RESUMEN
Molecular dynamics was used to optimize the droperidol-hERG complex obtained from docking. To accommodate the inhibitor, residues T623, S624, V625, G648, Y652, and F656 did not move significantly during the simulation, while F627 moved significantly. Binding sites in cryo-EM structures and in structures obtained from molecular dynamics simulations were characterized using solvent mapping and Atlas ligands, which were negative images of the binding site, were generated. Atlas ligands were found to be useful for identifying human ether-á-go-go-related potassium channel (hERG) inhibitors by aligning compounds to them or by guiding the docking of compounds in the binding site. A molecular dynamics optimized structure of hERG led to improved predictions using either compound alignment to the Atlas ligand or docking. The structure was also found to be suitable to define a strategy for lowering inhibition based on the proposed binding mode of compounds in the channel.
Asunto(s)
Canales de Potasio Éter-A-Go-Go , Éter , Sitios de Unión , Canal de Potasio ERG1/metabolismo , Canales de Potasio Éter-A-Go-Go/química , Canales de Potasio Éter-A-Go-Go/metabolismo , Humanos , Ligandos , SolventesRESUMEN
Targets in the protein docking experiment CAPRI (Critical Assessment of Predicted Interactions) generally present new challenges and contribute to new developments in methodology. In rounds 38 to 45 of CAPRI, most targets could be effectively predicted using template-based methods. However, the server ClusPro required structures rather than sequences as input, and hence we had to generate and dock homology models. The available templates also provided distance restraints that were directly used as input to the server. We show here that such an approach has some advantages. Free docking with template-based restraints using ClusPro reproduced some interfaces suggested by weak or ambiguous templates while not reproducing others, resulting in correct server predicted models. More recently we developed the fully automated ClusPro TBM server that performs template-based modeling and thus can use sequences rather than structures of component proteins as input. The performance of the server, freely available for noncommercial use at https://tbm.cluspro.org, is demonstrated by predicting the protein-protein targets of rounds 38 to 45 of CAPRI.
Asunto(s)
Simulación del Acoplamiento Molecular , Péptidos/química , Proteínas/química , Programas Informáticos , Secuencia de Aminoácidos , Benchmarking , Sitios de Unión , Humanos , Ligandos , Péptidos/metabolismo , Unión Proteica , Conformación Proteica en Hélice alfa , Conformación Proteica en Lámina beta , Dominios y Motivos de Interacción de Proteínas , Mapeo de Interacción de Proteínas , Multimerización de Proteína , Proteínas/metabolismo , Proyectos de Investigación , Homología Estructural de Proteína , TermodinámicaRESUMEN
As a participant in the joint CASP13-CAPRI46 assessment, the ClusPro server debuted its new template-based modeling functionality. The addition of this feature, called ClusPro TBM, was motivated by the previous CASP-CAPRI assessments and by the proven ability of template-based methods to produce higher-quality models, provided templates are available. In prior assessments, ClusPro submissions consisted of models that were produced via free docking of pre-generated homology models. This method was successful in terms of the number of acceptable predictions across targets; however, analysis of results showed that purely template-based methods produced a substantially higher number of medium-quality models for targets for which there were good templates available. The addition of template-based modeling has expanded ClusPro's ability to produce higher accuracy predictions, primarily for homomeric but also for some heteromeric targets. Here we review the newest additions to the ClusPro web server and discuss examples of CASP-CAPRI targets that continue to drive further development. We also describe ongoing work not yet implemented in the server. This includes the development of methods to improve template-based models and the use of co-evolutionary information for data-assisted free docking.
Asunto(s)
Biología Computacional , Conformación Proteica , Proteínas/ultraestructura , Programas Informáticos , Algoritmos , Sitios de Unión/genética , Bases de Datos de Proteínas , Humanos , Simulación del Acoplamiento Molecular , Simulación de Dinámica Molecular , Mapeo de Interacción de Proteínas , Proteínas/química , Proteínas/genética , Homología Estructural de ProteínaRESUMEN
Manifold representations of rotational/translational motion and conformational space of a ligand were previously shown to be effective for local energy optimization. In this paper we report the development of the Monte-Carlo energy minimization approach (MCM), which uses the same manifold representation. The approach was integrated into the docking pipeline developed for the current round of D3R experiment, and according to D3R assessment produced high accuracy poses for Cathepsin S ligands. Additionally, we have shown that (MD) refinement further improves docking quality. The code of the Monte-Carlo minimization is freely available at https://bitbucket.org/abc-group/mcm-demo .
Asunto(s)
Catepsinas/antagonistas & inhibidores , Simulación del Acoplamiento Molecular/métodos , Método de Montecarlo , Sitios de Unión , Diseño Asistido por Computadora , Cristalografía por Rayos X , Bases de Datos de Proteínas , Diseño de Fármacos , Ligandos , Conformación Molecular , Simulación de Dinámica Molecular , Unión Proteica , TermodinámicaRESUMEN
Many proteins in their unbound structures have cryptic sites that are not appropriately sized for drug binding. We consider here 32 proteins from the recently published CryptoSite set with validated cryptic sites, and study whether the sites remain cryptic in all available X-ray structures of the proteins solved without any ligand bound near the sites. It was shown that only few of these proteins have binding pockets that never form without ligand binding. Sites that are cryptic in some structures but spontaneously form in others are also rare. In most proteins the forming of pockets is affected by mutations or ligand binding at locations far from the cryptic site. To further explore these mechanisms, we applied adiabatic biased molecular dynamics simulations to guide the proteins from their ligand-free structures to ligand-bound conformations, and studied the distribution of druggability scores of the pockets located at the cryptic sites.