Opitz GBBB syndrome with total anomalous pulmonary venous connection: A new MID1 gene variant.

BACKGROUND: Opitz GBBB syndrome (GBBB) is an X-linked disease characterized by midline defects, including congenital heart defects. We present our diagnostic approach to the identification of GBBB in a consanguineous family in which two males siblings were concordant for a total anomalous connection of pulmonary veins and minor facial dysmorphias. METHODS: Targeted exome sequencing analysis of a 380-gene panel associated with cardiovascular disease was performed on the propositus. Interpretative analysis of the exome results was conducted, and 3D models of the protein changes were generated. RESULTS: We identified a NM_000381.4:c.608G>A;p.(Arg203Gln) change in MID1, affecting the conformation of the B-box 2 domain of the protein, with a zinc finger structure and associated protein interactions. This clinical phenotype is consistent with GBBB; however, the type of congenital heart disease observed in this case has not been previously reported. CONCLUSION: A new likely pathogenic variant on MID1 c.608G>A was found to be associated with Opitz GBBB syndrome.

Ligand recognition properties of the vasopressin V2 receptor studied under QSAR and molecular modeling strategies.

The design of new drugs that target vasopressin 2 receptor (V2R) is of vital importance to develop new therapeutic alternatives to treat diseases such as heart failure, polycystic kidney disease. To get structural insights related to V2R-ligand recognition, we have used a combined approach of docking, molecular dynamics simulations (MD) and quantitative structure-activity relationship (QSAR) to elucidate the detailed interaction of the V2R with 119 of its antagonists. The three-dimensional model of V2R was built by threading methods refining its structure through MD simulations upon which the 119 ligands were subjected to docking studies. The theoretical results show that binding recognition of these ligands on V2R is diverse, but the main pharmacophore (electronic and π-π interactions) is maintained; thus, this information was validated under QSAR results. QSAR studies were performed using MLR analysis followed by ANN analysis to increase the model quality. The final equation was developed by choosing the optimal combination of descriptors after removing the outliers. The applicability domains of the constructed QSAR models were defined using the leverage and standardization approaches. The results suggest that the proposed QSAR models can reliably predict the reproductive toxicity potential of diverse chemicals, and they can be useful tools for screening new chemicals for safety assessment.

Application of computational methods for anticancer drug discovery, design, and optimization / Aplicación de métodos computacionales para el descubrimiento, diseño y optimización de fármacos contra el cáncer

Abstract: Developing a novel drug is a complex, risky, expensive and time-consuming venture. It is estimated that the conventional drug discovery process ending with a new medicine ready for the market can take up to 15 years and more than a billion USD. Fortunately, this scenario has recently changed with the arrival of new approaches. Many novel technologies and methodologies have been developed to increase the efficiency of the drug discovery process, and computational methodologies have become a crucial component of many drug discovery programs. From hit identification to lead optimization, techniques such as ligand- or structure-based virtual screening are widely used in many discovery efforts. It is the case for designing potential anticancer drugs and drug candidates, where these computational approaches have had a major impact over the years and have provided fruitful insights into the field of cancer. In this paper, we review the concept of rational design presenting some of the most representative examples of molecules identified by means of it. Key principles are illustrated through case studies including specifically successful achievements in the field of anticancer drug design to demonstrate that research advances, with the aid of in silico drug design, have the potential to create novel anticancer drugs.

Resumen: El desarrollo de un nuevo fármaco es un proceso complejo y arriesgado que requiere una enorme cantidad de tiempo y dinero. Se estima que el proceso estándar para producir un nuevo fármaco, desde su descubrimiento hasta que acaba en el mercado, puede tardar hasta 15 años y tener un costo de mil millones de dólares (USD). Por fortuna, este escenario ha cambiado recientemente con la llegada de nuevas tecnologías y metodologías. Entre ellas, los métodos computacionales se han convertido en un componente determinante en muchos programas de descubrimiento de fármacos. En un esfuerzo por incrementar las posibilidades de encontrar nuevas moléculas con potencial farmacológico, se utilizan técnicas como el cribado virtual de quimiotecas construidas con base en ligandos o estructuras para la identificación de hits y hasta para la optimización de compuestos líder. En lo que respecta al diseño y descubrimiento de nuevos candidatos a fármacos contra el cáncer, estos enfoques tienen, a la fecha, un impacto importante y aportan nuevas posibilidades terapéuticas. En este artículo se revisa el concepto del diseño racional de moléculas con potencial farmacológico, ilustrando los principios clave con algunos de los ejemplos más representativos y exitosos de moléculas identificadas mediante estas aproximaciones. Se incluyen casos desarrollados en el campo del diseño de fármacos contra el cáncer con la finalidad de mostrar cómo, con la ayuda del diseño asistido por computadora, se pueden generar nuevos fármacos que den esperanza a millones de pacientes.

New perspectives on the computational characterization of the kinetics of binding-unbinding in drug design: implications for novel therapies / Nuevas perspectivas sobre la caracterización computacional de la cinética de unión-desunión en el diseño de fármacos: implicaciones para terapias de vanguardia

Abstract: The efficiency and the propensity of a drug to be bound to its target protein have been inseparable concepts for decades now. The correlation between the pharmacological activity and the binding affinity has been the first rule to design and optimize a new drug rationally. However, this argument does not prove to be infallible when the results of in vivo assays have to be confronted. Only recently, we understand that other magnitudes as the kinetic rates of binding and unbinding, or the mean residence time of the complex drug-protein, are equally relevant to draw a more accurate model of the mechanism of action of a drug. It is in this scenario where new computational techniques to simulate the all-atom dynamics of the biomolecular system find its valuable place on the challenge of designing new molecules for more effective and less toxic therapies.

Resumen: La eficiencia de un fármaco se ha relacionado habitualmente con su constante de afinidad, magnitud que puede ser medida experimentalmente in vitro y que cuantifica la propensión mostrada por la molécula ligando para interaccionar con su proteína diana. Este modo de entender el mecanismo de acción ha guiado durante años el desarrollo de nuevas moléculas con potencial farmacológico. Sin embargo, dicho modelo o criterio no es infalible cuando se confronta con los resultados de ensayos in vivo. Otras magnitudes, como las constantes cinéticas de asociación o disociación o el tiempo de residencia del ligando acoplado a su proteína diana, demuestran ser igualmente necesarias para comprender y predecir la capacidad farmacológica del compuesto químico. En este nuevo escenario, con ayuda de las técnicas computacionales de simulación molecular, la correcta caracterización del proceso dinámico de unión y desunión del ligando y receptor resulta imprescindible para poder diseñar racionalmente nuevas moléculas que permitan terapias más eficaces y menos tóxicas.

New perspectives on the computational characterization of the kinetics of binding-unbinding in drug design: implications for novel therapies.

The efficiency and the propensity of a drug to be bound to its target protein have been inseparable concepts for decades now. The correlation between the pharmacological activity and the binding affinity has been the first rule to design and optimize a new drug rationally. However, this argument does not prove to be infallible when the results of in vivo assays have to be confronted. Only recently, we understand that other magnitudes as the kinetic rates of binding and unbinding, or the mean residence time of the complex drug-protein, are equally relevant to draw a more accurate model of the mechanism of action of a drug. It is in this scenario where new computational techniques to simulate the all-atom dynamics of the biomolecular system find its valuable place on the challenge of designing new molecules for more effective and less toxic therapies.

Application of computational methods for anticancer drug discovery, design, and optimization.

Developing a novel drug is a complex, risky, expensive and time-consuming venture. It is estimated that the conventional drug discovery process ending with a new medicine ready for the market can take up to 15 years and more than a billion USD. Fortunately, this scenario has recently changed with the arrival of new approaches. Many novel technologies and methodologies have been developed to increase the efficiency of the drug discovery process, and computational methodologies have become a crucial component of many drug discovery programs. From hit identification to lead optimization, techniques such as ligand- or structure-based virtual screening are widely used in many discovery efforts. It is the case for designing potential anticancer drugs and drug candidates, where these computational approaches have had a major impact over the years and have provided fruitful insights into the field of cancer. In this paper, we review the concept of rational design presenting some of the most representative examples of molecules identified by means of it. Key principles are illustrated through case studies including specifically successful achievements in the field of anticancer drug design to demonstrate that research advances, with the aid of in silico drug design, have the potential to create novel anticancer drugs.

Thermal unfolding of apo- and holo-enolase from Saccharomyces cerevisiae: different mechanisms, similar activation enthalpies.

Yeast enolase is stabilized by its natural cofactor Mg(2+). This stabilization is ascribed to the reduced subunit dissociation of the holoprotein. Nevertheless, how Mg(2+) alters the unfolding mechanism has yet to be fully characterized. Here, we investigate the role of Mg(2+) in the denaturation mechanism and unfolding kinetics of yeast enolase. Apo-enolase unfolds through a three-state process (N(2)↔2I→2D). The intermediate species is described as a monomeric molten globule-like conformation that becomes noticeable in the presence of phosphate and is able to recover its native secondary structure when cooled down. Kinetic studies confirmed the presence of the intermediate species, even though it was not noticeable in the thermal scans. The cofactor increases the cooperativity of the unfolding transitions, while the intermediate species becomes less noticeable or nonexistent. Thus, holo-enolase follows a simple two-state mechanism (N(2)→2D). Our results indicate smaller unfolding rate-constants in the presence of Mg(2+), thus favoring the native state. The temperature dependence of the unfolding rates allowed us to calculate the activation enthalpies of denaturation. Interestingly, despite the different unfolding mechanisms of the apo and holo forms of enolase, they both have similar activation barriers of denaturation (185-190 kJ mol(-1)).

Thermal-unfolding reaction of triosephosphate isomerase from Trypanosoma cruzi.

Thermal denaturation of triosephosphate isomerase from Trypanosoma cruzi was studied by circular dicrhoism and fluorescence spectroscopies. The unfolding transition was found to be highly irreversible even at the very early stages of the reaction. Kinetic studies, allowed us to identify consecutive reactions. Firstly, only the tryptophan environment is altered. Next, changes on the secondary structure and hydrophobic surface exposure measured by 1-anilino-8-naphthalenesulfonate (ANS) binding were observed. Further conformational changes imply additional modifications on the secondary and tertiary structures and release of the hydrophobic dye leading to the formation of the unfolded state that is prone to aggregate.