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Accurate potential energy models are necessary for reliable atomistic simulations of chemical phenomena. In the realm of biomolecular modeling, large systems like proteins comprise very many noncovalent interactions (NCIs) that can contribute to the protein's stability and structure. This work presents two high-quality chemical databases of common fragment interactions in biomolecular systems as extracted from high-resolution Protein DataBank crystal structures: 3380 sidechain-sidechain interactions and 100 backbone-backbone interactions that inaugurate the BioFragment Database (BFDb). Absolute interaction energies are generated with a computationally tractable explicitly correlated coupled cluster with perturbative triples [CCSD(T)-F12] "silver standard" (0.05 kcal/mol average error) for NCI that demands only a fraction of the cost of the conventional "gold standard," CCSD(T) at the complete basis set limit. By sampling extensively from biological environments, BFDb spans the natural diversity of protein NCI motifs and orientations. In addition to supplying a thorough assessment for lower scaling force-field (2), semi-empirical (3), density functional (244), and wavefunction (45) methods (comprising >1M interaction energies), BFDb provides interactive tools for running and manipulating the resulting large datasets and offers a valuable resource for potential energy model development and validation. [ABSTRACT FROM AUTHOR]

Highlights: [•] Reliable simulations of biomolecules depend on the accuracy of potential functions. [•] Potential function errors propagate and increase with system size. [•] We propose a statistics-based method for estimating potential model uncertainties. [•] Conformational sampling naturally diminishes errors in free energy. [ABSTRACT FROM AUTHOR]

The routine prediction of three-dimensional protein structure from sequence remains a challenge in computational biochemistry. It has been intuited that calculated energies from physics-based scoring functions are able to distinguish native from nonnative folds based on previous performance with small proteins and that conformational sampling is the fundamental bottleneck to successful folding. We demonstrate that as protein size increases, errors in the computed energies become a significant problem. We show, by using error probability density functions, that physics-based scores contain significant systematic and random errors relative to accurate reference energies. These errors propagate throughout an entire protein and distort its energy landscape to such an extent that modern scoring functions should have little chance of success in finding the free energy minima of large proteins. Nonetheless, by understanding errors in physics-based score functions, they can be reduced in a post-hoc manner, improving accuracy in energy computation and fold discrimination. [ABSTRACT FROM AUTHOR]

An energy expansion (binding energy decomposition into n-body interaction terms for n ≥ 2) to express the receptor-ligand binding energy for the fragmented HIV II protease-Indinavir system is described to address the role of cooperativity in ligand binding. The outcome of this energy expansion is compared to the total receptor-ligand binding energy at the Hartree-Fock, density functional theory, and semiempirical levels of theory. We find that the sum of the pairwise interaction energies approximates the total binding energy to ∼82% for HF and to >95% for both the M06-L density functional and PM6-DH2 semiempirical method. The contribution of the three-body interactions amounts to 18.7%, 3.8%, and 1.4% for HF, M06-L, and PM6-DH2, respectively. We find that the expansion can be safely truncated after n = 3. That is, the contribution of the interactions involving more than three parties to the total binding energy of Indinavir to the HIV II protease receptor is negligible. Overall, we find that the two-body terms represent a good approximation to the total binding energy of the system, which points to pairwise additivity in the present case. This basic principle of pairwise additivity is utilized in fragment-based drug design approaches and our results support its continued use. The present results can also aid in the validation of non-bonded terms contained within common force fields and in the correction of systematic errors in physics-based score functions. [ABSTRACT FROM AUTHOR]

The development of SARS-CoV-2 main protease (Mpro) inhibitors for the treatment of COVID-19 has mostly benefitted from X-ray structures and preexisting knowledge of inhibitors; however, an efficient method to generate Mpro inhibitors, which circumvents such information would be advantageous. As an alternative approach, we show here that DNA-encoded chemistry technology (DEC-Tec) can be used to discover inhibitors of Mpro. An affinity selection of a 4-billion-membered DNA-encoded chemical library (DECL) using Mpro as bait produces novel non-covalent and non-peptide-based small molecule inhibitors of Mpro with low nanomolar Ki values. Furthermore, these compounds demonstrate efficacy against mutant forms of Mpro that have shown resistance to the standard-of-care drug nirmatrelvir. Overall, this work demonstrates that DEC-Tec can efficiently generate novel and potent inhibitors without preliminary chemical or structural information. Conventional structure-based design of Mpro inhibitors of SARS-CoV-2 often starts from the structural information of Mpro and their binders; however, the continual rise of resistant strains requires innovative routes to discover new inhibitors. Here, the authors develop a DNA-encoded chemical library screening to produce non-covalent, non-peptidic small molecule inhibitors for SARS-CoV-2 Mpro independently of preliminary knowledge regarding suitable starting points. [ABSTRACT FROM AUTHOR]

BRDT, BRD2, BRD3, and BRD4 comprise the bromodomain and extraterminal (BET) subfamily which contain two similar tandem bromodomains (BD1 and BD2). Selective BD1 inhibition phenocopies effects of tandem BET BD inhibition both in cancer models and, as we and others have reported of BRDT, in the testes. To find novel BET BD1 binders, we screened >4.5 billion molecules from our DNA-encoded chemical libraries with BRDT-BD1 or BRDT-BD2 proteins in parallel. A compound series enriched only by BRDT-BD1 was resynthesized off-DNA, uncovering a potent chiral compound, CDD-724, with >2,000-fold selectivity for inhibiting BRDT-BD1 over BRDT-BD2. CDD-724 stereoisomers exhibited remarkable differences in inhibiting BRDT-BD1, with the R-enantiomer (CDD-787) being 50-fold more potent than the S-enantiomer (CDD-786). From structure-activity relationship studies, we produced CDD-956, which maintained picomolar BET BD1 binding potency and high selectivity over BET BD2 proteins and had improved stability in human liver microsomes over CDD-787. BROMOscaw profiling confirmed the excellent pan-BET BD1 affinity and selectivity of CDD-787 and CDD-956 on BD1 versus BD2 and all other BD-containing proteins. A cocrystal structure of BRDT-BD1 bound with CDD-956 was determined at 1.82 Å and revealed BRDT-BD1-specific contacts with the αZ and αC helices that explain the high affinity and selectivity for BET BD1 versus BD2. CDD-787 and CDD-956 maintain cellular BD1-selectivity in NanoBRET assays and show potent antileukemic activity in acute myeloid leukemia cell lines. These BET BD1-specific and highly potent compounds are structurally unique and provide insight into the importance of chirality to achieve BET specificity. [ABSTRACT FROM AUTHOR]

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has killed more than 4 million humans globally, but there is no bona fide Food and Drug Administration-approved drug-like molecule to impede the COVID-19 pandemic. The sluggish pace of traditional therapeutic discovery is poorly suited to producing targeted treatments against rapidly evolving viruses. Here, we used an affinity-based screen of 4 billion DNA-encoded molecules en masse to identify a potent class of virus-specific inhibitors of the SARS-CoV-2 main protease (Mpro) without extensive and time-consuming medicinal chemistry. CDD-1714, the initial three-building-block screening hit (molecular weight [MW] = 542.5 g/mol), was a potent inhibitor (inhibition constant [Ki] = 20 nM). CDD-1713, a smaller two-building-block analog (MW = 353.3 g/mol) of CDD-1714, is a reversible covalent inhibitor of Mpro (Ki = 45 nM) that binds in the protease pocket, has specificity over human proteases, and shows in vitro efficacy in a SARS-CoV-2 infectivity model. Subsequently, key regions of CDD-1713 that were necessary for inhibitory activity were identified and a potent (Ki = 37 nM), smaller (MW = 323.4 g/mol), and metabolically more stable analog (CDD-1976) was generated. Thus, screening of DNA-encoded chemical libraries can accelerate the discovery of efficacious drug-like inhibitors of emerging viral disease targets. [ABSTRACT FROM AUTHOR]

Bromodomain testis (BRDT), a member of the bromodomain and extraterminal (BET) subfamily that includes the cancer targets BRD2, BRD3, and BRD4, is a validated contraceptive target. All BET subfamily members have two tandem bromodomains (BD1 and BD2). Knockout mice lacking BRDT-BD1 or both bromodomains are infertile. Treatment of mice with JQ1, a BET BD1/BD2 nonselective inhibitor with the highest affinity for BRD4, disrupts spermatogenesis and reduces sperm number and motility. To assess the contribution of each BRDT bromodomain, we screened our collection of DNA-encoded chemical libraries for BRDT-BD1 and BRDT-BD2 binders. High-enrichment hits were identified and resynthesized off-DNA and examined for their ability to compete with JQ1 in BRDT and BRD4 bromodomain AlphaScreen assays. These studies identified CDD-1102 as a selective BRDT-BD2 inhibitor with low nanomolar potency and >1,000-fold selectivity over BRDT-BD1. Structure-activity relationship studies of CDD-1102 produced a series of additional BRDT-BD2/BRD4-BD2 selective inhibitors, including CDD-1302, a truncated analog of CDD-1102 with similar activity, and CDD-1349, an analog with sixfold selectivity for BRDT-BD2 versus BRD4-BD2. BROMOscan bromodomain profiling confirmed the great affinity and selectivity of CDD-1102 and CDD-1302 on all BET BD2 versus BD1 with the highest affinity for BRDT-BD2. Cocrystals of BRDT-BD2 with CDD-1102 and CDD-1302 were determined at 2.27 and 1.90 Å resolution, respectively, and revealed BRDT-BD2 specific contacts that explain the high affinity and selectivity of these compounds. These BD2-specific compounds and their binding to BRDT-BD2 are unique compared with recent reports and enable further evaluation of their nonhormonal contraceptive potential in vitro and in vivo. [ABSTRACT FROM AUTHOR]

DNA-encoded chemical libraries are collections of compounds individually coupled to unique DNA tags serving as amplifiable identification barcodes. By bridging split-and-pool combinatorial synthesis with the ligation of unique encoding DNA oligomers, million- to billion-member libraries can be synthesized for use in hundreds of healthcare target screens. Although structural diversity and desirable molecular property ranges generally guide DNAencoded chemical library design, recent reports have highlighted the utility of focused DNA-encoded chemical libraries that are structurally biased for a class of protein targets. Herein, a protease-focused DNA-encoded chemical library was designed that utilizes chemotypes known to engage conserved catalytic protease residues. The three-cycle library features functional moieties such as guanidine, which interacts strongly with aspartate of the protease catalytic triad, as well as mild electrophiles such as sulfonamide, urea, and carbamate. We developed a DNAcompatible method for guanidinylation of amines and reduction of nitriles. Employing these optimized reactions, we constructed a 9.8-million-membered DNA-encoded chemical library. Affinity selection of the library with thrombin, a common protease, revealed a number of enriched features which ultimately led to the discovery of a 1 nM inhibitor of thrombin. Thus, structurally focused DNA-encoded chemical libraries have tremendous potential to find clinically useful high-affinity hits for the rapid discovery of drugs for targets (e.g., proteases) with essential functions in infectious diseases (e.g., severe acute respiratory syndrome coronavirus 2) and relevant healthcare conditions (e.g., male contraception). [ABSTRACT FROM AUTHOR]

Free energy perturbation theory, in combination with enhanced sampling of protein–ligand binding modes, is evaluated in the context of fragment-based drug design, and used to design two new small-molecule inhibitors of the Aurora A kinase–TPX2 protein–protein interaction. [ABSTRACT FROM AUTHOR]

[Display omitted] • Aberrant increase in JAK2 kinase activity causes myeloproliferative disorders. • Selective binding to the JAK2 pseudokinase domain JH2 may be deactivating. • Small molecules that selectively bind JH2 over the JH1 kinase domain are reported. • The best binding molecules have an indoloxytriazine core. Small molecules that selectively bind to the pseudokinase JH2 domain over the JH1 kinase domain of JAK2 kinase are sought. Virtual screening led to the purchase of 17 compounds among which 9 were found to bind to V617F JAK2 JH2 with affinities of 40 – 300 μM in a fluorogenic assay. Ten analogues were then purchased yielding 9 additional active compounds. Aminoanilinyltriazine 22 was particularly notable as it shows no detectable binding to JAK2 JH1, and it has a 65-μM dissociation constant K d with V617F JAK2 JH2. A crystal structure for 22 in complex with wild-type JAK2 JH2 was obtained to elucidate the binding mode. Additional de novo design led to the synthesis of 19 analogues of 22 with the most potent being 33n with K d values of 2–3 μM for WT and V617F JAK2 JH2, and with 16-fold selectivity relative to binding with WT JAK2 JH1. [ABSTRACT FROM AUTHOR]