AMBER Software Research Articles

Molecular insights from structural dynamics of HER2-inhibitor complexes pave the way for new breast cancer drugs

The human epidermal growth factor receptor 2 (HER2) is closely associated with the development and progression of breast cancer, making it a critical target for therapeutic interventions. In this study, we employed a comprehensive computational drug discovery strategy to identify potential inhibitors of HER2. Our approach combined virtual screening, re-docking procedures, molecular dynamics (MD) simulations, and free energy landscape analysis using principal component analysis (PCA). From the extensive PubChem library, we initially screened 733 compounds for their binding potential to HER2, using docking scores as a primary filter. These scores ranged notably from −11.172 to −7.028 kcal/mol, indicating substantial binding capacities. Following this screening, we selected four promising compounds (PubChem CID 166029206, 166544027, 21031510, and 11712721) along with a control compound (70I) for in-depth analysis. Utilizing the Amber software suite for MD simulations, we conducted 200-nanosecond simulations to assess the interactions and binding efficiencies of these selected compounds with HER2. We analysed the molecular interactions through various parameters such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), and hydrogen bond formation patterns, free binding energy calculations. The PCA-based free energy landscape analysis revealed that these compounds consistently occupied a distinct low-energy basin, indicating their high stability and strong binding affinity for the HER2. This detailed analysis provided insights into the stability and conformational dynamics of these potential inhibitors when bound to the HER2. Our findings pave the way for further experimental validation and development of these compounds as therapeutic agents in breast cancer treatment.

Metastasis-Associated Lung Adenocarcinoma Transcript 1 (MALAT1) lncRNA Conformational Dynamics in Complex with RNA-Binding Protein with Serine-Rich Domain 1 (RNPS1) in the Pan-cancer Splicing and Gene Expression.

Alternative splicing events increase the transcriptomic and proteomic complexity in cancers. Overexpression of metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), a highly conserved lncRNA, is widely known to promote cancer development, one mechanism for which may be through the regulation of alternative splicing and, thereby, gene expression. Its regulatory interactions with proteins have been a subject of much interest, yet little research has been carried out on the mechanisms adopted. It has been observed that MALAT1 binds to RNA-binding protein with serine-rich domain 1 (RNPS1), being colocalized in the nuclear speckles, and together, these two binding partners may regulate alternative splicing. Upregulated RNPS1 is predicted to play a key role in the pan-cancer development. Experimental tertiary structure of full-length MALAT1 is currently lacking despite the availability of the 3D structure of 3' expression and nuclear retention element. We hypothesize that the computationally modeled tertiary structures of the specific binding motifs in the M-region, E-region, and full-length structures of MALAT1 may adopt a modular structure and bind to the RNPS1 loop region of RS/P domain involved in exon skipping, interacting in a manner fully consistent with the biochemical experiments. Extensive observations using the powerful molecular dynamics (MD) simulations of MALAT1 regions bound to RNPS1 suggested that all three regions form interactive, yet stable complexes. The ranking of the MM-GBSA- and MM-PBSA-derived binding free energies between these complexes corroborated well in the MD simulations and experiments. Energy decomposition analyses suggested that arginines in the RNPS1 protein are among the major contributors toward the binding free energies as calculated by MM-GBSA present in the Amber package; while among the nucleotides, the major contributors were nucleotides with G and A nucleobases, with more contributory effect in comparison to arginines, across the bound M-region, E-region, and full-length MALAT1. This suggests that specific purines play a greater role in the complex formation, in a loop-specific manner, and the more proactive approach in complexation tilts toward MALAT1. To the best of our knowledge, our studies are the first studies taking a unique approach, utilizing the binding motifs to deduce a tertiary structure of MALAT1, toward our understanding of the lncRNA-protein interactions, stability, and binding on a structural basis. The therapeutic implications of targeting this complex formation to regulate splicing and hence, oncogenesis, is further envisaged.

Implicit Solvent with Explicit Ions Generalized Born Model in Molecular Dynamics: Application to DNA.

The ion atmosphere surrounding highly charged biomolecules, such as nucleic acids, is crucial for their dynamics, structure, and interactions. Here, we develop an approach for the explicit treatment of ions within an implicit solvent framework suitable for atomistic simulations of biomolecules. The proposed implicit solvent/explicit ions model, GBION, is based on a modified generalized Born (GB) model; it includes separate, modified GB terms for solute-ion and ion-ion interactions. The model is implemented in the AMBER package (version 24), and its performance is thoroughly investigated in atomistic molecular dynamics (MD) simulations of double-stranded DNA on a microsecond time scale. The aggregate characteristics of monovalent (Na+ and K+) and trivalent (Cobalt Hexammine, CoHex3+) counterion distributions around double-stranded DNA predicted by the model are in reasonable agreement with the experiment (where available), all-atom explicit water MD simulations, and the expectation from the Manning condensation theory. The radial distributions of monovalent cations around DNA are reasonably close to the ones obtained using the explicit water model: expressed in units of energy, the maximum deviations of local ion concentrations from the explicit solvent reference are within 1 kBT, comparable to the corresponding deviations expected between different established explicit water models. The proposed GBION model is able to simulate DNA fragments in a large volume of solvent with explicit ions with little additional computational overhead compared with the fully implicit GB treatment of ions. Ions simulated using the developed model explore conformational space at least 2 orders of magnitude faster than in the explicit solvent. These advantages allowed us to observe and explore an unexpected "stacking" mode of DNA condensation in the presence of trivalent counterions (CoHex3+) that was revealed by recent experiments.

Employing Hexahydroquinolines as PfCDPK4 Inhibitors to Combat Malaria Transmission: An Advanced Computational Approach.

Existing antimalarial drugs primarily target blood-stage parasites, but there is a need for transmission-blocking drugs to combat malaria effectively. Plasmodium falciparum Calcium-dependent Protein Kinase 4 (CDPK4) is a promising target for such drugs. This study employed advanced in silico analyses of hexahydroquinolines (HHQ) derivatives to identify PfCDPK4 inhibitors capable of disrupting malaria transmission. Structure-based virtual screening (SBVS) was employed to discover HHQ derivatives with the highest binding affinities against the 3D structure of PfCDPK4 (PDB 1D: 4QOX). Interaction analysis of protein-ligand complexes utilized Discovery Studio Client, while druglikeness and ADMET properties were assessed using SwissADME and pkCSM web servers, respectively. Quantum mechanical calculations of the top hits were conducted using density functional theory (DFT), and GROMACS was employed to perform the molecular dynamics (MD) simulations. Binding free energy was predicted using the MMPBSA.py tool from the AMBER package. SBVS identified ten best hits possessing docking scores within the range of -11.2 kcal/mol and -10.6 kcal/mol, surpassing the known inhibitor, BKI-1294 (-9.9 kcal/mol). Among these, 4-[4-(Furan-2-carbonyl)piperazin-1-yl]-1-(naphthalen-2-ylmethyl)-2-oxo-4a,5,6,7,8,8a-hexahydroquinoline-3-carbonitrile (PubChem ID: 145784778) exhibited the highest binding affinity (-11.2 kcal/mol) against PfCDPK4. Comparative analysis of this compound with BKI-1294 using advanced computational approaches demonstrated competitive potential. These findings suggest the potential of 4-[4-(Furan-2-carbonyl)piperazin-1-yl]-1-(naphthalen-2-ylmethyl)-2-oxo-4a,5,6,7,8,8a-hexahydroquinoline-3-carbonitrile as a promising PfCDPK4 inhibitor for disrupting malaria transmission. However, further experimental studies are warranted to validate its efficacy and safety profile.

Proposed molecular mechanism of non-competitive inhibition using molecular dynamics simulations between α-glucosidase enzyme and mangostin compound as antidiabetic.

Further understanding of the molecular mechanisms is necessary since it is important for designing new drugs. This study aimed to understand the molecular mechanisms involved in the design of drugs that are inhibitors of the α-glucosidase enzyme. This research aims to gain further understanding of the molecular mechanisms underlying antidiabetic drug design. The molecular docking process yielded 4 compounds with the best affinity energy, including γ-Mangostin, 1,6-dimethyl-ester-3-isomangostin, 1,3,6-trimethyl-ester-α-mangostin, and 3,6,7-trimethyl-ester-γ-mangostin. Free energy calculation with molecular mechanics with generalized born and surface area solvation indicated that the 3,6,7-trimethyl-γ-mangostin had a better free energy value compared to acarbose and simulated maltose together with 3,6,7-trimethyl-γ-mangostin compound. Based on the analysis of electrostatic, van der Waals, and intermolecular hydrogen interactions, 3,6,7-trimethyl-γ-mangostin adopts a noncompetitive inhibition mechanism, whereas acarbose adopts a competitive inhibition mechanism. Consequently, 3,6,7-trimethyl-ester-γ-mangostin, which is a derivative of γ-mangostin, can provide better activity in silico with molecular docking approaches and molecular dynamics simulations. This research commenced with retrieving protein structures from the RCSB database, generating the formation of ligands using the ChemDraw Professional software, conducting molecular docking with the Autodock Vina software, and performing molecular dynamics simulations using the Amber software, along with the evaluation of RMSD values and intermolecular hydrogen bonds. Free energy, electrostatic interactions, and Van der Waals interaction were calculated using MM/GBSA. Acarbose, used as a positive control, and maltose are simulated together with test compound that has the best free energy. The forcefields used for molecular dynamics simulations are ff19SB, gaff2, and tip3p.

X-ray Crystallography Module in MD Simulation Program Amber 2023. Refining the Models of Protein Crystals.

The MD simulation package Amber offers an attractive platform to refine crystallographic structures of proteins: (i) state-of-the-art force fields help to regularize protein coordinates and reconstruct the poorly diffracting elements of the structure, such as flexible loops; (ii) MD simulations restrained by the experimental diffraction data provide an effective strategy to optimize structural models of protein crystals, including explicitly modeled interstitial solvent as well as crystal contacts. Here, we present the new crystallography module xray, released as a part of the Amber 2023 package. This module contains functions to calculate and scale structure factors (including the contributions from bulk solvent), evaluate the maximum-likelihood-type crystallographic potential, and compute its derivative forces. The X-ray functionality of Amber no longer relies on external dependencies so that the full advantage of GPU acceleration can be taken. This makes it possible to refine in a short time hundreds of crystal models, including supercell models comprised of multiple unit cells. The new automated Amber-based refinement procedure leads to an appreciable improvement in Rfree (in some cases, by as much as 0.067) as well as MolProbity scores.

Grid-Robust Efficient Neural Interface Model for Universal Molecule Surface Construction from Point Clouds.

Molecular surfaces play a pivotal role in elucidating the properties and functions of biological complexes. While various surfaces have been proposed for specific scenarios, their widespread adoption faces challenges due to limited efficiency stemming from hand-crafted modeling designs. In this work, we proposed a general framework that incorporates both the point cloud concept and neural networks. The use of matrix multiplication in this framework enables efficient implementation across diverse platforms and libraries. We applied this framework to develop the GENIUSES (Grid-robust Efficient Neural Interface for Universal Solvent-Excluded Surface) model for constructing SES. GENIUSES demonstrates high accuracy and efficiency across data sets with varying conformations and complexities. Compared to the classical implementation of SES in the AMBER software package, our framework achieved a 26-fold speedup while retaining ∼95% accuracy when ported to the GPU platform using CUDA. Greater speedups can be obtained in large-scale systems. Importantly, our model exhibits robustness against variations in the grid spacing. We have integrated this infrastructure into AMBER to enhance accessibility for research in drug screening and related fields, where efficiency is of paramount importance.

Dynamics simulation and in vitro studies of betulinic acid derivative with liver X receptor

Molecular dynamics simulation of the dominant conformational conjugate was performed for 40 ns and 100 ns via Amber software based on molecular docking by Sybyl software. Because the RMSD and RMSF of 100 ns MD simulation were higher than that of 40 ns MD simulation, the 40 ns was reasonable and credible for MD simulation. The binding free energy and decomposition free energy of the two systems of betulinic acid, com3 with liver X receptor was calculated by the MM_GBSA and MM_PBSA methods, respectively. The results showed that the two systems reached equilibrium and convergence at 20 ns, both stable at about 2 Å, and exhibited low volatility in the range of amino acid 270 to 370 (RMSF <1 Å). The binding energy of com3 (ΔGbind = −68.02 kcal/mol by the MM_GBSA method or −55.50 kcal/mol by the MM_PBSA method) with the liver X receptor was lower than that of betulinic acid (ΔGbind = −55.70 kcal/mol or −42.73 kcal/mol) respectively, and van der Waals force was the most important main driving force, which was consistent with molecular docking and previous experiments. Hydrophobic groups and aromatic rings can be introduced appropriately in structure optimization to increase the van der Waals force and π-π accumulation effect of betulinic acid and liver X receptor, which is conducive to binding and thereby increasing antitumor activity. The clone formation assay and results of western blotting indicated that BA derivative com3 exposure inhibited cell proliferation may relate to the regulation of the AKT/mTOR pathway in 7721 cells. This study clarifies the dynamic interaction mode and potential mechanism of betulinic acid and its derivatives with the liver X receptor, which provides a new idea for the rapid screening of liver X receptor agonists from traditional Chinese medicines. Communicated by Ramaswamy H. Sarma

PO-01-206 MOLECULAR MODELING OF CLINICAL KCNJ2 MUTATIONS REVEALS STRUCTURE-FUNCTION IMPACT ON PIP2 BINDING SITE

Binding phosphatidylinositol 4,5-bisphosphate (PIP2) is essential for Kir2.1(encoded by KCNJ2), function. Disease associated KCNJ2 mutations, such as those associated with Andersen-Tawil Syndrome (ATS), may exert molecular dysfunction by interrupting PIP2 binding, however a full-length molecular model of Kir2.1 has not been developed to explore this hypothesis. Elucidate the molecular structure of Kir2.1 and determine the functional impact of clinical KCNJ2 mutations on PIP2 binding using experimental and improved molecular dynamic (MD) method. Whole-cell patch clamp experiments of WT-Kir2.1 and selected mutations were performed on stably transfected HEK293 cells using a standard protocol. A full-length Kir2.1 tetramer model (open and closed conformational states) based on Kir2.2 cryo-EM structure using MOE was created. Mutations (R67Q, G300D, R218L) were individually introduced to the channel, and a mutagenesis analysis was performed. Initially, MD simulation for 100ns was performed for wild-type (WT) and mutated structures (GROMACS software). We expanded the model to include +/- bound PIP2. Due to > 77% degree of homology of Kir2.2 (6m84) with Kir2.1, we developed a MD protocol with Kir2.2 as test system. The 2.5% free PIP2 molecules were released into the membrane and MD simulation was performed for 700ns using Amber software. Homomeric WT demonstrated normal Kir2.1 function while mutations G300D, R67Q, and R218L showed complete loss of function. Mutational analysis revealed that residue changes result in disruption of hydrogen bonding and affects the structural conformation at the residue sight and caused fluctuation of residues in other regions, i.e., selectivity filter and pore domain. The improved MD protocol validated Kir2.2 PIP2 binding sites. Moreover, we found mutation disruption of hydrogen bonds and hydrophobic interaction analysis between the channel and PIP2 molecules revealed significant structural changes. We developed the first full length MD model of Kir2.1 and found that ATS KCNJ2 mutations disrupt normal conformation and hydrogen bonding. Further, we validated PIP2 binding sites which illustrate the robustness of our method, and this technique can be applied to delineate Kir2.1 molecular PIP2 binding sites. Combined with experimental validation, our modeling will increase our understanding of structure-function relationships of KCNJ2 clinical mutations.

Multi-dimensional structural footprint identification for the design of potential scaffolds targeting METTL3 in cancer treatment from natural compounds

[Formula: see text]-adenosine-methyltransferase (METTL3) is the catalytic domain of the 'writer' proteins which is involved in the post modifications of [Formula: see text]-methyladinosine ([Formula: see text]). Though its activities are essential in many biological processes, it has been implicated in several types of cancer. Thus, drug developers and researchers are relentlessly in search of small molecule inhibitors that can ameliorate the oncogenic activities of METTL3. Currently, STM2457 is a potent, highly selective inhibitor of METTL3 but is yet to be approved. In this study, we employed structure-based virtual screening through consensus docking by using AutoDock Vina in PyRx interface and Glide virtual screening workflow of Schrodinger Glide. Thermodynamics via MM-PBSA calculations was further used to rank the compounds based on their total free binding energies. All atom molecular dynamics simulations were performed using AMBER 18 package. FF14SB force fields and Antechamber were used to parameterize the protein and compounds respectively. Post analysis of generated trajectories was analyzed with CPPTRAJ and PTRAJ modules incorporated in the AMBER package while Discovery studio and UCSF Chimera were used for visualization, and origin data tool used to plot all graphs. Three compounds with total free binding energies higher than STM2457 were selected for extended molecular dynamics simulations. The compounds, SANCDB0370, SANCDB0867, and SANCDB1033, exhibited stability and deeper penetration into the hydrophobic core of the protein. They engaged in relatively stronger intermolecular interactions involving hydrogen bonds with resultant increase in stability, reduced flexibility, and decrease in the surface area of the protein available for solvent interactions suggesting an induced folding of the catalytic domain. Furthermore, in silico pharmacokinetics and physicochemical analysis of the compounds revealed good properties suggesting these compounds could serve as promising MEETL3 entry inhibitors upon modifications and optimizations as presented by natural compounds. Further biochemical testing and experimentations would aid in the discovery of effective inhibitors against the berserk activities of METTL3.

AMBER Free Energy Tools: A New Framework for the Design of Optimized Alchemical Transformation Pathways.

We develop a framework for the design of optimized alchemical transformation pathways in free energy simulations using nonlinear mixing and a new functional form for so-called "softcore" potentials. We describe the implementation and testing of this framework in the GPU-accelerated AMBER software suite. The new optimized alchemical transformation pathways integrate a number of important features, including (1) the use of smoothstep functions to stabilize behavior near the transformation end points, (2) consistent power scaling of Coulomb and Lennard-Jones (LJ) interactions with unitless control parameters to maintain balance of electrostatic attractions and exchange repulsions, (3) pairwise form based on the LJ contact radius for the effective interaction distance with separation-shifted scaling, and (4) rigorous smoothing of the potential at the nonbonded cutoff boundary. The new softcore potential form is combined with smoothly transforming nonlinear λ weights for mixing specific potential energy terms, along with flexible λ-scheduling features, to enable robust and stable alchemical transformation pathways. The resulting pathways are demonstrated and tested, and shown to be superior to the traditional methods in terms of numerical stability and minimal variance of the free energy estimates for all cases considered. The framework presented here can be used to design new alchemical enhanced sampling methods, and leveraged in robust free energy workflows for large ligand data sets.

Stable Cavitation Interferes with Aβ16-22 Oligomerization.

Ultrasound and microbubbles are used for many medical applications nowadays. Scanning ultrasound can remove amyloid-β (Aβ) aggregates in the mouse brain and restores memory in an Alzheimer's disease mouse model. In vitro studies showed that amyloid fibrils are fragmented due to the ultrasound-induced bubble inertial cavitation, and ultrasonic pulses accelerate the depolymerization of Aβ fibrils into monomers at 1 μM of concentration. Under applied ultrasound, microbubbles can be in a stable oscillating state or unstable inertial cavitation state. The latter occurs when ultrasound causes a dramatic change of bubble sizes above a certain acoustic pressure. We have developed and implemented a nonequilibrium molecular dynamics simulation algorithm to the AMBER package, to facilitate the investigation of the molecular mechanism of Aβ oligomerization under stable cavitation. Our results indicated that stable cavitation not only inhibited oligomeric formation, but also prevented the formation of β-rich oligomers. The network analysis of state transitions revealed that stable cavitation altered the oligomerization pathways of Aβ16-22 peptides. Our simulation tool may be applied to optimize the experimental conditions to achieve the best therapeutical effect.

Large-scale application of free energy perturbation calculations for antibody design

Alchemical free energy perturbation (FEP) is a rigorous and powerful technique to calculate the free energy difference between distinct chemical systems. Here we report our implementation of automated large-scale FEP calculations, using the Amber software package, to facilitate antibody design and evaluation. In combination with Hamiltonian replica exchange, our FEP simulations aim to predict the effect of mutations on both the binding affinity and the structural stability. Importantly, we incorporate multiple strategies to faithfully estimate the statistical uncertainties in the FEP results. As a case study, we apply our protocols to systematically evaluate variants of the m396 antibody for their conformational stability and their binding affinity to the spike proteins of SARS-CoV-1 and SARS-CoV-2. By properly adjusting relevant parameters, the particle collapse problems in the FEP simulations are avoided. Furthermore, large statistical errors in a small fraction of the FEP calculations are effectively reduced by extending the sampling, such that acceptable statistical uncertainties are achieved for the vast majority of the cases with a modest total computational cost. Finally, our predicted conformational stability for the m396 variants is qualitatively consistent with the experimentally measured melting temperatures. Our work thus demonstrates the applicability of FEP in computational antibody design.

Molecular Dynamics Simulation of a tRNA-Leucine Dimer with an A3243G Heteroplasmy Mutation in Human Mitochondria Using a Secondary Structure Prediction Approach

Mitochondrial DNA mutations, such as A3243G, can affect changes in the structure of biomolecules, resulting in changes in the structure of Leucine transfer Ribose Nucleic Acid to form a dimer. Dimer structure modeling is needed to determine the properties of the structure. However, the lack of a structure template for the transfer of Ribose Nucleic Acid (tRNA) is challenging for the modeling of mutant structures of tRNA, especially mitochondrial tRNA that are susceptible to mutation. Therefore, this study predicted the structure of mitochondrial leucine tRNA and its stability through a knowledge-based method and molecular dynamics. Structural modeling and initial assessment were performed using RNAComposer and MolProbity, HNADOCK, and Discovery studios to form the dimer structure. Molecular dynamics simulations for stability analysis were performed using Amber and AmberTools20 software, showing that the conformational energy of the mutant leucine tRNA dimer structure was lower than the native structure. Moreover, the Root Mean Square Deviation (RMSD) of monomer native leucine tRNA was lower than the mutant, indicating that the dimer structure of mutant leucine tRNA is more stable than usual, and the normal leucine tRNA is more stable than the mutant.

Molecular Modeling of Penicillin Acylase Binding with a Penicillin Nucleus by High Performance Computing: Can Enzyme or its Mutants Possess beta-lactamase Activity?

High-performance computing has been used for molecular modeling of penicillin acylase interaction with a penicillin nucleus 6-aminopenicillanic acid (6-APA) to assess whether the wild-type enzyme or its mutants could possess β-lactamase activity. Applying parallel hybrid GPU/CPU computing technologies for metadynamics calculations with the PLUMED library in conjunction with AMBER software suite it has been shown that trace amounts of wild-type penicillin acylase6-APA complexes leading to a β-lactamase reaction can be formed. Higher β-lactamase activity can be observed in enzyme mutants by introducing charged residue in the substrate binding pocket and its proper positioning with respect to a catalytic nucleophile, including stabilization of the tetrahedral intermediate in the oxyanion hole. Thus, it has been shown that the certain mutations facilitate the orientation of the substrate required for the manifestation of β-lactamase activity in the penicillin acylase active center.

Limonene inhibits virulence associated traits in Candida albicans: In-vitro and in-silico studies

Background: Multidrug resistance and undesirable side effects of currently available antifungal drugs, has made treatment of Candidiasis difficult in immunocompromised patients. Limonene, commonly found in citrus essential oils, has immense therapeutic potential. Purpose: Efficacy of this monoterpene was studied against virulence attributes of C. albicans. Methods: Percentage haemolysis, antifungal susceptibility, time kill studies, secretion of hydrolytic enzymes, morphological transition, adhesion and biofilm formation (XTT reduction assay, scanning electron microscopic and calcofluor white stained fluorescence imaging) were studied in the presence of limonene. Molecular docking by InstaDock software followed by MD simulation studies (AMBER software suite) assessed the limonene-protein interactions with five virulence associated antifungal targets (Als3, Bcr1, Plb1, Sap2 and Tec1). Results: With MIC and MFC values of 300 µg/mL and 400 µg/mL, respectively, it caused only 1% haemolysis (3 times less than fluconazole) and significantly reduced adhesion to buccal epithelial cells. An incubation of 9 h at 2MIC reduced growth by 100%. At MIC, secretion of proteinases and phospholipases was reduced by 73% and 53%, respectively. Adhesion and biofilm formation was reduced by 91% and 87%, respectively. Biofilm biomass formed on silicon sheets was inhibited by 69%. Limonene treatment disrupted biofilm structure and integrity. Filamentation, studied in four different hyphae inducing media, was significantly reduced. Although stable hydrophobic interactions were observed with all target proteins, limonene gave a good docking score with Plb1 (−6.0 kcal/mol) and Tec1 (−5.7 kcal/mol). Complexes formed with both these proteins showed stable RMSD profiles except with Bcr1. Conclusion: Limonene binds to proteins critical to Candida pathogenicity and inhibits adhesion, biofilm formation and morphological transition. It is nontoxic and has immense potential in the management of invasive candidiasis.

Stress tensor and constant pressure simulation for polarizable Gaussian multipole model.

Our previous article has established the theory of molecular dynamics (MD) simulations for systems modeled with the polarizable Gaussian multipole (pGM) electrostatics [Wei et al., J. Chem. Phys. 153(11), 114116 (2020)]. Specifically, we proposed the covalent basis vector framework to define the permanent multipoles and derived closed-form energy and force expressions to facilitate an efficient implementation of pGM electrostatics. In this study, we move forward to derive the pGM internal stress tensor for constant pressure MD simulations with the pGM electrostatics. Three different formulations are presented for the flexible, rigid, and short-range screened systems, respectively. The analytical formulations were implemented in the SANDER program in the Amber package and were first validated with the finite-difference method for two different boxes of pGM water molecules. This is followed by a constant temperature and constant pressure MD simulation for a box of 512 pGM water molecules. Our results show that the simulation system stabilized at a physically reasonable state and maintained the balance with the externally applied pressure. In addition, several fundamental differences were observed between the pGM and classic point charge models in terms of the simulation behaviors, indicating more extensive parameterization is necessary to utilize the pGM electrostatics.

Modelling of Radiological Health Risk in Water from Abstraction Well Close to a Hypothetical Radioactive Waste Repository in the Accra Plains

This study evaluated the integrity of the geosphere of the Accra Plains to host a radioactive waste disposal facility for Ghana’s radioactive waste materials. The study thus assessed the migration of radioactive contaminant from a hypothetical radioactive waste disposal facility through the geosphere to the biosphere in the Accra Plains. The Accra Plains is predominantly underlain by schist rocks, hence the hydrogeologic parameters of schist rock from literature were used as input data. AMBER software was used to develop a model to estimate the peak total annual effective dose from all the radionuclides at various receptor locations. The endpoint of interest was the dose received by a receptor for ingesting water from an abstraction well located at distance; 100 m, 200 m, 500 m, 1 km, 2 km, 3 km, 4 km and 5 km from the hypothetical repository. From the simulation, the annual effective dose values ranged from 2.07E-25 Sv/y to 6.45E-17 Sv/y which are all below the International Commission on Radiological Protection (ICRP) dose constraint of 0.3 mSv/y. The lifetime cancer risk for ingesting water from the abstraction wells were then calculated from the annual effective dose values. The resulting values ranged from 1.06E-24 to 3.30E-16 thus indicating that the potential cancer risk for ingesting water from the abstraction wells located within 100 m to 5 km from the hypothetical disposal facility is negligible. The model results demonstrate that, siting a disposal facility in the study area might not pose any significant risk to the sprawling population and the environment.

Modeling Radiation Exposure from Normal Release of 137Cs Radionuclide to Groundwater for Post-Closure Assessment of Serpong Near Surface Disposal Demo Facility

Near-surface disposal (NSD) has been applied in several countries to dispose of low-level radioactive waste. The demo plant of this disposal type is planned to be constructed in Serpong Nuclear Area, Banten. An assessment of radiation exposure is necessary to ensure the safety requirement of the facility in order to support this program. This study aims to estimate radionuclide migration from the proposed NSD demo facility to the environment and the corresponding total human dose using AMBER mathematical modeling. The representative radionuclide,137Cs, was selected because of its high mobility in the environment and the relatively long half-life in the low-level waste inventory. The scenario considered in the modeling was the normal release to the environment through groundwater. Parameters such as initial radionuclide concentration, soil physical parameters of the study site, and disposal design were entered into AMBER software to be calculated using mathematical formulas. The results show that the radionuclide concentration value in the environment is below the safe limit recommended by the Environmental Supervisory Agency. Likewise, the maximum dose received by the community around the facility is 7.40×10-11 mSv/y, 550 years after the post-closure of the facility, which is also below the regulatory limit of 1 mSv/y for the public.

Changes in Protein Structural Motifs upon Post-Translational Modification in Kidney Cancer.

Post-translational modification (PTM) leads to conformational changes in protein structure, modulates the biological function of proteins, and, consequently, changes the signature of metabolic transformations and the immune response in the body. Common PTMs are reversible and serve as a mechanism for modulating metabolic trans-formations in cells. It is likely that dysregulation of post-translational cellular signaling leads to abnormal proliferation and oncogenesis. We examined protein PTMs in the blood samples from patients with kidney cancer. Conformational changes in proteins after modification were analyzed. The proteins were analyzed using ultra-high resolution HPLC-MS/MS and structural analysis was performed with the AMBER and GROMACS software packages. Fifteen proteins containing PTMs were identified in blood samples from patients with kidney cancer. For proteins with PDB structures, a comparative analysis of the structural changes accompanying the modifications was performed. Results revealed that PTMs are localized in stable and compact space protein globule motifs that are exposed to a solvent. The phenomenon of modification is accompanied, as a rule, by an increase in the area available for the solvent of the modified amino acid residue and its active environment.