A balance of van der Waals, electrostatic, and hydrophobic forces drive the folding and packing of protein side chains. Although such interactions between residues are often approximated as being pairwise additive, in reality, higher-order many-body contributions that depend on environment drive hydrophobic collapse and cooperative electrostatics. Beginning from dead-end elimination, we derive the first algorithm, to our knowledge, capable of deterministic global repacking of side chains compatible with many-body energy functions. The approach is applied to seven PCNA x-ray crystallographic data sets with resolutions 2.5-3.8 Å (mean 3.0 Å) using an open-source software. While PDB_REDO models average an Rfree value of 29.5% and MOLPROBITY score of 2.71 Å (77th percentile), dead-end elimination with the polarizable AMOEBA force field lowered Rfree by 2.8-26.7% and improved mean MOLPROBITY score to atomic resolution at 1.25 Å (100th percentile). For structural biology applications that depend on side-chain repacking, including x-ray refinement, homology modeling, and protein design, the accuracy limitations of pairwise additivity can now be eliminated via polarizable or quantum mechanical potentials.

First principles prediction of the structure, thermodynamics and solubility of organic molecular crystals, which play a central role in chemical, material, pharmaceutical and engineering sciences, challenges both potential energy functions and sampling methodologies. Here we calculate absolute crystal deposition thermodynamics using a novel dual force field approach whose goal is to maintain the accuracy of advanced multipole force fields (e.g. the polarizable AMOEBA model) while performing more than 95% of the sampling in an inexpensive fixed charge (FC) force field (e.g. OPLS-AA). Absolute crystal sublimation/deposition phase transition free energies were determined using an alchemical path that grows the crystalline state from a vapor reference state based on sampling with the OPLS-AA force field, followed by dual force field thermodynamic corrections to change between FC and AMOEBA resolutions at both end states (we denote the three step path as AMOEBA/FC). Importantly, whereas the phase transition requires on the order of 200 nsec of sampling per compound, only 5 nsec of sampling was needed for the dual force field thermodynamic corrections to reach a mean statistical uncertainty of 0.05 kcal/mol. For five organic compounds, the mean unsigned error between direct use of AMOEBA and the AMOEBA/FC dual force field path was only 0.2 kcal/mol and not statistically significant. Compared to experimental deposition thermodynamics, the mean unsigned error for AMOEBA/FC (1.4 kcal/mol) was more than a factor of two smaller than uncorrected OPLS-AA (3.2 kcal/mol). Overall, the dual force field thermodynamic corrections reduced condensed phase sampling in the expensive force field by a factor of 40, and may prove useful for protein stability or binding thermodynamics in the future.

Thole-style mutual induction models for molecular polarization have been adopted by several popular polarizable force fields (FFs) for their simplicity and transferability. The atomic polarizability parameters of these models are typically derived by fitting to ab initio or/and experimental molecular polarizabilities. In this work, we improve upon Thole polarizability parameters by employing both high-level quantum mechanics molecular polarizabilities and electrostatic potential (ESP) responses on threedimensional grids. Our results indicate that the two approaches to derive atomic polarizability parameters are both effective, while the ESP approaches can also capture the polarization for the atoms with lone pair electrons. The resulting polarizability parameters have been validated on a set of over 7200 molecules covering the most common elements found in organic molecules (C, H, O, N, P, S, F, Cl, Br, and I). These parameters have also been tested on the experimentally measured molecular polarizabilities of 422 molecules. The final set of parameters derived in this work show notable improvement over the current AMOEBA set. The result is a highly transferable, expanded set of atomic polarizabilities defined by the local chemical environment in the form of SMARTS patterns. These parameters can be used directly in molecular mechanics polarizable potential energy functions such as AMOEBA, AMOEBA+, and other Thole-style models.

Proliferating cell nuclear antigen (PCNA), a homotrimeric protein, is the eukaryotic sliding clamp that functions as a processivity factor for polymerases during DNA replication. Chromatin association factor 1 (CAF-1) is a heterotrimeric histone chaperone protein that is required for coupling chromatin assembly with DNA replication in eukaryotes. CAF-1 association with replicating DNA, and the targeting of newly synthesized histones to sites of DNA replication and repair requires its interaction with PCNA. Genetic studies have identified three mutant forms of PCNA in yeast that cause defects in gene silencing and exhibit altered association of CAF-1 to chromatin in vivo, as well as inhibit binding to CAF-1 in vitro. Three of these mutant forms of PCNA, encoded by the pol30-6, pol30-8, and the pol30-79 alleles, direct the synthesis of PCNA proteins with the amino acid substitutions D41A/D42A, R61A/D63A, and L126A/I128A, respectively. Interestingly, these double alanine substitutions are located far away from each other within the PCNA protein. To understand the structural basis of the interaction between PCNA and CAF-1 and how disruption of this interaction leads to reduced gene silencing, we determined the X-ray crystal structures of each of these mutant PCNA proteins. All three of the substitutions caused disruptions of a surface cavity on the front face of the PCNA ring, which is formed in part by three loops comprised of residues 21–24, 41–44, and 118–134. We suggest that this cavity is a novel binding pocket required for the interaction between PCNA and CAF-1, and that this region in PCNA also represents a potential binding site for other PCNA-binding proteins.

Hearing loss is associated with $8100 mutations in 152 genes, and within the coding regions of these genes are over 60,000 missense variants. The majority of these variants are classified as ''variants of uncertain significance'' to reflect our inability to ascribe a phenotypic effect to the observed amino acid change. A promising source of pathogenicity information is biophysical simulation, although input protein structures often contain defects because of limitations in experimental data and/or only distant homology to a template. Here, we combine the polarizable atomic multipole optimized energetics for biomolecular applications force field, many-body optimization theory, and graphical processing unit acceleration to repack all deafness-associated proteins and thereby improve average structure MolProbity score from 2.2 to 1.0. We then used these optimized wild-type models to create over 60,000 structures for missense variants in the Deafness Variation Database, which are being incorporated into the Deafness Variation Database to inform deafness pathogenicity prediction. Finally, this work demonstrates that advanced polarizable atomic multipole force fields are efficient enough to repack the entire human proteome.

Hearing loss is associated with ~8100 mutations in 152 genes, and within the coding regions of these genes are over 60,000 missense variants. The majority of these variants are classified as 'variants of uncertain significance' to reflect our inability to ascribe a phenotypic effect to the observed amino acid change. A promising source of pathogenicity information are atomic resolution simulations, although input protein structures often contain defects due to limitations in experimental data and/or only distant homology to a template. Here we combine the polarizable AMOEBA force field, many-body optimization theory and GPU acceleration to repack all deafness-associated proteins and thereby improve average structure resolution from 2.2 Å to 1.0 Å based on assessment with MolProbity. We incorporate these data into the Deafness Variation Database to inform deafness pathogenicity prediction, and show that advanced polarizable force fields could now be used to repack the entire human proteome using the Force Field X software.

In our proof-of-concept study of 1 patient with stage IIIC carcinosarcoma of the ovary, we discovered a rare mutation in the tumor suppressor, TP53, that results in the deletion of N131. Immunofluorescence imaging of the organoid culture revealed hyperstaining of p53 protein. Computational modeling suggests this residue is important for maintaining protein conformation. Drug screening identified the combination of a proteasome inhibitor with a histone deacetylase inhibitor as the most effective treatment. These data provide evidence for the successful culture of a patient tumor and analysis of drug response ex vivo.

Many biological processes are based on molecular recognition between highly charged molecules such as nucleic acids, inorganic ions, charged amino acids, etc. For such cases, it has been demonstrated that molecular simulations with fixed partial charges often fail to achieve experimental accuracy. Although incorporation of more advanced electrostatic models (such as multipoles, mutual polarization, etc.) can significantly improve simulation accuracy, it increases computational expense by a factor of 5–20×. Indirect free energy (IFE) methods can mitigate this cost by modeling intermediate states at fixed-charge resolution. For example, an efficient “reference” model such as a pairwise Amber, CHARMM, or OPLS-AA force field can be used to derive an initial estimate, followed by thermodynamic corrections to a more advanced “target” potential such as the polarizable AMOEBA model. Unfortunately, all currently described IFE methods encounter difficulties reweighting more than ∼50 atoms between resolutions due to extensive scaling of both the magnitude of the thermodynamic corrections and their statistical uncertainty. We present an approach called “simultaneous bookending” (SB) that is fundamentally different from existing IFE methods based on a tunable sampling approximation, which permits scaling to thousands of atoms. SB is demonstrated on the relative binding affinity of Mg2+/Ca2+ to a set of metalloproteins with up to 2972 atoms, finding no statistically significant difference between direct AMOEBA results and those from correcting Amber to AMOEBA. The ability to change the resolution of thousands of atoms during reweighting suggests the approach may be applicable in the future to protein–protein binding affinities or nucleic acid thermodynamics.