Journal of Computational Chemistry

Ovchinnikov, Victor; Karplus, Martin

doi: 10.1002/jcc.27512pmid: 39405551

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 et al. [Science (New York, N.Y.) 2022, 377, 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.

Fan, Qing; Liu, Yingxu; Zhang, Simeng; Ning, Xiangzhen; Xu, Chengcheng; Han, Weijie; Zhang, Yanmin; Chen, Yadong; Shen, Jun; Liu, Haichun

doi: 10.1002/jcc.27538pmid: 39653581

Identifying interactions between drugs and targets is crucial for drug discovery and development. Nevertheless, the determination of drug‐target binding affinities (DTAs) through traditional experimental methods is a time‐consuming process. Conventional approaches to predicting drug‐target interactions (DTIs) frequently prove inadequate due to an insufficient representation of drugs and targets, resulting in ineffective feature capture and questionable interpretability of results. To address these challenges, we introduce CGPDTA, a novel deep learning framework empowered by transfer learning, designed explicitly for the accurate prediction of DTAs. CGPDTA leverages the complementarity of drug–drug and protein–protein interaction knowledge through advanced drug and protein language models. It further enhances predictive capability and interpretability by incorporating molecular substructure graphs and protein pocket sequences to represent local features of drugs and targets effectively. Our findings demonstrate that CGPDTA not only outperforms existing methods in accuracy but also provides meaningful insights into the predictive process, marking a significant advancement in the field of drug discovery.

Patra, Nabajyoti; Gupta, Astha; Bharatam, Prasad V.

doi: 10.1002/jcc.27520pmid: 39476222

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 ΔES‐T 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 ω values indicate that it is possible to fine‐tune the chemical properties of azepinium ions with appropriate modulation.

Chakraborty, Bhrigu; Chattaraj, Pratim Kumar

doi: 10.1002/jcc.27525pmid: 39636032

In this study, we investigated the potential energy surface of BXY3 (X = B, Al, Ga; Y = C, Si, Ge) clusters employing a few global optimization techniques. Remarkably, the global minimum structure obtained for most of the cases revealed a planar tetracoordinate boron atom, shedding light on the inherent stability of this motif. A comparative analysis of the performance of the different global optimization techniques employed is presented, offering insights into their efficacy. Additionally, the overall stability of the obtained global minimum structures is thoroughly examined through Atom‐centered Density Matrix Propagation (ADMP) simulations spanning 20 ps at temperatures 300 and 500 K. The aromaticity of the respective clusters is also assessed via Nucleus Independent Chemical Shift (NICS) and Isochemical Shielding Surface (ICSS) calculations, providing valuable information regarding their electronic structure and stability. This comprehensive theoretical investigation contributes to our understanding of the structural properties of these clusters, with implications for their potential applications in various fields of chemistry.

Oopkaew, Lipika; Injongkol, Yuwanda; Kungwan, Nawee; Rungrotmongkol, Thanyada

doi: 10.1002/jcc.27511pmid: 39644131

Cisplatin (CDDP) is an effective Platinum (Pt) based anticancer drug used in chemotherapy. However, its effectiveness is limited due to its instability in solvents, along with the side effects it causes due to DNA damage. Nanoparticles (NPs) were developed in vitro to address these issues by loading CDDP into various types of NPs, including metal, lipid, and biological NPs. Citrate was employed as a biocompatible compound in nanomedicine to reduce cytotoxicity and enhance stability. In our study, the physicochemical and electronic properties of CDDP and citrate have been investigated using density functional theory (DFT), with a comparison of their behavior in water and DMSO. Additionally, TD‐DFT was applied to analyze the UV–Vis spectra results. Six complexes have been proposed to better understand the interaction between citrate and CDDP. The results demonstrated that the CDDP could form stable complexes with citrate in both water and DMSO, and the considered complexes exhibited UV–Vis spectra within the experiment range. The frontier orbitals, electron densities mapping, and electrostatic potential analysis revealed that complex 5, where citrate di‐substituted on two chlorides, is the most likely and effective complex. In summary, our investigation sheds light on the potential of CDDP‐citrate complexes to address the limitations of CDDP, offering insights into their stability and interaction in solvents and highlighting the promising efficacy of specific complex formations for future therapeutic applications.

Curtis, Kevin; Odoh, Samuel O.

doi: 10.1002/jcc.70006pmid: 39737882

Hydrogen gas (H2) can be produced via entirely solar‐driven photocatalytic water splitting (PWS). A promising set of organic materials for facilitating PWS are the so‐called inverted singlet‐triplet, INVEST, materials. Inversion of the singlet (S1) and triplet (T1) energies reduces the population of triplet states, which are otherwise destructive under photocatalytic conditions. Moreover, when INVEST materials possess dark S1 states, the excited state lifetimes are maximized, facilitating energy transfer to split water. In the context of solar‐driven processes, it is also desirable that these INVEST materials absorb near the solar maximum. Many aza‐triangulenes possess the desired INVEST property, making it beneficial to describe an approach for systematically and efficiently predicting the INVEST property as well as properties that make for efficient photocatalytic water splitting, while exploring the large chemical space of the aza‐triangulenes. Here, we utilize machine learning to generate post hoc corrections to simplified Tamm–Dancoff approximation density functional theory (sTDA‐DFT) for singlet and triplet excitation energies that are within 28–50 meV of second‐order algebraic diagrammatic construction, ADC(2), as well as the singlet‐to‐triplet, ΔES1T1, gaps of PWS systems. Our Δ‐ML model is able to recall 85% of the systems identified by ADC(2) as candidates for PWS. Further, with a modest database of ADC(2) excitation energies of 4025 aza‐triangulenes, we identified 78 molecules suitable for entirely solar‐driven PWS.

Xia, Qiancheng; Fu, Qiuyu; Shen, Cheng; Brenk, Ruth; Huang, Niu

doi: 10.1002/jcc.27516pmid: 39476310

Small molecule conformational sampling plays a pivotal role in molecular docking. Recent advancements have led to the emergence of various conformational sampling methods, each employing distinct algorithms. This study investigates the impact of different small molecule conformational sampling methods in molecular docking using UCSF DOCK 3.7. Specifically, six traditional sampling methods (Omega, BCL::Conf, CCDC Conformer Generator, ConfGenX, Conformator, RDKit ETKDGv3) and a deep learning‐based model (Torsional Diffusion) for generating conformational ensembles are evaluated. These ensembles are subsequently docked against the Platinum Diverse Dataset, the PoseBusters dataset and the DUDE‐Z dataset to assess binding pose reproducibility and screening power. Notably, different sampling methods exhibit varying performance due to their unique preferences, such as dihedral angle sampling ranges on rotatable bonds. Combining complementary methods may lead to further improvements in docking performance.

Pomogaeva, Anna V.; Lisovenko, Anna S.; Timoshkin, Alexey Y.

doi: 10.1002/jcc.27549pmid: 39670418

In the framework of SMD approach a systematic computational study of structural, electronic and thermodynamic properties of molecular complexes of Cl2, ICl and I2 with series of N‐containing Lewis bases in solvents of different polarity was carried out. Results indicate that molecular complexes of Cl2 with strong and medium‐strong LB undergo spontaneous ionization in the acetonitrile solution. The increase of the solvent polarity can change the nature of interaction in X'XLB systems from molecular X'X ← LB donor‐acceptor complexes to 3‐center 4‐electron bound X'→X+ ← LB in solvents of medium polarity and to the contact ion pairs X'→[XLB]+ in polar solvents. Thus, the controlled generation of cationic [LB∙X]+ species is possible by varying the nature of LB, varying the nature of the solvent, and varying the nature of the halogen X. Molecular Cl2 has the greatest tendency to form ionic species in polar solvents. Spontaneous ionization of molecular nσ complexes of chlorine with strong LB in medium‐polar solvents (starting from OEt2, ε = 4.24) should not be neglected and single point solvation energy computations on gas phase optimized geometries are not reliable for such systems.

Romeu, João Gabriel Farias; Ornellas, Fernando R.

doi: 10.1002/jcc.27530pmid: 39754406

Seventeen electronic states of the dication VH2+ were characterized by the SA‐CASSCF/icMRCI methodology using very extended basis sets; 11 were described for the first time. Potential energy curves were constructed and the associated spectroscopic parameters evaluated. Triplet and quintet states correlating with the V2+ + H channel are thermodynamic stable. For states dissociating into the channel V+ + H+, avoided crossings at large distances give rise to thermodynamic metastability but do not affect the characterization of the bound region. Configuration state functions with the 3σ orbital /doubly occupied give rise to covalent contributions to the bonding; the major contribution, however, comes from the electrostatic charge‐induced dipole interaction. This explains the shape and proximity of the potential energy curves beyond their equilibrium distances. Dipole moment functions and vibrationally averaged dipole moments quantify the polarity of the molecule. Spin–orbit couplings give rise to complex and dense regions of very close‐lying Ω states.

Lai, Rui; Li, Hui

doi: 10.1002/jcc.27544pmid: 39636155

The New Delhi metallo‐β‐lactamase 1 (NDM‐1) can hydrolyze nearly all clinically important β‐lactam antibiotics, narrowing the options for effective treatment of bacterial infections. QM/MM MP2 calculations are performed to reveal the mechanism of ampicillin hydrolysis catalyzed by NDM‐1. It is found that the rate‐determining step is the dissociation of hydrolyzed ampicillin from the NDM‐1 active site, which requires a proton transfer from the bridging neutral water molecule to the newly formed carboxylate group. The precedent reaction steps, including the hydroxide nucleophilic addition, CN bond cleavage, and the protonation of the negative lactam N atom by a solvent water molecule, all require insignificant activation free energies. The calculated activation free energy for this rate‐determining proton transfer step is 16.0 kcal/mol, in good agreement with experimental values of 13.7 ~ 14.7 kcal/mol. This proton transfer step exhibits a solvent hydrogen‐deuterium kinetic isotope effect of 3.4, consistent with several experimental kinetic results.