling: a computational perspective

Various studies have established that molecules specific for MDMX inhibition or optimized for dual inhibition of p53-MDM2/MDMX interaction signaling are more suitable for activating the Tp53 gene in tumor cells. Nevertheless, there are sparse numbers of approved molecules to treat the health consequences brought by the lost p53 functions in tumor cells. Consequently, this study explored the potential of a small molecule ligand containing 1, 8-naphthyridine scaffold to act as a dual inhibitor of p53-MDM2/X interactions using computational methods. The results obtained from quantum mechanical calculations revealed our studied compound entitled CPO is more stable but less reactive compared to standard dual inhibitor RO2443. Like RO2443, CPO also exhibited good non-linear optical properties. The results of molecular docking studies predicted that CPO has a higher potential to inhibit MDM2/MDMX than RO2443. Furthermore, CPO was stable over 50 ns molecular dynamics (MD) simulation in complex with MDM2 and MDMX respectively. On the whole, CPO also exhibited good drug-likeness and pharmacokinetics properties compared to RO2443 and was found with more anti-cancer activity than RO2443 in bioactivity prediction. CPO is anticipated to elevate effectiveness and alleviate drug resistance in cancer therapy. Ultimately, our results provide an insight into the mechanism that underlay the inhibition of p53-MDM2/X interactions by a molecule containing 1, 8-naphthyridine scaffold in its molecular structure.

Drug repurposing for the identification of new Bcl-2 inhibitors: In vitro, STD-NMR, molecular docking, and dynamic simulation studies

BACKGROUND

The anti-apoptotic protein B-Cell Lymphoma 2 (Bcl-2) is a key target for the development of anti-cancer agents, as its overexpression can render cancer cells resistant to chemotherapeutic treatments.

AIMS AND OBJECTIVES

The current study has systematically evaluated a library of FDA-approved drugs for Bcl-2 inhibition using a drug repurposing strategy via in vitro, biophysical, and in-silico techniques.

MATERIALS AND METHODS

In vitro anticancer activity was performed, followed by apoptosis assay. The selected compounds were subjected to Saturation Transfer Difference Nuclear Magnetic Resonance (STD-NMR) spectroscopy, molecular docking, and molecular dynamic simulation for ligand-protein interactions.

KEY FINDINGS

In the initial screening, seventy-five (75) drugs were evaluated against the HL-60 (human blood promyelocytic leukemia) cancer cell line. Among them, paroxetine HCl, carvedilol, clomipramine HCl, and clomifene citrate showed significant anti-proliferative activity (IC50 = 9.733 ± 0.524, 11.940 ± 0.079, 12.376 ± 1.242, and 6.155 ± 0.363 μM, respectively), in comparison to the reference drug venetoclax (IC50 = 7.086 ± 0.041 μM). This indicated that the test drugs have comparable IC50 values to the standard drug. Furthermore, the drugs were able to induce apoptosis in HL-60 cells. These drugs showed interactions with Bcl-2 protein in STD-NMR analysis. Docking and MD simulation studies further supported the interaction of these drugs with Bcl-2 protein, mainly via hydrophobic contacts leading to stable drug-Bcl-2 complexes.

SIGNIFICANCE

This study, identifies paroxetine HCl, carvedilol, clomipramine HCl, and clomifene citrate as significant Bcl-2 inhibitors and needs further pre-clinical and clinical studies for potential anti-cancer agents' evaluation.

Exploring the interactions of antihistamine with retinoic acid receptor beta (RARB) by molecular dynamics simulations and genome-wide meta-analysis

Kaposi sarcoma (KS) is one of the most common AIDS-related malignant neoplasms, which can leave lesions on the skin among HIV patients. These lesions can be treated with 9-cis-retinoic acid (9-cis-RA), an endogenous ligand of retinoic acid receptors that has been FDA-approved for treatment of KS. However, topical application of 9-cis-RA can induce several unpleasant side effects, like headache, hyperlipidemia, and nausea. Hence, alternative therapeutics with less side effects are desirable. There are case reports associating over-the-counter antihistamine usage with regression of KS. Antihistamines competitively bind to H1 receptor and block the action of histamine, best known for being released in response to allergens. Furthermore, there are already dozens of antihistamines that are FDA-approved with less side effects than 9-cis-RA. This led our team to conduct a series of in-silico assays to determine whether antihistamines can activate retinoic acid receptors. First, we utilized high-throughput virtual screening and molecular dynamics simulations to model high-affinity interactions between antihistamines and retinoic acid receptor beta (RARβ). We then performed systems genetics analysis to identify a genetic association between H1 receptor itself and molecular pathways involved in KS. Together, these findings advocate for exploration of antihistamines against KS, starting with our two promising hit compounds, bepotastine and hydroxyzine, for experimental validation study in the future.

Structure-Based Drug Design of Novel Triaminotriazine Derivatives as Orally Bioavailable IDH2R140Q Inhibitors with High Selectivity and Reduced hERG Inhibitory Activity for the Treatment of Acute Myeloid Leukemia

Neomorphic IDH2R140Q mutation is commonly found in acute myeloid leukemia (AML), and inhibiting its activity has been validated as an effective treatment for AML. Herein, we report a series of highly potent and selective IDH2R140Q inhibitors. Among them, compound 36 was identified as the most promising inhibitor, with an IC50 value of 29 nM and more than 490-fold selectivity over wild-type IDH2. The compound significantly suppressed D2HG production (IC50 = 10 nM) and induced differentiation in TF-1/IDH2R140Q cells. Furthermore, it showed reasonable pharmacokinetic properties with high bioavailability (F = 90.3%) and an appropriate half-life (T1/2 = 6.4 h). In vivo, oral administration of compound 36 at a dose of 25 mg/kg effectively reduced D2HG levels in the tumor of TF-1/IDH2R140Q xenograft mouse model. Besides, compound 36 displayed little effect on the hERG current. These results suggest that compound 36 has the potential to be an efficacious treatment for AML.

Role of ATP5G3 in sodium nitroprusside-induced cell death in cervical carcinoma cells

We identified a gene, subunit C3 (ATP5G3) of mitochondrial ATP synthase, that displayed changes in gene expression under oxidative stress. We examined the role of ATP5G3 and its molecular mechanisms in sodium nitroprusside (SNP)-induced cell death using ATP5G3 small interfering RNA (siATP5G3)-transfected HeLa cells. A significant increase in cytotoxicity was observed in the transfected cells treated with SNP, which suggests a protective role of ATP5G3 in SNP-induced cytotoxicity in the cells. The transfected cells treated with photodegraded SNP showed equal cytotoxicity to SNP, and pretreatment with deferoxamine (DFO) completely inhibited this cytotoxicity. Further, cytotoxicity was significantly inhibited by pretreatment with a p38 inhibitor and was accentuated by the p38 activator in cells. Pretreatment with the Bcl-xL inhibitor also significantly accentuated cytotoxicity. The increase in p38 phosphorylation was significantly higher in siATP5G3-transfected cells treated with SNP in immunoblotting, which was inhibited by pretreatment with DFO. The increase in cytotoxicity with siATP5G3 transfection was completely blocked by cotransfection with sip38, and the blocking effect disappeared by cotransfection with additional siBcl-xL, which suggests that the protective role of ATP5G3 is mediated by Bcl-xL via the inhibition of p38 activity. Cytotoxicity was completely blocked by the cotransfection of siATP5G3 with siBax. No change in apoptotic parameters was observed during cytotoxicity. However, pretreatment with lysosomal inhibitors significantly inhibited cytotoxicity and increased p62 protein levels. These findings suggest that ATP5G3 plays a protective role in autophagic cell death/lysosome-associated cell death induced by SNP via the sequential signaling of ROS/p38/Bcl-xL/Bax in HeLa cells.

Green Biosynthesis of Silver Nanoparticles Using Annona glabra and Annona squamosa Extracts with Antimicrobial, Anticancer, Apoptosis Potentials, Assisted by In Silico Modeling, and Metabolic Profiling

Annona glabra L. (AngTE) and Annona squamosa L. (AnsTE) fruits have been widely used in cancer treatment. Accordingly, their extracts were used to synthesize silver nanoparticles via a biogenic route (Ang-AgNPs) and (Ans-AgNPs), respectively. Chemical profiling was established using UPLC-QTOF-MS/MS. All species were tested for anticancer activity against human cervical cancer cells (HeLa), prostate adenocarcinoma metastatic (PC3), and ovary adenocarcinoma (SKOV3) using sulphorhodamine B assay. Apoptosis was determined using Annexin flow cytometry along with cell cycle analysis and supported by a molecular docking. The antibacterial and synergistic effect when combined with gentamicin were evaluated. A total of 114 compounds were tentatively identified, mainly acetogenins and ent-kaurane diterpenes. AnsTE and Ans-AgNPs had the most potent cytotoxicity on HeLa and SKOV3 cells, inducing a significant apoptotic effect against all tumor cells. The AnsTE and Ans-AgNPs significantly arrested PC3, SKOV3, and HeLa cells in the S phase. The nanoparticles demonstrated greater antibacterial and antifungal activities, as well as a synergistic effect with gentamicin against P. aeruginosa and E. coli. Finally, a molecular docking was attempted to investigate the binding mode of the identified compounds in Bcl-2 proteins’ receptor, implying that the fruits and their nanoparticles are excellent candidates for treating skin infections in patients with ovarian or prostatic cancer.

Structure-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation of VEGF inhibitors for the clinical treatment of Ovarian Cancer

Vascular endothelial growth factor (VEGF) and its receptor play an important role both in physiologic and pathologic angiogenesis, which is identified in ovarian cancer progression and metastasis development. The aim of the present investigation is to identify a potential vascular endothelial growth factor inhibitor which is playing a crucial role in stimulating the immunosuppressive microenvironment in tumor cells of the ovary and to examine the effectiveness of the identified inhibitor for the treatment of ovarian cancer using various in silico approaches. Twelve established VEGF inhibitors were collected from various literatures. The compound AEE788 displays great affinity towards the target protein as a result of docking study. AEE788 was further used for structure-based virtual screening in order to obtain a more structurally similar compound with high affinity. Among the 80 virtual screened compounds, CID 88265020 explicates much better affinity than the established compound AEE788. Based on molecular dynamics simulation, pharmacophore and comparative toxicity analysis of both the best established compound and the best virtual screened compound displayed a trivial variation in associated properties. The virtual screened compound CID 88265020 has a high affinity with the lowest re-rank score and holds a huge potential to inhibit the VGFR and can be implemented for prospective future investigations in ovarian cancer.

Selectivity mechanism of BCL-XL/2 inhibition through in silico investigation

BCL-XL protein is among the most important members of the anti-apoptotic subfamily of BCL-2 protein family, as currently a promising new target for anti-tumor drug research, even though BCL-XL/2 proteins...

Computer aided drug discovery review for infectious diseases with case study of anti-Chagas project

Neglected tropical diseases (NTDs) are parasitic and bacterial infections that are widespread, especially in the tropics, and cause health problems for about one billion people over 149 countries worldwide. However, in terms of therapeutic agents, for example, nifurtimox and benznidazole were developed in the 1960s to treat Chagas disease, but new drugs are desirable because of their side effects. Drug discovery takes 12 to 14 years and costs $2.6 billon dollars, and hence, computer aided drug discovery (CADD) technology is expected to reduce the time and cost. This paper describes our methods and results based on CADD, mainly for NTDs. An overview of databases, molecular simulation and pharmacophore modeling, contest-based drug discovery, and machine learning and their results are presented herein.

Quinoline and Quinazoline Alkaloids against COVID-19: An In Silico Multitarget Approach

The recent outbreak of the highly contagious coronavirus disease 2019 (COVID-19) caused by the novel coronavirus SARS-CoV-2 has created a global health crisis with socioeconomic impacts. Although, recently, vaccines have been approved for the prevention of COVID-19, there is still an urgent need for the discovery of more efficacious and safer drugs especially from natural sources. In this study, a number of quinoline and quinazoline alkaloids with antiviral and/or antimalarial activity were virtually screened against three potential targets for the development of drugs against COVID-19. Among seventy-one tested compounds, twenty-three were selected for molecular docking based on their pharmacokinetic and toxicity profiles. The results identified a number of potential inhibitors. Three of them, namely, norquinadoline A, deoxytryptoquivaline, and deoxynortryptoquivaline, showed strong binding to the three targets, SARS-CoV-2 main protease, spike glycoprotein, and human angiotensin-converting enzyme 2. These alkaloids therefore have promise for being further investigated as possible multitarget drugs against COVID-19.

Screening possible drug molecules for Covid-19. The example of vanadium (III/IV/V) complex molecules with computational chemistry and molecular docking

We are still facing a Covid-19 pandemic these days and after the aggressively infection control measures taken by the governments in the whole world, there is a need of a rapid pharmaceutical solution in order to control this crisis. The computer aided chemistry and molecular docking is a rapid tool for drug screening and investigation. Moreover, more metal-based drugs are tested daily by research institutes for their antiviral activity. Here, we make use of theoretical studies on previously published biological active complex molecules of vanadium as an example of evaluating possible drug candidates before entering the laboratory. We used DFT calculation studies for structural elucidation and optimization of the molecules and molecular docking studies on several Covid-19 related proteins. Our findings suggest that drug discovery should always be computer -aided. Additionally, it is found that Vtocdea and VXn molecules are seem to be good candidates for further studies as antiviral agents.

Molecular Docking Study of Naturally Derived Flavonoids with Antiapoptotic BCL-2 and BCL-XL Proteins toward Ovarian Cancer Treatment

The naturally derived flavonoids are well known to have anticarcinogenic effects. Flavonoids could be an alternative strategy for ovarian cancer treatment, due to existing platinum-based drugs are reported to develop resistance with low survival rates. Inhibition of antiapoptotic proteins, namely B-cell lymphoma (Bcl-2) and B-cell lymphoma-extra large (Bcl-xl), is the key target to stimulate apoptosis process in cancer cells. This study aimed to determine the binding interaction of five naturally derived flavonoids (biochanin A, myricetin, apigenin, galangin, and fisetin) with potential antiapoptotic target proteins (Bcl-2 and Bcl-xl). The molecular docking study was conducted using AutoDock Vina program. The binding affinity and the presence of hydrogen bonds between the flavonoids and target proteins were predicted. Our findings showed that all the flavonoids showed better binding affinity with Bcl-xl than that of Bcl-2 proteins. The highest binding affinity was recorded in fisetin-Bcl-xl protein complex (-8.8 kcal/mol). Meanwhile, the other flavonoids docked with Bcl-xl protein showed binding affinities, ranging from -8.0 to -8.6 kcal/mol. A total of four hydrogen bonds, four hydrophobic contacts, and one electrostatic interaction were detected in the docked fisetin-Bcl-xl complex, explaining its high binding affinity with Bcl-xl. The present results indicate that all flavonoids could potentially serve as Bcl-xl protein inhibitors, which would consequently lead to apoptotic process in ovarian cancers.

Identification of key interactions between SARS-CoV-2 main protease and inhibitor drug candidates

The number of cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (COVID-19) has reached over 114,000. SARS-CoV-2 caused a pandemic in Wuhan, China, in December 2019 and is rapidly spreading globally. It has been reported that peptide-like anti-HIV-1 drugs are effective against SARS-CoV Main protease (Mpro). Due to the close phylogenetic relationship between SARS-CoV and SARS-CoV-2, their main proteases share many structural and functional features. Thus, these drugs are also regarded as potential drug candidates targeting SARS-CoV-2 Mpro. However, the mechanism of action of SARS-CoV-2 Mpro at the atomic-level is unknown. In the present study, we revealed key interactions between SARS-CoV-2 Mpro and three drug candidates by performing pharmacophore modeling and 1 μs molecular dynamics (MD) simulations. His41, Gly143, and Glu166 formed interactions with the functional groups that were common among peptide-like inhibitors in all MD simulations. These interactions are important targets for potential drugs against SARS-CoV-2 Mpro.

Discovery of small molecule inhibitors through pharmacophore modeling, molecular docking, molecular dynamics simulation and experimental validation against myeloid cell leukemia-1 (Mcl-1)

Myeloid cell leukemia-1 (Mcl-1) protein is a family of Bcl-2 (B cell lymphoma 2) rich proteases of the most common increase threshold for genetic aberrations observed in human cancer, including lung, breast, pancreatic, cervical, and ovarian cancers as well as leukemia and lymphoma. Mcl-1 is recognized as an attractive drug target in number of diseases, including cancer. In the present study we surveyed and collected queries compounds from PDB database of Mcl-1 protein and generated pharmacophore-based models adapted to screen the drug-like compounds from FDA approved database. The 206 best lead molecules from pharmacophore-screening were further evaluated by molecular docking, molecular dynamics simulation, MM-GBSA calculation, as well as experimental validation. Two hits, ZINC00601272 and ZINC00002166, showed the best docking scores, which showed a tendency to inhibit cell viability of HL60 and K562 leukemia cells with Mcl-1 expressions. Conclusively, the present study provides structural information of Mcl-1 inhibitors for next generations of cancer therapeutics through computational and experimental validation approach.Communicated by Ramaswamy H. Sarma.

A biscoumarin scaffold as an efficient anti-Zika virus lead with NS3-helicase inhibitory potential: in vitro and in silico investigations

Competitive NTPase inhibition and the potential binding to the RNA binding pocket of Zika NS3-helicase were observed using biscoumarin derivatives. The SAR was established, and MN-9 and MN-10 were identified as potent anti-Zika leads.

Alpha-Tocotrienol Prevents Oxidative Stress-Mediated Post-Translational Cleavage of Bcl-xL in Primary Hippocampal Neurons

B-cell lymphoma-extra large (Bcl-xL) is an anti-apoptotic member of the Bcl2 family of proteins, which supports neurite outgrowth and neurotransmission by improving mitochondrial function. During excitotoxic stimulation, however, Bcl-xL undergoes post-translational cleavage to ∆N-Bcl-xL, and accumulation of ∆N-Bcl-xL causes mitochondrial dysfunction and neuronal death. In this study, we hypothesized that the generation of reactive oxygen species (ROS) during excitotoxicity leads to formation of ∆N-Bcl-xL. We further proposed that the application of an antioxidant with neuroprotective properties such as α-tocotrienol (TCT) will prevent ∆N-Bcl-xL-induced mitochondrial dysfunction via its antioxidant properties. Primary hippocampal neurons were treated with α-TCT, glutamate, or a combination of both. Glutamate challenge significantly increased cytosolic and mitochondrial ROS and ∆N-Bcl-xL levels. ∆N-Bcl-xL accumulation was accompanied by intracellular ATP depletion, loss of mitochondrial membrane potential, and cell death. α-TCT prevented loss of mitochondrial membrane potential in hippocampal neurons overexpressing ∆N-Bcl-xL, suggesting that ∆N-Bcl-xL caused the loss of mitochondrial function under excitotoxic conditions. Our data suggest that production of ROS is an important cause of ∆N-Bcl-xL formation and that preventing ROS production may be an effective strategy to prevent ∆N-Bcl-xL-mediated mitochondrial dysfunction and thus promote neuronal survival.

Molecular Dynamics Simulation reveals the mechanism by which the Influenza Cap-dependent Endonuclease acquires resistance against Baloxavir marboxil

Baloxavir marboxil (BXM), an antiviral drug for influenza virus, inhibits RNA replication by binding to RNA replication cap-dependent endonuclease (CEN) of influenza A and B viruses. Although this drug was only approved by the FDA in October 2018, drug resistant viruses have already been detected from clinical trials owing to an I38 mutation of CEN. To investigate the reduction of drug sensitivity by the I38 mutant variants, we performed a molecular dynamics (MD) simulation on the CEN-BXM complex structure to analyze variations in the mode of interaction. Our simulation results suggest that the side chain methyl group of I38 in CEN engages in a CH-pi interaction with the aromatic ring of BXM. This interaction is abolished in various I38 mutant variants. Moreover, MD simulation on various mutation models and binding free energy prediction by MM/GBSA method suggest that the I38 mutation precludes any interaction with the aromatic ring of BXA and thereby reduces BXA sensitivity.

Targeting cancer's Achilles’ heel: role of BCL-2 inhibitors in cellular senescence and apoptosis

Members of the antiapoptotic BCL-2 proteins are involved in tumor growth, progression and survival, and are also responsible for chemoresistance to conventional anticancer agents. Early efforts to target these proteins yielded some active compounds; however, newer methodologies involving structure-based drug design, Nuclear Magnetic Resonance (NMR)-based screening and fragment-based screening yielded more potent compounds. Discovery of specific as well as nonspecific inhibitors of this class of proteins has resulted in great advances in targeted chemotherapy and decrease in chemoresistance. Here, we review the history and current progress in direct as well as selective targeting of the BCL-2 proteins for anticancer therapy.

Influence of Amino Acid Mutations and Small Molecules on Targeted Inhibition of Proteins Involved in Cancer

Background:

Protein-protein interactions (PPIs) are of crucial importance in regulating the biological processes of cells both in normal and diseased conditions. Significant progress has been made in targeting PPIs using small molecules and achieved promising results. However, PPI drug discovery should be further accelerated with better understanding of chemical space along with various functional aspects.

Objective:

In this review, we focus on the advancements in computational research for targeted inhibition of protein-protein interactions involved in cancer.

Methods:

Here, we mainly focused on two aspects: (i) understanding the key roles of amino acid mutations in epidermal growth factor receptor (EGFR) as well as mutation-specific inhibitors and (ii) design of small molecule inhibitors for Bcl-2 to disrupt PPIs.

Results:

The paradigm of PPI inhibition to date reflect the certainty that inclination towards novel and versatile strategies enormously dictate the success of PPI inhibition. As the chemical space highly differs from the normal drug like compounds the lead optimization process has to be given the utmost priority to ensure the clinical success. Here, we provided a broader perspective on effect of mutations in oncogene EGFR connected to Bcl-2 PPIs and focused on the potential challenges.

Conclusion:

Understanding and bridging mutations and altered PPIs will provide insights into the alarming signals leading to massive malfunctioning of a biological system in various diseases. Finding rational elucidations from a pharmaceutical stand point will presumably broaden the horizons in future.

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

Myeloid cell leukemia-1 (Mcl1) is an anti–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—NNRRR—yielded a statistically significant 3D-QSAR model containing high confidence scores (R2 = 0.9209, Q2 = 0.8459, and RMSE = 0.3473). The contour maps—comprising hydrogen bond donor, hydrophobic, negative ionic and electron withdrawal effects—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—C40; 4-(N-benzyl-N-(4-(4-chloro-3,5-dimethylphenoxy) phenyl) sulfamoyl)-1-hydroxy-2-naphthoate—predicted the low-energy conformational pose, and the MD simulation revealed crucial details responsible for the molecular mechanism of binding with Mcl1.

Improved Method of Structure-Based Virtual Screening via Interaction-Energy-Based Learning

Virtual screening is a promising method for obtaining novel hit compounds in drug discovery. It aims to enrich potentially active compounds from a large chemical library for further biological experiments. However, the accuracy of current virtual screening methods is insufficient. In this study, we develop a new virtual screening method named Similarity of Interaction Energy VEctor Score (SIEVE-Score), in which protein-ligand interaction energies are extracted to represent docking poses for machine learning. SIEVE-Score offers substantial improvements compared to other state-of-the-art virtual screening methods, namely, other machine-learning-based scoring functions, interaction fingerprints, and docking software, for the enrichment factor 1% results on the Directory of Useful Decoys, Enhanced (DUD-E). The screening results are also human-interpretable in the form of important interactions for distinguishing between active and inactive compounds. The source code is available at https://github.com/sekijima-lab/SIEVE-Score .

Computational insights of K1444N substitution in GAP-related domain of NF1 gene associated with neurofibromatosis type 1 disease: a molecular modeling and dynamics approach

The NF1 gene encodes for neurofibromin protein, which is ubiquitously expressed, but most highly in the central nervous system. Non-synonymous SNPs (nsSNPs) in the NF1 gene were found to be associated with Neurofibromatosis Type 1 disease, which is characterized by the growth of tumors along nerves in the skin, brain, and other parts of the body. In this study, we used several in silico predictions tools to analyze 16 nsSNPs in the RAS-GAP domain of neurofibromin, the K1444N (K1423N) mutation was predicted as the most pathogenic. The comparative molecular dynamic simulation (MDS; 50 ns) between the wild type and the K1444N (K1423N) mutant suggested a significant change in the electrostatic potential. In addition, the RMSD, RMSF, Rg, hydrogen bonds, and PCA analysis confirmed the loss of flexibility and increase in compactness of the mutant protein. Further, SASA analysis revealed exchange between hydrophobic and hydrophilic residues from the core of the RAS-GAP domain to the surface of the mutant domain, consistent with the secondary structure analysis that showed significant alteration in the mutant protein conformation. Our data concludes that the K1444N (K1423N) mutant lead to increasing the rigidity and compactness of the protein. This study provides evidence of the benefits of the computational tools in predicting the pathogenicity of genetic mutations and suggests the application of MDS and different in silico prediction tools for variant assessment and classification in genetic clinics.