New bronchodilators selected by molecular topology.

Molecular topology has been applied to find new lead compounds with bronchodilator activity. Among the selected compounds stands out 3-(1H-tetrazol-5yl)-9H-thioxanthene-9 -one-10,10-dioxide, anthrarobin, 9-oxo-9H-thioxantene-3-carboxylic-10,10-dioxide acid, acenocoumarol and griseofulvin, with a percentage of relaxation, at 0.1 mM, of 91, 92, 85, 69, and 74%, respectively. Theophylline shows a correspondent value of 77% (Emax = 100% at 1 mM).

Anti- Toxoplasma Activities of 24 Quinolones and Fluoroquinolones In Vitro: Prediction of Activity by Molecular Topology and Virtual Computational Techniques

ABSTRACT The apicoplast, a plastid-like organelle of Toxoplasma gondii , is thought to be a unique drug target for quinolones. In this study, we assessed the in vitro activity of quinolones against T. gondii and developed new quantitative structure-activity relationship models able to predict this activity. The anti- Toxoplasma activities of 24 quinolones were examined by means of linear discriminant analysis (LDA) using topological indices as structural descriptors. In parallel, in vitro 50% inhibitory concentrations (IC 50 s) were determined in tissue culture. A multilinear regression (MLR) analysis was then performed to establish a model capable of classifying quinolones by in vitro acti…

Applications of Bond-Based 3D-Chiral Quadratic Indices in QSAR Studies Related to Central Chirality Codification

The concept of bond-based quadratic indices is generalized to codify chemical structure information for chiral drugs, making use of a trigonometric 3D-chirality correction factor. In order to evaluate the effectiveness of this novel approach in drug design, we have modeled several well-known data sets. In particularly, Cramer's steroid data set has become a benchmark for the assessment of novel QSAR methods. This data set has been used by several researchers using 3D-QSAR approaches. Therefore, it is selected by us for the shake of comparability. In addition, to evaluate the effectiveness of this novel approach in drug design, we model the angiotensin-converting enzyme inhibitory activity o…

Alzheimer: A Decade of Drug Design. Why Molecular Topology can be an Extra Edge?

Background The last decade was characterized by a growing awareness about the severity of dementia in the field of age-related and no age-related diseases and about the importance to invest resources in the research of new, effective treatments. Among the dementias, Alzheimer's plays a substantial role because of its extremely high incidence and fatality. Several pharmacological strategies have been tried but still now, Alzheimer keeps being an untreatable disease. In literature, the number of QSAR related drug design attempts about new treatments for Alzheimer is huge, but only few results can be considered noteworthy. Providing a detailed analysis of the actual situation and reporting the…

Discovery of new antimalarial compounds by use of molecular connectivity techniques.

Abstract Molecular connectivity has been applied to the search for new compounds with antimalarial activity. Linear discriminant analysis and connectivity functions were used to select several potentially suitable drugs which were tested for antimalarial properties by use of an in-vitro micro test which estimates parasite growth by measurement of incorporation of [3H]hypoxanthine. Hexetidine stands out among the compounds selected. Activity assays were performed with Plasmodium falciparum passou and 3CD7 strains, for which the IC50 values (doses resulting in 50% inhibition) were 320 and 400 ng mL−1 respectively. These results are comparable with those obtained for quinine chlorhydrate (IC50…

Spectrophotometric Determination of Hydralazine with 2-Hydroxy-1-naphthaldehyde in Pharmaceuticals

Abstract A new extraction-spectrophotometric method for the determination of hydralazine, based on its reaction with 2-hydroxy-1-naphthaldehyde at 25 °C, is described. The calibration curve was linear between 0.4 and 6 mg/mL of hydralazine. The molar absorbtivity of the product at 408 nm is 40 900 L · mol − 1 · cm − 1 . The method described was applied to the analysis of hydralazine in pharmaceutical preparations containing reserpine, hydrochlorothiazide, bendrofluorthiazine, propranolol, and other substances. The agreement with the U.S.P. XXI method was satisfactory for tablets and injections, but not for pellets.

Molecular Search of New Active Drugs AgainstToxoplasma Gondii

Molecular connectivity has been applied to the search of new compounds with activity against the protozoan Toxoplasma gondii, using a stepwise linear discriminant analysis (SLDA) which is able to classify a compound according its activity either as active or as inactive. Among the selected compounds, andrographolide and dibenzotiophene sulfone stand out, both with IC50 values lower than 1 microgram/ml, which are comparable to these of drugs such as sulfamethoxazole, pyrimethamine and trimethoprim, with IC50 values equal to 1.1, 0.04 and 2.31 micrograms/ml, respectively. These results confirm the usefulness of our topological approach for the selection and design of new-lead drugs active aga…

Application of molecular topology to the prediction of potency and selection of novel insecticides active against malaria vectors

Abstract A study on the basis of molecular topology has been carried out to predict the potency of insecticides active against malaria vectors (Culex) as well as to select novel compounds potentially active on those vectors. The results, performed over two sets of compounds, namely hormone-like and ‘common’ or wide-spectra insecticides, demonstrate that the adequate combination of topological charge indices and simple topological-geometric indices, yield very good results in both, the prediction of potency and the selection of new insecticides. Further development should be addressed in the future; however, the achievement described here is extremely encouraging.

Predictability and prediction of lowest observed adverse effect levels in a structurally heterogeneous set of chemicals

A database of chronic lowest observed adverse effect levels (LOAELs) for 234 compounds, previously compiled from different sources (Toxicology Letters79, 131-143 (1995)), was modelled using graph theoretical descriptors. This study reveals that data are not homogeneous. Only those data originating from the U.S. Environmental Protection Agency (EPA) reports could be well modelled by multilinear regression (MLR) and linear discriminant analysis (LDA). In contrast, data available from the specific procedures of the National Toxicology Program (NTP) database introduced noise and did not render good models either alone, or in combination with the EPA data.

Getting new bronchodilator compounds from molecular topology.

Abstract Molecular topology has been used to select new lead bronchodilator compounds. The main advantage of this method, as compared to others frequently used, is that it does not require a previous explicit knowledge of the mechanism of action (MOA) of the compounds analyzed. A large database (12,000 chemicals) has been examined in this study to find less than 5% compounds with bronchodilator activity. After removing those compounds already described as bronchodilators, we present here the results for 20 among these compounds, some of them showing other pharmacological activities. Some of the compounds selected in this study showed higher relaxation and higher potency than theophylline, w…

Retrained Classification of Tyrosinase Inhibitors and “In Silico” Potency Estimation by Using Atom-Type Linear Indices

In this paper, the authors present an effort to increase the applicability domain (AD) by means of retraining models using a database of 701 great dissimilar molecules presenting anti-tyrosinase activity and 728 drugs with other uses. Atom-based linear indices and best subset linear discriminant analysis (LDA) were used to develop individual classification models. Eighteen individual classification-based QSAR models for the tyrosinase inhibitory activity were obtained with global accuracy varying from 88.15-91.60% in the training set and values of Matthews correlation coefficients (C) varying from 0.76-0.82. The external validation set shows globally classifications above 85.99% and 0.72 fo…

What place does molecular topology have in today’s drug discovery?

Introduction: Most methods in molecular and drug design are currently based on physicochemical descriptors. However, molecular topology, which relies on topological descriptors, has also shown value for molecular design even if it does not take into account the physical or chemical properties of ligands and receptors, including the ligand-receptor interaction itself. Areas covered: Herein, the authors provide new insights into the importance of molecular topology according to some of the latest discoveries in physics and chemistry. Furthermore, the authors report on the most significant achievements in drug design using molecular topology over the last 5 years and give their expert perspect…

Biodegradability Prediction of Fragrant Molecules by Molecular Topology

Biodegradability is a key property in the development of safer fragrances. In this work we present a green methodology for its preliminary assessment. The structure of various fragrant molecules is characterized by computing a large set of topological indices. Those relevant to biodegradability are selected by means of a hybrid stepwise selection method to build a linear classifier. This model is compared with a more complex artificial neural network trained with the indices previously found. After validation, the models show promise for time and cost reduction in the development of new, safer fragrances. The methodology presented could easily be adapted to many quasi-big data problems in R…

Prediction of chromatographic properties of organophosphorus insecticides by molecular connectivity

A study is reported of the relationship between theR F values for a group of organophosphorus insecticides obtained by thin layer chromatography and a series of topological descriptors. By using multivariate regression, the corresponding connectivity functions were obtained, which had been selected on the basis of their respective statistical parameters: multiple correlation coefficient (r), standard error of estimate (s), F-Snedecor values and statistical significance (Student’s t). Regression analysis of the connectivity functions can predict the elution behaviour of any structurally similar derivative of this group of compounds with different stationary and mobile phases. Stability studi…

Getting discriminant functions of antibacterial activity from physicochemical and topological parameters.

Linear discriminant analysis has been demonstrated to be a very useful tool in the selection and design of new drugs. Up to now we have used it through the search of a topological pattern of activity. In this work our goal is to calculate a complete set of physicochemical parameters using semiempirical (quantum chemical) calculations as well as topological indices (TIs) and try to find out any discriminant function for antibacterial activity through the combined use of both types of descriptors. The physicochemical parameters, such as heat of formation, HOMO, LUMO, dipole moment, polarizability, hyperpolarizability, PM3 generated IR vibrational frequencies, etc., were calculated using PM3 H…

Bond-extended stochastic and nonstochastic bilinear indices. I. QSPR/QSAR applications to the description of properties/activities of small-medium size organic compounds

Bond-extended stochastic and nonstochastic bilinear indices are introduced in this article as novel bond-level molecular descriptors (MDs). These novel totals (whole-molecule) MDs are based on bilinear maps (forms) similar to use defined in linear algebra. The proposed nonstochastic indices try to match molecular structure provided by the molecular topology by using the kth Edge(Bond)-Adjacency Matrix (Ek, designed here as a nonstochastic E matrix). The stochastic parameters are computed by using the kth stochastic edge-adjacency matrix, ESk, as matrix operators of bilinear transformations. This new edge (bond)-adjacency relationship can be obtained directly from Ek and can be considered li…

Aplicación de la topología molecular a la predicción de la actividad antimalárica de análogos de la 4-anilinoquinolina

La malaria es una enfermedad parasitaria causada por protozoos del género Plasmodium y transmitida por vectores del género Anopheles . En 2019 esta enfermedad se cobró la vida de más de 400.000 personas, de las cuales un 94 % se concentraban en la región de África. Uno de los principales problemas en el control de la malaria es la aparición de resistencias frente a los diferentes fármacos que existen, es por ello que es necesario el desarrollo de alternativas antimaláricas eficaces. En este estudio se ha aplicado la topología molecular a una serie de compuestos análogos de la 4-anilinoquinolina con actividad inhibitoria de la proliferación de 3 cepas de Plasmodium falciparum, una sensibl…

Antiprotozoan lead discovery by aligning dry and wet screening: Prediction, synthesis, and biological assay of novel quinoxalinones

Protozoan parasites have been one of the most significant public health problems for centuries and several human infections caused by them have massive global impact. Most of the current drugs used to treat these illnesses have been used for decades and have many limitations such as the emergence of drug resistance, severe side-effects, low-to-medium drug efficacy, administration routes, cost, etc. These drugs have been largely neglected as models for drug development because they are majorly used in countries with limited resources and as a consequence with scarce marketing possibilities. Nowadays, there is a pressing need to identify and develop new drug-based antiprotozoan therapies. In …

Topological Approach to Analgesia

Topological Approach to Drug Design

In this paper we demonstrated that by an adequate combination of different topological indices it is possible to select and design new active compounds in different therapeutical scopes, with a very high efficiency level. Particularly successful in the search of new "lead drugs", the results show the surprising ability of the topological methods to describe molecular structures.

Topological virtual screening: a way to find new anticonvulsant drugs from chemical diversity.

A topological virtual screening (tvs) test is presented, which is capable of identifying new drug leaders with anticonvulsant activity. Molecular structures of both anticonvulsant-active and non active compounds, extracted from the Merck Index database, were represented using topological indexes. By means of the application of a linear discriminant analysis to both sets of structures, a topological anticonvulsant model (tam) was obtained, which defines a connectivity function. On the basis of this model, 41 new structures with anticonvulsant activity have been identified by a topological virtual screening.

New agents active against Mycobacterium avium complex selected by molecular topology: a virtual screening method

Objectives: In order to select new drugs and to predict their in vitro activity against Mycobacterium avium complex (MAC), new quantitative structure-activity relationship (QSAR) models were developed. Methods: The activities against MAC of 29 structurally heterogeneous drugs were examined by means of linear discriminant analysis (LDA) and multilinear regression analysis (MLRA) by using topological indices (TI) as structural descriptors. In vitro antimycobacterial activities were determined by a broth microdilution method with 7H9 medium. Results: The topological model obtained successfully classifies over 80% of compounds as active or inactive; consequently, it was applied in the search fo…

New antifungals selected by molecular topology.

Abstract Molecular topology has been applied to find the new lead antimycotic compounds. Among the selected compounds stands out 3,3′-(4,4′ - Biphenylene)bis(2,5-diphenyl-2H-tetrazolium chloride), Benztropine mesylate and Dicyclopentamethylenethiuram disulphide, with minimum inhibitory concentrations between 1.6 and 2 μg / mL.

ChemInform Abstract: Antimicrobial Activity Characterization in a Heterogeneous Group of Compounds.

In this work we carry out a study of pattern recognition to detect the microbiological activity in a group of heterogeneous compounds. The structural descriptors utilized are the topological connectivity indexes. The methods followed are stepwise linear discriminant analysis (linear analysis) and artificial neural network (nonlinear analysis). Although both methods are appropriate to differentiate between active and inactive compounds, the artificial neural network is, in this case, more adequate, since it shows in a test set a prediction success of 98%, versus 92% obtained with linear discriminant analysis.

New Analgesics Designed by Molecular Topology

Molecular topology has been applied to the design of new analgesic drugs, utilizing linear discriminant analysis and connectivity functions using different topological descriptors. Of a total of 26 compounds selected, 17 showed analgesic activity. The following stood out particularly, showing analgesic values greater than 75% regarding ASA (acetylsalicylic acid), the reference drug: 2-(1-propenyl)phenol, 2′4′ dimethylacetophenone, p-chlorobenzohydrazide, 1-(p-chlorophenyl) propanol and 4-benzoyl-3-methyl-1-phenyl-2-pyrazolin-5-one. The usefulness of the design method has been demonstrated in the search of new chemical structures having analgesic effects, some of which could become “lead dru…

Molecular connectivity to find β-blockers with low toxicity

Abstract Molecular connectivity has been used to find new β-blocker drugs using linear discriminant analysis and connectivity functions with different topological descriptors. Among the selected compounds stands out the probucol and the β-carotene. Both of them interact with β adrenoceptors.

Molecular Topology QSAR Strategy for Crop Protection: New Natural Fungicides with Chitin Inhibitory Activity

Nowadays, crop protection is a major concern and how to proceed is a delicate point of contention. New products must be safe and ecofriendly in accordance with the actual legislation. In this context, we present a quantitative structure-activity relationship strategy based on molecular topology as a tool for generating natural products as potential fungicides following a mechanism of action based on the synthesis of chitin inhibition (chitinase inhibition). Two discriminant equations using statistical linear discriminant analysis were used to identify three potential candidates (1-methylxanthine, hematommic acid, and antheraxanthin). The equations showed accuracy and specificity levels abov…

Search of Chemical Scaffolds for Novel Antituberculosis Agents

3 A method to identify chemical scaffolds potentially active against Mycobacterium tuberculosis is presented. The molecular features of a set of structurally heterogeneous antituberculosis drugs were coded by means of structural invariants. Three tech- niques were used to obtain equations able to model the antituberculosis activity: linear discriminant analysis, multilinear re- gression, and shrinkage estimation-ridge regression. The model obtained was statistically validated through leave-n-out test, and an external set and was applied to a database for the search of new active agents. The selected compounds were assayed in vitro, and among those identified as active stand reserpine, N,N,N…

Modeling anti-allergic natural compounds by molecular topology.

Molecular topology has been applied to the search of QSAR models able to identify the anti-allergic activity of a wide group of heterogeneous compounds. Through the linear discriminant analysis and artificial neural networks, correct classification percentages above 85% for both the training set and the test set have been obtained. After carrying out a virtual screening with a natural product library, about thirty compounds with theoretical anti-allergic activity have been selected. Among them, hesperidin, naringin, salinomycin, sorbitol, curcumol, myricitrin, diosmin and kinetin stand out. Some of these compounds have already been referenced as having anti-allergic activity.

Novel Cancer Chemotherapy Hits by Molecular Topology: Dual Akt and Beta-Catenin Inhibitors

Background and purposeColorectal and prostate cancers are two of the most common types and cause of a high rate of deaths worldwide. Therefore, any strategy to stop or at least slacken the development and progression of malignant cells is an important therapeutic choice. The aim of the present work is the identification of novel cancer chemotherapy agents. Nowadays, many different drug discovery approaches are available, but this paper focuses on Molecular Topology, which has already demonstrated its extraordinary efficacy in this field, particularly in the identification of new hit and lead compounds against cancer. This methodology uses the graph theoretical formalism to numerically chara…

Prediction of acute toxicity of organophosphorus pesticides using topological indices

Topological indices were used in the prediction of the acute toxicity (intraperitoneal and oral LD(50)) of organophosphorus pesticides on rats. Models with six variables for the prediction of LD(50)-i.p. (r = 0.849, Q(2) = 0.613) and eight variables for LD(50)-oral (r = 0.906, Q(2) = 0.701) were selected. External group and cross-validation by use of leave-n-out tests were also performed in order to assess the stability and the prediction performance of the selected topological models.

Molecular topology as a novel approach for drug discovery

Molecular topology (MT) has emerged in recent years as a powerful approach for the in silico generation of new drugs. One key part of MT is that, in the process of drug design/discovery, there is no need for an explicit knowledge of a drug's mechanism of action unlike other drug discovery methods.In this review, the authors introduce the topic by explaining briefly the most common methodology used today in drug design/discovery and address the most important concepts of MT and the methodology followed (QSAR equations, LDA, etc.). Furthermore, the significant results achieved, from this approach, are outlined and discussed.The results outlined herein can be explained by considering that MT r…

Application of molecular topology to the prediction of antifungal activity for a set of dication-substituted carbazoles, furans and benzimidazoles

In this paper, the endpoint is the application of molecular topology to the search of QSAR relations into a group of dicationsubstituted carbazoles, furans and benzimidazoles, all showing antifungal activity against C. albicans. Mathematical and statistical methods such as linear regression and discriminant analysis, are used to goal. The obtained results clearly show a high efficiency of the formalism on the prediction and classification of antifungal activity. 83% of the compounds showing MIC , 10 mg/ml (active group) are correctly classified, whilst 100% overall accuracy is achieved for those compounds showing MIC . 100 mg/ml (inactive group). q 2003 Elsevier Science B.V. All rights rese…

Application of Molecular Topology to the Prediction of the Reaction Yield and Anticancer Activity of Imidazole and Guanidine Derivatives

In this study molecular topology based QSAR has been applied to predict the reaction yield and anticancer activity of 18 imidazole and guanidine derivatives. Four properties were evaluated, namely reaction yield, anti prostatic-cancer activity, anti breast-cancer activity and anti lung-cancer activity. The four models have been validated by both internal and cross validation, and also by randomness tests. The results obtained are in full agreement with the experimental results and confirm the precision, accuracy and robustness of the method followed. After carrying out a virtual screening upon such models, new imidazole and guanidine derivatives with potential anticancer activity are propos…

Application of Molecular Topology for the Prediction of Reaction Yields and Anti-Inflammatory Activity of Heterocyclic Amidine Derivatives

Topological-mathematical models based on multiple linear regression analyses have been built to predict the reaction yields and the anti-inflammatory activity of a set of heterocylic amidine derivatives, synthesized under environmental friendly conditions, using microwave irradiation. Two models with three variables each were selected. The models were validated by cross-validation and randomization tests. The final outcome demonstrates a good agreement between the predicted and experimental results, confirming the robustness of the method. These models also enabled the screening of virtual libraries for new amidine derivatives predicted to show higher values of reaction yields and anti-infl…

Discovery of novel anti-inflammatory drug-like compounds by aligning in silico and in vivo screening: The nitroindazolinone chemotype

In this report, we propose the combination of computational methods and in vivo primary screening in zebrafish larvae and confirmatory in mice models as a novel strategy to accelerate anti-inflammatory drug discovery. Initially, a database of 1213 organic chemicals with great structural variability - 587 of them anti-inflammatory agents plus 626 compounds with other clinical uses - was divided into training and test groups. Atom-based quadratic indices - a TOMOCOMD-CARDD molecular descriptors family - and linear discriminant analysis (LDA) were used to develop a total of 13 models to describe the anti-inflammatory activity. The best model (Eq. (13)) shows an accuracy of 87.70% in the traini…

Prediction of Indices of Refraction and Glass Transition Temperatures of Linear Polymers by Using Graph Theoretical Indices

Graph theoretical indices were exclusively used in the prediction of indices of refraction, n, and glass transition temperatures, Tg, into a group of addition polymers. Models with 10 variables were selected for the prediction of n (r = 0.981, SEE = 0.0147) and Tg/M (r = 0.946, SEE = 0.439). The average errors in the predictions were 0.69% and 12.7% for n and Tg, respectively. The descriptors involved in these models were calculated from the structures of the monomers.

Application of molecular topology to the prediction of the antimalarial activity of a group of uracil-based acyclic and deoxyuridine compounds.

A topological-mathematical model has been arranged to search for new derivatives of deoxyuridine and related compounds acting as antimalarials against Plasmodium falciparum. By using linear discriminant and multilinear regression analysis a model with two functions was capable to predict adequately the IC(50) for each compound of the training and test series. After carrying out a virtual screening based upon such a model, new structures potentially active against P. falciparum are proposed.

Molecular topology: A new strategy for antimicrobial resistance control

The control of antimicrobial resistance (AMR) seems to have come to an impasse. The use and abuse of antibacterial drugs has had major consequences on the genetic mutability of both pathogenic and nonpathogenic microorganisms, leading to the development of new highly resistant strains. Because of the complexity of this situation, an in silico strategy based on QSAR molecular topology was devised to identify synthetic molecules as antimicrobial agents not susceptible to one or several mechanisms of resistance such as: biofilms formation (BF), ionophore (IA) activity, epimerase (EI) activity or SOS system (RecA inhibition). After selecting a group of 19 compounds, five of them showed signific…

Application of Molecular Topology to the Prediction of Water Quality Indices of Alkylphenol Pollutants

In this paper, topological-mathematical models based on multilineal regression analysis have been built as a model of the degradability of 26 alkylphenols through the Chemical Oxygen Demand (COD) and Biochemical Oxigen Demand (BOD5). Two models with three-variable were selected (r2= 0.8793 and q2=0.8075 for log(1/COD) and r2= 0.8928 and q2=0.8327 for log(1/BOD5). The models were validated by cross-validation, internal validation and randomization tests. The results, which stand in good accordance with the obtained results, confirm the robustness of the method.

Prediction of properties of chiral compounds by molecular topology

Abstract A common assumption in chemistry is that chiral behavior is associated with 3-D geometry. However, chiral information is related to symmetry, which allows the topological handling of chiral atoms by weighted graphs and the calculation of new descriptors that give a weight to the corresponding entry in the main diagonal of the topological matrix. In this study, it is demonstrated that, operating in this way, chiral topological indices are obtained that can differentiate the pharmacological activity between pairs of enantiomers. The 50% inhibitory concentration (IC50) values of the D2 dopamine receptor and the σ receptor for a group of 3-hydroxy phenyl piperidines are specifically pr…

Search of a topological pattern to evaluate toxicity of heterogeneous compounds.

Abstract Molecular connectivity has been applied to the search of mathematical models able to predict the carcinogenic and teratogenic activity of a wide group of structurally heterogeneous compounds. Through the linear discriminant analysis and the diagrams of distribution of pharmacological activity, the classification criteria that minimizes the percentage of error are established. The easiness and speed of the calculation of the descriptors used in this work make the models developed useful in data bases containing a huge number of compounds.

The Prediction of Human Intestinal Absorption Based on the Molecular Structure

Human Intestinal Absorption (HIA) has been modeled many times by using classification models. However, regression models are scarce. Here, Artificial Neural Networks (ANNs) are implemented for this purpose. A dataset of structurally diverse chemicals with their respective experimental HIA were used to design robust, true predictive and widespread applicable ANN models. An input variables pool was made up of structural invariants calculated by using either Dragon or our software Desmol 1. The selection of best variables was performed following three steps using the entire dataset of molecules. Firstly, variables poorly correlated with the experimental data were eliminated. Secondly, input va…

General topological patterns of known drugs.

Abstract Discriminating “drug-like” from “non-drug-like” compounds is a relatively emerging topic within the drug research. The basic assumption is that it is possible to obtain relevant information from structural features common to the known drugs, in order to discard a huge number of candidate chemical structures with low probability of becoming drugs. A graph-theoretical contribution to this subject is reported in this paper, by making exclusive use of linear relationships. The results suggest that it is possible to achieve a pattern of general pharmacological activity based on molecular topology. Conclusions are tentative pending verification of the results with larger compound librari…

Modeling Drug-Induced Anorexia by Molecular Topology

Molecular topology (MT) has demonstrated to be a very good technique for describing molecular structures and to predict physical, chemical, and biological properties of compounds. In this paper, a topological-mathematical model based on MT has been developed for identifying drug compounds showing anorexia as a side effect. An external validation (test set) has been carried out, yielding over an 80% correct classification in the active and inactive compounds. These results reinforce the role of MT as a potential useful tool for predicting drug side effects.

Antimicrobial Activity Characterization in a Heterogeneous Group of Compounds

In this work we carry out a study of pattern recognition to detect the microbiological activity in a group of heterogeneous compounds. The structural descriptors utilized are the topological connectivity indexes. The methods followed are stepwise linear discriminant analysis (linear analysis) and artificial neural network (nonlinear analysis). Although both methods are appropriate to differentiate between active and inactive compounds, the artificial neural network is, in this case, more adequate, since it shows in a test set a prediction success of 98%, versus 92% obtained with linear discriminant analysis.

Aplicación de la topología molecular a la predicción y optimización de la actividad repelente de mosquitos de derivados de la N-acylpiperidina

Se ha construido un modelo topológico-matemático con el fin de seleccionar nuevos repelentes de mosquito derivados de la N-acylpiperidina. Para ello se ha empleado la técnica estadística del análisis de regresión multilineal. Los compuestos empleados en la elaboración del modelo han sido caracterizados por medio de índices topológicos. Finalmente, se ha obtenido un modelo de 5 variables capaz de predecir los tiempos de protección de diversos repelentes de mosquitos derivados de la N-acylpiperidina (R2=0.8457 y Q2= 0.7486). El modelo ha sido validado mediante validación cruzada interna de tipo leave-one-out y un test de aleatoriedad. Los resultados han confirmado la capacidad del modelo para…

Estimation of ADME Properties in Drug Discovery: Predicting Caco-2 Cell Permeability Using Atom-Based Stochastic and Non-stochastic Linear Indices

The in vitro determination of the permeability through cultured Caco-2 cells is the most often-used in vitro model for drug absorption. In this report, we use the largest data set of measured P(Caco-2), consisting of 157 structurally diverse compounds. Linear discriminant analysis (LDA) was used to obtain quantitative models that discriminate higher absorption compounds from those with moderate-poorer absorption. The best LDA model has an accuracy of 90.58% and 84.21% for training and test set. The percentage of good correlation, in the virtual screening of 241 drugs with the reported values of the percentage of human intestinal absorption (HIA), was greater than 81%. In addition, multiple …

Latest advances in molecular topology applications for drug discovery

Molecular topology (MT) has emerged in recent years as a powerful approach for the in silico generation of new drugs. In the last decade, its application has become more and more popular among the leading research groups in the field of quantitative structure-activity relationships (QSAR) and drug design. This has, in turn, contributed to the rapid development of new techniques and applications of MT in QSAR studies, as well as the introduction of new topological indices.This review collates the main innovative techniques in the field of MT and provides a description of the novel topological indices recently introduced, through an exhaustive recompilation of the most significant works carri…

Molecular topology - dissimilar similarities.

The present paper depicts the role of molecular topology in the study of similarity–dissimilarity between molecular structures. It proves that molecular topology represents a very useful tool for getting common patterns of pharmacological activity and hence an efficient approach for the search of novel lead drugs.

Structural invariants for the prediction of relative toxicities of polychloro dibenzo-p-dioxins and dibenzofurans

Multivariate models are reported that can predict the relative toxicity of compounds with severe environmental impact, namely polychloro dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs). Multiple linear regression analysis (MLR) and partial least square projections of latent variables (PLS) show the usefulness of graph-theoretical descriptors, mainly topological charge indices (TCIs), in these series. The general trends of the group are correctly reproduced and better results are presented than have previously been published. In general, the more toxic compounds exhibit more symmetric molecular structures.

Some Relationships between Molecular Energy-Topology and Symmetry

Molecular Topology (M.T.) has demonstrated its efficiency in the prediction of many experimental parameters. The application of the topological indices to the prediction of pharmacological properties, and, above all, to its inverse problem, the drug design, is particularly interesting [1,2]. Several attempts to explain the reasons of such efficiency have been carried out [3,4]. So far, we are not close to a definitive answer.

QSAR methods for the discovery of new inflammatory bowel disease drugs

Inflammatory bowel disease (IBD) represents an important class of chronic gastrointestinal tract disease. And although there are already several useful treatments to reduce and control the symptoms, there is still no cure. One drug discovery technique used is the computer-aided (in silico) discovery approach which has largely demonstrated efficacy. Computational techniques, when used in combination with traditional drug discovery methodology, greatly increase the chance of drug discovery in a sustainable and economical fashion.This review aims to provide the most recent and important advances of in silico IBD drug discovery. While this review is mainly focused on QSAR methods, especially th…

Improving the local vertex invariants in alkane graphs through a standard molecular orbital approach

Abstract In this work, novel topological indices are introduced by the application of algorithms based on molecular orbital theory. Actually, the novel indices are obtained by computing new values of the local vertex invariants (LOVIs) in alkane graphs. The most significant result is the dramatic increase in the predictive capability achieved with the topological charge indices weighted according the new LOVIs’ values in the prediction of four key properties in the set of octane isomers, namely heat of atomization, molar refraction, heat of vaporization and boiling point.

Application de la topologie moléculaire à la prédiction de la viscosité liquide des composés organiques

Nous avons applique la topologie moleculaire a la recherche d'un modele mathematique capable de predire la viscosite liquide d'un large groupe de composes organiques contenant C, H, O, N, S et des halogenes. Les descripteurs topologiques utilises pour cette etude des relations quantitatives structure-propiete, R.Q.S.P., sont les indices de connectivite de Kier et Hall -jusqu'a l'ordre quatre- ainsi que les indices atomiques electrotopologiques. La qualite de l'equation de regression multilineaire obtenue (aussi dite « fonction de connectivite») a ete evaluee par une etude de validation croisee. Tous les composes excepte le 1,1,2-trichlorotrifluorethane s'ajustent au modele propose.

On the contribution of molecular topology to drug design and discovery.

Abstract The role of molecular topology (MT) in the design and selection of new drugs is discussed. After an overview of the different in silico molecular design current technologies, the QSAR analysis is dealt in detail with particular emphasis in the use of topological indices as molecular descriptors. The results of the application of MT in drug design and discovery are described and finally a possible explanation is given about some of the key reasons explaining it's the extraordinary performance.

Prediction of quinolone activity against Mycobacterium avium by molecular topology and virtual computational screening.

ABSTRACT We conducted a quantitative structure-activity relationship study using a database of 158 quinolones previously tested against Mycobacterium avium-M. intracellulare complex in order to develop a model capable of predicting the activity of new quinolones against the M. avium-M. intracellulare complex in vitro. Topological indices were used as structural descriptors and were related to anti- M. avium-M. intracellulare complex activity by using the linear discriminant analysis (LDA) statistical technique. The discriminant equation thus obtained correctly classified 137 of the 158 quinolones, including 37 of a test group of 44 randomly chosen compounds. This model was then applied to 2…

Application of molecular topology for the prediction of the reaction times and yields under solvent-free conditions

Ball milling and conventional magnetic stirring can be used to support different laboratory techniques with a highly efficient mixing of reagents under solvent-free conditions. By using multilinear regression and linear discriminant analysis, topological-mathematical models have been built to predict the yield and the reaction time for organocatalytic reactions, Suzuki reactions and reactions of synthesis of heterocyclic compounds. The results from the in silico predictions confirm the usefulness of the approach followed.

QSAR multi-target in drug discovery: a review.

The main purpose of the present review is to summarize the most significant works up to date in the field of multi-target QSAR (mt-QSAR), in order to emphasize the importance that this technique has acquired over the last decade. Unlike traditional QSAR techniques, mt-QSAR permits to calculate the probability of activity of a given compound against different biological or pharmacological targets. In simple terms, a single equation for multiple outputs. To emphasize more the importance of the mt-QSAR in the field of drug discovery, we also present a novel mt-QSAR model, made on purpose by our research group, for the prediction of the susceptibility of Gram + and Gram - anaerobic bacteria.

In silicoAntibacterial Activity Modeling Based on the TOMOCOMD-CARDD Approach

In the recent times, the race to cope with the increasing multidrug resistance of pathogenic bacteria has lost much of its momentum and health professionals are grasping for solutions to deal with the unprecedented resistance levels. As a result, there is an urgent need for a concerted effort towards the development of new antimicrobial drugs to stay ahead in the fight against the ever adapting bacteria. In the present report, antibacterial classification functions (models) based on the topological molecular computational design-computer aided >rational> drug design (TOMOCOMD-CARDD) atom-based non-stochastic and stochastic bilinear indices are presented. These models were built using the li…

Modeling Natural Anti-Inflammatory Compounds by Molecular Topology

One of the main pharmacological problems today in the treatment of chronic inflammation diseases consists of the fact that anti-inflammatory drugs usually exhibit side effects. The natural products offer a great hope in the identification of bioactive lead compounds and their development into drugs for treating inflammatory diseases. Computer-aided drug design has proved to be a very useful tool for discovering new drugs and, specifically, Molecular Topology has become a good technique for such a goal. A topological-mathematical model, obtained by linear discriminant analysis, has been developed for the search of new anti-inflammatory natural compounds. An external validation obtained with …

New hypoglycaemic agents selected by molecular topology.

Abstract New compounds showing hypoglycaemic activity have been designed through a computer aided method based on quantitative structure–activity relationship (QSAR) and molecular connectivity. After calculation of topological indices for a set of 89 compounds including active and inactive with regards to hypoglycaemic action, linear discriminant analysis was performed so that a useful model to predict such an activity was achieved. Later on, the discriminant model was applied on a huge database so that fourteen compounds were selected as potential new hypoglycaemics. From them, just five were finally selected for experimental test on expected hypoglycaemic activity. Among the selected comp…

Advances in the molecular modeling and quantitative structure–activity relationship-based design for antihistamines

Nowadays the use of antihistamines (AH) is increasing steadily. These drugs are able to act on a variety of pathological conditions of the organism. A number of computer-aided (in silico) approaches have been developed to discover and develop novel AH drugs. Among these methods stand the ones based on drug-receptor docking, thermodynamics, as well as the quantitative structure-activity relationships (QSAR).This review collates the most recent advances in the use of computer approaches for the search and characterization of novel AH drugs. Within the QSAR methods, particular attention will be paid to those based on molecular topology (MT) because of their demonstrated efficacy in discovering…

ChemInform Abstract: Getting Discriminant Functions of Antibacterial Activity from Physicochemical and Topological Parameters.

Linear discriminant analysis has been demonstrated to be a very useful tool in the selection and design of new drugs. Up to now we have used it through the search of a topological pattern of activity. In this work our goal is to calculate a complete set of physicochemical parameters using semiempirical (quantum chemical) calculations as well as topological indices (TIs) and try to find out any discriminant function for antibacterial activity through the combined use of both types of descriptors. The physicochemical parameters, such as heat of formation, HOMO, LUMO, dipole moment, polarizability, hyperpolarizability, PM3 generated IR vibrational frequencies, etc., were calculated using PM3 H…

Bond-based 3D-chiral linear indices: Theory and QSAR applications to central chirality codification

The recently introduced non-stochastic and stochastic bond-based linear indices are been generalized to codify chemical structure information for chiral drugs, making use of a trigonometric 3D-chirality correction factor. These improved modified descriptors are applied to several well-known data sets to validate each one of them. Particularly, Cramer's steroid data set has become a benchmark for the assessment of novel quantitative structure activity relationship methods. This data set has been used by several researchers using 3D-QSAR approaches such as Comparative Molecular Field Analysis, Molecular Quantum Similarity Measures, Comparative Molecular Moment Analysis, E-state, Mapping Prope…

Introduction to molecular topology: basic concepts and application to drug design.

In this review it is dealt the use of molecular topology (MT) in the selection and design of new drugs. After an introduction of the actual methods used for drug design, the basic concepts of MT are defined, including examples of calculation of topological indices, which are numerical descriptors of molecular structures. The goal is making this calculation familiar to the potential students and allowing a straightforward comprehension of the topic. Finally, the achievements obtained in this field are detailed, so that the reader can figure out the great interest of this approach.

Molecular topology: a useful tool for the search of new antibacterials.

Molecular topology has been applied to find new lead antibacterial compounds. Among the selected compounds, hesperidin, neohesperidin and Mordant Brown 24 stand out, with minimum inhibitory concentrations 90, MIC90<0.3 mg / mL.

New active drugs against liver stages of Plasmodium predicted by molecular topology.

ABSTRACT We conducted a quantitative structure-activity relationship (QSAR) study based on a database of 127 compounds previously tested against the liver stage of Plasmodium yoelii in order to develop a model capable of predicting the in vitro antimalarial activities of new compounds. Topological indices were used as structural descriptors, and their relation to antimalarial activity was determined by using linear discriminant analysis. A topological model consisting of two discriminant functions was created. The first function discriminated between active and inactive compounds, and the second identified the most active among the active compounds. The model was then applied sequentially t…

DesMol2, an Effective Tool for the Construction of Molecular Libraries and Its Application to QSAR Using Molecular Topology

A web application, DesMol2, which offers two main functionalities, is presented: the construction of molecular libraries and the calculation of topological indices. These functionalities are explained through a practical example of research of active molecules to the formylpeptide receptor (FPR), a receptor associated with chronic inflammation in systemic amyloidosis and Alzheimer&rsquo

Use of molecular topology for the prediction of physico-chemical, pharmacokinetic and toxicological properties of a group of antihistaminic drugs

We used molecular connectivity to search mathematical models for predicting physico-chemical (e.g. the partition coefficient, P), pharmacokinetic (e.g. the time of maximum plasma level, and toxicological properties (lethal dose, LD) for a group of antihistaminic drugs. The results obtained clearly reveal the high efficiency of molecular topology for the prediction of these properties. Randomization and cross-validation by use of leave-one-out tests were also performed in order to assess the stability and the prediction ability of the connectivity functions selected.

New cytostatic agents obtained by molecular topology

Abstract Four new cytostatic compounds have been obtained by computer aided selection based on Molecular Connectivity, a topological approach to molecular structural study. Three of them, namely tetracycline, doxycycline and piromidic acid are well known antibiotic agents, and the fourth, carminic acid, is an innocuous colorant. Although no previous report of activity was found, on the used cell lines, for any of the selected compounds, carminic acid may be considered a new lead one since no structure-related cytostatic molecules have been reported in the literature. These results are interesting for two reasons: First, new potential low-toxicity anticancer drugs show to be a possible thera…

Applying pattern recognition methods plus quantum and physico-chemical molecular descriptors to analyze the anabolic activity of structurally diverse steroids.

The great cost associated with the development of new anabolic-androgenic steroid (AASs) makes necessary the development of computational methods that shorten the drug discovery pipeline. Toward this end, quantum, and physicochemical molecular descriptors, plus linear discriminant analysis (LDA) were used to analyze the anabolic/androgenic activity of structurally diverse steroids and to discover novel AASs, as well as also to give a structural interpretation of their anabolic-androgenic ratio (AAR). The obtained models are able to correctly classify 91.67% (86.27%) of the AASs in the training (test) sets, respectively. The results of predictions on the 10% full-out cross-validation test al…

Pharmacological distribution diagrams: a tool for de novo drug design.

Abstract Discriminant analysis applied to SAR studies using topological descriptors allows us to plot frequency distribution diagrams: a function of the number of drugs within an interval of values of discriminant function vs. these values. We make use of these representations, pharmacological distribution diagrams (PDDs), in structurally heterogeneous groups where generally they adopt skewed Gaussian shapes or present several maxima. The maxima afford intervals of discrimianant function in which exists a good expectancy to find new active drugs. A set of β-blockers with contrasted activity has been selected to test the ability of PDDs as a visualizing technique, for the identification of n…

In silico Antibacterial Activity Modeling Based on the TOMOCOMD-CARDD Approach

In the recent times, the race to cope with the increasing multidrug resistance of pathogenic bacteria has lost much of its momentum and health professionals are grasping for solutions to deal with the unprecedented resistance levels. As a result, there is an urgent need for a concerted effort towards the development of new antimicrobial drugs to stay ahead in the fight against the ever adapting bacteria. In the present report, antibacterial classification functions (models) based on the topological molecular computational design-computer aided ‘‘rational’’ drug design (TOMOCOMD-CARDD) atom-based non-stochastic and stochastic bilinear indices are presented. These models were built using the …