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.

Exploring crucial structural attributes of quinolinyl methoxyphenyl sulphonyl-based hydroxamate derivatives as ADAM17 inhibitors through classification-dependent molecular modelling approaches.

A Disintegrin and Metalloproteinase 17 (ADAM17), a Zn2+-dependent metalloenzyme of the adamalysin family of the metzincin superfamily, is associated with various pathophysiological conditions including rheumatoid arthritis and cancer. However, no specific inhibitors have been marketed yet for ADAM17-related disorders. In this study, 94 quinolinyl methoxyphenyl sulphonyl-based hydroxamates as ADAM17 inhibitors were subjected to classification-based molecular modelling and binding pattern analysis to identify the significant structural attributes contributing to ADAM17 inhibition. The statistically validated classification-based models identified the importance of the P1' substituents such as the quinolinyl methoxyphenyl sulphonyl group of these compounds for occupying the S1' - S3' pocket of the enzyme. The quinolinyl function of these compounds was found to explore stable binding of the P1' substituents at the S1' - S3' pocket whereas the importance of the sulphonyl and the orientation of the P1' moiety also revealed stable binding. Based on the outcomes of the current study, four novel compounds of different classes were designed as promising ADAM17 inhibitors. These findings regarding the crucial structural aspects and binding patterns of ADAM17 inhibitors will aid the design and discovery of novel and effective ADAM17 inhibitors for therapeutic advancements of related diseases.

Assessing structural insights into in-house arylsulfonyl L-(+) glutamine MMP-2 inhibitors as promising anticancer agents through structure-based computational modelling approaches.

MMP-2 is potentially contributing to several cancer progressions including leukaemias. Therefore, considering MMP-2 as a promising target, novel anticancer compounds may be designed. Here, 32 in-house arylsulfonyl L-(+) glutamines were subjected to various structure-based computational modelling approaches to recognize crucial structural attributes along with the spatial orientation for higher MMP-2 inhibition. Again, the docking-based 2D-QSAR study revealed that the Coulomb energy conferred by Tyr142 and total interaction energy conferred by Ala84 was crucial for MMP-2 inhibition. Importantly, the docking-dependent CoMFA and CoMSIA study revealed the importance of favourable steric, electrostatic, and hydrophobic substituents at the terminal phenyl ring. The MD simulation study revealed a lower fluctuation in the RMSD, RMSF, and Rg values indicating stable binding interactions of MMP-2 and these molecules. Moreover, the residual hydrogen bond and their interaction analysis disclosed crucial amino acid residues responsible for forming potential hydrogen bonding for higher MMP-2 inhibition. The results can effectively aid in the design and discovery of promising small-molecule drug-like MMP-2 inhibitors with greater anticancer potential in the future.

Exploration of structural alerts and fingerprints for novel anticancer therapeutics: a robust classification-QSAR dependent structural analysis of drug-like MMP-9 inhibitors.

Among various matrix metalloproteinases (MMPs), overexpression of MMP9 has been established as a key player in a variety of cancers. Therefore, MMP9 has emerged as a promising biomolecule that may be targeted to design potent inhibitors as novel anticancer therapeutics. In this study, a large database containing 1,123 drug-like MMP-9 inhibitors was considered for robust classification-dependent fragment-based QSAR study through SARpy, Bayesian classification, and recursive partitioning analyses and were validated by both internal and external validation techniques. In a nutshell, all these classification-dependent techniques revealed some common structural alerts and sub-structural fingerprints responsible for modulating MMP-9 inhibition. These observations are in agreement with the interactions obtained from the ligand-bound co-crystal structures of MMP-9 justifying the robustness of the current study. Finally, based on these crucial structural fragments, some new lead compounds were designed and further validated by the binding mode of interaction analysis. Therefore, these findings may be beneficial in designing novel and potential MMP-9 inhibitors in the future as a weapon to combat several cancers.

A comparative quantitative structural assessment of benzothiazine-derived HDAC8 inhibitors by predictive ligand-based drug designing approaches.

Histone deacetylase 8 (HDAC8) is a verified biomolecular target associated with diverse diseases including cancer. Though several HDAC inhibitors emerged effective against such diseases, no selective HDAC8 inhibitor is approved to date. Therefore, the development of potent HDAC8-selective inhibitors is inevitable to combat such diseases. Here, some benzothiazine-derived HDAC8 inhibitors were considered for a comparative QSAR analysis which may elucidate the prime structural components responsible for modulating their efficacy. Several outcomes from these diverse modelling techniques justified one another and thus validated each other. The ligand-based pharmacophore modelling study identified ring aromatic, positive ionizable, and hydrophobic features as essential structural attributes for HDAC8 inhibition. Besides, MLR, HQSAR and field-based 3D-QSAR studies signified the utility of the positive ionizable and hydrophobic features for potent HDAC8 inhibition. Again, the field-based 3D-QSAR study provided useful insight regarding the substitution in the fused phenyl ring. Moreover, the current observations also validated the previously reported molecular docking observations. Based on the outcomes, some new molecules were designed and predicted. Therefore, this comparative structural analysis of these HDAC8 inhibitors will surely assist in the development of potent HDAC8 inhibitors as promising anticancer therapeutics in the future.

A quantitative structural analysis of AR-42 derivatives as HDAC1 inhibitors for the identification of promising structural contributors.

Alteration and abnormal epigenetic mechanisms can lead to the aberration of normal biological functions and the occurrence of several diseases. The histone deacetylase (HDAC) family of enzymes is one of the prime regulators of epigenetic functions modifying the histone proteins, and thus, regulating epigenetics directly. HDAC1 is one of those HDACs which have important contributions to cellular epigenetics. The abnormality of HDAC is correlated to the occurrence, progression, and poor prognosis in several disease conditions namely neurodegenerative disorders, cancer cell proliferation, metastasis, chemotherapy resistance, and survival in various cancers. Therefore, the progress of potent and effective HDAC1 inhibitors is one of the prime approaches to combat such diseases. In this study, both regression and classification-based molecular modelling studies were conducted on some AR-42 derivatives as HDAC1 inhibitors to elucidate the crucial structural aspects that are responsible for regulating their biological responses. This study revealed that the molecular polarizability, van der Waals volume, the presence of aromatic rings as well as the higher number of hydrogen bond acceptors might affect prominently their inhibitory activity and might be responsible for proper fitting and interactions at the HDAC1 active site to pertain effective inhibition.

Search for Subsolar-Mass Binaries in the First Half of Advanced LIGO's and Advanced Virgo's Third Observing Run.

We report on a search for compact binary coalescences where at least one binary component has a mass between 0.2 M_{⊙} and 1.0 M_{⊙} in Advanced LIGO and Advanced Virgo data collected between 1 April 2019 1500 UTC and 1 October 2019 1500 UTC. We extend our previous analyses in two main ways: we include data from the Virgo detector and we allow for more unequal mass systems, with mass ratio q≥0.1. We do not report any gravitational-wave candidates. The most significant trigger has a false alarm rate of 0.14 yr^{-1}. This implies an upper limit on the merger rate of subsolar binaries in the range [220-24200] Gpc^{-3} yr^{-1}, depending on the chirp mass of the binary. We use this upper limit to derive astrophysical constraints on two phenomenological models that could produce subsolar-mass compact objects. One is an isotropic distribution of equal-mass primordial black holes. Using this model, we find that the fraction of dark matter in primordial black holes in the mass range 0.2 M_{⊙}

Applying comparative molecular modelling techniques on diverse hydroxamate-based HDAC2 inhibitors: an attempt to identify promising structural features for potent HDAC2 inhibition.

Histone deacetylase 2 (HDAC2) has been implicated in a variety of cardiovascular and neurodegenerative disorders as well as in cancers. Thus, HDAC2 has become an exclusive target for anticancer drug development. Therefore, the development of newer HDAC2 inhibitors in disease conditions is a prime goal to restrain such a scenario. Although a handful of HDAC inhibitors was accepted for the treatment of HDAC-related disease conditions, the non-selective nature of these entities is one of the major setbacks in the treatment of specific HDAC isoform-related pathophysiology. In this framework, the analyses of pre-existing molecules are essential to identify the important structural features that can fulfil the requirements for the cap and linker moieties to obtain potent and effective HDAC2 inhibition. Thus, in this study, the implementation of a combined comparative 2D and 3D molecular modelling techniques was done on a group of 92 diverse hydroxamate derivatives having a wide range of HDAC2 inhibitory potency. Besides other crucial features, this study upheld the importance of groups like triazole and benzyl moieties along with the molecular fields that are crucial for regulating HDAC2 inhibition. The outcomes of this study may be employed for the designing of HDAC2 inhibitors in future.

Prevalence and Factors Associated with Postpartum Depression among Mothers Visiting Immunization Clinic at Birendranagar Municipality, Surkhet, Nepal.

Background Postpartum depression (PPD) is a disabling but treatable mental disorder that represents one of the most common complications of childbearing which can exert a wide range of effect on social, physical and mental health conditions of the mother and baby. Objective To identify the prevalence and factors associated with postpartum depression among mothers visiting immunization clinic at Birendranagar Municipality, Surkhet in year 2020. Method This study was a cross-sectional study. A total of 347 postpartum mothers were interviewed for data collection. Validated Nepali version of Edinburg Postnatal Depression Scale (EPDS) was used to identify postpartum depression. These mothers were permanent resident of Birendranagar who had delivered their babies in municipal hospital. Analysis was done using SPSS version 21.0. Chi square test was applied to identify association of postpartum depression with major interest of variables namely parity of mother, sex of a baby and recent planned or unplanned pregnancy. Odds ratio (OR) was calculated with 95% Confidence Interval (CI). Result The prevalence of postpartum depression was found to be 32.9% (27.9%, 37.8%). Several factors which were significantly associated with postpartum depression were; sex of the baby, history of abortion and recent pregnancy planned or unplanned. Conclusion Nearly one-third of postpartum mothers had depression. Hence screening of mothers for depression is of prime importance throughout the continuum of care. Likewise, the factors identified for postpartum depression needs to be taken care of well in advance for healthy mother and a baby.

Whole Genome Sequence Analysis to Identify SARS-CoV-2 Variant in Nepal.

Background The spread of SARS-CoV-2 has become a global public health crisis. Nepal is facing the second wave of COVID-19 pandemic but, there is still a limited data on the genomic sequence of SARS-CoV-2 variants circulating in Nepal. Objective The objective of this study is to sequence the whole genome of SARS-CoV-2 in Nepal to detect possible mutation profiles and phylogenetic lineages of circulating SARSCoV-2 variants. Method In this study, swab samples tested positive for SARS-CoV-2 were investigated. After RNA extraction, the investigation was performed through real-time PCR followed by whole genome sequencing. The consensus genome sequences were, then, analyzed with appropriate bioinformatics tools. Result Sequence analysis of two SARS-CoV-2 genomes from patient without travel history (Patient A1 and A2) were found to be of lineage B.1.1. Similarly, among other four samples from subjects returning from the United Kingdom, genomes of two samples were of lineage B.1.36, and the other two were of lineage B.1.1.7 (Alpha Variant). The mutations in the consensus genomes contained the defining mutations of the respective lineages of SARS-CoV-2. Conclusion We confirmed two genomic sequences of variant of concern VOC-202012/01 in Nepal. Our study provides the concise genomic evidence for spread of different lineages of SARS-CoV-2 - B.1.1, B.1.36 and B.1.1.7 of SARS-CoV-2 in Nepal.

A robust classification-dependent multi-molecular modelling study on some biphenyl sulphonamide based MMP-8 inhibitors.

Matrix metalloproteinases (MMPs) are a group of zinc and calcium-dependent endopeptidases, which contribute to different physiological and biological activities via extracellular matrix (ECM) degradation. Matrix metalloproteinase-8 (MMP-8) belongs to type-II collagenases of the MMP family that has contribution in several physiological disorders such as cardiovascular diseases, joint, renal, digestive and respiratory disorders as well as in cancer. In clinical study, MMP-8 is found to be associated with periodontal disease condition. Therefore, MMP-8 specific inhibitors should be developed to target these disorders. The biphenyl sulphonamide (BPS) moiety is one of the crucial structural characteristics found in several MMP-8 inhibitors. Here, different classification-based molecular modelling methods were used to explore the structural features that lead to the activity variation of a series of MMP-8 inhibitors possessing a BPS moiety. Our current classification-based structural analysis of these BPS-derived MMP-8 inhibitors was able to identify the importance of several structural features such as the tetrahydroisoquinoline and N-Boc pyridyl groups, which have positive influences on MMP-8 inhibition. This study was also reflected the importance of the zinc-binding groups (ZBGs) like the hydroxamate and phosphonate for potent and sub-nanomolar range MMP-8 inhibition, which may benefit the development of highly potent MMP-8 inhibitors.

Robust classification-based molecular modelling of diverse chemical entities as potential SARS-CoV-2 3CLpro inhibitors: theoretical justification in light of experimental evidences.

COVID-19 is the most unanticipated incidence of 2020 affecting the human population worldwide. Currently, it is utmost important to produce novel small molecule anti-SARS-CoV-2 drugs urgently that can save human lives globally. Based on the earlier SARS-CoV and MERS-CoV infection along with the general characters of coronaviral replication, a number of drug molecules have been proposed. However, one of the major limitations is the lack of experimental observations with different drug molecules. In this article, 70 diverse chemicals having experimental SARS-CoV-2 3CLproinhibitory activity were accounted for robust classification-based QSAR analysis statistically validated with 4 different methodologies to recognize the crucial structural features responsible for imparting the activity. Results obtained from all these methodologies supported and validated each other. Important observations obtained from these analyses were also justified with the ligand-bound crystal structure of SARS-CoV-2 3CLpro enzyme. Our results suggest that molecules should contain a 2-oxopyrrolidine scaffold as well as a methylene (hydroxy) sulphonic acid warhead in proper orientation to achieve higher inhibitory potency against SARS-CoV-2 3CLpro. Outcomes of our study may be able to design and discover highly effective SARS-CoV-2 3CLpro inhibitors as potential anticoronaviral therapy to crusade against COVID-19.

Exploring the structural aspects of ureido-amino acid-based APN inhibitors: a validated comparative multi-QSAR modelling study.

The zinc-dependent enzyme aminopeptidase N (APN) is a member of the M1 metalloenzyme family. The multi-functionality of APN as a peptidase, a receptor and a signalling molecule has provided it the access to influence a number of disease conditions namely viral diseases, angiogenesis, cellular metastasis and invasion including different cancer conditions. Hence, the development of potent APN inhibitors is a possible route for the treatment of diseases related to the activity of APN. In this study, different QSAR approaches have been adopted to identify the structural features of a group of hydroxamate-based ureido-amino acid derivative APN inhibitors. This study was able to identify different constitutional aspects of these APN inhibitors which are important for their inhibitory potency. Additionally, some of these observations were also aligned with the observations of previously performed QSAR studies conducted on different APN inhibitors. Therefore, the results of this study may help to design potent and effective APN inhibitors in the future.

Discriminations of active from inactive HDAC8 inhibitors Part II: Bayesian classification study to find molecular fingerprints.

In continuation of our earlier work (Doi: 10.1080/07391102.2019.1661876), a statistically validated and robust Bayesian model was developed on a large diverse set of HDAC8 inhibitors. The training set comprised of 676 small molecules and 293 compounds were considered as test set molecules. The findings of this analysis will help to explore some major directions regarding the HDAC8 inhibitor designing approach. Acrylamide (G1-G3, G9), N-substituted 2-phenylimidazole (G4-G8, G9, G12-G13, G16-G19), benzimidazole (G10-G11), piperidine substituted pyrrole (G13-G14) groups, alkyl/aryl amide (G15) and aryloxy carboxamide (G20) fingerprints were found to play a crucial role in HDAC8 inhibitory activity whereas -CH-N=CH- (B1, B4-B6, B14) motif, benzamide (B2-B3, B9-B13, B16-B17) groups and heptazepine (B7-B8, B15, B18-B20) group were found to influence negatively the HDAC8 inhibitory activity. The importance of such fingerprints was further validated by the HDAC8 enzyme and related inhibitor interactions at the receptor level. These results are in close agreement with those of our previous work that validate each other. Moreover, this comparative learning may enrich future endeavours regarding the designing strategy of HDAC8 inhibitors.

Treatment of Ebola-related critical illness.

PURPOSE: To explore contemporary clincial case management of patients with Ebola virus disease. METHODS: A narrative review from a clinical perspective of clinical features, diagnostic tests, treatments and outcomes of patients with Ebola virus disease. RESULTS: Substantial advances have been made in the care of patients with Ebola virus disease (EVD), precipitated by the unprecedented extent of the 2014-2016 outbreak. There has been improved point-of-care diagnostics, improved characterization of the clinical course of EVD, improved patient-optimized standards of care, evaluation of effective anti-Ebola therapies, administration of effective vaccines, and development of innovative Ebola treatment units. A better understanding of the Ebola virus disease clinical syndrome has led to the appreciation of a central role for critical care clinicians-over 50% of patients have life-threatening complications, including hypotension, severe electrolyte imbalance, acute kidney injury, metabolic acidosis and respiratory failure. Accordingly, patients often require critical care interventions such as monitoring of vital signs, intravenous fluid resuscitation, intravenous vasoactive medications, frequent diagnostic laboratory testing, renal replacement therapy, oxygen and occasionally mechanical ventilation. CONCLUSION: With advanced training and adherence to infection prevention and control practices, clinical interventions, including critical care, are feasible and safe to perform in critically ill patients. With specific anti-Ebola medications, most patients can survive Ebola virus infection.

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.

QSAR modelling on a series of arylsulfonamide-based hydroxamates as potent MMP-2 inhibitors.

Matrix metalloproteinase-2 (MMP-2) is a lucrative therapeutic target as far as anticancer drug discovery is concerned. Overexpression of MMP-2 is found to facilitate tumour propagation through the involvement of vascular endothelial growth factor (VEGF). However, even after different techniques, finding a target-specific MMP-2 inhibitor with respectable pharmacodynamic properties is still a challenging task. Regression-dependent quantitative structure-activity relationship (QSAR) strategies might be among the possible drug design methods to explore the essential structural features that would be valuable to find a suitable MMP-2 inhibitor. In this paper, 72 molecules were explored using the PaDEL descriptors and stepwise multiple linear regression (S-MLR). The partial least squares (PLS) method was also used to create a viable statistical model with an acceptable metric related to these models. The final statistical models were formed with statistical parameters within acceptable range (r2 = 0.797, Q2 = 0.725 and r2pred = 0.643 for the MLR model, and r2 = 0.780, Q2 = 0.685 and r2pred = 0.666 for the PLS model). The models were analysed and compared with those already published on the same endpoint.

Clinical and echocardiographic predictors of embolism in infective endocarditis: systematic review and meta-analysis.

OBJECTIVES: Prediction of embolic events (EEs) in infective endocarditis (IE) could inform clinical decisions, such as surgical timing. We conducted a systematic review to more precisely define associations between risk factors and EEs. METHODS: We searched two bibliographic databases (1994-2018) for observational studies that reported EEs in IE patients and considered clinical, microbiological or echocardiographic risk factors. Studies that did not use Duke criteria or only investigated a subset of IE patients were excluded. Study quality was assessed using the Newcastle-Ottawa scale. A pooled risk ratio (RR) for each risk factor was estimated using random-effects models; statistical heterogeneity was estimated using I2. RESULTS: Of 3862 unique citations, 47 cohort studies (11 215 IE cases) were included; 54 risk factors were analysed in at least two studies, with nine studies reporting other individual factors. Most studies were of high methodological quality. Major predictors of EEs were intravenous drug use (RR 1.69, 95% CI 1.32-2.17; I2 = 46%), Staphylococcus aureus infection (RR 1.64, 95% CI 1.45-1.86, I2 = 32%), mitral valve vegetation (RR 1.24, 95% CI 1.11-1.37, I2 = 30%), and vegetation size >10 mm (RR 1.87, 95% CI 1.57-2.21, I2 = 48%). EE risk was also higher with human immunodeficiency virus, chronic liver disease, elevated C-reactive protein, Staphylococcus spp. infection, vegetation presence, and multiple, mobile or prosthetic mechanical valve vegetation, and lower with Streptococcus spp. infection. Most findings were unchanged in sensitivity analyses that removed studies with pulmonary EEs from the outcome. CONCLUSIONS: Given the serious consequences of embolism, surgical evaluation may be considered in patients with these risk factors.

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.

Multiple molecular modelling studies on some derivatives and analogues of glutamic acid as matrix metalloproteinase-2 inhibitors.

Matrix metalloproteinase-2 (MMP-2) is a potential target in anticancer drug discovery due to its association with angiogenesis, metastasis and tumour progression. In this study, 67 glutamic acid derivatives, synthesized and evaluated as MMP-2 inhibitors, were taken into account for multi-QSAR modelling study (regression-based 2D-QSAR, classification-based LDA-QSAR, Bayesian classification QSAR, HQSAR, 3D-QSAR CoMFA and CoMSIA as well as Open3DQSAR). All these QSAR studies were statistically validated individually. Regarding the 3D-QSAR analysis, the Open3DQSAR results were better than CoMFA and CoMSIA, although all these 3D-QSAR models supported each other. The importance of biphenylsulphonyl moiety over phenylacetyl/naphthylacetyl moieties was established due to its association with favourable steric and hydrophobic characters. HQSAR, LDA-QSAR and Bayesian classification QSAR studies also suggested that the biphenylsulphonamido group was better than the phenylacetylcarboxamido function. Additionally, glutamines were proven to be far better inhibitors than isoglutamines. Observations obtained from the current study were revalidated and supported by the earlier reported molecular modelling studies. Depending on these observations, newer glutamic acid-based compounds may be designed further in future for potent MMP-2 inhibitory activity.