A large database is desired for machine learning(ML) technology to make accurate predictions of materials physicochemical properties based on their molecular structure.When a large database is not available,the develo...A large database is desired for machine learning(ML) technology to make accurate predictions of materials physicochemical properties based on their molecular structure.When a large database is not available,the development of proper featurization method based on physicochemical nature of target proprieties can improve the predictive power of ML models with a smaller database.In this work,we show that two new featurization methods,volume occupation spatial matrix and heat contribution spatial matrix,can improve the accuracy in predicting energetic materials' crystal density(ρ_(crystal)) and solid phase enthalpy of formation(H_(f,solid)) using a database containing 451 energetic molecules.Their mean absolute errors are reduced from 0.048 g/cm~3 and 24.67 kcal/mol to 0.035 g/cm~3 and 9.66 kcal/mol,respectively.By leave-one-out-cross-validation,the newly developed ML models can be used to determine the performance of most kinds of energetic materials except cubanes.Our ML models are applied to predict ρ_(crystal) and H_(f,solid) of CHON-based molecules of the 150 million sized PubChem database,and screened out 56 candidates with competitive detonation performance and reasonable chemical structures.With further improvement in future,spatial matrices have the potential of becoming multifunctional ML simulation tools that could provide even better predictions in wider fields of materials science.展开更多
Xanthomonas oryzae pv.oryzae(Xoo) is an important rice pathogen.This is a vascular pathogen entering the plant via the hydathodes causing rice bacterial blight.It has been known that most regulation of pathogenicity f...Xanthomonas oryzae pv.oryzae(Xoo) is an important rice pathogen.This is a vascular pathogen entering the plant via the hydathodes causing rice bacterial blight.It has been known that most regulation of pathogenicity factor F(RpfF) genes in Xanthomonas regulates virulence in response to the diffusible signal factor(DSF).The RpfF recognized as an attractive drug target in bacterial rice blight disease.In this study,we performed the gene-gene interaction of RpfF and pathway functional analysis.3 D structure of RpfF protein was predicted using a homology modelling tool Swiss-Model and refined by molecular dynamics(MD) simulation.The refined model protein was predicted structural assessment using various tools such as PROCHECK,ERRAT,and VERIFY-3 D.We have collected 2 500 rifampicin analogues from Zinc Database by virtual screening.The screened compounds were docked into the active site of the RpfF protein using AutoDock Vina in PyRx Virtual Screening Tool.Furthermore,docking result and in silico ADMET analysis described that the compounds ZINC03056414,ZINC03205310,ZINC08673779,ZINC09100848,ZINC09729566,ZINC11415953,ZINC12810788,ZINC24989313,ZINC27441787 and ZINC32739565 have best binding energies and less toxicity than reference compound.This study revealed that the active site residues such as HIS-118,HIS-147,THR-148,ARG-179,ASP-207,ARG-240 and THR-244 are key roles in the pathogenicity.It could be beneficial in the design of small molecule therapeutics or the treatment of rice bacterial blight disease.展开更多
The serotonin 2A（5-HT2A） receptor has been implicated in several neurological conditions and potent 5-HT2A antagonists have therapeutic effects in the treatment of schizo phrenia and depression.In this study,a poten...The serotonin 2A（5-HT2A） receptor has been implicated in several neurological conditions and potent 5-HT2A antagonists have therapeutic effects in the treatment of schizo phrenia and depression.In this study,a potent novel 5-HT2A inhibitor 05245768 with a Ki value of （593.89±34.10） nmol/L was discovered by integrating a set of computational approaches and experiments（protein structure prediction,pharmacophore-based virtual screening,automated molecular docking and pharmacological bioassay）.The 5-HT2A receptor showed a negatively charged bin-ding pocket.The binding mode of compound 05245768 with 5-HT2A was obtained by GOLD docking procedure,which revealed the conserved interaction between protonated nitrogen in compound 05245768 and carboxylate group of D3.32 at the active site of 5-HT2A.展开更多
基金support from the Ministry of Education(MOE) Singapore Tier 1 (RG8/20)。
文摘A large database is desired for machine learning(ML) technology to make accurate predictions of materials physicochemical properties based on their molecular structure.When a large database is not available,the development of proper featurization method based on physicochemical nature of target proprieties can improve the predictive power of ML models with a smaller database.In this work,we show that two new featurization methods,volume occupation spatial matrix and heat contribution spatial matrix,can improve the accuracy in predicting energetic materials' crystal density(ρ_(crystal)) and solid phase enthalpy of formation(H_(f,solid)) using a database containing 451 energetic molecules.Their mean absolute errors are reduced from 0.048 g/cm~3 and 24.67 kcal/mol to 0.035 g/cm~3 and 9.66 kcal/mol,respectively.By leave-one-out-cross-validation,the newly developed ML models can be used to determine the performance of most kinds of energetic materials except cubanes.Our ML models are applied to predict ρ_(crystal) and H_(f,solid) of CHON-based molecules of the 150 million sized PubChem database,and screened out 56 candidates with competitive detonation performance and reasonable chemical structures.With further improvement in future,spatial matrices have the potential of becoming multifunctional ML simulation tools that could provide even better predictions in wider fields of materials science.
文摘Xanthomonas oryzae pv.oryzae(Xoo) is an important rice pathogen.This is a vascular pathogen entering the plant via the hydathodes causing rice bacterial blight.It has been known that most regulation of pathogenicity factor F(RpfF) genes in Xanthomonas regulates virulence in response to the diffusible signal factor(DSF).The RpfF recognized as an attractive drug target in bacterial rice blight disease.In this study,we performed the gene-gene interaction of RpfF and pathway functional analysis.3 D structure of RpfF protein was predicted using a homology modelling tool Swiss-Model and refined by molecular dynamics(MD) simulation.The refined model protein was predicted structural assessment using various tools such as PROCHECK,ERRAT,and VERIFY-3 D.We have collected 2 500 rifampicin analogues from Zinc Database by virtual screening.The screened compounds were docked into the active site of the RpfF protein using AutoDock Vina in PyRx Virtual Screening Tool.Furthermore,docking result and in silico ADMET analysis described that the compounds ZINC03056414,ZINC03205310,ZINC08673779,ZINC09100848,ZINC09729566,ZINC11415953,ZINC12810788,ZINC24989313,ZINC27441787 and ZINC32739565 have best binding energies and less toxicity than reference compound.This study revealed that the active site residues such as HIS-118,HIS-147,THR-148,ARG-179,ASP-207,ARG-240 and THR-244 are key roles in the pathogenicity.It could be beneficial in the design of small molecule therapeutics or the treatment of rice bacterial blight disease.
基金Supported by the National High Technology Research and Development Program of China(No.2009AA02Z308)the Major State Basic Research Development Program of China(No.2010CB912601)the National Natural Science Foundation of China (No.20702009)
文摘The serotonin 2A（5-HT2A） receptor has been implicated in several neurological conditions and potent 5-HT2A antagonists have therapeutic effects in the treatment of schizo phrenia and depression.In this study,a potent novel 5-HT2A inhibitor 05245768 with a Ki value of （593.89±34.10） nmol/L was discovered by integrating a set of computational approaches and experiments（protein structure prediction,pharmacophore-based virtual screening,automated molecular docking and pharmacological bioassay）.The 5-HT2A receptor showed a negatively charged bin-ding pocket.The binding mode of compound 05245768 with 5-HT2A was obtained by GOLD docking procedure,which revealed the conserved interaction between protonated nitrogen in compound 05245768 and carboxylate group of D3.32 at the active site of 5-HT2A.
