Approaches to Three‐Dimensional Quantitative Structure‐Activity Relationships

Greco, Giovanni; Novellino, Ettore; Martin, Yvonne C.

doi:10.1002/9780470125885.ch4

Cited by 29 publications

(7 citation statements)

References 175 publications

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“…As a result, it is common practice to approximate protein electrostatic potentials as a sum of the electrostatic potentials of the constituent molecular fragments (e.g., amino acid residues), neglecting the mutual polarization effects. Computations based on popular MM force fields [61][62][63][64][65][66] as well as studies of protein docking 42,48 or activity relationships 94,95 are based on such an approximation, even though breakdown of this assumption is the rule rather than the exception whenever there are charged or polar fragments (e.g., amino acid residues) in the system. It would, therefore, prove a significant advance to extend such a methodology to compute distributions of ESP atomic charges where polarization effects are explicitly considered.…”

Section: Qm/mm Methodologymentioning

confidence: 99%

A Self-Consistent Space-Domain Decomposition Method for QM/MM Computations of Protein Electrostatic Potentials

Gascón

Leung

Batista

et al. 2005

J. Chem. Theory Comput.

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This paper introduces a self-consistent computational protocol for modeling protein electrostatic potentials according to static point-charge model distributions. The protocol involves a simple space-domain decomposition scheme where individual molecular domains are modeled as Quantum-Mechanical (QM) layers embedded in the otherwise classical Molecular-Mechanics (MM) protein environment. ElectroStatic-Potential (ESP) atomic charges of the constituent molecular domains are computed, to account for mutual polarization effects, and iterated until obtaining a self-consistent point-charge model of the protein electrostatic potential. The novel protocol achieves quantitative agreement with full QM calculations in the description of electrostatic potentials of small polypeptides where polarization effects are significant, showing a remarkable improvement relative to the corresponding electrostatic potentials obtained with popular MM force fields. The capabilities of the method are demonstrated in several applications, including calculations of the electrostatic potential in the potassium channel protein and the description of protein-protein electrostatic interactions.

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Section: Qm/mm Methodologymentioning

confidence: 99%

A Self-Consistent Space-Domain Decomposition Method for QM/MM Computations of Protein Electrostatic Potentials

Gascón

Leung

Batista

et al. 2005

J. Chem. Theory Comput.

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“…As a matter of fact, the general limit of the CoMFA approach in predicting potencies and/or affinities of the most and least active compounds is well-known. 18,19 All of the other new derivatives were reasonably well predicted.…”

Section: Resultsmentioning

confidence: 80%

“…In particular, concerning R - 1 , this was likely due to its biological activity (pIC 50 = 8.64), which was somewhat higher than the average activities of the 3D QSAR training set. As a matter of fact, the general limit of the CoMFA approach in predicting potencies and/or affinities of the most and least active compounds is well-known. , All of the other new derivatives were reasonably well predicted. In particular, the S enantiomers of 2 and 3 were predicted with errors as small as −0.10 and 0.07, respectively.…”

Section: Resultsmentioning

confidence: 99%

Enantioselective Nonsteroidal Aromatase Inhibitors Identified through a Multidisciplinary Medicinal Chemistry Approach

et al. 2005

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To identify enantioselective nonsteroidal aromatase inhibitors, a multidisciplinary medicinal chemistry approach was pursued. First, our earlier CoMFA model [Bioorg. Med. Chem. 1998,6, 377-388] was extended taking purposely into account previously discovered enantioselective aromatase inhibitors. The 3D QSAR model was then exploited to design chiral ligands, whose configurational assignment was obtained, after HPLC separation, by means of a combination of circular dichroism measurements and time dependent density functional calculations. Finally, the new enantiomeric inhibitors were separately tested to ascertain both their potency against the cytochrome P450 aromatase (CYP19; EC 1.14.14.1), and their selectivity relative to another enzyme of the P450 family. A satisfactory agreement between experimental and predicted data allowed us to assert that a properly built "enantioselective CoMFA model" might constitute a useful tool for addressing enantioselective ligands design.

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“…The identification, study, and use of quantitative structure−activity relationship (QSAR) approaches are important stages involved in the development of rational approaches in drug design. , In 1969, Hansch demonstrated the possibility of establishing mathematical functions which correlate chemical structures with biological activities of compounds. Since then, many scientists have been working on related topicsnamely, obtaining finer descriptors − (pieces of chemical information employed as predictive and modeling variables), the development of new chemometric techniques and validation strategies, , and so forthaimed at providing pharmaceuticals with powerful tools which guide the design of new drugs. Thus, a large number of QSAR models dealing with many chemical families have been developed and summarized in the bibliography.…”

Section: Introductionmentioning

confidence: 99%

Refinement and Use of the Approximate Similarity in QSAR Models for Benzodiazepine Receptor Ligands

Cuadrado

Ruiz

Gómez‐Nieto

2006

J. Chem. Inf. Model.

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Several considerations for refining the approximate similarity measurements have been introduced in this paper: the use of topological invariants for the calculation of similarity indexes and the development of new similarity correction processes. The quality of the new similarity measurements obtained with the proposed methods has permitted the development of fast, cheap, and simple quantitative structure-activity relationship models for the prediction of biological activities of nonbenzodiazepine gamma-aminobutyric acid(A)/benzodiazepine receptor ligands (58 compounds). Internal and external validations were carried out for the approximate similarity matrices computed using different approaches. Satisfactory results which compare reasonably well with a 3D approach were obtained: Q2= 0.65 and standard error in cross validation SECV= 0.83 for the training stage; r = 0.79 and error in external prediction = 0.82 for the test step. In addition, the method proposed was compared with other topological approaches based on constitutional similarity and on fingerprints. Satisfactory results were obtained.

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Approaches to Three‐Dimensional Quantitative Structure‐Activity Relationships

Cited by 29 publications

References 175 publications

A Self-Consistent Space-Domain Decomposition Method for QM/MM Computations of Protein Electrostatic Potentials

A Self-Consistent Space-Domain Decomposition Method for QM/MM Computations of Protein Electrostatic Potentials

Enantioselective Nonsteroidal Aromatase Inhibitors Identified through a Multidisciplinary Medicinal Chemistry Approach

Refinement and Use of the Approximate Similarity in QSAR Models for Benzodiazepine Receptor Ligands

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