Masahiko Taguchi

OaPAC, from Oscillatoria acuminata , is a homodimer protein consisting of the blue‐light using flavin domain and the adenylyl cyclase (AC) domain, linked by long coiled‐coil α3‐helices. Upon blue‐light absorption, a rearrangement of the hydrogen‐bonding network involving the flavin chromophore, Y6, and Q48 triggers signal propagation through the α3‐helices to the AC domain. While the recent crystallographic structure of the W90–M92‐switched conformation in the light state provided significant structural information, the underlying atomistic mechanism of signal transduction remains unclear. In this study, we performed molecular dynamics simulations of OaPAC for four models: wild‐type (WT) dark state, W90–M92 unswitched WT light state, W90–M92 switched WT light state, and W90–M92 unswitched L111A/L115A light state. Our results show that the switched WT light‐state model exhibits structural fluctuation approximately twice as large as that in the unswitched WT light state. Furthermore, we identified a pronounced transition between two distinct conformational states in the switched WT light—“open” and “closed” —characterized by the angle between the α3‐helices and the “handle” region. Notably, the occupancy of the closed conformation was highest in the switched WT light state. In contrast, the non‐functional L111A/L115A mutant remained trapped in a rigid open conformation, reflecting its loss of activity and linking structural flexibility to enzymatic competence. These findings suggest that the W90–M92 conformational switch is a critical, multi‐step trigger of OaPAC signal transduction, inducing a transient asymmetric (open–closed) conformation and a flexion motion that may facilitate enzymatic activation. This study would provide key atomistic insights for the rational design of advanced optogenetic actuators.

A human immunodeficiency virus-1 (HIV-1) protease is a homodimeric aspartic protease essential for the replication of HIV. The HIV-1 protease is a target protein in drug discovery for antiretroviral therapy, and various inhibitor molecules of transition state analogues have been developed. However, serious drug-resistant mutants have emerged. For understanding the molecular mechanism of the drug resistance, an accurate examination of the impacts of the mutations on ligand binding and enzymatic activity is necessary. Here, we present a molecular simulation study on the ligand binding of indinavir, a potent transition state analogue inhibitor, to the wild-type protein and a V82T/I84V drug-resistant mutant of the HIV-1 protease. We employed a hybrid ab initio quantum mechanical/molecular mechanical (QM/MM) free-energy optimization technique which combines a highly accurate QM description of the ligand molecule and its interaction with statistically ample conformational sampling of the MM protein environment by long-time molecular dynamics simulations. Through the free-energy calculations of protonation states of catalytic groups at the binding pocket and of the ligand-binding affinity changes upon the mutations, we successfully reproduced the experimentally observed significant reduction of the binding affinity upon the drug-resistant mutations and elucidated the underlying molecular mechanism. The present study opens the way for understanding the molecular mechanism of drug resistance through the direct quantitative comparison of ligand binding and enzymatic reaction with the same accuracy.

Human immunodeficiency virus 1 (HIV-1) protease is a homo-dimeric aspartic protease essential for replication of HIV. The HIV-1 protease is a target protein in drug discovery for antiretroviral therapy, and various inhibitor molecules of transition state analog were developed. However, serious drug-resistant mutants have emerged. For understanding molecular mechanism of the drug-resistance, accurate examination of the impacts of the mutations on ligand binding as well as enzymatic activity is necessary. Here, we present a molecular simulation study on the ligand binding of Indinavir, a potent transition state analog inhibitor, to the native protein and a V82T/I84V drug-resistant mutant of HIV-1 protease. We employed a hybrid ab initio quantum mechanical/molecular mechanical (QM/MM) free energy optimization technique which combines highly accurate QM description of the ligand molecule and its interaction with statistically ample conformational sampling of MM protein environment by long-time molecular dynamics simulations. Through free energy calculations of protonation states of catalytic groups at the binding pocket and of ligand binding affinity changes upon the mutations, we successfully reproduced the experimentally observed significant reduction of the binding affinity upon the drug-resistant mutations and elucidated the underlying molecular mechanism. The present study opens the way for understanding the molecular mechanism of drug-resistance through direct quantitative comparison of ligand binding and enzymatic reaction with the same accuracy.

Hepatocyte nuclear factor 1A (HNF1A) is the master regulator of liver homeostasis and organogenesis and regulates many aspects of hepatocyte functions. It acts as a tumor suppressor in the liver, evidenced by the increased proliferation in HNF1A knockout (KO) hepatocytes. Hence, we postulated that any loss-of-function variation in the gene structure or composition (mutation) could trigger dysfunction, including disrupted transcriptional networks in liver cells. From the International Cancer Genome Consortium (ICGC) database of cancer genomes, we identified several HNF1A mutations located in the functional Pit-Oct-Unc (POU) domain. In our biochemical analysis, we found that the HNF1A POU-domain mutations Y122C, R229Q and V259F suppressed HNF4A promoter activity and disrupted the binding of HNF1A to its target HNF4A promoter without any effect on the nuclear localization. Our results suggest that the decreased transcriptional activity of HNF1A mutants is due to impaired DNA binding. Through structural simulation analysis, we found that a V259F mutation was likely to affect DNA interaction by inducing large conformational changes in the N-terminal region of HNF1A. The results suggest that POU-domain mutations of HNF1A downregulate HNF4A gene expression. Therefore, to mimic the HNF1A mutation phenotype in transcription networks, we performed siRNA-mediated knockdown (KD) of HNF4A. Through RNA-Seq data analysis for the HNF4A KD, we found 748 differentially expressed genes (DEGs), of which 311 genes were downregulated (e.g., HNF1A, ApoB and SOAT2) and 437 genes were upregulated. Kyoto Encyclopedia of Genes and Genomes (KEGG) mapping revealed that the DEGs were involved in several signaling pathways (e.g., lipid and cholesterol metabolic pathways). Protein–protein network analysis suggested that the downregulated genes were related to lipid and cholesterol metabolism pathways, which are implicated in hepatocellular carcinoma (HCC) development. Our study demonstrates that mutations of HNF1A in the POU domain result in the downregulation of HNF1A target genes, including HNF4A, and this may trigger HCC development through the disruption of HNF4A–HNF1A transcriptional networks.

Human immunodeficiency virus 1 (HIV-1) protease is a homo-dimeric aspartic protease essential for replication of HIV. The HIV-1 protease is a target protein in drug discovery for antiretroviral therapy, and various inhibitor molecules of transition state analog were developed. However, serious drug-resistant mutants have emerged. For understanding molecular mechanism of the drug-resistance, accurate examination of the impacts of the mutations on ligand binding as well as enzymatic activity is necessary. Here, we present a molecular simulation study on the ligand binding of Indinavir, a potent transition state analog inhibitor, to the native protein and a V82T/I84V drug-resistant mutant of HIV-1 protease. We employed a hybrid ab initio quantum mechanical/molecular mechanical (QM/MM) free energy optimization technique which combines highly accurate QM description of the ligand molecule and its interaction with statistically ample conformational sampling of MM protein environment by long-time molecular dynamics simulations. Through free energy calculations of protonation states of catalytic groups at the binding pocket and of ligand binding affinity changes upon the mutations, we successfully reproduced the experimentally observed significant reduction of the binding affinity upon the drug-resistant mutations and elucidated the underlying molecular mechanism. The present study opens the way for understanding the molecular mechanism of drug-resistance through direct quantitative comparison of ligand binding and enzymatic reaction with the same accuracy.

Human immunodeficiency virus 1 (HIV-1) protease is a homo-dimeric aspartic protease essential for replication of HIV. The HIV-1 protease is a target protein in drug discovery for antiretroviral therapy, and various inhibitor molecules of transition state analog were developed. However, serious drug-resistant mutants have emerged. For understanding molecular mechanism of the drug-resistance, accurate examination of the impacts of the mutations on ligand binding as well as enzymatic activity is necessary. Here, we present a molecular simulation study on the ligand binding of Indinavir, a potent transition state analog inhibitor, to the native protein and a V82T/I84V drug-resistant mutant of HIV-1 protease. We employed a hybrid ab initio quantum mechanical/molecular mechanical (QM/MM) free energy optimization technique which combines highly accurate QM description of the ligand molecule and its interaction with statistically ample conformational sampling of MM protein environment by long-time molecular dynamics simulations. Through free energy calculations of protonation states of catalytic groups at the binding pocket and of ligand binding affinity changes upon the mutations, we successfully reproduced the experimentally observed significant reduction of the binding affinity upon the drug-resistant mutations and elucidated the underlying molecular mechanism. The present study opens the way for understanding the molecular mechanism of drug-resistance through direct quantitative comparison of ligand binding and enzymatic reaction with the same accuracy.