Enhanced Sampling Techniques Research Articles

Critical comparison of general-purpose collective variables for crystal nucleation.

The nucleation of crystals is a prominent phenomenon in science and technology that still lacks a full atomic-scale understanding. Much work has been devoted to identifying order parameters able to track the process, from the inception of early nuclei to their maturing to critical size until growth of an extended crystal. We critically assess and compare two powerful distance-based collective variables, an effective entropy derived from liquid state theory and the path variable based on permutation invariant vectors using the Kob-Andersen binary mixture and a combination of enhanced-sampling techniques. Our findings reveal a comparable ability to drive nucleation when a bias potential is applied, and comparable free-energy barriers and structural features. Yet, we also found an imperfect correlation with the committor probability on the barrier top which was bypassed by changing the order parameter definition.

Supporting data for "Girsanov Reweighting Enhanced Sampling Technique (GREST): On-the-fly data-driven discovery of and enhanced sampling in slow collective variables"

Supporting data for "Girsanov Reweighting Enhanced Sampling Technique (GREST): On-the-fly data-driven discovery of and enhanced sampling in slow collective variables"

Predictions of the Poses and Affinity of a Ligand over the Entire Surface of a NEET Protein: The Case of Human MitoNEET.

Human NEET proteins contain two [2Fe-2S] iron-sulfur clusters, bound to three Cys residues and one His residue. They exist in two redox states. Recently, these proteins have revealed themselves as attractive drug targets for mitochondrial dysfunction-related diseases, such as type 2 diabetes, Wolfram syndrome 2, and cancers. Unfortunately, the lack of information and mechanistic understanding of ligands binding to the whole functional, cytoplasmatic domain has limited rational drug design approaches. Here, we use an enhanced sampling technique, volume-based metadynamics, recently developed by a team involving some of us, to predict the poses and affinity of the 2-benzamido-4-(1,2,3,4-tetrahydronaphthalen-2-yl)-thiophene-3-carboxylate ligand to the entire surface of the cytoplasmatic domain of the human NEET protein mitoNEET (mNT) in an aqueous solution. The calculations, based on the recently published X-ray structure of the complex, are consistent with the measured affinity. The calculated free energy landscape revealed that the ligand can bind in multiple sites and with poses other than the one found in the X-ray. This difference is likely to be caused by crystal packing effects that allow the ligand to interact with multiple adjacent NEET protein copies. Such extra contacts are of course absent in the solution; therefore, the X-ray pose is only transient in our calculations, where the binding free energy correlates with the number of contacts. We further evaluated how the reduction and protonation of the Fe-bound histidine, as well as temperature, can affect ligand binding. Both such modifications introduce the possibility for the ligand to bind in an area of the protein other than the one observed in the X-ray, with no or little impact on affinity. Overall, our study can provide insights on the molecular recognition mechanisms of ligand binding to mNT in different oxidative conditions, possibly helping rational drug design of NEET ligands.

Nanoparticle-induced biomembrane fusion: unraveling the effect of core size on stalk formation.

Membrane fusion in vitro is a strategy to load model or cell-derived vesicles with proteins, drugs, and genetic materials for theranostic applications. It is thus crucial to develop strategies to control the fusion process, also through synthetic fusogenic agents. Ligand-protected, membrane-penetrating gold nanoparticles (Au NPs) can facilitate membrane fusion, but the molecular mechanisms remain unresolved. Here, we tackle NP-induced stalk formation using a coarse-grained molecular dynamics approach and enhanced sampling techniques. We show that smaller (2 nm in diameter) NPs lead to a lower free energy barrier and higher stalk stability than larger NPs (4 nm). We demonstrate that this difference is due to a different ligand conformational freedom, which in turn depends on the Au core curvature. Our study provides precious insights into the mechanisms underlying NP-mediated membrane fusion, while our computational approach is general and applicable to studying stalk formation caused by other fusogenic agents.

Improved reweighting protocols for variationally enhanced sampling simulations with multiple walkers.

In molecular dynamics simulations utilizing enhanced-sampling techniques, reweighting is a central component for recovering the targeted ensemble averages of the "unbiased" system by calculating and applying a bias-correction function c(t). We present enhanced reweighting protocols for variationally enhanced sampling (VES) simulations by exploiting a recent reweighting method, originally introduced in the metadynamics framework [Giberti et al. J. Chem. Theory Comput., 2020, 16, 100-107], which was modified and extended to multiple-walker simulations: these may be implemented either as "independent" walkers (associated with one unique correction function per walker) or "cooperative" ones that all share one correction function, which is the hitherto only explored option. When each case is combined with the two possibilities of determining c(t) by time integration up to either t or over the entire simulation period , altogether four reweighting options result. Their relative merits were assessed by well-tempered VES simulations of two model problems: locating the free-energy difference between two metastable molecular conformations of the N-acetyl-L-alanine methylamide dipeptide, and the recovery of an a priori known distribution when one water molecule in the liquid phase is perturbed by a periodic free-energy function. The most rapid convergence occurred for large cooperative walkers, regardless of the upper integration limit, but integrating up to t proved advantageous for small walker ensembles. That novel reweighting method compared favorably to the standard VES reweighting, as well as to current state-of-the-art reweighting options introduced for metadynamics simulations that estimate c(t) by integration over the collective variables. For further gains in computational speed and accuracy, we also introduce analytical solutions for c(t), as well as offering further insight into its features by approximative analytical expressions in the "high-temperature" regime.

Computing committors via Mahalanobis diffusion maps with enhanced sampling data.

The study of phenomena such as protein folding and conformational changes in molecules is a central theme in chemical physics. Molecular dynamics (MD) simulation is the primary tool for the study of transition processes in biomolecules, but it is hampered by a huge timescale gap between the processes of interest and atomic vibrations that dictate the time step size. Therefore, it is imperative to combine MD simulations with other techniques in order to quantify the transition processes taking place on large timescales. In this work, the diffusion map with Mahalanobis kernel, a meshless approach for approximating the Backward Kolmogorov Operator (BKO) in collective variables, is upgraded to incorporate standard enhanced sampling techniques, such as metadynamics. The resulting algorithm, which we call the target measure Mahalanobis diffusion map (tm-mmap), is suitable for a moderate number of collective variables in which one can approximate the diffusion tensor and free energy. Imposing appropriate boundary conditions allows use of the approximated BKO to solve for the committor function and utilization of transition path theory to find the reactive current delineating the transition channels and the transition rate. The proposed algorithm, tm-mmap, is tested on the two-dimensional Moro-Cardin two-well system with position-dependent diffusion coefficient and on alanine dipeptide in two collective variables where the committor, the reactive current, and the transition rate are compared to those computed by the finite element method (FEM). Finally, tm-mmap is applied to alanine dipeptide in four collective variables where the use of finite elements is infeasible.

Thermodynamic Insight into Thermal Cracking of n-Hexane in the H-FAU Zeolite

To understand catalytic cracking processes of alkanes in the petrochemical industry, the monomolecular cracking mechanism of n-hexane in the H-FAU zeolite has been examined using ab initio molecular dynamics simulations combined with enhanced sampling techniques. It has been found that the adsorption energies of short n-alkanes are linearly correlated with the chain length and contact areas with the zeolite framework, while no such correlation can be applied to the short n-alkenes. High-dimensional free energy landscapes characterizing four cracking modes of n-hexane at three different temperatures have been drawn. The electron transfer in the cracking process was analyzed by quantifying the charge evolution for carbon atoms. The formation of carbonium ions in each cracking mode is found to be the rate-limiting step. At high temperature, free energy differences are nonpositive values, suggesting that the cracking of n-hexane is spontaneous, which is also coincident with the experimental observation. The cracking of the central C–C bond of n-hexane is easier than the cracking of terminal C–C bonds, which is due to the lower free energy barrier. The present work sheds new insights into the cracking process of n-alkanes in the industrially used FAU zeolite catalysts.

Molecular Motion in the Interconverting σ-H2, Di-, and Tri-hydride Regimes: .

The transition-metal complex is known to exist in three possible isomeric forms, including a nonclassical, σ-bound dihydrogen complex and two classical dihydride isomers. As such, it has served as a model complex for the energies of conversion between these limiting structural regimes. In the present study, ab initio molecular dynamics computer simulations, combined with enhanced sampling techniques, were utilized to directly assess the degree of motion and isomerization of the dihydrogen/dihydride moieties in this complex. Ligand rotations (for both the H2 unit and the phosphine units) were found to be dominant in the low-temperature (298 K) regime, and the classical thermodynamic distribution showed no probability of thermally accessing dihydride forms, although unrestrained molecular dynamics trajectories showed fleeting configurations outside of the σ-H2 configuration. Simulations at higher temperatures surprisingly revealed new tri-hydride isomers that are energetically competitive with the σ-H2 and cis-/trans-dihydride isomers. Low-energy pathways to hydrogen/hydride transfer and phosphine dissociation were readily accessible, which considerably expands the known isomeric flexibility of this complex.

Water regulates the residence time of Benzamidine in Trypsin

The process of ligand-protein unbinding is crucial in biophysics. Water is an essential part of any biological system and yet, many aspects of its role remain elusive. Here, we simulate with state-of-the-art enhanced sampling techniques the binding of Benzamidine to Trypsin which is a much studied and paradigmatic ligand-protein system. We use machine learning methods to determine efficient collective coordinates for the complex non-local network of water. These coordinates are used to perform On-the-fly Probability Enhanced Sampling simulations, which we adapt to calculate also the ligand residence time. Our results, both static and dynamic, are in good agreement with experiments. We find that the presence of a water molecule located at the bottom of the binding pocket allows via a network of hydrogen bonds the ligand to be released into the solution. On a finer scale, even when unbinding is allowed, another water molecule further modulates the exit time.

The Conformational Transition Pathways and Hidden Intermediates in DFG-Flip Process of c-Met Kinase Revealed by Metadynamics Simulations.

Protein kinases intrinsically translate their conformations between active and inactive states, which is key to their enzymatic activities. The conformational flipping of the three-residue conservative motif, Asp-Phe-Gly (DFG), is crucial for many kinases' biological functions. Obtaining a detailed demonstration of the DFG flipping process and its corresponding dynamical and thermodynamical features could broaden our understanding of kinases' conformation-activity relationship. In this study, we employed metadynamics simulation, a widely used enhanced sampling technique, to analyze the conformational transition pathways of the DFG flipping for the c-Met kinase. The corresponding free energy landscape suggested two distinct transition pathways between the "DFG-in" and "DFG-out" states of the DFG-flip from c-Met. On the basis of the orientation direction of the F1223 residue, we correspondingly named the two pathways the "DFG-up" path, featuring forming a commonly discovered "DFG-up" transition state, and the "DFG-down" path, a unique transition pathway with F1223 rotating along the opposite direction away from the hydrophobic cavity. The free energies along the two pathways were then calculated using the Path Collective Variable (PCV) metadynamics simulation. The simulation results showed that, though having similar free energy barriers, the free energy cuve for the DFG-down path suggested a two-step conformational transition mechanism, while that for the DFG-up path showed the one-step transition feature. The c-Met DFG flipping mechanism and the new intermediate state discovered in this work could provide a deeper understanding of the conformation-activity relationship for c-Met and, possibly, reveal a new conformational state as the drug target for c-Met and other similar kinases.

Does Hamiltonian Replica Exchange via Lambda-Hopping Enhance the Sampling in Alchemical Free Energy Calculations?

In the context of computational drug design, we examine the effectiveness of the enhanced sampling techniques in state-of-the-art free energy calculations based on alchemical molecular dynamics simulations. In a paradigmatic molecule with competition between conformationally restrained E and Z isomers whose probability ratio is strongly affected by the coupling with the environment, we compare the so-called -hopping technique to the Hamiltonian replica exchange methods assessing their convergence behavior as a function of the enhanced sampling protocols (number of replicas, scaling factors, simulation times). We found that the pure -hopping, commonly used in solvation and binding free energy calculations via alchemical free energy perturbation techniques, is ineffective in enhancing the sampling of the isomeric states, exhibiting a pathological dependence on the initial conditions. Correct sampling can be restored in -hopping simulation by the addition of a “hot-zone” scaling factor to the -stratification (FEP+ approach), provided that the additive hot-zone scaling factors are tuned and optimized using preliminary ordinary replica-exchange simulation of the end-states.

Changes in Protonation States of In-Pathway Residues can Alter Ligand Binding Pathways Obtained From Spontaneous Binding Molecular Dynamics Simulations.

Protein-ligand binding processes often involve changes in protonation states that can be key to recognize and orient the ligand in the binding site. The pathways through which (bio)molecules interplay to attain productively bound complexes are intricate and involve a series of interconnected intermediate and transition states. Molecular dynamics (MD) simulations and enhanced sampling techniques are commonly used to characterize the spontaneous binding of a ligand to its receptor. However, the effect of protonation state changes of in-pathway residues in spontaneous binding MD simulations remained mostly unexplored. Here, we used molecular dynamics simulations to reconstruct the trypsin-benzamidine binding pathway considering different protonation states of His57. This residue is part of the trypsin catalytic triad and is located more than 10 Å away from Asp189, which is responsible for benzamidine binding in the trypsin S1 pocket. Our MD simulations showed that the binding pathways that benzamidine follow to target the S1 binding site are critically dependent on the His57 protonation state. Binding of benzamidine frequently occurs when His57 is protonated in the delta nitrogen while the binding process is significantly less frequent when His57 is positively charged. Constant-pH MD simulations retrieved the equilibrium populations of His57 protonation states at trypsin active pH offering a clearer picture of benzamidine recognition and binding. These results indicate that properly accounting for protonation states of distal residues can be important in spontaneous binding MD simulations.

Improving the Accuracy of Atomistic Simulations of the Electrochemical Interface.

Atomistic simulation of the electrochemical double layer is an ambitious undertaking, requiring quantum mechanical description of electrons, phase space sampling of liquid electrolytes, and equilibration of electrolytes over nanosecond time scales. All models of electrochemistry make different trade-offs in the approximation of electrons and atomic configurations, from the extremes of classical molecular dynamics of a complete interface with point-charge atoms to correlated electronic structure methods of a single electrode configuration with no dynamics or electrolyte. Here, we review the spectrum of simulation techniques suitable for electrochemistry, focusing on the key approximations and accuracy considerations for each technique. We discuss promising approaches, such as enhanced sampling techniques for atomic configurations and computationally efficient beyond density functional theory (DFT) electronic methods, that will push electrochemical simulations beyond the present frontier.

A Potential Route of Capsaicin to Its Binding Site in the TRPV1 Ion Channel.

Transient receptor potential (TRP) ion channels are important pharmacological targets because of their role in the perception of pain, and so, understanding their chemical regulation is essential for the development of analgesic drugs. Among the currently known TRP channel chemical agonists, capsaicin, the active compound of chili pepper, is probably the most exhaustively studied. The availability of the three-dimensional structure of the vanilloid receptor 1 (TRPV1) has fueled computational studies revealing the molecular details of capsaicin binding modes. Although this is a significant step, a comprehensible binding mechanism or pathway is invaluable for targeting TRP channels in modern pharmacology. In the present work, free-energy and enhanced sampling techniques have been used to explore a possible membrane-mediated pathway for capsaicin to enter the TRPV1 binding pocket where capsaicin accesses the protein starting at the extracellular milieu through the outer leaflet and into its binding site in the protein. The main states visited along this route have been characterized and include (i) a bound state in agreement with the binding mode “head-down, tail-up” and (ii) an alternative state corresponding to a “head-up, tail-down” binding mode. In agreement with previous reports, binding is mediated by both hydrogen bonds and van der Waals interactions, and residue Y511 is crucial for stabilizing the bound state and during the binding process. Together, these results provide a foundation to further understand TRPV channels, and they could be used to guide therapeutic design of selective inhibitors potentially leading to novel avenues for pharmacological applications targeting the TRPV1 channel.

Transient local secondary structure in the intrinsically disordered C‐term of the Albino3 insertase

Albino3 (Alb3) is an integral membrane protein fundamental to the targeting and insertion of light‐harvesting complex (LHC) proteins into the thylakoid membrane. Alb3 contains a stroma‐exposed C‐terminus (Alb3‐Cterm) that is responsible for binding the LHC‐loaded transit complex before LHC membrane insertion. Alb3‐Cterm has been reported to be intrinsically disordered, but precise mechanistic details underlying how it recognizes and binds to the transit complex are lacking, and the functional roles of its four different motifs have been debated. Using a novel combination of experimental and computational techniques such as single‐molecule fluorescence resonance energy transfer, circular dichroism with deconvolution analysis, site‐directed mutagenesis, trypsin digestion assays, and all‐atom molecular dynamics simulations in conjunction with enhanced sampling techniques, we show that Alb3‐Cterm contains transient secondary structure in motifs I and II. The excellent agreement between the experimental and computational data provides a quantitatively consistent picture and allows us to identify a heterogeneous structural ensemble that highlights the local and transient nature of the secondary structure. This structural ensemble was used to predict both the inter‐residue distance distributions of single molecules and the apparent unfolding free energy of the transient secondary structure, which were both in excellent agreement with those determined experimentally. We hypothesize that this transient local secondary structure may play an important role in the recognition of Alb3‐Cterm for the LHC‐loaded transit complex, and these results should provide a framework to better understand protein targeting by the Alb3‐Oxa1‐YidC family of insertases.

Time Evolution of the Millisecond Allosteric Activation of Imidazole Glycerol Phosphate Synthase.

Deciphering the molecular mechanisms of enzymatic allosteric regulation requires the structural characterization of functional states and also their time evolution toward the formation of the allosterically activated ternary complex. The transient nature and usually slow millisecond time scale interconversion between these functional states hamper their experimental and computational characterization. Here, we combine extensive molecular dynamics simulations, enhanced sampling techniques, and dynamical networks to describe the allosteric activation of imidazole glycerol phosphate synthase (IGPS) from the substrate-free form to the active ternary complex. IGPS is a heterodimeric bienzyme complex whose HisH subunit is responsible for hydrolyzing glutamine and delivering ammonia for the cyclase activity in HisF. Despite significant advances in understanding the underlying allosteric mechanism, essential molecular details of the long-range millisecond allosteric activation of IGPS remain hidden. Without using a priori information of the active state, our simulations uncover how IGPS, with the allosteric effector bound in HisF, spontaneously captures glutamine in a catalytically inactive HisH conformation, subsequently attains a closed HisF:HisH interface, and finally forms the oxyanion hole in HisH for efficient glutamine hydrolysis. We show that the combined effector and substrate binding dramatically decreases the conformational barrier associated with oxyanion hole formation, in line with the experimentally observed 4500-fold activity increase in glutamine hydrolysis. The allosteric activation is controlled by correlated time-evolving dynamic networks connecting the effector and substrate binding sites. This computational strategy tailored to describe millisecond events can be used to rationalize the effect of mutations on the allosteric regulation and guide IGPS engineering efforts.

Modeling‐Led Materials‐Binding Peptide Design for Hexagonal Boron Nitride Interfaces

AbstractPeptides that can bind specific nanomaterials with affinity and specificity are attractive for realizing a wide range of applications. Manipulation of biomolecule/2D‐material interfaces via noncovalent interactions in aqueous media has gained intensive attention due to the promising potential for biomolecule‐facilitated 2D‐material exfoliation, dispersion, and organization in water. Such advances have been recently achieved for graphene, where several peptide sequences have demonstrated this capability. However, few peptides are known specific binders of hexagonal boron nitride (h‐BN), resulting in a lack of fundamental knowledge regarding biomolecule/h‐BN interactions at the aqueous interface. To address this, enhanced sampling techniques are used to complete the set of interfacial adsorption free energies for all 20 amino acids, and a range of tripeptides. Based on these data, a reductionist approach is proposed to design new dodecapeptides anticipated to have stronger binding to h‐BN compared with a known h‐BN‐binding peptide, BP7, based on rearrangements of the tripeptide motifs within BP7. This hypothesis is tested using replica exchange with solute tempering molecular dynamics simulations, and the results indicate significantly increased surface contact for the two proposed BP7‐derived sequences. This work provides a rational, economical, and general approach to propose, design, and examine new material‐binding peptides based on their constituent properties.

Toward Convergence in Folding Simulations of RNA Tetraloops: Comparison of Enhanced Sampling Techniques and Effects of Force Field Modifications.

Atomistic molecular dynamics simulations represent an established technique for investigation of RNA structural dynamics. Despite continuous development, contemporary RNA simulations still suffer from suboptimal accuracy of empirical potentials (force fields, ffs) and sampling limitations. Development of efficient enhanced sampling techniques is important for two reasons. First, they allow us to overcome the sampling limitations, and second, they can be used to quantify ff imbalances provided they reach a sufficient convergence. Here, we study two RNA tetraloops (TLs), namely the GAGA and UUCG motifs. We perform extensive folding simulations and calculate folding free energies (ΔGfold°) with the aim to compare different enhanced sampling techniques and to test several modifications of the nonbonded terms extending the AMBER OL3 RNA ff. We demonstrate that replica-exchange solute tempering (REST2) simulations with 12-16 replicas do not show any sign of convergence even when extended to a timescale of 120 μs per replica. However, the combination of REST2 with well-tempered metadynamics (ST-MetaD) achieves good convergence on a timescale of 5-10 μs per replica, improving the sampling efficiency by at least 2 orders of magnitude. Effects of ff modifications on ΔGfold° energies were initially explored by the reweighting approach and then validated by new simulations. We tested several manually prepared variants of the gHBfix potential which improve stability of the native state of both TLs by ∼2 kcal/mol. This is sufficient to conveniently stabilize the folded GAGA TL while the UUCG TL still remains under-stabilized. Appropriate adjustment of van der Waals parameters for C-H···O5' base-phosphate interaction may further stabilize the native states of both TLs by ∼0.6 kcal/mol.

Assessing models of force-dependent unbinding rates via infrequent metadynamics.

Protein-ligand interactions are crucial for a wide range of physiological processes. Many cellular functions result in these non-covalent "bonds" being mechanically strained, and this can be integral to proper cellular function. Broadly, two classes of force dependence have been observed-slip bonds, where the unbinding rate increases, and catch bonds, where the unbinding rate decreases. Despite much theoretical work, we cannot predict for which protein-ligand pairs, pulling coordinates, and forces a particular rate dependence will appear. Here, we assess the ability of MD simulations combined with enhanced sampling techniques to probe the force dependence of unbinding rates. We show that the infrequent metadynamics technique correctly produces both catch and slip bonding kinetics for model potentials. We then apply it to the well-studied case of a buckyball in a hydrophobic cavity, which appears to exhibit an ideal slip bond. Finally, we compute the force-dependent unbinding rate of biotin-streptavidin. Here, the complex nature of the unbinding process causes the infrequent metadynamics method to begin to break down due to the presence of unbinding intermediates, despite the use of a previously optimized sampling coordinate. Allowing for this limitation, a combination of kinetic and free energy computations predicts an overall slip bond for larger forces consistent with prior experimental results although there are substantial deviations at small forces that require further investigation. This work demonstrates the promise of predicting force-dependent unbinding rates using enhanced sampling MD techniques while also revealing the methodological barriers that must be overcome to tackle more complex targets in the future.

Securing the Chain of Custody and Integrity of Data in a Global North-South Partnership to Monitor the Quality of Essential Medicines.

Substandard and falsified (SF) pharmaceuticals account for an estimated 10% of the pharmaceutical supply chain in low- and middle-income countries (LMICs), where a lack of regulatory and laboratory resources limits the ability to conduct effective post-market surveillance and allows SF products to penetrate the supply chain. The Distributed Pharmaceutical Analysis Laboratory (DPAL) was established in 2014 to expand testing of pharmaceutical dosage forms sourced from LMICs; DPAL is an alliance of academic institutions throughout the United States and abroad that provides high-quality, validated chemical analysis of pharmaceutical dosage forms sourced from partners in LMICs. Results from analysis are reported to relevant regulatory agencies and are used to inform purchasing decisions made by in-country stakeholders. As the DPAL program has expanded to testing more than 1,000 pharmaceutical dosage forms annually, challenges have surfaced regarding data management and sample tracking. Here, we describe a pilot project between DPAL and ARTiFACTs that applies the blockchain to organize and manage key data generated during the DPAL workflow, including a sample's progress through the workflow, its physical location, provenance of metadata, and lab reputability. Recording time and date stamps with these data will create a permanent and verifiable chain of custody for samples. This secure, distributed ledger will be linked to an easy-to-use dashboard, allowing stakeholders to view results and experimental details for each sample in real time and verify the integrity of DPAL analysis data. Introducing this blockchain-based system as a pilot will allow us to test the technology with real users analyzing real samples. Feedback from users will be recorded and necessary adjustments will be made to the system before the implementation of blockchain across all DPAL sites. Anticipated benefits of implementing the blockchain technology for managing DPAL data include efficient management for routing work, increasing throughput, creating a chain of custody for samples and their data in alignment with the distributed nature of DPAL, and using the analysis results to detect patterns of quality within and across brands of products and develop enhanced sampling techniques and best practices.