Exploring different classification-dependent QSAR modelling strategies for HDAC3 inhibitors in search of meaningful structural contributors.

Histone deacetylase 3 (HDAC3), a Zn2+-dependent class I HDACs, contributes to numerous disorders such as neurodegenerative disorders, diabetes, cardiovascular disease, kidney disease and several types of cancers. Therefore, the development of novel and selective HDAC3 inhibitors might be promising to combat such diseases. Here, different classification-based molecular modelling studies such as Bayesian classification, recursive partitioning (RP), SARpy and linear discriminant analysis (LDA) were conducted on a set of HDAC3 inhibitors to pinpoint essential structural requirements contributing to HDAC3 inhibition followed by molecular docking study and molecular dynamics (MD) simulation analyses. The current study revealed the importance of hydroxamate function for Zn2+ chelation as well as hydrogen bonding interaction with Tyr298 residue. The importance of hydroxamate function for higher HDAC3 inhibition was noticed in the case of Bayesian classification, recursive partitioning and SARpy models. Also, the importance of substituted thiazole ring was revealed, whereas the presence of linear alkyl groups with carboxylic acid function, any type of ester function, benzodiazepine moiety and methoxy group in the molecular structure can be detrimental to HDAC3 inhibition. Therefore, this study can aid in the design and discovery of effective novel HDAC3 inhibitors in the future.

Critical Appraisal of Paediatric Embryonal Cancers Treated with Image-guided Intensity-modulated Proton Therapy.

AIM: To carry out a comprehensive critical appraisal of image-guided intensity-modulated proton therapy practice for craniospinal irradiation (CSI). MATERIALS AND METHODS: An image-guided intensity-modulated proton therapy database of 45 consecutive paediatric patients with central nervous system embryonal malignancies treated between January 2019 and April 2022 were critically appraised for demography, diagnosis, treatment planning strategy and treatment delivery accuracy. RESULTS: Most patients (median age: 7.5 years; male:female ratio: 34:11) had medulloblastoma (56%), followed by recurrent ependymoma (19%), pinealoblastoma (5%), germ cell (5%) and others (15%). The dose to the planning target volume-craniospinal (PTV-CS; length 39.06-79.59 cm) varied from 21 to 35 GyRBE, whereas the combined median dose to craniospinal and boost was 54 GyRBE. In all patients, the 95% isodose line covered the cribriform plate completely and optic nerves mostly, with a median V95% of 100% and 82.96%, keeping Dmax to the lens <3.9 GyRBE. In skeletally immature patients (88.38%), the anterior vertebral body was completely covered in 18.18% and underdosed in 70.15% of the cases, resulting in a median Dmean of 10.11 GyRBE to the oesophagus. Lateral spine coverage was maintained on the edges of the vertebral body in 52.2%, whereas it extended beyond in 48.8%. The median V98% for clinical target volumes and V95% for PTVs of the brain, spine and craniospinal were >97%, with excellent conformity (0.89) and homogeneity (0.07) indices for PTV-CS. All neurological organs at risk received a median Dmax ranging from 36 to 44 GyRBE from the combined CSI and boost regimens. Analysis of patient-specific quality assurance results revealed that 545 (97.67%) planar dosage verification had gamma (3% at 3 mm) values >95%. The online patient set-up verification showed translational and rotational deviation within 2 mm and 0.5° in 88-94% and 97% of the cases. Systematic and random error were within 0.90 mm and 1.71 mm in translation and 0.1° and 0.2° in rotation. CONCLUSION: A change in practice pattern was observed. The findings from our comprehensive critical appraisal add to the growing library of CSI practice and may serve as a reference for inter-institutional comparison.

Insight into the structural requirements of gelatinases (MMP-2 and MMP-9) inhibitors by multiple validated molecular modelling approaches: Part II.

Inhibition of the matrix metalloproteinases (MMPs) is effective against metastasis of secondary tumours. Previous MMP inhibitors have failed in clinical trials due to their off-target toxicity in solid tumours. Thus, newer MMP inhibitors now have paramount importance. Here, different molecular modelling techniques were applied on a dataset of 110 gelatinase (MMP-2 and MMP-9) inhibitors. The objectives of the present study were to identify structural fingerprints for gelatinase inhibition and also to develop statistically validated QSAR models for the screening and prediction of different derivatives as MMP-2 (gelatinase A) and MMP-9 (gelatinase B) inhibitors. The Bayesian classification study provided the ROC values for the training set of 0.837 and 0.815 for MMP-2 and MMP-9, respectively. The linear model also produced the leave-one-out cross-validated Q2 of 0.805 (eq. 1, MMP-2) and 0.724 (eq. 2, MMP-9), an r2 of 0.845 (eq. 1, MMP-2) and 0.782 (eq. 2, MMP-9), an r2Pred of 0.806 (eq. 1, MMP-2) and 0.732 (eq. 2, MMP-9). Similarly, non-linear learning models were also statistically significant and reliable. Overall, this study may help in the rational design of newer compounds with higher gelatinase inhibition to fight against both primary and secondary cancers in future.

First molecular modelling report on tri-substituted pyrazolines as phosphodiesterase 5 (PDE5) inhibitors through classical and machine learning based multi-QSAR analysis.

Phosphodiesterase 5 (PDE5) falls under a broad category of metallohydrolase enzymes responsible for the catalysis of the phosphodiesterase bond, and thus it can terminate the action of cyclic guanosine monophosphate (cGMP). Overexpression of this enzyme leads to development of a number of pathological conditions. Thus, targeting the enzyme to develop inhibitors could be useful for the treatment of erectile dysfunction as well as pulmonary hypertension. In the current study, several molecular modelling techniques were utilized including Bayesian classification, single tree and forest tree recursive partitioning, and genetic function approximation to identify crucial structural fingerprints important for optimization of tri-substituted pyrazoline derivatives as PDE5 inhibitors. Later, various machine learning models were also developed that could be utilized to predict and screen PDE5 inhibitors in the future.

Autosomal Clonal Monoallelic Expression: Natural or Artifactual?

The prevalence of mitotically heritable clonal random monoallelic expression of autosomal genes (aRME) remains controversial. Specifically, presence of clonal aRME is well supported in vitro but remains elusive in vivo. Here, we provide critical insights into this matter and discuss whether prevalent clonal aRME is natural or artifactual.

Identification of structural fingerprints for ABCG2 inhibition by using Monte Carlo optimization, Bayesian classification, and structural and physicochemical interpretation (SPCI) analysis.

The human breast cancer resistance protein (BCRP), one of the members of the large ATP binding cassette (ABC) transporter superfamily, is crucial for resistance against chemotherapeutic agents. Currently, it has been emerged as one of the best biological targets for the designing of small molecule drugs capable of eliminating multidrug resistance in breast cancer. In order to gain insights into the relationship between the molecular structure of compounds and the ABCG2 inhibition, a multi-QSAR approach using different methods was performed on a dataset of 294 ABCG2 inhibitors with diverse scaffolds. The best models obtained by different chemometric methods have the following statistical characteristics: Monte Carlo Optimization-based QSAR (sensitivity = 0.905, specificity = 0.6255, accuracy = 0.756, and MCC = 0.545), Bayesian classification model (sensitivity = 0.735, specificity = 0.775, and concordance = 0.757); structural and physicochemical interpretation analysis-random forest method (balance accuracy = 0.750, sensitivity = 0.810, and specificity = 0.700). Additionally, structural fingerprints modulating the ABCG2 inhibitory properties were identified from the best models of each method and also validated with each other. The current modelling study is an attempt to get a deep insight into the different important structural fingerprints modulating ABCG2 inhibition.

Insight into structural features of phenyltetrazole derivatives as ABCG2 inhibitors for the treatment of multidrug resistance in cancer.

ABCG2 is the principal ABC transporter involved in the multidrug resistance of breast cancer. Looking at the current demand in the development of ABCG2 inhibitors for the treatment of multidrug-resistant cancer, we have explored structural requirements of phenyltetrazole derivatives for ABCG2 inhibition by combining classical QSAR, Bayesian classification modelling and molecular docking studies. For classical QSAR, structural descriptors were calculated from the free software tool PaDEL-descriptor. Stepwise multiple linear regression (SMLR) was used for model generation. A statistically significant model was generated and validated with different parameters (For training set: r = 0.825; Q2 = 0.570 and for test set: r = 0.894, r2pred = 0.783). The predicted model was found to satisfy the Golbraikh and Trospha criteria for model acceptability. Bayesian classification modelling was also performed (ROC scores were 0.722 and 0.767 for the training and test sets, respectively). Finally, the binding interactions of phenyltetrazole type inhibitor with the ABCG2 receptor were mapped with the help of molecular docking study. The result of the docking analysis is aligned with the classical QSAR and Bayesian classification studies. The combined modelling study will guide the medicinal chemists to act faster in the drug discovery of ABCG2 inhibitors for the management of resistant breast cancer.

Structural exploration of hydroxyethylamines as HIV-1 protease inhibitors: new features identified.

The current study deals with chemometric modelling strategies (Naïve Bayes classification, hologram-based quantitative structure-activity relationship (HQSAR), comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA)) to explore the important features of hydroxylamine derivatives for exerting potent human immunodeficiency virus-1 (HIV-1) protease inhibition. Depending on the statistically validated reliable and robust quantitative structure-activity relationship (QSAR) models, important and crucial structural features have been identified that may be responsible for enhancing the activity profile of these hydroxylamine compounds. Arylsulfonamide function along with methoxy or fluoro substitution is important for enhancing activity. Bulky steric substitution at the sulfonamide nitrogen disfavours activity whereas smaller hydrophobic substitution at the same position is found to be favourable. Apart from the crucial oxazolidinone moiety, pyrrolidine, cyclic urea and methyl ester functions are also responsible for increasing the HIV-1 protease inhibitory profile. Observations derived from these modelling studies may be utilized further in designing promising HIV-1 protease inhibitors of this class.

Hydroxyethylamine derivatives as HIV-1 protease inhibitors: a predictive QSAR modelling study based on Monte Carlo optimization.

Application of HIV-1 protease inhibitors (as an anti-HIV regimen) may serve as an attractive strategy for anti-HIV drug development. Several investigations suggest that there is a crucial need to develop a novel protease inhibitor with higher potency and reduced toxicity. Monte Carlo optimized QSAR study was performed on 200 hydroxyethylamine derivatives with antiprotease activity. Twenty-one QSAR models with good statistical qualities were developed from three different splits with various combinations of SMILES and GRAPH based descriptors. The best models from different splits were selected on the basis of statistically validated characteristics of the test set and have the following statistical parameters: r2 = 0.806, Q2 = 0.788 (split 1); r2 = 0.842, Q2 = 0.826 (split 2); r2 = 0.774, Q2 = 0.755 (split 3). The structural attributes obtained from the best models were analysed to understand the structural requirements of the selected series for HIV-1 protease inhibitory activity. On the basis of obtained structural attributes, 11 new compounds were designed, out of which five compounds were found to have better activity than the best active compound in the series.

Insight into the structural requirements of pyrimidine-based phosphodiesterase 10A (PDE10A) inhibitors by multiple validated 3D QSAR approaches.

Schizophrenia is a complex disorder of thinking and behaviour (0.3-0.7% of the population is affected). The over-expression of phosphodiesterase 10A (PDE10A) enzyme may be a potential target for schizophrenia and Huntington's disease. Because 3D QSAR analysis is one of the most frequently used modelling techniques, in the present study, five different 3D QSAR tools, namely CoMFA, CoMSIA, kNN-MFA, Open3DQSAR and topomer CoMFA methods, were used on a dataset of pyrimidine-based PDE10A inhibitors. All developed models were validated internally and externally. The non-commercial Open3DQSAR produced the best statistical results amongst 3D QSAR tools. The structural interpretations obtained from different methods were thoroughly analysed and were justified on the basis of information obtained from the crystal structure. Information from one method was mostly validated by the results of other methods and vice versa. In the current work, the use of multiple tools in the same analysis revealed more complete information about the structural requirements of these compounds. On the basis of the observations of the 3D QSAR studies, 12 new compounds were designed for better PDE10A inhibitory activity. The current investigation may help in further designing new PDE10A inhibitors with promising activity.

Fluorescence tomography of targets in a turbid medium using non-negative matrix factorization.

A near-infrared optical tomography approach for detection, three-dimensional localization, and cross-section imaging of fluorescent targets in a turbid medium is introduced. The approach uses multisource probing of targets, multidetector acquisition of diffusely transmitted fluorescence signal, and a non-negative matrix factorization based blind source separation scheme to obtain three-dimensional location of the targets. A Fourier transform back-projection algorithm provides an estimate of target cross section. The efficacy of the approach is demonstrated in an experiment involving two laterally separated small fluorescent targets embedded in a human breast tissue-simulating sample of thickness 60 times the transport mean free path. The approach could locate the targets within ∼1 mm of their known positions, and provide estimates of their cross sections. The high spatial resolution, fast reconstruction speed, noise tolerance, and ability to detect small targets are indicative of the potential of the approach for detecting and locating fluorescence contrast-enhanced breast tumors in early growth stages, when they are more amenable to treatment.

Near-infrared center-of-intensity time gated imaging for detection of a target in a highly scattering turbid medium.

A near-infrared optical imaging approach for locating a target embedded in a turbid medium is introduced. The target localization is based on an analysis of the spatial variation of the transmitted-light intensity distribution for illumination at different positions on the sample boundary. The approach is used to detect, locate and generate images of absorbing targets embedded inside model scattering media of thickness approximately 50 times the transport mean free path of the medium, as well as, of ex vivo biological tissue specimens.

Time reversal optical tomography: locating targets in a highly scattering turbid medium.

A time reversal optical tomography (TROT) method for near-infrared (NIR) diffuse optical imaging of targets embedded in a highly scattering turbid medium is presented. TROT combines the basic symmetry of time reversal invariance and subspace-based signal processing for retrieval of target location. The efficacy of TROT is tested using simulated data and data obtained from NIR imaging experiments on absorptive and scattering targets embedded in Intralipid-20% suspension in water, as turbid medium. The results demonstrate the potential of TROT for detecting and locating small targets in a turbid medium, such as, breast tumors in early stages of growth.

Analytical cumulant solution of the vector radiative transfer equation investigates backscattering of circularly polarized light from turbid media.

The backscattering of circularly polarized light pulses from an infinite uniform scattering medium is studied as a function of helicity of the incident light and size of scatterers in the medium. The approach considers a polarized short pulse of light incident on the scattering medium, and uses an analytical cumulant solution of the vector radiative transfer equation with the phase matrix obtained from the Mie theory to calculate the temporal profile of scattered polarized photons for any position and any angle of detection. The general expression for the scattered photon distribution function is an expansion in spatial cumulants up to an arbitrary high order. Truncating the expansion at the second-order cumulant, a Gaussian analytical approximate expression for the temporal profile of scattered polarized photons is obtained, whose average center position and half width are always exact. The components of scattered light copolarized and cross polarized with that of the incident light can be calculated and used for determining the degree of polarization of the scattered light. The results show that circularly polarized light of the same helicity dominates the backscattered signal when scatterer size is larger than the wavelength of light. For the scatterers smaller than the wavelength, the light of opposite helicity makes the dominant contribution to the backscattered signal. The theoretical estimates are in good agreement with our experimental results.

Lasers in cancer detection and diagnosis research: enabling characteristics with illustrative examples.

The salient properties of laser light and the way light interacts with biological tissues and molecular constituents of tissues offer possibilities for detection and diagnosis of cancer. In particular, the wavelength selectivity of tunable lasers, narrow bandwidth around the selected wavelength, and spectral brightness enable probing of key molecular constituents of tissues, and endow laser-based techniques with much desired diagnostic potential. This article presents an overview of some recent developments in optical imaging and optical biopsy of different types of cancers, and illustrates the diagnostic role of the color of light.

Optical imaging of turbid media using independent component analysis: theory and simulation.

A new imaging approach for 3-D localization and characterization of objects in a turbid medium using independent component analysis (ICA) from information theory is developed and demonstrated using simulated data. This approach uses a multisource and multidetector signal acquisition scheme. ICA of the perturbations in the spatial intensity distribution measured on the medium boundary sorts out the embedded objects. The locations and optical characteristics of the embedded objects are obtained from a Green's function analysis based on any appropriate model for light propagation in the background medium. This approach is shown to locate and characterize absorptive and scattering inhomogeneities within highly scattering medium to a high degree of accuracy. In particular, we show this approach can discriminate between absorptive and scattering inhomogeneities, and can locate and characterize complex inhomogeneities, which are both absorptive and scattering. The influence of noise and uncertainty in background absorption or scattering on the performance of this approach is investigated.

Spectral and temporal near-infrared imaging of ex vivo cancerous and normal human breast tissues.

Cancerous and normal ex vivo human breast tissues were investigated using spectroscopic and time-sliced two-dimensional (2-D) transillumination imaging methods in order to demonstrate the importance and potential of spectral and temporal measurements in breast cancer detection and diagnosis. The experimental arrangement for time-sliced optical imaging used 120 fs, 1 kHz repetition-rate, 800 nm light pulses from a Ti:sapphire laser system for sample illumination, and a 80 ps resolution ultrafast gated intensified camera system for recording 2-D time-sliced images. The spectroscopic imaging arrangement used 1225-1300 nm tunable output of a Cr: forsterite laser for sample illumination, a Fourier space gate to discriminate against multiple-scattered light, and a near-infrared area camera to record 2-D images. Images recorded with earlier temporal slices of transmitted light highlighted tumors, while those recorded with later slices accentuated normal tissues. When light was tuned closer to the 1203 nm absorption resonance of adipose tissues, a marked enhancement in contrast between the images of adipose and fibrous tissues was observed. A similar wavelength-dependent difference between normal and cancerous tissues was observed. These results correlate well with pathology and nuclear magnetic resonance based analyses of the samples.

Three-dimensional localization and optical imaging of objects in turbid media with independent component analysis.

A new approach for optical imaging and localization of objects in turbid media that makes use of the independent component analysis (ICA) from information theory is demonstrated. Experimental arrangement realizes a multisource illumination of a turbid medium with embedded objects and a multidetector acquisition of transmitted light on the medium boundary. The resulting spatial diversity and multiple angular observations provide robust data for three-dimensional localization and characterization of absorbing and scattering inhomogeneities embedded in a turbid medium. ICA of the perturbations in the spatial intensity distribution on the medium boundary sorts out the embedded objects, and their locations are obtained from Green's function analysis based on any appropriate light propagation model. Imaging experiments were carried out on two highly scattering samples of thickness approximately 50 times the transport mean-free path of the respective medium. One turbid medium had two embedded absorptive objects, and the other had four scattering objects. An independent component separation of the signal, in conjunction with diffusive photon migration theory, was used to locate the embedded inhomogeneities. In both cases, improved lateral and axial localizations of the objects over the result obtained by use of common photon migration reconstruction algorithms were achieved. The approach is applicable to different medium geometries, can be used with any suitable photon propagation model, and is amenable to near-real-time imaging applications.

Time-resolved ring structure of circularly polarized beams backscattered from forward scattering media.

The backscattering of circularly polarized light at normal incidence to a half-space of scattering particles is studied using the Electric Field Monte Carlo (EMC) method. The spatial distribution of the backscattered light intensity is examined for both the time-resolved and continuous wave cases for large particles with anisotropy factor, g, in the range 0.8 to 0.97. For the time-resolved case, the backscattered light with the same helicity as that of the incident beam (co-polarized) is found to form a ring centered on the point of incidence. The ring expands and simultaneously grows weak as time increases. The intensity of backscattered light with helicity opposite to that of the incident beam (cross-polarized) is found to exhibit a ring behavior for g >/= 0.85, with significant backscattering at the point of incidence. For the continuous-wave case no such ring pattern is observed in backscattered light for either helicity. The present EMC study suggests that the ring behavior can only be observed in the time domain, in contrast to previous studies of light backscattered from forward scattering media based on the scalar time-independent Fokker-Planck approximation to the radiative transfer equation. The time-dependent ring structure of backscattered light may have potential use in subsurface imaging applications.

Optical tomographic image reconstruction from ultrafast time-sliced transmission measurements.

Optical imaging and localization of objects inside a highly scattering medium, such as a tumor in the breast, is a challenging problem with many practical applications. Conventional imaging methods generally provide only two-dimensional (2-D) images of limited spatial resolution with little diagnostic ability. Here we present an inversion algorithm that uses time-resolved transillumination measurements in the form of a sequence of picosecond-duration intensity patterns of transmitted ultrashort light pulses to reconstruct three-dimensional (3-D) images of an absorbing object located inside a slab of a highly scattering medium. The experimental arrangement used a 3-mm-diameter collimated beam of 800-nm, 150-fs, 1-kHz repetition rate light pulses from a Ti:sapphire laser and amplifier system to illuminate one side of the slab sample. An ultrafast gated intensified camera system that provides a minimum FWHM gate width of 80 ps recorded the 2-D intensity patterns of the light transmitted through the opposite side of the slab. The gate position was varied in steps of 100 ps over a 5-ns range to obtain a sequence of 2-D transmitted light intensity patterns of both less-scattered and multiple-scattered light for image reconstruction. The inversion algorithm is based on the diffusion approximation of the radiative transfer theory for photon transport in a turbid medium. It uses a Green s function perturbative approach under the Rytov approximation and combines a 2-D matrix inversion with a one-dimensional Fourier-transform inversion to achieve speedy 3-D image reconstruction. In addition to the lateral position, the method provides information about the axial position of the object as well, whereas the 2-D reconstruction methods yield only lateral position.