Comprehensive genomic profiling reveals prognostic signatures and insights into the molecular landscape of colorectal cancer.

Background: Colorectal cancer (CRC) is a prevalent malignancy with diverse molecular characteristics. The NGS-based approach enhances our comprehension of genomic landscape of CRC and may guide future advancements in precision oncology for CRC patients. Method: In this research, we conducted an analysis using Next-Generation Sequencing (NGS) on samples collected from 111 individuals who had been diagnosed with CRC. We identified somatic and germline mutations and structural variants across the tumor genomes through comprehensive genomic profiling. Furthermore, we investigated the landscape of driver mutations and their potential clinical implications. Results: Our findings underscore the intricate heterogeneity of genetic alterations within CRC. Notably, BRAF, ARID2, KMT2C, and GNAQ were associated with CRC prognosis. Patients harboring BRAF, ARID2, or KMT2C mutations exhibited shorter progression-free survival (PFS), whereas those with BRAF, ARID2, or GNAQ mutations experienced worse overall survival (OS). We unveiled 80 co-occurring and three mutually exclusive significant gene pairs, enriched primarily in pathways such as TP53, HIPPO, RTK/RAS, NOTCH, WNT, TGF-Beta, MYC, and PI3K. Notably, co-mutations of BRAF/ALK, BRAF/NOTCH2, BRAF/CREBBP, and BRAF/FAT1 correlated with worse PFS. Furthermore, germline AR mutations were identified in 37 (33.33%) CRC patients, and carriers of these variants displayed diminished PFS and OS. Decreased AR protein expression was observed in cases with AR germline mutations. A four-gene mutation signature was established, incorporating the aforementioned prognostic genes, which emerged as an independent prognostic determinant in CRC via univariate and multivariate Cox regression analyses. Noteworthy BRAF and ARID2 protein expression decreases detected in patients with their respective mutations. Conclusion: The integration of our analyses furnishes crucial insights into CRC's molecular characteristics, drug responsiveness, and the construction of a four-gene mutation signature for predicting CRC prognosis.

In silico designing of therapeutic protein enriched with branched-chain amino acids for the dietary treatment of chronic liver disease.

Leucine, isoleucine, and valine are three essential branched-chain amino acids (BCAA) account for 40-45% of total essential amino acids. BCAA stimulates protein synthesis primarily in skeletal muscles, and it can directly transport to circulatory blood stream bypassing the liver. Hence, a protein enriched with BCAA is an important therapeutic target for the dietary treatment of chronic liver disease. The present study is to design a synthetic protein enriched with BCAA and the challenge is to maximize the BCAA content, keeping the balanced ratio of leucine, isoleucine, valine - 2: 1: 1.2 as specified by WHO/UNU/FAO. Here, we turned the general concept of homology modeling and tried to find a suitable scaffold (α-helix) to host an excess amount of BCAA for increased stability and digestibility. A total of 50 protein models were constructed by using SWISS-MODEL, Modeller 9.17, ProtParam tool, and allergen online tools. Out of 50 different protein models, protein model-50 was found to be best, which had a well-defined 3D structure, good in silico digestibility, balanced ratio of BCAA and showed 65.57% structure identity to the template apo-bovine α-lactalbumin (1F6R). Templates search was performed against PDB using PSI-BLAST, SWISS-MODEL, PROFUNC, I-TASSER, and ConSurf. The secondary structure was predicted by PSSPred, PSIPRED, I-TASSER, PORTER, and SPIDER2. The modeled structure of protein Model-50 was validated by PROCHECK, ERRAT, ProSA, and QMEAN. COACH and ProFUNC tools were performed to determine the functional effects of protein model-50. Overall, the BCAA was enriched from 22 to 56.4% with the balanced ratio of Leu: Ile: Val (2: 1: 1.2). The Ramachandran plot showed 97.7% of the amino acid residues in allowed regions with ERRAT score of 86.05. We have successfully modeled the complete three-dimensional structure of the target protein model-50 using highly reputed computational tools.

An Evolution-Based Approach to De Novo Protein Design.

EvoDesign is a computational algorithm that allows the rapid creation of new protein sequences that are compatible with specific protein structures. As such, it can be used to optimize protein stability, to resculpt the protein surface to eliminate undesired protein-protein interactions, and to optimize protein-protein binding. A major distinguishing feature of EvoDesign in comparison to other protein design programs is the use of evolutionary information in the design process to guide the sequence search toward native-like sequences known to adopt structurally similar folds as the target. The observed frequencies of amino acids in specific positions in the structure in the form of structural profiles collected from proteins with similar folds and complexes with similar interfaces can implicitly capture many subtle effects that are essential for correct folding and protein-binding interactions. As a result of the inclusion of evolutionary information, the sequences designed by EvoDesign have native-like folding and binding properties not seen by other physics-based design methods. In this chapter, we describe how EvoDesign can be used to redesign proteins with a focus on the computational and experimental procedures that can be used to validate the designs.

Proteomic analysis of mature and immature ejaculated spermatozoa from fertile men / 亚洲男科学杂志(英文版)

Dysfunctional spermatozoa maturation is the main reason for the decrease in sperm motility and morphology in infertile men. Ejaculated spermatozoa from healthy fertile men were separated into four fractions using three-layer density gradient. Proteins were extracted and bands were digested on a LTQ-Orbitrap Elite hybrid mass spectrometer system. Functional annotations of proteins were obtained using bioinformatics tools and pathway databases. Western blotting was performed to verify the expression levels of the proteins of interest. 1469 proteins were identified in four fractions of spermatozoa. The number of detected proteins decreased according to the maturation level of spermatozoa. During spermatozoa maturation, proteins involved in gamete generation, cell motility, energy metabolism and oxidative phosphorylation processes showed increasing expression levels and those involved in protein biosynthesis, protein transport, protein ubiquitination, and response to oxidative stress processes showed decreasing expression levels. We validated four proteins (HSP 70 1A, clusterin, tektin 2 and tektin 3) by Western blotting. The study shows protein markers that may provide insight into the ejaculated spermatozoa proteins in different stages of sperm maturation that may be altered or modified in infertile men.

Are accurate computations of the 13C' shielding feasible at the DFT level of theory?

The goal of this study is twofold. First, to investigate the relative influence of the main structural factors affecting the computation of the (13)C' shielding, namely, the conformation of the residue itself and the next nearest-neighbor effects. Second, to determine whether calculation of the (13)C' shielding at the density functional level of theory (DFT), with an accuracy similar to that of the (13)C(α) shielding, is feasible with the existing computational resources. The DFT calculations, carried out for a large number of possible conformations of the tripeptide Ac-GXY-NMe, with different combinations of X and Y residues, enable us to conclude that the accurate computation of the (13)C' shielding for a given residue X depends on the: (i) (ϕ,ψ) backbone torsional angles of X; (ii) side-chain conformation of X; (iii) (ϕ,ψ) torsional angles of Y; and (iv) identity of residue Y. Consequently, DFT-based quantum mechanical calculations of the (13)C' shielding, with all these factors taken into account, are two orders of magnitude more CPU demanding than the computation, with similar accuracy, of the (13)C(α) shielding. Despite not considering the effect of the possible hydrogen bond interaction of the carbonyl oxygen, this work contributes to our general understanding of the main structural factors affecting the accurate computation of the (13)C' shielding in proteins and may spur significant progress in effort to develop new validation methods for protein structures.