Free Energy Decomposition Research Articles

Potential matrix metalloproteinase 2 and 9 inhibitors identified from Ehretia species for the treatment of chronic wounds - Computational drug discovery approaches

Matrix metalloproteinases (MMPs) serve as prognostic factors in several pathophysiological conditions, including chronic wounds. Therefore, they are considered important therapeutic targets in the intervention and treatment of these conditions. In this study, computational tools such as molecular docking and molecular dynamics simulations were used to gain insight into protein‒ligand interactions and determine the free binding energy between Ehretia species phytoconstituents and gelatinases (MMP2 and MMP9). A total of 74 phytoconstituents from Ehretia species were compiled from the literature, and 46 of these compounds were identified as potential inhibitors of at least one type of MMP. Molecular docking revealed that lithospermic acid B, rosmarinic acid, and danshensu had stronger binding affinities against the two enzymes than the reference ligands. Furthermore, (9S, 10E, 12Z, 15Z)-9-hydroxy-10,12,15-octadecatrienoic (∗-octadecatrienoic) had a higher binding energy for MMP2, whereas caffeic anhydride and caffeic acid established stronger binding energy with MMP9 than the reference ligand. These complexes also demonstrated relatively stable, favourable, and comparable conformational changes with those of unbound proteins at 500 ns. The free energy decomposition results further provide detailed insights into the contributions of active site residues and different types of interactions to the overall binding free energy. Finally, most of the hit phytoconstituents (rosmarinic acid, caffeic anhydride, caffeic acid, and danshensu) had good physicochemical, drug-likeness, and pharmacokinetic properties. Collectively, our findings showed that phytoconstituents from Ehretia species could be beneficial in the search for novel MMP inhibitors as therapeutic agents for the treatment of chronic wounds.

A Mechanistic Approach on Perception Mode of ABA Receptors (PYLs) to Novel Opabactin Analogues.

This study explored the structural mechanisms governing the binding of opabactin (OP) analogues 2-6 to abscisic acid (ABA) receptors by employing a combination of micro-scale thermophoresis (MST), phosphatase activity inhibition assays, and molecular dynamics simulations. The compounds 3-6 selectively activated PYR1, PYL2, and PYL6, while exhibiting minimal activity against PYL10, thus identifying them as selective ABA receptor agonists. Additionally, these analogues exerted a significant inhibitory effect on the phosphatase HAB1 upon binding to the receptors. The molecular dynamics simulations further elucidated the detailed binding interactions between various OP analogues and the ABA receptor PYR1, highlighting their role in inducing conformational changes within the receptor. Specifically, the study focused on the facilitation of the closure of the Gate and CL1 loops and the fine-tuning of the Latch loop to enhance the plasticity of the binding pocket, thereby influencing receptor-ligand interactions. The investigation emphasized the critical role of conserved water molecules in stabilizing the ligand-PYLs-PP2Cs complexes. Furthermore, free energy decomposition calculations demonstrated that the ligand's affinity was significantly affected by its ability to establish polar contacts between the polar groups within the ligand tail and the residues at the base of the binding pocket. This research lays a robust foundation for the development of novel ABA functional analogues with improved activity.

Likely Overstabilization of Charge-Charge Interactions in CHARMM36m(w): A Case for a99SB-disp Water.

Recent years have witnessed drastic improvements in general-purpose explicit solvent protein force fields, partially driven by the need to study intrinsically disordered proteins (IDPs), and yet the state-of-the-art force fields such as CHARMM36m (c36m) and a99SB-disp still provide different performances in simulating disordered protein states, where c36m has a bias toward overcompaction for large IDPs. Here, we examine the performance of c36m and a99SB-disp in describing the stabilities of a set of 46 amino acid backbone and side chain pairs in various configurations. The free energy results show that c36m systematically predicts stronger interactions compared to a99SB-disp by an average of 0.2 kcal/mol for nonpolar pairs, 0.6 kcal/mol for polar pairs, and 0.8 kcal/mol for salt bridges. The most severe overstabilization in c36m is observed for charged pairs involving the Arg and Glu side chains by up to 2.9 kcal/mol. Importantly, the systematic overstabilization of c36m is only marginally alleviated by c36mw, an ad hoc patch to c36m that increases the dispersion interactions between TIP3P hydrogens and protein atoms. Guided by free energy decomposition, we evaluated if revising the charges alone could alleviate the severe overstabilization of salt bridges of c36m(w) vs a99SB-disp. The results suggested that the direct modification of protein-water interactions is also necessary. Toward this end, we proposed a tentative modification to c36m, referred to as c36mrb-disp, which combines modified Arg side chain charges, retuned backbone hydrogen bonding strength, and the a99SB-disp water model. The modified force field successfully reproduces the secondary structures of several intrinsically disordered peptides and proteins including (AAQAA)3, GB1p, and p53 transactivation domain, while maintaining the stability of a set of folded proteins. This work provides a set of useful systems for benchmarking and optimizing protein force fields and highlights the importance of balancing protein-protein and protein-water electrostatic interactions for accurately describing both folded and disordered proteins.

Hydrophobic forces at play: insights into AmelOBP4 and brood volatile interactions in Apis mellifera hygienic behavior

Understanding the intricate processes underlying olfaction necessitates unraveling the complexities of odorant binding protein’s interactions with volatile compounds triggering hygienic behavior in Apis mellifera, This study delves into the intricate processes of olfaction by focusing on the interactions between Apis mellifera Odorant Binding Protein 4 (AmelOBP4) and volatile compounds associated with hygienic behavior, employing a comprehensive computational approach. Molecular docking analyses reveal detailed binding interactions, emphasizing the significance of hydrophobic interactions and specific amino acid residues in stabilizing AmelOBP4-volatile complexes, notably with 2-nonacosanone (-8.4 kcal/mol) and hexacosyl acetate (-8.4 kcal/mol). Molecular dynamics simulations demonstrate sustained stability and principal component analysis affirms structural integrity through restricted global motions. Binding free energy calculations underscore robust interactions, with per-residue free energy decomposition identifying key amino acids contributing significantly to binding affinity. These findings illuminate the pivotal role of hydrophobic interactions and specific residues (Phe 60, Leu 83, Ile 116, Leu 126, and Leu 130) in modulating AmelOBP4-volatile interactions, providing foundational insights into volatile-based applications and potential olfactory response modulation, contributing to our understanding of olfactory processes.

Identification of novel inhibitors targeting PI3Kα via ensemble-based virtual screening method, biological evaluation and molecular dynamics simulation.

PIK3CA gene encoding PI3K p110α is one of the most frequently mutated and overexpressed in majority of human cancers. Development of potent and selective novel inhibitors targeting PI3Kα was considered as the most promising approaches for cancer treatment. In this investigation, a virtual screening platform for PI3Kα inhibitors was established by employing machine learning methods, pharmacophore modeling, and molecular docking approaches. 28 potential PI3Kα inhibitors with different scaffolds were selected from the databases with 295,024 compounds. Among the 28 hits, hit15 exhibited the best inhibitory effect against PI3Kα with IC50 value less than 1.0µM. The molecular dynamics simulation indicated that hit15 could stably bind to the active site of PI3Kα, interact with some residues by hydrophobic, electrostatic and hydrogen bonding interactions, and finally induced PI3Kα active pocket substantial conformation changes. Stable H-bond interactions were formed between hit15 and residues of Lys776, Asp810 and Asp933. The binding free energy of PI3Kα-hit15 was -65.3kJ/mol. The free energy decomposition indicated that key residues of Asp805, Ile848 and Ile932 contributed stronger energies to the binding free energy. The above results indicated that hit15 with novel scaffold was a potent PI3Kα inhibitor and considered as a promisingcandidateforfurther drugdevelopment to treat various cancers with PI3Kα over activated.

Exploring protein-berberine interactions via molecular dynamics and MM/GBSA calculations

Structural modification on berberine has garnered considerable attention among medicinal chemists as a means to enhance its therapeutic potential. The dissection of macrobiomolecule-berberine interactions is pivotal for guiding such modifications. In this study, four diverse crystal complexes of protein-berberine were selected, and simulated by molecular dynamics, in which each complex was conducted five times. Subsequently, the interactions of protein-berberine were collected, and analyzed by in-house scripts. Our findings indicated that the four oxygen atoms, namely O15, O16, O17, and O18, actively participated in the formation of hydrogen bonds and water bridges; the carbon atoms within the D and E rings were able to form hydrophobic interactions more than other carbon atoms; the positively charged N7 atom predominantly participated in the formation of cation-π interactions; π-π interactions were prevalent in the A, B, and D rings, with their frequency influenced by the presence of the residues Trp, Tyr, His, and Phe in the binding pocket. In the free energy decomposition analysis, the terms ΔG_Lipo and ΔG_vdW emerged as the most significant contributors to the overall energy, with ΔG_vdW accounting for over 50% of the energy contribution. Notably, the contribution of ΔG_Packing to the free energy was substantially greater than that of ΔG_Hbond, which contributed less than 1%. These insights into molecular interactions provide valuable guidance for the structural modification of berberine, such as site selection of structural modification, group optimization with the improvement of van der Waals and hydrophobic interactions, and the trade-off between hydrogen bonding and π-packing interactions in terms of interaction weights.

Pharmacophore-Assisted Covalent Docking Identifies a Potential Covalent Inhibitor for Drug-Resistant Genotype 3 Variants of Hepatitis C Viral NS3/4A Serine Protease.

The emergence of drug-resistance-inducing mutations in Hepatitis C virus (HCV) coupled with genotypic heterogeneity has made targeting NS3/4A serine protease difficult. In this work, we investigated the mutagenic variations in the binding pocket of Genotype 3 (G3) HCV NS3/4A and evaluated ligands for efficacious inhibition. We report mutations at 14 positions within the ligand-binding residues of HCV NS3/4A, including H57R and S139P within the catalytic triad. We then modelled each mutational variant for pharmacophore-based virtual screening (PBVS) followed by covalent docking towards identifying a potential covalent inhibitor, i.e., cpd-217. The binding stability of cpd-217 was then supported by molecular dynamic simulation followed by MM/GBSA binding free energy calculation. The free energy decomposition analysis indicated that the resistant mutants alter the HCV NS3/4A-ligand interaction, resulting in unbalanced energy distribution within the binding site, leading to drug resistance. Cpd-217 was identified as interacting with all NS3/4A G3 variants with significant covalent docking scores. In conclusion, cpd-217 emerges as a potential inhibitor of HCV NS3/4A G3 variants that warrants further in vitro and in vivo studies. This study provides a theoretical foundation for drug design and development targeting HCV G3 NS3/4A.

Multiple Functional Protein-Protein Interaction Interfaces Allosterically Regulate ATP-Binding in Cyclin-Dependent Kinase-1.

The ATP-dependent phosphorylation activity of cyclin-dependent kinase 1 (CDK1), an essential enzyme for cell cycle progression, is regulated by interactions with Cyclin-B, substrate, and Cks proteins. We have recently shown that active site acetylation in CDK1 abrogated binding to Cyclin-B which posits an intriguing long-range communication between the catalytic site and the protein-protein interaction (PPI) interface. Now, we demonstrate a general allosteric link between the CDK1 active site and all three of its PPI interfaces through atomistic molecular dynamics (MD) simulations. Specifically, we examined ATP binding free energies to CDK1 in native nonacetylated (K33wt) and acetylated (K33Ac) forms as well as the acetyl-mimic K33Q and the acetyl-null K33R mutant forms, which are accessible in vitro. In agreement with experiments, ATP binding is stronger in K33wt relative to the other three perturbed states. Free energy decomposition reveals, in addition to expected local changes, significant and selective nonlocal entropic responses to ATP binding/perturbation of K33 from the -helix, activation loop (A-loop), and - H segments in CDK1 which interface with Cyclin-B, substrate, and Cks proteins, respectively. Statistical analysis reveals that while entropic responses of protein segments to active site perturbations are on average correlated with their dynamical changes, such correlations are lost in about 9%-48% of the dataset depending on the segment. Besides proving the bi-directional communication between the active site and the CDK1:Cyclin-B interface, our study uncovers a hitherto unknown mode of ATP binding regulation by multiple PPI interfaces in CDK1.

De novo design of mini-binder proteins against IL-2 receptor β chain

IL-2 regulates the immune response by interacting with different IL-2 receptor (IL-2R) subunits. High dose of IL-2 binds to IL-2Rβγc heterodimer, which induce various side effects while activating immune function. Disrupting IL-2 and IL-2R interactions can block IL-2 mediated immune response. Here, we used a computational approach to de novo design mini-binder proteins against IL-2R β chain (IL-2Rβ) to block IL-2 signaling. The hydrophobic region where IL-2 binds to IL-2Rβ was selected and the promising binding mode was broadly explored. Three mini-binders with amino acid numbers ranging from 55 to 65 were obtained and binder 1 showed the best effects in inhibiting CTLL-2 cells proliferation and STAT5 phosphorylation. Molecular dynamics simulation showed that the binding of binder 1 to IL-2Rβ was stable; the free energy of binder1/IL-2Rβ complex was lower, indicating that the affinity of binder 1 to IL-2Rβ was higher than that of IL-2. Free energy decomposition suggested that the ARG35 and ARG131 of IL-2Rβ might be the key to improve the affinity of binder. Our efforts provided new insights in developing of IL-2R blocker, offering a potential strategy for ameliorating the side effects of IL-2 treatment.

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.

Molecular Generation, QSAR, and Molecular Dynamic Simulation Studies for Virtual Screening of DNA Polymerase Theta Inhibitors.

The machine learning-based QSAR modeling procedure, molecular generations, and molecular dynamic simulations were applied to virtually screen the DNA polymerase theta inhibitors. The DNA polymerase theta (Polθ or POLQ) is an attractive target for treatments of homologous recombination deficient (such as BRCA deficient) cancers. There are no approved drugs for targeting POLQ, and only one inhibitor is in Phase Ⅱclinical trials; thus, it is necessary to develop novel POLQ inhibitors. To build machine learning models that predict the bioactivities of POLQ inhibitors. To build molecular generation models that generate diverse molecules. To virtually screen the generated molecules by the machine learning models. To analyze the binding modes of the screening results by molecular dynamic simulations. In the present work, 325 inhibitors with POLQ polymerase domain bioactivities were Collected. Two machine learning methods, random forest and deep neural network, were used for building the ligand- and structure-based quantitative structure-activity relationship (QSAR) models. The substructure replacement-based method and transfer learning-based deep recurrent neural network method were used for molecular generations. Molecular docking and consensus QSAR models were carried out for virtual screening. The molecular dynamic simulations and MM/GBSA binding free energy calculation and decomposition were used to further analyze the screening results. The MCC values of the best ligand- and structure-based consensus QSAR models reached 0.651 and 0.361 for the test set, respectively. The machine learning-based docking scores had better-predicted ability to distinguish the highly and weakly active poses than the original docking scores. The 96490 molecules were generated by both molecular generation methods, and 10 molecules were retained by virtual screening. Four favorable interactions were concluded by molecular dynamic simulations. We hope that the screening results and the binding modes are helpful for designing the highly active POLQ polymerase inhibitors and the models of the molecular design workflow can be used as reliable tools for drug design.

Identification of mIDH1 R132C/S280F Inhibitors from Natural Products by Integrated Molecular Docking, Pharmacophore Modeling and Molecular Dynamics Simulations.

Mutant isocitrate dehydrogenase 1 (mIDH1) is a common driving factor in acute myeloid leukemia (AML), with the R132 mutation accounting for a high proportion. The U.S. Food and Drug Administration (FDA) approved Ivosidenib, a molecular entity that targets IDH1 with R132 mutations, as a promising therapeutic option for AML with mIDH1 in 2018. It was of concern that the occurrence of disease resistance or recurrence, attributed to the IDH1 R132C/S280F second site mutation, was observed in certain patients treated with Ivosidenib within the same year. Furthermore, it should be noted that most mIDH1 inhibitors demonstrated limited efficacy against mutations at this specific site. Therefore, there is an urgent need to investigate novel inhibitors targeting mIDH1 for combating resistance caused by IDH1 R132C/S280F mutations in AML. This study aimed to identify novel mIDH1 R132C/S280F inhibitors through an integrated strategy of combining virtual screening and dynamics simulations. First, 2000 hits were obtained through structure-based virtual screening of the COCONUT database, and hits with better scores than -10.67 kcal/mol were obtained through molecular docking. A total of 12 potential small molecule inhibitors were identified through pharmacophore modeling screening and Prime MM-GBSA. Dynamics simulations were used to study the binding modes between the positive drug and the first three hits and IDH1 carrying the R132C/S280F mutation. RMSD showed that the four dynamics simulation systems remained stable, and RMSF and Rg showed that the screened molecules have similar local flexibility and tightness to the positive drug. Finally, the lowest energy conformation, hydrogen bond analysis, and free energy decomposition results indicate that in the entire system the key residues LEU120, TRP124, TRP267, and VAL281 mainly contribute van der Waals forces to the interaction, while the key residues VAL276 and CYS379 mainly contribute electrostatic forces.

Inhibiting the oligomerization of mycobacterial DNA-directed RNA polymerase (RNAP) using natural compound via in-silico techniques

Mycobacterium tuberculosis (Mtb) is responsible for the spread of tuberculosis (TB). The current study employed virtual screening of 2569 natural compounds against the DNA-directed RNA polymerase (RNAP) of Mtb to identify the possible binders that can inhibit its function. The in-silico methodology included molecular docking to the compounds, further, the stability and flexibility of the best complexes were studied using molecular dynamics simulation, the MM/GBSA binding free energy technique with energy decomposition, PCA, FEL, steered MD simulation, and umbrella sampling. Individual virtual screenings were conducted for the five RNAP subunits (chains A, B, C, D, and E) to identify a compound capable of inhibiting RNAP oligomerization. A promising compound, isoestradiol 3-benzoate, exhibited a low binding score (−7.28 ​kcal/mol to −8.21 ​kcal/mol) and showed binding ability with all subunits of the protein. Thus, the five complexes with isoestradiol 3-benzoate were selected for molecular dynamics simulation analysis. Furthermore, RMSD showed that isoestradiol 3-benzoate bound with chain E showed the lowest RMSD of 0.49 ​nm, while with chains A and B it had the most stable and consistent conformations with RMSD of 1.75 ​nm and 1.2 ​nm, respectively. The H-bond between isoestradiol 3-benzoate and chains C and E showed the highest occupancy (58.27 ​%, 45.33 ​%, and 50.80 ​%, 42.25 ​%, 11.75 ​%). Moreover, the MMPBSA technique showed that isoestradiol 3-benzoate had a strong association with chains B and C (ΔGbind ​= ​−126.25 ​± ​2.03 and −129.27 ​± ​2.25). Additionally, free energy decomposition, PCA, FEL-steered MD simulation, and umbrella sampling were also performed to validate the association of the ligand with the protein. Isoestradiol 3-benzoate binds strongly to chains B and E; therefore, it should be considered as viable candidate for inhibiting the formation of RNAP protein complex, concluded in this study.

Molecular docking, 3D-QASR and molecular dynamics simulations of benzimidazole Pin1 inhibitors.

Pin1 (protein interacting with never-in-mitosis akinase-1) is a member of the family of peptidylprolyl cis-trans isomerases (PPIases) that specifically recognize and isomerize substrates containing phosphorylated Ser/Thr-Pro sequences. Pin1 is involved in many cellular processes and plays a key role in the cell cycle, transcriptional regulation, cell metabolism, proliferation and differentiation, and its abnormalities lead to degenerative and neoplastic diseases. Pin1 is highly expressed in human cancers and promotes the development of tumors by activating multiple oncogenes and inactivating multiple tumor suppressor genes, making it an attractive target for cancer therapy. In this study, we investigated the binding mechanism and conformational relationship between benzimidazole Pin1 inhibitors and Pin1 proteins by molecular docking, three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling, binding free energy calculations and decomposition, and molecular dynamics simulations. Molecular docking and molecular dynamics simulations disclosed the most likely binding pose of benzimidazoles with the Pin1 protein. The results of 3D-QSAR modeling indicated that electrostatic fields, hydrophobic fields and hydrogen bonding play important roles in the binding process of inhibitors to proteins. The binding free energy calculations and energy decomposition indicated that Lys63, Arg69, Cys113, Leu122, Met130, and Ser154 may be key residues in the binding of benzimidazole-based inhibitors to the Pin1 protein. This study provides an important theoretical basis for the design and optimization of benzimidazole compounds.

Free-energy decomposition of salt effects on the solubilities of small molecules and the role of excluded-volume effects.

The roles of cations and anions are different in the perturbation on solvation, and thus, the analyses of the separated contributions from cations and anions are useful to establish molecular pictures of ion-specific effects. In this work, we investigate the effects of cations, anions, and water separately in the solvation of n-alcohols and n-alkanes by free-energy decomposition. By utilising energy-representation theory of solvation, we address the contributions arising from the direct solute-solvent interactions and the excluded-volume effects. It is found that the change in solvation of n-alcohols and n-alkanes upon addition of salt depends primarily on the anion species. The direct interaction between the anion and solute is in agreement with the Setschenow coefficient in terms of the ranking of salting-in and salting-out for n-alkanes, which corresponds to the extent of accumulation of the anion on the solute surface. For each of the n-alcohols and n-alkanes examined, the excluded-volume component in the Setschenow coefficient is well correlated to the (total) Setschenow coefficient when the salt effects are concerned. The ranking of the excluded-volume component in the variation of the salt species is parallel to the water contribution, which is correlated further to the change in the water density upon the addition of the salt.

Accelerated molecular dynamics study of the interaction mechanism between small molecule inhibitors and phosphoglycerate mutase 1.

In 2020, cancer-related deaths reached 9.96 million globally, of which China accounted for 3 million, ranking first in the world. Phosphoglycerate mutase 1 (PGAM1) is a key metabolic enzyme in glycolysis, catalysing the conversion of 3-phosphoglycerate to 2-phosphoglycerate. Based on the excellent anticancer activity of PGMI-004A and HKB99, new small molecules with an anthraquinone core were synthesised to inhibit tumour growth. Developing small molecules with an anthraquinone core targeting PGAM1 may be an effective strategy for treating cancer. In this study, accelerated molecular dynamics (aMD) simulation, dynamic cross-correlation map (DCCM) calculation, principal component analysis (PCA) and free energy landscape (FEL) analysis were used to analyse conformational changes of PGAM1 caused by binding of inhibitors 8KX, 9HU and HKB. DCCM calculations and PCA showed that inhibitor binding significantly affected the kinetic behaviour of PGAM1 and conformational rearrangement of PGAM1. The binding ability and mechanism of 8KX, 9HU and HKB to PGAM1 were studied using the molecular mechanics generalised Born surface area (MM-GBSA) method. The results showed that compared with 8KX, the binding ability of 9HU and HKB to PGAM1 was enhanced by sulphonamide reversal and aminocarboxyl trifluoromethyl substitution. There were several hydrophobic interactions between inhibitors and PGAM1, providing significant contributions for inhibitor binding. Calculation of residue-based free energy decomposition revealed that F22, R90, Y92, L95, V112, W115, R116, V121, P123, P124, R191 and M206 were key residues of the PGAM1-inhibitor interaction and could be used as effective targets for designing drugs that inhibit the activity of PGAM1.

Exploring binding mechanisms of omicron spike protein with dolutegravir and etravirine by molecular dynamics simulation, principal component analysis, and free binding energy calculations

The COVID-19 pandemic was caused by the SARS-CoV-2 virus, frequent mutations occurred to the wild-type virus resulting in evolved new variants. The WHO classified the new variants as ‘Variants of Concern’. SARS-CoV-2 omicron evolved as the dominating variant at the end of 2021. Dolutegravir and etravirine were identified as inhibitors of SARS-CoV-2 entry to host cells in Omicron variants. In this study, combined in silico methods such as molecular docking, molecular dynamics, Principal component analysis, binding-free energy calculations, and Per Residues calculations were applied to investigate the mechanism of the bindings of the two inhibitors. The molecular dynamics results revealed the stability of dolutegravir-spike and etravirine-spike complexes in a similar manner to apo-protein. Dolutegravir and etravirine formed H-bonds and salt bridges with Omicron spike protein. The 2,4-difluoro phenyl moiety of dolutegravir plays an important role in binding the ligand. The binding mode and interactions of the two compounds indicated that Arg403, Tyr449, Tyr453, Arg493, Ser496, Arg498, Thr500, Tyr501, Gln502 and His505 are the key residues. The Principal Component Analyses suggested that no significant conformational changes happened for the two complexes during the simulations. Binding-free energy calculations showed that van der Waals interactions were the most important interactions for ligands’ binding. Per-residue free energy decomposition revealed residues Arg493, Arg498, and Tyr501 contributed to the binding of the ligands through H-bonds and salt bridges formation while His505 contributed to H-bonds and Pi-Pi stacking and Phe497 contributed to hydrophobic interactions between ligands and Omicron spike protein. Communicated by Ramaswamy H. Sarma

Insights into the selectivity of a brain-penetrant CDK4/6 vs CDK1/2 inhibitor for glioblastoma used in multiple replica molecular dynamics simulations

Cyclin dependent kinases (CDKs) play an important role in cell cycle regulation and their dysfunction is associated with many cancers. That is why CDKs have been attractive targets for the treatment of cancer. Glioblastoma is a cancer caused by the aberrant expression of CDK4/6, so exploring the mechanism of the selection of CDK4/6 toward inhibitors relative to the other family members CDK1/2 is essential. In this work, multiple replica molecular dynamics (MRMD) simulations, principal component analysis (PCA), free energy landscapes (FELs), molecular mechanics Poisson-Boltzmann/Generalized Born surface area (MM-PB/GBSA) and other methods were integrated to decipher the selectively binding mechanism of the inhibitor N1J to CDK4/6 and CDK1/2. Molecular electrostatic potential (MESP) analysis provides an explanation for the N1J selectivity. Residue-based free energy decomposition reveals that most of the hot residues are located at the same location of CDKs proteins, but the different types of residues in different proteins cause changes in binding energy, which is considered as a potential developmental direction to improve the selectivity of inhibitors to CDK4/6. These results provide insights into the source of inhibitor and CDK4/6 selectivity for the future development of more selective inhibitors. Communicated by Ramaswamy H. Sarma

Computational and in vitro targeting of HUVECs by ARA-Linker-TGFαL3 through VEGFR2

ABSTRACT Angiogenesis blockade represents a therapeutic strategy to inhibit the growth of the tumour and its progression and metastasis. Targeting the vascular endothelial growth factor receptor 2 (VEGFR2) is among the approaches approved as anti-cancer drugs. In this study, we examined ARA-linker-TGFαL3 and TGFαL3 binding affinity to VEGFR2. Next, the cytotoxicity effect of ARA-linker-TGFαL3 on human umbilical vein endothelial cells was evaluated. The 100 ns molecular dynamic simulation was employed to estimate the stability of the ligand–receptor interaction and the free energy decomposition was performed by molecular mechanics generalised Born surface area method. The MTT test evaluated the proliferation inhibition of ARA-linker-TGFαL3 and arazyme on HUVECs cells. Also, the change in VEGFR2 gene expression was investigated after treatment with recombinant proteins. Analysis of the trajectory using the root-mean-square deviation and fluctuation, radius of gyration, H-bond calculation, and binding free energy showed that ARA-linker-TGFαL3 formed the more stable complex with the D2 and D3 domains of VEGFR2 than TGFαL3. Meanwhile, ARA-linker-TGFαL3 revealed higher cytotoxicity and inhibition of VEGFR2 expression than arazyme. The results of the current study suggest the anti-angiogenesis effects of ARA-linker-TGFαL3 that can be useful in cancer therapy.

BINDING AFFINITIES OF SANGGENON DERIVATIVES AS PTP1B INHIBITORS; USING MOLECULAR DYNAMICS AND FREE ENERGY CALCULATIONS

Recently, protein tyrosine phosphatase 1B (PTP1B) inhibitors have become the frontier as possible targeting for anti-cancer and antidiabetic drugs. The contemporary observe represents a pc assisted version to investigate the importance of precise residues within the binding web site of PTP1B with numerous Sanggenon derivatives remoted from nature. Molecular dynamics (MD) simulations were performed to estimate the dynamics of the complexes, and absolute binding unfastened energies have been calculated with exclusive additives, and carried out through the usage of the Molecular Mechanics-Poisson-Boltzmann floor region (MM-PB/SA) and Generalized Born surface vicinity (MM-GB/SA) strategies. The effects show that the expected free energies of the complexes are normally constant with the available experimental statistics. MM/GBSA free energy decomposition analysis shows that the residues Asp29, Arg24, Met258, and , Arg254 in the second active site in PTP1B are crucial for the excessive selectivity of the inhibitors