The release of AlphaFold2 has sparked a rapid expansion in protein model databases.Efficient protein structure retrieval is crucial for the analysis of structure models,while measuring the similarity between structure...The release of AlphaFold2 has sparked a rapid expansion in protein model databases.Efficient protein structure retrieval is crucial for the analysis of structure models,while measuring the similarity between structures is the key challenge in structural retrieval.Although existing structure alignment algorithms can address this challenge,they are often time-consuming.Currently,the state-of-the-art approach involves converting protein structures into three-dimensional(3D)Zernike descriptors and assessing similarity using Euclidean distance.However,the methods for computing 3D Zernike descriptors mainly rely on structural surfaces and are predominantly web-based,thus limiting their application in studying custom datasets.To overcome this limitation,we developed FP-Zernike,a user-friendly toolkit for computing different types of Zernike descriptors based on feature points.Users simply need to enter a single line of command to calculate the Zernike descriptors of all structures in customized datasets.FP-Zernike outperforms the leading method in terms of retrieval accuracy and binary classification accuracy across diverse benchmark datasets.In addition,we showed the application of FP-Zernike in the construction of the descriptor database and the protocol used for the Protein Data Bank(PDB)dataset to facilitate the local deployment of this tool for interested readers.Our demonstration contained 590,685 structures,and at this scale,our system required only 4-9 s to complete a retrieval.The experiments confirmed that it achieved the state-of-the-art accuracy level.FP-Zernike is an open-source toolkit,with the source code and related data accessible at https://ngdc.cncb.ac.cn/biocode/tools/BT007365/releases/0.1,as well as through a webserver at http://www.structbioinfo.cn/.展开更多
Since its establishment in 2013,BioLiP has become one of the widely used resources for protein-ligand interactions.Nevertheless,several known issues occurred with it over the past decade.For example,the protein-ligand...Since its establishment in 2013,BioLiP has become one of the widely used resources for protein-ligand interactions.Nevertheless,several known issues occurred with it over the past decade.For example,the protein-ligand interactions are represented in the form of single chain-based tertiary structures,which may be inappropriate as many interactions involve multiple protein chains(known as quaternary structures).We sought to address these issues,resulting in Q-BioLiP,a comprehensive resource for quaternary structure-based protein-ligand interactions.The major features of Q-BioLiP include:(1)representing protein structures in the form of quaternary structures rather than single chain-based tertiary structures;(2)pairing DNA/RNA chains properly rather than separation;(3)providing both experimental and predicted binding affinities;(4)retaining both biologically relevant and irrelevant interactions to alleviate the wrong justification of ligands’biological relevance;and(5)developing a new quaternary structure-based algorithm for the modelling of protein-ligand complex structure.With these new features,Q-BioLiP is expected to be a valuable resource for studying biomolecule interactions,including protein-small molecule interaction,protein-metal ion interaction,protein-peptide interaction,protein-protein interaction,protein-DNA/RNA interaction,and RNA-small molecule interaction.Q-BioLiP is freely available at https://yanglab.qd.sdu.edu.cn/Q-BioLiP/.展开更多
Optical neural networks (ONNs), enabling low latency and high parallel data processing withoutelectromagnetic interference, have become a viable player for fast and energy-efficient processing andcalculation to meet t...Optical neural networks (ONNs), enabling low latency and high parallel data processing withoutelectromagnetic interference, have become a viable player for fast and energy-efficient processing andcalculation to meet the increasing demand for hash rate. Photonic memories employing nonvolatile phase-change materials could achieve zero static power consumption, low thermal cross talk, large-scale, andhigh-energy-efficient photonic neural networks. Nevertheless, the switching speed and dynamic energyconsumption of phase-change material-based photonic memories make them inapplicable for in situ training.Here, by integrating a patch of phase change thin film with a PIN-diode-embedded microring resonator,a bifunctional photonic memory enabling both 5-bit storage and nanoseconds volatile modulation wasdemonstrated. For the first time, a concept is presented for electrically programmable phase-changematerial-driven photonic memory integrated with nanosecond modulation to allow fast in situ training and zerostatic power consumption data processing in ONNs. ONNs with an optical convolution kernel constructedby our photonic memory theoretically achieved an accuracy of predictions higher than 95% when testedby the MNIST handwritten digit database. This provides a feasible solution to constructing large-scalenonvolatile ONNs with high-speed in situ training capability.展开更多
We demonstrate a high responsivity all-silicon in-line optical power monitor by using the thermal effect to enhance the quantum efficiency of defect-mediated absorption at 1550 nm.The doping compensation technique is ...We demonstrate a high responsivity all-silicon in-line optical power monitor by using the thermal effect to enhance the quantum efficiency of defect-mediated absorption at 1550 nm.The doping compensation technique is utilized to increase the density of lattice defects responsible for the sub-bandgap absorption and suppress the detrimental free carrier absorption.The 200-μm-long device presents a propagation loss as low as 2.9 d B/cm.Its responsivity is enhanced from 12.1 m A/W to 112 m A/W at-9 V bias by heating the optical absorption region.With this device,we build an optical power monitoring system that operates in the sampling mode.The minimal detectable optical power of the system is below-22.8 d Bm,while the average power consumption is less than1 m W at a sampling frequency of 10 Hz.Advantages of this scheme in terms of high responsivity,low insertion loss,and low power consumption lend itself to implement the feedback control of advanced large-scale silicon photonic integrated circuits.展开更多
We demonstrate a single-chip silicon optical single sideband (OSSB) modulator composed of a radio frequenc(RF) branch line coupler (BLC) and a silicon dual-parallel Mach–Zehnder modulator (DP-MZM).A co-design between...We demonstrate a single-chip silicon optical single sideband (OSSB) modulator composed of a radio frequenc(RF) branch line coupler (BLC) and a silicon dual-parallel Mach–Zehnder modulator (DP-MZM).A co-design between the BLC and the DP-MZM is implemented to improve the sideband suppression ratio (SSR).The modu lator has a modulation efficiency of V_(π)L_(π)~1.75 V·cm and a 3 dB electro-optical (EO) bandwidth of 48.7 GHz The BLC can generate a pair of RF signals with equal amplitudes and orthogonal phases at the optimal frequenc of 21 GHz.We prove through theoretical calculation and experiment that,although the BLC’s performance in terms of power balance and phase orthogonality deteriorates in a wider frequency range,high SSRs can be realized by adjusting relevant bias phases of the DP-MZM.With this technique,the undesired sidebands are completel suppressed below the noise floor in the frequency range from 15 GHz to 30 GHz when the chip operates in the ful carrier OSSB (FC-OSSB) mode.In addition,an SSR>35 dB and an carrier suppression ratio (CSR)>42 dB ar demonstrated at 21 GHz in the suppressed carrier OSSB (SC-OSSB) mode.展开更多
基金supported by the National Key R&D Program of China(Grant Nos.2021YFF0704300 and 2020YFA0712400)the National Natural Science Foundation of China(Grant Nos.62072280,61771009,61932018,62072441,32241027,and T2225007)+1 种基金the open project of BGI-Shenzhen,Shenzhen 518000,China(Grant No.BGIRSZ20220005)the Natural Science Foundation of Ningxia Province,China(Grant No.2023AAC05036).
文摘The release of AlphaFold2 has sparked a rapid expansion in protein model databases.Efficient protein structure retrieval is crucial for the analysis of structure models,while measuring the similarity between structures is the key challenge in structural retrieval.Although existing structure alignment algorithms can address this challenge,they are often time-consuming.Currently,the state-of-the-art approach involves converting protein structures into three-dimensional(3D)Zernike descriptors and assessing similarity using Euclidean distance.However,the methods for computing 3D Zernike descriptors mainly rely on structural surfaces and are predominantly web-based,thus limiting their application in studying custom datasets.To overcome this limitation,we developed FP-Zernike,a user-friendly toolkit for computing different types of Zernike descriptors based on feature points.Users simply need to enter a single line of command to calculate the Zernike descriptors of all structures in customized datasets.FP-Zernike outperforms the leading method in terms of retrieval accuracy and binary classification accuracy across diverse benchmark datasets.In addition,we showed the application of FP-Zernike in the construction of the descriptor database and the protocol used for the Protein Data Bank(PDB)dataset to facilitate the local deployment of this tool for interested readers.Our demonstration contained 590,685 structures,and at this scale,our system required only 4-9 s to complete a retrieval.The experiments confirmed that it achieved the state-of-the-art accuracy level.FP-Zernike is an open-source toolkit,with the source code and related data accessible at https://ngdc.cncb.ac.cn/biocode/tools/BT007365/releases/0.1,as well as through a webserver at http://www.structbioinfo.cn/.
基金supported in part by the National Natural Science Foundation of China(Grant Nos.T2225007 and T2222012)the Foundation for Innovative Research Groups of State Key Laboratory of Microbial Technology,China(Grant No.WZCX2021-03).
文摘Since its establishment in 2013,BioLiP has become one of the widely used resources for protein-ligand interactions.Nevertheless,several known issues occurred with it over the past decade.For example,the protein-ligand interactions are represented in the form of single chain-based tertiary structures,which may be inappropriate as many interactions involve multiple protein chains(known as quaternary structures).We sought to address these issues,resulting in Q-BioLiP,a comprehensive resource for quaternary structure-based protein-ligand interactions.The major features of Q-BioLiP include:(1)representing protein structures in the form of quaternary structures rather than single chain-based tertiary structures;(2)pairing DNA/RNA chains properly rather than separation;(3)providing both experimental and predicted binding affinities;(4)retaining both biologically relevant and irrelevant interactions to alleviate the wrong justification of ligands’biological relevance;and(5)developing a new quaternary structure-based algorithm for the modelling of protein-ligand complex structure.With these new features,Q-BioLiP is expected to be a valuable resource for studying biomolecule interactions,including protein-small molecule interaction,protein-metal ion interaction,protein-peptide interaction,protein-protein interaction,protein-DNA/RNA interaction,and RNA-small molecule interaction.Q-BioLiP is freely available at https://yanglab.qd.sdu.edu.cn/Q-BioLiP/.
基金supported by the National Key Research and Development Program of China (2019YFB2203002 and 2021YFB2801300)National Natural Science Foundation of China (62105287, 91950204, and 61975179)Zhejiang Provincial Natural Science Foundation (LD22F040002)
文摘Optical neural networks (ONNs), enabling low latency and high parallel data processing withoutelectromagnetic interference, have become a viable player for fast and energy-efficient processing andcalculation to meet the increasing demand for hash rate. Photonic memories employing nonvolatile phase-change materials could achieve zero static power consumption, low thermal cross talk, large-scale, andhigh-energy-efficient photonic neural networks. Nevertheless, the switching speed and dynamic energyconsumption of phase-change material-based photonic memories make them inapplicable for in situ training.Here, by integrating a patch of phase change thin film with a PIN-diode-embedded microring resonator,a bifunctional photonic memory enabling both 5-bit storage and nanoseconds volatile modulation wasdemonstrated. For the first time, a concept is presented for electrically programmable phase-changematerial-driven photonic memory integrated with nanosecond modulation to allow fast in situ training and zerostatic power consumption data processing in ONNs. ONNs with an optical convolution kernel constructedby our photonic memory theoretically achieved an accuracy of predictions higher than 95% when testedby the MNIST handwritten digit database. This provides a feasible solution to constructing large-scalenonvolatile ONNs with high-speed in situ training capability.
基金Ningbo 2025 Major Project of Science and Technology Innovation(2020Z021)National Key Research and Development Program of China(2018YFB2200602)。
文摘We demonstrate a high responsivity all-silicon in-line optical power monitor by using the thermal effect to enhance the quantum efficiency of defect-mediated absorption at 1550 nm.The doping compensation technique is utilized to increase the density of lattice defects responsible for the sub-bandgap absorption and suppress the detrimental free carrier absorption.The 200-μm-long device presents a propagation loss as low as 2.9 d B/cm.Its responsivity is enhanced from 12.1 m A/W to 112 m A/W at-9 V bias by heating the optical absorption region.With this device,we build an optical power monitoring system that operates in the sampling mode.The minimal detectable optical power of the system is below-22.8 d Bm,while the average power consumption is less than1 m W at a sampling frequency of 10 Hz.Advantages of this scheme in terms of high responsivity,low insertion loss,and low power consumption lend itself to implement the feedback control of advanced large-scale silicon photonic integrated circuits.
基金National Key Research and Development Program of China(2021YFB2800500)Scientific Project of Zhejiang Laboratory(2020LC0AD02)+1 种基金Science and Technology Program of Zhejiang Province(2022C01108)Science and Technology Innovation 2025 Major Project of Ningbo(2020Z021)
文摘We demonstrate a single-chip silicon optical single sideband (OSSB) modulator composed of a radio frequenc(RF) branch line coupler (BLC) and a silicon dual-parallel Mach–Zehnder modulator (DP-MZM).A co-design between the BLC and the DP-MZM is implemented to improve the sideband suppression ratio (SSR).The modu lator has a modulation efficiency of V_(π)L_(π)~1.75 V·cm and a 3 dB electro-optical (EO) bandwidth of 48.7 GHz The BLC can generate a pair of RF signals with equal amplitudes and orthogonal phases at the optimal frequenc of 21 GHz.We prove through theoretical calculation and experiment that,although the BLC’s performance in terms of power balance and phase orthogonality deteriorates in a wider frequency range,high SSRs can be realized by adjusting relevant bias phases of the DP-MZM.With this technique,the undesired sidebands are completel suppressed below the noise floor in the frequency range from 15 GHz to 30 GHz when the chip operates in the ful carrier OSSB (FC-OSSB) mode.In addition,an SSR>35 dB and an carrier suppression ratio (CSR)>42 dB ar demonstrated at 21 GHz in the suppressed carrier OSSB (SC-OSSB) mode.
