AlphaFold2-Enabled Atomistic Modeling of Structure, Conformational Ensembles, and Binding Energetics of the SARS-CoV-2 Omicron BA.2.86 Spike Protein with ACE2 Host Receptor and Antibodies: Compensatory Functional Effects of Binding Hotspots in Modulating Mechanisms of Receptor Binding and Immune Escape.

The latest wave of SARS-CoV-2 Omicron variants displayed a growth advantage and increased viral fitness through convergent evolution of functional hotspots that work synchronously to balance fitness requirements for productive receptor binding and efficient immune evasion. In this study, we combined AlphaFold2-based structural modeling approaches with atomistic simulations and mutational profiling of binding energetics and stability for prediction and comprehensive analysis of the structure, dynamics, and binding of the SARS-CoV-2 Omicron BA.2.86 spike variant with ACE2 host receptor and distinct classes of antibodies. We adapted several AlphaFold2 approaches to predict both the structure and conformational ensembles of the Omicron BA.2.86 spike protein in the complex with the host receptor. The results showed that the AlphaFold2-predicted structural ensemble of the BA.2.86 spike protein complex with ACE2 can accurately capture the main conformational states of the Omicron variant. Complementary to AlphaFold2 structural predictions, microsecond molecular dynamics simulations reveal the details of the conformational landscape and produced equilibrium ensembles of the BA.2.86 structures that are used to perform mutational scanning of spike residues and characterize structural stability and binding energy hotspots. The ensemble-based mutational profiling of the receptor binding domain residues in the BA.2 and BA.2.86 spike complexes with ACE2 revealed a group of conserved hydrophobic hotspots and critical variant-specific contributions of the BA.2.86 convergent mutational hotspots R403K, F486P, and R493Q. To examine the immune evasion properties of BA.2.86 in atomistic detail, we performed structure-based mutational profiling of the spike protein binding interfaces with distinct classes of antibodies that displayed significantly reduced neutralization against the BA.2.86 variant. The results revealed the molecular basis of compensatory functional effects of the binding hotspots, showing that BA.2.86 lineage may have evolved to outcompete other Omicron subvariants by improving immune evasion while preserving binding affinity with ACE2 via through a compensatory effect of R493Q and F486P convergent mutational hotspots. This study demonstrated that an integrative approach combining AlphaFold2 predictions with complementary atomistic molecular dynamics simulations and robust ensemble-based mutational profiling of spike residues can enable accurate and comprehensive characterization of structure, dynamics, and binding mechanisms of newly emerging Omicron variants.

Exploring conformational landscapes and binding mechanisms of convergent evolution for the SARS-CoV-2 spike Omicron variant complexes with the ACE2 receptor using AlphaFold2-based structural ensembles and molecular dynamics simulations.

In this study, we combined AlphaFold-based approaches for atomistic modeling of multiple protein states and microsecond molecular simulations to accurately characterize conformational ensembles evolution and binding mechanisms of convergent evolution for the SARS-CoV-2 spike Omicron variants BA.1, BA.2, BA.2.75, BA.3, BA.4/BA.5 and BQ.1.1. We employed and validated several different adaptations of the AlphaFold methodology for modeling of conformational ensembles including the introduced randomized full sequence scanning for manipulation of sequence variations to systematically explore conformational dynamics of Omicron spike protein complexes with the ACE2 receptor. Microsecond atomistic molecular dynamics (MD) simulations provide a detailed characterization of the conformational landscapes and thermodynamic stability of the Omicron variant complexes. By integrating the predictions of conformational ensembles from different AlphaFold adaptations and applying statistical confidence metrics we can expand characterization of the conformational ensembles and identify functional protein conformations that determine the equilibrium dynamics for the Omicron spike complexes with the ACE2. Conformational ensembles of the Omicron RBD-ACE2 complexes obtained using AlphaFold-based approaches for modeling protein states and MD simulations are employed for accurate comparative prediction of the binding energetics revealing an excellent agreement with the experimental data. In particular, the results demonstrated that AlphaFold-generated extended conformational ensembles can produce accurate binding energies for the Omicron RBD-ACE2 complexes. The results of this study suggested complementarities and potential synergies between AlphaFold predictions of protein conformational ensembles and MD simulations showing that integrating information from both methods can potentially yield a more adequate characterization of the conformational landscapes for the Omicron RBD-ACE2 complexes. This study provides insights in the interplay between conformational dynamics and binding, showing that evolution of Omicron variants through acquisition of convergent mutational sites may leverage conformational adaptability and dynamic couplings between key binding energy hotspots to optimize ACE2 binding affinity and enable immune evasion.

Comparative phenotypic and genotypic analysis of community-acquired and hospital-acquired intra-abdominal infections among liver transplanted patients.

AIM: During liver transplantation, both hospital-acquired (HA) and community-acquired (CA) intra-abdominal infections (IAIs) are involved causing life-threatening diseases. Therefore, comparative studies of aerobic and facultative anaerobic HA-IAIs and CA-IAIs after liver transplantation surgery are necessary. METHODS AND RESULTS: The species of detected isolates (310) from intra-abdominal fluid were identified and classified into hospital-acquired intra-abdominal infections (HA-IAIs) and community-acquired intra-abdominal infections (CA-IAIs). Klebsiella pneumoniae, Escherichia coli, Pseudomonas aeruginosa, and Acinetobacter baumannii were the most commonly detected species. The resistant phenotypes were commonly detected among the HA-IAIs; however, the virulent phenotypes were the predominant strains of CA-IAIs. Regrettably, the resistance profiles were shocking, indicating the inefficacy of monotherapy in treating these isolates. Therefore, we confirmed the use of empirical combination therapies of amikacin and meropenem for treating all IAIs (FICI ≤ 0.5). Unfortunately, the high diversity and low clonality of all identified HA and CA-IAIs were announced with D-value in the range of 0.992-1. CONCLUSION: This diversity proves that there are infinite numbers of infection sources inside and outside healthcare centers.

Structural and Dynamical Basis of VP35-RBD Inhibition by Marine Fungi Compounds to Combat Marburg Virus Infection.

The Marburg virus (MBV), a deadly pathogen, poses a serious threat to world health due to the lack of effective treatments, calling for an immediate search for targeted and efficient treatments. In this study, we focused on compounds originating from marine fungi in order to identify possible inhibitory compounds against the Marburg virus (MBV) VP35-RNA binding domain (VP35-RBD) using a computational approach. We started with a virtual screening procedure using the Lipinski filter as a guide. Based on their docking scores, 42 potential candidates were found. Four of these compounds-CMNPD17596, CMNPD22144, CMNPD25994, and CMNPD17598-as well as myricetin, the control compound, were chosen for re-docking analysis. Re-docking revealed that these particular compounds had a higher affinity for MBV VP35-RBD in comparison to the control. Analyzing the chemical interactions revealed unique binding properties for every compound, identified by a range of Pi-cation interactions and hydrogen bond types. We were able to learn more about the dynamic behaviors and stability of the protein-ligand complexes through a 200-nanosecond molecular dynamics simulation, as demonstrated by the compounds' consistent RMSD and RMSF values. The multidimensional nature of the data was clarified by the application of principal component analysis, which suggested stable conformations in the complexes with little modification. Further insight into the energy profiles and stability states of these complexes was also obtained by an examination of the free energy landscape. Our findings underscore the effectiveness of computational strategies in identifying and analyzing potential inhibitors for MBV VP35-RBD, offering promising paths for further experimental investigations and possible therapeutic development against the MBV.

Ensemble-Based Mutational Profiling and Network Analysis of the SARS-CoV-2 Spike Omicron XBB Lineages for Interactions with the ACE2 Receptor and Antibodies: Cooperation of Binding Hotspots in Mediating Epistatic Couplings Underlies Binding Mechanism and Immune Escape.

In this study, we performed a computational study of binding mechanisms for the SARS-CoV-2 spike Omicron XBB lineages with the host cell receptor ACE2 and a panel of diverse class one antibodies. The central objective of this investigation was to examine the molecular factors underlying epistatic couplings among convergent evolution hotspots that enable optimal balancing of ACE2 binding and antibody evasion for Omicron variants BA.1, BA2, BA.3, BA.4/BA.5, BQ.1.1, XBB.1, XBB.1.5, and XBB.1.5 + L455F/F456L. By combining evolutionary analysis, molecular dynamics simulations, and ensemble-based mutational scanning of spike protein residues in complexes with ACE2, we identified structural stability and binding affinity hotspots that are consistent with the results of biochemical studies. In agreement with the results of deep mutational scanning experiments, our quantitative analysis correctly reproduced strong and variant-specific epistatic effects in the XBB.1.5 and BA.2 variants. It was shown that Y453W and F456L mutations can enhance ACE2 binding when coupled with Q493 in XBB.1.5, while these mutations become destabilized when coupled with the R493 position in the BA.2 variant. The results provided a molecular rationale of the epistatic mechanism in Omicron variants, showing a central role of the Q493/R493 hotspot in modulating epistatic couplings between convergent mutational sites L455F and F456L in XBB lineages. The results of mutational scanning and binding analysis of the Omicron XBB spike variants with ACE2 receptors and a panel of class one antibodies provide a quantitative rationale for the experimental evidence that epistatic interactions of the physically proximal binding hotspots Y501, R498, Q493, L455F, and F456L can determine strong ACE2 binding, while convergent mutational sites F456L and F486P are instrumental in mediating broad antibody resistance. The study supports a mechanism in which the impact on ACE2 binding affinity is mediated through a small group of universal binding hotspots, while the effect of immune evasion could be more variant-dependent and modulated by convergent mutational sites in the conformationally adaptable spike regions.

Inhibition of SARS-CoV-2 NSP-15 by Uridine-5'-Monophosphate Analogues Using QSAR Modelling, Molecular Dynamics Simulations, and Free Energy Landscape.

SARS-CoV-2 is accountable for severe social and economic disruption around the world causing COVID-19. Non-structural protein-15 (NSP15) possesses a domain that is vital to the viral life cycle and is known as uridylate-specific endoribonuclease (EndoU). This domain binds to the uridine 5'-monophosphate (U5P) so that the protein may carry out its native activity. It is considered a vital drug target to inhibit the growth of the virus. Thus, in this current study, ML-based QSAR and virtual screening of U5P analogues targeting Nsp15 were performed to identify potential molecules against SARS-CoV-2. Screening of 816 unique U5P analogues using ML-based QSAR identified 397 compounds ranked on their predicted bioactivity (pIC50). Further, molecular docking and hydrogen bond interaction analysis resulted in the selection of the top three compounds (53309102, 57398422, and 76314921). Molecular dynamics simulation of the most promising compounds showed that two molecules 53309102 and 57398422 acted as potential binders of Nsp15. The compound was able to inhibit nsp15 activity as it was successfully bound to the active site of the nsp15 protein. This was achieved by the formation of relevant contacts with enzymatically critical amino acid residues (His235, His250, and Lys290). Principal component analysis and free energy landscape studies showed stable complex formation while MM/GBSA calculation showed lower binding energies for 53309102 (ΔGTOTAL = -29.4 kcal/mol) and 57398422 (ΔGTOTAL = -39.4 kcal/mol) compared to the control U5P (ΔGTOTAL = -18.8 kcal/mol). This study aimed to identify analogues of U5P inhibiting the NSP15 function that potentially could be used for treating COVID-19.

Consumption of aphrodisiac drugs without prescription among men in Saudi Arabia: cross-sectional study.

Background: The prevalence and patterns of aphrodisiac drug consumption without prescription among men in Saudi Arabia remain underexplored, with limited empirical evidence available. Given the potential health implications and societal considerations, a comprehensive investigation is warranted. Aim: Assess the Prevalence, pattern of use and the associated factors of Aphrodisiac drugs consumption without prescription among men at Najran City, Saudi Arabia. Methods: Employing a cross-sectional descriptive study, 500 participants were included through convenience sampling. The utilized questionnaires covered a range of data, including socio-demographic information, patterns of aphrodisiac use, knowledge about aphrodisiacs, lifestyle details, a sexual health inventory for men, and a perceived stress level scale. Results: The study reveals a significant prevalence of unsanctioned aphrodisiac drug use (31%) among men in Najran City, Saudi Arabia, with a majority (79.3%) consuming these substances four times monthly. Associated disparities in knowledge, lifestyle, stress, and sexual function underscore the urgent need for policy interventions and tailored health education initiatives for this demographic. Conclusion: Approximately one-third of the sampled population engaged in the unsanctioned use of aphrodisiac drugs, with the majority utilizing them four times monthly. Tablets emerged as the most prevalent form of consumption. Commonly cited motives and justifications included peer influence and the perceived safety of aphrodisiacs. Influential factors encompassed levels of knowledge, lifestyle, stress levels, erectile function, age, education, and the number of wives. Recommendations: Urgent policy interventions are warranted to regulate the acquisition and distribution of aphrodisiacs. Tailored health education initiatives should be implemented for married and prospective married men.

Exploring and Learning the Universe of Protein Allostery Using Artificial Intelligence Augmented Biophysical and Computational Approaches.

Allosteric mechanisms are commonly employed regulatory tools used by proteins to orchestrate complex biochemical processes and control communications in cells. The quantitative understanding and characterization of allosteric molecular events are among major challenges in modern biology and require integration of innovative computational experimental approaches to obtain atomistic-level knowledge of the allosteric states, interactions, and dynamic conformational landscapes. The growing body of computational and experimental studies empowered by emerging artificial intelligence (AI) technologies has opened up new paradigms for exploring and learning the universe of protein allostery from first principles. In this review we analyze recent developments in high-throughput deep mutational scanning of allosteric protein functions; applications and latest adaptations of Alpha-fold structural prediction methods for studies of protein dynamics and allostery; new frontiers in integrating machine learning and enhanced sampling techniques for characterization of allostery; and recent advances in structural biology approaches for studies of allosteric systems. We also highlight recent computational and experimental studies of the SARS-CoV-2 spike (S) proteins revealing an important and often hidden role of allosteric regulation driving functional conformational changes, binding interactions with the host receptor, and mutational escape mechanisms of S proteins which are critical for viral infection. We conclude with a summary and outlook of future directions suggesting that AI-augmented biophysical and computer simulation approaches are beginning to transform studies of protein allostery toward systematic characterization of allosteric landscapes, hidden allosteric states, and mechanisms which may bring about a new revolution in molecular biology and drug discovery.

Markov State Models and Perturbation-Based Approaches Reveal Distinct Dynamic Signatures and Hidden Allosteric Pockets in the Emerging SARS-Cov-2 Spike Omicron Variant Complexes with the Host Receptor: The Interplay of Dynamics and Convergent Evolution Modulates Allostery and Functional Mechanisms.

The new generation of SARS-CoV-2 Omicron variants displayed a significant growth advantage and increased viral fitness by acquiring convergent mutations, suggesting that the immune pressure can promote convergent evolution leading to the sudden acceleration of SARS-CoV-2 evolution. In the current study, we combined structural modeling, microsecond molecular dynamics simulations, and Markov state models to characterize conformational landscapes and identify specific dynamic signatures of the SARS-CoV-2 spike complexes with the host receptor ACE2 for the recently emerged highly transmissible XBB.1, XBB.1.5, BQ.1, and BQ.1.1 Omicron variants. Microsecond simulations and Markovian modeling provided a detailed characterization of the functional conformational states and revealed the increased thermodynamic stabilization of the XBB.1.5 subvariant, which can be contrasted to more dynamic BQ.1 and BQ.1.1 subvariants. Despite considerable structural similarities, Omicron mutations can induce unique dynamic signatures and specific distributions of the conformational states. The results suggested that variant-specific changes of the conformational mobility in the functional interfacial loops of the receptor-binding domain in the SARS-CoV-2 spike protein can be fine-tuned through crosstalk between convergent mutations which could provide an evolutionary path for modulation of immune escape. By combining atomistic simulations and Markovian modeling analysis with perturbation-based approaches, we determined important complementary roles of convergent mutation sites as effectors and receivers of allosteric signaling involved in modulation of conformational plasticity and regulation of allosteric communications. This study also revealed hidden allosteric pockets and suggested that convergent mutation sites could control evolution and distribution of allosteric pockets through modulation of conformational plasticity in the flexible adaptable regions.

Association of early mobility with the incidence of deep-vein thrombosis and mortality among critically ill patients: a post hoc analysis of PREVENT trial.

BACKGROUND: This study assessed the mobility levels among critically ill patients and the association of early mobility with incident proximal lower-limb deep-vein thrombosis and 90-day mortality. METHODS: This was a post hoc analysis of the multicenter PREVENT trial, which evaluated adjunctive intermittent pneumatic compression in critically ill patients receiving pharmacologic thromboprophylaxis with an expected ICU stay ≥ 72 h and found no effect on the primary outcome of incident proximal lower-limb deep-vein thrombosis. Mobility levels were documented daily up to day 28 in the ICU using a tool with an 8-point ordinal scale. We categorized patients according to mobility levels within the first 3 ICU days into three groups: early mobility level 4-7 (at least active standing), 1-3 (passive transfer from bed to chair or active sitting), and 0 (passive range of motion). We evaluated the association of early mobility and incident lower-limb deep-vein thrombosis and 90-day mortality by Cox proportional models adjusting for randomization and other co-variables. RESULTS: Of 1708 patients, only 85 (5.0%) had early mobility level 4-7 and 356 (20.8%) level 1-3, while 1267 (74.2%) had early mobility level 0. Patients with early mobility levels 4-7 and 1-3 had less illness severity, femoral central venous catheters, and organ support compared to patients with mobility level 0. Incident proximal lower-limb deep-vein thrombosis occurred in 1/85 (1.3%) patients in the early mobility 4-7 group, 7/348 (2.0%) patients in mobility 1-3 group, and 50/1230 (4.1%) patients in mobility 0 group. Compared with early mobility group 0, mobility groups 4-7 and 1-3 were not associated with differences in incident proximal lower-limb deep-vein thrombosis (adjusted hazard ratio [aHR] 1.19, 95% confidence interval [CI] 0.16, 8.90; p = 0.87 and 0.91, 95% CI 0.39, 2.12; p = 0.83, respectively). However, early mobility groups 4-7 and 1-3 had lower 90-day mortality (aHR 0.47, 95% CI 0.22, 1.01; p = 0.052, and 0.43, 95% CI 0.30, 0.62; p < 0.0001, respectively). CONCLUSIONS: Only a small proportion of critically ill patients with an expected ICU stay ≥ 72 h were mobilized early. Early mobility was associated with reduced mortality, but not with different incidence of deep-vein thrombosis. This association does not establish causality, and randomized controlled trials are required to assess whether and to what extent this association is modifiable. TRIAL REGISTRATION: The PREVENT trial is registered at ClinicalTrials.gov, ID: NCT02040103 (registered on 3 November 2013) and Current controlled trials, ID: ISRCTN44653506 (registered on 30 October 2013).

Pomegranate peel extract is an effective agent against MDR bacteria.

Multidrug-resistant (MDR) bacteria are one of the major public health threats facing humanity. Infections with MDR strains are difficult or impossible to treat with standard antibiotics leading to severe illnesses and even deaths. The spread of MDR bacteria has necessitated the search for alternative approaches that tackle MDR pathogens. Natural plants can be utilized as alternative therapeutic agents against the rise of MDR bacteria. In this study, we aimed to assess the antimicrobial activity of pomegranate peel extracts (PPE) against MDR clinical isolates. A total of 9 clinical isolates (8 MDR and 1 non-MDR clinical isolates) were collected and examined for their susceptibility to PPE. Using the zone of inhibition assay, 4 isolates (S. aureus, three MRSA isolates, Vancomycin-resistant Enterococci (VRE), and Acinetobacter baumannii) were sensitive to PPE. In Broth assay, 4 mg/ml PPE significantly reduced the growth (S. aureus, three MRSA isolates, Vancomycin-resistant Enterococci (VRE), and Acinetobacter baumannii), while 40 mg/ml PPE either significantly reduced or completely inhibited the growth of the isolates. The minimum bactericidal concentration (MBC) of PPE against S. aureus and MRSA-88 was 10 mg/ml. This study showed the potential of PPE as an alternative compound for treating infections caused by PPE-sensitive MDR bacteria.

Probing conformational landscapes of binding and allostery in the SARS-CoV-2 omicron variant complexes using microsecond atomistic simulations and perturbation-based profiling approaches: hidden role of omicron mutations as modulators of allosteric signaling and epistatic relationships.

In this study, we systematically examine the conformational dynamics, binding and allosteric communications in the Omicron BA.1, BA.2, BA.3 and BA.4/BA.5 spike protein complexes with the ACE2 host receptor using molecular dynamics simulations and perturbation-based network profiling approaches. Microsecond atomistic simulations provided a detailed characterization of the conformational landscapes and revealed the increased thermodynamic stabilization of the BA.2 variant which can be contrasted with the BA.4/BA.5 variants inducing a significant mobility of the complexes. Using the dynamics-based mutational scanning of spike residues, we identified structural stability and binding affinity hotspots in the Omicron complexes. Perturbation response scanning and network-based mutational profiling approaches probed the effect of the Omicron mutations on allosteric interactions and communications in the complexes. The results of this analysis revealed specific roles of Omicron mutations as conformationally plastic and evolutionary adaptable modulators of binding and allostery which are coupled to the major regulatory positions through interaction networks. Through perturbation network scanning of allosteric residue potentials in the Omicron variant complexes performed in the background of the original strain, we characterized regions of epistatic couplings that are centered around the binding affinity hotspots N501Y and Q498R. Our results dissected the vital role of these epistatic centers in regulating protein stability, efficient ACE2 binding and allostery which allows for accumulation of multiple Omicron immune escape mutations at other sites. Through integrative computational approaches, this study provides a systematic analysis of the effects of Omicron mutations on thermodynamics, binding and allosteric signaling in the complexes with ACE2 receptor.

Prophylactic Inferior Vena Cava Filters for Venous Thromboembolism in Adults With Trauma: An Updated Systematic Review and Meta-Analysis.

Background: Trauma is an independent risk factor for venous thromboembolism (VTE). Due to contraindications or delay in starting pharmacological prophylaxis among trauma patients with a high risk of bleeding, the inferior vena cava (IVC) filter has been utilized as alternative prevention for pulmonary embolism (PE). Albeit, its clinical efficacy has remained uncertain. Therefore, we performed an updated systematic review and meta-analysis on the effectiveness and safety of prophylactic IVC filters in severely injured patients. Methods: Three databases (MEDLINE, EMBASE, and Cochrane) were searched from August 1, 2012, to October 27, 2021. Independent reviewers performed data extraction and quality assessment. Relative risk (RR) at 95% confidence interval (CI) pooled in a randomized meta-analysis. A parallel clinical practice guideline committee assessed the certainty of evidence using the GRADE approach. The outcomes of interest included VTE, PE, deep venous thrombosis, mortality, and IVC filter complications. Results: We included 10 controlled studies (47 140 patients), of which 3 studies (310 patients) were randomized controlled trials (RCTs) and 7 were observational studies (46 830 patients). IVC filters demonstrated no significant reduction in PE and fatal PE (RR, 0.27; 95% CI, 0.06-1.28 and RR, 0.32; 95% CI, 0.01-7.84, respectively) by pooling RCTs with low certainty. However, it demonstrated a significant reduction in the risk of PE and fatal PE (RR, 0.25; 95% CI, 0.12-0.55 and RR, 0.09; 95% CI, 0.011-0.81, respectively) by pooling observational studies with very low certainty. IVC filter did not improve mortality in both RCTs and observational studies (RR, 1.44; 95% CI, 0.86-2.43 and RR, 0.63; 95% CI, 0.3-1.31, respectively). Conclusion: In trauma patients, moderate risk reduction of PE and fatal PE was demonstrated among observational data but not RCTs. The desirable effect is not robust to outweigh the undesirable effects associated with IVC filter complications. Current evidence suggests against routinely using prophylactic IVC filters.

Exploration of phytochemical compounds against Marburg virus using QSAR, molecular dynamics, and free energy landscape.

Marburg virus disease (MVD) is caused by the Marburg virus, a one-of-a-kind zoonotic RNA virus from the genus Filovirus. Thus, this current study employed AI-based QSAR and molecular docking-based virtual screening for identifying potential binders against the target protein (nucleoprotein (NP)) of the Marburg virus. A total of 2727 phytochemicals were used for screening, out of which the top three compounds (74977521, 90470472, and 11953909) were identified based on their predicted bioactivity (pIC50) and binding score (< - 7.4 kcal/mol). Later, MD simulation in triplicates and trajectory analysis were performed which showed that 11953909 and 74977521 had the most stable and consistent complex formations and had the most significant interactions with the highest number of hydrogen bonds. PCA (principal component analysis) and FEL (free energy landscape) analysis indicated that these compounds had favourable energy states for most of the conformations. The total binding free energy of the compounds using the MM/GBSA technique showed that 11953909 (ΔGTOTAL = - 30.78 kcal/mol) and 74977521 (ΔGTOTAL = - 30 kcal/mol) had the highest binding affinity with the protein. Overall, this in silico pipeline proposed that the phytochemicals 11953909 and 74977521 could be the possible binders of NP. This study aimed to find phytochemicals inhibiting the protein's function and potentially treating MVD.

Novel Glu-based pyrazolo[3,4-d]pyrimidine analogues: design, synthesis and biological evaluation as DHFR and TS dual inhibitors.

A novel series of multifunctional pyrazolo[3,4-d]pyrimidine-based glutamate analogs (6a-l and 7a,b) have been designed and synthesized as antifolate anticancer agents. Among the tested compounds, 6i exhibited the most potent anti-proliferative activity towards NSCLC, CNS, Ovarian, Prostate, Colon, Melanoma, Breast, and Renal cancers with good to weak cytostatic activity and non-lethal actions. 6i demonstrated higher selectivity for cancer than normal cells. 6i could significantly increase the accumulation of S-phase cells during the cell cycle distribution of cancer cells with high potency in the induction of apoptosis. The results unveiled that 6i probably acts through dual inhibition of DHFR and TS enzymes (IC50 = 2.41 and 8.88 µM, correspondingly). Docking studies of 6i displayed that N1-p-bromophenyl and C3-Methyl groups participate in substantial hydrophobic interactions. The drug-likeness features inferred that 6i met the acceptance criteria of Pfizer. Taking together, 6i could be a promising prototype for further optimization as an effective anticancer drug.

Coarse-Grained Molecular Simulations and Ensemble-Based Mutational Profiling of Protein Stability in the Different Functional Forms of the SARS-CoV-2 Spike Trimers: Balancing Stability and Adaptability in BA.1, BA.2 and BA.2.75 Variants.

Evolutionary and functional studies have suggested that the emergence of Omicron variants can be determined by multiple fitness tradeoffs including immune escape, binding affinity, conformational plasticity, protein stability, and allosteric modulation. In this study, we embarked on a systematic comparative analysis of the conformational dynamics, electrostatics, protein stability, and allostery in the different functional states of spike trimers for BA.1, BA.2, and BA.2.75 variants. Using efficient and accurate coarse-grained simulations and atomistic reconstruction of the ensembles, we examined the conformational dynamics of the spike trimers that agree with the recent functional studies, suggesting that BA.2.75 trimers are the most stable among these variants. A systematic mutational scanning of the inter-protomer interfaces in the spike trimers revealed a group of conserved structural stability hotspots that play a key role in the modulation of functional dynamics and are also involved in the inter-protomer couplings through local contacts and interaction networks with the Omicron mutational sites. The results of mutational scanning provided evidence that BA.2.75 trimers are more stable than BA.2 and comparable in stability to the BA.1 variant. Using dynamic network modeling of the S Omicron BA.1, BA.2, and BA.2.75 trimers, we showed that the key network mediators of allosteric interactions are associated with the major stability hotspots that are interconnected along potential communication pathways. The network analysis of the BA.1, BA.2, and BA.2.75 trimers suggested that the increased thermodynamic stability of the BA.2.75 variant may be linked with the organization and modularity of the residue interaction network that allows for allosteric communications between structural stability hotspots and Omicron mutational sites. This study provided a plausible rationale for a mechanism in which Omicron mutations may evolve by targeting vulnerable sites of conformational adaptability to elicit immune escape while maintaining their control on balancing protein stability and functional fitness through robust allosteric communications with the stability hotspots.

From Deep Mutational Mapping of Allosteric Protein Landscapes to Deep Learning of Allostery and Hidden Allosteric Sites: Zooming in on "Allosteric Intersection" of Biochemical and Big Data Approaches.

The recent advances in artificial intelligence (AI) and machine learning have driven the design of new expert systems and automated workflows that are able to model complex chemical and biological phenomena. In recent years, machine learning approaches have been developed and actively deployed to facilitate computational and experimental studies of protein dynamics and allosteric mechanisms. In this review, we discuss in detail new developments along two major directions of allosteric research through the lens of data-intensive biochemical approaches and AI-based computational methods. Despite considerable progress in applications of AI methods for protein structure and dynamics studies, the intersection between allosteric regulation, the emerging structural biology technologies and AI approaches remains largely unexplored, calling for the development of AI-augmented integrative structural biology. In this review, we focus on the latest remarkable progress in deep high-throughput mining and comprehensive mapping of allosteric protein landscapes and allosteric regulatory mechanisms as well as on the new developments in AI methods for prediction and characterization of allosteric binding sites on the proteome level. We also discuss new AI-augmented structural biology approaches that expand our knowledge of the universe of protein dynamics and allostery. We conclude with an outlook and highlight the importance of developing an open science infrastructure for machine learning studies of allosteric regulation and validation of computational approaches using integrative studies of allosteric mechanisms. The development of community-accessible tools that uniquely leverage the existing experimental and simulation knowledgebase to enable interrogation of the allosteric functions can provide a much-needed boost to further innovation and integration of experimental and computational technologies empowered by booming AI field.

Meta-Analysis and Systematic Review of HLA DQ2/DQ8 in Adults with Celiac Disease.

Although people with human leukocyte antigens (HLA) DQ2 and/or DQ8 are more likely to develop celiac disease (CD), the condition cannot be fully explained by this genetic predisposition alone. Multiple, as yet unidentified, factors contribute to the genesis of CD, including genetics, the environment, and the immune system. In order to provide insight into a prospective possibility and an expanded screening technique, we aim to undertake a comprehensive and meta-analytical study of the assessment and distribution of HLA class II (HLA-DQ2/DQ8) in adult CD patients. A systematic review was conducted using an electronic search of databases (PubMed, Google Scholar, Embase, and Direct Science) from January 2004 to February 2022. DQ2/DQ2 homozygotes have the highest risk of developing CD. DQ2/DQ8 typing is an effective test to exclude CD from the differential diagnosis of a patient with CD symptoms. Although other non-HLA genes have been associated with CD, they are rarely considered at diagnosis because they account for only a small proportion of the heritability of CD. This finding, together with the information gathered previously, may be useful in considering widely available and economically feasible screening options for celiac disease in young people.

Establishing the Role of Iridoids as Potential Kirsten Rat Sarcoma Viral Oncogene Homolog G12C Inhibitors Using Molecular Docking; Molecular Docking Simulation; Molecular Mechanics Poisson-Boltzmann Surface Area; Frontier Molecular Orbital Theory; Molecular Electrostatic Potential; and Absorption, Distribution, Metabolism, Excretion, and Toxicity Analysis.

The RAS gene family is one of the most frequently mutated oncogenes in human cancers. In KRAS, mutations of G12D and G12C are common. Here, 52 iridoids were selected and docked against 8AFB (KRAS G12C receptor) using Sotorasib as the standard. As per the docking interaction data, 6-O-trans-p-coumaroyl-8-O-acetylshanzhiside methyl ester (dock score: -9.9 kcal/mol), 6'-O-trans-para-coumaroyl geniposidic acid (dock score: -9.6 kcal/mol), 6-O-trans-cinnamoyl-secologanoside (dock score: -9.5 kcal/mol), Loganic acid 6'-O-beta-d-glucoside (dock score: -9.5 kcal/mol), 10-O-succinoylgeniposide (dock score: -9.4), Loganic acid (dock score: -9.4 kcal/mol), and Amphicoside (dock score: -9.2 kcal/mol) showed higher dock scores than standard Sotorasib (dock score: -9.1 kcal/mol). These common amino acid residues between iridoids and complexed ligands confirmed that all the iridoids perfectly docked within the receptor's active site. The 100 ns MD simulation data showed that RMSD, RMSF, radius of gyration, and SASA values were within range, with greater numbers of hydrogen bond donors and acceptors. MM/PBSA analysis showed maximum binding energy values of -7309 kJ/mol for 6-O-trans-p-coumaroyl-8-O-acetylshanzhiside methyl ester. FMO analysis showed that 6-O-trans-p-coumaroyl-8-O-acetylshanzhiside methyl ester was the most likely chemically reactive molecule. MEP analysis data highlighted the possible electrophilic and nucleophilic attack regions of the best-docked iridoids. Of all the best-docked iridoids, Loganic acid passed Lipinski, Pfizer, and GSK filters with a similar toxicity profile to Sotorasib. Thus, if we consider these iridoids to be KRAS G12C inhibitors, they will be a boon to mankind.

Determination of Chemical Composition and Investigation of Biological Activities of Ocimum basilicum L.

This study aimed to determine the chemical composition of the essential oils (EOs) of Ocimum basilicum L., as well as to evaluate the antibacterial, antidiabetic, dermatoprotective, and anti-inflammatory properties, and the EOs and aqueous extracts of O. basilicum. The antibacterial activity was evaluated against bacterial strains, Gram-positive and Gram-negative, using the well diffusion and microdilution methods, whereas the antidiabetic activity was assessed in vitro using two enzymes involved in carbohydrate digestion, α-amylase and α-glucosidase. On the other hand, the dermatoprotective and anti-inflammatory activities were studied by testing tyrosinase and lipoxygenase inhibition activity, respectively. The results showed that the chemical composition of O. basilicum EO (OBEO) is dominated by methyl chavicol (86%) and trans-anethol (8%). OBEO exhibited significant antibacterial effects against Gram-negative and Gram-positive strains, demonstrated by considerable diameters of the inhibition zones and lower MIC and MBC values. In addition, OBEO exhibited significant inhibition of α-amylase (IC50 = 50.51 ± 0.32 µg/mL) and α-glucosidase (IC50 = 39.84 ± 1.2 µg/mL). Concerning the anti-inflammatory activity, OBEO significantly inhibited lipoxygenase activity (IC50 = 18.28 ± 0.03 µg/mL) compared to the aqueous extract (IC50 = 24.8 ± 0.01 µg/mL). Moreover, tyrosinase was considerably inhibited by OBEO (IC50 = 68.58 ± 0.03 µg/mL) compared to the aqueous extract (IC50 = 118.37 ± 0.05 µg/mL). The toxicological investigations revealed the safety of O. basilicum in acute and chronic toxicity. The finding of in silico analysis showed that methyl chavicol and trans-anethole (main compounds of OBEO) validate the pharmacokinetics of these compounds and decipher some antibacterial targets.