Multi-Target In-Silico modeling strategies to discover novel angiotensin converting enzyme and neprilysin dual inhibitors.

Cardiovascular diseases, including heart failure, stroke, and hypertension, affect 608 million people worldwide and cause 32% of deaths. Combination therapy is required in 60% of patients, involving concurrent Renin-Angiotensin-Aldosterone-System (RAAS) and Neprilysin inhibition. This study introduces a novel multi-target in-silico modeling technique (mt-QSAR) to evaluate the inhibitory potential against Neprilysin and Angiotensin-converting enzymes. Using both linear (GA-LDA) and non-linear (RF) algorithms, mt-QSAR classification models were developed using 983 chemicals to predict inhibitory effects on Neprilysin and Angiotensin-converting enzymes. The Box-Jenkins method, feature selection method, and machine learning algorithms were employed to obtain the most predictive model with ~ 90% overall accuracy. Additionally, the study employed virtual screening of designed scaffolds (Chalcone and its analogues, 1,3-Thiazole, 1,3,4-Thiadiazole) applying developed mt-QSAR models and molecular docking. The identified virtual hits underwent successive filtration steps, incorporating assessments of drug-likeness, ADMET profiles, and synthetic accessibility tools. Finally, Molecular dynamic simulations were then used to identify and rank the most favourable compounds. The data acquired from this study may provide crucial direction for the identification of new multi-targeted cardiovascular inhibitors.

Computational Screening of Hydrophobic Zeolites for the Removal of Emerging Organic Contaminants from Water.

The pollution of water resources by pharmaceuticals and agents of personal care products (PPCPs) poses an increasingly pressing issue that has received considerable attention from scientists and government agencies alike. Hydrophobic zeolites can serve as selective adsorbents to remove these contaminants from aqueous solution. So far, the adsorption of PPCPs in zeolites has often been investigated in case studies focusing on a small number of contaminants and one or a few zeolites. We present a computational screening approach to investigate the interaction of 53 PPCPs with 14 all-silica zeolites, aiming at a more comprehensive understanding of factors that are beneficial for a strong host-guest interaction and thus an efficient adsorption. The systems are modelled on the classical force field level of theory, allowing for the efficient computational treatment of a large number of PPCP-zeolite combinations and evaluated in terms of the interaction energy between PPCP and zeolite framework. For selected PPCP-zeolite combinations additional Free Energy Perturbation simulations are employed to compute Free Energies of Transfer between the aqueous phase and the adsorbed state. These results can serve as a starting point for experimental studies of relevant PPCP-zeolite combination or more in-depth theoretical investigations.

Combined experiments and molecular simulations for understanding the thermo-responsive behavior and gelation of methylated glucans with different glycosidic linkages.

HYPOTHESIS: Elucidation of the micro-mechanisms of sol-gel transition of gelling glucans with different glycosidic linkages is crucial for understanding their structure-property relationship and for various applications. Glucans with distinct molecular chain structures exhibit unique gelation behaviors. The disparate gelation phenomena observed in two methylated glucans, methylated (1,3)-ß-d-glucan of curdlan (MECD) and methylated (1,4)-ß-d-glucan of cellulose (MC), notwithstanding their equivalent degrees of substitution, are intricately linked to their unique molecular architectures and interactions between glucan and water. EXPERIMENTS: Density functional theory and molecular dynamics simulations focused on the electronic property distinctions between MECD and MC, alongside conformational variations during thermal gelation. Inline attenuated total reflection Fourier transform infrared spectroscopy tracked secondary structure alterations in MECD and MC. To corroborate the simulation results, additional analyses including circular dichroism, rheology, and micro-differential scanning calorimetry were performed. FINDINGS: Despite having similar thermally induced gel networks, MECD and MC display distinct physical gelation patterns and molecular-level conformational changes during gelation. The network of MC gel was formed via a "coil-to-ring" transition, followed by ring stacking. In contrast, the MECD gel comprised compact irregular helices accompanied by notable volume shrinkage. These variations in gelation behavior are ascribed to heightened hydrophobic interactions and diminished hydrogen bonding in both systems upon heating, resulting in gelation. These findings provide valuable insights into the microstructural changes during gelation and the thermo-gelation mechanisms of structurally similar polysaccharides.

How arginine inhibits substrate-binding domain 2 elucidated using molecular dynamics simulations.

The substrate-binding domain 2 (SBD2) is an important part of the bacterial glutamine (GLN) transporter and mediates binding and delivery of GLN to the transporter translocation subunit. The SBD2 consists of two domains, D1 and D2, that bind GLN in the space between domains in a closed structure. In the absence of ligand, the SBD2 adopts an open conformation with larger space between domains. The GLN binding and closing are essential for the subsequent transport into the cell. Arginine (ARG) can also bind to SBD2 but does not induce closing and inhibits GLN transport. We use atomistic molecular dynamics (MD) simulations in explicit solvent to study ARG binding in the presence of the open SBD2 structure and observed reversible binding to the native GLN binding site with similar contacts but no transition to a closed SBD2 state. Absolute binding free energy simulations predict a considerable binding affinity of ARG and GLN to the binding site on the D1 domain. Free energy simulations to induce subsequent closing revealed a strong free energy penalty in case of ARG binding in contrast to GLN binding that favors the closed SBD2 state but still retains a free energy barrier for closing. The simulations allowed the identification of the molecular origin of the closing penalty in case of bound ARG and suggested a mutation of lysine at position 373 to alanine that strongly reduced the penalty and allowed closing even in the presence of bound ARG. The study offers an explanation of the molecular mechanism of how ARG competitively inhibits GLN from binding to SBD2 and from triggering the transition to a closed conformation. The proposed Lys373Ala mutation shows promise as a potential tool to validate whether a conformational mismatch between open SBD2 and the translocator is responsible for preventing ARG uptake to the cell.

Primitive Chain Network Simulations for Double Peaks in Shear Stress under Fast Flows of Bidisperse Entangled Polymers.

A few experiments have reported that the time development of shear stress under fast-startup shear deformations exhibits double peaks before reaching a steady state for bimodal blends of entangled linear polymers under specific conditions. To understand this phenomenon, multi-chain slip-link simulations, based on the primitive chain network model, were conducted on the literature data of a bimodal polystyrene solution. Owing to reasonable agreement between their data and our simulation results, the stress was decomposed into contributions from long- and short-chain components and decoupled into segment number, stretch, and orientation. The analysis revealed that the first and second peaks correspond to the short-chain orientation and the long-chain stretch, respectively. The results also implied that the peak positions are not affected by the mixing of short and long chains, although the intensity of the second peak depends on mixing conditions in a complicated manner.

Organic-solvent ditch overlap in reversed-phase liquid chromatography: A molecular dynamics simulation study in cylindrical 6-12 nm-diameter pores.

Mass transport through the mesopore space of a reversed-phase liquid chromatography (RPLC) column depends on the properties of the chromatographic interface, particularly on the extent of the organic-solvent ditch that favors the analyte surface diffusivity. Through molecular dynamics simulations in cylindrical RPLC mesopore models with pore diameters between 6 and 12 nm we systematically trace the evolution of organic-solvent ditch overlap due to spatial confinement in the mesopore space of RPLC columns for small-molecule separations. Each pore model of a silica-based, endcapped, C18-stationary phase is equilibrated with two mobile phases of comparable elution strength, namely 70/30 (v/v) water/acetonitrile and 60/40 (v/v) water/methanol, to consider the influence of the mobile-phase composition on the onset of organic-solvent ditch overlap. The simulations show that, as the pore diameter decreases from 9 to 6 nm, the bonded-phase density extends and compacts towards the pore center, which leads to increased accumulation of organic-solvent excess and thus enhanced organic-solvent diffusivity in the ditch. Because the acetonitrile ditch is more pronounced than the methanol ditch, acetonitrile ditch overlap sets in at less severe spatial confinement than methanol ditch overlap. The pore-averaged methanol and acetonitrile diffusivities are considerably raised by ditch overlap in the 6 nm-diameter pore, but also benefit from the ditch (without overlap) in the 7 to 12 nm-diameter pores, whereby local and pore-averaged effects are generally larger for acetonitrile than methanol.

Sequence - dynamics - function relationships in protein tyrosine phosphatases.

Protein tyrosine phosphatases (PTPs) are crucial regulators of cellular signaling. Their activity is regulated by the motion of a conserved loop, the WPD-loop, from a catalytically inactive open to a catalytically active closed conformation. WPD-loop motion optimally positions a catalytically critical residue into the active site, and is directly linked to the turnover number of these enzymes. Crystal structures of chimeric PTPs constructed by grafting parts of the WPD-loop sequence of PTP1B onto the scaffold of YopH showed WPD-loops in a wide-open conformation never previously observed in either parent enzyme. This wide-open conformation has, however, been observed upon binding of small molecule inhibitors to other PTPs, suggesting the potential of targeting it for drug discovery efforts. Here, we have performed simulations of both enzymes and show that there are negligible energetic differences in the chemical step of catalysis, but significant differences in the dynamical properties of the WPD-loop. Detailed interaction network analysis provides insight into the molecular basis for this population shift to a wide-open conformation. Taken together, our study provides insight into the links between loop dynamics and chemistry in these YopH variants specifically, and how WPD-loop dynamic can be engineered through modification of the internal protein interaction network.

Structures, dynamics, complexes, and functions: From classic computation to artificial intelligence.

Computational approaches can provide highly detailed insight into the molecular recognition processes that underlie drug binding, the assembly of protein complexes, and the regulation of biological functional processes. Classical simulation methods can bridge a wide range of length- and time-scales typically involved in such processes. Lately, automated learning and artificial intelligence methods have shown the potential to expand the reach of physics-based approaches, ushering in the possibility to model and even design complex protein architectures. The synergy between atomistic simulations and AI methods is an emerging frontier with a huge potential for advances in structural biology. Herein, we explore various examples and frameworks for these approaches, providing select instances and applications that illustrate their impact on fundamental biomolecular problems.

Molecular Simulation Studies of Pharmaceutical Pollutant Removal (Rosuvastatin and Simvastatin) Using Novel Modified-MOF Nanostructures (UIO-66, UIO-66/Chitosan, and UIO-66/Oxidized Chitosan).

The ubiquitous presence of pharmaceutical pollutants in the environment significantly threatens human health and aquatic ecosystems. Conventional wastewater treatment processes often fall short of effectively removing these emerging contaminants. Therefore, the development of high-performance adsorbents is crucial for environmental remediation. This research utilizes molecular simulation to explore the potential of novel modified metal-organic frameworks (MOFs) in pharmaceutical pollutant removal, paving the way for the design of efficient wastewater treatment strategies. Utilizing UIO-66, a robust MOF, as the base material, we developed UIO-66 functionalized with chitosan (CHI) and oxidized chitosan (OCHI). These modified MOFs' physical and chemical properties were first investigated through various characterization techniques. Subsequently, molecular dynamics simulation (MDS) and Monte Carlo simulation (MCS) were employed to elucidate the adsorption mechanisms of rosuvastatin (ROSU) and simvastatin (SIMV), two prevalent pharmaceutical pollutants, onto these nanostructures. MCS calculations demonstrated a significant enhancement in the adsorption energy by incorporating CHI and OCHI into UIO-66. This increased ROSU from -14,522 to -16,459 kcal/mol and SIMV from -17,652 to -21,207 kcal/mol. Moreover, MDS reveals ROSU rejection rates in neat UIO-66 to be at 40%, rising to 60 and 70% with CHI and OCHI. Accumulation rates increase from 4 Å in UIO-66 to 6 and 9 Å in UIO-CHI and UIO-OCHI. Concentration analysis shows SIMV rejection surges from 50 to 90%, with accumulation rates increasing from 6 to 11 Å with CHI and OCHI in UIO-66. Functionalizing UIO-66 with CHI and OCHI significantly enhanced the adsorption capacity and selectivity for ROSU and SIMV. Abundant hydroxyl and amino groups facilitated strong interactions, improving performance over that of unmodified UIO-66. Surface functionalization plays a vital role in customizing the MOFs for pharmaceutical pollutant removal. These insights guide next-gen adsorbent development, offering high efficiency and selectivity for wastewater treatment.

Molecular choreography: Unveiling the dynamic landscape of type IIA DNA topoisomerases before T-segment passage through all-atom simulations.

Type IIA DNA topoisomerases are molecular nanomachines responsible for controlling topological states of DNA molecules. Here, we explore the dynamic landscape of yeast topoisomerase IIA during key stages of its catalytic cycle, focusing in particular on the events preceding the passage of the T-segment. To this end, we generated six configurations of fully catalytic yeast topo IIA, strategically inserted a T-segment into the N-gate in relevant configurations, and performed all-atom simulations. The essential motion of topo IIA protein dimer was characterized by rotational gyrating-like movement together with sliding motion within the DNA-gate. Both appear to be inherent properties of the enzyme and an inbuilt feature that allows passage of the T-segment through the cleaved G-segment. Coupled dynamics of the N-gate and DNA-gate residues may be particularly important for controlled and smooth passage of the T-segment and consequently the prevention of DNA double-strand breaks. QTK loop residue Lys367, which interacts with ATP and ADP molecules, is involved in regulating the size and stability of the N-gate. The unveiled features of the simulated configurations provide insights into the catalytic cycle of type IIA topoisomerases and elucidate the molecular choreography governing their ability to modulate the topological states of DNA topology.

Membrane specificity of the human cholesterol transfer protein STARD4.

STARD4 regulates cholesterol homeostasis by transferring cholesterol between the plasma membrane and endoplasmic reticulum. The STARD4 structure features a helix-grip fold surrounding a large hydrophobic cavity holding the sterol. Its access is controlled by a gate formed by the Ω1 and Ω4 loops and the C-terminal α-helix. Little is known about the mechanisms by which STARD4 binds to membranes and extracts/releases cholesterol. All available structures of STARD4 are without a bound sterol and display the same closed conformation of the gate. The cholesterol transfer activity of the mouse STARD4 is enhanced in the presence of anionic lipids, and in particular of phosphatidylinositol biphosphates (PIP2) for which two binding sites were proposed on the mouse STARD4 surface. Yet only one of these sites is conserved in human STARD4. We here report the results of a liposome microarray-based assay and microseconds-long molecular dynamics simulations of human STARD4 with complex lipid bilayers mimicking the composition of the donor and acceptor membranes. We show that the binding of apo form of human STARD4 is sensitive to the presence of PIP2 through two specific binding sites, one of which was not identified on mouse STARD4. We report two novel conformations of the gate in holo-STARD4: a yet-unobserved close conformation and an open conformation of Ω4 shedding light on the opening/closure mechanism needed for cholesterol uptake/release. Overall, the modulation of human STARD4 membrane-binding by lipid composition, and by the presence of the cargo supports the capacity of human STARD4 to achieve directed transfer between specific organelle membranes.

Tackling antibiotic contaminations in wastewater with novel Modified-MOF nanostructures: A study of molecular simulations and DFT calculations.

The contamination of wastewater with antibiotics has emerged as a critical global challenge, with profound implications for environmental integrity and human well-being. Adsorption techniques have been meticulously investigated and developed to mitigate and alleviate their effects. In this study, we have investigated the adsorption behaviour of Erythromycin (ERY), Gentamicin (GEN), Levofloxacin (LEVO), and Metronidazole (MET) antibiotics as pharmaceutical contaminants (PHCs) on amide-functionalized (RC (=O)NH2)/MIL-53 (Al) (AMD/ML53A), using molecular simulations and density functional theory (DFT) calculations. Based on our DFT calculations, it becomes apparent that the adsorption tendencies of antibiotics are predominantly governed by the presence of AMD functional groups on the adsorbent surface. Specifically, hydrogen bonding (HB) and van der Waals (vdW) interactions between antibiotics and AMD groups serve as the primary mechanisms facilitating adsorption. Furthermore, we have observed that the adsorption behaviors of these antibiotics are influenced by their respective functional groups, molecular shapes, and sizes. Our molecular simulations delved into how the AMD/ML53A surfaces interact with antibiotics as PHCs. Moreover, various chemical quantum descriptors based on Frontier Molecular Orbitals (FMO) were explored to elucidate the extent of AMD/ML53A adsorption and to assess potential alterations in their electronic properties throughout the adsorption process. Monte Carlo simulation showed that ERY molecules adsorb stronger to the adsorbent in acidic and basic conditions than other contaminants, with high energies: -404.47 kcal/mol in acidic and -6375.26 kcal/mol in basic environments. Molecular dynamics (MD) simulations revealed parallel orientation for the ERY molecule's adsorption on AMD/ML53A with 80% rejection rate. In conclusion, our study highlighted the importance of modeling in developing practical solutions for removing antibiotics as PHCs from wastewater. The insights gained from our calculations can facilitate the design of more effective adsorption materials, ultimately leading to a more hygienic and sustainable ecosystem.

BDNF- and VEGF-Responsive Stimulus to an NGF Mimic Cyclic Peptide with Copper Ionophore Capability and Ctr1/CCS-Driven Signaling.

Neurotrophins are a family of growth factors that play a key role in the development and regulation of the functioning of the central nervous system. Their use as drugs is made difficult by their poor stability, cellular permeability, and side effects. Continuing our effort to use peptides that mimic the neurotrophic growth factor (NGF), the family model protein, and specifically the N-terminus of the protein, here we report on the spectroscopic characterization and resistance to hydrolysis of the 14-membered cyclic peptide reproducing the N-terminus sequence (SSSHPIFHRGEFSV (c-NGF(1-14)). Far-UV CD spectra and a computational study show that this peptide has a rigid conformation and left-handed chirality typical of polyproline II that favors its interaction with the D5 domain of the NGF receptor TrkA. c-NGF(1-14) is able to bind Cu2+ with good affinity; the resulting complexes have been characterized by potentiometric and spectroscopic measurements. Experiments on PC12 cells show that c-NGF(1-14) acts as an ionophore, influencing the degree and the localization of both the membrane transporter (Ctr1) and the copper intracellular transporter (CCS). c-NGF(1-14) induces PC12 differentiation, mimics the protein in TrkA phosphorylation, and activates the kinase cascade, inducing Erk1/2 phosphorylation. c-NGF(1-14) biological activities are enhanced when the peptide interacts with Cu2+ even with the submicromolar quantities present in the culture media as demonstrated by ICP-OES measurements. Finally, c-NGF(1-14) and Cu2+ concur to activate the cAMP response element-binding protein CREB that, in turn, induces the brain-derived neurotrophic factor (BDNF) and the vascular endothelial growth factor (VEGF) release.

Molecular-level insight into the chlorofluorocarbons adsorption by defective covalent organic polymers.

Halocarbons have important industrial applications, however they contribute to global warming and the fact that they can cause ozone depletion. Hence, the techniques that can capture and recover the used halocarbons with energy efficiency methods have recently received greater attention. In this contribution, we report the capture of dichlorodifluoromethane (R12), which has high global warming and ozone depletion potential, using covalent organic polymers (COPs). The defect-engineered COPs were synthesized and demonstrated outstanding sorption capacities, ~226 wt% of R12 combined with linear-shaped adsorption isotherms. We further identified the plausible microscopic adsorption mechanism of the investigated COPs via grand canonical Monte Carlo simulations applied to non-defective and a collection of atomistic models of the defective COPs. The modeling work suggests that significant R12 adsorption is attributed to a gradual increment of porosities due to isolated/interconnected micro-/meso-pore channels and the change of the long-range ordering of both COPs. The successive hierarchical-pore-filling mechanism promotes R12 molecular adsorption via moderate van der Waals adsorbate-adsorbent interactions in the micropores of both COPs at low pressure followed by adsorbate-adsorbate interactions in the extra-voids created at moderate to high pressure ranges. This continuous pore-filling mechanism makes defective COPs as promising sorbents for halocarbon adsorption.

Molecular Ballet: Investigating the Complex Interaction between Self-Assembling Dendrimers and Human Serum Albumin via Computational and Experimental Methods.

Dendrimers, intricate macromolecules with highly branched nanostructures, offer unique attributes including precise control over size, shape, and functionality, making them promising candidates for a wide range of biomedical applications. The exploration of their interaction with biological environments, particularly human serum albumin (HSA), holds significant importance for biomedical utilization. In this study, the interaction between HSA and a recently developed self-assembling amphiphilic dendrimer (AD) was investigated using various experimental techniques. Fluorescence spectroscopy and isothermal titration calorimetry revealed moderate interactions between the protein and the AD nanomicelles (NMs), primarily attributed to favorable enthalpic contributions arising from electrostatic interactions and hydrogen bonding. Structural analysis indicated minimal changes in HSA upon complexation with the AD NMs, which was further supported by computational simulations demonstrating stable interactions at the atomistic level. These findings provide valuable insights into the binding mechanisms and thermodynamic parameters governing HSA/AD NM interactions, thereby contributing to the understanding of their potential biomedical applications.

The Interplay of Solvation and Polarization Effects on Ion Pairing in Nanoconfined Electrolytes.

The nature of ion-ion interactions in electrolytes confined to nanoscale pores has important implications for energy storage and separation technologies. However, the physical effects dictating the structure of nanoconfined electrolytes remain debated. Here we employ machine-learning-based molecular dynamics simulations to investigate ion-ion interactions with density functional theory level accuracy in a prototypical confined electrolyte, aqueous NaCl within graphene slit pores. We find that the free energy of ion pairing in highly confined electrolytes deviates substantially from that in bulk solutions, observing a decrease in contact ion pairing but an increase in solvent-separated ion pairing. These changes arise from an interplay of ion solvation effects and graphene's electronic structure. Notably, the behavior observed from our first-principles-level simulations is not reproduced even qualitatively with the classical force fields conventionally used to model these systems. The insight provided in this work opens new avenues for predicting and controlling the structure of nanoconfined electrolytes.

The mechanism of epigallocatechin-3-gallate inhibiting the antigenicity of ß-lactoglobulin under pH 6.2, 7.4 and 8.2: Multi-spectroscopy and molecular simulation methods.

The antigenicity of ß-lactoglobulin (ß-LG) can be influenced by pH values and reduced by epigallocatechin-3-gallate (EGCG). However, a detailed mechanism concerning EGCG decreasing the antigenicity of ß-LG at different pH levels lacks clarity. Here, we explore the inhibition mechanism of EGCG on the antigenicity of ß-LG at pH 6.2, 7.4 and 8.2 using enzyme-linked immunosorbent assay, multi-spectroscopy, mass spectrometry and molecular simulations. The results of Fourier transform infrared spectroscopy (FTIR) and circular dichroism (CD) elucidate that the noncovalent binding of EGCG with ß-LG induces variations in the secondary structure and conformations of ß-LG. Moreover, EGCG inhibits the antigenicity of ß-LG the most at pH 7.4 (98.30 %), followed by pH 6.2 (73.18 %) and pH 8.2 (36.24 %). The inhibitory difference is attributed to the disparity in the number of epitopes involved in the interacting regions of EGCG and ß-LG. Our findings suggest that manipulating pH conditions may enhance the effectiveness of antigenic inhibitors, with the potential for further application in the food industry.

Allosteric pathways of SARS and SARS-CoV-2 spike protein identified by neural relational inference.

The receptor binding domain (RBD) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein must undergo a crucial conformational transition to invade human cells. It is intriguing that this transition is accompanied by a synchronized movement of the entire spike protein. Therefore, it is possible to design allosteric regulators targeting non-RBD but hindering the conformational transition of RBD. To understand the allosteric mechanism in detail, we establish a computational framework by integrating coarse-grained molecular dynamic simulations and a state-of-the-art neural network model called neural relational inference. Leveraging this framework, we have elucidated the allosteric pathway of the SARS-CoV-2 spike protein at the residue level and identified the molecular mechanisms involved in the transmission of allosteric signals. The movement of D614 is coupled with that of Q321. This interaction subsequently influences the movement of K528/K529, ultimately coupling with the movement of RBD during conformational changes. Mutations that weaken the interactions within this pathway naturally block the allosteric signal transmission, thereby modulating the conformational transitions. This observation also offers a rationale for the distinct allosteric patterns observed in the SARS-CoV spike protein. Our result provides a useful method for analyzing the dynamics of potential viral variants in the future.

Preliminary insights on the mutational spectrum of BRCA1 and BRCA2 genes in Pakhtun ethnicity breast cancer patients from Khyber Pakhtunkhwa (KP), Pakistan.

Gene mutations are a source of genetic instability which fuels the progression of cancer. Mutations in BRCA1 and BRCA2 are considered as major drivers in the progression of breast cancer and their detection indispensable for devising therapeutic and management approaches. The current study aims to identify novel pathogenic and recurrent mutations in BRCA1 and BRCA2 in Pakhtun population from the Khyber Pakhtunkhwa. To determine the BRCA1 and BRCA2 pathogenic mutation prevalence in Pakhtun population from KP, whole exome sequencing of 19 patients along with 6 normal FFPE embedded blocks were performed. The pathogenicity of the mutations were determined and they were further correlated with different hormonal, sociogenetic and clinicopathological features. We obtained a total of 10 mutations (5 somatic and 5 germline) in BRCA1 while 27 mutations (24 somatic and 3 germline) for BRCA2. Five and seventeen pathogenic or deleterious mutations were identified in BRCA1 and BRCA2 respectively by examining the mutational spectrum through SIFT, PolyPhen-2 and Mutation Taster. Among the SNVs, BRCA1 p.P824L, BRCA2 p. P153Q, p.I180F, p.D559Y, p.G1529R, p.L1576F, p.E2229K were identified as mutations of the interaction sites as predicted by the deep algorithm based ISPRED-SEQ prediction tool. SAAFEQ-SEQ web-based algorithm was used to calculate the changes in free energy and effect of SNVs on protein stability. All SNVs were found to have a destabilizing effect on the protein. ConSurf database was used to determine the evolutionary conservation scores and nature of the mutated residues. Gromacs 4.5 was used for the molecular simulations. Ramachandran plots were generated using procheck server. STRING and GeneMania was used for prediction of the gene interactions. The highest number of mutations (BRCA1 7/10, 70 %) were on exon 9 and (BRCA2, 11/27; 40 %) were on exon 11. 40 % and 60 % of the BRCA2 mutations were associated Grade 2 and Grade 3 tumors respectively. The present study reveals unique BRCA1 and BRCA2 mutations in Pakhtun population. We further suggest sequencing of the large cohorts for further characterizing the pathogenic mutations.

Sulfonyl thioureas with a benzo[d]thiazole ring as dual acetylcholinesterase/butyrylcholinesterase and human monoamine oxidase A and B inhibitors: An in vitro and in silico study.

A series of sulfonyl thioureas 6a-q containing a benzo[d]thiazole ring with an ester functional group was synthesized from corresponding substituted 2-aminobenzo[d]thiazoles 3a-q and p-toluenesulfonyl isothiocyanate. They had remarkable inhibitory activity against acetylcholinesterase (AChE), butyrylcholinesterase (BChE), monoamine oxidase (MAO)-A, and MAO-B. Among thioureas, several compounds had notable activity in the order of 6k > 6 h > 6c (AChE), 6j > 6g > 6k (BChE), 6k > 6g > 6f (MAO-A), and 6i > 6k > 6h (MAO-B). Compound 6k was an inhibitor of interest due to its potent or good activity against all studied enzymes, with IC50 values of 0.027 ± 0.008 µM (AChE), 0.043 ± 0.004 µM (BChE), 0.353 ± 0.01 µM (MAO-A), and 0.716 ± 0.02 µM (MAO-B). This inhibitory capacity was comparable to that of the reference drugs for each enzyme. Kinetic studies of two compounds with potential activity, 6k (against AChE) and 6j (against BChE), had shown that both 6k and 6j followed competitive-type enzyme inhibition, with Ki constants of 24.49 and 12.16 nM, respectively. Induced fit docking studies for enzymes 4EY7, 7BO4, 2BXR, and 2BYB showed active interactions between sulfonyl thioureas of benzo[d]thiazoles and the residues in the active pocket with ligands 6k, 6i, and 6j, respectively. The stability of the ligand-protein complexes while each ligand entered the active site of each enzyme (4EY7, 7BO4, 2BXR, or 2BYB) was confirmed by molecular dynamics simulations.