{"title":"Stable, aromatic, and electrophilic azepinium ions: Design using quantum chemical methods","authors":"Nabajyoti Patra, Astha Gupta, Prasad V. Bharatam","doi":"10.1002/jcc.27520","DOIUrl":"https://doi.org/10.1002/jcc.27520","url":null,"abstract":"Cyclic nitrenium ions containing five-membered and six-membered rings are available, however, the seven-membered cyclic nitrenium ions (azepinium ions) are rare. The chemistry of these species is related to their stability originating from the aromaticity due to 6π electrons. Very few theoretical and experimental studies have been conducted on the azepinium ions. Related clozapine and olanzapine cations (diazepinium ions) were observed during drug metabolism studies. In this work, quantum chemical analysis has been carried out to estimate the stability, aromaticity, and electrophilicity of several derivatives of azepinium ions. A few of the designed azepinium ions carry Δ<i>E</i><sub>S-T</sub> values in the range of 50 kcal/mol favoring singlet state; π donating groups at the 2nd position increase the singlet-triplet energy differences. Most of the substituents reduce the NICS(1) values compared to the parent system. Ring fusion with heterocyclic five-membered rings generally increases the aromaticity and the stability of the azepinium ion ring systems. The electrophilicity parameters estimated in terms of HIA, FIA, and <i>ω</i> values indicate that it is possible to fine-tune the chemical properties of azepinium ions with appropriate modulation.","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"111 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142541462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shailesh Kumar Panday, Arghya Chakravorty, Shan Zhao, Emil Alexov
{"title":"On delivering polar solvation free energy of proteins from energy minimized structures using a regularized super-Gaussian Poisson–Boltzmann model","authors":"Shailesh Kumar Panday, Arghya Chakravorty, Shan Zhao, Emil Alexov","doi":"10.1002/jcc.27496","DOIUrl":"10.1002/jcc.27496","url":null,"abstract":"<p>The biomolecules interact with their partners in an aqueous media; thus, their solvation energy is an important thermodynamics quantity. In previous works (<i>J. Chem. Theory Comput. 14</i>(2): 1020–1032), we demonstrated that the Poisson–Boltzmann (PB) approach reproduces solvation energy calculated via thermodynamic integration (TI) protocol if the structures of proteins are kept rigid. However, proteins are not rigid bodies and computing their solvation energy must account for their flexibility. Typically, in the framework of PB calculations, this is done by collecting snapshots from molecular dynamics (MD) simulations, computing their solvation energies, and averaging to obtain the ensemble-averaged solvation energy, which is computationally demanding. To reduce the computational cost, we have proposed Gaussian/super-Gaussian-based methods for the dielectric function that use the atomic packing to deliver smooth dielectric function for the entire computational space, the protein and water phase, which allows the ensemble-averaged solvation energy to be computed from a single structure. One of the technical difficulties associated with the smooth dielectric function presentation with respect to polar solvation energy is the absence of a dielectric border between the protein and water where induced charges should be positioned. This motivated the present work, where we report a super-Gaussian regularized Poisson–Boltzmann method and use it for computing the polar solvation energy from single energy minimized structures and assess its ability to reproduce the ensemble-averaged polar solvation on a dataset of 74 high-resolution monomeric proteins.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"46 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcc.27496","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142542366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dušan Ćoćić, Liu Yang, Ralph Puchta, Tiesheng Shi, Rudi van Eldik
{"title":"Investigation of the complete encapsulation process of the noble gases by cryptophanes","authors":"Dušan Ćoćić, Liu Yang, Ralph Puchta, Tiesheng Shi, Rudi van Eldik","doi":"10.1002/jcc.27519","DOIUrl":"https://doi.org/10.1002/jcc.27519","url":null,"abstract":"Based on DFT calculations (ωB97XD/def2‐SVP/SVPfit), the ability and mechanism of noble gas encapsulation by series of cryptophanes were investigated. The focus was set to study the influence of different functionalization groups placed at the “gates” of cryptophanes cavity entrance by which the energy criteria were chosen as a main indicator for selective encapsulation of noble gases. Chosen functionalization groups were CH<jats:sub>3</jats:sub>, OCH<jats:sub>3</jats:sub>, OH, NH<jats:sub>2</jats:sub>, and Cl, and the encapsulation process of these cryptophanes was compared to a cryptophane without any functionalization group on its outer rim. Those groups were selected based on their different chemical properties and based on their size which will subsequently put additional steric restrictions on the cavity entrance. Chosen functionalization groups, beside their steric influence on the energy barrier magnitude, influence also the gating process through its chemical nature by which they can put an additional stabilization on noble gases encapsulation transition states enhancing the encapsulation process. Objective of this study was clearly to get better insights on the influence of those functional groups on the whole encapsulation process of noble gases. Large‐size noble gases (Xe and Rn) from all noble gases are best accommodated in the cavities of selected cryptophanes, on the other hand these noble gases require to pass the highest energy barrier through the gating process. From the series of investigated cryptophanes, the cryptophane with the OCH<jats:sub>3</jats:sub> functionalization group has been identified as the one with the best capabilities to host investigated noble gases, but on the other side this cryptophane puts the highest energy criteria required for the previous gating process.","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"1 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142490530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Pre-training strategy for antiviral drug screening with low-data graph neural network: A case study in HIV-1 K103N reverse transcriptase.","authors":"Kajjana Boonpalit, Hathaichanok Chuntakaruk, Jiramet Kinchagawat, Peter Wolschann, Supot Hannongbua, Thanyada Rungrotmongkol, Sarana Nutanong","doi":"10.1002/jcc.27514","DOIUrl":"https://doi.org/10.1002/jcc.27514","url":null,"abstract":"<p><p>Graph neural networks (GNN) offer an alternative approach to boost the screening effectiveness in drug discovery. However, their efficacy is often hindered by limited datasets. To address this limitation, we introduced a robust GNN training framework, applied to various chemical databases to identify potent non-nucleoside reverse transcriptase inhibitors (NNRTIs) against the challenging K103N-mutated HIV-1 RT. Leveraging self-supervised learning (SSL) pre-training to tackle data scarcity, we screened 1,824,367 compounds, using multi-step approach that incorporated machine learning (ML)-based screening, analysis of absorption, distribution, metabolism, and excretion (ADME) prediction, drug-likeness properties, and molecular docking. Ultimately, 45 compounds were left as potential candidates with 17 of the compounds were previously identified as NNRTIs, exemplifying the model's efficacy. The remaining 28 compounds are anticipated to be repurposed for new uses. Molecular dynamics (MD) simulations on repurposed candidates unveiled two promising preclinical drugs: one designed against Plasmodium falciparum and the other serving as an antibacterial agent. Both have superior binding affinity compared to anti-HIV drugs. This conceptual framework could be adapted for other disease-specific therapeutics, facilitating the identification of potent compounds effective against both WT and mutants while revealing novel scaffolds for drug design and discovery.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142454269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Fragment and torsion biasing algorithms for construction of small organic molecules in proteins using DOCK","authors":"John D. Bickel, Brock T. Boysan, Robert C. Rizzo","doi":"10.1002/jcc.27508","DOIUrl":"10.1002/jcc.27508","url":null,"abstract":"<p>The computational construction of small organic molecules (de novo design), directly in a protein binding site, is an effective means for generating novel ligands tailored to fit the pocket environment. In this work, we present two new methods, which aim to improve de novo design outcomes using (1) biasing algorithms to prioritize selection and/or acceptance of fragments and torsions during growth, and (2) parallel-based clustering and pruning algorithms to remove duplicate molecules as candidate fragment are added. Large-scale testing encompassing thousands of simulations were employed to interrogate the methods in terms of multiple metrics which include numbers of duplicate molecules generated, pairwise-similarity, focused library reconstruction rates, fragment and torsion frequencies, fragment and torsion rank scores, interaction energy and drug-likeness scores, and 3D pose comparisons. The biasing algorithms, particularly those that include fragment and torsion components simultaneously, led to molecules that more closely mimicked the distributions of fragments and torsions found in drug-like libraries. The new parallel-based clustering and pruning algorithms, compared with the existing serial approach, also led to larger ensembles comprised of topologically unique molecules with much greater efficiency by removing redundant growth paths.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"46 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142487388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Piotr Matczak, Philipp Buday, Stephan Kupfer, Helmar Görls, Grzegorz Mlostoń, Wolfgang Weigand
{"title":"Probing the performance of DFT in the structural characterization of [FeFe] hydrogenase models","authors":"Piotr Matczak, Philipp Buday, Stephan Kupfer, Helmar Görls, Grzegorz Mlostoń, Wolfgang Weigand","doi":"10.1002/jcc.27515","DOIUrl":"https://doi.org/10.1002/jcc.27515","url":null,"abstract":"In this work, a series of DFT and DFT-D methods is combined with double-<i>ζ</i> basis sets to benchmark their performance in predicting the structures of five newly synthesized hexacarbonyl diiron complexes with a bridging ligand featuring a <i>μ</i>-S<sub>2</sub>C<sub>3</sub> motif in a ring-containing unit functionalized with aromatic groups. Such complexes have been considered as [FeFe] hydrogenase catalytic site models with potential for eco-friendly energetic applications. According to this assessment, r<sup>2</sup>SCAN is identified as the density functional recommended for the reliable description of the molecular and crystal structures of the herein studied models. However, the butterfly (<i>μ</i>-S)<sub>2</sub>Fe<sub>2</sub> core of the models demonstrates a minor deformation of its optimized geometry obtained from both molecular and periodic calculations. The Fe<span></span>Fe bond length is slightly underestimated while the Fe<span></span>S bonds tend to be too long. Adding the D3(BJ) correction to r<sup>2</sup>SCAN does not lead to any improvement in the calculated structures.","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"24 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142444366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"High‐throughput molecular simulations of SARS‐CoV‐2 receptor binding domain mutants quantify correlations between dynamic fluctuations and protein expression","authors":"Victor Ovchinnikov, Martin Karplus","doi":"10.1002/jcc.27512","DOIUrl":"https://doi.org/10.1002/jcc.27512","url":null,"abstract":"Prediction of protein fitness from computational modeling is an area of active research in rational protein design. Here, we investigated whether protein fluctuations computed from molecular dynamics simulations can be used to predict the expression levels of SARS‐CoV‐2 receptor binding domain (RBD) mutants determined in the deep mutational scanning experiment of Starr <jats:italic>et al.</jats:italic> [<jats:italic>Science</jats:italic> (New York, N.Y.) 2022, <jats:italic>377</jats:italic>, 420] Specifically, we performed more than 0.7 milliseconds of molecular dynamics (MD) simulations of 557 mutant RBDs in triplicate to achieve statistical significance under various simulation conditions. Our results show modest but significant anticorrelation in the range [−0.4, −0.3] between expression and RBD protein flexibility. A simple linear regression machine learning model achieved correlation coefficients in the range [0.7, 0.8], thus outperforming MD‐based models, but required about 25 mutations at each residue position for training.","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"1 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142440004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An ANI-2 enabled open-source protocol to estimate ligand strain after docking","authors":"Francois Berenger, Koji Tsuda","doi":"10.1002/jcc.27478","DOIUrl":"10.1002/jcc.27478","url":null,"abstract":"<p>In protein-ligand docking, the score assigned to a protein-ligand complex is approximate. Especially, the internal energy of the ligand is difficult to compute precisely using a molecular mechanics based force-field, introducing significant noise in the rank-ordering of ligands. We propose an open-source protocol (https://github.com/UnixJunkie/MMO), using two quantum mechanics (QM) single point energy calculations, plus a Monte Carlo (Monte Carlo) based ligand minimization procedure in-between, to estimate ligand strain after docking. The MC simulation uses the ANI-2x (QM approximating) force field and is performed in the dihedral space. On some protein targets, using strain filtering after docking allows to significantly improve hit rates. We performed a structure-based virtual screening campaign on nine protein targets from the Laboratoire d'Innovation Thérapeutique—PubChem assays dataset using Cambridge crystallographic data centre genetic optimization for ligand docking. Then, docked ligands were submitted to the strain estimation protocol and the impact on hit rate was analyzed. As for docking, the method does not always work. However, if sufficient active and inactive molecules are known for a given protein target, its efficiency can be evaluated.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"46 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcc.27478","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142377462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Fluxional halogen bonds in linear complexes of tetrafluorodiiodobenzene with dinitrobenzene","authors":"Cai-Yue Gao, Bin-Bin Pei, Si-Dian Li","doi":"10.1002/jcc.27483","DOIUrl":"10.1002/jcc.27483","url":null,"abstract":"<p>The fluxional nature of halogen bonds (XBs) in small molecular clusters, supramolecules, and molecular crystals has received considerable attention in recent years. In this work, based on extensive density-functional theory calculations and detailed electrostatic potential (ESP), natural bonding orbital (NBO), non-covalent interactions-reduced density gradient (NCI-RDG), and quantum theory of atoms in molecules (QTAIM) analyses, we unveil the existence of fluxional halogen bonds (FXBs) in a series of linear (IC<sub>6</sub>F<sub>4</sub>I)<sub><i>m</i></sub>(OONC<sub>6</sub>H<sub>4</sub>NOO)<sub><i>n</i></sub> (<i>m</i> + <i>n</i> = 2–5) complexes of tetrafluorodiiodobenzene with dinitrobenzene which appear to be similar to the previously reported fluxional hydrogen bonds (FHBs) in small water clusters (H<sub>2</sub>O)<sub><i>n</i></sub> (<i>n</i> = 2–6). The obtained <span></span><math>\u0000 <mrow>\u0000 <mi>GS</mi>\u0000 <mo>⇌</mo>\u0000 <mi>TS</mi>\u0000 <mo>⇌</mo>\u0000 <msup>\u0000 <mi>GS</mi>\u0000 <mo>'</mo>\u0000 </msup>\u0000 </mrow></math> fluxional mechanisms involve one FXB in the systems which fluctuates reversibly between two linear C<span></span>I···O XBs in the ground states (GS and GS') via a bifurcated C<span></span>I O<sub>2</sub>N van der Waals interaction in the transition state (TS). The cohesive energies (<i>E</i><sub>coh</sub>) of these complexes with up to four XBs exhibit an almost perfect linear relationship with the numbers of XBs in the systems, with the average calculated halogen bond energy of <i>E</i><sub>coh/XB</sub> = 3.48 kcal·mol<sup>−1</sup> in the ground states which appears to be about 55% of the average calculated hydrogen bond energy (<i>E</i><sub>coh/HB</sub> = 6.28 kcal·mol<sup>−1</sup>) in small water clusters.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"46 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142337873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Theoretical design of new ligands to boost reaction rate and selectivity in palladium-catalyzed aromatic fluorination.","authors":"Josefredo R Pliego","doi":"10.1002/jcc.27513","DOIUrl":"https://doi.org/10.1002/jcc.27513","url":null,"abstract":"<p><p>The development of palladium-catalyzed fluorination with biaryl monophosphine ligands has faced two important problems that limit its application for bromoarenes: the formation of regioisomers and insufficient catalysis for heteroaryl substrates as bromothiophene derivatives. Overcoming these problems requires more ligand design. In this work, reliable theoretical calculations were used to elucidate important ligand features necessary for achieving more rate acceleration and selectivity. These features include increasing the ligand-substrate repulsion and creating a negative charge in the space around the fluoride ion bonded to the palladium. The investigated L5 ligand presents these features, and the calculations predict that this ligand completely suppresses the regioisomer formation in the difficult case of 4-bromoanisole. In addition, the free energy barriers are decreased by 2-3 kcal mol<sup>-1</sup> in comparison with the catalysis involving the AlPhos ligand. Thus, the present study points out a direction for new developments in palladium-catalyzed fluorination.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142337874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}