Abnormal expression or mutations in Ras proteins has been found in up to 30% of cancer cell types, making them excellent protein models to probe structure-function relationships of cell-signaling processes that mediat...Abnormal expression or mutations in Ras proteins has been found in up to 30% of cancer cell types, making them excellent protein models to probe structure-function relationships of cell-signaling processes that mediate cell transformtion. Yet, there has been very little development of therapies to help tackle Ras-related diseased states. The development of small molecules to target Ras proteins to potentially inhibit abnormal Ras-stimulated cell signaling has been conceptualized and some progress has been made over the last 16 or so years. Here, we briefly review studies characterizing Ras protein-small molecule interactions to show the importance and potential that these small molecules may have for Ras-related drug discovery. We summarize recent results, highlighting small molecules that can be directly targeted to Ras using Structure-Based Drug Design (SBDD) and Fragment-Based Lead Discovery (FBLD) methods. The inactivation of Ras oncogenic signaling in vitro by small molecules is currently an attractive hurdle to try to and leap over in order to attack the oncogenic state. In this regard, important features of previously characterized properties of small molecule Ras targets, as well as a current understanding of conformational and dynamics changes seen for Ras-related mutants, relative to wild type, must be taken into account as newer small molecule design strategies towards Ras are developed.展开更多
Epilepsy is described as the most common chronic brain disorder. A typical symptom of epilepsy results in uncontrolled convulsions caused by temporary excessive neuronal discharges. Although several new anticon-vulsan...Epilepsy is described as the most common chronic brain disorder. A typical symptom of epilepsy results in uncontrolled convulsions caused by temporary excessive neuronal discharges. Although several new anticon-vulsants have been introduced, some types of seizures have still not been adequately controlled with these new and current therapies. There is an urgent need to develop new anticonvulsant drugs to control the many different types of seizures. Many studies have shown that the epilepsies involve more than one mechanism and therefore may be responsible for the various types of observed seizures. Recently reported studies have shown that a group of newly synthesized 6 Hz active anticonvulsant fluorinated N-benzamide enaminones exhibited selective inhibitions of voltage-gated sodium (Nav) channels. Nav channels are responsible for the initial inward currents during the depolarization phases of the action potential in excitable cells. The activation and opening of Nav channels result in the initial phases of action potentials. We hypothesize that there is an essential pharmacophore model for the interactions between these enaminones and the active sites of Nav channels. The research reported here is focused on molecular docking studies of the interactions that occur between the fluorinated N-benzamide enaminones and the Nav channels. These studies may open an avenue for designing anticonvulsant drugs by inhibiting Nav channels.展开更多
BEAR (Binding Estimation After Refinement) is a computational method for structure-based virtual screening. It was set up as a post-docking processing tool for the refinement of ligand binding modes predicted by molec...BEAR (Binding Estimation After Refinement) is a computational method for structure-based virtual screening. It was set up as a post-docking processing tool for the refinement of ligand binding modes predicted by molecular docking programs and the accurate evaluation of free energies of binding. BEAR has been validated in a number of computational drug discovery applications. It performed well in discriminating active ligands with respect to molecular decoys of biological targets belonging to different protein families as well as in discovering biologically active hits. Recently, it has also been validated in the emerging field of G-protein coupled receptors structure based virtual screening.展开更多
The three-dimensional structure of a biomolecule rather than its one-dimensionM sequence determines its biological function. At present, the most accurate structures are derived from experimental data measured mainly ...The three-dimensional structure of a biomolecule rather than its one-dimensionM sequence determines its biological function. At present, the most accurate structures are derived from experimental data measured mainly by two techniques： X-ray crystallog- raphy and nuclear magnetic resonance （NMR） spec- troscopy. Because neither X-ray crystallography nor NMR spectroscopy could directly measure the positions of atoms in a biomolecule, algorithms must be designed to compute atom coordinates from the data. One salient feature of most NMR structure computation algorithms is their reliance on stochastic search to find the lowest energy conformations that satisfy the experimentally- derived geometric restraints. However, neither the cor- rectness of the stochastic search has been established nor the errors in the output structures could be quantified. Though there exist exact algorithms to compute struc- tures from angular restraints, similar algorithms that use distance restraints remain to be developed. An important application of structures is rational drug design where protein-ligand docking plays a crit- ical role. In fact, various docking programs that place a compound into the binding site of a target protein have been used routinely by medicinal chemists for both lead identification and optimization. Unfortunately, de- spite ongoing methodological advances and some success stories, the performance of current docking algorithms is still data-dependent. These algorithms formulate the docking problem as a match of two sets of feature points. Both the selection of feature points and the search for the best poses with the minimum scores are accomplished through some stochastic search methods. Both the un- certainty in the scoring function and the limited sam- pling space attained by the stochastic search contribute to their failures. Recently, we have developed two novel docking algorithms： a data-driven docking algorithm and a general docking algorithm that does not rely on experimental data. Our algorithms 展开更多
文摘Abnormal expression or mutations in Ras proteins has been found in up to 30% of cancer cell types, making them excellent protein models to probe structure-function relationships of cell-signaling processes that mediate cell transformtion. Yet, there has been very little development of therapies to help tackle Ras-related diseased states. The development of small molecules to target Ras proteins to potentially inhibit abnormal Ras-stimulated cell signaling has been conceptualized and some progress has been made over the last 16 or so years. Here, we briefly review studies characterizing Ras protein-small molecule interactions to show the importance and potential that these small molecules may have for Ras-related drug discovery. We summarize recent results, highlighting small molecules that can be directly targeted to Ras using Structure-Based Drug Design (SBDD) and Fragment-Based Lead Discovery (FBLD) methods. The inactivation of Ras oncogenic signaling in vitro by small molecules is currently an attractive hurdle to try to and leap over in order to attack the oncogenic state. In this regard, important features of previously characterized properties of small molecule Ras targets, as well as a current understanding of conformational and dynamics changes seen for Ras-related mutants, relative to wild type, must be taken into account as newer small molecule design strategies towards Ras are developed.
文摘Epilepsy is described as the most common chronic brain disorder. A typical symptom of epilepsy results in uncontrolled convulsions caused by temporary excessive neuronal discharges. Although several new anticon-vulsants have been introduced, some types of seizures have still not been adequately controlled with these new and current therapies. There is an urgent need to develop new anticonvulsant drugs to control the many different types of seizures. Many studies have shown that the epilepsies involve more than one mechanism and therefore may be responsible for the various types of observed seizures. Recently reported studies have shown that a group of newly synthesized 6 Hz active anticonvulsant fluorinated N-benzamide enaminones exhibited selective inhibitions of voltage-gated sodium (Nav) channels. Nav channels are responsible for the initial inward currents during the depolarization phases of the action potential in excitable cells. The activation and opening of Nav channels result in the initial phases of action potentials. We hypothesize that there is an essential pharmacophore model for the interactions between these enaminones and the active sites of Nav channels. The research reported here is focused on molecular docking studies of the interactions that occur between the fluorinated N-benzamide enaminones and the Nav channels. These studies may open an avenue for designing anticonvulsant drugs by inhibiting Nav channels.
文摘BEAR (Binding Estimation After Refinement) is a computational method for structure-based virtual screening. It was set up as a post-docking processing tool for the refinement of ligand binding modes predicted by molecular docking programs and the accurate evaluation of free energies of binding. BEAR has been validated in a number of computational drug discovery applications. It performed well in discriminating active ligands with respect to molecular decoys of biological targets belonging to different protein families as well as in discovering biologically active hits. Recently, it has also been validated in the emerging field of G-protein coupled receptors structure based virtual screening.
文摘The three-dimensional structure of a biomolecule rather than its one-dimensionM sequence determines its biological function. At present, the most accurate structures are derived from experimental data measured mainly by two techniques： X-ray crystallog- raphy and nuclear magnetic resonance （NMR） spec- troscopy. Because neither X-ray crystallography nor NMR spectroscopy could directly measure the positions of atoms in a biomolecule, algorithms must be designed to compute atom coordinates from the data. One salient feature of most NMR structure computation algorithms is their reliance on stochastic search to find the lowest energy conformations that satisfy the experimentally- derived geometric restraints. However, neither the cor- rectness of the stochastic search has been established nor the errors in the output structures could be quantified. Though there exist exact algorithms to compute struc- tures from angular restraints, similar algorithms that use distance restraints remain to be developed. An important application of structures is rational drug design where protein-ligand docking plays a crit- ical role. In fact, various docking programs that place a compound into the binding site of a target protein have been used routinely by medicinal chemists for both lead identification and optimization. Unfortunately, de- spite ongoing methodological advances and some success stories, the performance of current docking algorithms is still data-dependent. These algorithms formulate the docking problem as a match of two sets of feature points. Both the selection of feature points and the search for the best poses with the minimum scores are accomplished through some stochastic search methods. Both the un- certainty in the scoring function and the limited sam- pling space attained by the stochastic search contribute to their failures. Recently, we have developed two novel docking algorithms： a data-driven docking algorithm and a general docking algorithm that does not rely on experimental data. Our algorithms
