A computational study to probe the binding aspects of potent polyphenolic inhibitors of pancreatic lipase.

Pancreatic lipase (PL) is a keen target for anti-obesity therapy that reduces dietary fat absorption. Here, we investigated the binding patterns of 220 PL inhibitors having experimental IC50 values, using molecular docking and binding energy calculations. Screening of these compounds illustrated most of them bound at the catalytic site (S1-S2 channel) and a few compounds are at the non-catalytic site (S2-S3 channel/S1-S3 channel) of PL. This binding pattern could be due to structural uniqueness or bias in conformational search. A strong correlation of pIC50 values with SP/XP docking scores, binding energies (ΔGMMGBSA) assured the binding poses are more true positives. Further, understanding of each class and subclasses of polyphenols indicated tannins preferred non-catalytic site wherein binding energies are underestimated due to huge desolvation energy. In contrast, most of the flavonoids and furan-flavonoids have good binding energies due to strong interactions with catalytic residues. While scoring functions limited the understanding of sub-classes of flavonoids. Hence, focused on 55 potent PL inhibitors of IC50 < 5 µM for better in vivo efficacy. The prediction of bioactivity, drug-likeness properties, led to 14 bioactive compounds. The low root mean square deviation (0.1-0.2 nm) of these potent flavonoids and non-flavonoid/non-polyphenols PL-inhibitor complexes during 100 ns molecular dynamics runs (MD) as well as binding energies obtained from both MD and well-tempered metadynamics, support strong binding to catalytic site. Based on the bioactivity, ADMET properties, and binding affinity data of MD and wt-metaD of potent PL-inhibitors suggests Epiafzelechin 3-O-gallate, Sanggenon C, and Sanggenofuran A shall be promising inhibitors at in vivo conditions.Communicated by Ramaswamy H. Sarma.

High-Risk Patient Experiences Associated With an Intensive Primary Care Management Program in the Veterans Health Administration.

Intensive management programs may improve health care experiences among high-risk and complex patients. We assessed patient experience among (1) prior enrollees (n = 59) of an intensive management program (2014-2018); (2) nonenrollees (n = 356) at program sites; and (3) nonprogram site patients (n = 728), using a patient survey based on the Consumer Assessment of Healthcare Providers and Systems in 2019. Outcomes included patient ratings of patient-centered care; overall health care experience; and satisfaction with their usual outpatient care provider. In multivariate models, enrollees were more satisfied with their current provider versus nonenrollees within program sites (adjusted odds ratio 2.36; 95% confidence interval 1.15-4.85).

Clinical Evaluation of Efficacy of Triamcinolone Acetonide with Tacrolimus in the Management of Oral Lichen Planus: A Pilot Prospective Observational Study.

Introduction: Lichen planus (LP) is a relatively common chronic, mucocutaneous disease of autoimmune origin, involves oral mucosa, skin, scalp, nails, and genital mucosa. The prevalence of oral LP (OLP) varies worldwide, commonly seen in middle-aged and elderly people. It usually presents as symmetrical and bilateral or multiple lesions with burning sensation (BS) sometimes accompanied by pain. Corticosteroids and calcineurin inhibitors have shown promising results in the treatment of OLP, but its chronic course and unpredictable exacerbations/remission continues to result in a high degree of morbidity. The study aimed to evaluate the efficacy of intralesional triamcinolone acetonide (injection TA) combined with topical application of TA orabase and Tacrolimus (TAC) ointment for symptomatic cases of OLP. Materials and Methods: The prospective study included 52 symptomatic OLP patients to receive (0.5 ml) intralesional injection of TA once a week for the first 4 weeks followed by one injection in the 6th week along with TA mucosal paste (0.1%.) and TAC ointment (0.03%) in tapering dose till 8th week. The subjective symptoms including BS and pain were assessed on a 10 cm visual analog scale (VAS) and objective signs like size and site of the lesion were scored according to criterion scale modified by Thongprasom et al. Differences were compared after 8 weeks treatment course and follow-up observations were performed at 20th week to record any recurrent lesion. Results: 41 patients (78.8%) had complete remission of disease and 11 (21%) had shown partial improvement. The VAS scores for BS and pain improved significantly. Improvement was also noted with decrease in the average size of active lesions and the number of sites with treatment. The relapse was seen in 17 patients (41%) in the 20th week. Conclusion: TA combined with TAC is a valuable therapeutic option for the treatment of symptomatic OLP. Our findings suggest that patients have shown statistically significant improvement.

Mechanistic insights of key host proteins and potential repurposed inhibitors regulating SARS-CoV-2 pathway.

The emergence of pandemic situations originated from severe acute respiratory syndrome (SARS)-CoV-2 and its new variants created worldwide medical emergencies. Due to the non-availability of efficient drugs and vaccines at these emergency hours, repurposing existing drugs can effectively treat patients critically infected by SARS-CoV-2. Finding a suitable repurposing drug with inhibitory efficacy to a host-protein is challenging. A detailed mechanistic understanding of the kinetics, (dis)association pathways, key protein residues facilitating the entry-exit of the drugs with targets are fundamental in selecting these repurposed drugs. Keeping this target as the goal of the paper, the potential repurposing drugs, Nafamostat, Camostat, Silmitasertib, Valproic acid, and Zotatifin with host-proteins HDAC2, CSK22, eIF4E2 are studied to elucidate energetics, kinetics, and dissociation pathways. From an ensemble of independent simulations, we observed the presence of single or multiple dissociation pathways with varying host-proteins-drug systems and quantitatively estimated the probability of unbinding through these specific pathways. We also explored the crucial gateway residues facilitating these dissociation mechanisms. Interestingly, the residues we obtained for HDAC2 and CSK22 are also involved in the catalytic activity. Our results demonstrate how these potential drugs interact with the host machinery and the specific target residues, showing involvement in the mechanism. Most of these drugs are in the preclinical phase, and some are already being used to treat severe COVID-19 patients. Hence, the mechanistic insight presented in this study is envisaged to support further findings of clinical studies and eventually develop efficient inhibitors to treat SARS-CoV-2.

Integrated docking and enhanced sampling-based selection of repurposing drugs for SARS-CoV-2 by targeting host dependent factors.

Since the onset of global pandemic, the most focused research currently in progress is the development of potential drug candidates and clinical trials of existing FDA approved drugs for other relevant diseases, in order to repurpose them for the COVID-19. At the same time, several high throughput screenings of drugs have been reported to inhibit the viral components during the early course of infection but with little proven efficacies. Here, we investigate the drug repurposing strategies to counteract the coronavirus infection which involves several potential targetable host proteins involved in viral replication and disease progression. We report the high throughput analysis of literature-derived repurposing drug candidates that can be used to target the genetic regulators known to interact with viral proteins based on experimental and interactome studies. In this work we have performed integrated molecular docking followed by molecular dynamics (MD) simulations and free energy calculations through an expedite in silico process where the number of screened candidates reduces sequentially at every step based on physicochemical interactions. We elucidate that in addition to the pre-clinical and FDA approved drugs that targets specific regulatory proteins, a range of chemical compounds (Nafamostat, Chloramphenicol, Ponatinib) binds to the other gene transcription and translation regulatory proteins with higher affinity and may harbour potential for therapeutic uses. There is a rapid growing interest in the development of combination therapy for COVID-19 to target multiple enzymes/pathways. Our in silico approach would be useful in generating leads for experimental screening for rapid drug repurposing against SARS-CoV-2 interacting host proteins.Communicated by Ramaswamy H. Sarma.

Metadynamics-based enhanced sampling protocol for virtual screening: case study for 3CLpro protein for SARS-CoV-2.

In recent times, computational methods played an important role in the down selection of chemical compounds, which could be a potential drug candidate with a high affinity to target proteins. However, the screening methodologies, including docking, often fails to identify the most effective compound, which could be a ligand for the target protein. To solve that, here we have integrated meta-dynamics, an enhanced sampling molecular simulation method, with all-atom molecular dynamics to determine a specific compound that could target the main protease of novel severe acute respiratory syndrome coronavirus 2 (SARS-COV-2). This combined computational approach uses the enhanced sampling to explore the free energy surface associated with the protein's binding site (including the ligand) in an explicit solvent. We have implemented this method to find new chemical entities that exhibit high specificity of binding to the 3-chymotrypsin-like cysteine protease (3CLpro) present in the SARS-CoV-2 and segregated to the most strongly bound ligands based on free energy and scoring functions (defined and implemented) from a set of 17 ligands which were prescreened for synthesizability and druggability. Additionally, we have compared these 17 ligands' affinities against controls, N3 and 13b α-ketoamide inhibitors, for which experimental crystal structures are available. Based on our results and analysis from the combined molecular simulation approach, we could identify the best compound which could be further taken as a potential candidate for experimental validation.Communicated by Ramaswamy H. Sarma.

Design-for-Trust Techniques for Digital Microfluidic Biochip Layout with Error Control Mechanism.

Among recent technological advances, microfluidic biochips have been leading a prominent solution for healthcare and miniaturized bio-laboratories with the assurance of high sensitivity and reconfigurability. On increasing more unreliable communication networks day-by-day, technological shifts in the fields of communication and security are now converging. In today's cyber threat landscape, these microfluidic biochips are ripe targets of powerful cyber-attacks from different hackers or cyber-criminals. Hence, securing such systems is of paramount importance. This paper presents the security aspects of digital microfluidic (DMF) biochip layout to protect the confidentiality of layout data from unscrupulous people and man-in-the-middle attacks. We propose an authentication mechanism with an error control mechanism that provides reliability, authentication, trustworthy and safety for both storage and communication of GDS, i.e., Graphical Design System, file generally used for DMF biochip layouts. Simulation results articulate the efficacy of the proposed security model without the overhead of the bioprotocol completion time. The proposed scheme, which used AES as an encryption algorithm with a 256-bit encryption key, has also shown a speedup of 6.0 (with 85% efficiency) faster than the prior efficient scheme. We hope to develop a secure layout design flow for DMF biochips to achieve better resistance to any attack.

Author Correction: Computationally designed antibody-drug conjugates self-assembled via affinity ligands.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Computationally designed antibody-drug conjugates self-assembled via affinity ligands.

Antibody-drug conjugates (ADCs) combine the high specificity of antibodies with cytotoxic payloads. However, the present strategies for the synthesis of ADCs either yield unstable or heterogeneous products or involve complex processes. Here, we report a computational approach that leverages molecular docking and molecular dynamics simulations to design ADCs that self-assemble through the non-covalent binding of the antibody to a payload that we designed to act as an affinity ligand for specific conserved amino acid residues in the antibody. This method does not require modifications to the antibody structure and yields homogenous ADCs that form in less than 8 min. We show that two conjugates, which consist of hydrophilic and hydrophobic payloads conjugated to two different antibodies, retain the structure and binding properties of the antibody and its biological specificity, are stable in plasma and improve anti-tumour efficacy in mice with non-small cell lung tumour xenografts. The relative simplicity of the approach may facilitate the production of ADCs for the targeted delivery of cytotoxic payloads.

Theoretical investigations of a platinum-water interface using quantum-mechanics-molecular-mechanics based molecular dynamics simulations.

Pt-water interfaces have been of immense interest in the field of energy storage and conversion. Studying this interface using both experimental and theoretical tools is challenging. On the theoretical front, typically one uses classical molecular dynamics (MD) simulations to handle large system sizes or time scales while for a more accurate quantum mechanical description Born Oppenheimer MD (BOMD) is typically used. The latter is limited to smaller system sizes and time-scales. In this study using quantum-mechanics-molecular-mechanics (QMMM), we have performed atomistic MD simulations to have a microscopic understanding of the structure of the Pt-water interface using a system size that is much larger than that accessible when using BOMD simulations. In contrast to recent reports using BOMD simulations, our study reveals that the water molecules typically form two distinct layers above the Pt-surface before they form bulk like structures. Further, we also find that a significant fraction of the water molecules at the interface are pointed towards the surface thereby disrupting the H-bond network. Consistent with this observation, the layer resolved oxygen-oxygen radial distribution function for the water molecules belonging to the solvating water layer shows a high density liquid like behaviour even though the overall water behaves like a low density liquid. A charge transfer analysis reveals that this solvating water layer donates electrons to the Pt atoms in contact with it thereby resulting in the formation of an interface dipole that is pointing towards the surface. Our results suggest that, using QMMM-MD, on one hand it is possible to study more realistic models of solid-liquid interfaces that are inaccessible with BOMD, while on the other hand one also has access to information about such systems that are not obtained from conventional classical MD simulations.

Effect of Sodium Dodecyl Sulfate Surfactant on Methane Hydrate Formation: A Molecular Dynamics Study.

In experimental studies, it has been observed that the presence of sodium dodecyl sulfate (SDS) significantly increases the kinetics of hydrate formation and the final water-to-hydrate conversion ratio. In this study, we intend to understand the molecular mechanism behind the effect of SDS on the formation of methane hydrate through molecular dynamics simulation. Hydrate formation conditions similar to that of laboratory experiments were chosen to study hydrate growth kinetics in 1 wt % SDS solution. We also investigate the effect of interactions with isolated SDS molecules on methane hydrate growth. It was observed that the hydrophobic tail part of the SDS molecule favorably interacts with the growing hydrate surface and may occupy the partial hydrate cages while the head groups remain exposed to water.

Molecular View of CO2 Capture by Polyethylenimine: Role of Structural and Dynamical Heterogeneity.

The molecular thermodynamics and kinetics of CO2 sorption in Polyethylenimine (PEI) melt have been investigated systematically using GCMC and MD simulations. We elucidate presence of significant structural and dynamic heterogeneity associated with the overall absorption process. CO2 adsorption in a PEI membrane shows a distinct two-stage process of a rapid CO2 adsorption at the interfaces (hundreds of picoseconds) followed by a significantly slower diffusion limited release toward the interior bulk regions of PEI melt (hundreds of nanoseconds to microseconds). The spatial heterogeneity of local structural features of the PEI chains lead to significantly heterogeneous absorption characterized by clustering and trapping of CO2 molecules that then lead to subdiffusive motion of CO2. In the complex interplay of interaction and entropy, the latter emerges out to be the major determining factor with significantly higher solubility of CO2 near the interfaces despite having lower density of binding amine groups. Regions having higher free-volume (entropically favorable) viz. interfaces, pores and loops demonstrate higher CO2 capture ability. Various local structural features of PEI conformations, for example, inter- and intrachain loops, pores of different radii, and di- or tricoordinated pores are explored for their effects on the varying CO2 adsorption abilities.

Mechanism of the formation of microphase separated water clusters in a water-mediated physical network of perfluoropolyether tetraol.

Perfluoropolyether tetraol (PFPE tetraol) possesses a hydrophobic perfluoropolyether chain in the backbone and two hydroxyl groups at each chain terminal, which facilitates the formation of hydrogen bonds with water molecules resulting in the formation an extended physical network. About 3 wt% water was required for the formation of the microphase separated physical network of PFPE tetraol. The mechanism responsible for the microphase separation of water clusters in the physical network was studied using a combination of techniques such as NMR spectroscopy, molecular dynamics (MD) simulations and DSC. MD simulation studies provided evidence for the formation of clusters in the PFPE tetraol physical network and the size of these clusters increased gradually with an increase in the extent of hydration. Both MD simulations and NMR spectroscopy studies revealed that these clusters position themselves away from the hydrophobic backbone or vice versa. The presence of intra- and inter-chain aggregation possibility among hydrophilic groups was evident. DSC results demonstrated the presence of tightly and loosely bound water molecules to the terminal hydroxyl groups of PFPE tetraol through hydrogen bonding. The data from all the three techniques established the formation of a physical network driven by hydrogen bonding between the hydrophilic end groups of PFPE tetraol and water molecules. The flexible nature of the PFPE tetraol backbone and its low solubility parameter favour clustering of water molecules at the terminal groups and result in the formation of a gel.

Coarse-Grained Molecular Dynamics Force-Field for Polyacrylamide in Infinite Dilution Derived from Iterative Boltzmann Inversion and MARTINI Force-Field.

We present a mesoscale model of aqueous polyacrylamide in the infinitely dilute concentration regime, by combining an extant coarse-grained (CG) force-field, MARTINI, and the Iterative Boltzmann Inversion protocol (IBI). MARTINI force-field was used to retain the thermodynamics of solvation of the polymer in water, whereas the structural properties and intrapolymer interactions were optimized by IBI. Atomistic molecular dynamics simulations of polymer in water were performed to benchmark the mesoscale simulations. Our results from the CG model show excellent agreement in structure with the atomistic system. We also studied the dynamical behavior of our CG system by computing the shear viscosity and compared it with the standard IBI model. The viscosity trends of our model were similar to the atomistic system, whereas the standard IBI model was highly dissimilar as expected. In summary, our hybrid CG model sufficiently mimics an infinitely dilute system, and is superior to both MARTINI and IBI in representing the structure and thermodynamics of the atomistic system, respectively. Our hybrid coarse-graining strategy promises applicability in large-scale simulations of polymeric/biological systems where the structure needs to be replicated accurately while preserving the thermodynamics of a smoother surrounding.

Evaluation of a new flow cytometry based method for detection of BCR-ABL1 fusion protein in chronic myeloid leukemia.

BACKGROUND: Philadelphia chromosome, a hallmark of chronic myeloid leukemia (CML), plays a key role in disease pathogenesis. It reflects a balanced reciprocal translocation between long arms of chromosomes 9 and 22 involving BCR and ABL1 genes, respectively. An accurate and reliable detection of BCR-ABL fusion gene is necessary for the diagnosis and monitoring of CML. Previously, many technologies, most of which are laborious and time consuming, have been developed to detect BCR-ABL chimeric gene or chromosome. METHODS: A new flow cytometric immunobead assay was used for detection of BCR-ABL fusion proteins and applicability, sensitivity, reliability, efficacy and rapidity of this method was evaluated. RESULTS: From February 2009 to January 2014, a total 648 CML patients were investigated for the status of BCR-ABL1 protein. Among them, 83 patients were enrolled for comparative study of BCR-ABL1 positivity by three routinely used procedures like karyotyping, and quantitative real time PCR (RT-PCR) as well as immunobead flow cytometry assay. BCR-ABL protein analysis was found consistent, more sensitive (17% greater sensitivity) and reliable than the conventional cytogenetics, as flow cytometry showed 95% concordance rate to RT-PCR. CONCLUSION: BCR-ABL fusion protein assay using a new flow cytometric immunobead might be useful in the diagnosis and monitoring CML patients.

Disorganized histomorphology: Dentinogenic ghost cell tumor.

Calcifying odontogenic cyst (COC) is a term used broadly to define lesions which were either cystic/solid in nature. However, a new term defining dentinogenic ghost cell tumor (DGCT), as its neoplastic counterpart, histopathologically showed the presence of dentinoid-like areas, ghost cells and ameloblastomatous-like odontogenic epithelium. This possesses a great challenge to an oral pathologist in diagnosing and differentiating it from solid multicystic ameloblastoma or COCs so as to ensure the biological behavior and pathogenesis behind its multifaceted nature. The author presents an exceptional case of DGCT, with special emphasis on its pathogenesis, occurring in an 80-year-old female with facial asymmetry and unique histopathology.

Drug-Triggered Self-Assembly of Linear Polymer into Nanoparticles for Simultaneous Delivery of Hydrophobic and Hydrophilic Drugs in Breast Cancer Cells.

Breast cancer is the most devastating disease among females globally. Conventional chemotherapeutic regimen relies on the use of highly cytotoxic drugs as monotherapy and combination therapy leading to severe side effects to the patients as collateral damage. Moreover, combining hydrophobic and hydrophilic drugs create erratic biodistribution and suboptimal medicinal outcome. Hence, packaging multiple drugs of diverse mechanisms of action and biodistribution for safe delivery into tumor tissues with optimal dosages is indispensable for next-generation breast cancer therapy. To address these, in this report, we describe a unique cisplatin-triggered self-assembly of linear polymer into 3D-spherical sub 200 nm particles. These nanoparticles comprise a hydrophobic (paclitaxel) and hydrophilic drug (cisplatin) simultaneously in a single particle. Molecular dynamics simulation revealed hydrophilic-hydrophilic interaction and interchain H-bonding as underlying mechanisms of self-assembly. Confocal microscopy studies evidently demonstrated that these novel nanoparticles can home into lysosomes in breast cancer cells, fragment subcellular nuclei, and prevent cell division, leading to improved breast cancer cell death compared to free drug combination. Moreover, 3D-breast tumor spheroids were reduced remarkably by the treatment of these nanoparticles within 24 h. These dual-drug-loaded self-assembled polymeric nanoparticles have prospective to be translated into a clinical strategy for breast cancer patients.

Free Energy of Bare and Capped Gold Nanoparticles Permeating through a Lipid Bilayer.

Herein, we study the permeation free energy of bare and octane-thiol-capped gold nanoparticles (AuNPs) translocating through a lipid membrane. To investigate this, we have pulled the bare and capped AuNPs from bulk water to the membrane interior and estimated the free energy cost. The adsorption of the bare AuNP on the bilayer surface is energetically favorable but further loading inside it requires energy. However, the estimated free-energy barrier for loading the capped AuNP into the lipid membrane is much higher compared to bare AuNP. We also demonstrate the details of the permeation process of bare and capped AuNPs. Bare AuNP induces the curvature in the lipid membrane whereas capped AuNP creates an opening in the interacting monolayer and get inserted into the membrane. The insertion of capped AuNP induces a partial unzipping of the lipid bilayer, which results in the ordering of the local lipids interacting with the nanoparticle. However, bare AuNP disrupts the lipid membrane by pushing the lipid molecules inside the membrane. We also analyze pore formation due to the insertion of capped AuNP into the membrane, which results in water molecules penetrating the hydrophobic region.

Algorithm for Designing Nanoscale Supramolecular Therapeutics with Increased Anticancer Efficacy.

In the chemical world, evolution is mirrored in the origin of nanoscale supramolecular structures from molecular subunits. The complexity of function acquired in a supramolecular system over a molecular subunit can be harnessed in the treatment of cancer. However, the design of supramolecular nanostructures is hindered by a limited atomistic level understanding of interactions between building blocks. Here, we report the development of a computational algorithm, which we term Volvox after the first multicellular organism, that sequentially integrates quantum mechanical energy-state- and force-field-based models with large-scale all-atomistic explicit water molecular dynamics simulations to design stable nanoscale lipidic supramolecular structures. In one example, we demonstrate that Volvox enables the design of a nanoscale taxane supramolecular therapeutic. In another example, we demonstrate that Volvox can be extended to optimizing the ratio of excipients to form a stable nanoscale supramolecular therapeutic. The nanoscale taxane supramolecular therapeutic exerts greater antitumor efficacy than a clinically used taxane in vivo. Volvox can emerge as a powerful tool in the design of nanoscale supramolecular therapeutics for effective treatment of cancer.