Binding Conformation Research Articles

T4 gp32 forms dynamic, compacting filaments on ssDNA that reorganize through interprotein interactions.

Bacteriophage T4 gene 32 protein (gp32) is a model single-stranded DNA (ssDNA) binding protein, essential for DNA replication, recombination, and repair. gp32 forms cooperative filaments on ssDNA through interprotein interactions mediated by its N-terminal domain. Detailed understanding of gp32 filament structure and organization remains incomplete, particularly with respect to longer, biologically-relevant DNA lengths. We use optical tweezers and atomic force microscopy (AFM) to probe the structure and binding dynamics of gp32 on long (∼7-8 knt) ssDNA substrates. We find that cooperative binding of gp32 reduces the contour length of ssDNA by ∼40%, suggesting that gp32 filaments helically wind ssDNA, a binding conformation that may be favorable for the synthesis of dsDNA on the ssDNA template during replication. Additionally, gp32 binding gives rise to multiphasic DNA extension changes which reflect competition between increases in ssDNA persistence length and changes in its contour length. Notably, under conditions of high force or high protein concentration, cooperative gp32 clusters are able to modulate their binding footprint to drive elongation of the DNA molecule relative to its compacted state. This binding mode is unstable and marked by an additional phase of rapid protein dissociation not seen at lower concentrations, suggesting a possible mechanism for prompt gp32 dissociation during DNA replication.

Improving the CHARMM36m force field for arginine-phosphate interactions.

Noncovalent binding interactions between arginine and phosphate, such as the anchoring of transmembrane helices to phospholipid membrane interfaces or the binding of SH2 domain proteins with phosphorylated peptides, are essential for structural integrity or signal recognition in many biological processes. Using 120 ns long MD simulations, we find that arginine and phosphate have multiple binding conformations. The binding conformations are clustered into five groups and we compute binding energies for these clusters. Free energy perturbation (FEP) calculations are used to estimate the binding free energy using the current CHARMM36m and its CUFIX corrected version. Umbrella sampling (US) is used to generate the potential of mean force (PMF) along the inter-group distance reaction coordinate. Our results were compared with data from isothermal calorimetry (ITC) and suggest that neither the CHARMM36m nor the CUFIX-correct version match experiment and the ITC value is in between these force field estimates. Our current work focuses on the generation of improved force field parameters for arginine-phosphate interactions and experimental validation of these parameters for peptide-liposome binding.

Structures of LRP2 reveal a molecular machine for endocytosis

The low-density lipoprotein (LDL) receptor-related protein 2 (LRP2 or megalin) is representative of the phylogenetically conserved subfamily of giant LDL receptor-related proteins, which function in endocytosis and are implicated in diseases of the kidney and brain. Here, we report high-resolution cryoelectron microscopy structures of LRP2 isolated from mouse kidney, at extracellular and endosomal pH. The structures reveal LRP2 to be a molecular machine that adopts a conformation for ligand binding at the cell surface and for ligand shedding in the endosome. LRP2 forms a homodimer, the conformational transformation of which is governed by pH-sensitive sites at both homodimer and intra-protomer interfaces. A subset of LRP2 deleterious missense variants in humans appears to impair homodimer assembly. These observations lay the foundation for further understanding the function and mechanism of LDL receptors and implicate homodimerization as a conserved feature of the LRP receptor subfamily.

Computational prognostic evaluation of Alzheimer's drugs from FDA-approved database through structural conformational dynamics and drug repositioning approaches.

Novel drug design is time consuming and very expensive process having particularly low success rate. To overcome these difficulties, drug repositioning also referred to as drug repurposing approach is being used to predict the possible alternative therapeutic effects of drugs approved by FDA for different diseases. In this study, we designed a computational mechanism-based approach to fetch promising drugs from the pool of FDA approved drugs to screen them for treatment of Alzheimer's disease (AD). The binding interaction patterns and conformations of screened drugs within active region of MAP Kinase Activating Death Domain (MADD) protein were confirmed through molecular docking profiles. The possible associations of selected drugs with AD related genes were predicted by pharmacogenomics analysis and confirmed through data mining. Furthermore, the stability behavior of docked (Drug-MADD) complexes was checked by MD simulations. Taken together, five drugs displayed promising features and can be used as possible therapeutic agents in the treatment of AD after detailed in vitro studies and clinical assessments.

Water is a powerful dynamic allosteric modulator in rhodopsin activation.

Rhodopsin is an archetype for G protein-coupled receptors (GPCRs) which are membrane proteins involved in cellular signal transduction. Although GPCR X-ray structures show the presence of structural water molecules, their physiological role in the signaling process remains uncertain. Our previous work has shown that in lipid membranes rhodopsin activation is coupled to bulk water movements into the protein to stabilize the effector binding conformation [1,2]. Here we extend the experimental approach to explore modulation of the conformational energetics of rhodopsin activation in lipid membranes. We hypothesized that the thermodynamic stability of conformational substates of photoactivated rhodopsin is hydration mediated. Accordingly, we changed the osmotic stress on rhodopsin using different hydrophilic polymers including polyethylene glycols (PEGs), dextrans, polyvinylpyrrolidones, and their monomers. Reversible shifting of the metarhodopsin equilibrium due to the osmotic stress was probed using UV-visible spectroscopy. We observed that the rhodopsin activation is associated with a bulk influx of water due to the osmotic dehydration by large, excluded polymers which inhibit GPCR activation. By contrast small penetrable osmolytes and monomers have lower conformational entropy and showed a nonosmotic trend in rhodopsin activation. Small osmolytes penetrate the receptor core and stabilize the more expanded active state of rhodopsin until reaching a quantifiable saturation point. Both PEGs and dextrans with very high molar masses deviated in their trends from other large polymers due to a crowding effect, whereby extremely large osmolytes induce steric forces on rhodopsin and restrict their volume occupancy. Further studies of hydration effects on binding of the G-protein and receptor catalyzed exchange of GTP for GDP are expected to provide significant clues on the complete mechanism of G-protein binding and release

The kinetic and molecular docking analysis of interactions between three V-type nerve agents and four human cholinesterases

G and V-type nerve agents represent the most toxic chemical warfare agents. Their primary toxicity was the consequence of the covalent inhibition of the pivotal acetylcholinesterase (AChE), which induces overstimulation of cholinergic receptors and overaccumulation of cholines, eventually leading to death by respiratory arrest. The inhibitory and reactivation kinetics of cholinesterase (ChE) are essential for the toxicology and countermeasures of nerve agents. Medical defensive research on V-type nerve agents (V agents) has been mainly reported on VX and VR. Here we demonstrated the first systematical kinetic analysis between the type of ChE [native or recombinant human AChE and butyrylcholinesterase (BChE)] and three V agents, including VX, VR, and Vs, another isomer of VX, and highlighted the effects of native and recombinant ChE differences. The spontaneous reactivation and aging kinetics data of Vs-inhibited BChEs were firstly reported here.The results showed that AChE was more easily inhibited by three V agent compared to BChE, regardless of whether it is native or recombinant. The increased inhibitory potency order on AChE was VX, Vs, then VR, and on BChE was VX, then Vs and VR. The difference between native and recombinant ChE could influence the inhibition, aging, and spontaneous reactivation kinetics of three V agents, whether AChE or BChE, which was systematically revealed for the first time. For inhibition kinetics, the ki of three V agents for recombinant AChE was significantly higher than native AChE, and the stronger the inhibitory potency of V agents, the more pronounced difference in ki. In terms of aging and spontaneous reactivation kinetics, recombinant ChE was found to be more prone to spontaneous reactivation, but more resistant to aging compared to native ChE, particularly for AChE. The performed covalent molecular docking results partially explained the effects of differences between native and recombinant ChE on enzyme kinetics from the perspective of binding energy and conformation.

2-Aminothiazole-Oxadiazole Bearing N-Arylated Butanamides: Convergent Synthesis, Tyrosinase Inhibition, Kinetics, Structure-Activity Relationship, and Binding Conformations.

A multi-step synthesis of novel bi-heterocyclic N-arylated butanamides was consummated through a convergent strategy and the structures of these medicinal scaffolds, 7a-h, were corroborated using spectral techniques. The in vitro analysis of these hybrid molecules revealed their potent tyrosinase inhibition as compared to the standard used. The kinetics mechanism was investigated through Lineweaver-Burk plots which exposed that, 7f, inhibited tyrosinase enzyme non-competitively by forming the enzyme-inhibitor complex. The inhibition constants Ki calculated from Dixon plots for this compound was 0.025 μM. Their binding conformations were ascertained by in silico computational studies whereby these molecules disclosed good binding energy values (kcal/mol). So, it was anticipated from the current research that these bi-heterocyclic butanamides might be probed as imperative therapeutic agents for melanogenesis.

Identification of Natural Products Inhibiting SARS-CoV-2 by Targeting Viral Proteases: A Combined in Silico and in Vitro Approach.

In this study, an integrated in silico-in vitro approach was employed to discover natural products (NPs) active against SARS-CoV-2. The two SARS-CoV-2 viral proteases, i.e., main protease (Mpro) and papain-like protease (PLpro), were selected as targets for the in silico study. Virtual hits were obtained by docking more than 140,000 NPs and NP derivatives available in-house and from commercial sources, and 38 virtual hits were experimentally validated in vitro using two enzyme-based assays. Five inhibited the enzyme activity of SARS-CoV-2 Mpro by more than 60% at a concentration of 20 μM, and four of them with high potency (IC50 < 10 μM). These hit compounds were further evaluated for their antiviral activity against SARS-CoV-2 in Calu-3 cells. The results from the cell-based assay revealed three mulberry Diels-Alder-type adducts (MDAAs) from Morus alba with pronounced anti-SARS-CoV-2 activities. Sanggenons C (12), O (13), and G (15) showed IC50 values of 4.6, 8.0, and 7.6 μM and selectivity index values of 5.1, 3.1 and 6.5, respectively. The docking poses of MDAAs in SARS-CoV-2 Mpro proposed a butterfly-shaped binding conformation, which was supported by the results of saturation transfer difference NMR experiments and competitive 1H relaxation dispersion NMR spectroscopy.

A convergent multicomponent synthesis, spectral analysis, molecular modelling and docking studies of novel 2H-pyrido[1,2-a]pyrimidine-2,4(3H)-dione derivatives as potential anti-cervical cancer agents

A series of Novel hybrid 3,3-dimethyl-13-(substituted-phenyl)-3,4,5,13-tetrahydro-1H-pyrido[1′,2′:1,2]pyrimido[4,5-b]quinoline-1,12(2H)-dione derivatives were designed and chemically synthesized in useful yields. The newly synthesized compounds were characterized on the basis of spectral (FT-IR, 1H, 13C NMR, Mass spectral) analyses, and biologically screened in-vitro for their anti-cervical cancer activity against HeLa cancer cell line. The results of cytotoxic evaluation indicated that compounds 7a, 7b, 7c and 7e were appeared to have broad-spectrum cytotoxic activity with IC50 values of 270 µM, 320, 330, and 400 µM, against HeLa cell line. Compound 7a exhibited the most promising inhibitory activity against HeLa cell line as compared to 7b, 7c and 7e. Structural-Activity Relationship (SAR) results show that the presence of electron withdrawing substituents play an important role in the anti-cervical cancer activity of these tested compounds. Moreover, molecular docking studies were conducted to investigate the probable binding conformations of these anti-cancer agents and in-silico ADME (Absorption, Distribution, Metabolism, and Excretion) properties were calculated to predict physicochemical, lipophilicity, pharmacokinetics and medicinal properties of the target compounds.

Mechanistic Insights of Polyphenolic Compounds from Rosemary Bound to Their Protein Targets Obtained by Molecular Dynamics Simulations and Free-Energy Calculations.

Rosemary represents an important medicinal plant that has been attributed with various health-promoting properties, especially antioxidative, anti-inflammatory, and anticarcinogenic activities. Carnosic acid, carnosol, and rosmanol, as well as the phenolic acid ester rosmarinic acid, are the main compounds responsible for these actions. In our earlier research, we carried out an inverse molecular docking at the proteome scale to determine possible protein targets of the mentioned compounds. Here, we subjected the previously identified ligand-protein complexes with HIV-1 protease, K-RAS, and factor X to molecular dynamics simulations coupled with free-energy calculations. We observed that carnosic acid and rosmanol act as viable binders of the HIV-1 protease. In addition, carnosol represents a potential binder of the oncogene protein K-RAS. On the other hand, rosmarinic acid was characterized as a weak binder of factor X. We also emphasized the importance of water-mediated hydrogen-bond networks in stabilizing the binding conformation of the studied polyphenols, as well as in mechanistically explaining their promiscuous nature.

Naringenin protects against acute pancreatitis-associated intestinal injury by inhibiting NLRP3 inflammasome activation via AhR signaling.

Background: In this study, we examined the functions and mechanisms by which naringenin protects against SAP (severe acute pancreatitis)-related intestinal injury by modulating the AhR/NLRP3 signaling pathway. Material and methods: Fifteen healthy male C57BL/6 mice were randomly divided into SAP (n = 12) and normal (n = 3) groups. Mice in the SAP group received caerulein and lipopolysaccharide intraperitoneal injections and were then randomly assigned to the SAP, NAR, CH223191, and Dexamethasone (DEX) groups. Pathological changes in the pancreatic and intestinal mucosa were observed by Hematoxylin & Eosin (H&E) staining. In vitro, RAW264.7 cells were exposed to lipopolysaccharide and treated with naringenin. The levels of NLRP3, AhR, IL-1β, TNF, and IL-6 in the SAP model and RAW264.7 cells were evaluated by enzyme-linked immunosorbent assay (ELISA), quantitative real-time PCR (qRT-PCR), western blot, and immunohistochemistry. The nuclear translocation of AhR was shown by immunofluorescence. AutoDockTools was used to predict the conformations of naringenin-AhR binding, and PyMol 2.4 was used to visualize the conformations. Results: Mouse pancreatic and intestinal injury was alleviated by treatment with naringenin. Naringenin inhibited the activation of the NLRP3 inflammasome and inhibited damage to intestinal tight junctions. Moreover, naringenin increased AhR nuclear translocation and activated the AhR pathway. Conclusion: Naringenin can reduce SAP-associated intestinal injury by inhibiting the activation of the NLRP3 inflammasome via the AhR signaling pathway.

Big Data analytics for improved prediction of ligand binding and conformational selection.

This research introduces new machine learning and deep learning approaches, collectively referred to as Big Data analytics techniques that are unique to address the protein conformational selection mechanism for protein:ligands complexes. The novel Big Data analytics techniques presented in this work enables efficient data processing of a large number of protein:ligand complexes, and provides better identification of specific protein properties that are responsible for a high probability of correct prediction of protein:ligand binding. The GPCR proteins ADORA2A (Adenosine A2a Receptor), ADRB2 (Adrenoceptor Beta 2), OPRD1 (Opioid receptor Delta 1) and OPRK1 (Opioid Receptor Kappa 1) are examined in this study using Big Data analytics techniques, which can efficiently process a huge ensemble of protein conformations, and significantly enhance the prediction of binding protein conformation (i.e., the protein conformations that will be selected by the ligands for binding) about 10-38 times better than its random selection counterpart for protein conformation selection. In addition to providing a Big Data approach to the conformational selection mechanism, this also opens the door to the systematic identification of such "binding conformations" for proteins. The physico-chemical features that are useful in predicting the "binding conformations" are largely, but not entirely, shared among the test proteins, indicating that the biophysical properties that drive the conformation selection mechanism may, to an extent, be protein-specific for the protein properties used in this work.

In-silico docking and molecular dynamic introspective study of multiple targets of AChE with Rivastigmine and NMDA receptors with Riluzole for Alzheimer’s disease

The present study was initiated with PDB selection and validation where 11 acetylcholinesterase (AChE) and 4 N-methyl-D-aspartate receptor (NMDAR) proteins were considered for docking with Rivastigmine and Riluzole respectively. Out of the 15 proteins, selected significant binding was observed for AChE, with 5FPQ, and NMDA receptors with 5I2K. Molecular docking studies of 5FPQ/Rivastigmine complex displayed a binding score of −8.6 kcal/mol, and the predicted inhibitory concentration (Ki) was found to be 31 nM, whereas the 5I2K/Riluzole complex showed a binding score of −9.6 kcal/mol, with an inhibitory concentration (Ki) of 21 nM. Riluzole in complex with 5I2K formed predominant π-π stacking interactions with Tyr144, pi-alkyl interaction with Pro129, and conventional hydrogen bond with Phe130. In contrast, Rivastigmine in a complex with 5FPQ formed a hydrogen bond with Gln413 and pi-alkyl with Pro537. Molecular dynamics simulation study of both complexes 5FPQ/Rivastigmine and 5I2K/Riluzole exhibited stable RMSD, RMSF, Rg, and significant numbers of hydrogen bonds. From free energy landscape (FEL) analysis both complexes were observed to achieve global minima. Overall, molecular docking and MD simulation with subsequent binding free energies studies (MM-PBSA) elucidate the binding conformations and stability of these reprogrammed drugs in the AChE and NMDAR targets. From these in-silico predictions, it can be suggested that both Rivastigmine and Riluzole combination may provide better insights as a starting point combination therapy for the treatment of Alzheimer’s disease. Communicated by Ramaswamy H. Sarma

Design and Synthesis of Scopoletin Sulfonate Derivatives as Potential Insecticidal Agents.

(1) Background: Scopoletin and scoparone, two naturally occurring coumarins, have garnered considerable attention and have been introduced to the market in China due to their high insecticidal efficacy and low toxicity. To investigate the structure-activity relationship of these coumarins, a series of scopoletin derivatives with aryl sulfate at C7 and different substitutes at C3 were designed and synthesized, and their insecticidal activity was studied. (2) Methods: A total of 28 new scopoletin derivatives were designed and synthesized. Most target compounds exhibited moderate insecticidal activity against the phytophagous mite Tetranychus cinnabarinus and the brine shrimp Artemia salina. (3) Results: Among these compounds, compounds 5a and 5j possessed the best insecticidal activities against T. cinnabarinus, with LC50 values of 57.0 and 20.0 μg/mL, respectively, whereas that of the control drug was 15.0 μg/mL. Compound 4j exhibited selective insecticidal activities against A. salina, with an LC50 value of 9.36 μg/mL, whereas its LC50 value against T. cinnabarinus was 93.0 μg/mL. The enzymatic inhibitory activity on acetylcholinesterase (AChE) showed a consistent tendency with the insecticidal activity. Further molecular docking analyses predicted the binding conformations of these compounds, which showed a good correlation between the insecticidal activity and the binding scores. (4) Conclusions: In general, a decreased electron cloud density of the Δ3,4 olefinic bond is beneficial for improving the insecticidal activity against both T. cinnabarinus and A. salina. In addition, naphthyl or benzene groups with a sulfate ester at the C7 position could further improve the insecticidal activity against A. salina. AChE was implied to be a site of action for potential insecticidal activity. The results provide insight into the rational design of a new generation of effective coumarin insecticides.

Curcumin's mechanism of action against ischemic stroke: A network pharmacology and molecular dynamics study.

Ischemic stroke (IS) is one of the major global causes of death and disability. Because blood clots block the neural arteries provoking ischemia and hypoxia in the brain tissue, IS results in irreversible neurological damage. Available IS treatments are currently limited. Curcumin has gained attention for many beneficial effects after IS, including neuroprotective and anti-inflammatory; however, its precise mechanism of action should be further explored. With network pharmacology, molecular docking, and molecular dynamics (MD), this study aimed to comprehensively and systematically investigate the potential targets and molecular mechanisms of curcumin on IS. We screened 1096 IS-related genes, 234 potential targets of curcumin, and 97 intersection targets. KEGG and GO enrichment analyses were performed on these intersecting targets. The findings showed that the treatment of IS using curcumin is via influencing 177 potential signaling pathways (AGE-RAGE signaling pathway, p53 signaling pathway, necroptosis, etc.) and numerous biological processes (the regulation of neuronal death, inflammatory response, etc.), and the AGE-RAGE signaling pathway had the largest degree of enrichment, indicating that it may be the core pathway. We also constructed a protein-protein interaction network and a component-target-pathway network using network pharmacology. From these, five key targets were screened: NFKB1, TP53, AKT1, STAT3, and TNF. To predict the binding conformation and intermolecular affinities of the key targets and compounds, molecular docking was used, whose results indicated that curcumin exhibited strong binding activity to the key targets. Moreover, 100 ns MD simulations further confirmed the docking findings and showed that the curcumin-protein complex could be in a stable state. In conclusion, curcumin affects multiple targets and pathways to inhibit various important pathogenic mechanisms of IS, including oxidative stress, neuronal death, and inflammatory responses. This study offers fresh perspectives on the transformation of curcumin to clinical settings and the development of IS therapeutic agents.

PH dependence of the assembly mechanism and properties of poly(L-lysine) and poly(L-glutamic acid) complexes.

We show by extensive experimental characterization combined with molecular simulations that pH has a major impact on the assembly mechanism and properties of poly(L-lysine) (PLL) and poly(L-glutamic acid) (PGA) complexes. A combination of dynamic light scattering (DLS) and laser Doppler velocimetry (LDV) is used to assess the complexation, charge state, and other physical characteristics of the complexes, isothermal titration calorimetry (ITC) is used to examine the complexation thermodynamics, and circular dichroism (CD) is used to extract the polypeptides' secondary structure. For enhanced analysis and interpretation of the data, analytical ultracentrifugation (AUC) is used to define the precise molecular weights and solution association of the peptides. Molecular dynamics simulations reveal the associated intra- and intermolecular binding changes in terms of intrinsic vs. extrinsic charge compensation, the role of hydrogen bonding, and secondary structure changes, aiding in the interpretation of the experimental data. We combine the data to reveal the pH dependency of PLL/PGA complexation and the associated molecular level mechanisms. This work shows that not only pH provides a means to control complex formation but also that the associated changes in the secondary structure and binding conformation can be systematically used to control materials assembly. This gives access to rational design of peptide materials via pH control.

How are N-methylcarbamates encapsulated by β-cyclodextrin: insight into the binding mechanism.

Guest molecules containing chromophore groups encapsulated by β-cyclodextrin (β-CD) generate circular dichroism (CD) signals, which enables a preliminary prediction of their binding modes. However, the accurate determination of the representative binding conformation (RC) remains a challenging task due to the complex conformational space of these host-guest systems. Here, we combine a molecular dynamics/quantum mechanics/continuum solvent model (MD/QM/CSM) with induced circular dichroism (ICD) data (N. L. Pacioni, A. B. Pierini and A. V. Veglia, Spectrochim. Acta A Mol. Biomol. Spectrosc., 2013, 103, 319-324.) to explore the binding mechanism of β-CD with four N-methylcarbamate molecules: promecarb (PC), bendiocarb (BC), carbaryl (CY) and carbofuran (CF). In aqueous solution, their stability decreases as: PC > BC > CY > CF. Comparing the ECD spectra computed from TD-DFT with the ICD data can help eliminate many common binding configurations and identify the RC. The host-guest binding affinities (BAs) estimated using a ONIOM2(B971:PM6)/SMD model reproduce the measured binding trend, reveal the competition between the non-covalent interaction and solvent effect and explain the large difference in their binding modes. We also examine the fluctuations in the computed BA using similar structures.

Structural Dynamics of P‐Rex1 Complexed with Natural Leads Establishes the Protein as an Attractive Target for Therapeutics to Suppress Cancer Metastasis

Phosphatidylinositol 3,4,5‐trisphosphate‐ (PIP3‐) dependent Rac exchanger 1 (P‐Rex1) functions as Rho guanine nucleotide exchange factor and is activated by synergistic activity of Gβγ and PIP3 of the heterotrimeric G protein. P‐Rex1 activates Rac GTPases for regulating cell invasion and migration and promotes metastasis in several human cancers including breast, prostate, and skin cancer. The protein is a promising therapeutic target because of its multifunction roles in human cancers. Herein, the present study attempts to identify selective P‐Rex1 natural inhibitors by targeting PIP3‐binding pocket using large‐size multiple natural molecule libraries. Each library was filtered subsequently in FAF‐Drugs4 based on Lipinski’s rule of five (RO5), toxicity, and filter pan assay interference compounds (PAINS). The output hits were virtually screened at the PIP3‐binding pocket through PyRx AutoDock Vina and cross‐checked by GOLD. The best binders at the PIP3‐binding pocket were prioritized using a comparative analysis of the docking scores. Top‐ranked two compounds with high GOLD fitness score (&gt;80) and lowest AutoDock binding energy (&lt; ‐12.7 kcal/mol) were complexed and deciphered for molecular dynamics along with control‐P‐Rex1 complex to validate compound binding conformation and disclosed binding interaction pattern. Both the systems were seen in good equilibrium, and along the simulation time, the compounds are in strong contact with the P‐Rex1 PIP3‐binding site. Hydrogen bonding analysis towards simulation end identified the formation of 16 and 22 short‐ and long‐distance hydrogen bonds with different percent of occupancy to the PIP3 residues for compound I and compound 2, respectively. Radial distribution function (RDF) analysis of the key hydrogen bonds between the compound and the PIP3 residues demonstrated a strong affinity of the compounds to the mentioned PIP3 pocket. Additionally, MMGB/PBSA energies were performed that confirmed the dominance of Van der Waals energy in complex formation along with favorable contribution from hydrogen bonding. These findings were also cross‐validated by a more robust WaterSwap binding energy predictor, and the results are in good agreement with a strong binding affinity of the compounds for the protein. Lastly, the key contribution of residues in interaction with the compounds was understood by binding free energy decomposition and alanine scanning methods. In short, the results of this study suggest that P‐Rex1 is a good druggable target to suppress cancer metastasis; therefore, the screened druglike molecules of this study need in vitro and in vivo anti‐P‐Rex1 validation and may serve as potent leads to fight cancer.

Design of a novel multi-epitopes based vaccine against brucellosis

Brucella melitensis is a gram-negative coccobacillus that causes brucellosis in humans. The lack of effective treatment and increasing antibiotic-resistant patterns shown by B. melitensis, warrant the search for novel therapeutics. In this study, comprehensive bioinformatics, reverse vaccinology, and biophysics techniques were employed to design a novel multi-epitopes based vaccine (MEBV) against B. melitensis. Core proteomics, subtractive proteomics and immunoinformatic studies revealed three core proteins: Flagellar hook protein (FlgE), TonB-dependent receptor, and Porin family protein as promising vaccine targets. The proteins have exposed topology, and are antigenic, and adhesive. Furthermore, B and T cell epitopes were predicted from these proteins. Highly antigenic, immunogenic, non-toxic and non-allergenic epitopes were shortlisted and used in the MEBV design. The designed MEBV also showed stable docked conformation with different immune receptors such as MHC-I, MHC-II, and TLR-4. The global energy of selected docked complexes was as; solution 4 of MEBV-TLR-4 (−45.73 kJ/mol), solution 5 of MEBV-MHC-I (−20.94 kJ/mol), and solution 1 of MEBV-MHC-II (−3.45 kJ/mol). Molecular dynamics simulation studies unveiled a steady root mean square deviation (RMSD) pattern for the systems. However, all of them were stable in terms of intermolecular binding conformation and chemical interactions. Further, the systems showed robust binding energies with net binding energy < −300 kcal/mol. The van der Waals and electrostatic energies were the dominating energies and were found as intermolecular stabilizing factors. The vaccine was also predicted to generate promising immunological responses and thus could be an attractive candidate to be evaluated in experimental studies.

A flexible data-free framework for structure-based de novo drug design with reinforcement learning.

Contemporary structure-based molecular generative methods have demonstrated their potential to model the geometric and energetic complementarity between ligands and receptors, thereby facilitating the design of molecules with favorable binding affinity and target specificity. Despite the introduction of deep generative models for molecular generation, the atom-wise generation paradigm that partially contradicts chemical intuition limits the validity and synthetic accessibility of the generated molecules. Additionally, the dependence of deep learning models on large-scale structural data has hindered their adaptability across different targets. To overcome these challenges, we present a novel search-based framework, 3D-MCTS, for structure-based de novo drug design. Distinct from prevailing atom-centric methods, 3D-MCTS employs a fragment-based molecular editing strategy. The fragments decomposed from small-molecule drugs are recombined under predefined retrosynthetic rules, offering improved drug-likeness and synthesizability, overcoming the inherent limitations of atom-based approaches. Leveraging multi-threaded parallel simulations combined with a real-time energy constraint-based pruning strategy, 3D-MCTS achieves remarkable efficiency. At a fixed computational cost, it outperforms other state-of-the-art (SOTA) methods by producing molecules with enhanced binding affinity. Furthermore, its fragment-based approach ensures the generation of more dependable binding conformations, exhibiting a success rate 43.6% higher than that of other SOTAs. This advantage becomes even more pronounced when handling targets that significantly deviate from the training dataset. 3D-MCTS is capable of achieving thirty times more hits with high binding affinity than traditional virtual screening methods, which demonstrates the superior ability of 3D-MCTS to explore chemical space. Moreover, the flexibility of our framework makes it easy to incorporate domain knowledge during the process, thereby enabling the generation of molecules with desirable pharmacophores and enhanced binding affinity. The adaptability of 3D-MCTS is further showcased in metalloprotein applications, highlighting its potential across various drug design scenarios.