Tool For Molecular Analysis Research Articles

Determining uncertainties in PICRUSt analysis – An easy approach for autotrophic nitrogen removal

The diversity and dynamics of microorganisms in engineered ecosystems have a high impact on performance and operational stability. Nitrogen removal from wastewater is one example of such complex and dynamic ecosystems. Following the microbial community composition and its functional potential is highly valuable information for optimizing performance. Molecular methods and data analysis tools have become more and more popular in recent years. PICRUSt, a bioinformatics tool to predict the functional potential of a sample from 16S rRNA amplicon sequencing, was tested in the context of autotrophic nitrogen removal for its accuracy. Two experimental studies were extended by qPCR to demonstrate how qPCR can be used to deliver information about the accuracy of PICRUSt predictions. Two main points were discovered: (1) the correlation between qPCR data and PICRUSt predictions depends on the relative abundance of the target gene. With higher abundance, better correlations are achievable; (2) the more genome information available, the stronger the correlation.

Predicting Molecular Energy Using Force-Field Optimized Geometries and Atomic Vector Representations Learned from an Improved Deep Tensor Neural Network.

The use of neural networks to predict molecular properties calculated from high level quantum mechanical calculations has made significant advances in recent years, but most models need input geometries from DFT optimizations which limit their applicability in practice. In this work, we explored how machine learning can be used to predict molecular atomization energies and conformation stability using optimized geometries from Merck Molecular Force Field (MMFF). On the basis of the recently introduced deep tensor neural network (DTNN) approach, we first improved its training efficiency and performed an extensive search of its hyperparameters, and developed a DTNN_7ib model which has a test accuracy of 0.34 kcal/mol mean absolute error (MAE) on QM9 data set. Then using atomic vector representations in the DTNN_7ib model, we employed transfer learning (TL) strategy to train readout layers on the QM9M data set, in which QM properties are the same as in QM9 [calculated at the B3LYP/6-31G(2df,p) level] while molecular geometries are corresponding local minima optimized with MMFF94 force field. The developed TL_QM9M model can achieve an MAE of 0.79 kcal/mol using MMFF optimized geometries. Furthermore, we demonstrated that the same transfer learning strategy with the same atomic vector representation can be used to develop a machine learning model that can achieve an MAE of 0.51 kcal/mol in molecular energy prediction using MMFF geometries for an eMol9_CM conformation data set, which consists of 9959 molecules and 88 234 conformations with energies calculated at the B3LYP/6-31G* level. Our results indicate that DFT-level accuracy of molecular energy prediction can be achieved using force-field optimized geometries and atomic vector representations learned from deep tensor neural network, and integrated molecular modeling and machine learning would be a promising approach to develop more powerful computational tools for molecular conformation analysis.

Characterization of 15 nuclear microsatellite markers for Afzelia africana (Fabaceae) and related species.

Premise Afzelia africana (Fabaceae) is a valuable, internationally vulnerable tree species in tropical Africa. The development of specific simple sequence repeat (SSR) loci is necessary for population genetic studies in this tree species and its closest relatives.Methods And ResultsFifteen new polymorphic microsatellite markers were developed for A. africana using Illumina next‐generation sequencing. We tested the polymorphism of the 15 loci in three populations in Benin, West Africa. The number of expressed alleles per locus varied from one to 12. The levels of observed and expected heterozygosity ranged from 0.100 to 1.000 and from 0.095 to 0.882, respectively. Most markers successfully amplified in the closely related species A. quanzensis and A. bipindensis, but less so in A. bipindensis.ConclusionsBecause of their cross‐amplification ability, these newly developed loci will serve as useful tools for future molecular analyses on A. africana and related species.

A Simple and Cost-Effective Freeze-Thaw Based Method for Plasmodium DNA Extraction from Dried Blood Spot

Available DNA isolation methods for Plasmodium involve numerous processing steps, adding to the cost and conferring risk of contamination. Here we devise a simple and cost-effective method for direct extraction of Plasmodium DNA from dried filter paper spot (DBS), appropriate for resource-limited setups. The protocol involves simple freezing and thawing of DBS, neither involves any purification step nor any chemical reagent. The method was assessed in terms of DNA quantity, PCR detection sensitivity, time requirement, cost effectiveness, labor intensiveness and degree of shearing. The reliability of this method was confirmed by comparing it with other in use methods for Plasmodium DNA isolation. Pure DNA was obtained with this method, as exemplified by the absorbance ratio (260nm /280nm) of 1.2. The protocol produced digestible, PCR-grade genomic DNA, also found to be suitable for sequencing. DNA isolated remained stable and retained its integrity after storage for one month at 4 °C. Our process substantiated as efficient, reproducible, simple, fast, and inexpensive. Development of this optimized freeze-thaw based DNA extraction method for malaria parasite may provide a valuable tool for molecular analysis in resource-limited setups. This is the first report of DNA extraction from DBS of Plasmodium utilizing freeze-thaw.

Filamentous phages: masters of a microbial sharing economy.

Bacteriophage ("bacteria eaters") or phage is the collective term for viruses that infect bacteria. While most phages are pathogens that kill their bacterial hosts, the filamentous phages of the sub-class Inoviridae live in cooperative relationships with their bacterial hosts, akin to the principal behaviours found in the modern-day sharing economy: peer-to-peer support, to offset any burden. Filamentous phages impose very little burden on bacteria and offset this by providing service to help build better biofilms, or provision of toxins and other factors that increase virulence, or modified behaviours that provide novel motile activity to their bacterial hosts. Past, present and future biotechnology applications have been built on this phage-host cooperativity, including DNA sequencing technology, tools for genetic engineering andmolecular analysis of gene expression and protein production, and phage-display technologies for screening protein-ligand and protein-protein interactions. With the explosion of genome and metagenome sequencing surveys around the world, we are coming to realize that our knowledge of filamentous phage diversity remains at a tip-of-the-iceberg stage, promising that new biology and biotechnology are soon to come.

The Placental Atlas Tool (PAT): A collaborative research and discovery platform for the placental research community

IntroductionThe placenta is one of the least understood, yet arguably one of the most important organs for human health and development. While there have been numerous research efforts dedicated to understanding the placenta's critical role, these studies and the data they produced remain separated and largely disparate. In order to facilitate placental research, the Eunice Kennedy Shriver National Institute of Child and Human Development (NICHD) released in October 2018 the Placental Atlas Tool (PAT) (https://pat.nichd.nih.gov/), an internet-based platform offering users a centralized placental database of molecular datasets, analytic tools, and images. MethodsPAT is a cloud-based system developed by the business requirements defined by NICHD leadership and extramural placental researchers. PAT employs a metadata-driven web interface to provide curated placental datasets and images, enriched with structured, descriptive metadata to enhance data discoverability. PAT also incorporates open source molecular data analytical tools to provide a flexible analytics workflow for placental researchers. ResultsPAT launched with 426 analyzable molecular placental datasets consisting of over 12,500 samples from 10 distinct species, all systematically annotated and processed for enhanced research utility. 828 placental images, consisting of 7 imaging modalities across 47 species, and nearly 300 annotated linked publications supplement the datasets to facilitate knowledge integration and hypothesis generation across disparate molecular studies. DiscussionPAT will maximize the NICHD's investment in placental research by reinforcing open scientific inquiry, facilitating reuse of datasets, promoting novel research and testing of new hypotheses and analytic methods, and facilitating education of new researchers.

Quantitative, Diffusion NMR Based Analytical Tool To Distinguish Folded, Disordered, and Denatured Biomolecules.

The key questions in folding studies are the protein dimensions and the degree of folding. These properties are best characterized by the self-diffusion coefficients D determining the hydrodynamic dimensions. In our present study, we derive empirical variations of D as a function of molecular mass M that distinguish folded, intrinsically disordered, and urea-denatured biomolecules. Reliable D values are obtained from diffusion NMR measurements performed under identical conditions using a representative set of proteins/peptides with diverse amino acid sequence and length. The established relations are easy to use analytical tools for molecular mass analysis and aggregation studies as well. Deriving equations under denaturing conditions has several pitfalls, and here, we provide a simple quantitative method for estimating the debated end point of denaturation, while already the 1D 1H spectrum gives a qualitative picture of the collapsed, denatured structure. Data indicate that the intrinsically disordered proteins have a similar behavior as synthetic polymers and urea-denatured proteins.

Diversity of Biomphalaria spp. freshwater snails and associated mollusks in areas with schistosomiasis risk, using molecular and spatial analysis tools

Abstract: The Middle Paranapanema River region of São Paulo, Brazil is home to significant diversity of Biomphalaria species and is very vulnerable to health and environmental impacts such as schistosomiasis. This study updates freshwater malacological surveys for ecosystems in one portion of the Middle Paranapanema River Basin, with emphasis on the genus Biomphalaria. Snails were collected from 114 distinct bodies of water between 2015 and 2018. Biomphalaria specimens were identified according to morphological and molecular characteristics, while animals in other genera (Drepanotrema, Lymnaea, Melanoides, Physa and Pomacea) were identified solely according to shell characteristics. A geographic information system was used to update intermediate host colonization sites and consequently assist in identifying probable hotspots for intermediate hosts of schistosomiasis. The sequences of the COI gene relating to the DNA barcode stretch were tested for similarity against sequences found in GenBank, for monophyly through Maximum Likelihood phylogenetic inference, and analyzed in ABDG, bPTP and GMYC for the delimitation of putative species. Of the 10,722 snails collected, 86.7% were in the Planorbidae family (75.5% Biomphalaria and 11.2% Drepanotrema) and 13.3% were other non-Planorbidae species (Lymnaea, Melanoides, Physa and Pomacea). The taxonomic COI reference sequences in the NCBI nucleotide database used for DNA sequence comparison, and phylogenetic analysis used to test the monophyly of the groups, resulted in more reliable taxonomic units than delimitation of the COI sequences in MOTUs using statistical taxonomic models. Analysis of the species distribution shows that B. glabrata and B. tenagophila are heterogeneously distributed in the study area. B. glabrata colonizes only five water bodies, in the study area, most of them in Ourinhos, while B. tenagophila predominates in water bodies in Ipaussu. Contrasting with this, B. straminea, B. occidentalis and B. peregrina are evenly distributed throughout the study area.

Giant Chemical Surface Enhancement of Coherent Raman Scattering on MoS2

Raman spectroscopy is a powerful tool for molecular chemical analysis and bioimaging, which shows an astonishing sensitivity when combined with a huge enhancement by the coherence and surface effects. Noble metal nanoparticles have been commonly used for the spontaneous surface-enhanced Raman scattering (SERS) and for the surface-enhanced coherent anti-Stokes Raman scattering (SECARS) spectroscopies, as they provide large enhancement factors via the electromagnetic and chemical mechanisms. Recently, two-dimensional (2D) semiconductors, such as monolayer molybdenum disulfide (MoS2), were used for potential SERS applications as cheaper substrates compared to noble metal nanoparticles. However, the coherent enhancement of SECARS on 2D materials has not been previously explored. Here we present the experimental SECARS measurements of pyridine–ethanol solutions containing 2D MoS2 nanocrystals with the giant chemical enhancement factor of 109 over coherent anti-Stokes Raman scattering (CARS), which is attribute...

Progress of analytical tools and techniques for human gut microbiome research

Massive DNA sequencing studies have expanded our insights and understanding of the ecological and functional characteristics of the gut microbiome. Advanced sequencing technologies allow us to understand the close association of the gut microbiome with human health and critical illnesses. In the future, analyses of the gut microbiome will provide key information associating with human individual health, which will help provide personalized health care for diseases. Numerous molecular biological analysis tools have been rapidly developed and employed for the gut microbiome researches; however, methodological differences among researchers lead to inconsistent data, limiting extensive share of data. It is therefore very essential to standardize the current methodologies and establish appropriate pipelines for human gut microbiome research. Herein, we review the methods and procedures currently available for studying the human gut microbiome, including fecal sample collection, metagenomic DNA extraction, massive DNA sequencing, and data analyses with bioinformatics. We believe that this review will contribute to the progress of gut microbiome research in the clinical and practical aspects of human health.

SERS-Active-Charged Microgels for Size- and Charge-Selective Molecular Analysis of Complex Biological Samples.

Surface-enhanced Raman scattering (SERS) provides a dramatic increase of Raman intensity for molecules adsorbed on nanogap-rich metal nanostructures, serving as a promising tool for molecular analysis. However, surface contamination caused by protein adsorption and low surface concentration of small target molecules reduce the sensitivity, which severely restricts the use of SERS in many applications. Here, charged microgels containing agglomerates of gold nanoparticles (Au NPs) are designed using droplet-based microfluidics to provide a reliable SERS substrate with molecular selectivity and high sensitivity. The limiting mesh size of hydrogel enables the autonomous exclusion of large proteins and the charged matrix concentrates oppositely charged small molecules through electrostatic attraction. As nanogaps among Au NPs in the agglomerates enhance Raman intensity, Raman spectrum of the adsorbed molecules is selectively measured with high sensitivity in the absence of interruption from adhesive proteins. Therefore, the SERS-active-charged microgels can be used for direct analysis of pristine biological samples without the pretreatment steps of separation and concentration, which are commonly a prerequisite for Raman analysis. For the purpose of demonstration, a direct detection of fipronil sulfone with partial negative charges, a metabolite of toxic insecticide, dissolved in eggs using the positively charged microgels without any pretreatment of the samples, is shown.

Nanofluidic terahertz metasensor for sensing in aqueous environment

The terahertz spectral region has received tremendous attention for label free chemical and biological sensing, due to the presence of molecular fingerprints, low energy characteristics, and remote sensing capabilities. However, a major hindrance for the realization of a high performance terahertz bio-chemical sensor comes from the large absorption of terahertz waves by aqueous solution. Here, we overcome this limitation by confining the analyte-aqueous solution in a nanovolumetric fluidic chamber, integrated on metamaterial resonant cavities. The metamaterial resonators confine electromagnetic fields in extremely subwavelength space and hence allow for the enhanced interaction between the nanovolumetric analyte-aqueous solution and terahertz waves, while minimizing the absorption loss. We compare the sensing performance of split ring resonator and Fano resonator systems as metamaterial resonators. As a demonstration of chemical sensing, three alcoholic solutions with different concentrations were measured. Selective adenosine triphosphate (ATP) sensing capability was examined through ATP aptamer functionalization on gold metamaterials, where a decrease in the transmittance value was observed as the ATP concentration increased. The proposed sensing approach has the potential to be an effective tool for molecular analysis through exploiting the advantages offered by low energy terahertz, subwavelength metamaterial resonators and nanofluidic technologies.

PO-463 Multiparametric analysis of lung cancer tissue sections using imaging mass cytometry

IntroductionA novel tool for multiparametric molecular pathology analysis of tissue sections is described. Imaging Mass Cytometry (IMC), a new mass spectrometer-based technology, provides visualisation and spatial distribution of up to 40 markers in a single tissue section with 1 µm resolution. IMC uses metal-tagged antibodies (mtAbs), a pulsed UV laser for ablating regions of interest, and a stream of inert gas to transfer material generated by the laser to the mass cytometer.1Material and methodsTissue microarray (TMA) of human lung cancer was stained according to IMC protocol2 using a mix of 23 mtAbs.The samples were inserted into the ablation chamber of the Hyperion Imaging System. CyTOF® Software v6.7 and MCD Viewer 1.0 were used for data acquisition and rendering of pseudo three-colour images. Quantification of selected markers was done with Definiens Tissue Studio® (DTS) software. Standard HPA protocol was used for immunohistochemical (IHC) staining.Results and discussionsIMC analysis of human lung cancer TMA stained with a panel of 23 mtAbs revealed that core morphology was consistent with anatomopathological tumour classification. Immune cell phenotype and spatial distribution assessed by IHC and IMC were equivalent.IMC generated data was used to quantitate PD-L1 marker expression. Percentages of cells expressing different levels of PD-L1 and average intensity of PD-L1 related signal were calculated for tumour and stroma regions of each core. In addition, PD-L1 corresponding signal intensity was calculated in cytoplasm and membrane compartments of marker-positive cells.ConclusionIMC technology is a powerful tool for multiparametric histopathological analysis. It allows researchers to simultaneously detect up to 40 markers with single-cell detection resolution equivalent to conventional IHC. Using DTS software we demonstrate quantitation of multiple markers in lung tumour sections probed with a panel of 23 mtAbs.ReferencesChang Q, Ornatsky OI, Siddiqui I, Loboda A, Baranov VI, Hedley DW. Imaging Mass Cytometry. Cytometry A 2017;91:160–169.Chang Q, Ornatsky O, Hedley D. Staining of frozen and formalin-fixed, paraffin-embedded tissues with metal-labeled antibodies for Imaging Mass Cytometry analysis. Curr Protoc Cytom, 2017;82(October):12.47.1–12.47.8.

Isolation and characterization of Bacillus sp. strain BC01 from soil displaying potent antagonistic activity against plant and fish pathogenic fungi and bacteria.

Fungal and bacterial pathogens infect a diverse range of hosts including various plant and animal species. Fungal and bacterial diseases, especially of plants and aquatic animals, such as fish, lead to significant damage to crops and aquaculture, respectively, worldwide. The present study was conducted to isolate and characterize potent Bacillus strains with significant antagonistic activity against the major plant and fish pathogenic fungi and bacteria. We randomly collected 22 isolates of Bacillus from the soil, rhizosphere, and sediment from different parts of Bangladesh. Initial characterization, based on in vitro antagonistic activity on the culture plate, resulted in the selection of four gram-positive Bacillus sp. isolates. Among these, the isolate BC01, obtained from soil demonstrated the highest broad-spectrum anti-bacterial and anti-fungal activities. We confirmed the genus of BC01 to be Bacillus by morphological and biochemical tests as well as using molecular data analysis tools, including the study of 16s rDNA, phylogenetic relationship, and evolutionary divergence scores. The isolate significantly inhibited the mycelial growth of the plant pathogen, Penicillium digitatum and fish pathogen, Aphanomyces invadans in vitro. The anti-bacterial effect of the isolate was also evaluated against Pseudomonas spp. and Xanthomonas spp., the two deadliest plant pathogens, and Aeromonas veronii, Pseudomonas fluorescens, and Streptococcus iniae, three major fish pathogens that are primarily responsible for global aquaculture loss. The results of the present study could pave the way for developing potent drugs to combat microbial infection of plants and fish.

Biology Needs Evolutionary Software Tools: Let's Build Them Right.

Research in population genetics and evolutionary biology has always provided a computational backbone for life sciences as a whole. Today evolutionary and population biology reasoning are essential for interpretation of large complex datasets that are characteristic of all domains of today’s life sciences ranging from cancer biology to microbial ecology. This situation makes algorithms and software tools developed by our community more important than ever before. This means that we, developers of software tool for molecular evolutionary analyses, now have a shared responsibility to make these tools accessible using modern technological developments as well as provide adequate documentation and training.

Rapidly evolving sex-specific sequences in Calamus travancoricus Bedd. ex. Becc. and Calamus nagbettai R.R.Fernald & Dey

Gene sequences mediating sexual reproduction are more divergent within and between closely related species. Microsatellite or simple sequence repeat (SSR) markers are valuable molecular tools for analysis of genetic variability, phylogeny, and also for identifying sex at seedling stage in dioecious plant species. Calamus travancoricus Bedd. ex. Becc. and Calamus nagbettai R.R.Fernald & Dey are economically important rattan species. The dioecious nature of the Calamus spp. limits its breeding and cultivation. The sex of rattans can only be identified after attaining reproductive maturity which ranges from 5 to 15 years. A study was carried out in this background and 9 putative sex-specific PCR products were identified as sex markers for C. travancoricus and C. nagbettai and sequenced by Sanger method. The sequence homology search revealed occurrence of identical sequences in many plant species across different families indicating the conserved nature of the sequences. However, these sequences were not present in opposite sex in the studied species, indicating divergent evolution favoring sex determination. Annotation of these sequences revealed that most of these are mediating sexual reproduction by and large. An adequate sex ratio is to be maintained for these dioecious palms in natural habitat for producing offsprings having equal gene complements for continual evolution and sustainable utilization. Developing scientific management strategies and improved utilization of canes could help to generate employment locally and thus contribute to the socioeconomics sustainably.

Optimizing the performance of reactive molecular dynamics simulations for many-core architectures

Reactive molecular dynamics simulations are computationally demanding. Reaching spatial and temporal scales where interesting scientific phenomena can be observed requires efficient and scalable implementations on modern hardware. In this article, we focus on optimizing the performance of the widely used LAMMPS/ReaxC package for many-core architectures. As hybrid parallelism allows better leverage of the increasing on-node parallelism, we adopt thread parallelism in the construction of bonded and nonbonded lists and in the computation of complex ReaxFF interactions. To mitigate the I/O overheads due to large volumes of trajectory data produced and to save users the burden of post-processing, we also develop a novel in situ tool for molecular species analysis. We analyze the performance of the resulting ReaxC-OMP package on two different architectures: (i) Mira, an IBM Blue Gene/Q system and (ii) Cori-II, a Cray XC-40 sytem with Knights Landing processors. For Pentaerythritol tetranitrate (PETN) systems of sizes ranging from 32 thousand to 16.6 million particles, we observe speedups in the range of 1.5–4.5×. We observe sustained performance improvements for up to 262,144 cores (1,048,576 processes) of Mira and a weak scaling efficiency of 91.5% in large simulations containing 16.6 million particles. The in situ molecular species analysis tool incurs only insignificant overheads across various system sizes and runs configurations.

Flow cytometric fingerprinting for microbial strain discrimination and physiological characterization.

The analysis of microbial populations is fundamental, not only for developing a deeper understanding of microbial communities but also for their engineering in biotechnological applications. Many methods have been developed to study their characteristics and over the last few decades, molecular analysis tools, such as DNA sequencing, have been used with considerable success to identify the composition of microbial populations. Recently, flow cytometric fingerprinting is emerging as a promising and powerful method to analyze bacterial populations. So far, these methods have primarily been used to observe shifts in the composition of microbial communities of natural samples. In this article, we apply a flow cytometric fingerprinting method to discriminate among 29 Lactobacillus strains. Our results indicate that it is possible to discriminate among 27 Lactobacillus strains by staining with SYBR green I and that the discriminatory power can be increased by combined SYBR green I and propidium iodide staining. Furthermore, we illustrate the impact of physiological changes on the fingerprinting method by demonstrating how flow cytometric fingerprinting is able to discriminate the different growth phases of a microbial culture. The sensitivity of the method is assessed by its ability to detect changes in the relative abundance of a mix of polystyrene beads down to 1.2%. When a mix of bacteria was used, the sensitivity was as between 1.2% and 5%. The presented data demonstrate that flow cytometric fingerprinting is a sensitive and reproducible technique with the potential to be applied as a method for the dereplication of bacterial isolates. © 2017 International Society for Advancement of Cytometry.

Proteometabolomic response of Deinococcus radiodurans exposed to UVC and vacuum conditions: Initial studies prior to the Tanpopo space mission.

The multiple extremes resistant bacterium Deinococcus radiodurans is able to withstand harsh conditions of simulated outer space environment. The Tanpopo orbital mission performs a long-term space exposure of D. radiodurans aiming to investigate the possibility of interplanetary transfer of life. The revealing of molecular machinery responsible for survivability of D. radiodurans in the outer space environment can improve our understanding of underlying stress response mechanisms. In this paper, we have evaluated the molecular response of D. radiodurans after the exposure to space-related conditions of UVC irradiation and vacuum. Notably, scanning electron microscopy investigations showed that neither morphology nor cellular integrity of irradiated cells was affected, while integrated proteomic and metabolomic analysis revealed numerous molecular alterations in metabolic and stress response pathways. Several molecular key mechanisms of D. radiodurans, including the tricarboxylic acid cycle, the DNA damage response systems, ROS scavenging systems and transcriptional regulators responded in order to cope with the stressful situation caused by UVC irradiation under vacuum conditions. These results reveal the effectiveness of the integrative proteometabolomic approach as a tool in molecular analysis of microbial stress response caused by space-related factors.

Quantitative Assessment of the Energetics of Dopamine Translocation by Human Dopamine Transporter.

Computational evaluation of the energetics of substrate binding, transport, and release events of neurotransmitter transporters at the molecular level is a challenge, as the structural transitions of these membrane proteins involve coupled global and local changes that span time scales of several orders of magnitude, from nanoseconds to seconds. Here, we provide a quantitative assessment of the energetics of dopamine (DA) translocation through the human DA transporter (hDAT), using a combination of molecular modeling, simulation, and analysis tools. DA-binding and -unbinding events, which generally involve local configurational changes, are evaluated using free-energy perturbation or adaptive biasing force methods. The global transitions between the outward-facing state and the inward-facing state, on the other hand, require a dual-boost accelerated molecular dynamics simulation. We present results on DA-binding/unbinding energetics under different conditions, as well as the conformational energy landscape of hDAT in both DA-bound and -unbound states. The study provides a tractable method of approach for quantitative evaluation of substrate-binding energetics and efficient estimation of conformational energy landscape, in general.